A State-Space Stochastic Frontier Panel Data Model
A. Peyrache () and
Alicia Rambaldi ()
No WP012012, CEPA Working Papers Series from University of Queensland, School of Economics
In this paper we introduce a state-space approach to the econometric modelling of cross-sectional specific trends (temporal variation in individual heterogeneity) and time varying slopes in the context of panel data regressions. We show that our state-space panel stochastic frontier model nests some of the popular models proposed in the literature on stochastic frontier to accommodate time varying inefficiency and its dynamic version (productivity). A detailed discussion of alternative model specifications is provided and estimation (along with testing procedures for model selection) is presented. The empirical application uses the EU-KLEMS dataset which provides data in the period 1977-2007 for 13 countries and 20 sectors of each economy. Our main empirical interest is centered on productivity analysis and thus we focus on the stochastic frontier interpretation of this cross-sectional specific temporal variation. A post-estimation growth accounting is introduced in order to provide a quantitative assessment of the main factors behind sectoral labour productivity growth for each country.
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:qld:uqcepa:77
Access Statistics for this paper
More papers in CEPA Working Papers Series from University of Queensland, School of Economics Contact information at EDIRC.
Bibliographic data for series maintained by SOE IT ().