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A comparison of the technical efficiency of accounting firms among the US, China, and Taiwan under the framework of a stochastic metafrontier production function

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Abstract

This study employs the newly developed stochastic metafrontier production function by Huang et al. (A new approach to estimating the metafrontier production function based on a stochastic frontier framework. Working paper, Vanderbilt University, National Cheng-chi University, Taiwan, 2012) to compare the technical efficiencies of accounting firms (AFs) among the US, China, and Taiwan, operating under different technologies. Although AFs play an important role in a nation’s capital market, the accounting industry has not attracted much attention to academic researchers. The main difference between the stochastic metafrontier function and the one proposed by Battese et al. (J Prod Anal 21:91–103, 2004) and O’Donnell et al. (Empir Econ 34:231–255, 2008) lies in the second step, where the stochastic frontier approach (SFA) is recommended instead of programming techniques. Taiwan’s AFs are found to have the highest average metafrontier technical efficiency (MTE) and AFs in the US have the highest technology gap ratio (TGR). Nonetheless, the average TGR and MTE values of American AFs are closer to those of Taiwan. The low performance of Chinese AFs may be attributed to government regulations and the lack of market competition. However, the programming technique suggests reverse results for AFs in Taiwan and the US and larger variances for TGR and MTE. Then these three countries’ AFs show decreasing returns to scale, indicating that mergers and acquisitions may not be advantageous for expanding their production scale.

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Notes

  1. This specification is in line with Battese and Coelli (1992). Note that the assumption that \(u_{i}^{j}\) is a half-normal random variable for all groups of j, instead of a truncated-normal, allows us to compare the technical efficiency of accounting firms in different countries under the same standard, i.e., the distribution of u j i in each group is kept by the same portion of the right-half.

  2. Readers are suggested to refer to Battese and Rao (2002), Battese et al. (2004), O’Donnell et al. (2008) and Huang et al. (2012) for the detailed formulation and interpretation of the TGR.

  3. However, the information provided by CICPA only provides data on two types of revenue: auditing and non-auditing service. The accounting and auditing services on US firms comprises compilations, special reports, and reviews in addition to engagement involving the attest function which could be categorized as revenue from auditing services and non-auditing services. The Taiwan’s database on the other hand provided complete data on various revenue items.

  4. Our estimation results show that a little more than a half of the parameter estimates achieve statistical significance. This appears to be acceptable due to the fact that our data set is not large, including only 297, 105, and 300 observations in the US, Taiwan, and China, respectively.

  5. Due to space limitations, we have not listed the coefficient estimation results; interested readers may obtain this data from the author.

  6. The estimation results are quite similar to the ones without the firm size dummy variable. But, including the firm size variable makes this empirical result more intuition about practices. We are grateful to anonymous referee for providing the suggestion.

  7. We have not listed the LP metafrontier estimates, as they are similar to those resulting from the QP model. Interested readers may obtain this data from the author.

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Acknowledgments

The first author is indebted to the financial support of Ministry of Science and Technology, Taiwan, ROC, with grant number: NSC 100-2410-H-032-036. The three authors are also indebted to anonymous referees for their valuable comments and suggestions.

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Correspondence to Chun-Yi Kuo.

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Chang, BG., Huang, TH. & Kuo, CY. A comparison of the technical efficiency of accounting firms among the US, China, and Taiwan under the framework of a stochastic metafrontier production function. J Prod Anal 44, 337–349 (2015). https://doi.org/10.1007/s11123-014-0397-8

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