This chapter examines the effect of the division of labor from a Bayesian viewpoint. While organizational reforms are crucial for cost reduction in the Japanese water supply industry, the effect of labor division in intra-organizational units on total costs has, to the best of our knowledge, not been examined empirically. Fortunately, a one-time survey of 79 Japanese water suppliers conducted in 2010 enables us to examine the effect. To examine this problem, a cost stochastic frontier model with endogenous regressors is considered in a cross-sectional setting, because the cost and the division of labor are regarded as simultaneously determined factors. From the empirical analysis, we obtain the following results: (1) total costs rise when the level of labor division becomes high; (2) ignoring the endogeneity leads to the underestimation of the impact of labor division on total costs; and (3) the estimation bias on inefficiency can be mitigated for relatively efficient organizations by including the labor division variable in the model, while the bias for relatively inefficient organizations needs to be controlled by considering its endogeneity. In summary, our results indicate that integration of internal sections is better than specialization in terms of costs for Japanese water supply organizations.
We would like to thank the editor and an anonymous referee for their valuable comments and suggestions, which have improved the chapter substantially. Part of this research was conducted while Kazuhiko Kakamu and Eri Nakamura were visiting Vienna University of Economics and Business, whose hospitality is gratefully acknowledged. This work is partially supported by KAKENHI #15K17049, #17K03738, #16KK0081, and #25245035.
Nakamura, E., Urakami, T. and Kakamu, K. (2019), "A Bayesian Stochastic Frontier Model with Endogenous Regressors: An Application to the Effect of Division of Labor in Japanese Water Supply Organizations", Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part B (Advances in Econometrics, Vol. 40B), Emerald Publishing Limited, pp. 29-46. https://doi.org/10.1108/S0731-90532019000040B003Download as .RIS
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