Environmental Efficiency and Regional Convergence Clusters in Japan: A Nonparametric Density Approach

Environmental Efficiency and Regional Convergence Clusters in Japan: A Nonparametric Density Approach

Abstract

This presentation is about environmental efficiency convergence across the prefectures of Japan over the 1992-2008 period. Using a novel nonparametric density estimation clustering framework, two alternative indicators of environmental efficiency are contrasted: a conventional indicator, based on the ratio of gross regional product to CO2 emissions, and a more comprehensive indicator, based on the data envelopment analysis (DEA) model. Results show, on the one hand, a lack of intra-distributional mobility and potentially a unique convergence cluster when using the more conventional indicator. On the other hand, large backward mobility and at least two convergence clusters are identified when using the DEA-based indicator of environmental efficiency. The paper concludes arguing the importance of accounting for production inputs, as they appear to be driving the formation of regional convergence clusters in Japan.

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Ritsumeikan University, Osaka Prefecture, Japan
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Carlos Mendez
Associate Professor of Development Economics

My research interests focus on the integration of econometrics, data science and machine learning methods to understand and inform the process of economic growth and development of countries, regions, industries, and firms.