Modeling Regional Heterogeneity with Panel Data: Application to Spanish Provinces

Antonio Alvarez and Julio del Corral

No 2006/06, Efficiency Series Papers from University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG)

Abstract: The estimation of aggregate production functions is common in regional economics. Regional data are usually characterized by a high level of heterogeneity among observations which are not frequently reflected in the data. If this unobserved heterogeneity, is not treated adequately can arise serious econometric problems. In this paper we review the different approaches the literature has used to deal with this problem. Moreover, in order to compare different models we estimate aggregate production functions using data from Spanish regions. First we estimate the Cornwell, Schmidt and Sickles (1990) model. Furthermore, we estimate a Battese and Coelli (1995) model. We include a time trend as an efficiency explanatory variable so the efficiency is time varying. We compare both estimates with the traditional fixed effects model.

Keywords: aggregate production function; time-variant efficiency; regional unobserved heterogeneity (search for similar items in EconPapers)
Pages: 16
Date: 2006
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.unioviedo.es/oeg/ESP/esp_2006_06.pdf (application/pdf)

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:oeg:wpaper:2006/06

Access Statistics for this paper

More papers in Efficiency Series Papers from University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG) Departamento de Economía, Facultad de Economía y Empresa, Universidad de Oviedo, Avenida del Cristo, s/n. 33006 Oviedo - SPAIN. Contact information at EDIRC.
Bibliographic data for series maintained by Luis Orea () and David Roibas ().