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

Rosa Bernardini Papalia and Silvia Bertarelli
Additional contact information
Rosa Bernardini Papalia: Dipartimento di Scienze Statistiche, Università di Bologna, Bologna, Italy, rossella.bernardini@unibo.it

International Regional Science Review, 2010, vol. 33, issue 1, 31-59

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.

Keywords: conditional convergence; mapping models; dynamic panel data; maximum entropy estimation (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0160017609334183 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:inrsre:v:33:y:2010:i:1:p:31-59

DOI: 10.1177/0160017609334183

Access Statistics for this article

More articles in International Regional Science Review
Bibliographic data for series maintained by SAGE Publications (sagediscovery@sagepub.com).