EconPapers    
Economics at your fingertips  
 

A novel model of costly technical efficiency

Mike Tsionas and Marwan Izzeldin

European Journal of Operational Research, 2018, vol. 268, issue 2, 653-664

Abstract: This paper presents a novel model of measuring technical inefficiency based on the notion that higher efficiency requires a certain cost. First, we apply the “rational inefficiency hypothesis” of Bogetoft and Hougaard (2003) but we fail to find that it rationalizes our data set of large U.S banks with multiple inputs and outputs. In consequence, we adopt a novel model of profit maximization which explicitly incorporates the cost of technical inefficiency. The cost of inefficiency is treated as unknown and is parametrized as a function of inputs, outputs and decision-making-unit specific fixed effects. More importantly, by showing the model to be equivalent to one in which inefficiency is an arbitrary function of inputs, outputs and the inefficiency cost, we are able to determine optimal directions in the input-output space that would reduce inefficiency. Bayesian techniques organized around Markov Chain Monte Carlo are used to perform the computations and provide statistical inferences as well as useful policy measures to reduce inefficiencies in the U.S banking sector through an examination of different realistic scenarios.

Keywords: Production; Technical inefficiency; Profit maximization; Distance functions; Bayesian methods (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0377221718300341
Full text for ScienceDirect subscribers only

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:eee:ejores:v:268:y:2018:i:2:p:653-664

Access Statistics for this article

European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati

More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().

 
Page updated 2019-04-22
Handle: RePEc:eee:ejores:v:268:y:2018:i:2:p:653-664