We address the bias from using potential vs. actual experience in earnings models. Statistical tests reject the classical errors-in-variable framework. The nature of the measurement error is best viewed as a model misspecification problem. We correct for this by modeling actual experience as a...

We document the educational integration of immigrant children with a focus on the link between family size and educational decisions and distinguishing particularly between first- and second-generation immigrants and between source country groups. First, for immigrant adolescents, we show...

This paper identifies and quantifies the contribution of a set of covariates in affecting levels and over time changes of happiness inequality. Using a decomposition methodology based on RIF regression, we analyse the increase in happiness inequality observed in Germany between 1992 and 2007,...

Our objective is to analyse the role of teacher and school quality to explain differences in students' educational outcomes. With this aim, we use PISA microdata for 10 middle income and 2 high income countries and we apply decomposition methods in order to identify the role of these factors for...

In this paper I demonstrate, both theoretically and empirically, that the interpretation of regression estimates of between-group differences in economic outcomes depends on the relative sizes of subpopulations under study. When the disadvantaged group is small, regression estimates are similar...

We revisit the much-investigated relationship between schooling and health, focusing on cognitive abilities at older ages using the Harmonized Cognition Assessment Protocol in the Health & Retirement Study. To address endogeneity concerns, we employ a nonparametric partial identification...

To assess the impact of tax-benefit policy changes on income distribution over time, we suggest a methodology based on counterfactual simulations. We start by decomposing changes in inequality/poverty indices into three contributions: reforms of the tax-benefit structure (rules, rates, etc.),...

Proxy variables are often used in linear regression models with the aim of removing potential confounding bias. In this paper we formalise proxy variables within the potential outcome framework, giving conditions under which it can be shown that causal effects are nonparametrically identified....

Causal effects of a policy change on hazard rates of a duration outcome variable are not identified from a comparison of spells before and after the policy change, if there is unobserved heterogeneity in the effects and no model structure is imposed. We develop a discontinuity approach that...