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Through Monte Carlo experiments the small sample behavior is examinedof various inference techniques for dynamic panel …
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We consider likelihood inference and state estimation by means of importance sampling for state space models with a … are presented that lead to a more effective implementation of importance sampling for state space models. An illustration …
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Several lessons learned from a Bayesian analysis of basic economic time series models by means of the Gibbs sampling … Panel Data model. We discuss issues involved when drawing Bayesian inference on regression parameters and variance …
Persistent link: https://www.econbiz.de/10011349180
We consider the dynamic factor model where the loading matrix, the dynamic factors and the disturbances are treated as latent stochastic processes. We present empirical Bayes methods that enable the efficient shrinkage-based estimation of the loadings and the factors. We show that our estimates...
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The relative magnitudes are compared of successive terms in a higher-order asymptotic expansion of the bias of the LSDV estimator in dynamic panels. We find that the leading term accounts for the major part of the actual bias in small samples. This implies that bias correction procedures can be...
Persistent link: https://www.econbiz.de/10011327523
dynamic panel data models. To illustrate particular pitfalls some further Monte Carlo results are produced, obtained from a … moments (GMM) estimators in homoskedastic stable zero-mean panel AR(1) models with random individual specific effects. We …
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