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Erschienen in: Empirical Economics 2/2006

01.06.2006 | original paper

Firm exit and technical inefficiency

verfasst von: Efthymios G. Tsionas, Theodore A. Papadogonas

Erschienen in: Empirical Economics | Ausgabe 2/2006

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Abstract

The purpose of the paper is to examine formally the fundamental implication that technical inefficiency (TI) is related to firm exit. Traditional stochastic frontier models allow for the measurement of TI but do not allow for a direct effect of TI on exit. We propose a model which allows for such effects and consists of a stochastic frontier model, and an additional equation that describes the probability of exit as a function of covariates and TI. Since TI is unobserved, econometric complications arise, and obtaining consistent estimates is non-trivial due to the presence of integrals in the likelihood function. We propose and implement maximum likelihood estimation one step, employing data for 3,404 manufacturing firms in Greece. We find significant positive effects from TI on the probability of exit. We also propose and provide measures of TI that respect the fact that unobserved TI affects the probability of exit and compare them to TI measures from the traditional stochastic frontier model.

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Fußnoten
1
An alternative is to obtain inefficiency measures using the data envelopment analysis (DEA) technique as in Wheelock and Wilson (1995). Dimara et al. (2003) have used inefficiency estimates derived from a Battese and Coelli (1995) model.
 
2
Cost frontiers can be considered by using +u i instead of −u i in Eq. (1).
 
3
It seems that more emphasis has been placed on frontier models where technical inefficiency is a dependent variable and can be explained using covariates, see Kumbhakar et al. (1991) and Battese and Coelli (1995).
 
4
An alternative technique to compute the integral would be by simulation resulting in maximum simulated likelihood (MSL) estimation. Since the integrals involved in the likelihood function are univariate, Gaussian quadrature is significantly more precise and computationally far less expensive compared to MSL. In this study we have used a ten-point rule to implement Gaussian quadrature.
 
5
We have used the BFGS algorithm with numerical derivatives as implemented in the GAUSS software package. The programs are available on request from the first author. We have first estimated the logit model. The parameter estimates were supplied as starting values for the extreme value model, and parameter estimates from that model were supplied as starting values for the probit specification.
 
6
The logit and extreme value specifications give nearly the same results for technical inefficiency measures so in Fig. 1 it is not possible to distinguish between the two kernel densities.
 
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Metadaten
Titel
Firm exit and technical inefficiency
verfasst von
Efthymios G. Tsionas
Theodore A. Papadogonas
Publikationsdatum
01.06.2006
Verlag
Springer-Verlag
Erschienen in
Empirical Economics / Ausgabe 2/2006
Print ISSN: 0377-7332
Elektronische ISSN: 1435-8921
DOI
https://doi.org/10.1007/s00181-005-0045-2

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