EconPapers    
Economics at your fingertips  
 

Copula-based Stochastic Cost Frontier with Correlated Technical and Allocative Inefficiency

Arabinda Das ()
Additional contact information
Arabinda Das: Acharya Prafulla Chandra College

Journal of Quantitative Economics, 2021, vol. 19, issue 2, No 2, 207-222

Abstract: Abstract This paper considers the duality between stochastic frontier production and cost functions, under the assumption of cost minimization (technical and allocative inefficiency) and dependence structure for both measures of technical and allocative inefficiency as assumed by (Schmidt and Lovell, Journal of Econometrics 13:83–100, 1980). However, the assumed dependence structure comprise of positive dependence for higher technical inefficiency and higher (positive) allocative inefficiency; and negative dependence for higher technical inefficiency and higher (negative) allocative inefficiency through a mixture of copula model. The dependence structure is presented by a multivariate Farlie–Gumbel–Morgenstern (FGM) copula as there will be choice of probability distributions for both technical and allocative inefficiency. The proposed model is estimated using simulated maximum likelihood (SML) method. An application of the illustrated model to the US electricity utility data (Greene, Journal of Econometrics 46:141–164, 1990) shows a significant dependence between technical and allocative inefficiency.

Keywords: Cost minimization; Copula function; Multivariate FGM copula; SML method; C15; C31; C51 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s40953-021-00230-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:jqecon:v:19:y:2021:i:2:d:10.1007_s40953-021-00230-6

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/40953

DOI: 10.1007/s40953-021-00230-6

Access Statistics for this article

Journal of Quantitative Economics is currently edited by Dilip Nachane and P.G. Babu

More articles in Journal of Quantitative Economics from Springer, The Indian Econometric Society (TIES) Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:jqecon:v:19:y:2021:i:2:d:10.1007_s40953-021-00230-6