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Small Business Economics

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01-04-2009

Are small firms less efficient?

Authors: Chih-Hai Yang, Ku-Hsieh Chen

Published in: Small Business Economics | Issue 4/2009

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Abstract

This paper compares the technical efficiency of small and medium-sized enterprises (SMEs) with that of large firms and studies the factors influencing technical efficiency for Taiwan’s electronics industry. Unlike conventional studies, we use two alternative approaches to control for the influence of size effect. One is the two-stage switching regression to correct for endogenous size effect on technical efficiency and, the other is, a metafrontier production function for firms in different groups. The main results are as follows. First, the average technical efficiency for large firms is higher than that of SMEs, without considering the size effect, and lower when considering the endogenous choice on firm size. This study cannot, therefore, conclude that there is a negative size–technical efficiency relationship. It however, sheds light on the importance of size effect on the size–technical efficiency nexus. Second, the estimates on the determinants of technical efficiency show that being a subcontractor has a statistically significant positive influence on SMEs’ technical efficiency, but the effect decreases with firm size.

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For a study on the role of SMEs in economic development and growth, please refer to Acs (1992). On the basis of both economics and welfare, You (1995) argued that an expansion of the small-firm segment leads to more efficient resource allocation, less unequal income distribution, and less underemployment, because small firms tend to use more labor-intensive technologies.

The concepts of efficiency, allocative efficiency, and technical efficiency, please refer to Kumbhakar and Lovell (2000).

In fact, this is just why the statement that SMEs tend to employ a more labor-intensive technology is usually stressed in literature (e.g., You 1995; Berry and Mazumdar 1991; Kitching 1982).

X-efficiency is the effectiveness with which a given set of inputs are used to produce outputs. If a firm is producing the maximum output it can, given the resources it employs and the best technology available, it is said to be x-efficient. Therefore, X-inefficiency occurs when X-efficiency is not achieved. The concept of X-efficiency was introduced by Leibenstein (1966).

For the linkage between factor demand and a firm’s technology and factor price, see Little et al. (1987) for an extensive discussion.

As for the pre-1990 studies, please refer to Lundvall and Battese (2000) for a comprehensive review.

A large body of related literature defines this behavior as “outsourcing.” We prefer to adopt the term “subcontracting” in this article, because the term is traditionally used in many of the Asian countries.

For the calculation of technical efficiency in the stochastic frontier production function, please refer to Jondrow et al. (1982).

There is also a two-stage approach using the technique of the Tobit model as the second-step to investigate the determinants of technical efficiency. However, recent research has shown how inappropriate the two-step framework is and suggests that the single-stage estimation procedure is more appropriate (Wang and Schmidt 2002; Greene 2005; Simar and Wilson 2007).

Due to the null values of inputs or output, 246 observations are dropped from our empirical work.

The value of the generalized likelihood-ratio (LR) statistic not displayed in this article shows that the Cobb–Douglas technology is rejected, meaning that input and substitution elasticities are not constant among firms.

There is also literature developing a single-stage approach combining the latent class structure and the stochastic frontier approach, without the need for the a priori sample separation information (see Kumbhakar and Tsionas 2006; Orea and Kumbhakar 2003; Greene 2002).

Refer to Battese et al. (2004) for more details.

The LR statistic is defined by \(\lambda=-2\ \{\ln[\hbox{H}_{0}/\hbox{H}_{1}]\}= -2\ \{\ln[(\hbox{H}_{0})]-\ln[(\hbox{H}_{1})]\},\) where \(\ln[(\hbox{H}_{0})]\) is the value of the log likelihood function for the stochastic frontier estimated by pooling the data for LEs and SMEs and \(\ln[(\hbox{H}_{1})]\) is the sum of the values of the likelihood functions for production frontiers of LEs and SMEs.

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Title: Are small firms less efficient?
Authors: Chih-Hai Yang
Ku-Hsieh Chen
Publication date: 01-04-2009
Publisher: Springer US
Published in: Small Business Economics / Issue 4/2009
Print ISSN: 0921-898X
Electronic ISSN: 1573-0913
DOI: https://doi.org/10.1007/s11187-007-9082-x

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