Arbeitspapier
Improved errors-in-variables estimators for grouped data
Grouping models are widely used in economics but are subject to nite sample bias. I show that the standard errors-in-variables estimator (EVE) is exactly equivalent to the Jackknife Instrumental Variables Estimator (JIVE), and use this relationship to develop an estimator which, unlike EVE, is unbiased in nite samples. The theoretical results are demonstrated using Monte Carlo experiments. Finally, I implement a model of intertemporal male labor supply using microdata from the United States Census. There are sizeable differences in the wage elasticity across estimators, showing the practical importance of the theoretical issues even when the sample size is quite large.
- Language
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Englisch
- Bibliographic citation
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Series: UCD Centre for Economic Research Working Paper Series ; No. WP06/02
- Classification
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Wirtschaft
- Subject
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psuedo-panel
small sample bias
labor supply
Mathematische Ökonomie
Arbeitsangebot
Lohn
Elastizität
Stichprobenverfahren
Monte-Carlo-Methode
- Event
-
Geistige Schöpfung
- (who)
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Devereux, Paul J.
- Event
-
Veröffentlichung
- (who)
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University College Dublin, UCD School of Economics
- (where)
-
Dublin
- (when)
-
2006
- Handle
- Last update
-
10.03.2025, 11:45 AM CET
Data provider
This object is provided by:
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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Devereux, Paul J.
- University College Dublin, UCD School of Economics
Time of origin
- 2006
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