Empirical research in economics often examines the behavior of agents located in a geographic space. In such cases, statistical inference is complicated by the interdependence of economic outcomes across locations. A common approach to account for this dependence is to cluster standard errors...

We provide the first analysis of racial in-group bias in Type-I and Type-II errors. Using player-referee matched data from NBA games we show that there is no overall racial bias or in-group bias in foul calls made by referees. Similarly, there is no racial bias or in-group bias in Type-I errors...

This paper proposes a minimum distance (MD) estimator to estimate panel regression models with measurement error. The model considered is more general than examined in the literature in that (i) measurement error can be non-classical in the sense that they are allowed to be correlated with the...

Broadband availability data collected by the Federal Communications Commission (“FCC”) using its Form 477 are heavily criticized as inaccurate. These data certainly overstate availability since a census block is indicated as having broadband throughout the block even if only a single home in...

In analyses of minimum wages, positive "ripple effects" and subminimum wages are difficult to distinguish from measurement error. Indeed, prior work posits that a simple, symmetric measurement process may underlie both phenomena in Current Population Survey data for the full working age...

We develop a practical way of addressing the Errors-In-Variables (EIV) problem in the Generalized Method of Moments (GMM) framework. We focus on the settings in which the variance of the measurement errors is a fraction of that of the mismeasured variables, which is typical for empirical...