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

Listed author(s):
  • Rosa Bernardini Papalia

    (Dipartimento di Scienze Statistiche, Università di Bologna, Bologna, Italy, rossella.bernardini@unibo.it)

  • Silvia Bertarelli

    (Dipartimento di Economia Istituzioni Territorio, Università di Ferrara, Ferrara, Italy, silvia.bertarelli@unife.it)

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.

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File URL: http://irx.sagepub.com/content/33/1/31.abstract
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Article provided by in its journal International Regional Science Review.

Volume (Year): 33 (2010)
Issue (Month): 1 (January)
Pages: 31-59

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Handle: RePEc:sae:inrsre:v:33:y:2010:i:1:p:31-59
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