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Evaluating Total Factor Productivity Differences by a Mapping Structure in Growth Models

¹ Dipartimento di Scienze Statistiche, Università di Bologna
² Dipartimento di Economia Istituzioni Territorio, Università di Ferrara

^* To whom correspondence should be addressed. E-mail: rossella.bernardini{at}unibo.it.

	Abstract

The article aims at providing a suitable measure of total factor productivity (TFP) levels within the conditional convergence framework by introducing unobserved heterogeneity in terms of a "mapping model". Our goal is twofold. First, we develop a generalized maximum entropy estimation procedure to account for ill-posed and ill-conditioned inference problems in estimating a conditional convergence regression with fixed effects and heterogeneous coefficients across regions. Second, we provide an endogenous spatial representation of unobserved fixed effects by using a multidimensional scaling technique. The proposed approach is applied to assess the existence of catching-up across Italian regions over the period 1960–1995 and to identify the effects of technology and geographic spillovers on the determination of TFP levels.

First published on April 17, 2009
International Regional Science Review 2009, doi:10.1177/0160017609334183


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