Session-specific features of a laboratory experiment, if those exist, do not disappear by clustering standard errors at … typical controlled laboratory experiment where subjects make choices in the same environment repeatedly, clustering at a …

become controversial in the wake of recent demonstrations showing that this type of regression is prone to bias in small … samples. Bias may even remain when units are sampled from a larger population of infnite size. This paper uses a combination … of simulated and actual examples to show that, as a practical matter, bias tends to be negligible when the sample size is …

In a recent study, Beccarini showed that one can eliminate or reduce the bias in OLS regression estimators caused by an …, then elimination or reduction of the bias requires the estimation of a K-component mixture model. In his Monte Carlo …

, therefore Monte Carlo experiments are provided in order to explore the performance of the method. A companion software is …

We show how using censored regressors leads to expansion bias, or estimated effects that are proportionally too large …. We show the necessity of this effect in bivariate regression and illustrate the bias using results for normal regressors …. We study the bias when there is a censored regressor among many regressors, and we note how censoring can work to undo …

Interference between units may pose a threat to unbiased causal inference in randomized controlled experiments … experiments. Naive estimators of interference that attempt to exploit the proximity of units may be biased because simple … demonstrated through simulation studies and, using this method, interference between units is detected in a field experiment …

the treatment estimator. I show that in each experiment satisfying the linear model assumptions, there exists at least one …