EconPapers    
Economics at your fingertips  
 

Technical efficiency with state-contingent production frontiers using maximum entropy estimators

Pedro Macedo (), Elvira Silva and Manuel Scotto

Journal of Productivity Analysis, 2014, vol. 41, issue 1, 140 pages

Abstract: Although the theory of state-contingent production is well-established, the empirical implementation of this approach is still in an infancy stage. The possibility of finding a large number of states of nature, few observations per state and models affected by collinearity have led some researchers to claim the urgent need to develop robust estimation techniques. In this paper, we investigate the performance of some maximum entropy estimators to assess technical efficiency with state-contingent production frontiers. The methodological discussion and the simulation study provided in the paper reveal some of the potential of these estimators. Small mean squared error loss and small differences between the true and the estimated mean of technical efficiency show that the maximum entropy can be a powerful tool in the estimation of state-contingent production frontiers. Copyright Springer Science+Business Media, LLC 2014

Keywords: Maximum entropy; State-contingent production; Technical efficiency; C13; C15 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://hdl.handle.net/10.1007/s11123-012-0314-y (text/html)
Access to full text is restricted to subscribers.

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:kap:jproda:v:41:y:2014:i:1:p:131-140

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

DOI: 10.1007/s11123-012-0314-y

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 () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-19
Handle: RePEc:kap:jproda:v:41:y:2014:i:1:p:131-140