Estimating Labor Supply at the Extensive Margin in the presence of Sample Selection Bias

This paper illustrates the static labor supply model using a large cross sectional data set encompassing the countries of Great Britain. I focus on estimating the labor force participation decision what is referred in the literature as labor supply on the extensive margin. The sensitivity along the extensive margin is expressed by calculating two specifications of a participation elasticity, defined as the percentage change in the labor force participation rate induced by a one percentage change in the gross wage or the net effective wage. The elasticities of labor supply are computed separately for men and women. The basic problem in estimating labor supply models with non-workers is unobservability of their wage rates that makes a non-random nature of the sample. I follow Heckman (1979) approach to correct for sample selection bias by estimating wage equation for workers and non-workers. Predicted wage rates along with non-wage incomes and a range of household characteristics are used in the probit regression model while the standard errors of the predicted wage rates were bootstrapped to correct for error-prone sampling distribution of predicted wage regressors that are non-linear functions of the estimated model parameters. I find that semi-elasticities of labor supply on the extensive margin with respect to gross wage are 0.09 and -0.03 percentage points for men and women, respectively. Using the net effective wage rate these elasticities are 0.10 and -0.01 for men and women, respectively. Both estimated elasticities are marginally larger in the net effective wage specification which I interpreted as a marginal incentive for men to join the labor market and less disincentive effect for women to withdraw from the labor market.