Evaluating Business Incentives Through DEA. An Analysis on Capitalia Firm Data

Sergio Destefanis and Giuseppe Storti

MPRA Paper from University Library of Munich, Germany

Abstract: We analyse the impact of business incentives on the technical efficiency of Italian manufacturing firms. Using DEA allows a novel treatment of the omitted-variable and sample-selection bias. Through DEA one carries out direct comparisons between similar observations akin to those carried out in non-parametric matching analysis. The selection bias can be treated by conditioning these comparisons on the variables ruling the distribution of state aid. We separately utilise four Capitalia surveys, in order to test whether policy effectiveness has changed during the 1990s. Moreover we consider separately the effects of the three main kinds of state aid to manufacturing (soft loans, grants, and tax rebates). The results indicate that state aid had a negative impact on technical efficiency. However, this impact mostly relates to soft loans, and looses significance in the late 1990s.

Keywords: Local development policies; Policy evaluation; Technical efficiency; Frontier analysis. (search for similar items in EconPapers)
JEL-codes: G32 H25 O20 O40 (search for similar items in EconPapers)
Date: 2005-11-07
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Published in DISES Working Papers 3.173 (2005): pp. 1-29

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/62336/1/MPRA_paper_62336.pdf original version (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:pra:mprapa:62336

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter (winter@lmu.de).