Arbeitspapier
Generalized Dynamic Panel Data Models with Random Effects for Cross-Section and Time
An exact maximum likelihood method is developed for the estimation of parameters in a nonlinear non-Gaussian dynamic panel data model with unobserved random individual-specific and time-varying effects. We propose an estimation procedure based on the importance sampling technique. In particular, a sequence of conditional importance densities is derived which integrates out all random effects from the joint distribution of endogenous variables. We disentangle the integration over both the cross-section and the time series dimensions. The estimation method facilitates the flexible modeling of large panels in both dimensions. We evaluate the method in a Monte Carlo study for dynamic panel data models with observations from the Student's t distribution. We finally present an extensive empirical study into the interrelationships between the economic growth figures of countries listed in the Penn World Tables. It is shown that our dynamic panel data model can provide an insightful analysis of common and heterogeneous features in world-wide economic growth.
- Sprache
-
Englisch
- Erschienen in
-
Series: Tinbergen Institute Discussion Paper ; No. 12-009/4
- Klassifikation
-
Wirtschaft
Multiple or Simultaneous Equation Models: Panel Data Models; Spatio-temporal Models
Model Construction and Estimation
International Business Cycles
- Thema
-
Panel data
Non-Gaussian
Importance sampling
Random effects
Student's t
Economic growth
Stochastischer Prozess
Maximum-Likelihood-Methode
Statistische Verteilung
Monte-Carlo-Methode
Schätzung
Wirtschaftswachstum
Welt
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Mesters, Geert
Koopman, Siem Jan
- Ereignis
-
Veröffentlichung
- (wer)
-
Tinbergen Institute
- (wo)
-
Amsterdam and Rotterdam
- (wann)
-
2012
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:41 MEZ
Datenpartner
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Objekttyp
- Arbeitspapier
Beteiligte
- Mesters, Geert
- Koopman, Siem Jan
- Tinbergen Institute
Entstanden
- 2012
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