Arbeitspapier
Estimating SUR systems wiht random coefficients: The unbalanced panel data case
A system of regression equations (SURE) for analyzing panel data with random heterogeneity in intercepts and coefficients, and unbalanced panel data is considered. A Maximum Likelihood (ML) procedure for joint estimation of all parameters is described. Since its implementation for numerical computation is complicated, simplified procedures are presented. The simplifications essentially concern the estimation of the covariance matrices of the random coefficients. The application and 'anatomy' of the proposed algorithm for modified ML estimation is illustrated by using panel data for output, inputs and costs for 111 manufacturing firms observed up to 22 years.
- Language
-
Englisch
- Bibliographic citation
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Series: Memorandum ; No. 22/2012
- Classification
-
Wirtschaft
Multiple or Simultaneous Equation Models: Panel Data Models; Spatio-temporal Models
Model Construction and Estimation
Computational Techniques; Simulation Modeling
Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
- Subject
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Panel Data
Unbalanced data
Random Coefficients
Heterogeneity
Regression Systems , Iterated Maximum Likelihood
Panelforschung
Modellierung
Maximum-Likelihood-Methode
Schätztheorie
- Event
-
Geistige Schöpfung
- (who)
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Biørn, Erik
- Event
-
Veröffentlichung
- (who)
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University of Oslo, Department of Economics
- (where)
-
Oslo
- (when)
-
2012
- Handle
- Last update
-
20.09.2024, 8:23 AM CEST
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
- Biørn, Erik
- University of Oslo, Department of Economics
Time of origin
- 2012
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