Estimation of Input Distance Functions: A System Approach

Mike Tsionas, Subal Kumbhakar and Emir Malikov

American Journal of Agricultural Economics, 2015, vol. 97, issue 5, 1478-1493

Abstract: This article offers a methodology to address the endogeneity of inputs in the input distance function (IDF) formulation of the production processes. We propose to tackle endogenous input ratios appearing in the normalized IDF by considering a flexible (simultaneous) system of the IDF and the first-order conditions from the firm's cost minimization problem. Our model can accommodate both technical and (input) allocative inefficiencies among firms. We also present the algorithm for quantifying the cost of allocative inefficiency. We showcase our cost-system-based model by applying it to study the production of Norwegian dairy farms during the 1991–2008 period. Among other things, we find both an economically and statistically significant improvement in the levels of technical efficiency among dairy farms associated with the 1997 quota scheme change, which a more conventional single-equation stochastic frontier model appears to be unable to detect.

Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (14)

Downloads: (external link)
http://hdl.handle.net/10.1093/ajae/aav012 (application/pdf)
Access to full text is restricted to subscribers.

Related works:
Working Paper: Estimation of Input Distance Functions: A System Approach (2015)
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:oup:ajagec:v:97:y:2015:i:5:p:1478-1493.

Access Statistics for this article

American Journal of Agricultural Economics is currently edited by Madhu Khanna, Brian E. Roe, James Vercammen and JunJie Wu

More articles in American Journal of Agricultural Economics from Agricultural and Applied Economics Association Contact information at EDIRC.
Bibliographic data for series maintained by Oxford University Press ().