Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/37270
Authors: 
Savin, Ivan
Winker, Peter
Year of Publication: 
2010
Series/Report no.: 
Beiträge zur Jahrestagung des Vereins für Socialpolitik 2010: Ökonomie der Familie - Session: Computational Econometrics A3-V2
Abstract: 
Innovations, be they radical new products or technology improvements are widely recognized as a key factor of economic growth. To identify the factors triggering innovative activities is a main concern for economic theory and empirical analysis. As the number of hypotheses is large, the process of model selection becomes a crucial part of the empirical implementation. The problem is complicated by the fact that unobserved heterogeneity and possible endogeneity of regressors have to be taken into account. A new efficient solution to this problem is suggested, applying optimization heuristics, which exploits the inherent discrete nature of the problem. The model selection is based on information criteria and the Sargan test of overidentifying restrictions. The method is applied to Russian regional data within the framework of a log-linear dynamic panel data model. To illustrate the performance of the method, we also report the results of Monte-Carlo simulations.
Subjects: 
Innovation
dynamic panel data
GMM
model selection
threshold accepting
genetic algorithms
JEL: 
C63
O31
C52
Document Type: 
Conference Paper

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