Search Results - subject:"Cluster bootstrap"

Asymptotic theory and wild bootstrap inference with clustered errors

Djogbenou, Antoine A.; MacKinnon, James G.; Nielsen, … - 2019

Persistent link: https://www.econbiz.de/10012063541

Randomization inference for difference-in-differences with few treated clusters

MacKinnon, James G.; Webb, Matthew - 2019

different variants of the wild cluster bootstrap can either overreject or underreject dramatically. We study two randomization …

Persistent link: https://www.econbiz.de/10011962945

How cluster-robust inference is changing applied econometrics

MacKinnon, James G. - 2019

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...

Persistent link: https://www.econbiz.de/10012183351

Wild bootstrap and asymptotic inference with multiway clustering

MacKinnon, James G.; Nielsen, Morten Ørregaard; Webb, … - 2019

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...

Persistent link: https://www.econbiz.de/10012183373

When and how to deal with clustered errors in regression models

MacKinnon, James G.; Webb, Matthew - 2019

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...

Persistent link: https://www.econbiz.de/10012183510

Asymptotic Theory and Wild Bootstrap Inference with Clustered Errors

Djogbenou, Antoine A.; MacKinnon, James G.; Nielsen, … - 2018

, focusing on the wild cluster bootstrap and the ordinary wild bootstrap. We state conditions under which both asymptotic and …

Persistent link: https://www.econbiz.de/10011939450

Wild Bootstrap Randomization Inference for Few Treated Clusters

MacKinnon, James G.; Webb, Matthew - 2018

cluster-robust variance estimator (CRVE) can severely over-reject. Although procedures based on the wild cluster bootstrap …

Persistent link: https://www.econbiz.de/10011939455

Fast and Wild: Bootstrap Inference in Stata Using boottest

Roodman, David Malin; MacKinnon, James G.; Nielsen, … - 2018

-Rubin tests, optionally with (multi-way) clustering. We review the main ideas of the wild cluster bootstrap, offer tips for use … reghdfe, as well as many estimation commands based on maximum likelihood. Although it is designed to perform the wild cluster … bootstrap, boottest can also perform the ordinary (non-clustered) version. Wrappers offer classical Wald, score/LM, and Anderson …

Persistent link: https://www.econbiz.de/10011939457

Wild bootstrap randomization inference for few treated clusters

MacKinnon, James G.; Webb, Matthew - 2018

cluster-robust variance estimator (CRVE) can severely over-reject. Although procedures based on the wild cluster bootstrap …

Persistent link: https://www.econbiz.de/10011809450

Fast and wild : bootstrap inference in stata using boottest

Roodman, David Malin; MacKinnon, James G.; Nielsen, … - 2018

Persistent link: https://www.econbiz.de/10011872385