Conditional Logit with one Binary Covariate: Link between the Static and Dynamic Cases

Disentangling state dependence from unobserved heterogeneity is a common issue in economics. It arises for instance when studying transitions between different states on the labor market. When the outcome variable is binary, one of the usual strategies consists in using a conditional logit model with an appropriate conditioning suitable for a dynamic framework. Although static conditional logit procedures are widely available, these procedures cannot be used directly in a dynamic framework. Indeed, it is inappropriate to use them with a lag dependent variable in the list of regressors. Moreover, reprogramming this kind of procedures in a dynamic framework can prove quite cumbersome because the likelihood can have a very high number of terms when the number of periods increases. Here, we consider the case of a conditional logit model with one binary regressor which can be either exogenous or the lagged dependent variable itself. We provide closed forms for the conditional likelihoods in both cases and show the link between them. These results show that in order to evaluate a conditional logit model with one lag of state dependence and no other covariate, it is possible to simply generate a two variable dataset and use standard procedures originally intended for models without state dependence. Moreover, the closed forms help reduce the computational burden even in the static case in which preimplemented procedures usually exist.conditional logit, state dependence, binary model, incidental parameter

National Origin Differences in Wages and Hierarchical Positions - Evidence on French Full-Time Male Workers from a matched Employer-Employee Dataset

This paper estimates the differences in wages and hierarchical positions that can be attributed to national origin in France. Our data come from a matched employer-employee wage survey performed in 2002. The business survey provides very reliable wage data which are matched to many individual-level variables collected in a household survey. The sample of male full-time workers is decomposed into three sub-samples according to the parents' birthplace (France, North Africa and Southern Europe). The large number of executives in the sample allows us to perform a switching regression model of wage determination and occupational employment. We adapt and extend existing decomposition methods to this framework: while usual methods only take care of selection issues, we develop here a methodology which also properly takes into account composition effects due to differences in hierarchical positions when comparing mean wage gaps. Moreover the method we use only requires model estimation on the reference population and therefore yields more precise results when the sample size of the potentially discriminated group is small. Our results show no wage discrimination but a certain degree of occupational segregation yielding composition effects. Moreover, differences in the returns to some of the individual characteristics including higher diplomas might reveal mechanisms of statistical discrimination on the labor market.immigration, discrimination, wage gap, France

Learning, Incomplete Contracts and Export Dynamics: Theory and Evidence from French Firms

We consider a model where exporting requires finding a local partner in each market. Contracts are incomplete and exporters must learn the reliability of their partners through experience. In the model, export behavior is state-dependent due to matching frictions, although there are no sunk costs. Better legal institutions alleviate contracting frictions especially in sectors with large contracting problems. Thus, measures of legal quality help reduce the risk that a match between an exporter and a local distributor splits, and they are all the more effective in sectors that are more exposed to hold-up problems. Moreover, the breaking risk declines with the age of the relationship, as unreliable partners are weeded out. We find strong evidence in favor of the model's predictions when testing them with a French dataset that includes information on firm-level exports by destination country.Trade Dynamics, Learning, Incomplete Contracts, State dependence, Firm-level Trade Data

Employment and wages of immigrants and descendants of immigrants: Measures of inequality and perceived discrimination

Descendants of immigrants of non-European origin are much more likely to be unemployed than people in the French mainstream population, even after controlling for differences in structural characteristics (education, experience, age, region of residence, etc.). After entering employment, their wages are lower than those of their mainstream counterparts, although the wage penalty is relatively small. These groups also feel strongly that they are subject to discrimination in recruitment procedures and career advancement. When the two ways of measuring discrimination are matched against each other, we find that the strength of perceived discrimination at individual level is correlated with the degree of inequality measured on the labour market. Individuals who are unemployed despite observed personal characteristics that would be favourable to employment if they belonged to the mainstream population are also those who express the strongest perception of discrimination

Employment and Wages of Immigrants and Descendants of Immigrants: Measures of Inequality and Perceived Discrimination

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