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A comparison of two model averaging techniques with an application to growth empirics
[Zeitschriftenartikel]
Abstract Parameter estimation under model uncertainty is a difficult and fundamental issue in econometrics. This paper compares the performance of various model averaging techniques. In particular, it contrasts Bayesian model averaging (BMA) — currently one of the standard methods used in growth empirics — w... mehr
Parameter estimation under model uncertainty is a difficult and fundamental issue in econometrics. This paper compares the performance of various model averaging techniques. In particular, it contrasts Bayesian model averaging (BMA) — currently one of the standard methods used in growth empirics — with a new method called weighted-average least squares (WALS). The new method has two major advantages over BMA: its computational burden is trivial and it is based on a transparent definition of prior ignorance. The theory is applied to and sheds new light on growth empirics where a high degree of model uncertainty is typically present.... weniger
Klassifikation
Wirtschaftsstatistik, Ökonometrie, Wirtschaftsinformatik
Freie Schlagwörter
C51; C52; C13; C11; Model averaging; Bayesian analysis; Growth determinants
Sprache Dokument
Englisch
Publikationsjahr
2009
Seitenangabe
S. 139-153
Zeitschriftentitel
Journal of Econometrics, 154 (2009) 2
DOI
https://doi.org/10.1016/j.jeconom.2009.07.004
Status
Postprint; begutachtet (peer reviewed)
Lizenz
PEER Licence Agreement (applicable only to documents from PEER project)