We propose a generalization of the linear quantile regression model to accommodate possibilities afforded by panel data. Specifically, we extend the correlated random coefficients representation of linear quantile regression (e.g., Koenker, 2005; Section 2.6). We show that panel data allows the...

We propose several multivariate variance ratio statistics. We derive the asymptotic distribution of the statistics and scalar functions thereof under the null hypothesis that returns are unpredictable after a constant mean adjustment (i.e., under the weak form Efficient Market Hypothesis). We do...

We develop an equilibrium lifecycle model of education, marriage and labor supply and consumption in a transferable utility context. Individuals start by choosing their investments in education anticipating returns in the marriage market and the labor market. They then match based on the...

The impact of school resources on the quality of education in developing countries may depend crucially on whether resources are targeted efficiently. In this paper we use a randomized experiment to analyze the impact of a school grants program in Senegal, which decentralized a portion of the...

We study identification and estimation in first-price auctions with risk-averse bidders and selective entry, building on a flexible entry and bidding framework we call the Affiliated Signal with Risk Aversion (AS-RA) model. This framework extends the AS model of Gentry and Li (2014) to...

This paper estimates a structural model of private provision of public goods to provide some new empirical evidence on individuals' strategic contributing behaviors. In the model, individuals' contributing behaviors are allowed to be heterogenous and time-varying. We show that all the main...

Fixed effects estimators of nonlinear panel data models can be severely biased because of the incidental parameter problem. We develop analytical and jackknife bias corrections for nonlinear models with both individual and time effects. Under asymptotic sequences where the time-dimension (T)...

Common high-dimensional methods for prediction rely on having either a sparse signal model, a model in which most parameters are zero and there are a small number of non-zero parameters that are large in magnitude, or a dense signal model, a model with no large parameters and very many small...

We investigate a nonparametric panel model with heterogeneous regression functions. In a variety of applications, it is natural to impose a group structure on the regression curves. Specifically, we may suppose that the observed individuals can be grouped into a number of classes whose members...

We propose an alternative Ratio Statistic for measuring predictability of stock prices. Our statistic is based on actual returns rather than logarithmic returns and is therefore better suited to capturing price predictability. It captures not only linear dependence in the same way as the...