In this paper we propose a new variance estimator for OLS as well as for nonlinear estimators such as logit, probit and GMM, that provcides cluster-robust inference when there is two-way or multi-way clustering that is non-nested. The variance estimator extends the standard cluster-robust...

Researchers have increasingly realized the need to account for within-group dependence in estimating standard errors of regression parameter estimates. The usual solution is to calculate cluster-robust standard errors that permit heteroskedasticity and within-cluster error correlation, but...

Using nonparametric techniques, we develop a methodology for estimating conditional alphas and betas and long-run alphas and betas, which are the averages of conditional alphas and betas, respectively, across time. The tests can be performed for a single asset or jointly across portfolios. The...

It is widely believed that correlations between international equity markets tend to increase in highly volatile bear markets. This has led some to doubt the benefits of international diversification. This article solves the dynamic portfolio choice problem of a US investor faced with a...

The theoretical and empirical econometric literatures on long memory and regime switching have evolved largely independently, as the phenomena appear distinct. We argue, in contrast, that they are intimately related, and we substantiate our claim in several environments, including a simple...

Since Black, Jensen, and Scholes (1972) and Fama and MacBeth (1973), the two-pass cross-sectional regression (CSR) methodology has become the most popular approach for estimating and testing asset pricing models. Statistical inference with this method is typically conducted under the assumption...

Matching estimators (Rubin, 1973a, 1977; Rosenbaum, 2002) are widely used in statistical data analysis. However, the large sample distribution of matching estimators has been derived only for particular cases (Abadie and Imbens, 2006). This article establishes a martingale representation for...

Estimation of average treatment effects under unconfoundedness or exogenous treatment assignment is often hampered by lack of overlap in the covariate distributions. This lack of overlap can lead to imprecise estimates and can make commonly used estimators sensitive to the choice of...

In this paper we address the following question: To what extent is the hypothesis that voters vote sincerely testable or falsifiable? We show that using data only on how individuals vote in a single election, the hypothesis that voters vote sincerely is irrefutable, regardless of the number of...

Non-random assignment of students to teachers can bias value added estimates of teachers' causal effects. Rothstein (2008a, b) shows that typical value added models indicate large counter-factual effects of 5th grade teachers on students' 4th grade learning, indicating that classroom assignments...