Arbeitspapier

Cluster-robust inference: A guide to empirical practice

Methods for cluster-robust inference are routinely used in economics and many other disciplines. However, it is only recently that theoretical foundations for the use of these methods in many empirically relevant situations have been developed. In this paper, we use these theoretical results to provide a guide to empirical practice. We do not attempt to present a comprehensive survey of the (very large) literature. Instead, we bridge theory and practice by providing a thorough guide on what to do and why, based on recently available econometric theory and simulation evidence. The paper includes an empirical analysis of the effects of the minimum wage on teenagers using individual data, in which we practice what we preach.

Sprache
Englisch

Erschienen in
Series: Queen’s Economics Department Working Paper ; No. 1456

Klassifikation
Wirtschaft
Hypothesis Testing: General
Statistical Simulation Methods: General
Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models
Thema
clustered data
grouped data
cluster-robust variance estimator
CRVE
robust inference
wild cluster bootstrap

Ereignis
Geistige Schöpfung
(wer)
MacKinnon, James G.
Nielsen, Morten Ørregaard
Webb, Matthew
Ereignis
Veröffentlichung
(wer)
Queen's University, Department of Economics
(wo)
Kingston (Ontario)
(wann)
2021

Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • MacKinnon, James G.
  • Nielsen, Morten Ørregaard
  • Webb, Matthew
  • Queen's University, Department of Economics

Entstanden

  • 2021

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