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Labor supply as a discrete choice among latent jobs: Unobserved heterogeneity and identification

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Abstract

This paper discusses aspects of a framework for modeling labor supply where the notion of job choice is fundamental. In this framework, workers are assumed to have preferences over latent job opportunities belonging to worker-specific choice sets from which they choose their preferred job. The observed hours of work and wage is interpreted as the job-specific hours and wage of the chosen job. The main contribution of this paper is an analysis of the identification problem of this framework under various conditions, when conventional cross-section micro-data are applied. The modeling framework is applied to analyze labor supply behavior for married/cohabiting couples using Norwegian micro data. Specifically, we estimate two model versions with in the general framework. Based on the empirical results, we discuss further qualitative properties of the model versions. Finally, we apply the preferred model version to conduct a simulation experiment of a counterfactual policy reforms.

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  • John K. Dagsvik & Zhiyang Jia, 2014. "Labor supply as a discrete choice among latent jobs: Unobserved heterogeneity and identification," Discussion Papers 786, Statistics Norway, Research Department.
    • Handle: RePEc:ssb:dispap:786
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    Cited by:

    1. Decoster, André & Capéau, Bart, 2016. "Getting tired of work, or re-tiring in absence of decent job opportunities? Some insights from an estimated Random Utility/Random Opportunity model on Belgian data," EUROMOD Working Papers EM4/16, EUROMOD at the Institute for Social and Economic Research.

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    More about this item

    Keywords

    labor supply; non-pecuniary job attributes; latent choice sets; random utility models; identification;
    All these keywords.

    JEL classification:

    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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