We formulate and estimate a structural, static model of household labor supply and multiple welfare program participation. Given the complicated nature of both the income tax schedule and the benefit rules for different welfare programs, we use a detailed micro simulation model to generate...

In this Paper, we formulate and estimate a structural, static model of household labour supply and multiple welfare programme participation. Given the complicated nature of both the income tax schedule and the benefit rules for different welfare programmes, we use unique access to a very...

In this paper, we formulate and estimate a structural, static model of household labor supply and multiple welfare program participation. Given the complicated nature of both the income tax schedule and the benefit rules for different welfare programs, we use unique access to a very detailed...

Previous studies on gender wage discrimination have relied on OLS when estimating the wage equations. However, there exists a number of recent studies, devoted to estimating the return to education, that have shown that OLS may produce biased estimates for a number of reasons. Consequently, if...

We estimate the relationship between wages and occupational gender segregation in Sweden. Because of high wage equality in Sweden compared to the U.S., we expect a lower wage penalty of job femaleness in Sweden than in the U.S. Our results supports this hypothesis. We also investigate how the...

Previous studies on the gender wage gap have relied on OLS when estimating the wage equations. However, a number of recent studies, devoted to estimating the return to education, have shown that OLS may produce biased estimates for a number of reasons. As a consequence, previous results...

This Paper analyses the persistence of poverty in Sweden using a hazard rate model based on multiple spells. The model also accounts for unobserved heterogeneity and possibly endogenous initial conditions. We estimate the model on a large representative Swedish panel dataset, LINDA, for the...