Although the Japanese water sector is economically and socially important, few empirical studies are available to help analysts and policy-makers understand the performance patterns in the industry. This study applies data envelopment analysis to 5,538 observations of 1,144 utilities that supplied drinking water between 2004 and 2007. With a comprehensive census of utilities, the present study controls for many factors affecting efficiency: region, prefecture, ownership/governance, water source, vertical integration (purchased or produced alone), water or integrated system, production, treatment, transport and distribution of water), peak factor, per capita consumption, customer density, water losses, monthly water charge, outsourcing, subsidies, gross prefecture product, and time. Thus, this study derives comprehensive conclusions regarding efficiency patterns in Japan. The analysis finds that the average level of inefficiency (weighted by volume) is 57% in the constant return to scale model, but only 24% for the (more flexible) variable return to scale model. Improving sector efficiency and transferring funds to more innovative sectors rather than using scarce funds to subsidize water distribution would benefit citizens. Thus, the application of advanced quantitative techniques to Japanese water utilities improves the understanding of efficiency patterns and underscores the importance of in-depth studies of the individual factors examined in this study.

This paper examines the robustness of efficiency score rankings across four distributional assumptions for trans-log stochastic production-frontier models, using data from 1,221 Japanese water utilities (for 2004 and 2005). One-sided error terms considered include the half-normal, truncated normal, exponential, and gamma distributions. Results are compared for homoscedastic and doubly heteroscedastic models, where we also introduce a doubly heteroscedastic variable mean model, and examine the sensitivity of the nested models to a stronger heteroscedasticity correction for the one-sided error component. The results support three conclusions regarding the sensitivity of efficiency rankings to distributional assumptions. When four standard distributional assumptions are applied to a homoscedastic stochastic frontier model, the efficiency rankings are quite consistent. When those assumptions are applied to a doubly heteroscedastic stochastic frontier model, the efficiency rankings are consistent when proper and sufficient arguments for the variance functions are included in the model. When a more general model, like a variable mean model is estimated, efficiency rankings are quite sensitive to heteroscedasticity correction schemes.

This paper examines a model of privatization and divestiture of a vertically integrated public monopoly. The framework is used to derive general conditions of how mixed companies might be used to promote efficient outcomes without assuming either an ideal social planner or superior cost performance of private enterprise. The conditions suggest that efficient public policy towards mixed (public‐private partnership) companies depends on basic cost and demand conditions. The results indicate that: (1) a vertically integrated private monopoly can be more efficient than any combination of mixed companies when there is a sufficiently flat linear (elastic) demand curve and relatively greater (upward sloping) marginal cost for the downstream sector; (2) an upstream public and downstream public firm can achieve the first best outcome when the downstream firm has constant marginal costs; and (3) a partial privatization of the upstream firm achieves higher welfare than taking that action for the downstream firm. The intuition behind the propositions is provided using standard features of cost and demand. While the implications for public policy regarding privatization and divestiture in infrastructure sectors are not definitive, the results underscore the importance of understanding cost and demand conditions when developing and implementing public policies.

This paper examines the robustness of efficiency score rankings across four distributional assumptions for trans-log stochastic production-frontier models, using data from 1,221 Japanese water utilities (for 2004 and 2005). One-sided error terms considered include the half-normal, truncated normal, exponential, and gamma distributions. Results are compared for homoscedastic and doubly heteroscedastic models, where we also introduce a doubly heteroscedastic variable mean model, and examine the sensitivity of the nested models to a stronger heteroscedasticity correction for the one-sided error component. The results support three conclusions regarding the sensitivity of efficiency rankings to distributional assumptions. When four standard distributional assumptions are applied to a homoscedastic stochastic frontier model, the efficiency rankings are quite consistent. When those assumptions are applied to a doubly heteroscedastic stochastic frontier model, the efficiency rankings are consistent when proper and sufficient arguments for the variance functions are included in the model. When a more general model, like a variable mean model is estimated, efficiency rankings are quite sensitive to heteroscedasticity correction schemes.