´ DE LA MEDITERRAN ´ ´ (AIX-MARSEILLE II) UNIVERSITE EE ´ des Sciences Economiques et de Gestion Faculte Ecole Doctorale de Sciences Economiques et de Gestion d’Aix-Marseille n°372

Ann´ ee 2010

Num´ero attribu´e par la biblioth`eque

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Th` ese pour le Doctorat ` es Sciences Economiques Pr´esent´ee et soutenue publiquement par

Paul MAAREK le 1er F´evrier 2010 ——————————

D´ eveloppement, mondialisation et part des salaires dans la valeur ajout´ ee —————————— `se Directeur de The M. Bruno Decreuse, Professeur a` l’Universit´e de la M´editerran´ee, GREQAM Jury Rapporteurs M. Pierre Cahuc

Professeur a` l’Ecole Polytechnique, CREST

M. Franck Portier

Professeur a` l’Universit´e Toulouse 1, GREMAQ

Examinateurs M. Gilbert Cette

Professeur a` l’Universit´e de la M´editerran´ee, BdF

Mme. Cecilia Garc´ıa-Pe˜ nalosa

Directrice de Recherche, CNRS

M. Farid Toubal

Professeur a` l’Universit´e d’Angers, PSE

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L’Universit´e de la M´editerran´ee n’entend ni approuver, ni d´esapprouver les opinions particuli`eres du candidat: ces opinions doivent ˆetre consid´er´ees comme propres `a leur auteur.

R´ esum´ e Cette th`ese a pour th`eme central l’impact de la mondialisation et du d´eveloppement ´economique sur la part des salaires dans la valeur ajout´ee aussi bien dans les pays en d´eveloppement que dans les pays d´evelopp´es. La premi`ere contribution est consacr´ee `a l’impact du d´eveloppement ´economique sur la part des salaires dans la valeur ajout´ee. Il souligne le rˆole crucial que peut avoir la forte dualit´e du march´e du travail dans les pays en d´eveloppement o` u un secteur formel compos´e de firmes relativement productives, cohabite avec un secteur informel compos´e de firmes moins productives. Dans un tel contexte, les imperfections et les frictions du march´e du travail ont des implications importantes sur la part des salaires dans la mesure o` u le travailleur type n’est pas r´emun´er´e ` a sa productivit´e marginale et o` u ses opportunit´es externes d´ependent du secteur informel peu productif. La deuxi`eme contribution s’int´eresse `a l’impact des investissements directs `a l’´etranger (IDE) sur la part des salaires dans les pays en d´eveloppement. L’entr´ee d’IDE dans les pays en d´eveloppement correspond ` a la rencontre sur un mˆeme march´e du travail de deux technologies productives tr`es diff´erentes. Ainsi l’entr´ee de firmes ´etrang`eres accroit l’h´et´erog´en´eit´e productive des firmes dans ces pays. Lorsque le march´e du travail est frictionnel, cette diff´erence de productivit´e a de fortes implications sur la part des salaires dans la mesure o` u les opportunit´es externes du travailleur embauch´e par une firme ´etrang`ere se trouvent en grande partie localis´ees dans des firmes locales relativement moins productives. La troisi`eme contribution examine l’impact des crises de change sur la part des salaires. Les crises de change ont un coˆ ut tr`es important en termes de production ; elles r´eduisent ´egalement la part des salaires. On se demande dans quelle mesure cette r´eduction de la part des salaires agr´eg´ee refl`ete une diminution du pouvoir de n´egociation ou des ph´enom`enes de r´eallocation factorielle entre secteurs ` a intensit´e capitalistique h´et´erog`ene. La quatri`eme contribution envisage l’effet des rigidit´es salariales sur la part des salaires dans un environnement global de d´etermination du coˆ ut des facteurs. Dans un tel contexte l’´elasticit´e de la demande de travail est plus ´elev´ee qu’en ´economie ferm´ee et les rigidit´es salariales se traduisent pour les pays qui les mettent en place par des r´eallocations factorielles vers les secteurs intensifs en capital. Ces r´eallocations peuvent induire une chute de la part des salaires, tout en la faisant augmenter dans les pays n’ayant pas introduit les rigidit´es. Mots cl´ es : frictions d’appariement, march´e du travail dual, secteur informel, investissement directs ` a l’´etrangers, h´et´erogn´eit´e des firmes, crise de change, commerce international, rigidit´es salariales, r´eallocation factorielle.

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Remerciements Que toute les personnes m’ayant aid´e ou soutenu dans ce travail, de quelque mani`ere que ce fˆ ut, trouvent dans ces lignes le signe de ma reconnaissance. Bien sˆ ur, cette th`ese doit ´enormement `a l’implication de mon directeur de th`ese. Je tiens donc `a remercier Bruno Decreuse pour avoir accept´e d’encadrer cette th`ese et m’avoir guid´e vers ce sujet, qui s’est r´ev´el´e ˆetre une th´ematique passionnante `a ´etudier, d`es le m´emoire de Master 2. Je lui suis tr`es reconnaissant pour sa grande disponibilit´e et pour avoir consacr´e un temps important ` a m’apprendre le m´etier de chercheur dans tous ses aspects allant de la rigueur scientifique jusqu’aux standards de r´edaction. Nos rencontres ont toujours ´et´e tr`es enrichissantes et ont eu un rˆ ole d’acc´el´erateur dans cette th`ese. Nos interactions ne se sont pas limit´ees au simple champ de la th`ese mais aussi `a des ´echanges sur la litt´erature ´economique en g´en´eral, la politique, les d´ebats de soci´et´e et mˆeme....la musique. Cette collaboration a ´et´e f´econde sur le plan scientifique puisque deux chapitres de cette th`ese ont ´et´e ´ecrit conjointement. Fin 2006, apr`es l’obtention de mon master 2 recherche `a l’universit´e de la m´editerran´ee, le formalisme de la discipline m’a fait traverser une p´eriode de doute sur mon avenir et sur mon int´erˆet, pourtant ancien, pour les sciences ´economiques. Trois ann´ees plus tard je regarde mon avenir avec confiance et j’appr´ecie r´eellement le travail de recherche en ´economie. L’encadrement de Bruno est pour beaucoup, j’en suis sur, dans ce regain d’int´erˆet. Je veux ´egalement t´emoigner de toute ma reconaissance `a C´ecilia Garcia-Penalosa. Si C´ecilia n’a pas de statut officiel dans l’encadrement de ma th`ese, elle a n´eanmoins consacr´e un temps tr`es important ` a mon encadrement comme l’aurait fait un co-directeur de th`ese. Sa grande connaissance de la litt´erature sur des champs tr`es vari´es de la macro´economie et sa grande disponibilit´e `a mon ´egard ont ´et´e tr´es pr´ecieux dans le d´eroulement de ma th`ese. Le temps non n´egligeable consacr´e `a la relecture des travaux en anglais m’a beaucoup apport´e dans l’apprentissage des standards de r´edaction et a consid´erablement am´elior´e la forme de la th`ese. J’esp`ere qu’` a la suite de cette th`ese, j’aurai l’occasion de continuer `a collaborer avec ces deux chercheurs qui resteront ceux qui m’ont initi´e au monde de la recherche acad´emique. Je tiens ensuite ` a remercier les membres du jury de m’avoir fait l’honneur de bien vouloir juger mes travaux. Je remercie ainsi Pierre Cahuc et Franck Portier d’avoir accept´e d’ˆetre rapporteur de cette th`ese malgr´e leur tr`es nombreuses responsabilit´es. Leurs rapports de pr´e-soutenance ont grandement contribu´e ` a am´eliorer mes travaux. La longue discussion t´el´ephonique que j’ai eu avec Franck Portier ou l’entretien avec Pierre Cahuc lors du Congr´es annuel de l’EALE `a Tallinn ont ´et´e tr´es appr´eci´es et enrichissants.

8 Je remercie ´egalement Farid Toubal pour sa pr´esence dans ce jury. J’ai appr´eci´e la discussion que nous avons eu ` a la conf´erence doctorale RIEFF de 2009 qui se d´eroulait `a Aix-en-Provence. Discussion au cours de laquelle ses conseils scientifiques ont trouv´e une oreille attentive de ma part. Cette discussion fut reprise un mois plus tard `a la Maison des Sciences Economiques ` a Paris. Il a mis ` a ma disposition de nombreuses donn´ees qui m’ont permis de progresser dans l’avancement de mes travaux. Enfin je remercie Gilbert Cette dont l’int´erˆet pour la th´ematique de la part des salaires est ancien. Nous nous sommes rencontr´es lors de cours qu’il donnait en Master 2. Ses remarque sur le dernier chapitre ont ´enormement aliment´e ma r´eflexion sur le sujet de la part des salaires dans les pays de l’OCDE. Je le remercie ´egalement pour m’avoir permis d’acc´eder `a des donn´ees sectorielles tr`es r´ecentes pour les pays de l’OCDE. Je souhaite ´egalement remercier Elsa Orgiazzi. Nous partageons un chapitre de th`ese. A l’occasion de cette fructueuse collaoration, nous avons partag´e les nombreux moments de doute mais ´egalement les moments de joie qui caract´erisent l’´elaboration d’une th`ese. J’esp`ere que nous pourrons ` a nouveau collaborer dans le cadre de futurs travaux au-del`a de l’amiti´e qui est n´ee de notre travail en commun. Au-del` a, je souhaite remercier par la pr´esente tous les membres du GREQAM avec qui de multiples discussions informelles m’ont permis d’avancer dans le processus de cette th`ese. Tout dabord, je remercie Alain Venditti et Carine Nourry dont la pr´esence r´eguli`ere aux s´eminaires internes de doctorants, la gentillesse et les conseils avis´es m’ont beaucoup soutenu. Je tiens ´egalement ` a les remercier pour m’avoir permis de participer `a deux conf´erences en Macro-Economie dynamique d’une tr´es grande qualit´e scientifique et qui m’ont fait cotoyer des chercheurs de renom´ee internationale. Je remercie ´egalement Pierre-Philippe Combes de sa pr´esence r´eguli`ere aux s´eminaires doctorant et pour les nombreux entretiens qu’il nous a accord´e avec Elsa Orgiazzi dans la r´ealisation de notre article en commun. Je remercie Pierre Granier pour sa participation au groupe de travail en ´economie du travail organis´e alors que j’´etais en premi`ere ann´ee de th`ese et qui m’a ´enorm´ement stimul´e. Je remercie Antoine Soubeyran et Tanguy Van Ypersele dont l’entrain et la bonne humeur lors des repas au chateau Lafarge, lors de discussions tr`es anim´ees, ont souvent apport´e une bouff´ee d’oxyg`ene au quotidien parfois morose du doctorant. Enfin je remercie Sebastien Bervoets, Frederic Dero¨ıan, Eric Girardin, Nicolas Gravel, Alain Tranoy, Karine Gente, Xavier Joutard, Patrick Pintus, Anne Peguin-Feissolle et Jean Benoit Zimmermann de leur soutien et de leurs encouragements. Je tiens ` a remercier Fran¸cois Langot et Arnaud Cheron de m’avoir accueilli au sein de l’´equipe

9 du GAINS en qualit´e d’ATER. Ce travail doit ´egalement beaucoup aux retours que j’ai pu avoir lors de mes pr´esentations `a l’ext´erieur du GREQAM, en colloques ou en s´eminaires. Je tiens ainsi `a remercier les participants `a l’´ecole d’´et´e en ´economie du travail (2007, Aix en provence), `a la conf´erence ”Open Macroeconomics and Development” (2007, Aix en procence), `a la conf´erence ”Labor market outcomes : A transatlantic perspective” (2008, paris), `a la conf´erence doctorale du ”Leverhulme center for globalization” (2008, Nottingham), au congr´es de l’Association Fran¸caise de science ´economique (2008, paris), ` a la conf´erence ”Theory and Methods in Macroeconomics” (2008, Paris), `a la conf´erence doctorale ”Research in International Economics and Finance” (2009, Aix en provence), ` a la conf´erence ”Agents interactions, Market interdependencies and Aggregate instabilities” (2009, Paris), au Journ´ee Louis-Andr´e G´erard-Varet (2009, Marseille), au congr`es de l’ ”European Econometric Society” (2009, Barcelone) et au congr`es de l’ ”European Association of Labor Economics” (Tallinn, 2009), ainsi qu’aux s´eminaires internes du DEFI (2007, 2008 Aix en provence) et du GAINS (2009, Le Mans). Je remercie d’ailleurs l’´ecole doctorale de l’Universit´e de la M´editerran´ee et le GREQAM de m’avoir permis, grˆ ace ` a un soutien financier, de participer `a ces manifestations. J’en profite pour t´emoigner ma reconnaissance aux ´equipes administratives de ces deux institutions (Bernadette, Brigitte, Corinne, Isabelle et Lydie) pour le soutien logistique qu’elles m’ont apport´e. Le lien directeur de th`ese - doctorant est souvent assimil´e, parfois `a juste titre, `a un lien de filiation. En poussant l’all´egorie jusqu’au bout je souhaite ici remercier mes fr`eres d’arme doctorants, ou neo docteurs. Je tiens d’abord ` a exprimer ` a Renaud Bourles toute mon amiti´e et ma consid´eration. Je tiens `a le remercier pour son rˆ ole de grand fr`ere, r´epondant `a n’importe quelle sollicitation et donnant des conseils avis´es. Nos avis, souvent divergents sur le monde et la soci´et´e, ont ´et´e la source d’une grande animation lors des repas entre doctorants et je dois dire que mes opinions ont quelque peu chang´e ` a son contact (et r´eciproquement, je l’esp`ere). J’esp`ere que nous pourrons poursuivre le projet de collaboration scientifique que nous avons en commun. Je remercie ´egalement Jimmy Lopez, Filippo Scoccianti, Gwenola Trotin, Mandy Michel, Paul Antoine Berretti, Leila Ben Aoun, Morgane Laouenan, Gabriele Esposito, Ivy Xiaoyan Lu, Silvia Tanga, Mathieu Goudard, Oph´elie Cerdan, Remy Oddou, Cl´ement Bosquet et Zakaria Moussa pour les bons moments partag´es, les soir´ee inoubliables pass´ees ensemble, l’aide ponctuelle sur des questionnements ´economiques, les d´ebats politiques endiabl´es et, pour avoir cr´ee une fraternit´e de doctorants GREQAM qui je l’esp`ere perdurera. Je remercie particuli`erement Anne Bucher, B´en´edicte Rouland et Pierre-Jean Messe pour

leur accueil au Mans et les bons moments pass´es ensemble. Je remercie ensuite pˆele-mˆele Adriana, Agn`es, Andreea, Benoit, Elsa, Kalila, Sonia, Carmen, Waqar, Shamaila, Camila, Louis, Philippe et Katia pour leur soutien. Enfin ces remerciements ne sauraient ˆetre complets sans un mot pour ma famille. Je remercie bien sur ma m`ere et mon p`ere dont le soutien infaillible tout au long de cette aventure m’ont permis de surmonter les moments de doute. Je remercie mon grand-p`ere paternel pour m’avoir toujours encourag´e ` a poursuivre des ´etudes, la chose la plus importante `a ses yeux. Il rˆevait d’avoir un petit enfant m´edecin, il commencera par un petit enfant docteur. Son soutien financier tout au long de mes ´etudes sup´erieures m’ont permis d’acqu´erir mon ind´ependance sans pour autant devoir travailler et ainsi cet accomplissement lui est sans doute en partie du. Je remercie ´egalement ma grand-m`ere maternelle ainsi que mes grand oncles eux-mˆemes chercheurs qui m’ont transmis tr`es jeune la fibre de la recherche aux travers de r´ecits ´epiques d’aventures scientifiques. Je remercie ´egalement mon petit fr`ere et mes plus petits demi fr`eres et soeurs ainsi que ma bellem`ere Catherine. Enfin je remercie Maria pour toute la douceur qu’elle a amen´ee dans ma vie, lors de cette fin de th`ese qui fut charg´ee.

Table des mati` eres 1 Chapitre introductif

15

1.1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

15

1.2

Pourquoi s’int´eresser ` a la part des salaires . . . . . . . . . . . . . . . . . . . . . .

18

1.2.1

La technologie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

18

1.2.2

Les in´egalit´es . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

19

1.2.3

Taxation/Redistribution . . . . . . . . . . . . . . . . . . . . . . . . . . . .

21

1.2.4

Autres raisons de s’int´eresser `a la part des salaires . . . . . . . . . . . . .

22

La part de salaires n’est pas constante dans le temps et dans l’espace . . . . . . .

24

1.3.1

Mesurer la part des salaires dans la valeur ajout´ee . . . . . . . . . . . . .

24

1.3.2

Evolutions dans les pays de l’OCDE et dans les pays en d´eveloppement .

28

1.3.3

Part des salaires et d´eveloppement : une courbe de Kuznets . . . . . . . .

31

1.3.4

Part des salaires et mondialisation : une corr´elation n´egative . . . . . . .

32

Questionnements de la th`ese . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

33

1.4.1

La mondialisation : d´ebats et controverses . . . . . . . . . . . . . . . . . .

34

1.4.2

Nouveaux angles d’approche

41

1.3

1.4

. . . . . . . . . . . . . . . . . . . . . . . . .

2 Labor share, Informal sector and Development

49

2.1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

50

2.2

Stylized facts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

54

2.2.1

Labor share and development . . . . . . . . . . . . . . . . . . . . . . . . .

54

2.2.2

Entry costs on the good market and development . . . . . . . . . . . . . .

58

2.2.3

Informal sector and development . . . . . . . . . . . . . . . . . . . . . . .

60

The model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

63

2.3.1

Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

63

2.3.2

Equilibrium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

66

2.3.3

The labor share . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

67

2.3

11

`res Table des matie 2.3.4 2.4

2.5

Labor share and development . . . . . . . . . . . . . . . . . . . . . . . . .

68

Empirical investigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

71

2.4.1

Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

71

2.4.2

Empirical evidence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

74

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

77

3 FDI and the labor share in developing countries

79

3.1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

80

3.2

The model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

83

3.2.1

Basic environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

83

3.2.2

Labor market equilibrium . . . . . . . . . . . . . . . . . . . . . . . . . . .

84

3.2.3

Labor share . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

85

3.2.4

Impact of foreign firms on the labor share . . . . . . . . . . . . . . . . . .

86

3.2.5

Firm heterogeneity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

89

3.2.6

Accounting for technological transfers . . . . . . . . . . . . . . . . . . . .

90

3.2.7

Accounting for capital choice . . . . . . . . . . . . . . . . . . . . . . . . .

91

3.2.8

From the theory to empirical analysis . . . . . . . . . . . . . . . . . . . .

92

Empirical analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

93

3.3.1

Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

93

3.3.2

Core regressions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

96

3.3.3

Understanding the results . . . . . . . . . . . . . . . . . . . . . . . . . . .

99

3.3

3.4

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106

4 Who bears the cost of currency crises?

109

4.1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110

4.2

The model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114

4.3

4.2.1

The macroeconomic background of the crisis . . . . . . . . . . . . . . . . 114

4.2.2

The basic model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116

4.2.3

Currency crises and the labour share . . . . . . . . . . . . . . . . . . . . . 121

Empirical analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 4.3.1

Empirical Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125

4.3.2

Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129

4.3.3

A first glance at the data . . . . . . . . . . . . . . . . . . . . . . . . . . . 132

4.3.4

Econometric Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135

4.4

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150

4.5

Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152

12

`res Table des matie 4.5.1

Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152

4.5.2

Sectorial regression in level . . . . . . . . . . . . . . . . . . . . . . . . . . 152

4.5.3

Regressions in level within each sector . . . . . . . . . . . . . . . . . . . . 156

5 Can the HOS model explain changes in labor shares

159

5.1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160

5.2

Stylized facts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163

5.3

HOS, labor shares and wage rigidities . . . . . . . . . . . . . . . . . . . . . . . . 168

5.4

5.3.1

A reminder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169

5.3.2

HOS model with relative wage rigidity . . . . . . . . . . . . . . . . . . . . 170

5.3.3

Labor share and globalization . . . . . . . . . . . . . . . . . . . . . . . . . 173

5.3.4

Labor share and relative wage rigidity . . . . . . . . . . . . . . . . . . . . 174

5.3.5

Sector-specific vs aggregate labor share . . . . . . . . . . . . . . . . . . . 175

Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176 5.4.1

Explaining LS changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176

5.4.2

Capital-skill complementarity . . . . . . . . . . . . . . . . . . . . . . . . . 179

5.5

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183

5.6

Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184

Conclusion g´ en´ erale

187

Bibliographie

197

13

Chapitre 1 Chapitre introductif 1.1

Introduction

La part des salaires constituait un ´el´ement central du d´ebat social au cours du XIX e`me si`ecle alors que la soci´et´e ´etait analys´ee sous l’angle de la lutte des classes. Les auteurs qui forg`erent l’analyse ´economique ` a l’´epoque, et dont la pens´ee actuelle reste emprunte, repr´esentaient l’organisation productive de la soci´et´e comme une organisation en classes distinctes ayant chacune des int´erˆets divergents ` a d´efendre. Il s’ensuit une lutte permanente afin de retirer la plus grande part possible du gˆ ateau issue de la coop´eration productive entre les diff´erentes classes. Alors que les classes chez Smith (1776) se r´ef`erent principalement `a la distinction entre individus productifs (artisans, bourgeois, entrepreneurs) et non productifs (clerg´e, noblesse), la distinction prend une toute autre forme chez Marx (1867), que l’on consid`ere souvent comme le dernier classique. Pour lui la soci´et´e se d´ecompose entre une classe dominante poss´edant le capital et les travailleurs n’ayant que leur force de travail ` a monnayer. La baisse tendancielle du taux de profit, devant faire disparaitre ` a terme le capitalisme, pousse les poss´edants `a accroitre l’”exploitation” des travailleurs afin de pr´eserver les marges, cens´ees faire perdurer le syst`eme. Dans ce contexte de lutte des classes, la part des salaires dans la valeur ajout´ee constitue un indicateur du degr´e d’exploitation de la force de travail. Au XX e`me si`ecle, l’analyse de la soci´et´e change radicalement. Alors que les pr´emisses de la r´evolution industrielle donnent naissance `a une soci´et´e tr`es polaris´ee, caract´eris´ee par une classe ouvri`ere tr`es pauvre (ce que Krugman (2006) appelle l’ˆage dor´e), le XX e`me voit l’´emergence d’une classe moyenne dans les ann´ees folles et une forte r´eduction des in´egalit´es notamment ` a partir des politiques du New Deal aux Etats-Unis ou de l’av`enement du front populaire en France. Si les in´egalit´es, faibles au lendemain de la seconde guerre mondiale, se mettent `a augmenter, elle

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Chapitre introductif n’atteindront jamais les niveaux du d´ebut du si`ecle et resteront relativement faibles durant les 30 glorieuses. Durant cette p´eriode, les travailleurs deviennent ´egalement d´etenteurs de capital et commencent ` a en tirer des revenus. Le sentiment qui domine `a cette ´epoque est radicalement oppos´e de celui qui pr´evalait au XIX e`me . La prosp´erit´e entraˆıne une relation de confiance mutuelle entre les employeurs et les employ´es et chacun a le sentiment qu’il retire sa juste part de sa participation ` a la soci´et´e productive. Krugman fait r´ef´erence `a cette p´eriode comme un v´eritable ˆ age d’or, caract´erisant l’Am´erique de son enfance qu’il consid`ere comme une utopie perdue. A cet instant, la part des salaires n’occupe que peut de place dans le d´ebat publique. Elle est d’ailleurs consid´er´ee comme constante par beaucoup d’´economistes de l’´epoque (Kaldor, 1955). Les ann´ees 1980 voient une rupture majeure se produire (ce que Krugman appel le retour de l’age dor´e). Apr`es des ann´ees de baisse, les in´egalit´es vont de nouveau augmenter. Cela se produit d’abord entre les travailleurs, le salaire relatif des travailleurs qualifi´es augmentant consid´erablement dans les pays anglo-saxons et en particulier aux Etats-Unis. Le d´ebat prend une toute autre tournure au cours des ann´ees 2000, p´eriode pendant laquelle il apparaˆıt qu’aux EtatsUnis la classe moyenne n’a que tr`es peu profit´e des gains de productivit´e depuis 2000 (Mishel et al, 2009). En France, le sentiment d’une majorit´e de concitoyens d’avoir perdu du pouvoir d’achat trouve une r´esonance particuli`ere au regard de l’exp´erience am´ericaine. Il apparaˆıt en r´ealit´e que la classe moyenne se scinde et n’est plus aussi homog`ene qu’avant (Chauvel, 2006). Le sentiment qui pr´evalait pendant les 30 glorieuses n’est plus partag´e et l’impression qui domine d´esormais est de ne plus retirer sa juste part de la collaboration productive. Dans l’imaginaire collectif, la part des salaires est ´etroitement li´ee `a la probl´ematique de l’in´egalit´e de revenus. Il n’y a d`es lors rien d’´etonnant que la part des salaires revienne sur le devant de la sc`ene et fasse l’objet de d´ebats passionn´es au sein de la classe syndicale et politique jusque dans les rangs des plus fervents d´efenseurs du march´e. La Commission Europ´eenne consacre ainsi un chapitre du rapport 2007 sur l’emploi en Europe `a la part des salaires, de mˆeme que le Fonds Mon´etaire International dans le ”World Economic Outlook” de 2007. La mˆeme ann´ee, un compte rendu de l’autobiographie de Alan Greenspan paraˆıt au Financial Times : ”We know in an accounting sense what is causing it” – the share of worker compensation in national income in the US and some other developed countries is unusually low by historical standards – “but we don’t know in an economic sense what the processes are”.(...) “real compensation tends to parallel real productivity, and we have seen that for generations, but not now. It has veered off course for reasons I am not clear about.”(...) Mr Greenspan says “I did and still do” expect some normalisation of profit and wage shares. But asked whether the high profit

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1.1. Introduction share remains a puzzle to him, he says : “Yes, it does.” In his book, he worries that if wages for the average US worker do not start to rise more quickly political support for free markets may be undermined. Au-del` a de l’int´erˆet suscit´e par la part des salaires dans le d´ebat public, nous pr´esentons dans cette introduction ` a la th`ese les raisons objectives de s’int´eresser `a la part des salaires. Elles sont de deux ordres. Tout d’abord, l’´etude de la part des salaires permet d’´eclairer plusieurs ph´enom`enes importants pour la th´eorie ´economique. Nous d´eveloppons cet aspect dans la section 2 de cette introduction ` a la th`ese. Les mouvements de part des salaires et leurs causes peuvent nous renseigner sur le degr´e de substituabilit´e entre les facteurs de production, degr´e dont d´epend de mani`ere cruciale la th´eorie macro´economique. L’´evolution de la part des salaires a ´egalement des implications en terme d’in´egalit´e totale de revenus dans la mesure o` u les revenus du capital sont davantage concentr´es que les revenus du travail. La base fiscale des gouvernements dans un monde o` u le facteur capital est devenu tr`es mobile se trouve fortement affect´ee par des mouvements de parts des salaires. Enfin nous examinons d’autres raisons plus sp´ecifiques de s’int´eresser `a la part des salaires dans la valeur ajout´ee. Ensuite, et contrairement ` a une id´ee re¸cue, la part des salaires est une variable ´economique qui varie fortement dans le temps et l’espace. Ce diagnostic est pr´esent´e dans la section 3. Nous d´ecrivons les diff´erentes m´ethodes de mesure de la part des salaires et rappelons que le choix de la m´ethode n’est pas neutre quant aux niveaux mesur´es de la part des salaires. Nous d´ecrivons ensuite les ´evolutions de la part des salaires dans les pays de l’OCDE ainsi que dans les pays en d´eveloppement. La part des salaires a diminu´e fortement dans les ann´ees 1980 dans les pays d’Europe continentale mais semble constante dans les pays Anglo-Saxons. Nous montrons ´egalement que la part des salaires est en forte diminution dans les pays en d´eveloppement et augmente avec le d´eveloppement ´economique. En section 4, nous d´eveloppons la probl´ematique de la th`ese. Nous ´etudions l’impact de la mondialisation et du processus de d´eveloppement sur la part des salaires dans la valeur ajout´ee. A cette fin, nous rappelons bri`evement que si la mondialisation est associ´ee `a d’importants gains de productivit´e pour de nombreux pays ´emergents, elle entraˆıne ´egalement des coˆ uts en termes de chˆomage, d’in´egalit´es ou encore d’instabilit´e. La diminution de la part des salaires est souvent per¸cue dans la litt´erature comme ´etant un coˆ ut induit par la mondialisation des ´echanges et la libre circulation des capitaux. La pression concurrentielle et la mobilit´e accrue du facteur capital exerceraient une pression ` a la baisse sur les salaires n´egoci´es ainsi que sur la part des salaires. Nous d´eveloppons ensuite les arguments mis en avant dans la th`ese. Nous nous situons pour notre part dans un cadre th´eorique o` u le march´e du travail est caract´eris´e par des imperfections

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Chapitre introductif concurrentielles comme les rigidit´es salariales ou les frictions dans le processus d’appariement entre chˆ omeurs et postes vacants. Dans un tel contexte, nous montrons que l’entr´ee d’Investissements Directs Etrangers dans les pays en d´eveloppement, les crises de change, le processus de d´eveloppement ou encore le commerce international ont des cons´equences importantes pour la part des salaires dans la valeur ajout´ee.

1.2

Pourquoi s’int´ eresser ` a la part des salaires

Dans cette section nous ´etudions les raisons de s’int´eresser au partage de la valeur ajout´ee entre revenus du travail et revenus du capital. La premi`ere raison concerne les propri´et´es de la technologie productive. Des variations de parts des salaires peuvent ˆetre le r´ev´elateur que les technologies diff`erent de la fonction Cobb-Douglas. Etudier les mouvements de part des salaires peut nous renseigner sur la nature de la technologie utilis´ee. La seconde raison touche `a l’´economie des in´egalit´es. Si les revenus du capital sont davantage concentr´es que les revenus du travail, des mouvements de parts des salaires ont une influence sur les in´egalit´es individuelles de revenus. La troisi`eme raison tient aux cons´equences de la distribution factorielle des revenus sur les possibilit´es de taxation. Nous terminons par une s´erie d’autre raisons plus mineures de s’int´eresser ` a la part des salaires.

1.2.1

La technologie

Les ´evolutions de la part des salaires peuvent nous renseigner sur la nature de la technologie de production. Les fonctions de production de type Cobb-Douglas jouent un rˆole consid´erable dans la th´eorie ´economique. L’´elasticit´e de substitution entre le capital et le travail est unitaire, ce qui permet d’exclure des ph´enom`enes ´economiques int´eressants mais n´eanmoins pathologiques comme les fluctuations endog`enes. Cependant, les technologies de production Cobb-Douglas impliquent un partage constant de la valeur ajout´ee entre revenus du capital et revenus du travail lorsque les facteurs de production sont r´emun´er´es `a leur productivit´e marginale. Dans ce cadre th´eorique bien particulier, toute augmentation du prix relatif de l’un des facteurs se traduit par un mouvement proportionnellement inverse de la quantit´e de ce facteur dans la production (et inversement). D`es lors, la part des salaires n’est pas affect´ee par la croissance `a long terme qui induit une accumulation de facteurs sur longue p´eriode, ni pas les chocs de court terme qui induisent des ajustements rapides dans la quantit´e de facteurs. A contrario, des mouvements de parts de salaires signalent des imperfections concurrentielles ou des technologies de production plus complexes que les technologies Cobb-Douglas.

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´resser a ` la part des salaires 1.2. Pourquoi s’inte Prenons par exemple le cas du mod`ele `a deux g´en´erations imbriqu´ees avec un secteur de production. Lorsque la technologie de production est Cobb-Douglas et que l’utilit´e de la consommation est homoth´etique, l’´equilibre stationnaire est unique et globalement stable. Cela n’est plus forc´ement le cas lorsque l’on consid`ere des technologies alternatives. L’existence, l’unicit´e, et la stabilit´e de l’´equilibre stationnaire ne sont plus garantis. De mˆeme, une branche r´ecente de la macro´economie initi´ee par Benhabib and Farmer (1994) s’int´eresse aux fluctuations endog`enes dans le cadre du mod`ele de croissance optimal de Ramsey, puis du mod`ele ` a g´en´erations imbriqu´ees de Diamond (1968). Ils montrent que dans le cas d’une technologie qui diff`ere d’une Cobb-Douglas et de petites externalit´es dans la fonction de production, l’´equilibre stationnaire n’est plus n´ecessairement un point selle de sorte qu’une infinit´e de trajectoires m`ene ` a l’´equilibre stable. Toutes ces trajectoires sont compatibles avec avec les conditions de transversalit´e, ce qui pose la question de la coordination des agents ´economiques. Ce probl`eme de coordination peut donner naissance `a des ´equilibres avec taches solaires, o` u un processus exog`ene permet la coordination des anticipations, mais peut entraˆıner dans le mˆeme temps des fluctuations de l’activit´e ´economique. La dynamique de transition peut ´egalement g´en´erer des cycles permanents autour de l’´etat stationnaire. Dans un travail influent, Jones (2003) r´econcilie les mouvements de parts de salaire avec une technologie Cobb-Douglas ` a long terme. Il propose un mod`ele o` u la technologie de production agr´eg´ee est endog`ene. Elle diff`ere selon que l’on se situe dans une perspective de court ou de long terme. A court terme, l’´elasticit´e de substitution entre le capital et le travail est inf´erieure ` a un. A plus long terme, le renouvellement des id´ees utilis´ees dans les relations productives aboutit ` a une fonction Cobb-Douglas. Dans ce contexte, la part des salaires change `a moyen terme mais demeure constante dans le long terme. Cependant, et en dehors du travail de Jones, les mouvements de parts de salaires et leurs causes nous renseignent sur la nature des technologies de production, et sur les ´eventuels d´esordres macro´economiques qui leur sont associ´es.

1.2.2

Les in´ egalit´ es

Les m´enages tirent une faible proportion de leur revenus des revenus du patrimoine. Cependant, l’in´egalit´e dans la d´etention du capital est telle que des mouvements de part des salaires peuvent avoir un impact ´economiquement significatif sur l’in´egalit´e totale de revenus entre les m´enages. Paradoxalement, l’´economie des in´egalit´es s’est longtemps int´eress´ee `a la distribution factorielle des revenus. Les ´economistes n’ont commenc´e `a s’int´eresser `a la distribution personnelle des revenus qu’` a partir des ann´ees 1970 avec l’apparition de bases de donn´ees individuelles de revenus. Ce profond changement de perspective s’est op´er´e `a partir des travaux fondateurs de

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Chapitre introductif Atkinson (1970, 1975), Champernowne (1973), Sen (1973), Stiglitz (1969), ou Tinbergen (1975). Les revenus des individus peuvent provenir de deux sources : les revenus du travail et les revenus du capital. Si beaucoup d’auteurs s’int´eressent `a la distribution des salaires (voir Acemoglu,1998, 2002a,b, 2003a,b ou Katz et Murphy, 1992) ou `a l’in´egalit´e de revenus totale (Atkinson, 1997), peu s’int´eressent ` a la part des salaires alors qu’il existe un lien ´evident avec l’in´egalit´e totale de revenus. En effet, si la distribution des facteurs entre les individus diff`ere selon le facteur consid´er´e, alors un changement dans la part des salaires peut avoir `a des cons´equences sur la distribution personnelle des revenus. La question est de savoir si l’un des deux facteurs est beaucoup plus in´egalement distribu´e que l’autre. Il apparait au regard des diff´erentes sources de donn´ees disponibles que ce soit le cas : Garcia Penalosa et Orgiazzi (2009) d´ecomposent un indice d’in´egalit´e portant sur l’in´egalit´e de revenu, pour 8 pays de l’OCED. L’indice d’in´egalit´e de revenus individuel utilis´e est le carr´e du coefficient de variation (CCV) dans la mesure o` u cet indice est facilement d´ecomposable. Il apparaˆıt que les in´egalit´es de revenus du capital sont bien plus importantes que les in´egalit´es portant sur les autres revenus. A titre d’exemple, en 2000, pour l’Italie et la France, le CCV pour les revenus du capital s’´el`eve respectivement ` a 9.92 et 11.42 contre seulement 0.85 et 0.68 pour les revenus du travail. Mˆeme si les revenus du patrimoine p`esent relativement peu dans le total des revenus des m´enages, la tr`es forte in´egalit´e observ´ee dans les revenus du capital a un impact non n´egligeable sur l’indice d’in´egalit´e total. Ainsi, pour la France cela repr´esente 13% de l’in´egalit´e totale et monte jusqu’` a 20% pour l’Italie. De mani`ere ´etonnante, ce pourcentage est substantiellement plus ´elev´e pour les pays scandinaves puisque qu’il passe `a presque 50% pour la Su`ede et la Finlande (cela peut ˆetre du au fait que la structure salariale est faiblement in´egalitaire dans ces pays). Dans ce contexte un changement de part des salaires peut avoir des cons´equences non n´egligeables sur les indices d’in´egalit´e de revenus. Ainsi, une diminution de la part des salaires doit avoir pour cons´equence une augmentation des in´egalit´es de revenus entre les individus et les m´enages. On peut noter que cette ´etude fait ´egalement ressortir de forte in´egalit´es de d´etention du patrimoine entre les diff´erentes classes d’ˆage et, plus ou moins fortes au seins des diff´erentes classes d’ˆage. Ainsi, des mouvements de part des salaires n’ont pas le mˆeme impact en terme d’in´egalit´e selon la classe d’ˆ age et peuvent ´egalement induire des redistributions interg´en´erationnelles. Au niveau agr´eg´e, des ´etudes empiriques font ressortir un lien significatif entre part des salaires et in´egalit´es de revenus. Daudey et Garcia Penalosa (2006) montrent sur 32 pays que la part des salaires a un impact fort sur le coefficient de Gini en coupe transversale (pour une ann´ee) et en donn´ees “pool´ees” sur plusieurs ann´ees. Ce r´esultat est confirm´e par les travaux de

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´resser a ` la part des salaires 1.2. Pourquoi s’inte Checchi et Garcia Penalosa (2008, 2009) qui montrent que les in´egalit´es personnelles de revenus sont li´ees ` a la part des salaires pour 12 pays de l’OCDE en estimation `a effets fixes sur donn´ees de panel. Notamment, la hausse des in´egalit´es salariales aux Etats-Unis a ´et´e att´enu´ee par une part des salaires relativement stable et ´elev´ee. Si la part des salaires ob´eit ` a des m´ecanismes de d´etermination distincts des autres composantes de l’in´egalit´e, ` a savoir l’in´egalit´e salariale ou l’in´egale possession du capital, alors l’´etude de la part des salaires peut s’av´erer ˆetre un objet en tant que tel.

1.2.3

Taxation/Redistribution

La part des salaires a un impact fort sur la politique fiscale. D’une part, elle affecte le gouvernement dans sa capacit´e ` a taxer la richesse cr´e´ee. D’autre part, une part des salaires faible peut induire de nombreuses compensations fiscales afin de limiter les cons´equences de cette distribution primaire des revenus d´efavorable aux travailleurs. Tout d’abord, nous examinons les cons´equences que peuvent avoir le niveau de la part des salaires sur la capacit´e d’un gouvernement `a taxer la richesse produite. Depuis 1975, le taux de taxe sur le revenu des entreprises ainsi que le taux de taxe sur les plus hautes tranches de revenus (o` u les revenus du capital sont surrepr´esent´es) ont consid´erablement diminu´e. Une explication `a ce ph´enom`ene couramment avanc´ee est que dans un monde ouvert o` u la mobilit´e du capital est tr`es forte relativement ` a celle du travail, taxer les revenus issus du facteur mobile est plus difficile. La concurrence fiscale diminue ainsi la pression fiscale sur les revenus issus de ce facteur. Cela conduit ` a un sous financement de biens publiques et `a une pression fiscale accrue sur le facteur travail. Mˆeme si cette vision est contest´ee, notamment en science politique1 , elle reste tr`es populaire parmi les ´economistes. De nombreux travaux traitent de cette question au cours des derni`eres d´ecennies marqu´ees par un accroissement de la mobilit´e internationale des capitaux. A titre d’exemple Gordon (1992), Razin et Sadka (1991), Rodrik et Van Ypersele (2001) ou Person et Tabellini (1995) pour un survey, expliquent bien les m´ecanismes de concurrence fiscale `a l’œuvre dans un monde ou circulent librement les capitaux. Person et Tabellini (1992) nuancent cependant cette assertion en montrant que dans un processus de vote les groupes qui perdent au processus d’ouverture seront plus enclin `a porter au pouvoir des gouvernements de gauche, plus favorables ` a la taxation des revenus du capital. Dans un tel contexte o` u les revenus du capital sont relativement moins ais´es `a taxer que les revenus du travail, une diminution de la part des salaires `a pour cons´equence directe une diminution de la base fiscale des gouvernements et une diminution des rentr´ees fiscales associ´ees. 1

Voir par exemple Swank (1998) ou Przeworski et Wallerstein (1995).

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Chapitre introductif Cependant, des mouvements de parts des salaires peuvent conduire les gouvernements ` a compenser cette distribution primaire des revenus d´efavorable aux travailleurs par des transferts. Ainsi, Fuchs-Sch¨ undeln et al (2008) utilisent des donn´ees micro´economiques pour l’Allemagne et montrent que l’augmentation des in´egalit´es et la tr`es forte diminution de part des salaires concomitante ` a ´et´e accompagn´e d’une forte augmentation des transferts pour les plus vuln´erables ce qui a consid´erablement r´eduit le niveau des in´egalit´es apr`es transferts.

1.2.4

Autres raisons de s’int´ eresser ` a la part des salaires

Nous pr´esentons bri`evement les raisons additionnelles de s’int´eresser `a la part des salaires. Nous arguons tout d’abord que la part des salaires est elle-mˆeme un outil de concurrence fiscale et peut influencer les choix de localisation des activit´es dans le monde. Nous expliquons ensuite que dans la mesure o` u les m´enages tirent la grande majorit´e de leur revenus des revenus du travail, la part des salaires et plus particuli`erement l’´evolution de la part des salaires mesure les gains des m´enages relativement aux gains de productivit´e. Nous montrons enfin que dans le cas de certains pays en d´eveloppement, la part des salaires peut recevoir une tout autre interpr´etation dans la mesure o` u les d´etenteurs du facteur capital sont pour beaucoup des r´esidents ´etrangers. La part des salaires mesure directement le rapport entre le coˆ ut et la productivit´e du travail. Un bref aper¸cu des bases de donn´ees disponibles (pr´esent´ees en section 3) sugg`ere que les niveaux de parts des salaires sont tr`es diff´erents d’un pays `a l’autre. Si la part des salaires repr´esente 60% du PIB en France ou en Italie, elle est nettement plus faible en Irlande o` u elle ne repr´esente gu`ere plus de 40% du PIB. Dans un monde o` u la production se fragmente, dans un contexte de mobilit´e accrue du facteur capital, une part des salaires faible, toutes choses ´egales par ailleurs, constitue une force d’attraction et la part des salaires peut ˆetre un ´el´ement d´eterminant de la localisation des activit´es. Toutefois, une ´etude d´etaill´ee des causes pour lesquelles la part des salaires varie d’un pays ` a l’autre peut mettre en doute l’id´ee selon laquelle une part des salaires faible constitue une source d’attractivit´e des capitaux ´etrangers. Dans le cas de l’Irlande par exemple une lecture na¨ıve pourrait sugg´erer que le pays tire sont attractivit´e d’une faible r´emun´eration du facteur travail relativement ` a sa productivit´e. Un regard attentif aux donn´ees propose une autre interpr´etation : une cause potentielle de la faiblesse de la part des salaires en Irlande est le ph´enom`ene du ”transfer pricing”. Dans la mesure o` u le taux de taxe sur les b´en´efices est tr`es faible en Irlande, les firmes multinationales manipulent les prix du commerce intra-firme entre les diff´erentes filiales afin de localiser une grande part du profit agr´eg´e en Irlande. Ainsi une grande partie des profits d´eclar´es en Irlande ne pourrait en fait correspondre qu’`a une forme d’´evasion fiscale provoqu´ee par un jeu comptable o` u la firme ne d´eclare qu’une partie faible de la valeur ajout´ee dans le pays o` u elle est

22

´resser a ` la part des salaires 1.2. Pourquoi s’inte constitu´ee (mais tax´ee). Selon cette interpr´etation, la faible part des salaires en Irlande ne veut pas forc´ement dire que le travailleur est r´emun´er´e de mani`ere anormalement basse au regard de sa productivit´e. De mˆeme, une faible part des salaires peut correspondre `a un poids important des activit´es ` a forte intensit´e capitalistique ayant traditionnellement une part des salaires plus faible sans pour autant qu’au niveau de chaque secteur la part des salaires soit anormalement basse. Une autre raison de s’int´eresser ` a la part des salaires est d’identifier qui gagne ou qui perd relativement lors d’un ´ev`enement particulier qui affecte la productivit´e, ou encore si il y a r´eellement des perdants. Prenons l’exemple de la mondialisation. La mondialisation a engendr´e d’importants gains de productivit´e dans les ´economies aussi bien d´evelopp´ees que les ´economies ´emergentes. Un sentiment fr´equemment partag´e est que la mondialisation est ´egalement associ´ee `a une chute de la part des salaires dans la valeur ajout´ee. Une ´etude d´etaill´ee des m´ecanismes qui influent la part des salaires durant cette p´eriode nous indique `a quel facteur b´en´eficie relativement plus la mondialisation et si la chute de la part des salaires correspond `a une d´et´erioration absolue ou relative du bien-ˆetre des travailleurs. Nous montrons par exemple dans le deuxi`eme chapitre de la th`ese que les Investissements Directs `a l’Etranger accroissent le bien-ˆetre des travailleurs mˆeme si ils sont associ´es ` a une diminution de la part des salaires. Il apparaˆıt au regard des donn´ees disponible sur les revenus des m´enages que dans la plupart des cas, une tr`es grande majorit´e de ces revenus correspond `a des revenus du travail (voir GarciaPenalosa et Orgiazzi, 2009). D`es lors des mouvements de parts des salaires nous indique plus g´en´eralement si les m´enages profitent des gains de productivit´e tels que ceux g´en´er´es par la mondialisation. Une baisse de la part des salaires peut signifier que les revenus des m´enages m´edians augmentent moins vite de la productivit´e. Dans le cas des PED la part des salaires revˆet une importance particuli`ere. En effet au cours des derni`eres d´ecennies, ces pays sont devenus de plus en plus en plus ouverts aux capitaux ´etrangers. Ainsi une part non n´egligeable du stock de capital dans ces pays est d´etenue par des r´esidents ´etrangers. Une baisse de la part des salaires peut ˆetre synonyme d’appauvrissement pour le pays consid´er´e. Le stock d’IDE ramen´e au stock de capital est de 15,38% pour les pays en d´eveloppement et, il d´epasse frequemment les 50% du stock de capital pour certain d’entre eux tels que Hong Kong, le Botswana, la Bolivie ou le Congo. Cette moyenne n’est que de 5% pour les pays d´evelopp´es et ne d´epasse que tr´es rarement les 15%.2

2

Les donn´ees disponibles ` a ce sujet proviennent de l’UNCTAD et de Lane et Milesi-Ferretti (2007) pour les stock d’IDE et de Klenow et Rodriguez-Clare pour les stocks de capital.

23

Chapitre introductif

1.3

La part de salaires n’est pas constante dans le temps et dans l’espace

Nous montrons dans cette section que contrairement `a une id´ee r´epandue, la part des salaires n’est pas constante dans le temps et dans l’espace : la part des salaires varie beaucoup dans le temps au sein d’un mˆeme pays et varie consid´erablement d’un pays `a l’autre. Dans une perspective positiviste, l’´etude de la part des salaires et la compr´ehension des m´ecanismes qui la font fluctuer au cours du temps devient un objet d’´etude en tant que tel. Nous nous focalisons dans un premier temps sur la mesure de la part des salaires et rappelons que les conventions retenues pour la mesure de la part des salaires ne sont pas neutres. Nous montrons ensuite que la part des salaires a connu des ´evolutions majeures dans les pays d´evelopp´es quoique plus marqu´ees dans les pays d’Europe continentale, ainsi que dans les pays en d´eveloppement et de mani`ere plus prononc´ee dans les pays les moins avanc´es. Nous montrons ´egalement que le processus de d´eveloppement ´economique sur longue p´eriode n’est pas ´etranger `a ces ´evolutions notamment dans le cas des pays en d´eveloppement.

1.3.1

Mesurer la part des salaires dans la valeur ajout´ ee

Il existe diff´erentes conventions de mesure pour la part de la valeur ajout´ee qui revient au facteur travail. Nous pr´esentons les avantages et inconv´enients de chaque convention et relatons les diff´erentes sources de donn´ees disponibles afin de mesurer la part des salaires dans les pays d´evelopp´es et les pays en d´eveloppement. La part des salaires dans le revenu national mesure la proportion des richesses cr´e´ees qui reviennent au facteur travail. On la d´efinit comme le rapport de la masse salariale totale d’un pays sur sa valeur ajout´ee. Il est important de noter qu’il faut consid´erer tous les revenus du travail : les cotisations salariales par exemple sont inclues dans la masse salariale car elles correspondent en fait ` a un revenu diff´er´e. La r´ealisation des stocks options correspond ´egalement `a des revenus salariaux. Au del` a de cette d´efinition simple de la part des salaires, plusieurs questions majeures doivent ˆetre consid´er´ees afin d’en avoir une mesure convenable. Tout d’abord il convient de clairement d´efinir ce qui doit ˆetre pris en compte dans le d´enominateur. Il existe deux formulations possibles pour le d´enominateur. Une premi`ere approche consiste ` a utiliser le PIB comme proxy pour la valeur ajout´ee. On dit alors que la part des salaires est calcul´ee au prix de march´e. Cette m´ethode est la plus couramment utilis´ee. Une autre approche consiste ` a calculer la part des salaires au coˆ ut des facteurs. Il s’agit de soustraire au

24

1.3. La part de salaires n’est pas constante dans le temps et dans l’espace num´erateur les taxes nettes3 . La part des salaires calcul´ee au coˆ ut des facteurs est plus ´elev´ee de 6 points environ dans les pays de l’OCDE que la part des salaires calcul´ee au prix de march´e. Cependant le coefficient de corr´elation entre les deux mesures pour les membres de l’union Europ´eenne est tr`es ´elev´e (0.986). D`es lors, lorsque l’on ´etudie les variations de la part des salaires, peu importe la mesure consid´er´ee. Nous utiliserons tout au long de cette th`ese la part des salaires calcul´ee au prix de march´e dans la mesure o` u les informations sur les taxes d’op´eration sont tr`es peu disponibles dans le cas des pays en d´eveloppement notamment. Une autre question d’importance est la prise en compte du secteur public. Batini, Jackson et Nickell (2000) montrent que la part des salaires en Angleterre est r´eduite de 5 points lorsque l’on consid`ere uniquement les activit´es de march´e. Cela n’a rien d’´etonnant au regard de la prise en compte de certaine de ces activit´es hors march´e dans le calcul du PIB. A titre d’exemple, un professeur de l’´education nationale participe au PIB `a hauteur de son salaire, ce qui correspond `a une part des salaires de 100%. Dans la mesure o` u le poids du secteur public n’a cess´e d’augmenter au cours des ann´ees 1980 et 1990 dans la plupart des pays de l’OCDE, consid´erer uniquement les activit´es de march´e dans le calcul de la part des salaires devrait induire une tendance baissi`ere ` a la part des salaires mesur´ee de la sorte relativement `a la mesure incluant le secteur public. Blanchard (1997), Blanchard et Giavazzi (2003) ou De Serres et al (2002) prennent le partie dans leurs contributions respectives de mesurer la part des salaires uniquement pour les activit´es de march´e pour les pays Europ´eens. La baisse observ´ee de part des salaires dans les principaux pays d’Europe continentale s’en trouve accentu´ee. Lorsque l’analyse porte sur les pays en d´eveloppement, les donn´ees utilis´ees dans cette th`ese correspondent au secteur manufacturier (qui permettent de r´egler le probl`eme du travailleur ind´ependant pr´esent´e ci-dessous) et n’incluent par cons´equent pas le secteur public. Lorsque l’analyse porte sur les pays de l’OCDE nous prenons le parti d’utiliser les donn´ees pour l’´economie dans son ensemble provenant de diverses bases disponibles (voir ci-dessous) ce qui amoindrit la baisse de la part des salaires observ´ee dans ces pays. La d´efinition simple de la part des salaires expos´ee plus haut masque toutefois une difficult´e majeure dans le cas des PED mais ´egalement dans le cas des pays d´evelopp´es : la prise en compte des revenus des non-salari´es, des travailleurs ind´ependants. La valeur ajout´ee int`egre en effet la richesse cr´e´ee par ce groupe d’individus, alors que leur contribution `a la masse salariale est nulle par d´efinition. N´egliger ce ph´enom`ene a deux cons´equences importantes. D’une part, cela revient `a consid´erer que les revenus des travailleurs ind´ependants correspondent exclusivement `a des revenus issus d’autres facteurs de production que le facteur travail. Les revenus des agriculteurs, des avocats, des m´edecins sont ainsi assimil´es `a des revenus du capital par exemple. Autrement 3

Taxes li´ees ` a la production et aux importations - subventions d’op´eration.

25

Chapitre introductif dit, la part des salaires est artificiellement biais´ee vers le bas. D’autre part, les comparaisons internationales et les analyses temporelles sont fauss´ees, dans la mesure o` u le nombre de travailleurs ind´ependants varie d’un pays `a l’autre et varie ´egalement dans le temps (Nunziata, 2008). Mais comment d´efinir correctement la part des revenus des travailleurs ind´ependants issue du travail ? La solution consiste ` a appliquer un revenu salarial fictif `a ces travailleurs (voir Krueger, 1999). Le point d´elicat est de fixer ce revenu : quelle valeur lui donner ? Dans le cas des pays d´evelopp´es, on suppose le plus souvent que le salaire fictif des travailleurs ind´ependants est ´egal au salaire moyen des salari´es. Cette hypoth`ese revient `a corriger la part des salaires d’un facteur qui ne d´epend que de la proportion de travailleurs ind´ependants dans la population active. Si cette hypoth`ese semble donner des r´esultats probants dans le cas des pays d´evelopp´es, elle semble moins adapt´ee dans le cas des pays en d´eveloppement o` u les travailleurs ind´ependants sont tr`es nombreux et tr`es diff´erents des salari´es. Gollin (2002) pratique cet ajustement pour un faible nombre de pays en d´eveloppement, pour une ann´ee, sur les donn´ees provenant des Nations Unies, et montre que le lien entre d´eveloppement et part des salaires disparaˆıt. La part des salaires continue cependant d’ˆetre tr`es (autant) dispers´ee entre les pays. Bernanke et G¨ urkaynak (2001) g´en´eralisent l’analyse de Gollin (2002) pour un bien plus grand nombre de pays en d´eveloppement avec des r´esultats parfois surprenant. La part des salaires atteint 971% pour le Burkina Faso et 384% pour la Cˆote d’Ivoire. D`es lors, cette correction g´en´eralement usit´ee pour les pays d´evelopp´es et qui impute aux non-salari´es le salaire moyen des salari´es semble tr`es forte et peu adapt´ee dans le cas des PED, o` u la plupart des travailleurs ind´ependants sont des petits exploitants et travailleurs pauvres. De plus, les donn´ees sur le nombre de travailleurs ind´ependants ´etant assez peu disponible, le calcul de s´eries temporelles ajust´ees pour les PED devient impossible. D`es lors, si dans le cas des pays d´evelopp´es l’utilisation de donn´ees provenant de l’OCDE (base STAN), de la base EU-KLEMS ou des Nation Unies4 est compatible avec un ajustement simple des parts des salaires selon le pourcentage de travailleurs ind´ependants, l’´etude de la part des salaires dans les pays en d´eveloppement n´ecessite l’utilisation de donn´ees alternatives comme l’explique Daudey (2003). Une solution, initi´ee par Rodrik (1999) consiste `a utiliser les donn´ees provenant de l’ ”United Nations Industrial Development Organization” (UNIDO). UNIDO a compil´e des donn´ees pour le secteur manufacturier comprenant les salaires, la valeur ajout´ee et l’investissement (entre autres), pour une p´eriode allant de 1963 `a 2003 (avec de nombreuses 4

Les donn´ees sont disponibles pour un grand nombre de pays de l’OCDE, pour un nombre relativement important de secteurs et pour une p´eriode allant de 1970 `a 2005 dans le cas de la base EU-KLEMS. Les donn´ees des Nations Unis sont disponibles pour un grand nombre de pays aussi bien d´evelopp´es que en d´eveloppement.

26

1.3. La part de salaires n’est pas constante dans le temps et dans l’espace valeurs manquantes), pour plus de 120 pays. Pour une ann´ee donn´ee les salaires incluent (a) les salaires directs (b) les r´emun´erations correspondants ` a du temps non travaill´e (c) les bonus et primes (d) les allocations logements et familiales vers´ee par l’employeur et (e) les paiements en nature. Ne sont pas prises en compte les contributions employeurs et employ´es aux syst`emes de s´ecurit´e sociale de mˆeme que les prestations re¸cues sous ces r´egimes ou d’´eventuelles indemnit´es de licenciements. Cette base de donn´ees pr´esente de nombreux avantages dans le cadre des pays en d´eveloppement. Tout d’abord, les donn´ees sont disponibles pour un nombre important de pays en d´eveloppement ce qui n’est pas le cas pour les autres bases de donn´ees disponibles. De plus, le fait que les donn´ees ne concernent que le secteur manufacturier peut ˆetre un avantage dans le cas de pays en d´eveloppement, selon l’objet que l’on ´etudie. La structure de l’´economie change en effet tr`es rapidement au cours du processus de d´eveloppement, le secteur agricole tendant ` a occuper une place moins importante au profit du secteur urbain manufacturier (Kuznets, 1955, Harris et Todarro, 1971). Dans la mesure o` u les parts des salaires entre les deux secteurs peuvent ˆetre tr`es diff´erentes, ce simple effet de structure peut avoir des effets important sur la part des salaires agr´eg´ee sans pour autant nous renseigner sur les forces qui guident le partage de la valeur ajout´ee dans l’´economie entre le facteur travail et le facteur capital. Gollin (2002) montre, en appliquant la structure sectorielle am´ericaine aux pays en d´eveloppement pour un nombre de pays en d´eveloppement relativement restreint, que la diff´erence de part des salaires entre pays riches et en d´eveloppement ne change que tr`es peu. Cependant l’analyse n’est effectu´ee que sur coupe transversales et n’indique donc pas que des changements de structure n’induisent pas de changements de la part des salaires au cours du temps. Se focaliser sur la part des salaires dans le secteur manufacturier nous pr´emunit de ce biais. Enfin, le principal avantage que pr´esente cette base de donn´ees dans le cadre des pays en d´eveloppement tient au fait que la prise en compte des travailleurs ind´ependants est inutile. Cela nous ´evite d’op´erer des ajustements en se servant d’hypoth`eses ad hoc et qui semblent tr`es peu adapt´ees au cas des pays en developpement o` u les travailleurs ind´ependants sont extrˆemement nombreux et semblent avoir des caract´eristiques tr`es diff´erentes des salari´es. Tout d’abord une rapide ´etude des donn´ees sectorielles am´ericaines disponibles semble sugg´erer que la part des ind´ependants dans le secteur manufacturier est tr`es faible et ne repr´esente par exemple que 2.1% des travailleurs en 1994 contre 48.3% pour le secteur agricole. Ensuite les donn´ees UNIDO excluent les entreprises dont le nombre d’employ´es se situe en dessous d’un certain seuil (5 employ´es, voir Ortega et Rodriguez, 2006) ce qui exclut de fait les travailleurs ind´ependants. Pour ces raisons, nous privil´egions les donn´ees UNIDO dans cette th`ese lorsque nous focalisons notre analyse sur les pays en d´eveloppement.

27

Chapitre introductif

1.3.2

Evolutions dans les pays de l’OCDE et dans les pays en d´ eveloppement

La communaut´e scientifique a longtemps consid´er´e la part des salaires comme constante dans le temps, justifiant d`es lors l’utilisation intensive de la fonction Cobb-Douglas en macro´economie. Cette observation constitue l’un des faits stylis´es de Kaldor (1955) et semble directement inspir´ee de l’exp´erience am´ericaine. Un bref aper¸cu des donn´ees brutes (non corrig´ee des travailleurs ind´ependants) provenant de l’OCDE pour ce pays sugg`ere cette constance comme le montre la Figure 1.1.

Figure 1.1 – Evolution de la part des salaires aux Etats-Unis, 1970-1995, donn´ees brutes des Nations Unies D`es 1958, Solow remet en question cette suppos´ee constance de la part des salaires. L’exp´erience de nombreux pays dans le monde semble lui donner raison. La part des salaires semble avoir diminu´e de mani`ere assez brutale dans de nombreux pays europ´eens ainsi que dans les pays en d´eveloppement. Elle semble par contre relativement stable dans les pays anglo-saxons. Ainsi que nous l’avons justifi´e dans la section pr´ec´edente, nous utilisons pour les pays de l’OCDE les donn´ees provenant des comptes de l’OCDE ajust´ees des travailleurs ind´ependants. Nous graphons s´epar´ement la part des salaires agr´eg´ee pour six pays d’Europe continentale (France, Allemagne, Italie, Espagne, Hollande et Finlande) et trois pays anglo-saxons (RoyaumeUnis, Etats Unis et Canada). Si la part des salaires semble d´ecroˆıtre fortement dans les pays d’Europe continentale, elle est davantage stable dans les pays anglo-saxons. Une l´eg`ere tendance n´egative apparaˆıt cependant avec les donn´ees corrig´ees du ph´enom`ene du travailleur ind´ependant (ce qui n’est pas le cas

28

1.3. La part de salaires n’est pas constante dans le temps et dans l’espace

Figure 1.2 – Evolution de la part des salaires dans les pays anglo-saxons et dans les pays d’Europe continentale, 1971-2003. Source : donn´ees OCDE ajust´ees du ph´enom`ene du travailleur ind´ependant.

pou les donn´ees non ajust´ees). Ces mouvements importants de parts des salaires dans les pays europ´eens ont interpel´e les macro´economistes les plus renomm´es comme Bruno et Sachs (1985), Blanchard (1997), Caballero et Hammour (1998), Bertolila et Saint-Paul (2003), Blanchard et Giavazzi (2003), ou Jones (2003). Tous notent le declin tr`es rapide de la part des salaires en Europe continentale ` a des niveaux inf´erieurs `a ceux observ´es au d´ebut des ann´ees 1970. Cette baisse est mˆeme plus importante si l’on se concentre uniquement sur les activit´es de march´e comme le montre les donn´ees pr´esent´ees dans Blanchard (1997), De Serres et Al (2002) ou encore Blanchard et Giavazzi (2003). Par contre, comme le notent d´ej`a ces derniers la part des salaires dans les pays anglo-saxons semble confirmer le fait stylis´e de Kaldor (1955) de relative constance de la part des salaires. Cette vision n’est pas unanimement accept´ee. Askenazy (2003) montre que les caract´eristiques des travailleurs ind´ependants ont beaucoup ´evolu´e dans le temps. Ils ´etaient relativement moins qualifi´es que le reste de la force de travail dans les ann´ees 1970, et sont aujourd’hui relativement plus qualifi´es. De ce point de vue, l’ajustement qui consiste `a attribuer aux ind´ependants un salaire fictif ´egal au salaire moyen conduit `a sur-estimer la part des salaires dans les ann´ees 1970, et `a la sous-estimer plus r´ecemment. Cette et al (2009) montrent qu’en consid´erant uniquement les entreprises du secteur marchand non financier, la part des salaires n’est pas plus faible qu’en 1970 pour la France (voir ´egalement Canry (2007) et Baghli et al (2003)).

29

Chapitre introductif Concernant les pays en d´eveloppement, le constat est tr`es similaire `a celui qui a ´et´e r´ealis´e pour les pays d’Europe continentale et la part des salaires semble avoir fortement diminu´e. Ce fait a d´ej` a ´et´e mis en ´evidence par Harrison (2001) pour les donn´ees des Nations Unies non corrig´ees des travailleurs ind´ependants. Nous utilisons pour notre part les donn´ees plus robustes provenant de la base UNIDO comme justifi´e dans la section pr´ec´edente. Nous utilisons ´egalement les donn´ees des Nations Unies non ajust´ees afin de s’assurer de la robustesse aux donn´ees du ph´enom`ene mis en ´evidence. Nous mettons en exergue le mˆeme fait qu’Harrison (2001). La part des salaires semble avoir diminu´e de mani`ere tr`es prononc´ee dans les pays en d´eveloppement. Nous exploitons le caract`ere dynamique des donn´ees en estimant un mod`ele de panel avec effets fixes pays et effets temporels communs `a l’ensemble des pays. Les effets temporels estim´es sont repr´esent´es sur la Figure 1.3.

Figure 1.3 – Evolution de la part des salaires dans les PED, 1970-2000. Le graphique repr´esente les constantes temporelles estim´ees `a partir du mod`ele statistique suivant : PSit = αi + βt + εit , o` u PS est la part des salaires, i est l’indice du pays, t est l’indice de l’ann´ee, α est un effet fixe pays, β est un effet temporel, et ε est le terme d’erreur. Source des donn´ees : UNIDO et Nations-Unies Afin d’affiner le constat, nous divisons les pays en d´eveloppement en trois groupes d´efinis par la classification de la Banque Mondiale : pays `a faibles revenus (BR), pays `a revenus interm´ediaires bas (RIB) et les pays ` a revenus interm´ediaires hauts (RIH). La Figure 1.4 repr´esente les effets temporels estim´es sur donn´ees UNIDO pour chaque groupe de pays. La part des salaires a diminu´e de mani`ere beaucoup plus prononc´ee dans les pays les moins

30

1.3. La part de salaires n’est pas constante dans le temps et dans l’espace

Figure 1.4 – Evolution de la part des salaires par groupe de PED, 1970-2000. Le graphique repr´esente les constantes temporelles estim´ees a` partir des mod`eles statistiques suivants : PSijt = αi + βjt + εijt , o` u PS est la part des salaires, i est l’indice du pays, j l’indice du groupe de pays, t l’indice temporel, α l’effet fixe pays, et ε le terme d’erreur. Source des donn´ees : UNIDO. avanc´es alors qu’elle semble remonter progressivement dans les pays `a revenus interm´ediaires hauts `a partir du milieu des ann´ees 1990.

1.3.3

Part des salaires et d´ eveloppement : une courbe de Kuznets

Le lien entre d´eveloppement ´economique et in´egalit´es `a suscit´e une litt´erature abondante depuis les travaux fondateurs de Kuznets (1955). Selon Kuznets, le d´eveloppement ´economique diminue la part dans l’emploi total du secteur agricole rural relativement plus ´egalitaire et pauvre au profit du secteur manufacturier urbain relativement plus in´egalitaire et riche. Par la suite le secteur manufacturier urbain devient moins in´egalitaire. Cela g´en`ere une courbe en U entre le niveau d’in´egalit´e et le d´eveloppement ´economique. Cette id´ee est formalis´ee par Robinson (1976), Knight (1976), et Fields (1979) et donne lieu `a de nombreuses ´etudes empiriques. Nous montrons dans cette sous section qu’un lien similaire existe entre la part des salaires et le d´eveloppement ´economique d’un pays. Les donn´ees agr´eg´ees des Nations Unies sugg`erent une corr´elation positive significative entre la part des salaires et le d´eveloppement en coupe transversale. A une date donn´ee, la part des

31

Chapitre introductif

Table 1.1 – Part des salaires et d´eveloppement BR RIB RIH HR Part des salaires moyennea 30.69 28.87 33.51 45.68 Nb de pays 14 25 19 33 a

Le tableau rapporte la part des salaires moyenne (en %) dans le secteur manufacturier pour chaque sous-groupe de pays. Donn´ees pour l’ann´ee 1990. Source : UNIDO

salaires est substantiellement plus ´elev´ee dans les pays d´evelopp´es relativement aux pays en d´eveloppement. Cependant, Gollin (2002) montre, sur coupe transversale et pour un nombre relativement restreint de pays, que la relation entre part des salaires et niveau de d´eveloppement disparaˆıt lorsqu’on ajuste les donn´ees pour tenir compte du ph´enom`ene du travailleur ind´ependant. Dans le mˆeme temps la dispersion de part des salaires entre les pays reste extrˆemement ´elev´ee, l’´ecart type passant de 0.119 avant ajustement `a 0.110 apr`es ajustement (ce qui peut signifier une mauvaise qualit´e de l’ajustement pour les pays en d´eveloppement). Les donn´ees du secteur manufacturier de l’UNIDO ne n´ecessitent aucun ajustement. On montre ` a l’aide de ces donn´ees que la part des salaires est significativement plus ´elev´ee dans les pays d´evelopp´es. Le Tableau 1.1 reproduit le niveau moyen de part des salaires pour les trois groupes de pays en d´eveloppement d´efinis par la Banque Mondiale ainsi que pour les pays developp´es (HR). La dimension temporelle des donn´ees UNIDO nous autorise `a estimer directement la relation entre la part des salaires et le d´eveloppement ´economique au niveau des pays directement et non plus en coupe transversale. Nous estimons pour ce faire un mod`ele en donn´ees de panel avec des effets fixes pays, des effets fixes temporels, le niveau de d´eveloppement (approxim´e par le logarithme du PIB) et le niveau de d´eveloppement au carr´e, ainsi que diverse variables de contrˆole telles que l’accumulation de facteurs ou l’ouverture commerciale et financi`ere susceptibles d’impacter la part des salaires. La relation est estim´ee pour les pays en d´eveloppement. La Figure 1.5 montre la corr´elation partielle entre le log du PIB et la part des salaires. La relation entre part des salaires et d´eveloppement prend la forme d’une courbe en U `a la Kuznets.

1.3.4

Part des salaires et mondialisation : une corr´ elation n´ egative

Nous avons montr´e que la part des salaires n’est pas constante dans le temps et dans l’espace. Dans le mˆeme temps, aussi bien les pays en d´eveloppement que les pays d´evelopp´es sont deve-

32

`se 1.4. Questionnements de la the

Figure 1.5 – Corr´elation partielle entre part des salaires et d´eveloppement. Le graphique est tir´e du mod`ele statistique suivant : PSit = αi +β log P IBit +γ (log P IBit )2 +δXit +εit , o` u PS est la part des salaires, i est l’indice du pays, t l’indice de l’ann´ee, X est un vecteur de variables agr´eg´ees, et ε est le terme d’erreur. Nous avons repr´esent´e la variable b it (axe des ordonn´ees) en fonction de P IBit (axe des abscisses). PSit − α bi − δX nus de plus en plus ouverts aux flux de capitaux et commerciaux. On doit donc se demander dans quelle mesure les deux ph´enom`enes sont interd´ependants. En particulier, la mondialisation entraˆıne-t-elle la baisse de la part des salaires dans les pays d’Europe continentale et dans les pays en d´eveloppement ? Nous pr´esentons dans la section suivante les questionnements de la th`ese. Elle traite pour une grande part du rˆ ole que peut jouer la mondialisation des ´echanges et la libre circulation des capitaux dans les mouvements observ´es de la part des salaires. Elle traˆıte ´egalement de l’impact du d´eveloppement ´economique sur la part des salaires.

1.4

Questionnements de la th` ese

Dans cette section, nous soulignons que l’ouverture commerciale et financi`ere des pays est associ´ee `a des gains de productivit´e consid´erables mais ´egalement `a des coˆ uts non n´egligeables. La chute de la part des salaires est per¸cue comme un coˆ ut important induit par la mondialisation et qui entraˆıne une d´et´erioration relative, voire absolue du bien-ˆetre des travailleurs. Nous

33

Chapitre introductif examinons bri`evement les arguments classiques de la litt´erature qui lient part des salaires et mondialisation. Nous pr´esentons ensuite les arguments avanc´es dans la th`ese.

1.4.1

La mondialisation : d´ ebats et controverses

1.4.1.1

Les gains

Si l’impact de l’ouverture sur les gains de productivit´e a longtemps fait d´ebat il est maintenant admis que la mondialisation a ´et´e la source d’importants gains de productivit´e dans les ´economies en d´eveloppement aussi bien que dans les pays d´evelopp´es. Nous pr´esentons dans un premier temps la litt´erature liant ouverture commerciale et gains de productivit´e. Nous nous penchons ensuite sur le lien plus controvers´e entre libre circulation des capitaux et croissance. Une litt´erature th´eorique abondante existe d´esormais sur les gains associ´es `a l’ouverture commerciale. On peut citer la litt´erature, parfois ancienne, des th´eories statiques de l’´echange5 ou plus recemment la litt´erature liant le taux de croissance `a long terme et le taux d’ouverture commerciale, bas´ee sur les mod`eles de croissance endog`ene d’innovation verticale et horizontale6 . Dans le cas des pays en d´eveloppement, deux autres sources de croissance induites par le commerce peuvent ˆetre mentionn´ees. Grossman et Helpman (1991) ou Helpman (1993) d´eveloppent des mod`eles dans lesquels les pays en d´eveloppement imitent `a moindre coˆ ut les innovations. Un deuxi`eme argument valable dans le cas des pays en d´eveloppement et plus particuli`erement dans le cas des ´economies asiatiques est propos´e par Ventura (1997). Du fait du th´eor`eme d’´egalisation du prix des facteurs, ces pays ont pu continuer `a accumuler du capital sans pour autant connaˆıtre une diminution des rendements, inexorable en ´economie ferm´ee. Les taux de croissances durablement tr`es ´elev´es qu’on connu ces pays r´esulteraient ainsi d’une forte accumulation de facteurs alors que le mod`ele de Solow pr´edit que le taux de croissance doit inexorablement diminuer au fur et ` a mesure que l’on se rapproche de l’´etat stationnaire. De nombreuses ´etudes empiriques ´etablissent un lien positif entre le taux de croissance et le taux d’ouverture commerciale. La difficult´e dans ce type d’´etudes tient au fait que le taux de croissance et le taux d’ouverture sont des variables endog`enes et la causalit´e entre les deux variables est difficile ` a ´etablir (Rodriguez et Rodrik, 2000). Frankel et Romer (1999) utilisent la 5

Ricardo ou Heckscher-Ohlin-Samuelson pour les th´eories de l’avantage comparatif, bas´ees sur des diff´erences entre pays, Krugman (1979, 1980) pour un commerce de biens diff´erenci´es entre des pays similaires ou encore plus r´ecemment Melitz (2003) pour une extension du mod`ele de Krugman au cas o` u la productivit´e des firmes est h´et´erog`ene. Tous les pays r´ealisent des gains nets lorsque le pays s’ouvre. 6 Grossman et Helpman (1989,1990), Romer (1990) ou encore Romer et Rivera-Batiz (1991) d´eveloppent des mod`eles bas´es sur le mod`ele d’innovation horizontal de Romer (1986, 1990). Grossman et Helpman (1991) d´eveloppent une th´eorie bas´ee sur le mod`ele shump´eterien de croissance endog`ene d’innovation verticale de Haghion et Howitt (1992).

34

`se 1.4. Questionnements de la the m´ethode des variables instrumentales afin de traiter ce biais. Ils ´etablissent un lien clair entre taux de croissance et commerce7 . D’un autre cot´e, l’impact de l’ouverture financi`ere sur le taux de croissance, notamment dans les pays en d´eveloppement fait plus d´ebat et l’id´ee selon laquelle la lib´eralisation financi`ere peut avoir un impact positif sur le taux de croissance a longtemps laiss´e sceptique. Nous examinons dans un premier temps les arguments th´eoriques permettant de lier le taux de croissance et l’ouverture financi`ere avant de nous pencher sur la validit´e empirique de ces arguments. Le principal argument en faveur de l’ouverture du compte capital pour les pays en d´eveloppement repose sur le canal de l’accumulation du capital. Dans la mesure o` u les pays en d´eveloppement sont moins intensif en capital, l’ouverture, en diminuant le taux d’int´eret permet une augmentation temporaire du taux de croissance comme sp´ecifi´e dans le mod`ele de Solow (1958). Pour Alfaro et Hammel (2007), l’ouverture du compte capital accroˆıt consid´erablement les importations de biens capital servant d’inputs. Cela favorise la diffusion de la technologie dans les pays en d´eveloppement et permet d’accroˆıtre la productivit´e totale des facteurs. De mˆeme, une litt´erature abondante existe sur le partage du risque au niveau international (Obstfeld, 1994, Athanasoulis et Van Wincoop, 2000) que permet l’ouverture financi`ere. Enfin, l’ouverture du compte capital pour les pays en d´eveloppement peut se traduire par une forte entr´ee d’Investissement Direct Etranger, dont la productivit´e est bien plus ´elev´ee que celle des firmes locales et permettant des transferts de technologies. Cependant, il apparait au regard des donn´ees sur les stocks d’IDE que deux pays pr´esentant une ouverture du compte capital similaire peuvent attirer des quantit´es tr`es diff´erentes d’IDE. L’impact de l’ouverture financi`ere en termes de croissance par le biais des IDE demeure tr`es hypoth´etique et d´epend d’une multitude d’autres facteurs. Les ´economistes ont longtemps ´et´e partag´es sur l’opportunit´e de l’ouverture financi`ere et ce notamment pour les pays en d´eveloppement du fait principalement d’un manque d’´evidence empirique quant ` a ses bienfaits. Si certaines ”success stories”, notamment dans les pays d’Asie de l’Est, ont ´et´e favoris´ees par l’ouverture aux capitaux ´etrangers, une relation g´en´erale est loin de faire l’unanimit´e parmi les chercheurs. Cela conduit Bhagwati `a s’interroger en 1998 : ”It is time to shift the burden of proof from those who oppose to those who favor liberated capital”. Depuis cette date, de nombreux papiers empiriques ont ´et´e ´ecrits sur l’impact de la lib´eralisation financi`ere sur la croissance ´economique. 7

Voir ´egalement Buch et Toubal (2007) pour l’Allemagne ou encore Dollar et Kraay (2003) ou Lee et al (2004) pour les pays en d´eveloppement.

35

Chapitre introductif G´en´eralement, ces ´etudes d´erivent un indice d’ouverture en prenant le nombre d’ann´ees durant lesquels un pays peut ˆetre consid´er´e comme ouvert pour une p´eriode de temps donn´ee8 . On r´egresse ensuite le taux de croissance moyen sur la p´eriode sur cet indice en contrˆolant d’une s´erie de variables usuelles. La plupart des ´etudes sur le sujet ne trouvent pas d’effets significatifs de l’ouverture financi`ere sur le taux de croissance.9 Henry (2007) rel`eve que la m´ethodologie utilis´ee afin de tester l’impact de l’ouverture financi`ere sur la croissance n’est pas adapt´ee pour tester le principal argument th´eorique en faveur de l’ouverture pour les pays en d´eveloppement, `a savoir le canal de l’accumulation du capital. Tout d’abord, les indices composites d’ouverture sont inadapt´es. Ils ne mesurent par exemple pas quelle composante du compte capital a ´et´e lib´eralis´e. Ce qui importe est de rendre possible l’entr´ee de capitaux. D’autre part, l’argument de l’accumulation du capital au travers d’une r´eduction du coˆ ut de financement induit par l’ouverture implique une augmentation temporaire du taux de croissance10 . D`es lors les m´ethodologies d´ecrites pr´ec´edemment ne semblent pas capable de capturer de tels effets. Henry (2007) explique qu’il est pr´ef´erable de se tourner vers des exp´eriences de politique ´economique particuli`eres concernant l’ouverture d’une composante particuli`ere du compte capital. La lib´eralisation du march´e des actions semble un bon candidat puisque cela provoque une disparition discr`ete des barri`eres `a l’entr´ee pour les flux de capitaux entrants (Frankel, 1994). Cela procure un grand nombre d’exp´eriences de politiques ´economique dans la mesure o` u de nombreux pays en d´eveloppement ont lib´eralis´e de tels march´es au cours des ann´ees 1980 et au d´ebut des ann´ees 1990. On peut alors montrer que la p´eriode suivant l’ouverture financi`ere est caract´eris´ee par une diminution du coˆ ut du capital entraˆınant une hausse importante mais temporaire de l’investissement.11 Le taux de croissance et les salaires augmentent fortement dans les ann´ees qui suivent la lib´eralisation.12 8

Il utilisent les donn´ee du FMI disponibles dans le ”annual report on exchange arrangements and exchange restrictions (AREAER)” 9 Les plus cit´ees sont Rodrik (1998), Levine and Zervos (1998), Alesina, Grilli and Milesi-Ferretti (1994), Kraay (1998) ou Prasad et al (2003) pour un survey des ´etudes disponibles. Quelques ´etudes trouvent un impact positif telles que Quinn (1997). Edward (2001) montre que l’impact de l’ouverture est positif ` a partir d’un certain niveau de d´eveloppement. Plus g´en´eralement, il semble raisonnable de conclure que les ´etudes en coupes transversales ne permettent pas de conclure `a un lien positif entre croissance et ouverture sur longue p´eriode. 10 Mais n´eanmoins une augmentation permanente du niveau de vie. 11 Si le coˆ ut du capital n’est pas une variable directement observable, le prix des actions l’est. Henry (2000), Kim et Singal (2000) et Martell et Slutz (2003) montrent que le cours des actions augmente consid´erablement pendant les ann´ees qui suivent une p´eriode de lib´eralisation financi`ere. Bekaert et Harvey (2000) mettent en ´evidence une diminution des dividendes. Dans le mˆeme temps, le taux d’investissement augmente de 22 point de pourcentage les 5 ann´ees suivant la lib´eralisation relativement aux 5 ann´ees la pr´ec´edant pour 11 pays en d´eveloppement selon Henry (2003) et Henry (2000,b). 12 Pour le secteur manufacturier, Henry et Sasson (2009) trouvent que le taux de croissance des salaires et de la productivit´e est de 8 ` a 10 points sup´erieur dans les 3 ann´ees qui suivent la lib´eralisation relativement

36

`se 1.4. Questionnements de la the L’ouverture du compte capital favorise ´egalement l’entr´ee d’IDE impliquant par d´efinition davantage l’investisseur ´etranger dans la gestion de l’entreprise que les investissements de portefeuille. Deux types d’´etudes tentent de mesurer l’impact des IDE sur le taux de croissance. Les ´etudes macro´economiques montrent que l’entr´ee d’IDE est corr´el´ee `a la croissance ´economique.13 Les ´etudes micro´economiques sont plus nuanc´ees. Si elles montrent que les IDE augmentent la productivit´e totale des facteurs au niveau de la firme qui a re¸cu l’investissement et que les firmes ´etrang`eres sont nettement plus productives que les firmes locales, il existe peu d’´evidences sur d’´eventuels transferts de technologies entre les firmes ´etrang`eres et les firmes locales.14 Si un stock d’IDE important induit un niveau de productivit´e accru dans la mesure o` u les firmes ´etrang`eres sont plus productives que les firmes locales, un stock d’IDE important n’induit pas pour autant une croissance durable de la productivit´e dans la mesure ou les externalit´es positives pour les firmes locales sont tr`es incertaines.

1.4.1.2

Les coˆ uts

De nombreux auteurs mettent l’accent sur les coˆ uts potentiels de la mondialisation. Nous nous penchons tout d’abord sur le commerce international et ses effets sur le chˆomage et les in´egalit´es de revenus entre travailleurs qualifi´es et non qualifi´es. Nous abordons ensuite l’impact de l’ouverture financi`ere. La libre circulation des capitaux est associ´ee `a une instabilit´e financi`ere accrue et les IDE sont potentiellement associ´es `a une augmentation des in´egalit´es. La mondialisation est fr´equemment ´evoqu´e pour expliquer la d´esindustrialisation et l’apparition du chˆ omage de masse depuis le milieu des ann´ees 70. Pendant longtemps la recherche n’a pas consid´er´e la mondialisation comme une cause importante du chˆomage ou des in´egalit´es (Krugman,1995), lui pr´ef´erant des explications d’ordre technologique ou institutionnel. Une litt´erature abondante a ´emerg´e depuis afin d’´etablir un lien entre le chˆomage, les in´egalit´es, et l’ouverture. Davis (1998), Merckl (2008) ou Boulhol (2008) pour une evidence empirique contredisent la vision de Krugman (1995) en montrant que la prise en compte du th´eor`eme d’´egalisation du prix des facteurs dans une approche d’´equilibre g´en´eral global peut induire un coˆ ut important des rigidit´es salariales en terme de chˆ omage en ´economie ouverte. aux 3 ann´ees la pr´ec´edant pour 18 ´economies ´emergentes (voir ´egalement Henry, 2003, ou Bekaert et al 2005). 13 Par exemple, Borensztein et al (1998) trouvent un lien positif d’autant plus important que la maind’œuvre est ´eduqu´ee, Alfaro et al (2003) trouvent un lien d’autant plus important que les march´es financiers sont d´evelopp´es et Balasubramanyam et al (1996) un lien d’autant plus important que le pays est ouvert au commerce. 14 Voir Harrison et Addad (1993), Aitken et Harrison (1999) ou Gorg et Greenaway (2004). Il existe n´eanmoins des exceptions telles que Blomstrom (1986).

37

Chapitre introductif Davidson et al (1999) ou encore More et Ranjan (2005) introduisent des frictions sur le march´e du travail dans un mod`ele de commerce bas´e sur l’avantage comparatif `a deux secteurs et montrent que le commerce peut ˆetre associ´e `a une augmentation du chˆomage ainsi qu’` a une d´et´erioration du revenus relatif des nons qualifi´es. Plus r´ecemment, Janiak (2007) ou encore Helpman et Itskhoky (2007) ou Helpman et al (2008, 2009) montrent que le commerce, en pr´esence de frictions sur le march´e du travail et d’h´et´erog´en´eit´e des firmes induit une augmentation des in´egalit´es salariales, de mˆeme qu’une augmentation du chˆ omage. Dans un registre diff´erent, Bhagwati (1998) ou Sener (2001) montrent dans le cadre d’un mod`ele d’innovation verticale sur un continuum d’industries, que le commerce augmente le chˆ omage des non qualifi´es (chˆ omage shump´et´erien `a la Aghion et Howitt, 1994). Pour Dinopoulos et Segerstrom (1999), ce type de mod`ele implique ´egalement une augmentation des in´egalit´es entre qualifi´es et non qualifi´es dans la mesure o` u l’ouverture augmente le rendement de l’innovation, activit´e qui est intensive en travail qualifi´e. Notons n´eanmoins que certains papiers dans cette litt´erature montrent que le taux de chˆ omage et l’ouverture peuvent ˆetre n´egativement corr´el´es. Dutt et al (2009) montrent que dans le mod`ele HOS ou le mod`ele Ricardien de l’avantage comparatif et en pr´esence de frictions sur le march´e du travail avec un seul type de travailleur, l’ouverture diminue le taux de chˆomage. De mˆeme Mitra et Ranjan (2008) montrent que les d´elocalisations ou la sous-traitance de certaines activit´es intensives en travail non qualifi´e peut induire une r´eduction du taux de chˆomage des travailleurs non qualifi´es. Concernant plus sp´ecifiquement les in´egalit´es (sans aucune implication en terme de chˆ omage), Acemoglu (2003) montre dans le cadre du mod`ele HOS que le commerce peut avoir un impact sur les in´egalit´es salariales bien plus important que ce qui ´etait envisag´e jusqu’alors (Krugman 1995). Dans ce mod`ele le commerce entraine l’adoption de technologies ´economes en main-d’œuvre non qualifi´ee ce qui d´ecuple l’impact du commerce sur les in´egalit´es dans les pays d´evelopp´es. Par un ph´enom`ene d’imitation des technologies le commerce peut ´egalement accroˆıtre les in´egalit´es qu’il ´etait cens´e r´eduire dans les pays en d´eveloppement15 . Epifani et Gancia (2008) montrent que le commerce dans le cadre du mod`ele de Krugman (1979) peut induire une augmentation des in´egalit´es si les biens intensifs en travail qualifi´e b´en´eficient de rendements d’echelle plus importants. Concernant l’impact de l’ouverture financi`ere, de nombreux auteurs ont point´e qu’elle est g´en´eralement associ´ee ` a une forte augmentation du nombre de crises financi`eres et plus g´en´eralement de crises de change. Kaminsky et Reinhart (1999) ou Henry (2007) montrent que 15

Voir ´egalement Gancia et Bonfiglioli (2008)

38

`se 1.4. Questionnements de la the l’ouverture du compte capital dans les pays en d´eveloppement mais ´egalement dans les pays d´evelopp´es est associ´ee ` a une multiplication des crises de change. Le coˆ ut de ces crises en terme de production est potentiellement tr`es important. Kaminsly et Reinhart (1999), Kaminsky (2006), ou encore Hutchison et Noy (2005, 2006) montrent que ces crises conduisent `a des r´ecessions de grande ampleur. A titre d’exemple, Hutchison et Noy (2006) montrent qu’une crise de change est associ´ee ` a une diminution de la production comprise entre 2 et 3 points l’ann´ee de la crise et une diminution comprise entre 6 et 8 points lorsque la crise est de type sudden stop (sorties de capitaux). Une litt´erature pointe ´egalement l’impact des investissements directs ´etrangers sur les in´egalit´es salariales. N´eanmoins les ´evidences sur ce sujet concernent principalement les pays en d´eveloppement et restent d´ebattues16 . L’ouverture des fronti`eres aux ´echanges et aux capitaux peut induire des coˆ uts tr´es importants pour certains groupes d’individus. Ces coˆ uts peuvent induire des transferts de revenu massifs. Ainsi, Rodrik (1998) montre que les pays dont les taux d’ouverture sont les plus ´elev´es sont ´egalement les pays dont les gouvernements sont les plus importants en taille.

1.4.1.3

Et la part des salaires : les arguments classiques

Dans l’imaginaire collectif, la mondialisation occupe un rˆole tr`es important dans les mouvements de parts des salaires observ´es depuis les ann´ees 1980 dans les pays d´evelopp´es mais ´egalement dans les pays en d´eveloppement. En t´emoigne l’id´ee commun´ement admise selon laquelle les entreprises ´etrang`eres exploitent les travailleurs des pays en d´eveloppement lorsqu’elles s’y implantent. Cette id´ee largement r´epandue sous-entend que le travailleur ne profite pas du processus d’ouverture. Rodrik (1997) est le premier ` a th´eoriser ce type d’argumentaire. Selon lui, l’ouverture d´et´eriore la position du travailleur dans le processus de n´egociation salariale pour deux raisons. Tout d’abord, l’ouverture du compte capital rend le capital beaucoup plus mobile qu’avant alors que le travailleur reste lui relativement immobile au niveau international. Cette mobilit´e accrue augmente les opportunit´es externes du capital relativement au travail et r´eduit son pouvoir de n´egociation relativement aux d´etenteurs de capitaux. Il en d´ecoule une diminution du salaire n´egoci´e et une diminution de la part des salaires. L’ouverture commerciale, engendre pour sa 16

Feenstra et Hanson (1997) pour le Mexique, Figini et G¨org (1999) pour l’Irlande ou Taylor et Driffield (2005) pour le Royaume-Uni trouvent un impact positif des IDE sur les in´egalit´es salariales, alors que Blonigen et Slaughter (2001) ne trouvent pas d’impact significatif pour les Etats-Unis. Tsai (1995) ou Gopinath et Chen (2003) trouvent que les IDE ont augment´e les in´egalit´es salariales uniquement pour certain pays en d´eveloppement, alors que Basu et Guariglia (2007) trouvent une relation plus g´en´erale. Figini et G¨ org (2006) montrent que la relation positive d´ecroˆıt avec le d´eveloppement.

39

Chapitre introductif part un accroissement de la concurrence sur le march´e des biens. Ces pressions concurrentielles conduisent ` a affaiblir le travailleur dans ses exigences salariales. Encore une fois, le salaire n´egoci´e doit diminuer. Le lien entre salaire n´egoci´e et part des salaires n’est pas aussi ´evident que Rodrik (1997) le sugg`ere. Cela d´epend fortement du type de mod`ele de n´egociation consid´er´e. A titre d’exemple, dans un mod`ele de droit ` a g´erer, le lien entre part des salaires et salaire n´egoci´e d´epend exclusivement de l’´elasticit´e de la demande de travail des firmes. Ainsi une diminution du salaire n´egoci´e n’entraine pas n´ecessairement une diminution de la part des salaires dans l’´economie. Ortega et Rodriguez (2002) pour l’ouverture commerciale ou encore Harrison (2001) pour l’ouverture financi`ere mod´elisent l’argument de Rodrik (1997) au travers de mod`eles de n´egociation sophistiqu´es. Ils en arrivent aux conclusions selon laquelle une diminution du salaire n´egoci´e, induit par l’ouverture, est associ´e `a une diminution de la part des salaires. Ortega et Rodriguez (2002) utilisent une mod`ele d’´equilibre partiel ou une firme locale et une firme ´etrang`ere sont en concurrence ` a la cournot. Un syndicat n´egocie simultan´ement le salaire et le niveau d’emploi dans un mod`ele de n´egociation efficace. Dans un tel environnement, ils montrent qu’une augmentation des droits de douane augmente le salaire n´egoci´e dans la mesure ou le pouvoir de march´e de la firme et par cons´equent le surplus augmentent. Si la pr´ef´erence du syndicat pour le salaire est suffisament importante, la part des salaires augmente. Harrison (2001) d´eveloppe un mod`ele dans lequel il existe des imperfections sur le march´e des biens. Les facteurs sont r´emun´er´es ` a leur productivit´e marginale et partagent le surplus dans un jeu de n´egociation `a la Nash. La part du surplus qui revient ` a chaque facteur d´epend de ses opportunit´es externes. L’ouverture, en rendant le capital plus mobile, accroit les opportunit´es externes de ce dernier, ce qui fragilise le travailleur dans le processus de n´egociation et diminue la part du surplus qu’il retire. Il s’ensuit une diminution de la part des salaires. De nombreuses ´etudes empiriques tentent de valider l’argumentation de Rodrik en ´etablissant une relation n´egative entre part des salaires et degr´e d’ouverture commerciale ou financi`ere des ´economies au niveau macro-´economique. Ortega et Rodriguez (2002), Harrison (2001), Guscina (2006), Jayadev (2007) pour les pays en d´eveloppement et d´evelopp´es ou encore Sylvain (2008) pour les pays d´evelopp´es trouvent une corr´elation n´egative entre degr´e d’ouverture et part des salaires. Sylvain note n´eanmoins que l’ouverture commerciale ne semble pas avoir d’effets significatifs dans le cas des pays anglo-saxons. Ces ´etudes consistent principalement en l’estimation de mod`eles ` a effet fixe en utilisant des donn´ees macro´economique17 . Le principal d´efaut de ces ´etudes r´eside dans le fait que le canal par lequel la part des salaire est affect´ee, `a savoir le canal de la n´egociation, n’est pas directement test´e `a l’exception notable de Ortega et Rodriguez (2002) 17

Ortega et Rodriguez estiment ´egalement leur mod`ele sur donn´ees sectorielles issues de la base UNIDO.

40

`se 1.4. Questionnements de la the qui ne trouvent que peu d’´evidences en faveur de cet argumentaire. Deux papiers se d´emarquent. Bush et al (2008) testent l’impact de l’ouverture sur donn´ees italiennes et allemandes directement au niveau des r´egions en utilisant des m´ethodes ´econom´etriques plus avanc´ees. Ils montrent que l’impact n´egatif de la mondialisation est assez peu robuste. B¨ockerman et Maliranta (2009) montrent sur donn´ees finlandaises que la mondialisation est bien associ´ee `a une diminution de la part des salaires mais pas au niveau des firmes. Elle est plutˆot la source de r´eallocations entre firmes dont les parts des salaires sont diff´erentes. D`es lors le canal de la n´egociation ne joue aucun role dans la diminution observ´ee de la part des salaires en Finlande.

1.4.2

Nouveaux angles d’approche

Cette th`ese traite de l’impact de l’ouverture et du d´eveloppement sur la part des salaires dans la valeur ajout´ee. Elle d´eveloppe n´eanmoins un argumentaire assez diff´erent de celui d´efendu par Rodrik selon lequel le travailleur perd du pouvoir de n´egociation du fait de la pression concurrentielle accrue sur le march´e des biens ou du fait de la mobilit´e internationale du capital. La th`ese est compos´ee de quatre contributions distinctes chacune bas´ee sur un article de recherche et, correspondant ` a un chapitre de la th`ese. Nous pr´esentons dans cette section la probl´ematique associ´ee `a chacun des chapitres.

1.4.2.1

D´ eveloppement et part des salaires : le rˆ ole des frictions et du secteur informel

Nous avons vu en section 3 que la part des salaires varie fortement avec le d´eveloppement ´economique, et vraisemblablement selon une courbe en U. Nous apportons dans le deuxi`eme chapitre de th`ese une explication ` a ce ph´enom`ene. Cette explication est bas´ee sur la dualit´e du march´e du travail dans les pays en d´eveloppement associ´ee `a des frictions d’appariement entre travailleurs et postes vacants dans le march´e du travail formel. Le march´e du travail urbain des pays en d´eveloppement est caract´eris´e par une forte dualit´e entre le secteur formel compos´e de firmes relativement productives et le secteur informel compos´e de firmes bien moins productives g´er´ees par des individus `a faible capital humain (La Porta et Shleifer, 2008). Le secteur informel repr´esente plus ou moins 50% de la force de travail dans les zones urbaines selon les estimations. N´eanmoins les travailleurs dans ces deux types de firmes ne semble pas ˆetre tr`es diff´erents en terme de capital humain sugg´erant que le secteur informel dans les pays en d´eveloppement sert avant tout de refuge aux travailleurs n’ayant pas trouv´e d’emploi dans le secteur formel. Le d´eveloppement ´economique dans les pays en d´eveloppement est avant tout associ´e `a une

41

Chapitre introductif augmentation de la productivit´e dans le secteur formel. Ainsi, au premier stade du processus de d´eveloppement, la productivit´e des firmes formelles augmente, mais les opportunit´es externes du travailleur d´ependent fortement du secteur informel peu productif. D`es lors, en pr´esence de frictions sur le march´e du travail, les salaires n’augmentent pas proportionellement `a la productivit´e et la part des salaires tend ` a d´ecroitre. Au fur et `a mesure du processus de d´eveloppement, le poids du secteur informel dans l’emploi total diminue et les opportunit´es externes du travailleur d´ependent davantage du secteur formel. La part des salaires tend `a augmenter au fur et ` a mesure que le dualisme du syst`eme productif disparaˆıt. Les aspects empiriques du mod`ele font l’objet de trois analyses distinctes. Tout d’abord, le mod`ele th´eorique pr´edit la relation en U recherch´ee entre part des salaires et d´eveloppement. Ensuite, nous le calibrons sur les donn´ees UNIDO pour la part des salaires et sur les donn´ees de La Porta et Shleifer (2008) pour les coˆ uts d’entr´ee des firmes dans le secteur formel. Le mod`ele pr´edit alors la baisse observ´ee de la part du secteur informel avec le d´eveloppement. Enfin, nous utilisons les dates de lib´eralisation des march´es d’action comme des exp´eriences naturelles permettant de tester l’effet d’une baisse du coˆ ut d’acc`es au capital exog`ene. Nous montrons que la lib´eralisation des march´es de capitaux est associ´ee `a de fortes baisses de part des salaires dans les pays relativement pauvres, et `a des hausses dans les pays relativement riches.

1.4.2.2

IDE et part des salaires : h´ et´ erogeneit´ e productive des firmes et frictions sur le march´ e du travail

Le troisi`eme chapitre examine l’effet des IDE sur la part des salaires dans les pays en d´eveloppement. Nous avons vu en section 3 que la part des salaires a diminu´e fortement au cours des derni`eres d´ecennies dans l’ensemble des pays en d´eveloppement. Dans le mˆeme temps, ces pays ont accueilli des IDE en proportion croissante du PIB comme en t´emoigne la Figure 1.6. Nous avan¸cons que les IDE sont suceptibles d’expliquer une partie de la baisse de la part des salaires dans les PED. La relation causale irait ainsi des IDE vers la part des salaires. Le m´ecanisme repose sur l’h´et´erog´en´eit´e productive des firmes dans les pays en d´eveloppement. L’ouverture financi`ere permet la rencontre de deux technologies productives d’ˆages diff´erents dans un mˆeme espace : la technologie de la firme ´etrang`ere, b´en´eficiant d’un meilleur acc`es aux circuits de financements et de distribution internationaux, et celle de la firme locale associ´ee au niveau de d´eveloppement du pays hˆote. L’augmentation de l’h´et´erog´en´eit´e productive cons´ecutive `a l’ouverture aux IDE peut se traduire par une baisse de la part des salaires dans la valeur ajout´ee dans un contexte d’imperfections concurrentielles sur le march´e du travail. Consid´erons un pays ferm´e aux capitaux dans lequel une firme ´etrang`ere vient s’implanter. Une telle firme est bien plus productive que la firme locale repr´esentative. Pourtant, la firme

42

`se 1.4. Questionnements de la the

Figure 1.6 – Flux d’IDE entrant et sortant dans les PED. ´etrang`ere n’a aucune raison de payer un travailleur embauch´e `a sa productivit´e marginale. En effet, les opportunit´es externes du travailleur sont avant tout localis´ees dans des firmes locales faiblement productives. D`es lors, le PIB du pays augmente mais la masse salariale dans le pays n’augmente pas dans les mˆemes proportions. Ainsi la part des salaires doit diminuer. Au fur et ` a mesure que de nouvelles firmes ´etrang`eres rentrent sur le march´e local, les opportunit´es externes du travailleur proviennent de plus en plus de firmes ´etrang`eres, et la concurrence salariale doit faire augmenter la part des salaires. Cet argumentaire liant ouverture financi`ere et part des salaires diff`ere de la vision initi´ee par Rodrik en deux points. D’une part, ce ne sont pas des flux de capitaux hypoth´etiques (la menace de d´elocalisation par exemple) qui entraˆınent le d´eclin de la part des salaires mais bien des flux effectifs (le d´epart ou l’entr´ee concr`ete de capitaux). D’autre part, la baisse de la part des salaires ne diminue pas le bien-ˆetre du travailleur. La mondialisation continue d’ˆetre associ´ee ` a une augmentation du bien-ˆetre du travailleur puisque les salaires augmentent grˆace `a l’entr´ee de FDI. Cependant, les salaires n’augmentent pas aussi vite que l’augmentation de la productivit´e associ´ee aux IDE. Nous testons cette th´eorie sur les donn´ees provenant de la base UNIDO pour la part des salaires. La part des activit´es li´ees aux firmes ´etrang`eres est captur´ee par le ratio du stock

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Chapitre introductif d’IDE au PIB. Nous r´egressons la part des salaires dans le secteur manufacturier sur le ratio du stock d’IDE au PIB, sur son carr´e, et sur diff´erentes variables de contrˆole dict´ees par le mod`ele th´eorique. Nos estimations tiennent compte d’effets fixes pays, d’effets temporels, et nous utilisons l’estimateur de Blundell et Bonds (1998) bas´e sur la M´ethode des Moments G´en´eralis´es pour tenir compte des biais d’auto-corr´elation et d’endog´en´eit´e. Nos estimations font apparaˆıtre une courbe en U entre la part des salaires et le ratio du stock d’IDE au PIB. Cependant, la plupart des pays en d´eveloppement sont situ´es dans la partie d´ecroissante de la courbe. Les IDE contribuent ainsi fortement au d´eclin de la part des salaires dans la valeur ajout´ee.

1.4.2.3

Crises de change et part des salaires

L’ouverture financi`ere est associ´ee `a l’apparition de nombreuses crises de change pour les ´economies ´emergentes mais ´egalement pour les pays d´evelopp´es. Ces crises ont un coˆ ut en terme de production tr`es important. Nous ´etudions dans le quatri`eme chapitre comment se r´epartit ce coˆ ut entre les diff´erents facteurs de production et notamment si le facteur travail voit son revenu se d´et´eriorer de mani`ere plus ou moins que proportionnelle `a la chute de l’output. Les crises de change sont susceptibles d’entraˆıner deux types d’effets distincts sur la part des salaires. D’une part, la d´epr´eciation drastique du taux de change r´eel et les d´eparts de capitaux massifs qui caract´erisent les crises de change (et plus particuli`erement les crises de type Sudden Stop) engendrent des r´eallocations de facteurs importantes entre les secteurs des biens ´echangeables et non ´echangeables et entre les secteurs intensifs en capital et les secteurs intensifs en travail. La part des salaires ´etant diff´erente entre ces deux types de secteurs, ces r´eallocations de facteurs peuvent engendrer un changement de la part des salaires agr´eg´ee par un simple effet de composition. D’autre part, si la crise financi`ere r´eduit drastiquement la production, il n’est pas certain que cette diminution se traduise par une diminution similaire des r´emun´erations du facteur capital et du facteur travail ` a l’int´erieur de chaque secteur. En effet, le capital ´etant un facteur mobile, ses opportunit´es externes d´ependent grandement du niveau des rendements internationaux. Les opportunit´es externes du travail restent locales et diminuent de ce fait drastiquement avec la crise. D`es lors, le travailleur perd du pouvoir de n´egociation pendant cet ´episode particulier que constitue la crise et la part des salaires diminue `a l’int´erieur de chaque secteur. Cet argumentaire renvoie aux intuitions de Rodrik (1997), `a la diff´erence pr`es qu’il est appliqu´e `a un ´episode tr`es particulier, celeui dune crise de change. Ces deux types d’effet sont pr´esent´es au sein d’un mod`ele th´eorique qui distinguent deux secteurs de production et des frictions d’appariement entre chˆomeurs et postes vacants. La crise de change est mod´elis´ee comme une modification brutale du stock de capital et du prix relatif

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`se 1.4. Questionnements de la the du bien ´echangeable. Elle entraˆıne des effets de r´eallocation susceptibles de jouer `a la hausse comme `a la baisse sur la part des salaires. Elle induit ´egalement au sein de chaque secteur une baisse de la part des salaires d’autant plus forte que les opportunit´es externes du capital sur le march´e mondial sont peu affect´ees par la crise. D’un point de vue empirique, la question est donc de savoir si les ´episodes de crise de change entraˆınent des baisses de part de salaire agr´eg´ees, et si ces baisses correspondent `a des effets de r´eallocation entre les secteurs ou correspondent `a des r´eductions de parts de salaire dans chaque secteur. Nous montrons sur donn´ees du secteur manufacturier que la crise est bien associ´ee ` a une diminution de la part des salaires au niveau agr´eg´e. Cette diminution correspond pour sa quasi totalit´e ` a une diminution ` a l’int´erieur de chaque sous-secteur. Les effets de reallocation, si ils existent, ne semblent pas modifier la part des salaires agr´eg´ee de mani`ere significative.

1.4.2.4

Part des salaires et ouverture commerciale : le rˆ ole des rigidit´ es salariales

Nous examinons enfin l’impact de l’ouverture commerciale sur la part des salaires dans les pays d´evelopp´es et en d´eveloppement. Nous utilisons pour cela le mod`ele HOS dans lequel les avantages comparatifs reposent sur les diff´erences de dotations factorielles entre les pays. Nous montrons que la consid´eration de rigidit´es salariales h´et´erog`enes entre groupes de pays permet d’expliquer les mouvements de part des salaires observ´es dans le monde. Nous avons document´e en section 3 des mouvements de parts des salaires assez h´et´erog`enes pour diff´erents groupes de pays dans le monde. Ainsi, si la part des salaires semble avoir diminu´e fortement dans les pays en d´eveloppement et les pays d’Europe continentale, elle semble en revanche davantage stable dans les pays anglo-saxons. Dans le mˆeme temps, le niveau des rigidit´es salariales diff`ere entre pays. Les pays anglo-saxons ont une tradition juridique issue de la loi commune anglaise dans laquelle le contrat occupe une place pr´edominante. Dans un tel environnement l´egal, les salaires sont relativement flexibles et s’ajustent afin de garantir le plein emploi des facteurs. Les pays d’Europe continentale ont une tradition juridique issue de la loi civile fran¸caise caract´eris´ee par des r`egles beaucoup plus strictes r´egissant les relations entre les agents ´economiques. Dans cet environnement l´egal, le coˆ ut relatif des facteurs est plus rigide et ne s’ajuste pas forcement pour garantir le plein emploi des facteurs. Or, ces diff´erents pays sont devenus de plus en plus ouverts au commerce international. Nous montrons que dans un tel contexte, les rigidit´es pr´esentes sur le march´e du travail des pays d’Europe continentale peuvent avoir des effets inattendus sur les diff´erentes parts des salaires. Notre raisonnement prend place dans le mod`ele de Davis (1998) qui introduit une rigidit´e salariale pour un groupe de pays dans le mod`ele HOS. Davis examine les cons´equences de

45

Chapitre introductif l’ouverture commerciale sur le chˆomage dans les diff´erents groupes de pays. Nous ´etendons son analyse au cas des parts de salaires. Lorsque les march´es de biens finaux sont parfaitement int´egr´es entre diff´erents pays, le march´e des facteurs de production devient global et le coˆ ut des facteurs d´epend de l’offre et de la demande globale de facteurs. Le commerce d´etermine le prix des biens sur le march´e mondial et le th´eor`eme de Stolper-Samuelson lie le prix relatif des biens au coˆ ut relatif des facteurs. Dans un tel contexte, la mise en place d’une rigidit´e salariale dans un groupe de pays – soit en Europe continentale – se traduit par une augmentation du chˆomage proportionnelle ` a la taille de l’espace commercial. L’argumentaire repose sur le th´eor`eme d’´egalisation du prix des facteurs. La rigidit´e europ´eenne fixe le prix relatif des biens et le coˆ ut relatif des facteurs au niveau mondial. Cependant, la quantit´e de facteurs ne s’ajuste que dans le groupe de pays o` u le coˆ ut des facteurs est rigide. Dans la mesure o` u la quantit´e de facteurs doit s’ajuster afin de rendre compatible la quantit´e utilis´ee de facteur dans la production au niveau mondial au coˆ ut relatif rigide des facteurs, l’impact de la rigidit´e en terme d’emploi est bien plus importante qu’en ´economie ferm´ee. Qu’advient-il des parts de salaire dans les diff´erents groupes de pays ? La rigidit´e salariale provoque dans les pays d’Europe continentale une r´eallocation des facteurs de production vers le secteur intensif en capital. Comme la part des salaires dans ce secteur est plus faible que dans l’autre, la part des salaires agr´eg´ee tend `a diminuer. Une autre mani`ere de comprendre ce r´esultat est de remarquer que l’ouverture commerciale provoque une augmentation de l’´elasticit´e de la demande de travail agr´eg´ee vis-`a-vis des variations du coˆ ut relatif des facteurs. Cette augmentation de la demande de travail se traduit `a son tour par un accrosissement de l’´elasticit´e de substitution agr´eg´ee entre le capital et le travail. Et c’est pourquoi la part des salaires tend `a diminuer dans les pays d’Europe continentale. On peut illustrer ce raisonnement avec le cas de technologies de production Cobb-Douglas dans chaque secteur. Dans ce cas, on sait que les rigidit´es salariales n’ont aucun impact sur la part des salaires en ´economie ferm´ee : l’augmentation du coˆ ut relatif du travail est exactement compens´ee par une augmentation proportionnelle du chˆomage en raison de l’´elasticit´e de substitution unitaire entre capital et travail. En ´economie ouverte, cela n’est plus le cas. Les pays anglo-saxons b´en´eficient d’une augmentation du coˆ ut relatif du travail sans pour autant en payer le coˆ ut en terme d’emploi et la part des salaires augmente. Si les pays d’Europe continentale fixent le coˆ ut des facteurs au niveau concurrentiel en autarce, la part des salaires d´ecroˆıt dans les pays d’Europe continentale en mˆeme temps que le chˆomage augmente, et la part des salaires reste constante dans les pays anglo-saxons. Nous introduisons par la suite la distinction entre travail qualifi´e et travail non qualifi´e. Nous supposons que le travail qualifi´e est compl´ementaire au capital productif, alors que le travail non

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`se 1.4. Questionnements de la the qualifi´e est parfaitement substituable au capital. Ces hypoth`eses nous permettent de r´epondre `a la critique de Leontieff selon laquelle les ´echanges commerciaux sont davantage expliqu´es par l’intensit´e en travail en qualifi´e que par l’intensit´e capitalistique. Elles nous permettent ´egalement de rendre compte du fait que la part des salaires est plus faible dans les pays en d´evelopement que dans les pays d´evelopp´es, et du fait que la part des salaires tend `a diminuer avec l’ouverture commerciale dans les pays en d´eveloppement. L’approche de ce chapitre de th`ese est radicalement diff´erente de celle de Rodrik. Ici ce n’est pas une diminution du pouvoir de n´egociation qui provoque la chute de la part des salaires, mais bien la r´eallocation des facteurs de production vers les industries plus intensives en capital. De plus nous montrons que ce sont les rigidit´es sur le march´e du travail associ´ees `a un march´e des facteurs global qui, en modifiant le lien entre coˆ ut des facteurs et emploi des facteurs, provoque une chute de la part des salaires dans le groupe de pays ayant introduit la rigidit´e. Cependant la part des salaires ne change pas au niveau des entreprises ou des diff´erents secteurs.

47

Chapitre introductif

48

Chapter 2 Labor share, Informal sector and Development Summary: This chapter aims at understanding the pattern of the labor share during the development process. On the one hand, the labor share is substantially higher in developed than in developing countries. On the other hand, the labor share has decreased during the past two decades in less advanced economies. Our theory emphasizes the interplay between firms’ monopsony power and the size of the informal sector when the formal labor market is frictional. The size of the informal sector parameterizes workers’ outside opportunities in wage setting. In a first stage of development, productivity gains are not compensated by wage increases, as most of workers’ outside opportunities depend on the informal sector whose productivity remains unchanged. The labor share decreases as a result. In a second stage of development, outside opportunities rely more on productivity in formal firms as the formal sector expands. Consequently, the labor share increases.

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Labor share, Informal sector and Development

2.1

Introduction

There is a vast literature linking inequality to economic development. In this paper, we adopt a new perspective concerning this debate by focusing on the labor share, that is the ratio of wage bill to value-added. Dualism in the organization of production activities is very pervasive in developing countries (DCs), with informal, low-productivity methods of production coexisting with higher-productivity, formal methods in urban areas. We question the impact of economic development on the labor share of income in such an environment in which a significant proportion of the economy-wide resources remains trapped in the low-productivity informal sector. The factor distribution of income is a key component of income inequality. However, most of the studies focus on wage inequality. By contrast, there is little focus on the labor share. Still, labor share movements can modify income inequality, in particular when the capital distribution is more concentrated than the wage distribution. Checchi and Garcia Penalosa (2009) show that the labor share is an important determinant of income inequality in OECD countries. Similarly, Garcia-Penalosa and Orgiazzi (2009) highlight the increasing role in unequal possession of capital in OECD countries. Concerning developing countries, Daudey and Garcia-Penalosa (2006) show that a larger labor share is associated with a lower Gini coefficient of personal incomes and that the effect is quantitatively large. The main reason behind the neglect of the labor share relies on Kaldor’s stylized fact (1955) in favor of constant labor shares across time and space, in spite of Solow’s skepticism as early as 1958. This fact - mainly inspired from the US experience - is contradicted by recent empirical studies. Not only the labor share sharply decreased in many European countries in the 1980s, but it also plunged in developing countries and more particularly in low developing countries (LDCs). In addition, the labor share remains substantially higher in developed countries than in DCs. Our article offers several contributions. First it provides a new explanation to the decrease in labor share that LDCs experienced in the last decades. Then, it predicts that, over the very long run, the labor share should increase to reach a higher level than initially. Finally, it explains the spectacular decrease of the informal sector that DCs experience during development. We proceed in four steps. Section 2 presents a variety of facts that (i) we plan to explain and (ii) that we take as a starting point in the rest of the paper. (i) We document a Kuznets curve between the labor share and the log of GDP per capita. The labor share decreases with GDP per capita at early stages of development, while it increases with GDP per capita at later stages. Although we do not control for causality (however, see below), this finding is robust to country fixed effects, time effects, and control variables like capital deepness, trade, and institutional financial openess. (ii) We highlight three channels that could drive this relationship.

50

2.1. Introduction First, cross-country studies show that regulation and entry barriers on good market decrease with development. Second, the informal sector shrinks with development. Finally, firms in the informal sector are less productive than firms in the formal sector. Section 3 proposes a theoretical model that is based on the facts highlighted previously. The model is static and features a formal and an informal sectors, shadow entry costs and endogenous frictions in the formal sector, multiple applications, and capital choice. We now comment each assumption separately. The model assumes there are rents in the product market, and that such rents are shared between workers and employers according to market frictions and informal sector productivity. Rents in the product market are introduced in a simple way. Following Blanchard and Giavazzi (2003), we suppose that firm entry in the formal sector involves paying a shadow entry cost. Unlike resource costs, shadow costs imply rents that must be split between firm owners and their employees. Shadow costs refer to the product market regulation that limits the number of competitors at sector level. Although we make this assumption for simplicity, the idea whereby entry costs determine product market competition is consistent with Djankov et al (2002) who show that high entry costs are generally associated with a low degree of product market competition in DCs. Using panel data on network industries, Azmat et al (2007) show theoretically and empirically that (shadow) entry barriers on the good market have a major impact on the labor share for OECD countries. The formal sector is characterized by frictions on the labor market whereas the labor market is competitive in the informal sector. Matching frictions usually characterize the labor market of developed countries. Nevertheless, estimates of the matching function show that matching frictions are also very strong in DCs (see Rama (1998) for Tunisia, and Berman (1997) and Yashiv (2000) for Israel). By contrast, the informal sector seems much less frictional.1 Frictions together with the informal sector determine firms’ ability to pays workers below marginal product and enjoy the rents obtained in the product market. We follow Albrecht, Gautier and Vroman (2006) – thereafter AGV – who allow for wage posting, multiple applications of workers, and Bertrand competition between potential employers. In this model, individual wage depends on the number of offers the worker receives. Individuals either receive their marginal product, or get paid the monopsony wage. As inidviduals can always work in the informal sector, 1

Mc Kenzie and Woodruff (2006) show that (real) entry costs to open a micro-firm are very low in the Mexican informal sector. Fleck and Sorrentino (1994) show that a majority of micro-firms in the informal sector corresponds to an individual, working at home and without any loans. Yamada (1996), Marcouiller et al (1997) and Maloney (1999) show for Peru, El Salvador and Mexico that self-employed workers and workers in family business represent a large part of the informal sector that correspond to a vast unregulated sector of entrepreneurs. As noted by Zenou (2008) if frictions exist in this sector, they should not be very important.

51

Labor share, Informal sector and Development informal income provides a lower bound to indiviual wage and sizes the monopsony wage. In equilibrium, the number of firms in the formal sector depends on the entry cost, on the capital cost, on total factor productivity, and on the productivity differential between formal and informal firms. We use our model to predict the impact of development on the labor share. The development process is modeled through two aspects: a decrease in entry costs and an increase in formal sector productivity / a decrease in capital cost. On the one hand, the decrease in entry costs fosters competition on the good market. The entry of new firms increases wage competition as workers’ outside opportunities become higher, relying more on high-productive formal sector firms. As a result, the labor share increases. On the other hand, productivity increases more in the formal than in the informal sector. The rising productivity gap between the formal and informal sectors gives birth to two opposite effects. Firstly, the monopsony wage does not increase with productivity growth. At given number of firms this implies that the mean wage does not increase as fast as formal productivity and the labor share goes down. Secondly, the increase in profits induces entry of new firms, which makes the labor share increases because of wage competition. The negative effect dominates at early stages of development. That allows us to explain the decrease in labor share observed in DCs and more particularly in LDCs, whose growth has accelerated the last decades. At some point, the competition effect should dominate and the labor share rises with development. In Section 4, we assess the empirical validity of our model through two different methods. We first calibrate the model and test its ability to reproduce the major stylized facts highlighted in Section 2. The idea of the calibration is to match the observed relationships between entry cost and development on the one side and labor share and development on the other side. The model predicts the corresponding productivity gap between formal and informal firms, and the percentage of the workforce in the informal sector. The model replicates the quantitative decline of the informal sector observed along development. We then use financial liberalization episodes to evaluate the impact of a decline in capital cost on the labor share. Financial liberalization episodes have substantial impact on output growth during the 3-5 years following a liberalization date (see Henry, 2003, 2007, and Henry and Sasson, 2009). We use such liberalization dates as natural experiments to test the impact of an unexpected decrease in capital cost on the labor share of income for DCs. Our results are in line with the theoretical model. We show that financial liberalization has a strong negative effect on the labor share in DCs, while the effect is positive in developed economies. This paper relates to different strands of literature. First, it belongs to the growing literature on the determinants of the labor share, as emphasized by the contributions of Bertolila and Saint

52

2.1. Introduction Paul (2003), Blanchard and Giavazzi (2003), Jones (2003), and Acemoglu and Guerrieri (2008). None of them focus on developing countries. Second, the paper is connected with the literature on inequality along the development path. This litterature starts with Kuznets (1955) and was formalized later by Robinson (1976), Knight (1976), and Fields (1979) who argue that the rural-urban income differential is constant but the share of the population in the agricultural sector changes with development, producing the familiar U-shape for evolution of income inequality over time (inequality between sectors). In this paper we adopt a quite different perspective by focusing only on urban areas where an important fraction of the workforce lies in the informal sector (aroung 40% according to Sethuraman, 1981, and Rauch, 1993). Third, the idea whereby the informal sector plays a key role in the formal sector performance is widely accepted in the literature2 . Our framework relies on the coexistence of a frictional labor market in the formal sector and a competitive market in the informal sector in DCs. Zenou (2008) and Satchi and temple (2009) make a similar assumption and include workforce migration in their model, following Harris and Todaro (1971). They study the impact of different labor market policies on economic outcomes at the short and medium run (taxation, minimum wage or unionization). Albrecht et al (2008) follow Amaral and Quintin (2006) and adopt a different perspective. In their work, formal and informal sectors are both characterized by frictions. Workers differ in formal sector productivity and choose whether they work in the formal sector or not. Wages are negotiated in three approaches and outside opportunities rely on the size and productivity of the informal sector. Whether the informal sector is frictional or not is not important in our paper. What is important is the fact that informal sector productivity sizes the monospony wage. Our paper offers a simple and tractable model in the spirit of these various contributions to address a different problem, namely the impact of development on the labor share of income. Finally, this article is closely related to the literature dealing with the impact of firm monopsony power on the labor share. Decreuse and Maarek (2009) show that FDI have a negative impact on the labor share because of the monopsony power that foreign firms derive from their technological advance. Daudey and Decreuse (2007) study the impact of education on workers’ mobility between jobs and their ability to generate wage competition between potential employers. They show that education has a positive impact on the labor share in OECD countries. In this paper we are interested in the evolution of firms’ monopsony power during the development process and we highlight the role played by the informal sector. 2

See for example Harris and Todaro (1971), Mazumdar (1983), Rauch (1991), Dessy and Pallage (2003) or Straub (2005) for theoretical literature and Banerjee and Dufflo (2007) or Djankov and Shleifer (2008) for empirical literature.

53

Labor share, Informal sector and Development The rest of the paper is organized as follows. Section 2 presents the stylized facts and discusses the various assumptions we make in the theoretical model. Section 3 presents the model and examines the predicted relationship between labor share and development. Section 4 turns to the quantitative assessment of the theory through a calibration exercise and natural experiments at the aggregate level. Section 5 concludes.

2.2

Stylized facts

In this section, we present different stylized facts. First, we show that the labor share is higher in developed countries than in DCs and it tends to decrease over time in DC and more particularly in LDCs. Second, we emphasize the fact that regulation on the good market decreases with development. Then, we present some evidence of a negative correlation between development and the size of the informal sector and we document the nature of agents who operate in the informal sector. Finally, we relate the sharp increase in trade and capital inflow in DCs.

2.2.1

Labor share and development

The labor share is defined as the ratio of total wage bill over value added: LS =

wL Y

(2.1)

We first compute labor shares through national account data from UN statistics division. We then use data from UNIDO (a subdivision of UN), for the manufacturing sector only. The reference year is 1999 as many data used in the paper are only available for this year. This simple definition for the labor share does not deal with measurement difficulties that bias international comparisons (see Daudey 2005). The most important issue - highlighted by Gollin (2002) - is to accurately account for the income of self-employed workers. Self-employed income is usually considered as capital income. This downward biases the measure of the labor share and makes international comparisons difficult as the proportion of self-employed in the total workforce is very different from one country to another (see Nunziata, 2008). This problem is particularly accurate in our case as the proportion of self-employed is much more important in DC than in developed countries3 . The wage data come from the Industrial Statistics Database of the United Nations Industrial 3

To correct this bias, Gollin (2002) suggests to attribute a fictive wage to self-employed workers corresponding to the mean wage of employees. This adjustment is open to criticism as in the case of DC, the majority of self employed are poor workers.

54

2.2. Stylized facts

Table 2.1: Labor share and development, Part I Low incomea Low-middle Upper-middle High income mean LS 30.69 28.87 33.51 45.68 Nb of countries 14 25 19 33 a

The table reports the mean labor share (in %) in the manufacturing sector for each subgroup of countries. Data are for the year 1990. Source: UNIDO.

Development Organization (UNIDO). UNIDO provides data on total wages and salaries and value added for the manufacturing sector, from 1963 to 2003 (unbalanced) for more than 120 countries. For a given year, wages and salaries include all payments in cash or in kind paid to employees. Payments include: (a) direct wages and salaries; (b) remuneration for time not worked; (c) bonuses and gratuities; (d) housing allowances and family allowances paid directly by the employer; and (e) payments in kind. Excluded from wages and salaries are employers’ contributions on behalf of their employees to social security, pension and insurance schemes, as well as the benefits received by employees under these schemes and severance and termination pay.4 Reasons to use this dataset are twofold. First, The UNIDO database allows us to avoid the bias induced by self-employed workers described above. The dataset only covers the manufacturing sector and contains wage and value added for almost 120 countries. Firms with less than 4 employees are excluded from the survey (this threshold can differ between countries, see Ortega and Rodriguez, 2006). Therefore, self-employed workers are excluded from the data and adjustments are not necessary. Furthermore, our model focuses on the urban labor force.Thus, focusing on the manufacturing sector seems more relevant for our purpose. The second reason we use this dataset is that it provides long series for wages for some low-income economies (10-year series), which is not the case for UN data. As a crude measure of development we use the log of GDP per capita measured in purchasing power parity. This variable is provided by the World Bank. We identify four subgroups of countries according to the World Bank classification in 2006: lower-income, lower middle-income, upper middle-income, and high-income groups. Table 2.1 computes the mean labor share for each subgroup in 1990. It shows that the labor share is subtantially higher in developed than in DCs. We then turn to econometrics and run regressions on panel data. Time series on the labor 4

If social contributions were included, the gap between labor shares in developed and developing countries would even be more important and the labor share would increase much more with development.

55

Labor share, Informal sector and Development

Table 2.2: Labor share and development, Part II GDP 2

GDP

Low incomea

Low-middle

Upper-middle

High income

DCs

−13.69∗∗∗

−2.59

4.97

−0.877

−59.63∗∗∗

(3.02)

(2.35)

(3.23)

(2.86)

(18.27)

.

.

.

.

3.58∗∗∗ (1.157)

dummies R2 (within) nb countries nb observations

yes 0.242 29 340

yes 0.237 34 500

yes 0.101 25 378

yes 0.122 31 610

yes 0.149 88 1218

a

All regressions include country and time effects. Squared errors are clustered at country level. Significance levels: *** 1%, ** 5%, * 10%.

share are not long enough to identify the long-term development process. Thus, we first run regressions on different subgroups of countries. We control for time and country fixed effects. Standard errors are clustered at country level and regressors are lagged one period to deal with endogeneity issues. Second, we estimate a regression for all DCs that include the square of the log of GDP per capita in order to identify a non-monotonic relationship between the labor share in manufacturing sector and development. Note, however, that the results presented in this subsection are simple correlations and deducing causality would require a more sophisticated econometric approach. The first regressions we run are: LSit = ai + at + β1 GDPt−1 + uit

(2.2)

LSit = ai + at + β1 GDPt−1 + β2 GDP 2 t−1 + uit

(2.3)

Results are presented in Table 2.2. Development has a negative impact on the labor share at early stages of development. Then the labor share increases with development. The impact of development for low-income countries (at the begenning of development process) is strongly negative. It becomes less negative for lower-middle income countries. For the upper middle-income group the impact is strongly positive. Those correlations between the labor share and GDP per capita suggest a U-shaped ` a la Kuznet for the labor share. It is consistent with other studies showing a clear decrease of the labor share in DCs and more particularly in LDCs.5 5

See for example Harrison (2002) or Maarek and Decreuse (2009).

56

2.2. Stylized facts

Table 2.3: Labor share and development, Part III GDP 2

GDP I/Y

OPENT OPENK dummies R2 (within) nb countries nb observations

Low incomea

Low-middle

Upper-middle

High income

DCs

−15.86∗∗∗

−2.15

23.06∗∗∗

5.98∗∗

−119.31∗∗∗

(3.93)

(3.02)

(4.94)

(2.95)

(22.33)

.

.

.

.

7.59∗∗∗

∗∗∗

3.37

∗∗∗

1.17

5.93

(0.89)

(1.10)

(6.60)

(5.88)

(0.83)

−0.253∗∗∗

0.018

−0.029

−0.274∗∗∗

−0.043

(0.044) ∗∗

(0.040)

(0.053)

(0.026) ∗∗

(0.05) ∗∗∗

26.11

(1.41) ∗∗

2.12

−0.645

0.042

(1.10)

(0.89)

(0.709)

(0.477)

(0.53)

yes 0.529 18 164

yes 0.310 23 320

yes 0.341 19 204

yes 0.227 26 460

yes 0.262 60 688

3.27

1.94

1.27

a

All regressions include country and time effects. Squared errors are clustered at country level. Significance levels: *** 1%, ** 5%, * 10%.

We now control for other variables that could introduce potential biases. First, we control for factor accumulation. Indeed, development can impact the labor share through factor accumulation depending on the elasticity of substitution between capital and labor. We add a proxy for the capital-ouput ratio. We use the investment-output ratio I/Y available from the UNIDO database. Then, we use proxies for openness. It is important to control for openness to deal with omitted variable bias as development and openness frequently go toghether. We use the trade ratio of exports plus imports to GDP OP EN as a proxy for trade openness. We also use the index of Ito and Chinn (2006) OP EN K for financial oppeness. The regressions we run are:

LSit = ai + at + β1 GDPit−1 + β2 I/Yit−1 + β3 OP EN Tit−1 + β4 OP EN Kit−1 + uit

(2.4)

LSit = ai + at + β1 GDPit−1 + β2 GDP 2 it−1 + β3 I/Yit−1 + β4 OP EN Tit−1 + β5 OP EN Kit−1 + uit (2.5) Results are presented in Table 2.3. The relationship between the labor share and development is unaffected by the various controls. We conclude that there exists a U-shaped curve between labor share and development, robust to the inclusion of controls such as country and time dummies, openness variables, and

57

Labor share, Informal sector and Development capital deepness. Figure 2.1 represents the relation between development and the labor share. We substract to the labor share the estimated countries fixed effects, time dummies and impact of controls in order to have the partial correlation between the labor share and log GDP per capita6 .

Figure 2.1: LS and development: A Kuznets type relation

2.2.2

Entry costs on the good market and development

In this subsection, we document the entry costs on the good market and their evolution with respect to development level. This analysis is based on Djankov et al (2002) who compute three different measures of entry costs for 1999. The dataset covers the number of procedures, official time (in business days) to comply with those procedures and official cost7 (as a percentage of per capita income) a start up must bear before it can legally operate. The sample used includes 85 countries. Table 2.4 reproduces part of the results. Entry costs drastically diminish with development. 6

Formally, LS − β3 I/Yit−1 + β4 OP EN Tit−1 + β5 OP EN Kit−1 − ai −at = β1 GDP + β2 GDP 2 + εit 7 This cost does not include the opportunity cost due to time spent in administrative procedures. It would be redundant.

58

2.2. Stylized facts

a

Income quartile Top Quartile 2nd Quartile 3rd Quartile 4th Quartile a

Table 2.4: Entry costs on the good market Nb procedures Nb days Cost (%GDP) 6.77 24.5 0.1 11.11 49.29 0.33 12.33 53.1 0.41 11.9 63.73 1.08

GDP 24,372 5,847 1,568 349

Source: Djankov et al (2002).

Figure 2.2: Number of days to start a business and development level. Source: Djankov et al (2002) The most striking difference concerns cost as a percentage of per capita GDP. Although creating a start up is quite cheap for the first quartile countries (10% of per capita GDP), this cost may become unbearable for many potential entrants in DC where it can reach 400% of GDP and where credit market imperfections are often important8 . Figure 2.2 highlights a negative relation between the number of days to comply with procedures and development. Corruption is another aspect of entry costs that is difficult to account for. One can imagine that corruption is all the more important than entry costs are high. Indeed, rents associated with entry costs and the importance of these costs lead to a demand for corruption to avoid paying entry costs and an offer of corruption to extract the rent. It is very likely that legal entry costs and corruption go together. Djankov et al (2002) regress a corruption index over the number of procedures an entrant must comply. The correlation between those two variables is very high and DC suffer more from corruption than developed countries. This could add an 8

Those means are statistically different between groups except for countries of quartiles 2 and 3.

59

Labor share, Informal sector and Development extra cost to high formal entry cost. Finally, entry costs could result from a lack of skilled workers. La Porta and Shleifer (2008) show managers have higher human capital in formal than in informal sector. We can imagine, as Dessy and Pallage (2003) suggest, that human capital of managers has to be high in order to benefit from the best production technology available in the formal sector. Hence, low education of workforce can be assimilated to an entry cost and creates rents in the formal sector (see subsection 2.3 and 3.1) as firms in formal and informal sector operate in a different sector.

2.2.3

Informal sector and development

We document two aspects of the informal sector central in our modelization. On the one hand the size of the informal sector sharply decreases over the development process. Therefore, the informal sector is much more important in DC than in developed countries. On the other hand, the informal sector in the urban area is composed of small firms whose productivity is very low relative to formal ones. We use the database of Djankov et al (2002) although there exist many ways to measure the size of informal sector (see for example Schneider and Enste, 2000). Data correspond to 1999 and we represent in Figure 2.3the weight of the informal sector as a percentage of GDP9 .

Figure 2.3: Informal sector and development level. Source: Djankov et al (2002) The size of the informal sector, measured as a percentage of GDP or as a percentage of 9

This measure is better documented even if it underestimates the proportion of workers working in the informal sector as they are less productive than formal workers.

60

2.2. Stylized facts the workforce (not reported), decreases with GDP per capita. Actually, Straub (2005) and La porta and Shleifer (2008) point out that GDP per capita is the main determinant of the informal sector. We now have to understand the characteristics of firms operating in the informal sector. Our analysis is based on La Porta and Shleifer (2008) who use the Micro Survey and the Informal Survey constructed by the World Bank.10 Samples are composed of very poor countries and mainly cover the manufacturing sector (urban area) only for one year for each country, between 2002 and 2007.11 They find that formal firms are substantially more productive than informal ones. From the Micro Survey, formal firms are 39%, 59% or 74% more productive than informal firms depending on the productivity measure we adopt: sales, value added or a more structural measure of productivity.12 There still exists a debate in the literature concerning the relative productivity of the informal sector and the nature of agents operating in this sector. As noted by La Porta and Shleifer (2008), this debate can be synthetized into three different views of the informal sector. First of all, the romantic view (de Soto, 1989, 2000) according to which firms operating in the informal sector are not intrinsically different than firms operating in the formal sector. They are potentially very productive but taxes and regulations keep them in the informal sector that curbs their development. Therefore, making those firms registered would considerably increase productivity and would lead to economic development. Nevertheless, La Porta and Shleifer (2008) show that very few firms operating in the formal sector have ever operated in the informal sector, which is not in line with this theory. Second, according to the parasite view (Farell, 2004, Baily et al, 2005), firms in the informal sector are intrinsically less productive. But avoiding taxes and regulation, informal firms exert an unfair competition and hurt formal firms what curbs economic development. Still, as shown by La Porta and Shleifer (2008) firms operating in the formal sector do not seem to consider informal firms as a threat. This suggests that these firms do not operate on the same market. Finally, the dual view (see Harris and Todaro, 1970 and Rauch, 1991 among others) predicts that unofficial firms should look very different from official firms. Productive entrepreneurs pay taxes and bear the cost of government regulation in order to advertise their 10

Those surveys include only firms with less than 5 employees with an important share of informal firms. 11 Informal Survey: Bangladesh, Brazil, Cambodia, Cape Verde, Guatemala, India, Indonesia, Kenya, Niger, Pakistan, Senegal, Tanzania, Uganda. Micro Survey: Angola, Botswana, Burundi, Congo, Gambia, Guinea, Guinea-Bissau, India, Mauritania, Namibia, Rwanda, Swaziland, Tanzania, Uganda. 12 For the Informal Survey, the differences are 18%, 38% and 47%. When we compare the informal firms of the Micro and Informal Surveys with formal firms of larger size from the Enterprise Survey, the productivity differential is even more important. Small firms from the Enterprise Survey (less than 20 employee) have a per employee value added that is 104% (154%) higher than informal firms of the Micro Survey (Informal Survey).

61

Labor share, Informal sector and Development products, raise outside capital, and access public goods (use the high-productivity formal method - see Rauch, 1991, and Dessy and Pallage, 2003). Such entrepreneurs find it more profitable to run the bigger official firms than the smaller unofficial ones. In contrast, the increase in profits that less-able entrepreneurs or managers would be able to generate by operating formally is not large enough to offset the additional costs in terms of taxes and regulations. Thus, the strong prediction of the dual view is that managers and assets are matched through a sorting process that results in low-ability managers being paired with low-quality assets. Official and unofficial firms operate in different markets and have different customers. The dual view sees the unofficial economy as an archaic sector and informal firms as providers of livelihood to millions, perhaps billions, of extremely poor people (Tokman 1992), and cautions against any policies raising the costs of the unofficial firms. La Porta and Shleifer (2008) find strong empirical support for the dual view. They show that if managers have higher human capital in the formal sector, other workers are identical in the two sectors suggesting that workers in the informal sector are mainly those who did not find any job in the formal sector due to lack of opportunities.13 We follow La Porta and Shleifer and focus on the dual view in our modelization. Note, however, that the data used by La Porta and Shleifer only deal with a single aspect of the informal sector. The informal sector is not only composed of small and low productive firms but also of millions of very poor self employed looking for some ways to subsist. The idea of an informal sector relatively less productive than the formal sector consisting of self-employed individuals is confirmed by Barnerjee and Dufflo (2007) who account for economic living of the poor and focus on individuals with less than one or two dollars per day. They show that those individuals are often independent entrepreneurs getting subsistence income from informal sector due to lack of better opportunities. These entrepreneurs have low human capital and in best cases have access to informal finance with very high interest rate.14 Through lack of insurance or saving systems, these workers does not specialize and have many activities to protect from risks. Economies of scale are impossible and workers have a low productivity. Again, the dual view of labor market seems comforted in DC. An important informal sector exists through lack of opportunities and potential employers in the formal sector. The informal 13

In the Informal Survey, only 6.1% of the managers in the informal firms have a college degree wheraes for the same countries, 63.9% of the managers in the Enterprise Survey have a college degree. For the Micro Survey those proportions are respectively 12.2% and 43.1%. Concerning the average employee, in the informal firms of the Informal Survey 48.7% only have a primary education and 44.8 for the same countries of the Enterprise Survey. For the Micro Survey those proportions are respectively 59% and 47.9% 14 Straub (2005) gives theoretical justifications for the inefficiency of informal finance and high interest rates that result.

62

2.3. The model sector can be assimilated to a workforce stock looking for a job in the formal sector.

2.3

The model

The paper aims at constructing a model able to explain the impact of development on the labor share in developing countries. The model must fit several fundamental characteristics of development put forward in the former section. Namely: (i) entry costs decrease along development, (ii) formal sector productivity increases, (iii) the labor market is dual and the informal sector shrinks during development.

2.3.1

Environment

We use a static matching model with enrty costs in the good market in the spirit of Daudey and Decreuse (2006) and Decreuse and Maarek (2009). Our model differs in two aspects. First, we introduce an informal sector specific to DCs. The formal sector is characterized by frictions on the labor market contrary to the competitive informal labor market. Then, we study the implications over the long run of changes in capital cost (or more generally of an increase in formal sector productivity) and changes in entry costs. There is a continuum of identical individuals normalized to one. There are two sectors. In the informal sector, each worker produces z > 0. In the formal sector, each firm is endowed with a single job slot, which can be available or not. Holding an available job slot is costly. The cost is χ > 0. As in Blanchard and Giavazzi (2003), this is a shadow cost induced by regulation on the good market. We consider this cost as a mean to generate a rent. This assumption implies that firms make pure profits. The cost can correspond to regulations as documented in Djankov et al (2002), or to the lack of managers with high human capital who find it profitable to comply with different regulations in order to benefit from high-productivity formal technology. Following the dual view of the informal sector documented in the former section, high and low human capital managers do not operate in the same market. In turn, the scarcity of high human capital managers induces rents in the formal sector. If χ were a cost in terms of productive resources, extra profits would be dissipated in entry costs. Finally, to ensure that the unemployment rate does not directly depend on GDP per capita, we assume that entry costs are proportional to mean output y, that is χ = cy. Before starting producing in the formal sector, firms and workers meet according to the meeting technology M (u, v) that defines the number of meets (not the number of effective matches as we will see) and depends on the number of job seekers u and the number of vacant

63

Labor share, Informal sector and Development jobs v. It is important to specify the microfoundations we use in this framework as it determines the pattern of wages. We use the model of Albrecht et al (2007) - AGV - of equilibrium directed search with multiple applications. The game played by workers and potential employers occurs in several steps as specified in AGV. 1. Each vacancy posts a wage w. 2. Each unemployed worker observes all posted wages and submits a applications with no more than one application for each vacancy and where a ∈ {1, 2, ..., A}. 3. Each vacancy randomly selects one application if it receives at least one; other applications are rejected. 4. The firm offers the worker the posted wage if the worker has a single offer. If more than one vacancy makes an offer to the worker, then each vacancy can increase its bid. This leads to Bertrand competition and the worker obtains the whole surplus of the match. 5. The worker can reject any offer. 6. If the match occurs, the firm chooses the amount of capital at unit cost r. Let θ = v/u be the labor market tightness. AGV show that when the labor market is large (v, u → ∞) the probability for a worker to become employed, that is the number of matches over the number of job seekers Q(u, v, a)/u = q(θ, a), converges to  a θ −a/θ q(θ, a) = 1 − 1 − (1 − e ) a

(2.6)

where q(θ, a) is increasing and concave in θ. The probability of filling a vacancy Q(u, v, a)/v is decreasing and concave in θ and Q(u, v, a) is homogenous of degree one in u and v. The probability that any application leads to an offer equals the number of meets divided by the number of applications M (u, v, a)/au = m(θ, a) can be deduced: m(θ, a) =

θ (1 − e−a/θ ) a

(2.7)

The meeting technology has the same properties as the matching technology. AGV (2006) show that in the case of multiple applications when a > 1 the equilibrium posted wage is the monopsony wage. In our case, the monopsony wage equals output that can be achieved in the informal sector. The intuition for this result is as follows. Suppose there is a common wage w e that is larger than the monopsony wage. With multiple applications, a

64

2.3. The model vacancy always has an incentive to deviate from the common wage and undercuts it. Indeed, if the vacancy undercuts the posted wage by ε, the benefit (if he recruits a worker) amounts to ε. The corresponding cost is the decrease in the probability of receiving at least one application. However, this cost is not large as the following reasoning illustrates. Workers aim at generating wage competition between potential employers. In this purpose, they need two offers. They know that a vacancy that offers a lower wage will be less demanded. Therefore, they have strong incentives to apply to such a vacancy. This mechanism implies that the probability to fill the vacancy does not decline much with the decrease in offer wage. Actually, the probability even increases when the common wage is low. It ensures that the equilibrium posted wage decreases up to the monopsony wage. We refer to AGV for a formal proof. Without loss of generality, we assume in the remaining of the paper that each worker can apply for two vacancies that is a = 2. All workers start unemployed and u = 1. The probability for a worker to receive an offer for a particular application is m(v), which is increasing in v. Similarly, the probability for a worker not to find any offer for a particular application is 1− m(v). The probability for a firm to meet a worker can be computed as follows. The total mass of workers who receive an offer is 2m (v). Those offers must come from the v firms. Therefore, the probability that one particular firm meets at least one worker is 2m (v) /v. This probability is equal to 1 − e−2/v and decreases with v. When a vacant job becomes occupied, the firm sets the quantity of capital k at unit cost r. The production technology is f (k) and is strictly increasing and concave in k. We define α (k) ≡ kf 0 (k)/f (k) ∈ (0, 1) as the elasticity of output with respect to per capita capital. As the labor market is large, having an offer with the first application does not affect the probability to have one with the second application. Those two probabilities are independent. Hence, with probability (1 − m(v))2 the worker does not find any offer and does not contribute to production. In this case, the worker works in the informal sector. With probability 2m(v)(1 − m(v)), only one application leads to an offer. In this case, as we have shown above, the worker receives the monopsony wage z. Monopsony power appears here. If a worker does not find an alternative offer, he is unable to generate wage competition and is paid under its marginal product. Finally search can be successful for two applications with probability m(v)2 . The two firms enter Bertrand competition to attach labor services and offer the whole surplus that is the competitive wage. Indeed, a firm unable to attract any worker cannot produce but has already paid the entry cost.15 Satchi and Temple (2009) and Zenou (2008) also make the assumption that a worker who 15

Maloney (1998, 1999, 2002), Gong and van Soest (2002) or Gong et al (2004) estimate for Mexico that there exist many moves of workers from formal to informal sector and vice-versa. The two worlds are not completely separate.

65

Labor share, Informal sector and Development does not find any offer in the formal sector works in the informal sector. As specified and justified in introduction, the implicit assumption is that the labor market in the informal sector is perfect and hence worker can automatically find a job in this sector. Nevertheless if there are frictions in this sector, z can correspond to gain expectations. This would not alter the results. In our model, frictions in the formal sector parameterize the size of the informal sector. Satchi and Temple (2009) calibrate a matching model a la Mortensen Pissarides (2000) and generate an informal sector corresponding to 30% of the urban workforce. Nevertheless, they consider that in Nash bargaining process, worker takes out 70% of the surplus of the match in order to limit job creation in the formal sector. This assumption, as they note, seems unrealistic as the labor share in DCs is very low. We focus on entry costs to explain the important size of the informal sector.

2.3.2

Equilibrium

We solve the model. This mainly consists in determining the number of firms in the formal sector. We start by writing the profit function of the representative firm:   2m (v) [(1 − m (v)) (f (k) − rk − z)] π = max −χ + k v

(2.8)

With probability m(v)/v the firm meets a worker and makes a wage offer. With probability 1 − m(v) this is the only offer that the worker receives and he is paid the monopsony wage that is z. With probability m(v) the worker receives another offer from another firm and he receives the whole match surplus f (k) − rk. It is important to note that the higher v, the lower the expected profit. On the one hand, the probability for a firm to meet a worker decreases with v. On the other hand, the probability m(v) for a worker to find an alternative offer increases with v. As χ is exogenous and as k does not depend on v, we can rewrite the maximisation problem as follows: π = −χ +

2m (v) (1 − m (v)) max (f (k) − rk − z) k v

(2.9)

The optimal choice of capital result from f 0 (k) = r: the marginal product of capital equals its cost. We have seen that an increase in v leads to a decrease in expected profit through two different channels. If firms could freely enter the market, the profit expectation π for a new entrant would be nil. As there are profit opportunities to make profit, new firms enter the market, increasing

66

2.3. The model v. As the number of job seekers is constant the expected profit decreases for each firm. At equilibrium, π = 0 and the free-entry condition implicitly defines the number of firms   2m (v ∗ ) z ∗ ∗ c= (1 − m (v )) 1 − α(k ) − v∗ f (k ∗ )

(2.10)

We assume for the rest of paper that z < (1 − α (k ∗ )) f (k ∗ ). That is, outside opportunities in the informal sector are lower than the competitive wage. This assumption is in line with the empirical evidence reported in Section 2 thereby formal firms are more productive than informal firms. Equation (2.10) determines the number of firms as a function of entry cost c, outside opportunities in the informal sector z, capital cost r and parameters of the production technology such as total factor productivity.

2.3.3

The labor share

We determine the total wage bill, total output and the labor share. In a first step, we compute total output. The worker has two different probabilities to meet a firm. Its two applications can be successful with probability m(v)2 and he receives two offers or only one application is successful with probability 2(1 − m(v))m(v). The sum of those probabilities corresponds to the total probability for a worker to match with a firm. When a worker matches with a firm, he produces f (k) that depends on the quantity of capital firms rent. Hence, total output is defined as   Y = 2m (v) (1 − m (v)) + m(v)2 f (k)

(2.11)

We now compute the wage bill. There are two possible wages for worker. Either he is paid z if he receives a single offer, or he is paid the competitive wage if he receives two offers. Hence total wage bill is W = 2m (v) (1 − m (v))z + m(v)2 (1 − α(k))f (k)

(2.12)

Finally, the labor share LS is LS =

W 2m (v) (1 − m (v))z + m(v)2 (1 − α(k))f (k) = Y [2m (v) (1 − m (v)) + m(v)2 ] f (k)

After simplification, we get

67

(2.13)

Labor share, Informal sector and Development

LS = (1 − α(k))

m(v) 2(1 − m(v)) z + 2 − m(v) 2 − m(v) f (k)

(LS)

As we assume that z < (1 − α (k ∗ )) f (k ∗ ) the labor share is lower than in the competitive case where LS= 1 − α(k). Firms derive monopsony power from the lack of opportunities in the formal sector (lack of potential employers and hence low probability of finding two offers) and from the low productivity of informal sector that determines workers’ outside opportunities. We now study the links between development and the labor share and highlight the crucial role played by the informal sector.

2.3.4

Labor share and development

We study the impact of development on the labor share. The development process is captured through the evolution of three parameters: a decrease in the entry cost c, a decrease in capital cost r, and an increase in total factor productivity A. We show that a decrease in c translates into a positive effect on the labor share whereas a decrease in r (or an increase in A) has ambiguous effects. As we saw in the previous subsection, a decrease in entry cost implies an increase in the ratio of vacancies over the number of job seekers. To see the global effect on the labor share, we must differentiate the expression for LS with respect to c: 2m0 (v ∗ ) dLS = dc (2 − m (v ∗ ))2



1 − α (k ∗ ) −

z f (k ∗ )



dv ∗ yR . This reflects the technological advance of foreign firms (so that total factor productivity is higher), and/or their better access to the financial market (so that capital intensity is higher). The numbers of local and foreign firms are limited and the labor market features matching frictions. The combination of those assumptions imply that firms enjoy local monopsony power. Firm entry involves paying a cost that is proportional to expected output. From a national accounting perspective, it is important to make explicit the nature of the cost. It can receive wage dispersion once controlled for firm and individual effects.

83

FDI and the labor share in developing countries two interpretations. On the one hand, it can correspond to the purchase of capital units prior to searching a worker. On the other hand, it can be due to the regulation that limits the number of firms and guarantees superprofits for the firms managing to enter. Capital costs and superprofits are part of value added and do not coincide with labor income. By contrast, entry costs cannot correspond to spendings in intermediary goods (that would be subtracted from value added) or to wage payments (that would enter the wage bill). The cost per unit of output depends on whether the firm is foreign or local. Foreign firms pay cF , while local firms pay cR . We assume that foreign firms face higher costs than local firms and cF > cR . Workers and vacancies meet according to the meeting technology M = M (u, n). Here, u stands for the effective number of job-seekers and n stands for the number of vacancies. The meeting technology M is homogenous of degree one to ensure that the unemployment rate does not depend on the number of traders in the economy. It is also strictly increasing in both arguments, strictly concave, and bounded by min {u, n}. Each worker is endowed with two search units – two applications. Hence, u = 2. Given such an assumption, M (2, n) /2 = m(n) is the probability for a given worker to receive an offer per search unit. It is increasing in n. Similarly, 2m(n)/n is the probability of a firm finding a worker. It is decreasing in n. Firms set wages. If a worker receives a unique offer, he is paid the monopsony wage. Without loss of generality, the market value of outside opportunities is normalized to zero, and so is the monopsony wage. If a worker receives two offers, one from each application, firms enter Bertrand competition to attach labor services. Therefore, the model is static, but it features some of the properties of dynamic models with on-the-job search.

3.2.2

Labor market equilibrium

We first consider wage determination. The probability that a worker receives a single job offer is 2m(n)(1 − m(n)). Then, the wage is nil and the firm gets the whole output. The probability of receiving two offers is m (n)2 . Then, the wage depends on the productivity of the two firms. Let ρ denote the proportion of foreign firms. With probability (1 − ρ)2 , the two offers are from local firms and the worker receives output yR . With probability ρ (1 − ρ), one of the offers comes from a foreign firm, and the other comes from a local firm. Then, the worker is hired by the foreign firm and his wage is yR . The firm gets the difference yF − yR . Finally, with probability ρ2 , the two offers come from foreign firms. Then, the worker gets the marginal product yF .

84

3.2. The model Expected profits for the two types of firms are: πF πR

2m (n) [(1 − m(n)) yF + m(n)(1 − ρ)(yF − yR )] n 2m (n) = −cR yR + [1 − m(n)] yR n

= −cF yF +

(3.1) (3.2)

Firms enter the economy until profits cover the shadow costs. In equilibrium, πR = πF = 0. cF

=

cR =

  yF − yR 2m (n) 1 − m(n) + m(n)(1 − ρ) n yF 2m (n) [1 − m(n)] n

(3.3) (3.4)

These two equations simultaneously define ρ, the proportion of foreign firms, and n, the total number of firms. The system can be solved recursively. The free-entry condition (3.4) for the local firms determines the total number of firms n. Then, the free-entry condition (3.3) determines the proportion of foreign firms ρ. The facts that cF > cR and yF > yR imply that there exists a unique equilibrium with a non-trivial proportion of foreign firms. The reason why the total number of firms only depends on the effective entry cost faced by local firms is the following. If cF decreases, profits for foreign firms become positive. New foreign firms enter as result. Since cR remains constant, profit expectations for local firms become negative as they find it more difficult to recruit a worker. The number of local firms goes down until the total number of firms returns to its initial value. Changes in foreign firms’ entry cost cF do not modify the total number of firms, but increase the proportion of foreign firms – applying the implicit function theorem to equations (3.3) and (3.4) shows that dn/dcF = 0 and dρ/dcF < 0. An increase in productivity gap (yF − yR ) /yR has similar effects to a fall in foreign firms’ entry cost cF . It increases the proportion of foreign firms, but does not impact the total number of firms.

3.2.3

Labor share

The total wage bill paid by foreign firms is WF = m (n)2 ρ [ρyF + 2(1 − ρ)yR ]

(3.5)

The wage bill corresponds to workers who receive two offers. This happens with probability m (n)2 . With probability ρ2 the two offers are from foreign firms and the worker receives the totality of output yR . With probability 2ρ(1 − ρ), one of the two offers is from a local firm, and

85

FDI and the labor share in developing countries the worker gets yR . The total wage bill paid by local firms is WR = m (n)2 (1 − ρ)2 yR

(3.6)

Wages correspond to workers who receive two offers from local firms. Total output in foreign firms is YF = m (n) ρ [2 − m (n) ρ] yF

(3.7)

The probability that a worker does not receive a job offer from a foreign firm is (1 − m (n) ρ)2 . Therefore, the probability that a worker receives an offer from such firms is 1 − (1 − m (n) ρ)2 . However, the worker may receive two offers from such firms with probability m (n) 2 ρ2 . But, only one of the firms hires him. Hence, we subtract m (n) 2 ρ2 . The result follows. Similarly, total output in local firms is YR = m (n) (1 − ρ) [2 − m (n) (1 + ρ)] yR

(3.8)

The total wage bill is W = WF + WR , while total output is Y = YF + YR . We obtain   m (n) ρ2 yF + (1 − ρ2 )yR W LS = = Y ρ [2 − m (n) ρ] yF + (1 − ρ) [2 − m (n) (1 + ρ)] yR

3.2.4

(3.9)

Impact of foreign firms on the labor share

In this sub-section, we analyze how the labor share responds to changes in foreign firms’ entry cost. First, entry costs only affect the labor share through effective changes in the proportion of foreign firms. Second, there is a U-shaped relationship between the labor share and the proportion of foreign firms. Finally, multinationals’ opportunity costs of entry limit the effectiveness of openness policies, and may forbid the possibility of reaching the increasing part of the curve. The gap in entry costs paid by foreign and local firms is cF − cR = cO + π. This gap depends on the degree of financial openness, which determines cO , and alternative profit opportunities, which determine π. According to the free-entry conditions (3.3) and (3.4), changes in either one or both of these cost components only lead to changes in the proportion ρ of foreign firms in the total number of firms. Therefore, to capture the impact of a decrease in foreign firms’ entry cost, we only need to

86

3.2. The model differentiate LS given by equation (5.4) with respect to ρ. We obtain: dLS dρ

sign

= −dY /dρ × LS + dW/dρ

sign

= −(1 − ρm (n)) (yF − yR ) LS + ρm (n) (yF − yR ) technological gap effect

(3.10)

wage competition effect

Two opposite forces are involved: The technological gap effect tends to decrease the labor share. An increase in the proportion of foreign firms raises output, as they benefit from better productivity. At given wages, this reduces the labor share. This effect depends on the ability of foreign firms to extract a rent on labor thanks to their better technology. The wage competition effect tends to increase the labor share. An increase in the proportion of foreign firms raises wage competition between them, which increases wages. At given output, this tends to raise the labor share. The impact of foreign firms’ entry cost on the labor share results from the interplay between these two forces. We get: dLS sign 2 = ρ yF − (1 − ρ)2 yR dρ

(3.11)

Hence, dLS/dρ is non-monotonic in ρ. It decreases at first, reaches a minimum, and finally increases. The technological rent effect initially dominates, while it is dominated at a larger proportion of foreign firms. The threshold proportion of foreign firms ρ∗ below (above) which increased financial openness deteriorates (raises) the labor share results from dLS/dρ = 0. We find ρ∗ =

1 1 + (yF /yR )1/2

(3.12)

The pattern of the labor share with respect to the proportion of foreign firms reflects the pattern of productive heterogeneity among firms. The labor share is the same when there are no foreign investors (cF sufficiently large, which implies that ρ = 0), and when output is only produced by foreign firms (cR = cF , which implies that ρ = 1). For these two extreme cases: LS =

m(n) 2 − m(n)

(3.13)

Figure 3.1 depicts the U-shaped relationship between the proportion of foreign firms and the labor share. Reducing foreign firms’ entry costs cR means moving along the curve from the left to the right. By setting institutions that favor foreign investment, Governments can alter the proportion of foreign firms, which affects the labor share. Financial openness has no impact per se: it only

87

FDI and the labor share in developing countries

Figure 3.1: Labor share and proportion of jobs in foreign firms. LS goes from 0 to 1 as cF goes from infinity to cR . The proportion ρ corresponds to cO = 0. affects the labor share to the extent it alters the proportion of foreign firms. This prediction differs from Rodrik-type models in which the labor share decreases with institutional openness. However, financial openness policies cannot arbitrarily attract foreign investors. Those policies are limited by multinational firms’ alternative profits in the rest of the world. Suppose for instance that the entry cost for foreign firms has three components: the cost cR borne by local firms to open a new business, the cost induced by imperfect financial openness cO , and the opportunity cost of entry π. Formally, cF = cR + cO + π. It is important to disentangle costs induced by imperfect financial openness cO from opportunity costs π. Governments can alter the degree of financial openness; however, they cannot reduce profit opportunities in alternative countries. The proportion of foreign firms easily responds to financial openness policies at early stages of financial openness. It is, therefore, easy to go along the decreasing part of the curve. However, opportunity costs of entry limit the ability of openness policies to reach the increasing part of the curve. In Figure 3.1, ρ is the proportion of foreign firms implied by the entry cost cF = cR + π. This constraint may be so tight that ρ is actually lower than ρ∗ . In our empirical analysis, we show that most of the developing countries are actually stuck on the decreasing part of the locus. In line with the current discussion, we argue that this is implied by multinationals’ alternative profit locations.

88

3.2. The model We now turn to various extensions of the basic framework.

3.2.5

Firm heterogeneity

The basic model assumes that national firms and multinational enterprises differ in factor productivity for exogenous reasons. While there is indeed empirical support for a productivity advantage of multinational firms, recent theoretical work focusing on international trade considers compositional effects to be responsible for this outcome (see e.g. Helpman et al, 2004). Put differently, recent work on heterogeneous firms has emphasized that only the best firms engage in foreign investment, implying that multinationals are on average more productive than their foreign competitors. However, the basic model assumes that all national firms are less productive than foreign multinational. In this sub-section, we relax this assumption. We modify our model as follows. A firm may either be a high-productivity firm or a lowproductivity firm. High-productivity firms, whether foreign or local, produce yF , while lowproductivity firms produce yR . Firms do not know ex-ante whether they will turn highly productive or not. Let pi be the proportion of high-productivity firms among the firms of type i, i = F, R. The overall proportion of high-productivity firms is ρe = ρpF + (1 − ρ) pR . Profit functions write 2m (n) pi [(1 − m(n)) yF + m(n)(1 − ρe)(yF − yR )] n 2m (n) + pi (1 − m(n)) yR n

πi = −ci +

(3.14)

In equilibrium, πF = πR = 0, which jointly determines n and ρ. In an interior solution, that is ρ ∈ (0, 1), the proportion of foreign firms strictly decreases with the cost of entry specific to such firms. The labor share now writes   m (n) ρe2 yF + (1 − ρe2 )yR LS = ρe [2 − m (n) ρe] yF + (1 − ρe) [2 − m (n) (1 + ρe)] yR

(3.15)

The only difference comes from the fact that ρe is now the proportion of high-productivity firms rather than the proportion of foreign firms. Following a decrease in foreign firm entry cost, the proportion of foreign firms goes up. That increase in the proportion of foreign firms modifies the labor share of income as follows: dLS ∂LS de ρ ∂LS = = (pF − pR ) dρ ∂ ρe dρ ∂ ρe

89

(3.16)

FDI and the labor share in developing countries The relationship is qualitatively similar as before provided that the proportion of high-productivity firms is larger among the foreign firms than among the local firms. However, there is a non-trivial proportion of high-productivity firms when ρ = 0 and when ρ = 1. Therefore, the relationship between the proportion of foreign firms and the labor share is U-shaped if and only if pR < ρ∗ ≡

1 1 + (yF /yR )1/2

< pF

(3.17)

The proportion of high-productivity firms must be sufficiently low among the local firms, and sufficiently large among the foreign firms. The threshold depends on the technological gap between local and foreign firms. This condition is likely to be satisfied in developing countries, and much less likely in developed economies. When the proportion of high-productivity firms is too large among the local firms, the labor share strictly increases with the proportion of foreign firms. This is so because foreign firms contribute to reducing firm heterogeneity in such a case. Conversely, when the proportion of high-productivity firms is too small among the foreign firms, the labor share strictly decreases with the proportion of foreign firms. Foreign firms always raise firm heterogeneity in such a case.

3.2.6

Accounting for technological transfers

In this sub-section, we introduce technological transfers from foreign to local firms and examine how they alter the relationship between the proportion of foreign firms and the labor share. As far as foreign firms have positive spillover effects on local firms, the technological rent effect tends to decrease with the size of the spillover effect. We assume that output produced by local firms depends on the proportion ρ of foreign firms, i.e. yR = yR (ρ). The spillover may be either positive – in case of technological transfers – or negative – in case foreign firms reduce the ability of local firms to attract local investors, or destroy the network of connections that local firms have7 . A positive spillover has a stabilizing effect. An increase in the proportion of foreign firms reduces the technological gap between foreign and local firms. Foreign firms must pay a higher wage as a result, which reduces the incentives to further invest in the country. A negative spillover has a multiplier effect. An increase in the proportion of foreign firms raises the technological 7

See Blomstr¨ om and Kokko (2003) for a survey of the empirical evidence. They conclude that spillovers of foreign technology and skills to local industry is not an automatic consequence of foreign investment. Harrison and McMillan (2003) for instance show that foreign firms crowd local firms out of domestic capital market in Ivory Coast.

90

3.2. The model gap. Wages go down in foreign firms. This attracts new foreign investors. When this effect is sufficiently strong, there maybe multiple equilibria: equilibria with a large number of foreign firms and low wages, and equilibria with a low number of foreign firms and high wages. As far as there exists a unique equilibrium, a decrease in entry cost cF raises the proportion of foreign firms. We can still study the derivative of the labor share with respect to such a proportion: dLS dρ

sign

= − ∂Y ∂ρ × LS +

∂W ∂ρ

 ∂Y + − ∂y × LS + R

∂W ∂yR



0 (ρ) yR

sign

= −(1 − ρm (n)) (yF − yR ) LS + ρm (n) (yF − yR ) technological gap effect

+(1 −

wage competition effect 0 (ρ) ρ) {m (1 + ρ) − [2 − m (1 + ρ)] LS} yR technological transfer effect

(3.18)

0 (ρ). The sign As LS< m (n) / (2 − m (n)), the technological transfer effect has the sign of yR

as well as the size of the technological transfer effect depends on the sign and magnitude of the spillover. When the spillover is positive, the technological transfer effect tends to reduce the technological gap effect. Conversely, when the spillover effect is negative, the technological transfer effect tends to magnify the technological gap effect. This extension underlines the need to control for the technological differential between foreign and local firms while trying to assess the relationship between the proportion of foreign firms and the labor share.

3.2.7

Accounting for capital choice

The basic model abstracts from capital choice. In this sub-section, we allow firms to set their capital intensity. We also make the difference between foreign and local firms, which face different capital costs and different total factor productivity. Provided that the elasticity of substitution between capital and labor is lower than one, a decrease in foreign firms’ entry cost can raise the labor share by increasing average capital intensity. Let k denote capital intensity, and assume that output is ai y (k), with y (0) = 0, y 0 (k) > 0, and y 00 (k) < 0. The elasticity of output with respect to capital intensity is α (k) ≡ ky 0 (k) /y (k) ∈ (0, 1). Total factor productivity parameters and the rental cost of capital are asymmetric. Local firms face the price rR , while foreign firms face the price rF ≤ rR . To simplify, capital investment is made once the worker is recruited. Capital intensity results from the equality between marginal productivity and marginal cost of capital: ai y 0 (ki ) = ri , i = F, R

91

(3.19)

FDI and the labor share in developing countries This implies that foreign firms are more productive than local firms. The labor share is: 
 m(n) ρ2 (1 − αF ) yF + 1 − ρ2 (1 − αR ) yR LS = ρ [2 − m(n)ρ] yF + (1 − ρ) [2 − m(n)(1 + ρ)] yR

(3.20)

where ai yi = y (ki ), and αi = α (ki ), i = F, R. As rR = rF and aF = aR = α, foreign and local firms are no longer different, and the labor share tends to LS = (1 − α)

m(n) 2 − m(n)

(3.21)

The labor share is composed of two terms, of which the first is the elasticity of output with respect to labor, and the second accounts for monopsony power derived from search frictions. As m (n) → 1, the second term tends to one and we are back to the competitive model. A marginal increase in ρ induced by a marginal decline in cF has the following impacts: dLS sign = −(1 − ρm (n)) (yF − yR ) LS + ρm (n) [(1 − αF ) yF − (1 − αR ) yR ] dρ technological gap effect wage competition effect

(3.22)

The wage competition effect now depends on the competitive wage differential (1 − αF ) yF − (1 − αR ) yR , rather than on the output differential yF − yR . Given that kF > kR , we have αR > αF whenever the elasticity of substitution between capital and labor is lower than one. The wage competition effect is magnified when capital and labor are complementary. This point has important implications for the empirical analysis. In the empirical part of the paper (next section), changes in ρ are captured by changes in FDI stock to GDP ratio. This means that changes in ρ and changes in total capital held by foreign firms are observationally equivalent. This may induce a spurious positive impact of FDI stock to GDP ratio on the labor share: an increase in such a ratio may simply raise aggregate capital intensity. It follows that one must control for changes in aggregate capital intensity while trying to find an empirical relationship between the proportion of foreign firms and the labor share. In the empirical part of the paper, regressions include a proxy for capital intensity.

3.2.8

From the theory to empirical analysis

The theoretical model explains the labor share of income as a function of exogenous parameters, among which the degree of financial openness, foreign firms’ opportunity cost of entry, and the cost to set up jobs. However, these parameters only affect the labor share because they have an impact on endogenous variables like the vacancy/unemployment ratio, or the proportion of jobs in foreign firms. Formally, the labor share is a function LS(ρ, m (n) , k, Γ) where Γ is a set

92

3.3. Empirical analysis of exogenous parameters. Our empirical analysis consists in estimating a linearized version of this equation, allowing for a quadratic impact of the variable ρ.

3.3

Empirical analysis

This section examines the relationship between the size of economic activity due to foreign firms and the labor share. We use panel data covering developing countries. Fixed effects estimations show that the stock of inward FDI to GDP has a non-monotonic impact on the labor share: decreasing at first, and then increasing. The threshold above which the labor share starts increasing with FDI is in the range 150-180%. Most of the countries are stuck in the decreasing part of the curve. This relationship appears robust to the consideration of outliers, to endogeneity and autocorrelation problems, and to the introduction of globalization variables. The other determinants of the labor share are in line with the theoretical model, especially the technological gap (-), unemployment rate (-), and capital intensity (weakly +).

3.3.1

Data

The data set covers 94 developing countries over the period 1980-2000. We consider all available countries whose GDP per capita was lower than 60% that of the US in 1980.8 This threshold allows us to consider a large variety of countries, from very poor countries that received very few FDI to high-growth countries that received enormous amounts of FDI. In sub-section 3.3.3, we consider alternative development threshold to define the set of developing countries. Our preferred estimates are performed on yearly data to keep the maximum number of observations. The number of observations depends on the number of variables included in the regression. The basic regression with country fixed effects, FDI variables and a proxy for the technological gap is run over 1189 observations. Adding controls and instrumenting some of the explicative variables lower the number of observations according to data availability. Data sources are detailed in the Appendix. The dependent variable is the labor share. Following Daudey (2003) and Ortega and Rodriguez (2006), we compute it from the UNIDO dataset INDSTAT3. This dataset only covers the manufacturing sector. The data are collected through a survey in more than 180 countries and cover a period from 1963 to 2003 (with gaps). There are three reasons why we use the UNIDO dataset. First, UNIDO harmonizes data definitions and computations across countries. Second, this dataset allows to abstract from changes in the sectorial composition of output. Third, the 8

If there is no observation in 1980, we consider the closest year available.

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FDI and the labor share in developing countries UNIDO dataset reduces the measurement problems associated with self-employment9 . There is a minimum level of activity that eliminates most self-employed and small-family firms from the sample. The main drawback of the dataset is that wages do not include employers’ contributions. This tends to underestimate the labor shares. This problem is not very serious for our purpose, because we do not proceed to international comparisons. All our estimates include country fixed effects. Fixed effects models use within country variations to estimate the desired parameters. However, there may be changes over time in the labor shares that are only driven by changes in employers’ contribution rates. Part of these changes will be captured by time dummies and by a variable that is highly correlated to GDP per capita. The key explicative variable is the proportion of foreign firms. We use two different proxies: the ratio of (inward) FDI stock to GDP (FDI/Y), and the ratio of FDI stock to total capital stock (FDI/K). The former ratio is available from UNCTAD for 200 countries over the period 1980-2005. The latter ratio is computed from UNCTAD data on FDI stock and from Klenow and Rodriguez-Clare (2005) for the capital stock.10 FDI refers to equity participation over 10%. Such investments indicate that foreign investors play an active role in the management of the firm. These firms are more likely to benefit from technological advance. Of course, other firms may also benefit from foreign investment. The presumption here is that the percentage of jobs concerned by our analysis is highly correlated with the ratio of FDI stock to GDP and/or the ratio of FDI stock to capital. Stocks are computed from the historical record of FDI inflows given by the balance of payments. Capital account data have been criticized on the ground that they fail to account for the valuation effect11 . We also use data on FDI stocks provided by Lane and Milesi-Ferretti (2006) – LMF –, which correct for the valuation effect. These data are available over the longer period 1970-2005 and allow us to test the robustness of our results. The theoretical model suggests that the impact of FDI on the labor share depends on the technological gap TG= (yF − yR ) /yF between the host economy which receives FDI and the home-based transnational firm. Unfortunately, there are no time-varying statistics for the mean productivity differential yR /yF between local and foreign firms. As a proxy for this variable, 9

The labor share is the ratio of wage bill to value-added. The self-employed contribute to the denominator, but typically do not appear in the denominator. There are several ways to ascribe a fictious wage to the self-employed (see Bernanke and G¨ urkayanak, 2001, and Gollin, 2002). These methods require strong assumptions on such a wage, as well as data on self-employment. Focusing on the manufacturing sector does not require the gross wage bill to output ratio to be manipulated. 10 Initial values for the capital stock and the FDI stock have not been computed in the same way. This explains why the ratio FDI/K can be larger than one. 11 When a country is indebted in foreign money (dollars), changes in parity alter the debt level. This phenomenon is very large for the US.

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3.3. Empirical analysis we use the ratio of local GDP per capita to US GDP per capita, both measured at purchasing power parity. The technological gap variable is measured accordingly by one minus the latter ratio. The idea behind this proxy is that foreign firms are close to the productivity frontier, and the US GDP per capita broadly captures this frontier. Of course, the proxy is not perfect as GDP per capita not only depends on total factor productivity and capital intensity, but also on the skill level of the workforce. Average skills are much higher in developed countries than in developing countries, so that GDP per capita may overstate the productivity advantage of multinational firms.12 The labor share also depends on the matching probability m (n). This probability shapes workers’ ability to generate wage competition for their services. This probability is not available as such. However, we use the following property of our model. The probability of staying unemployed coincides with the unemployment rate. It is equal to UNR= (1 − m (n))2 . Therefore, we use the unemployment rate as a proxy for (one minus) the matching probability. This variable is available for a limited number of years and countries. Finally, we must separate the impact of FDI from changes in overall capital intensity as indicated in subsection 2.7. We consider the ratio of capital stock to output K/Y rather than the ratio of capital stock to labor. The former ratio is governed by changes in the ratio of capital stock to effective units of labor. Unfortunately, the UNIDO dataset does not allow us to compute a reliable capital stock series – in many cases, the number of observations is clearly insufficient. Therefore, we use the ratio I/Y of investment to value added. We perform sensitivity regressions with the overall capital to output ratio. Some regressions include a measure of trade openness (OPENT, the usual openness degree, that is the ratio of imports plus exports to GDP), a measure of de jure capital account openness (OPENK) (the composite index constructed by Chinn and Ito, 2007), a dummy variable (CRISIS) that takes the value 1 when the nominal exchange rate depreciates by more than 25%. Table 3.1 displays descriptive statistics for the core variables. There is substantial variation in the dataset: the standard deviation in the labor share variable accounts for half of the mean value. There is more volatility in the cross-section dimension than in the time dimension. However, the mean standard deviation within country is sufficiently large to apply panel data analysis.

12

Using data for total factor productivity would not be satisfying. Multinational firms benefit from both higher TFP and better access to the capital market. One solution would be to extract the contribution of education to GDP per worker, and consider the resulting productivity residual as a proxy for the mean local technological level.

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FDI and the labor share in developing countries

Table 3.1: Descriptive statistics

Table 3.1 bis: Descriptive statistics Variable LS

Mean

Stand dev

Min

Max

Obs

33.69

14.19

2.23

85.33

N = 1203

Between

12.55

12.99

71.03

n = 98

Within

7.12

3.63

83.90

T = 12.27

34.69

0.0000261

283.60

N = 1203

Between

25.92

0.14

165.75

n = 98

Within

18.48

-68.07

193.71

T = 12.27

Overall

FDI/GDP (FDI/Y, UNCTAD)

Overall

21.27

For sources and/or calculations see Appendix.

3.3.2

Core regressions

Let i denote the country and t the period. We aim to estimate the following fixed effects model: LSit = a0i + a1t + a2 FDI/Yit + a3 (FDI/Yit )2 + a4 TGit + a5 UNRit + a6 K/Yit + εit

96

(3.23)

3.3. Empirical analysis where a0i is the country fixed effect, and a1t is a period dummy. The error term εit is supposed serially uncorrelated. The validation of our model requires that a2 < 0, a3 > 0, a4 < 0, a5 < 0. This statistical model assumes that the different regressors have the same impact in each country. In particular, the relationship between financial openness and the labor share must be the same throughout the sample. This prediction differs somewhat from the theoretical model, whereby the magnitude of the relationship depends on output gap. We also present regressions in which the variable FDI/Y is replaced by the interaction term FDI/Y×TG. Table 3.2 depicts our main results. Each column is associated with a particular specification. In column a, we estimate the relationship without controlling for capital intensity (this assumes a Cobb-Douglas technology), unemployment rate and time dummies. In column b, we add time dummies. In column c, we include capital intensity (this allows for CES technologies for instance). In column d, we add the unemployment rate – and lose half the observations. In columns e and f, we replace the regressor FDI/Y by an interaction term between FDI/Y and technological gap. In columns b to f, regressors are one-period lagged. This allows for potential contemporeanous correlation between the regressors and the error term to be controlled. Squared errors are robust to arbitrary heteroskedasticity between countries. The results can be commented along five dimensions. First, the estimations validate the existence of a U-shaped relationship between FDI/Y and the labor share. The coefficient associated with FDI/Y is negative, while the coefficient associated with (FDI/Y)2 is positive. This relationship is robust to country fixed effects, time dummies, and to our different control variables. FDI has two opposite effects on the labor share, in line with our theoretical model. Our estimates also imply that the threshold above which an increase in FDI stock to GDP starts increasing the labor share is very high. This threshold can
be computed as follows: −a2 / 2a3 . It varies between 150% and 180%. This is far above the mean ratio in developing countries. Second, the quantitative impact of FDI is substantially large. Consider a country that is characterized by the mean value of FDI/Y (given by Table 3.1) and experiences an increase of one standard deviation in this ratio, everything else being equal. Estimates in columns a to d imply a fall in the labor share that varies between 3.0 to 7 points. This impact amounts to between 9% to 21% of the mean labor share of our sample. Third, the two other variables that our model emphasizes have the predicted negative impact. In columns a to d, the technological gap (TG) has a negative sign, in line with the argument whereby foreign firms use their technological advance to derive extra rents on the labor market. Consider a country that experiences a decline in technological gap of one standard deviation.

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FDI and the labor share in developing countries

Table 3.2: Fixed effects regressions

The labor share should increase by 1.5 to 5.5 points. Note, however, that TG is highly correlated to GDP per capita, which means that TG captures a variety of factors that are embodied in GDP per capita. The unemployment rate (UNR) has a strong negative impact on the labor share. Fourth, the parameter associated with capital intensity (K/Y) has a positive sign – though it is not always significant. This indicates that the elasticity of substitution between capital and labor is lower than one. The fact that capital and labor are complementary in output is not controversial, at least in developing countries (see for instance Duffy and Papageorgiou, 2000). Fifth, Table 3.2 displays strong interaction effects between FDI/Y and TG. Columns e and f show that TG loses significance and impact once we replace the regressor FDI/Y by the interaction term FDI/Y×TG, and the regressor (FDI/Y)2 by (FDI/Y)2 ×TG. This has two implications. On the one hand, the technological gap mainly affects the labor share through magnifying the effects of FDI/Y. This is in line with the theoretical model and strengthens the view according to which the technological gap variable is more than a simple proxy for time-

98

3.3. Empirical analysis varying country-specific features that are correlated with GDP per capita. On the other hand, the magnitude of the relationship between FDI and the labor share is conditional on TG. The higher the technological gap, the larger the impact of foreign firms on the labor share. These estimates do not invalidate the magnitude of the effects reported in columns a to d. For instance, consider a country characterized by the mean technological gap and the mean ratio FDI/Y, and assume that this country experiences an increase in FDI/Y of one standard deviation. According to columns e and f, this would reduce the labor share by 9 to 10 points.

3.3.3

Understanding the results

In this sub-section, we check the robustness of the relationship between FDI stock to GDP and the labor share. There are three main reasons why this statistical relationship may be spurious: existence of outliers, endogeneity and autocorrelation biases, and omitted globalization variables causing both FDI and the labor share. We first start with outliers. Figure 3.2 plots the partial relationship between the labor share and the ratio of FDI stock to GDP. This displays two main features. First, there are some outliers, but they do not seem to drive the global negative impact of FDI.13 Second, Figure 3.2 visually confirms that most of the sample is below the threshold. The flat and increasing parts of the curve are due to a very few countries. The countries that drive the positive part of the curve are Hong-Kong, Ireland, Macao, and Singapore. These countries have two characteristics: they have experienced impressive growth rates over the period, and they have attracted enormous amounts of FDI. These two features are related. High growth rates imply high profit opportunities for the multinationals and foreign investors in general. In terms of our model, the effective cost of entry cF is very low in these countries, not only because of financial openness cO , but also because alternative profits π are relatively low. Conversely, effective costs of entry are very large in the other countries despite financial openness, because opportunity costs of entry are very high. Put otherwise, FDI lowers the labor shares throughout the developing world because most of the FDI has been captured by booming countries in East-Asia and Europe. In terms of economic policy, multinationals’ opportunity cost of entry limits the effectiveness of policies designed to attract FDI. To confirm that view, we run the regressions over various alterations of the initial sample. Table 3.3 displays the results. We first compute the empirical distribution of percentage change in LS (∆LSit /LSit ). Then, we omit the observations belonging to the top 1 and top 2 percentile of this distribution, and run fixed effects regressions. The results are reported in columns a and b. 13

Figure 3.2 shows one observation that is an obvious outlier: El Salvador in 1997, when the labor share goes from 26 to 81 before going back to 31.

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FDI and the labor share in developing countries

Figure 3.2: Partial relationship between labor share and FDI stock to GDP. Countryspecific controls are TG, I/Y, time effects, and country fixed effects. The magnitude of the relationship between FDI/Y and LS is almost unchanged. Columns c and d omit observations where the FDI stock to GDP is larger than 100% and 75% respectively14 . As expected, the negative coefficient associated to FDI/Y is much stronger, while the positive coefficient associated to (FDI/Y)2 is less significant. Column e restricts the sample to countries whose GDP per capita was lower than 50% that of the US in 1980. The results are close to the initial estimates. We then discuss endogeneity and autocorrelation biases. Endogeneity may arise for two reasons. On the one hand, the regressors may be correlated with the error terms in the fixed effects model. The explicative variables and the labor share are general equilibrium variables. As such, they may be affected by correlated shocks, generating a statistical bias in the fixed effects estimator. Regressions displayed in Table 3.2 and Table 3.3 address this potential endogeneity bias by considering lagged regressors. This method is 14

We have also run regressions omitting the countries where such extreme changes have occured. The results are very close.

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3.3. Empirical analysis

Table 3.3: In search for outliers

based on the idea that the regressors are strongly autoregressive, so that we do not lose too much information. The main advantage is that we do not lose many observations, and we do not bias the sample towards richer countries. On the other hand, the labor share may directly alter FDI incentives for reasons that our model leaves aside. For instance, a high labor share may mean a good social climate, which lowers investment risk and attracts foreign investors. If this relationship were true, the negative impact of FDI would be underestimated, while the increasing part of the curve would reflect the causal effect of the labor share on FDI. This type of bias cannot be addressed by lagging the regressors, because the lagged regressors would also be correlated with the error terms. Autocorrelation is a serious problem with panel data. Table 3.2 accounts for heteroskedasticity, but not for autocorrelation. Dealing with autocorrelation requires us to add the lagged labor share to the set of regressors. However, the fixed-effect estimator is biased in finite samples because the residuals are correlated with the new regressor. The size of the bias is typically magnified in small-T-large-N panel datasets such as ours. To address these two sources of bias, we use the system-GMM estimator due to Blundell and

101

FDI and the labor share in developing countries Bond (1998). This estimator proves to be more stable vis-`a-vis sample and instrument alterations than the Arellano-Bond difference estimator. Formally, the model is written as follows:

∆LSit = a1 ∆LSit−1 + a2 ∆FDI/Yit + a3 ∆ (FDI/Yit )2 + a4 ∆TGit +a6 ∆K/Yit + ∆εit LSit

(3.24) 2

= a1 LSit−1 + a2 FDI/Yit + a3 (FDI/Yit ) + a4 TGit + a6 K/Yit + εit

where all the variables have been centered in their period mean to account for common period shocks. The model has two components: the difference and level submodels. In both components, the lagged dependent variable is correlated with the error terms and must be instrumented. In addition, FDI terms may also be weakly exogenous, which also requires an instrumenting strategy. In the absence of good instruments, the set of instruments only contains lagged endogenous regressors and exogenous variables. In the difference submodel, the differenced lagged labor share is instrumented by past levels of the labor share (from LSit−2 ), while the lagged labor share is instrumented by past differences of the labor share in the level submodel (from ∆LSit−1 ). This generates a large number of instruments in GMM-style. The set of instruments is finally reduced by collapsing the matrix of GMM-style instruments15 . The model is estimated by two-step GMM, while reported squared errors feature Windmeijer correction. This method corrects for individual heteroskedasticity, arbitrary patterns of autocorrelation within individuals, and downward squared-error bias in finite sample. Table 3.4 reports the results. In columns a to d, FDI/Y and (FDI/Y)2 are presumed weakly exogenous, i.e. FDI/Yit is correlated with εit . The regressors ∆FDI/Yit and ∆ (FDI/Yit )2 are
2 instrumented by FDI/Yit−2 and FDI/Yit−2 in the difference equation, while the regressors
2 FDI/Yit and (FDI/Yit )2 are instrumented by ∆FDI/Yit−1 and ∆ FDI/Yit−1 in the level equation. In columns e and f, FDI/Y and (FDI/Y)2 are presumed predetermined. The various regressors containing FDI/Yit are replaced by their first lags – like in the fixed effects regressions. However, they may be correlated with εit−1 , and still need to be instrumented (for the same reason LSit−1 needs to be instrumented). The instruments are the same as in the case where FDI/Yit and (FDI/Yit )2 are weakly exogenous. The various columns differ in the number of lags that we consider for the various endogenous variables. The number of instruments goes from 69 to 12. Clearly, 69 is too much with respect to the number of countries, 61. Column g displays the results of a standard fixed effects regression, 15

The number of instruments increases with the time index of each observation. The total number of instruments is quadratic in the number of periods as a result. Collapsing allows such a number to be reduced, while exploiting the same information displayed by the dataset (see Roodman, 2006).

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3.3. Empirical analysis

Table 3.4: Accounting for endogeneity and autocorrelation

where we restrict the sample to the one effectively used by system-GMM estimations. The results are remarkably consistent across the various system-GMM estimations. Parameter a1 is about 0.60, which is lower than a unit root, but sufficiently high to prefer the system-GMM estimator rather than the difference estimator. Specification tests like the Sargan and Hansen tests of overidentifying restrictions, and the Arellano-Bover test of second-order autocorrelation, suggest that the model is well specified most of the times. This leads us to prefer the estimates with the smallest number of instruments, and in particular the one where FDI/Y and FDI/Y2 are predetermined16 . The estimated relationship between LS and FDI/Y 16

Column f shows that the P-value of the Hansen test of overidentifying restrictions is 0.645. This is

103

FDI and the labor share in developing countries is qualitatively similar to the one displayed by Table 3.2. Quantitatively, the magnitude of the parameters associated to FDI variables is in the range 50-75% of the initial one. This may receive three intrepretations. First, we lose more than 60 observations, and selection bias may lead to a different estimation. Our model predicts that the threshold and the magnitude of the relationship should be governed by the technological gap. If the selected sample is richer than the initial sample, FDI have a smaller effect on the labor share as the typical productivity differential between foreign and local firms is lower. The fixed effects regression shows that the relationship between FDI/Y and LS is marginally smaller than the initial one. Second, endogeneity affects both the decreasing and increasing parts of the curve. Once purged of endogeneity bias, the true relationship proves to be more modest by 10-40%. Third, the statistical method itself may weaken the relationship. For those reasons, we interpret the GMM findings as a lower bound on the magnitude of the true relationship between FDI and the labor share. We now discuss other globalization variables. They have received some attention in the recent past, and they may be correlated with both FDI and the labor share. Table 3.5 introduces a new set of regressors that deal with these various aspects of globalization: institutional financial openness, international trade, and, following Diwan (2000, 2002), exchange rate crises. Table 3.5 shows that globalization variables do not affect the relationship between FDI and the labor share. In particular, institutional financial openness does not lower the labor share. The variable OPENK is the Chinn and Ito (2006) index of financial openness. Other studies (see Harrison, 2002, Ortega and Rodriguez, 2002, Lee and Jayadev, 2005) point out that capital account openness can deteriorate the labor share through increased capital mobility, thereby improving the bargaining position of capital owners. In line with such a theory, they report positive impacts of capital controls. Our model suggests that such effects of capital openness should disappear once we account for actual changes in foreign capital stocks. Indeed, column b displays a positive coefficient for the index of capital openness. Our model does not predict anything regarding trade flows. However, trade flows are associated to multinationals. Therefore, it is difficult to disentangle the impact of trade from the impact of foreign firms. Harrison (2002) and Ortega and Rodriguez (2002) estimate a negative effect of trade on the labor share in developing countries. However, Harrison considers FDI flows (rather than stocks as we do), and Ortega and Rodriguez do not control for FDI variables. Table 3.5 displays a non-significant parameter. Finally, we consider several alterations in the main explicative variable, i.e. the ratio of FDI stock to GDP. In Table 3.6 column a reproduces our benchmark regression: FDI stock is from obtained with a remarkably low number of instruments, which suggests that this value does not suffer from upward bias.

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3.3. Empirical analysis

Table 3.5: Globalization

UNCTAD, and it is divided by GDP. In column b, FDI stock is from Lane and Milesi-Ferretti (2007) – hereafter LMF. In column c and d, the two FDI stock variables are divided by the total capital stock rather than GDP. Columns e to h introduce the unemployment rate among the regressors.

Results are qualitatively unchanged: all the different parameters have the same sign and significance.

105

FDI and the labor share in developing countries

Table 3.6: Changes in FDI variable

3.4

Conclusion

This paper addresses the impact of FDI on the labor share of income in developing countries. We build on the idea that FDI increases productive heterogeneity within firms acting in the host country. Foreign firms are more productive, and, in a frictional labor market, only need to pay slightly more than local competitors to attract workers. This explains why the labor share falls with FDI. At some point, the magnitude of foreign firms in host activity may become so large that productive heterogeneity starts going down. The labor share would then increase with FDI. The paper offers a search-theoretic model that allows these two effects to be discussed, and tests the main predictions on aggregate data through fixed effect and system-GMM estimations.

106

3.4. Conclusion Policy implications of our work are non-ambiguous. The average wage always increases with financial openness, whether the labor share increases or not. Workers’ welfare improves as a result. In addition, the negative effects of FDI decline with FDI stock to GDP ratio. The largest effects of FDI on the labor share arise at early stages of financial openness. Such negative effects should not be considered at the time of evaluating the impact of a further increase in financial openness, unless one is willing to considerably overestimate them. We point out a negative relationship between productive heterogeneity and the labor share of income. This relationship naturally arises in the context of globalization where modern firms can meet technologically obsolete and under-equipped competitors. However, this also happens in times of rapid technological change with emerging industries. We leave this extrapolation of our paper to future work. APPENDIX • CRISIS: Exchange rate crisis. Dummy equal to one if the percentage increase in nominal exchange rate is larger than 25%. The exchange rate is measured at the end of the year. Source: IMF • FDI/Y = Ratio of Foreign Direct Investment stock to GDP Source: UNCTAD and Lane and Milesi-Ferretti (2007) for FDI Data available at http://www.imf.org/external/pubs/ft/wp/2006/data/wp0669.zip • FDI/K = Ratio of Foreign Direct Investment stock to total capital stock Source: UNCTAD and Lane and Milesi-Ferretti (2007) for FDI Data available at http://www.imf.org/external/pubs/ft/wp/2006/data/wp0669.zip Source: Klenow and Rodriguez-Clare (2005) for the capital stock • I/Y = Ratio of Investment to value-added in the manufacturing sector Source: UNIDO industrial statistics database INDSTAT3 2005 ISIC Rev.2 Values lower than 0 have been omitted from the sample • K/Y = Ratio of total capital stock to total GDP Source: Klenow and Rodriguez-Clare (2005) • LS: Labor share = Ratio of wages and salaries to value added (×100) Source: UNIDO industrial statistics database INDSTAT3 2005 ISIC Rev.2

107

FDI and the labor share in developing countries • OPENK: Chinn and Ito financial openness index. Composite index varying between 2.62 (very open) and -1.75 (close). It is based on four dummy variables reflecting the four major categories on the restrictions on external accounts: presence of multiple exchange rates, restrictions on current account transactions, restrictions on capital account transactions, requirement of the surrender of export proceed. Source: Chinn and Ito (2007) Data available at http://www.ssc.wisc.edu/˜mchinn/kaopen 2006.xls • OPENT = Ratio of total exports and imports to GDP Source: World bank. World Development Indicators 2005 • TG: Technological gap = One - percentage gap between local GDP (PPP) per capita and US GDP per capita (×100) Source: World bank. World Development Indicators 2005 • UNR: Unemployment rate = Ratio of unemployed workers to total labor force Source: World bank. World Development Indicators 2005 • List of the developing countries: Algeria, Argentina, Bangladesh, Barbados, Belize, Bolivia, Botswana, Brazil, Bulgaria, Burkina-Faso, Burundi, Cameroon, Central African Republic, Chile, China, China (Hong Kong), China (Macao), Colombia, Congo, Costa Rica, Cote d’Ivoire, Croatia, Cyprus, Dominican Republic, Ecuador, Egypt, El Salvador, Eritrea, Ethiopia, Fiji, Gabon, Gambia, Ghana, Guatemala, Honduras, Hungary, India, Indonesia, Iran, Ireland, Israel, Jamaica, Jordan, Kenya, Korea, Latvia, Lesotho, Madagascar, Malawi, Malaysia, Malta, Mauritius, Mexico, Mongolia, Morocco, Namibia, Nepal, Nicaragua, Niger, Nigeria, Oman, Pakistan, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Romania, Russian Federation, Rwanda, Senegal, Sierra Leone, Singapore, Slovakia, Slovenia, South Africa, Spain, Sri Lanka, Swaziland, Syrian Arab Republic, Tanzania, Thailand, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Uganda, Uruguay, Venezuela, Zambia, Zimbabwe • List of the developed countries: Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Iceland, Italy, Japan, Kuwait, Netherlands, New Zealand, Norway, Sweden, United Kingdom, United States of America

108

Chapter 4 Who bears the cost of currency crises? Summary: This chapter identifies which of the two factors, namely labour and capital, bears the cost of currency crises and for what reasons. It analyzes two main types of effects that currency crises may have on the labour share: within sector effects and across sector effects. We build a descriptive model with a tradable sector and a non-tradable one which differ in their factor intensities. Labour market is characterized by search frictions and goods market by shadow entry costs. Our model describes two sectoral reallocation effects resulting from exchange rate depreciation and capital outflows. These two sectoral effects can move in opposite directions, depending on whether the tradable sector is capital or labour intensive. Our model also highlights that crises erode the bargaining power of workers so that within sectors, crises lower the labour share. We also perform estimations on manufacturing sectoral panel data for 20 countries which have experienced currency crises. The empirical analysis concludes that currency crises lower the aggregate manufacturing labour share by 2 points on average and that this decline is not explained by reallocations across manufacturing sectors.1

1

Ce chapitre est issu d’un travail co´ecrit avec Elsa Orgiazzi.

109

Who bears the cost of currency crises?

4.1

Introduction

The consequences of financial crises on macroeconomic variables such as output, investment or unemployment are relatively well understood by economists (see, for instance, Reinhart and Rogoff (2009), Hutchison and Noy (2005) or Gupta et al. (2007)). Recently, empirical analyses have also started to address the question of whether crises have an impact on distributional variables. Crises have been found to increase poverty and to make the personal distribution of income more unequal (see Baldacci et al. (2002) and Galbraith and Lu (2009)). Surprisingly, the question of how financial crises impact the factor distribution of income has received little attention. The effect on the capital and labour shares is particularly important given that crises lead to output losses, and hence examining changes in factor shares helps us to understand which of the two factors bears the cost of the crisis, and for what reasons. The notable exception is Diwan (2001) and Diwan (2002) who finds that the aggregate labour share falls sharply after a financial crisis. Diwan argues that the reason for this is that the high mobility of capital during crises reduces the bargaining power of workers and hence the labour share. However, there is an alternative hypothesis. The exchange rate depreciation that characterizes a crisis tends to induce reallocations across sectors which can differ in their labour share. If sectoral labour shares differ, this reallocation will result in changes in the aggregate labour share even if sectoral ones remain constant. That is, changes in the aggregate labour share may be simply due to changes in the weight of different sectors in aggregate output. This paper presents a two-sector model which highlights these two different effects and uses sectoral panel data to discriminate between them. Over the last decade there has been a revival of interest in the evolution and the determinants of the labour share, largely driven by the fact that in the last decades of the 20th century it declined sharply in a number of countries, as documented, for example, by Blanchard (1997), Poterba (1999), and Harrison (2002).2 The distributional effects can be important since, because capital income is more concentrated than labour income, reductions in the labour share result in higher personal income inequality; see Daudey Garc´ıa-Pe˜ nalosa (2007) and Checchi and Garc´ıaPe˜ nalosa (2008) and Checchi and Garc´ıa-Pe˜ nalosa (2009). The consequences can be even more dramatic in developing countries where capital is largely held by foreigners. Several possible determinants of the labour share have been examined by the literature. Blanchard and Giavazzi (2003) emphasize the role of product and labour market deregulations, while Blanchard (1997) and Acemoglu (2003) highlight the role of capital-biased technological 2

Note, however, that this variable was of major interest for classical economists. Kaldor (1955) argued that the evidence indicated that factor shares were constant over time, although some of his contemporaries were suspicious about this presupposed constancy; see Solow (1958) and Kravis (1959).

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4.1. Introduction change. Bentolila and Saint-Paul (2003) argue that movements in the labour share can be decomposed into three types of effects: changes in factor inputs (notably in the capital-output ratio), shifts in the relative demands of capital and labour (due, for instance, to biased technological progress), and movements off the relative demand schedule caused, for example, by changes in union bargaining power or labour adjustment cost. A question that has received substantial attention has been the impact of openness on factor shares, since the decline in labour shares has, to a large extent, coincided with a period of increasing trade in goods and assets. Following Rodrik (1997) and Rodrik (1998), this literature maintains that globalization has eroded the bargaining power of labour since the current wave of globalization is characterised by a greater mobility of capital relatively to labour, which increases the outside options of the former and hence its bargaining power. Ortega and Rodriguez (2002) focus on trade liberalization, and find a negative correlation between liberalization and the labour share. Harrison (2002) develops a model whereby financial globalization increases the relative bargaining power of capital and her empirical analysis finds that financial and trade openness are associated with a lower labour share. Jayadev (2007) shows, using panel data, that capital account openness has a negative impact on the labour share. Diwan (2001, 2002) has examined the impact of financial crises3 on the factor income distribution. He uses aggregate UN data and defines a financial crisis as a depreciation of the nominal exchange rate of at least 25%, a criterion inspired by Frankel and Rose (1996).4 His results indicate that the labour share falls sharply after a financial crisis and recovers partially some time latter. There are two major drawbacks of Diwan’s analysis. The first concerns his definition of crisis, since a nominal exchange rate depreciation could simply reflect high inflation episodes. Moreover, his criterion does not take into account the level of reserves and thus the fact that central banks can fight speculative attacks on foreign exchange markets. In fact, foreign investors can flee, anticipating a devaluation which finally does not occur, or attempt a speculative attack without success. In this case, currency market turbulences are not reflected by exchange rate variations but by the levels of reserves. In this paper we use a more suitable definition of currency crisis, as will be defined below, following Kaminsky and Reinhart (1999) or Hutchison and Noy (2006). The second question raised by Diwan’s analysis is what causes the reduction in the labour share. He argues that capital mobility shifts the balance of power in favour of capital, in line with the literature examining the relationship between globalization 3

Financial liberalization has given rise to a higher frequency of financial crises episodes, as shown for instance by Kaminsky and Reinhart (1999), Demirguc-Kent and Detragiache (1998) or Diaz-Alejandro (1985) 4 Frankel and Rose (1996) define a currency crisis as a nominal depreciation of at least 25% during the year as long as this represents an increase in the rate of depreciation of at least a 10%.

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Who bears the cost of currency crises? and the labour share. Yet, reductions in the labour share could simply reflect a reallocation of output across sectors with different factor shares. In order to assess the role of these competing explanations, this paper will use sectoral data to distinguish amongst the different mechanisms through which crises can affect factor shares. To examine the various channels, we construct a model based on Dutt et al (2008) who study the impact of trade on unemployment. We modify their model to focus on the impact of financial crises on the labour share, and assume that there is a tradable sector and a non-tradable one which differ in their capital intensity. The product market is characterized by shadow entry costs which imply that firms make ’super profits’, while the labour market is characterized by search frictions. The combination of shadow entry costs and search frictions implies that workers are not paid their marginal product. As a result, wages depart from the marginal product of labour and movements in wages can lead to labour share changes. The model highlights two types of sectoral reallocation effects induced by the crisis, driven, respectively, by the exchange rate depreciation and by the reduction in the capital stock that characterize financial crises. The effect occurring through the exchange rate works as follows: the exchange rate depreciation induces factor flows to the tradable sector and an increase in the sector’s output share, implying that the aggregate labour share decreases (increases) if the tradable sector is more capital (labour) intensive that the non-tradable one. The impact of a reduction in the aggregate capital stock implies aggregate factor reallocations from the capital intensive to the labour intensive sector, and tends to increase the labour share. Consequently, depending on whether the tradable sector is capital or labour intensive, the two reallocation effects may move in opposite directions. The second type of effect examined by the model describes the impact of currency crises on the labour share within sectors. It echoes Diwan’s argument that the high mobility of capital during crises hurts labour in the bargaining process due to the fact that outside opportunities of capital are ”global” whereas those of labour are only ”local”. The resulting loss of labour’s bargaining power leads to a decrease in the labour share within sectors. Note that the overall impact of crises on the labour share is in principle ambiguous, with two of the three effects just described tending to reduce it if the tradable sector is labour intensive, and one of them tending to increase it. We next turn to the data to examine the relationship between currency crises and the labour share, using manufacturing sectoral panel data. Our empirical analysis has three goals. The first one is to see whether the negative correlation between crises and the labour share still holds when we use more suitable data than Diwan, notably when we consider the labour share in manufacturing and adopt a different currency crisis criterion. To do that, we compute the labour share from UNIDO sectoral data, and use the panel dataset of Kaminsky (2006) to

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4.1. Introduction identify currency crises. Currency crises are defined according to the index of Kaminsky and Reinhart (1999). The index is a weighted average of the rate of change of the real exchange rate and of reserves, with weights such that the two components of the index have equal sample volatilities.5 Our second aim is to understand to what extent changes in the overall labour share in manufacturing are due to within sector effects or to across sector effects. Lastly, we examine whether the impact of currency crises on the factor income distribution is the same for all kinds of currency crises.6 Following Kaminsky (2006) we distinguish several types of crises: crises linked to current account deterioration, fiscal imbalances, financial excess, foreign debt unsustainability, sudden stop, and self-fulfilling crises. We find that currency crises are associated with a reduction in the aggregate manufacturing labour share and that this decrease reflects a decrease within manufacturing sectors, which suggests a fall in the bargaining power of workers in this context of currency market turbulence. This conclusion is in line with the theories pointing out that openness and financial crises hurt labour, see Rodrik (1997), Jayadev (2007) or Diwan (2001, 2002). We also show that this decrease hides large disparities across the different types of crises since our results indicate that some of them actually lead to an increase in the labour share. The rest of the paper is organized as follows. Section 2 presents the theoretical model which allows us to examine the different channels through which currency crises can impact the labour share. Section 3 undertakes the empirical analysis of the link between currency crises and the labour share. Section 4 concludes. σe ∆R Formally the index is : I = ∆e e − σR R . where σe is the standard deviation of the exchange rate and σR the one of reserves. σe /σR stands for the weights of the average and allows the index I to be such that its two components have equal volatilities. When the index takes a value greater than three standard deviation above the mean (on monthly data), the observation is considered as a crisis observation. To deal with high inflation countries, Kaminsky and Reinhart (1999) divide their sample into two groups, the high inflation one (inflation rate higher than 150 percent in the six previous month) and low inflation one and apply the criteria on each group. 6 Let us recall that in the theoretical literature, there are roughly speaking three generations of models which aim to explain the causes of currency crises. The first generation of models, based on the seminal work of Krugman (1979), shows that crises are due to persistent imbalances financed by monetary creation which conflict with limited amount of reserves : parity of exchange rate is no longer defendable and foreign investors disengage because they expect the ineluctable depreciation of currency (see Mundell (1963) for the incompatibility of fixed exchange rate, capital mobility, and independent monetary policy). Crises are qualified as standard in those kinds of models. The second generation tries to explain financial crises which occur in an environment where there is no imbalances and good fundamentals, see Obstfeld (1986), Obstfeld (1994) and Obstfeld (1996). Here the currency crisis results from speculative attacks and mainly concerns developed economies. The third generation of models, related to tequila crisis (1994) and the Asiatic one, is more devoted to explain crises in emerging economies. Here currency crises are linked with banking fragilities and imperfect information on financial markets. The so-called twin crises (see Kaminsky and Reinhart (1999)) are a characteristic feature of the crises of the eighties and of the nineties. 5

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Who bears the cost of currency crises?

4.2

The model

In this section, we present a model highlighting the different channels through which currency crises may have an impact on the aggregate labour share. The aim of this section is not to explain why a currency crisis occurs but rather to describe its potential effects on the labour share. Hence we take the crisis as an exogenous variable. Our model is mainly based on Dutt et al. (2008), who study the impact of trade on unemployment according to various theories. We propose a static version of the model, changing several assumptions in order to focus on the labour share and financial crisis. We design the model to describe what happens during a crisis in terms of factor reallocations across sectors and in terms of changes in the bargaining power of labour within sectors. Before starting with the presentation of the theoretical model we briefly describe how the macroeconomic aggregates behave during a crisis, since some of these will then have an impact on factor shares.

4.2.1

The macroeconomic background of the crisis

In this subsection we present some stylized facts coming mainly from Kaminsky and Reinhart (1999) and Kaminsky (2006) concerning what happens to some macroeconomic aggregates during a currency crisis. The main features of the theoretical model presented below are compatible with these facts. Kaminsky and Reinhart (1999) examine the evolution of several macroeconomic aggregates during currency crisis episodes and their period of financial turbulence is defined as the period going from 18 months before the crisis occurs to 18 months after. A currency crisis is characterized by a major and sudden exchange rate depreciation. Kaminsky and Reinhart show that during the 18 months before the crisis occurs, the real exchange rate is overvalued by 20% relative to its trend. Just after the currency crisis occurs, the real exchange rate is 10% undervalued relative to its trend and remains stable during the 18 months following the crisis. As a result exports underperform prior to the currency crisis and sharply increase after the crisis, suggesting major factor reallocations from non tradable sectors to tradable ones, see Tornell and Westermann (2002) or Kehoe and Ruhl (2009) for evidence. Moreover, crisis episodes are generally associated with a decrease in the capital stock. Indeed, several indicators in Kaminsky and Reinhart (1999) suggest a decrease in the funds available to finance firms’ investments. For example, the growth rate of bank deposits remains close to normal during the 18 months prior to a financial crisis, but the loss of deposits accelerates as the crisis unfolds, and deposits only starts to recover a year and a half after the crisis. Furthermore, the annual growth of the domestic credit/GDP ratio decreases after the crisis occurs and 12

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4.2. The model months after the crisis, is 5 percent below what it is during ’tranquil’ periods . Kaminsky (2006) shows that currency crises are associated with losses of foreign exchange reserves, with a decrease of about -12% with respect to its level 6 months before the crisis. Finally, Kaminsky and Reinhart (1999) document that during crises episodes, annual ”changes in stock prices (...) are about 40 percent below those observed in non-crisis period”, which reflect capital flights among other things. Therefore there is evidence that financial crises are associated with massive capital flights. Hutchison and Noy (2005), using panel data over the 1975-1997 period for 24 emergingmarket economies, that currency crises reduce output by about 5 to 8 percent over a two to four year period. Kaminsky and Reinhart (1999) also document slow-downs in economic activity. To use their exact words: ”For balance of payments crises, the 12-month growth in output bounces in a range of 2 to 6 percent below the comparable growth rates during tranquil periods-with a tendency for the recession to deepen as the crisis nears”. Hence the cost of financial crisis in terms of economic activity is high for the economy as a whole7 . The reasons why currency crises and more particularly crises associated with a reversal in capital flows cause severe recessions are summarized in Hutchison and Noy (2006). Reinhart and Calvo (2000) identify the credit channel and the resulting impact on aggregate demand attributable to the sudden stop in capital inflows combined with an external financing premium. For Mendoza (2001) the sudden stop in capital inflows hurts the financial sector and, given collateral constraints, leads to credit crunch which induces debt-deflation and a contraction in activity. Furthermore the macroeconomic environment during crisis, characterized by firm bankruptcies, makes banks more cautious (Calvo (2000)), making them reduce their loans which contribute to recession. As a result, investment and capital stock drop during a currency crisis. A number of authors have pointed out that many currency crises result from a shock to world capital interest rates (see Calvo (1998) or Kaminsky (2006)). Frankel and Rose (1996) show that foreign interest rates play a significant role in predicting currency crashes. Kaminsky and Reinhart (1999) show that many of these crises are concentrated at the beginning of the 1980s and suggest that they could be due to the sharp increase in US interest rates during this period. Another fact we want to highlight on is the pattern of unemployment and employment during crisis periods. As noted by Fallon and Lucas (2002) in a survey devoted to the impact of financial crisis on the labour market outcome, unemployment rises quite sharply in the year of the crisis 7

Note that Kaminsky (2006) shows that currency crises associated with financial excess are more severe. Hutchison and Noy (2006) show that currency crisis classified as sudden stop crisis (60% of crisis in emerging economies), characterized by a reversal in capital flows, are much more severe as they reduce output growth by 8-11 percentage points in the year of the crisis.

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Who bears the cost of currency crises? in six of the seven cases studied in their paper. Finally, currency crisis imply reallocation effects across sectors. Fallon and Lucas (2002) report an increase in self employment and employment changes across sectors suggesting reallocation effects. Tornell and Westermann (2002) show that in the aftermath of crisis, the tradable sector experiences an acceleration of growth after a mild recession, while the non-tradable sector experiences a sharp fall and a sluggish recuperation. In contrast, prior to a crisis the non tradable sector grows faster than the tradable sector. This suggests major reallocations of factors across those two sectors. We now turn to the basic model which incorporates those aspects: capital scarcity, nominal and real exchange rate depreciation,output losses, and rise in unemployment rate.

4.2.2

The basic model

4.2.2.1

Environment

We propose a static model designed to analyze the impacts of financial crises on the labour share. In this model, we take the crisis as exogenous and focus on the possible consequences for the labour share. As in Dutt et al. (2008) the model features two sectors with different factor intensities allowing for factor reallocation across sectors. In this model, the labour share can change due to a composition effect as factors reallocate during the crisis. We add to the model the exchange rate and the possibility for factors to reallocate across sectors. The model also exhibits matching frictions with shadow entry costs and rents on the good market. Wages are bargained over the surplus as in standard Pissarides (2000) framework. Those assumptions allow us to study movements in the labour share since workers are not paid at marginal product8 , while frictions allow the model to be consistent with an increase in unemployment observed during financial turbulences. We also include a parameter d that captures the cost of crisis in term of debt repayment labelled in foreign currencies and we add outside options for capital I. The main idea is that although outside options of labour, as they are mainly local, shrink during a crisis, outside options of capital are determined at the world level and do not change as much. As a result, a currency crisis hurts labour in the wage setting and can negatively affect the labour share within each sector. We first present and solve the model, then we turn to financial crises. There is a final non-tradable good Z, produced under perfect competition using two intermediate inputs: X which is tradable and Y which is not. The production function is the following: 8

If workers are paid at marginal product, labour share only depend on technological determinants.

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4.2. The model

Z=

AX 1−α Y α − α)1−α

(4.1)

αα (1

The good Z is the numeraire and its price is normalized to one. We obtain the following cost function: 1 (px )1−α (py )α = 1 A

(4.2)

where px stands for the price of X and py for the price of Y . We can write the relative demand function for the two goods as Xd /Yd = ((1 − α)/α) py /px . We make the simplifying assumption that there is a foreign demand component so that we can write the total relative demand for the country i in a more general formulation as: 

X Y

d = f (p, e) , with fp < 0 and fe > 0

(4.3)

where p = px /py is the relative price of good x and e is the exchange rate. An exchange rate depreciation increases the relative demand of good X. The two intermediate goods are produced using two factors, labour and capital, with a Cobbφ

Douglas technology. Per worker production functions are x = Ax kxφx and y = Ay ky y , where φx and φy stand for constant output-capital elasticities, and kx and ky for capital per worker φ

ratios. Total production in each sector is X = Ax (1 − ux )Lx kxφx and Y = Ay (1 − uy )Ly ky y where us stands for unemployment rate in sector s = x, y, As for total factor productivity, and Ls corresponds to the number of workers who seek for a job in sector s and (1 − us )Ls corresponds to total employment in sector s. Labour is allocated across the two sectors: Lx + Ly = L

(4.4)

and the market clearing condition for capital is: (1 − ux )Lx kx + (1 − uy )Ly ky = K

(4.5)

where K is the total stock of capital in the economy and is assumed to be fully employed. Factor endowments are exogenous, but the allocation across sectors is endogenous. Capital is allocated across sectors so as to equalize the marginal product of capital to the world interest rate:

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Who bears the cost of currency crises?

ps As φs ksφs −1 = r.

(4.6)

Hence the relative supply of good X is: Ax (1 − ux )Lx kxφx Xs = . φ Ys Ay (1 − uy )Ly ky y

(4.7)

We now turn to the labour market. Each firm is endowed with a single job slot and can search for a worker after paying the entry cost χ. We assume that this entry cost is a shadow cost induced by product market regulation (see Blanchard and Giavazzi (2003)). From a national accounting perspective, it is important to make explicit the nature of the cost. It can receive two interpretations. On the one hand, it can correspond to the purchase of capital units prior to searching a worker. On the other hand, it can be due to the regulation that limits the number of firms and guarantees superprofits for the firms managing to enter. Capital costs and superprofits are part of value added and do not coincide with labor income. By contrast, entry costs cannot correspond to spendings in intermediary goods (that would be subtracted from value added) or to wage payments (that would enter the wage bill). This implies that the cost does not have to be deduced from output to compute value added as a monetary cost would. As a result firms make ’superprofits’, and changes in wage to productivity ratios translate into labour share changes.9 We denote the number of vacancies in each sector by vs Ls and the number of unemployed by us Ls . We define θs = vs /us as the sector-specific tightness and we assume a segmented search place: each worker can search in one sector. The number of matches is a linear homogeneous function of us Ls and vs Ls , and we assume for simplicity a Cobb-Douglas matching function: Ms (vs Ls , us Ls ) = mvsγ us1−γ Ls = mθsγ us Ls

(4.8)

where m is a scale parameter of the matching technology. The exit rate from unemployment is Ms / (us Ls ) = ms θsγ and the rate at which vacancies are filled is Ms / (vs Ls ) = ms θsγ−1 . A firm’s expected profits are: πs = −χ + mθsγ−1 Js .

(4.9)

where Js = ps As ksφs − rks − ws − d is the value of a filled job denominated in local currency. d stands for the extra-cost of loans contracted before depreciation. Hence, d = 0 during peaceful 9

We could also take a standard search cost but we would have to assume that the sharing of value added for this activity is the same as the rest of economy.

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4.2. The model periods. Free entry conditions imply πx = πy = 0 and the value of an occupied job becomes Js =

χ

(4.10)

ms θsγ−1

Wages are bargained according to the Nash solution ws = max arg(Js − I)β (ws − B)(1−β)

(4.11)

w

Where B corresponds to workers’ outside opportunities whereas I stands for the outside opportunities of capital owners. We assume that outside options for workers depend on local considerations that is, to the mean wage w. Hence, we set B = bw in the economy. As capital can relocate easily at the world level, outside options of capital owners should depend on external factors such as productivity and profits in alternative location choice. During peaceful periods, we assume that world outside options for capital increase with local ones and is not sector specific. That is, I outside option for capital is proportional to the local mean productivity in P sectors, net of capital costs, such that I = i(1/2) (1 − φs )ps As ksφs . This assumption ensures s

that wages increase proportionally with productivity during peaceful periods and that the labour share is stable over the long run as we are going to see below. When we will turn to the impact of currency crisis below, we will relax this assumption. The solution of the maximisation problem is ws − B =

β 1−β (Js

− I) and by replacing we can

obtain the solution for wage h i ws = (1 − β)B + β ps As ksφs − rks − d − I

(4.12)

Using the equilibrium value of an occupied job (4.10) we can have the solution for tightness   β χ ws = B + −I 1 − β ms θsγ−1

(4.13)

From (4.6), (4.10) and (4.12) we can find a solution for sectorial capital intensities as a function of relative prices kx∗

ky∗

 =

 =

φy φx



φy φx



φy φx −φy



φx φx −φy



1 − φx 1 − φy



1 − φx 1 − φy



φy −1 φx −φy



φx −1 φx −φy



Ax px Ay py



Ax p x Ay p y



1 φy −φx

1 φy −φx

(4.14)

(4.15)

For example, assume (without any implication for the rest of the paper) that sector X is

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Who bears the cost of currency crises? capital intensive, that is kx > ky . Then an increase in p lowers the capital intensity in both sectors. Intuitively, an increase in p reallocates labour from sector Y to sector X. As sector X is capital intensive, the capital demand from sector X is too high with respect to the quantities available in sector Y . Hence, capital intensities have to adjust to clear the market. Furthermore from (4.2) an increase in px implies a decrease in py and from (4.6) an increase in r. This is the standard Rybczynski theorem. It is also possible to show that the relative supply curve (4.7) increases in p. We can define the utility of a job seeker as Us = (1−mθsγ )B+mθsγ ws . Using the Nash solution and (4.10), we can write the utility of a job seeker as Us = B + mθsγ [(β/(1 − β))(χ/mθsγ−1 − I)]. Workers must be indifferent between the two sectors, which implies Ux = Uy . We can deduce P φ θx = θy , ux = uy , wx = wy = w, and (1 − φx )px Ax kxφx = (1 − φy )py Ay ky y = (1/2) (1 − s

φs )ps As ksφs . Recall that we have seen in the previous subsection that currency crises increase the unemployment rate. The presence of matching frictions in the model aims at replicating this stylized fact. We can derive the impact of crises on the unemployment rate from equations (4.12) and (4.13). A decrease in sectoral productivity or an increase in d following a currency crisis have a positive impact on the unemployment rate if χ remains constant. This is a reasonable assumption over the short and medium run, widely used to generate fluctuations of the unemployment rate over the business cycle in the matching literature (constant search costs)10 . If we assume χ is proportional to the productivity over the long run and using previous assumption concerning parameters I and B, we can see that tightness and the unemployment rate do not depend on the productivity (peaceful period)11 .

4.2.2.2

The labour share

The labour share is the total wage bill over value added. Entry costs must not be deduced from output due to our assumption that χ is a shadow cost. The labour share in sector s is h i β/(1 − (1 − β)b) (1 − φs )ps As ksφs − d − I LSs =

ps As ksφs

10

(4.16)

In a dynamic setting where wages are renegotiated in each period, the possibility for match destruction and state transition from an employed to an unemployed position imply that tightness (and unemployment) enter in worker outside option with positive sign. Hence, an increase in unemployment hurts labour in the wage setting process and decreases the labour share. 11 As noted in Pissarides (2000), chapter 1, the flow income of an unemployed worker and the entry cost (search cost) must be proportional to productivity. If it were not the case, the unemployment rate would depend on output level over the long run, which is not a satisfying property of an equilibrium unemployment model.

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4.2. The model During peaceful periods, due to our assumptions d = 0, that is there are no extra fees for debt repayment due to depreciation, and I = i(1 − φs )ps As ksφs the labour share at sector level becomes LSs = [β/(1 − (1 − β)b)] [(1 − φs )(1 − i)]. The aggregate labour share corresponds to the labour shares at sector level weighted by each sectors’ output shares. For d = 0: LS = [π((1 − φx )(1 − i)) + (1 − π)((1 − φy )(1 − i))] , [β/(1 − (1 − β)b)]

(4.17)

where π stands for output share of sector X. As the unemployment rate is the same in both sectors,

π=

Lx px Ax kxφx Lx px Ax kxφx +

φ Ly py Ay ky y

1

= 1+

Ly (1−φx ) Lx (1−φy )

(4.18)

The aggregate labour share depends on sector-specific technologies weighted by the share of each sector in the total labour force. It also depends on the bargaining power β of workers, on the replacement rate b and on outside opportunities of capital owners i12 We now turn to the impact of currency crises on the labour share.

4.2.3

Currency crises and the labour share

We distinguish between two kinds of effects. First, financial crises are generally followed by a reallocation of factors across sectors due to capital outflows and the exchange rate depreciation. We show that if sectors have different capital intensities, factor reallocation implies that the labour share changes. We then turn to the impacts of currency crises on wage setting, and examine the impact on the labour shares within sectors. Parameters I, b and d play a crucial role in the model to study the relative bargaining strengths during crisis.

4.2.3.1

Reallocation effects

To derive the market clearing condition for capital, use the fact that ux = uy to set: εkx + (1 − ε)ky =

K L(1 − u)

where ε = Lx /L. 12

This parameter could be interpreted as the capital degree of mobility.

121

(4.19)

Who bears the cost of currency crises? To study the impact of an exchange rate depreciation, note from (4.3) and (4.7) that a depreciation makes the relative demand of the tradable good X increase, which induces an increase in the relative price p. Proposition 4.1 The increase in the relative price of good X makes the share π of sector X increase. If sector X is capital intensive, this implies a decrease in the aggregate labour share. If sector X is labour intensive, the aggregate labour share increases. Proof. If φx > φy , from (4.14) and (4.15), an increase in p lowers capital intensities in both sectors. We know that unemployment in each sector is not affected by productivity. Hence the right hand side of (4.19) is unaffected. At constant ε the left hand side of (4.19) decreases. Since φx > φy , as kx > ky and there is no possibility for factor intensity reversal in the Cobb-Douglas case, ε must increase for (4.19) to hold. Negative impact on the labour share comes from the fact that ∂LS/∂e = (∂ε/∂e)(∂π/∂ε)(∂LS/∂π) < 0 . The proof is similar in the case of φx < φy . We now turn to the impact of a sudden stop in capital inflows. Firms are no longer able to finance their investment and the aggregate capital stock decreases. Such capital outflows unambiguously raise the aggregate labour share. Proposition 4.2 The decrease in capital stock raises the weight of the labour intensive sector and reduces that of the capital intensive sector. This unambiguously increases the aggregate labour share. Proof. If φx > φy , then kx > ky . That is, sector X is capital intensive and sector Y is labour intensive. A decrease in capital stock makes the right hand side of (4.19) decreases. If ε does not decrease, the supply curve does not move and prices do not change. That is, from (4.14) and (4.15) kx and ky do not change and equality (4.19) does not hold. Hence, ε decreases making the relative supply of good X decreases. As p increases, kx and ky also decrease. The only possibility for equality (4.19) to hold is that kx , ky and ε decrease together. We can see that ∂LS/∂k = (∂ε/∂k)(∂π/∂ε)(∂LS/∂π) < 0. The proof is similar in the case of φx < φy . Therefore, the overall effect of the crisis is ambiguous. We have shown that if φx > φy , i.e. the tradable sector is capital intensive, the two reallocation effects work in opposite direction. If φx < φy , that is if the tradable sector is labour intensive, both reallocation effects tend to increase the aggregate labour share. We now turn to the impact of currency crises inside each sector through the bargaining channel.

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4.2. The model

4.2.3.2

Intrasectoral variations in the labour share

There are various mechanisms that could link within-sector labour share movements with currency crises. Our arguments hinge on the fact that the outside opportunities of capital owners are global whereas those of labour are only local. During crises, local business opportunities shrink and so do outside options of workers. By contrast, capital can be invested abroad. Then, it pressures wages down and the labour share tends to decrease. In the previous subsection, we assumed that world outside options for capital owners were proportional to local productivity in order to ensure the stability of sectoral labour shares over the long run. This is not the case during an important macroeconomic shock such as a currency crisis that hurts just one country or a small number of countries. During such a period, outside options of capital owners remain constant contrary to labour. Massive capital outflows lead to a decrease in both sectors productivity (per capita output). Currency crisis could also affect productivity through TFP. We can see that if I is constant, ∂LSs /∂ps As ksφs < 0. As we saw in the previous subsection world outside options may increase during currency crisis. This corresponds to an increase in I and this makes the labour share decreases. Other kinds of arguments could explain a decrease in the labour share following a crisis. Many crises result in a credit boom as noted by Chang and Velasco (2001) or Kaminsky and Reinhart (1999). During those periods of financial excess, the loans were often made in dollars and firms (or Governments) were linked by contract with banks and lenders (see Jeanne (2003)). The exchange rate depreciation increases repayment charges and d become positive and increases. This reduces the surplus over which wages are bargained and, so do wages at given output. We can show that ∂LSs /∂d < 0. Those effects disappear as soon as loans are repaid and new loans are contracted at the new exchange rate. There is another mechanism driven by structural adjustment policies. During the 1980s and the 1990s, IMF interventions in response to financial crises generally required countries to implement the so-called structural adjustment plans. Adjustment programs consisted in reducing public spending. As a result there were often sharp cuts in welfare payments. The immediate impact in terms of our model is to decrease b. We can check that ∂LSs /∂b > 0.That is, the reduction in benefit payments that follows a crisis tends to reduce the labour share. Those arguments, all in favour of a decrease in the labour share within each sector during a currency crisis are summarized in the following proposition.

123

Who bears the cost of currency crises? Proposition 4.3 During a currency crisis, the labour share should decrease in each sector due to (i) the sharp decrease in productivity associated to constant I outside options of capital owners, (ii) the increase in repayment charges labelled in foreign currencies d and (iii) the decrease in b resulting from IMF structural ajustment plans. Proof. (ii) and (iii) are derived from the fact that ∂LSs /∂d < 0 and ∂LSs /∂b > 0. Proof of (i) is derived as follows. From proposition 2, we know that the decrease in aggregate capital stock lowers kx , ky and that the relative price p increases. From (4.2) this implies a decrease in py . φ

From (1 − φx )px Ax kxφx = (1 − φy )py Ay ky y the productivity ps As ksφs decreases in both sectors as the right-hand side unambiguously decreases. The decrease in the labour share within sector comes from the fact that ∂LSs /∂ps As ksφs < 0. We can summarize the previous findings in Table 4.1:

Table 4.1: summary of results parameters crisis effect ps As ksφs LSs LS u K − − − −/+ + e + ? 0 −/+ ? i + 0 − − − b − 0 − − − d + 0 − − + The first column gives the various parameters that may change during a currency crisis. The second column describes how they change during the crisis. The other columns give the actual impact of the parameter change on each endogenous variable. A question mark means that we cannot sign the effect. For instance, the capital stock (K) collapses (-) during a sudden stop crisis, which implies a decrease in sector-specific labor shares (LSs ) and an ambiguous impact (-/+) on the aggregate labor share (LS) -depending on the magnitude of reallocation effects.

124

4.3. Empirical analysis

4.3

Empirical analysis

We have shown that currency crises can affect the labour share in two different ways. On the one hand a currency crisis can affect the structure of the economy through factor reallocations across sectors which differ in their labour shares. On the other hand, a currency crisis can affect the labour share within each sector. Moreover, different effects have opposite signs, and the overall impact is ambiguous. This raises two central questions. First, do crises increase or reduce the overall labour share? Second, to what extent is the aggregate impact due to within sector effects, and to what extent is it due to a reallocation? A first glance at the data suggests that currency crises reduce the labor share in a significant way. We divide the sample in subperiods lasting four years. In each subperiod, and for each country, we compute the percentage change in the aggregate labour share. Then, we compare the mean variation when a crisis occurs and when it does not. On the crisis subsample, the mean variation between one year before the crisis occurs and two years after is a 2.9 percentage point decrease. On the no-crisis subsample, the mean variation is a decrease by 0.11 percentage point. In the rest of this section, we show that the labor share recovers four years after the crisis occurs and that the observed decrease mainly corresponds to a within-sector fall.

4.3.1

Empirical Strategy

Our empirical analysis consists in estimating a reduced form equation on panel data. The dependent variable is the labour share and our regressor of interest is a currency crisis dummy. In a first step we will estimate this relation in levels on aggregate manufacturing data which allows us to compare our results to those of Diwan (2001) and Diwan (2002).13 Our basic equation is :

LSit =a + ai + at + β1 Crisisit + β2 Crisisit−1 + β3 Crisisit−2 + β4 Crisisit−3 X + γk Xk,i,t + εit

(4.20)

k

where ai and at are respectively country fixed effects and time dummies and Xk are various 13

Comparability is however limited since Diwan works on UN data and does not use the same crisis criterion since he defines a crisis episode as a nominal annual exchange rate depreciation greater than 25%

125

Who bears the cost of currency crises? control variables.14 . Index i stands for country The crisis dummy is included both in the current year and with 3 lags in order to estimate the timing of the impact of the crises on the labour share.15 We control for heterogeneity across countries thanks to country fixed effects. In our case, controlling for unobserved heterogeneity across countries is important since in developing countries the labour share tends to be lower than in developed ones (see Ortega and Rodriguez (2006)). If crises are more likely to occur in developing countries, a negative coefficient could capture only the fact that the labour share is negatively correlated to development. Diwan (2001) does not control for unobserved heterogeneity and this could be the reason why he finds a such high impact of the crisis (-10 points in some regressions). Time dummies control for global shocks which could affect the labour share and which are not captured by the other explanatory variables, such as biased technological progress. Our second step is to turn to sectoral data in order to control for unobserved heterogeneity across sectors. The estimated model is the following :

LSits =a + ai + at + as + β1 Crisisit + β2 Crisisit−1 + β3 Crisisit−2 + β4 Crisisit−3 X + γk Xk,i,t,(s) + εits

(4.21)

k

where as is a sectoral dummy which allows us to control for unobserved heterogeneity across sectors. Note that due to a lack of data for developing countries, the only sectoral explanatory variable we dispose of is investment over value added (IY ) which is a proxi for capital accumulation. In order to distinguish between intra sectoral variations of the labour share and reallocation effects we perform estimations in differences. First of all we estimate an equation in differences at the aggregate level to appraise once again the overall impact of the currency crises on the labour share. Then we will turn to sectoral data in order to understand what is the share of the variation at the aggregate level explained by within sector variations of the labour share. More precisely, we first estimate an equation in first-order differences16 (except for the crisis dummy which we do not differentiate) to compare all the results which will follow in this section with this benchmark estimation. We regress the variations of the aggregate labour share ∆LSit on 14

We control for factors accumulation and trade and financial openness We show in figure A-III that the 4-period lagged dummy is non significant. 16 The operator ∆ stands for the first order difference operator between t and t − 1. 15

126

4.3. Empirical analysis financial crisis dummies at t, t − 1 and t − 2. Defining ∆LSit ≡ LSi,t − LSi,t−1 the variation of the aggregate labour share, the estimated model is the following:

∆LSit =at + β1 Crisisit + β2 Crisisit−1 + β3 Crisisit−2 X + γk ∆k Xk,i,t + εit .

(4.22)

k

Second we perform a decomposition of the aggregate variation into a ”within” term which captures the variations of the labour share within sectors, and a ”between” term which captures the extent to which the variation in the aggregate labour share is due to changes in the structure of the manufacturing sector. Recall that the labour share is the sum of the sectoral labour shares LSi,t,s weighted by the sectoral shares φi,t,s ≡ yi,t,s /yi,t , that is LSi,t =

n X

φi,t,s LSi,t,s .

s=1

We can decompose the variation of the labour share as follows:

∆LSit =

n X

(LSi,t,s − LSi,t−1,s )φi,t−1,s +

s=1

n X (φi,t,s − φi,t−1,s )LSi,t,s . s=1

within effect

(4.23)

composition effect

Two terms appear.17 . The first one represents the within effect and equals the sum of the variations of the labour share within each sector, weighted by the initial sector share. This corresponds to the ”real variation” of the labour share which can be due to changes in factor intensity or institutional determinants, like the bargaining power of workers. The second term corresponds to what we call the ”composition effect” and equals the variation of the share of each sector in the economy, weighted by the final value of the labour share. This term captures 17

In an alternative decomposition, a third terms appears

LSt −LSt−1 =

n X

i (LSt,s − LSt−1,s )φt−1,s +

s=1

n X

(φt,s − φt−1,s )LSt−1,s +

s=1 within effect

n X

(LSt,s − LSt−1 )(φt,s − φt−1,s )

s=1 net composition effect

interaction term

In this decomposition, the ”within” term remains the same as in the previous one. The ”composition” effect is here itself decomposed in two terms: the first can be named ’net composition effect’ (the variation of sector shares weighted by the initial labour shares of each sectors), and the second one is an interaction term corresponding to the covariance of the variation of labour share and the variation of sector share.)

127

Who bears the cost of currency crises? the fact that a change in the aggregate labour share can be due to a change in the composition of output. The decomposition allows us to assess the importance of the two effects. We run the regressions :

W ithin ≡

n X

(LSi,s,t − LSi,s,t−1 )φi,s,t−1

s=1

(4.24)

=at + β1 Crisisit + β2 Crisisit−1 + β3 Crisisit−2 +

X

γk ∆k Xk,i,t + εit ,

k

Between ≡

n X

(φi,s,t − φi,s,t−1 )LSi,s,t

s=1

(4.25)

=at + β1 Crisisit + β2 Crisisit−1 + β3 Crisisit−2 +

X

γk ∆k Xk,i,t + εit ,

k

to understand whether changes in the aggregate labour share estimated in equation (4.22) reflect intra sectoral changes of the labour share or composition effects. Performing these two estimations is the most obvious way to appraise these two effects of financial crises since we regress the two terms of the decomposition of the changes in the labour share. Next, to perform regressions on sectoral data, we regress not the weighted sum of the changes in the sectoral labour shares but simply these variations of the sectoral labour shares ∆LSits weighted by sectoral shares φi,t−1,s :

∆LSi,t,s ∗ φi,t−1,s =at + β1 Crisisit + β2 Crisisit−1 + β3 Crisisit−2 X + γk ∆k Xk,i,t,(s) + εits .

(4.26)

k

This estimation should also allow us to appraise the effects of financial crises on the labour share within sectors. In the same manner, to capture the composition effects of the financial crisis in another way than regressing the between term, we simply regress the variation of the sector shares, weighted by the labour shares:

∆φi,t,s ∗ LSi,t,s =at + β1 Crisisit + β2 Crisisit−1 + β3 Crisisit−2 X + γk ∆k Xk,i,t,(s) + εits . k

128

(4.27)

4.3. Empirical analysis Lastly, in order to estimate differently the intra sectoral impact of financial crises on the labour share, we estimate the changes in the sectoral labour shares, weighting all of the observations by the sector shares at t − 1. These weighted regressions should capture a within effect of the financial crises on the labour share and allow us to perform a robustness check of our results about the within impact of the crises:

∆LSits =at + β1 Crisisit + β2 Crisisit−1 + β3 Crisisit−2 X + γk ∆k Xk,i,t,(s) + εits .

(4.28)

k

4.3.2

Data

We compute the labour share using the UNIDO data which covers 180 countries over the period 1963-2003. This database provides various variables at the aggregate manufacturing level, as well as at 3 digit level for 28 sectors (see appendix). The UNIDO data mainly come from industrial surveys which are sent by UNIDO to the country statistical offices. The labour share is defined as the ratio of wages and salaries over value added.18 As argued by Gollin (2002) this definition implies that all the income of the self-employed is treated as capital income which underestimates the labour share. This is particularly problematic in our study because it could bias the impact of financial crises. Indeed, during financial turbulence, many workers go back to the agricultural sector and/or become self-employed (see Fallon and Lucas (2002) ). Hence, this could lead us to misinterpret a negative relationship between financial crises and the labour share. The data from UNIDO allow us to avoid this problem. Indeed, the surveys sent by UNIDO are designed to collect data only in the corporate manufacturing sector and specify a cut-off point below which economic activity is not measured. The cutoff can change between countries. For example, in developing countries, firms with less than five employees are not covered. In the US, the requirement is that establishments must have at least one paid employee. This selection removes, to a large extent, the problem of self-employment. The drawback is that we can examine the effects of crises only on the manufacturing labour share and not on the labour sahre for the whole economy. A second problem of the UNIDO data is that the way in which the manufacturing sector is desagregated in subsectors can change over time and countries. For instance in France in 1979, sectors 311, 313 and 314 are distinct but in 1980, sectors 313 and 314 are merged into sector 311. We will simply do not perform any regression or decomposition of the labour share for 18

See Appendix for a more precise definition of these variables.

129

Who bears the cost of currency crises? the country-year in which this happens, since an observed sectoral variation of the labour share over time could simply reflect the merge of two sectors. We also ignore observations where the weighted sum of sectoral labour shares does not equal the aggregate one and where the sector shares does not sum up to one, which is rare.19 Data on currency crises come from Kaminsky (2006). The data comprises a panel dataset of 20 countries, 6 developed and 14 developing,20 which have experienced various currency crises in the sense of Kaminsky and Reinhart (1999) and Kaminsky (2006), over the 3 past decades. This sample is actually borrowed from Kaminsky (2006). As we discussed previously, we have chosen the currency crisis definition of Kaminsky and Reinhart (1999) because their criterion include reserve variations, which avoids misinterpreting an exchange rate depreciation as a financial crisis episode, which is what could have occurred with economies which have experienced high inflation. In the sample of Kaminsky (2006), 96 crises are identified. The 20 countries which form part of the sample have been selected by Kaminsky (2006) because they present characteristics which can allow her to apply the financial crisis criteria of Kaminsky and Reinhart (1999). More precisely, to form part of the sample countries must be small open economies, with a fixed exchange rate, crawling peg or band through portions of the sample. We have kept only the sample of Kaminsky (2006) to define the database we work on. Since some observations are missing in the UNIDO database for some years, we do not observe the same number of crises in our dataset as in the sample of Kaminsky (2006),21 and have only 82 crises episodes. More precisely, 28 crises episodes are observed in the 6 developed countries we dispose of and 54 in the 14 developing ones. We include a number of control variables suggested either by our model or the previous literature. We control for capital accumulation since it is the only determinant of the labour share when factors are paid their marginal product. Moreover it allows us to test for the capitalaccumulation channel of financial crises in the case of non-Cobb-Douglas function. We use the ratio of gross fixed capital formation to value added as a proxy for capital-output ratio. Gross fixed capital formation and value added both come from the UNIDO dataset. We also add an education variable to control for the quality of labour as there is empirical evidence of a positive link between education and the labour share, at least for OECD countries, see Daudey and Decreuse (2006). Although Daudey and Decreuse (2006) empirically find a positive link between education and the labour share using the proportion of people attaining with tertiary 19

We have also dropped the 34 observations where the labour shares were negative or greater than 100%. 20 See appendix for the list of countries and how developing and developed are differentiated. 21 For instance, the UNIDO data set does not cover 1986 for Brazil which prevents us from including this country/year in our dataset.

130

4.3. Empirical analysis education, we have chosen to use as a proxy of human capital the average number of years of formal schooling of adults over age 15 (see Barro and Lee (2000)). This variable is more appropriate in our case since 14 out of 20 countries of our sample are developing. Data on schooling are available every five year and yearly data are constructed by linear interpolation. The second kind of control variables we use, namely trade and financial openness, are related to globalization. As mentioned above, various studies have shown that those variables are negatively correlated to the labour share, see Rodrik (1997), Harrison (2002), Jayadev (2007) and Ortega and Rodriguez (2002). Moreover, Kaminsky and Reinhart (1999) find that many of the crises occur a couple of years after financial liberalization. Therefore, omitting openness variables would create endogeneity problems. We use as a proxy for trade openness the ratio of import plus export to GDP for the whole economy from the World Bank available from 1960 to 2006 for more than 200 countries. Unfortunately, sectoral data on this variable are not available for developing countries. To measure financial openness we dispose of two indexes, one de jure and one de facto. The first one captures how policies are restrictive toward capital flows ; the second one measures how much capital actually flows over borders. Our de jure financial openness is the continuous composite index of Chinn and Ito (2007),22 available from 1960 to 2006 for more than 200 countries. Our de facto financial index is the sum of total external assets and liabilities as a share of GDP which have been estimated by Lane and Milesi-Ferretti (2007) in their ”EWNII” dataset. Lastly, our theoretical analysis indicates that the labour market institutions are an important determinant of the labour share, and there is evidence for OECD countries that this is indeed the case (see Checchi and Garc´ıa-Pe˜ nalosa (2008, 2009) ). Unfortunately we have not been able to include a measure of institutional context due to the lack of data for developing countries.

Table 4.2: Descriptive Statistics Descriptive statistics (aggregate) Obs Mean Stand dev Min Max LS 580 32.90 15.60 5.21 71.40 IY 472 0.18 0.22 -0.05 3.13 School 666 5.94 2.29 2.02 11.86 OPENK (de jure) 580 0.22 1.40 -1.75 2.62 OPENK (de facto) 580 0.91 0.54 0.09 4.51 OPENT 643 50.80 28.50 7.98 228.87 Table 4.2 summarizes the data used in regressions: LS corresponds to the labor share, IY 22

See appendix for construction.

131

Who bears the cost of currency crises? to our variable for capital acumulation (see appendix for details), School to our our variable for human capital accumulation, OPENK (de jure) to our de jure measure of financial openness, OPENK (de facto) to our de facto measure of financial openness and OPENT to trade openness. The mean labor share is 32.90%. This could seem very low. However, our data cover the manufacturing sector where the labor share is typically lower than in the rest of the economy. In addition, the wage bill does not include social contributions in the UNIDO dataset.

4.3.3

A first glance at the data

To get a first glimpse at the impact of financial crises on the labour share, we compute various variations over time of the aggregate labour share during crises episodes for each country/year. Let t be the date at which the crisis occurs. Between t and t + 1, the labour share falls by 1.9 percentage points. The decline is larger when we consider the period t to t + 2, with the labour share falling by 2.8 points. It then recovers so that the decline three years after the crisis is of 2.4 points. Moreover, the decline in the labour share often stars the periode before the crisis, with the decrease between t − 1 and t + 2 being of 2.9 points23 . Since the largest variation takes place between t − 1 and t + 2, we will focus on this time period in the following descriptive statistics. Figure 4.1 depicts the distribution of the variations of the aggregate labour share between t − 1 and t + 2, given that the crisis has occurred at t, for each country-year crisis episode. We can observe that about 72% of the country-year crises are marked by a decrease in the aggregate labour share. The question which arises is whether these changes reflect variations within sectors, or whether they are the results of sectoral composition effects. This question is relevant in our econometric study because manufacturing sectors are heterogenous in terms of their labour share. Note that in our theoretical model those differences are due to different technologies across sectors, but other factors could also explain such differences, for example different union bargaining power. Figure 4.2 plots the sectoral fixed effects γs obtained by the regression LSi,t,s = γi +γt +γs , where γi and γt are country and year fixed effects. The figure 4.2 shows that the labour share varies across sectors.24 It is particularly large in sector 324 (footwear) and almost 20 points below average in sector 353 (petroleum). Consider now the decomposition of the aggregate variation in a ”within” and a ”between” composition term described in subsection 3.1, equation (4.23). The decomposition of the changes in the labour share between t − 1 and t + 2 is : 23

The decrease is of about 2.4 percentage points between t − 1 and t + 1 compared to 1.9 between t and t + 1 indicating that the labour share starts to fall before the crisis occurs. 24 Numbers at the top of the bars represent standard errors.

132

4.3. Empirical analysis

Figure 4.1: Variations of the labour share between t − 1 and t + 2, crisis in t

Figure 4.2: Estimated sectoral fixed effect

LSi,t+2 − LSi,t−1 =

n n X X (LSi,t+2,s − LSi,t−1,s )φi,t−1,s + (φi,t+2,s − φi,t−1,s )LSi,t+2,s . (4.29) s=1

s=1 within effect

composition effect

Performing this decomposition of the changes in the aggregate labour share for each crisis episode gives us a first indication of the importance of the two effects when a crisis happens. Figure 4.3 plots the distribution of the ”within” term of the decomposition for each country/year episode. Figure 4.4 depicts the distribution of the ”composition” term for each crisis. Figure 4.1 and 4.3 indicate that the distribution of the variation of the aggregate labour share and of the within

133

Who bears the cost of currency crises? effect term are similar : about 70% of the observations are negative, and the magnitude of the variations is similar in the two cases. As to the distribution of the between effect (composition effect) we can observe that it is clearly less important, see figure 4.4.

Figure 4.3: Distribution of the within term between t − 1 and t + 2

Figure 4.4: Distribution of the between term between t − 1 and t + 2 Finally, we plot in figure 4.5 the share of the ”within” and of the ”between” term in the variation of the aggregate labour share to appraise the relative importance of the two effects. Figure 4.5 suggests that most of the observed variations of the labour share are within sectors variations.

134

4.3. Empirical analysis

Figure 4.5: Shares of the within and the between term in the total variation of the LS

4.3.4

Econometric Analysis

4.3.4.1

Regressions in level

Our first specification, equation (4.20), regresses the labour share on our variable of interest, the currency crisis dummy, at the aggregate level, that is at the level of the manufacturing sector as a whole. Our controls are capital accumulation (IY ), education (school), financial openness (OP EN K) and trade openness (OP EN T ). Note that all control variables are included at date t, but our results are virtually identical if we introduce them at date t − 1, as treatment for endogeneity. Results are reported in table 4.3. We see that crises negatively impact the labour share but with a lagged effect since the coefficient on Crisist is not significant whereas those on Crisist−1 , Crisist−2 and Crisist−3 are. Note that it is the crisis two years before which has the strongest impact on the labour share. Surprisingly, our proxy for the capital-output ratio is not significant. The education variable is positive and significant, in line with Daudey and Decreuse (2006). Adding our control variables does not change the significance of the crisis dummies and increases some of their coefficient in absolute terms when the de facto financial openness variable is added25 .

25

For example, the coefficient of Crisist−1 increases of about 0.25 points.

135

Who bears the cost of currency crises?

Table 4.3: Aggregate Data- Core Regressions-All countries Aggregate Data a b c d e Crisist 0.31 0.43 0.55 -0.03 0.14 (0.94) (0.92) (0.87) (0.83) (0.82) Crisist−1 -2.19** -1.91** -2.14** -2.17** (0.86) (0.86) (0.84) (0.84) Crisist−2 -2.22*** -2.19*** -2.27*** (0.81) (0.77) (0.79) Crisist−3 -1.80** -1.68** -1.74** (0.81) (0.80) (0.82) IY 0.57 0.96 (7.35) (7.38) school 2.71*** 2.77*** (0.74) (0.74) OPENK (de jure) -0.55 (0.43) OPENK (de facto) 3.00 (1.89) OPENT -0.10*** -0.12*** (0.03) (0.04) Dummies Yes Yes Yes Yes Yes R-squared 0.91 0.92 0.92 0.92 0.92 Nb of Observations 324 321 318 318 318 * p 0. In the autarkic case, factor accumulation or relative wage rigidity have no impact on the aggregate labor share of income. Aggregate elasticity of substitution equals one. This is no longer the case when the economy is open.

5.3.5

Sector-specific vs aggregate labor share

Globalization and wage rigidities alter the aggregate labor share of income. Aggregate changes reflect changes within and between sectors. Formally, aggregate labor share can be decomposed as follows: LS1 = φa LSa + (1 − φa ) LSb

(5.21)

with ya = Ya /(Ya + Yb ) the share of the capital intensive good in total output. Consider a marginal increase in relative wage ω: dLS1 dφa dLSa dLSb = (LSa − LSb ) + φa + (1 − φa ) dω dω dω dω

(5.22)

The global effect results from a composition effect and sector-specific effects. The relative wage rigidity increases the relative demand for capital k1 . The Rybczinsky theorem implies factor

175

Can the HOS model explain changes in labor shares reallocation towards the capital-intensive sector. It follows that dφa /dω > 0. As LSa 1 < 0 if and only if dω ki In the case of Cobb-Douglas technologies, the elasticity ω (dki /dω) /ki = 1.

(5.23) This implies

dLSi /dω = 0. Meanwhile, the aggregate labor share goes down. Hence, the decrease in aggregate labor share is only due the composition effect thereby factor reallocation benefits the low labor share sector. Using the same rationale we can decompose the impact of globalization. We know that dLS1 /dN−1 < 0 while dLS1 /dK−1 > 0. Such effects are associated with sector-specific effects as globalization modifies the relative demand for capital k1 . In the Cobb-Douglas case, LSa and LSb remain constant. Hence the decrease in labor share comes from changes in the sectorial composition of output.

5.4

Implications

We discuss the implications of the previous findings. We first show that the model can explain the different patterns of the labor share observed in Anglo-Saxon and European countries. However, the model also predicts that the labor share should be larger in developing countries than in developed economies. Then, we extend the model to capital-skill complementarity, and show that the extended model can predict rising labor shares with development.

5.4.1

Explaining LS changes

The model can predict the set of facts presented in section 2, namely constant labor share in Anglo-Saxon countries, decreasing shares in continental European countries, and constant shares at the sector/firm level. However, the model is less convincing in the case of developing countries. Time t goes from 1980 to 2000. There are three sets of countries, two equally developed (Continental Europe E, and Anglo-Saxon countries U S) and one set of developing countries (D). Europe corresponds to country 1, while Anglo-Saxon and developing countries belong to the set of countries −1. The set of factor endowments at date t is {(KE,t , NE,t ) , (KU S,t , NU S,t ) , (KD,t , ND,t )}. P P The relative supply of capital is kts = Ki,t / Ni,t . The relative supply of capital is initially sN the same in Europe and in the US. It also stays fixed over time, so that KE,t = kE E,t and sN KU S,t = kE U S,t for all t. Developing countries gradually open to trade. Therefore KD,t and

ND,t increase over time.

176

5.4. Implications The relative wage rigidity ωt takes place in Europe. It stays fixed over time. The initial value s ). Full employment is ensures that full employment holds in Europe in 1980, so that ωt = ω (k80

a strong assumption, as unemployment was quite high in 1980. But it was not larger in Europe than in the US. The model writes: ωt = ω(kt ) Kt LE,t = − (NU S,t + ND,t ) kt ωt LSi,t = ωt + ki,t

(5.24) (5.25) (5.26)

with kD,t = KD,t /ND,t , kU S,t = KU S,t /NU S,t , and kE,t = KE,t /LE,t . Figure 5.4 depicts the patterns of LSU S , LSE , and LSD .

Figure 5.4: Predicted labor shares. The Figure assumes that developing countries gradually open to trade and depicts the labor share pattern in one of them. We start with the US labor share. As ωt remains fixed at the competitive level of 1980 and s does not change over time, US employment adopts the US relative supply of capital kUs S = kE

the pattern of the labor supply NU S,t . Meanwhile, the US labor share remains constant from

177

Can the HOS model explain changes in labor shares 1980 to 2000. Employment and the labor share have independent patterns. Put differently, they should not be correlated. In Continental European countries, employment and the labor share move jointly. The rigid relative factor price ωt does not correspond to the competitive one after the inclusion of new s ) 6= ω(k s ). The impacts on European employment and labor share traders. That is ωt = ω(k80 t

are given by Result 4 and Proposition 5.1. They both decrease from a year to another whenever ∆KD,t /∆ND,t < k, stay constant when ∆KD,t /∆ND,t = k, and increase when ∆KD,t /∆ND,t > k. European employment and labor share should be positively correlated. The fall in European share observed in the 1980s and 1990s can be predicted assuming that ∆KD,t /∆ND,t < k for t = 80, ..., 00. As new countries open to trade, the relative supply of capital decreases over a decade. The stagnation of the share observed in the mid-1990s means that the relative supply of capital stays constant from 1990 to 2000. This is possible if older entrants in world trade accumulate physical capital at a rate that compensates the entry of newer and more labor-abundant countries. The fall in European aggregate labor shares is associated to factor reallocation towards capital-intensive sectors. The pattern of aggregate labor shares may contrast with micro (sectorspecific) patterns. The model predicts that sector-specific shares do not change at industry/firm level provided that technologies are Cobb-Douglas. This prediction distinguishes the HOS model with wage rigidity from the Rodrik-type models discussed in the introduction. In such models, the labor share goes down because globalization boosts the outside options of capital owners, pushing wages down at given output. This mechanism should take place at firm level, which contradicts the micro evidence. In developing countries, employment is determined by the labor supply ND,t . Globalization affects the labor share through two distinct mechanisms, depending on whether we consider the country at world trade entry or after entry. At entry, say in t (so the country is closed in t − 1), the variation in the labor share is: ∆LSD,t =

s ω(kD,t−1 ) ω >0 − s s s ω + kD,t ω(kD,t−1 ) + kD,t−1

(5.27)

The labor share increases at world trade entry. It is consistent with labor share patterns observed in some Newly Industrialized Countries and East Asian countries. After entry, the labor share is larger than in Europe and the US. The year-to-year change s . As long as those countries accumulate physical capital over time, ∆LSD,t has the sign of −∆kD,t

the labor share must go down. This explanation to the decrease in the labor share of developing countries hinges on the fact that the corresponding countries belong to the diversification cone

178

5.4. Implications of the developed economies. The evidence is mixed in this respect. Cunat (2000) and Debaere and Demiroglu (2003) show that factor price equalization must hold among developed countries but not with all developing countries suggesting multiple diversification cones. Schoot (2003) argues that there are two diversification cones. Debaere and Demiroglu (2006) suggest that newly industrialized countries and developed countries belong to the same diversification cone. Overall, factor price equalization may hold at local level and countries accumulating capital at a higher rate than trade partners in the cone of diversification can experience a decrease in the labor share. The model may predict labor share changes in developing countries. However, it also predicts that the labor share should be larger in such countries than in developed economies. We now turn to a slight alteration of the model that allows us to get rid off such a prediction.

5.4.2

Capital-skill complementarity

We use an alternative specification for the technology. We decompose the labor force into H skilled and L unskilled workers. We assume an extreme form of capital-skill complementarity: unskilled labor and physical capital are perfect substitutes. We generalize the former results for Anglo-Saxon and European countries suggesting they are robust to alternative specification. We also show that the labor share should be lower in developing countries than in developed economies, and that the labor share may decrease in developing countries at the time of world trade entry. Let h = H/ (K + L) be the skill intensity, and ω = wL /wH be the relative wage of unskilled workers as well as the relative cost of capital. Goods differ according to whether they are skill-intensive or not, and p is the relative price of the skill-intensive good. Before analyzing the consequences of relative factor cost rigidity in such an environment, we turn to sectoral data and examine the impact of sector-specific factor combinations on sectorspecific labor shares. The labor share in sector j writes LSj =

Hj + ωLj Hj + ω (Kj + Lj )

(5.28)

where ω is the same across sectors, and (Hj , Kj , Lj ) is the vector of factor quantities specific to sector j. Rewriting the labor share, we obtain LSj =

hj + ωlj hj + ω

(5.29)

where hj = Hj / (Kj + Lj ) is the skill intensity, and lj = Lj / (Kj + Lj ) is the share of unskilled

179

Can the HOS model explain changes in labor shares employment in the aggregate unskilled labor plus capital stock. The labor share increases with skill intensity hj and decreases with lj . To check that such a pattern makes sense, we use the KLEMS dataset that provides information on capital services and labor services for different skill classes of the labor force, e.g. unskilled, medium-skilled and high-skilled workers. Data are available for 37 sectors and for many OECD countries. We focus on the nine countries discussed in section 2 but Canada, which is not covered by the KLEMS dataset. We start by pooling the labor shares for the eight countries. Figure 5.5 depicts them against the corresponding skill intensity hj . The relationship is strictly increasing and strictly concave.

Figure 5.5: Skill intensity and the labor share at sector level in eight OECD countries, 2000. Data source: EU KLEMS dataset. The countries are France, Finland, Germany, Italy, Netherlands, Spain, UK, US. Table 5.3 presents various estimations. We first regress the labor share at sector level LSj on hj in cross-section for the year 2000 and including country fixed effects (column a). The country fixed effects do not play a key role as can be inferred from the visual inspection of Figure 5.5. The skill aggregate H is the sum of high-skill and medium-skill services. We add the square of skill intensity to account for a concave relationship between the labor share and skill intensity (column b). We then add the lj ratio (column c), and also the squared ratio (column d). Labor shares are adjusted by the usual correction to account for self-employed employment.

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5.4. Implications

Table 5.3: Factor intensity and the labor share at sector level LS (a) (b) (c) (d) H/(K+L) .0143984∗∗∗ .0969833∗∗∗ .0653136∗∗∗ .0588364∗∗∗ a

(.0046455)

(.0172185)

(.0147447) ∗∗∗

2

−.0015841

H/(K+L)

(.0003002)

L/(K+L)

∗∗∗

−.0011131

(.0002488) ∗∗∗

.4755852

(.0149345) ∗∗∗

−.000981

(.0002501)

1.285996∗∗∗

(.0742825)

(.1570186)

−.9118522∗∗∗

2

L/(K+L)

(.1652282)

N. obs N. countries R2

270 8 0.15

270 8 0.449

270 8 0.578

270 8 0.646

a

∗∗∗

All the coefficients are significant at the 1% confidence level, which is denoted by the superscript . All estimations account for country fixed effects.

Table 5.3 shows that both the skill intensity and the share of unskilled labor L in the aggregate K + L determine the pattern of labor shares across sectors. We now consider the aggregate implications of a relative wage rigidity ω = wH /wU . The key equations of the model become ωt = ω(p (ht )) Ht LE,t = − (Kt + NU S,t + ND,t ) ht Hit + ωt Lit LSi,t = Hit + ωt (Kit + Lit )

(5.30) (5.31) (5.32)

where ht = (HU S,t + HE,t + HD,t )/(NU S,t + KU S,t + ND,t + KD,t + LE,t + KE,t ). The rigid wage is constant over time with ωt = ω (p (hs80 )), which ensures full employment in 1980. Factor endowments do not change over time in Europe and the US. Developing countries gradually open over time, which means that HD,t , KD,t , and ND,t increase over time. Figure 5.6 depicts the patterns of LSU S , LSE and LSD .

As for Europe and the US, the predictions of the augmented model are very similar to the standard model. Employment follows the labor supply in the US. As hU S,t and kU S,t are constant over time, the US labor share does not change over time. European employment goes down with trade openness, reflecting the decrease in the relative

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Can the HOS model explain changes in labor shares

Figure 5.6: Predicted labor shares with capital-skill complementarity. The Figure assumes that developing countries gradually open to trade and depicts the labor share pattern in one of them. supply of skilled workers at the world level. The European labor share writes LSE,t =

HE + ωLE,t HE + ω (K + LE,t )

(5.33)

The pattern of the labor share reflects the pattern of European employment. As employment goes down, LSE goes down as well. The fall in European labor shares is still due to factor reallocation across sectors as in the case without capital-skill complementarity. However, the model predicts that factors should flow towards the skill-intensive sector rather than towards the unskill- and capital-intensive sector. Now, consider a developing country, say j, that opens to international trade in time t. The change in labor share is ∆LSj,t =

Hj + ω (p (hj )) Nj Hj + ωNj −