Arbeitspapier
Exploiting Information from Singletons in Panel Data Analysis: A GMM Approach
We propose a novel procedure, built within a Generalized Method of Moments framework, which exploits unpaired observations (singletons) to increase the efficiency of longitudinal fixed effect estimates. The approach allows increasing estimation efficiency, while properly tackling the bias due to unobserved time-invariant characteristics. We assess its properties by means of Monte Carlo simulations, and apply it to a traditional Total Factor Productivity regression, showing efficiency gains of approximately 8-9 percent.
- Language
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Englisch
- Bibliographic citation
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Series: IZA Discussion Papers ; No. 12465
- Classification
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Wirtschaft
Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models
Multiple or Simultaneous Equation Models: Panel Data Models; Spatio-temporal Models
Model Construction and Estimation
- Subject
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efficient estimation
panel data
singletons
unobserved heterogeneity
GMM
- Event
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Geistige Schöpfung
- (who)
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Bruno, Randolph Luca
Magazzini, Laura
Stampini, Marco
- Event
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Veröffentlichung
- (who)
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Institute of Labor Economics (IZA)
- (where)
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Bonn
- (when)
-
2019
- Handle
- Last update
-
10.03.2025, 11:41 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
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
- Bruno, Randolph Luca
- Magazzini, Laura
- Stampini, Marco
- Institute of Labor Economics (IZA)
Time of origin
- 2019
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