Arbeitspapier
Inference with Difference-in-Differences Revisited
A growing literature on inference in difference-in-differences (DiD) designs with grouped errors has been pessimistic about obtaining hypothesis tests of the correct size, particularly with few groups. We provide Monte Carlo evidence for three points: (i) it is possible to obtain tests of the correct size even with few groups, and in many settings very straightforward methods will achieve this; (ii) the main problem in DiD designs with grouped errors is instead low power to detect real effects; and (iii) feasible GLS estimation combined with robust inference can increase power considerably whilst maintaining correct test size again, even with few groups.
- Sprache
-
Englisch
- Erschienen in
-
Series: IZA Discussion Papers ; No. 7742
- Klassifikation
-
Wirtschaft
Hypothesis Testing: General
Estimation: General
Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
- Thema
-
difference in differences
hypothesis test
power
cluster robust
feasible GLS
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Brewer, Mike
Crossley, Thomas F.
Joyce, Robert
- Ereignis
-
Veröffentlichung
- (wer)
-
Institute for the Study of Labor (IZA)
- (wo)
-
Bonn
- (wann)
-
2013
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:44 MEZ
Datenpartner
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Objekttyp
- Arbeitspapier
Beteiligte
- Brewer, Mike
- Crossley, Thomas F.
- Joyce, Robert
- Institute for the Study of Labor (IZA)
Entstanden
- 2013