Ponçon Beffy, Magali (2008) Mobility and wage dynamics on the French labor market. PhD thesis UFR de Sciences Economiques, Laboratoire de Microeconometrie, ENSAE p.240.

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Licence: Copyright cMagali BEFFY (née PONCON), 2008

Official URL: https://gestion4.bibli.fr/genes/doc_num.php?explnum_id=7502

Abstract

This paper proposes to model labor market transitions accounting specifically for individual

heterogeneity in the ability to accede to stable jobs. The model used is based on a Markovchain

mixture of four types of transition dynamics: the stayers in stable-jobs, the stayers in

nonparticipation, the unconfined movers, and the individuals stuck on confined states and who

cannot accede to stable jobs. Conditional heterogeneity is allowed. The probabilities of being

of a certain type depend on observable individual characteristics. Estimation is done focusing

on a population already well inserted in the labor market but yet not ready to retire: men and

women aged 30 to 49.

Our main results are the following. Individuals trapped in confined mover histories represent

5% of the population under study (versus 13% apparently observed). Unconfined-mover

dynamics depend on gender, whereas male and female confined movers cannot be proved to

experience different dynamics. At equilibrium, an individual whose labor market history is

generated by the confined mover process has between 3 and 4 times more chances to be unemployed

than a confined mover. Participation, however, is not different across the two categories.

The probability to be a confined mover decreases with the quality of education. For men, a high

probability is also correlated with being single, and living in a distressed area

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Table of content

Introduction générale 1

Chapitre 1 : The returns to seniority in France (andWhy they are lower than in the

United States? 15

1. Introduction 16

2. The Statistical Model 19

2.1. The structural model - 19

2.2. Specification of the General Model - 23

2.3. Stochastic Assumptions - 26

3. Estimation 28

3.1. Principles of the Gibbs Sampler - 29

3.2. Application to our Problem - 29

4. The Data 32

5. The Empirical Results 35

5.1. A brief summary of main results - 35

5.2. Certificat d’Etudes Primaires Holders (High School Dropouts) - 37

5.3. CAP-BEP Holders (Vocational Technical School, basic) - 39

5.4. Baccalauréat Holders (High-School Graduates) - 41

5.5. University and Grandes Ecoles Graduates - 42

6. A Comparison with the United States 44

6.1. Comparison of Selected Parameters - 44

6.2. The Returns to Experience and Seniority - 46

6.3. Robustness and Specification Checks - 47

6.4. Are the Returns to Seniority an “Incentive Device”? - 48

7. Conclusion 51

ii

A. Appendix A 53

A.1. Mobility equation - 53

A.2. Wage equation - 54

A.3. Participation equation - 55

A.4. Initial equations - 57

A.5. Latent variables - 57

A.6. Variance-Covariance Matrix of Residuals - 58

A.7. Individual effects - 59

B. Results 62

C. Simulations 75

Chapitre 2 : Job Mobility andWages withWorker and Firm Heterogeneity 84

1. Introduction 84

2. Statistical model 86

2.1. Some definitions - 86

2.2. Specification of the General Model - 87

2.3. Stochastic Assumptions - 88

3. Estimation 90

3.1. Principles of the Gibbs Sampler - 90

3.2. Application - 91

4. Data 94

5. Results 96

5.1. Women with a Vocational-Technical Degree (Basic, CAP - BEP) - 96

5.2. Men with a Vocational Technical degree - 99

5.3. Women with Technical College and Undergraduate University (BTS, DEUG) . 99

5.4. Men with a Technical College or a Undergraduate University degree (BTS,

DEUG) - 101

iii

6. Conclusion 101

A. Appendix A 103

A.1. Mobility equation - 103

A.2. Wage equation - 104

A.3. Participation equation - 105

A.4. Initial equations - 107

A.5. Latent variables - 108

A.5.1. Latent participation - 108

A.5.2. Latent mobility - 109

A.5.3. Latent location - 110

A.6. Variance-Covariance Matrix of Residuals - 111

A.7. Variance-Covariance Matrices of Effects - 111

A.8. Firm effects - 113

B. Results 116

Chapitre 3 : Is civil-servant human capital sector-specific? 146

1. Introduction 146

2. The Search Model 148

3. The data 153

3.1. A brief description - 153

3.2. Some descriptive statistics on balanced data - 154

4. Econometric model and estimation principles 156

4.1. Model - 156

4.2. Likelihood and estimation principles - 158

5. Results 161

5.1. Identification - 161

5.2. Estimations - 161

5.2.1. Estimation results - 161

iv

5.2.2. Types - 166

6. Simulations 166

6.1. Model fit - 166

6.2. What private wages would civil servants have? Counterfactual distributions . . 169

7. Conclusion 173

A. Structural model 174

B. Descriptive Statistics 179

C. Implementation 180

D. Cross-section results 180

E. Quantile differences between the public log of wage distributions and the counterfactual

distribution 185

Chapitre 4 : Who is confronted to insecure labor market histories? Some evidence

based on the French labor market transitions. 188

1. Introduction 188

2. Data 191

2.1. Summary statistics and representativeness - 192

2.2. Descriptive statistics on transitions - 195

3. Methodology: the conditional confined-unconfined worker model 196

4. Results 199

4.1. Sectorisation in the labor market - 199

4.1.1. The confined movers - 200

4.1.2. The nonparticipant stayers - 201

4.1.3. The stable-job stayers - 202

4.2. Dynamics on the labor market - 202

4.2.1. Confined and unconfined mover transitions - 202

v

5. Robustness analysis 204

5.1. Heckman-Singer approach - 204

5.2. Specification tests: stability of transition matrices across gender - 206

6. Conclusion 209

A. Stationary occupation probabilities 210

B. Darmois-type test for coefficient equality across subsamples 211

C. Detailed results 211

C.1. Women between 30 and 49 - 211

C.2. Men between 30 and 49 - 212

Bibliographie 218

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