Labor market uncertainty, sectoral earnings, and private sector labor supply in Russia
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The development of a vibrant private sector has been one of the key failures of the transitional period in Russia. This dissertation develops a theoretical model of individual labor supply behavior under uncertainty. An individual's decision to work in the private sector is modeled as a function of: (1) The difference in expected earnings between sectors; (2) The difference in sectoral earnings variability, where the effect variability has on decision-making depends on the individual's ability to smooth consumption both intertemporally and within their household; and (3) Individual preferences towards a particular sector. In order to estimate the structural labor supply model, it is necessary to predict individual expected earnings in both the government and private sector regardless of the actual sector of employment. Thus, the dissertation develops a two-stage econometric model to estimate sectoral earnings equations, which controls for two possible sources of selection bias: (1) Self-selection into the workforce; and (2) Self-selection into either the private or government sector, and allows for simultaneity in the selection decisions. It then uses representative panel data from the Russian Longitudinal Monitoring Survey for the years 1994-1996 & 1998 to estimate the sectoral earnings equations and the structural labor supply model. Three important results are found in the dissertation: (1) Sectoral earnings equations are strongly biased when failing to control for both sources of selection bias; (2) Private sector earnings variability discourages private sector employment for individuals with constrained consumption smoothing ability; and (3) Individuals ex-ante reduce their exposure to risk by sharing income with other household members and diversifying the portfolio of jobs held by the household.
Stillman, Steven. (2000). Labor market uncertainty, sectoral earnings, and private sector labor supply in Russia. Doctoral dissertation, University of Washington.
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