Maximum likelihood estimation has been the workhorse of statistics for decades, but alternative methods, going under the name “regularization,” are proving to have lower predictive variance. Regularization shrinks fitted values towards the overall mean, much like credibility does. There is...

We develop an R package panelView and a Stata package panelview for panel data visualization. They are designed to assist causal analysis with panel data and have three main functionalities: (1) they plot the treatment status and missing values in a panel dataset; (2) they visualize variables of...

Herein we attempt to quantify Tom McClellan’s notion of Dance Steps between two series of data, often of differing time periods (a current, or dependent and a previous, or independent period data series), looking for similarities in the turning points to use as a reference for the future...

We propose a nonparametric Bayesian approach for conducting inference on probabilistic surveys. We use this approach to study whether U.S. Survey of Professional Forecasters density projections for output growth and inflation are consistent with the noisy rational expectations hypothesis. We...

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...

This paper examines the econometric causal model for policy analysis developed by the seminal ideas of Ragnar Frisch and Trygve Haavelmo. We compare the econometric causal model with two popular causal frameworks: Neyman-Holland causal model and the do-calculus. The Neyman-Holland causal model...

In this paper, we consider an optimal stopping problem that addresses model uncertainty. Model uncertainty is the uncertainty affecting the model assumptions, e.g., the assumed form of the probability distribution, the parameters embedded in the probability distribution. The result presented in...