EconPapers    
Economics at your fingertips  
 

A Stochastic Frontier Production Function with Flexible Risk Properties

G. Battese, Alicia Rambaldi () and Guanghua Wan ()

Journal of Productivity Analysis, 1997, vol. 8, issue 3, 269-280

Abstract: This paper considers a stochastic frontier production function which has additive, heteroscedastic error structure. The model allows for negative or positive marginal production risks of inputs, as originally proposed by Just and Pope (1978). The technical efficiencies of individual firms in the sample are a function of the levels of the input variables in the stochastic frontier, in addition to the technical inefficiency effects. These are two features of the model which are not exhibited by the commonly used stochastic frontiers with multiplicative error structures. An empirical application is presented using cross-sectional data on Ethiopian peasant farmers. The null hypothesis of no technical inefficiencies of production among these farmers is accepted. Further, the flexible risk models do not fit the data on peasant farmers as well as the traditional stochastic frontier model with multiplicative error structure. Copyright Kluwer Academic Publishers 1997

Keywords: stochastic frontier production function; production risks; technical efficiency (search for similar items in EconPapers)
Date: 1997
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (26) Track citations by RSS feed

Downloads: (external link)
http://hdl.handle.net/10.1023/A:1007755604744 (text/html)
Access to full text is restricted to subscribers.

Related works:
Working Paper: A Stochastic Frontier Production Function with Flexible Risk Properties (1995) Downloads
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:kap:jproda:v:8:y:1997:i:3:p:269-280

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/11123/PS2

DOI: 10.1023/A:1007755604744

Access Statistics for this article

Journal of Productivity Analysis is currently edited by William Greene, Chris O'Donnell and Victor Podinovski

More articles in Journal of Productivity Analysis from Springer
Bibliographic data for series maintained by Sonal Shukla ().

 
Page updated 2020-09-11
Handle: RePEc:kap:jproda:v:8:y:1997:i:3:p:269-280