approximation algorithm is provided that enables accurate computation of the estimator in very large datasets. We study the large … sample properties of our estimator allowing the number of regressors to grow in proportion to the number of observations …

In the early 1940s, Haavelmo proposed a probabilistic structure for econometric modeling, aiming to make econometrics … initiated his own seminal development of statistical decision theory. Haavelmo favorably cited Wald, but econometrics …

investigate the performance of stacked DID estimators. We show that the most basic stacked estimator does not identify the target … bias can be eliminated using corrective sample weights. We present a weighted stacked DID estimator, and show that it … correctly identifies the target aggregate, providing justification for using the estimator in applied work …

encountered often in health and other applications. The paper's main motivation is that the applied econometrics literature lacks …

. We provide constructive arguments for the identification of model primitives, and establish the estimator's consistency … illustrate the estimator's good finite-sample performance in a Monte Carlo study, and we estimate a labor supply model …