Indirect Inference Estimation of a First-Order Dynamic Panel Data Model View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2021-11-29

AUTHORS

Yong Bao

ABSTRACT

A new estimator is proposed in this paper that inverts a binding function that is based on the asymptotic bias of the within-groups (WG) estimator in a first-order dynamic panel model with fixed effects under the asymptotic regime of large N and finite T. The new estimator is in the spirit of indirect inference (II) and corrects the inconsistency of the WG estimator. It is simulation-free, does not rely on any distributional assumption on the idiosyncratic error term, and is asymptotically normally distributed. Monte Carlo results indicate its good finite-sample performance in comparison with other consistent estimators. More... »

PAGES

79-98

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s40953-021-00264-w

DOI

http://dx.doi.org/10.1007/s40953-021-00264-w

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1143455453


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