Explaining Productivity Differentials in Eastern European Agriculture: Efficiency or Class Structure ?

Jean-Louis Leslie Arcand () and BORODAK Daniela
Additional contact information
BORODAK Daniela: Ecole Supérieure de Commerce (Clermont-Ferrand)

No 200612, Working Papers from CERDI

Abstract: This paper considers whether it is differences in technical efficiency or differences in factor endowments that explain productivity differentials in Moldovan agriculture. We compute non-parametric measures of technical efficiency for a sample of Moldovan small-holders using the four-step Data Envelopment Analysis (DEA) approach suggested by Fried, Schmidt and Yaisawang (1999). We also consider a model of class structure inspired by the work of Eswaran and Kotwal (1986), and estimate a bivariate probit model that explains a household's labor market participation decisions (and hence class membership) in terms of its factor endowments. These constructs are then used in an effort to understand the determinants of output per hectare in Moldovan agriculture. We find that differences in technical efficiency explain very little of the great heterogeneity in productivity observed in our sample, while class membership is slightly more successful. Our empirical model of class structure suggests that self sufficient households will disappear and be replaced by a class of small capitalist farmers as land and credit markets develop.

Keywords: Technical efficiency; agrarian reform; household model; transaction costs; transitional economy (search for similar items in EconPapers)
Date: 2006
View list of references

Downloads: (external link)
http://publi.cerdi.org/ed/2006/2006.12.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: http://EconPapers.repec.org/RePEc:cdi:wpaper:804

Access Statistics for this paper

More papers in Working Papers from CERDI
Contact information at EDIRC.
Series data maintained by Vincent Mazenod ().