Inference using difference-in-differences with clustered data requires care. Previous research has shown that, when there are few treated clusters, t-tests based on cluster-robust variance estimators (CRVEs) severely overreject, and different variants of the wild cluster bootstrap can either...

This paper assesses the performance of 355 actively managed Japanese Equity Mutual Funds between April 2011 and April 2016. The equal weight portfolio and Jensen’s alpha measures of active management provide strong evidence that Japanese Mutual Funds fail to outperform the benchmark...

This paper provides inference methods for best linear approximations to functions which are known to lie within a band. It extends the partial identifi cation literature by allowing the upper and lower functions de ning the band to carry an index, and to be unknown but parametrically or...

In many fields of economics, and also in other disciplines, it is hard to justify the assumption that the random error terms in regression models are uncorrelated. It seems more plausible to assume that they are correlated within clusters, such as geographical areas or time periods, but...

We study two cluster-robust variance estimators (CRVEs) for regression models with clustering in two dimensions and give conditions under which t-statistics based on each of them yield asymptotically valid inferences. In particular, one of the CRVEs requires stronger assumptions about the nature...

We discuss when and how to deal with possibly clustered errors in linear regression models. Specifically, we discuss situations in which a regression model may plausibly be treated as having error terms that are arbitrarily correlated within known clusters but uncorrelated across them. The...

This preliminary note investigates perception bias: To what extent do individual opinions confound reality? We estimate the relative gap between self-declared estimates and real data. We asked a sample of Philippine respondents about the incidence of diabetes and smartphone usage in their...

The present study applies a bootstrapped data envelopment analysis (DEA) procedure to compute bias-corrected measures of agricultural total factor productivity (TFP) change and its components (technical change and technical efficiency change) using a panel data of 19 regions of Bangladesh...