The provision of nursery facilities by local governments is a critical issue in Japan these days. In this paper, we examine the determinants of the provision policies of local governments in 2012 and 2013, when there were significant systemic institutional changes related to the provision of nursery facilities.

　We empirically test strategic interaction over provision policies of nursery facilities. After addressing several issues related to examining strategic interaction among governments, we find significant evidence of the interaction. In other words, different interactions were observed between the Kanto and Kansai regions in terms of public and private nursery facility provision rates, and provision policies in the 2010s appear to have been influenced by this strategic behavior.

　Recent epistemic democracy research on political theory has focused on the epistemic effectiveness of the democratic decision-making process, by which the collective intelligence derived is intended to find correct answers. The methodological characteristic of epistemic democracy is that it uses mathematical model analysis as the basis for its normative argument. The problem is that controversy has surrounded the implications of mathematical models built using ideal and normative democratic conditions for real-world political issues.

　The current research presented this problem by introducing the controversy over the "diversity trumps ability" theorem, a collective intelligence model in deliberation. It developed two approaches to alleviating the problem via the theory of epistemic democracy: One is to enhance the internal validity of a model and prepare the necessary conditions for ensuring its external validity through the robustness analysis of mathematical models within the scope of model analysis. The other is to go beyond model analysis to investigate the behaviors of mathematical models in an experimental system and accumulate results as a "library of phenomena." These proposals enable explorations into the range at which model analysis is generalizable to the real world while maintaining the normative nature of political theory.

　In order to explain social phenomena that standard economic models cannot explain, economists have taken into account non-economic factors such as identity. In particular, stigma, which is a negative identity, has received much attention because of its potential to affect the effectiveness of policies. This paper provides an overview of economic research that considers stigma as a social psychological factor, particularly research related to welfare policy, environmental issues, financial crises, and infectious disease control, and presents a perspective on the economic study of stigma.

　The efficient management of water utilities is a key issue in Japan, where the population is declining. This study examines the existence of cost inefficiencies and economies of scale in Japan's water utilities using the short-run cost function approach with stochastic frontier analysis. The results of this study confirm that cost inefficiencies exist in Japan's water utilities, suggesting that Japan's water utilities could be managed more efficiently. The study also confirms that economies of scale exist in Japan's water utilities. Further, it suggests that smaller water utilities in particular are likely to benefit from economies of scale by expanding their service areas. However, it may be necessary to devise a way to prevent an increase in the fixed asset amount when expanding the area.

　This paper investigates the effectiveness of matching techniques in improving covariate balance and reducing bias in estimating the effects of treatment through Monte Carlo simulation analysis. The results suggest that Propensity score matching (PSM), Mahalanobis distance matching (MDM), and Coarsened exact matching (CEM) are all effective in improving covariate balance, and that the "PSM paradox" pointed out by King and Nielsen (2019) is not observed in the relationship between the number of pruned observations and covariate balance. Rather, the results suggest that regardless of the matching method, improving covariate balance may lead to a paradoxical situation: beyond a certain point, the improvement of covariate balance no longer contributes to reducing bias in estimated effects of treatment. Also suggested is that even though the matching techniques cannot adjust for the bias of excluded variables and unmeasured confounders, when both are present, estimation after matching may reduce bias in estimated treatment effects better than OLS without matching.