We develop methodology for estimation and inference using machine learning to enrich economic models. Our framework takes a standard economic model and recasts the parameters as fully flexible nonparametric functions, to capture the rich heterogeneity based on potentially high dimensional or...

We develop methodology for estimation and inference using machine learning to enrich economic models. Our framework takes a standard economic model and recasts the parameters as fully flexible nonparametric functions, to capture the rich heterogeneity based on potentially high dimensional or...

Decomposition of a bivariate rank dependent index, such as the concentration index, is commonly used to explain socioeconomic inequalities in health. We introduce a new decomposition technique based on the recentered influence function that yields the marginal effects of covariates on the...

Despite tremendous recent interest in the subject of student debt by both researchers and policy makers, little is known about how the distribution of college graduate debt has been evolving and what factors can explain it. We use National Postsecondary Student Aid Study data from 1990 through...

Despite tremendous recent interest in the subject of student debt by both researchers and policy makers, little is known about how the distribution of college graduate debt has been evolving and what factors can explain it. We use National Postsecondary Student Aid Study data from 1990 through...

In this paper I investigate the impact of informality on earnings inequality in Russia using RLMS-HSE data for 2000-2010. I find that during the whole period earnings inequality was substantially higher in the informal sector. Informality increases earnings polarization, thereby widening both...