Mendez-Guerra, Carlos (2019): Environmental Efficiency and Regional Convergence Clusters in Japan: A Nonparametric Density Approach.
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Abstract
This paper studies 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.
Item Type: | MPRA Paper |
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Original Title: | Environmental Efficiency and Regional Convergence Clusters in Japan: A Nonparametric Density Approach |
Language: | English |
Keywords: | environmental efficiency, convergence, nonparametric density, Japan |
Subjects: | O - Economic Development, Innovation, Technological Change, and Growth > O4 - Economic Growth and Aggregate Productivity > O47 - Empirical Studies of Economic Growth ; Aggregate Productivity ; Cross-Country Output Convergence O - Economic Development, Innovation, Technological Change, and Growth > O5 - Economywide Country Studies > O53 - Asia including Middle East R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R1 - General Regional Economics > R10 - General R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R1 - General Regional Economics > R11 - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes |
Item ID: | 92245 |
Depositing User: | Carlos Mendez-Guerra |
Date Deposited: | 23 Feb 2019 14:24 |
Last Modified: | 02 Oct 2019 15:14 |
References: | Arbia, G., Basile, R., and Piras, G. (2006). Analyzing Intra-Distribution Dynamics: A Reappraisal. ERSA conference papers ersa06p262, European Regional Science Association. Barro, R. J. and Sala-I-Martin, X. (1991). Convergence across states and regions. Brookings Papers on Economic Activity, 1991(1):107–182. Barro, R. J. and Sala-i Martin, X. (1992). Convergence. Journal of Political Economy, 100(2):223–251. Barro, R. T. and Sala-I-Martin, X. (1992). Regional growth and migration: A japan-united states comparison. Journal of the Japanese and International Economies, 6(4):312–346. Baumol, W. J. (1986). Productivity growth, convergence, and welfare: what the long-run data show. The American Economic Review, pages 1072–1085. Bianco, S. D. (2016). Going clubbing in the eighties: convergence in manufacturing sectors at a glance. Empirical Economics, 50(2):623–659. Eguchi, S. (2017). Accounting for resource accumulation in japanese prefec-tures: An environmental efficiency analysis. Journal of Economic Structures, 6(1):16. Epstein, P., Howlett, P., and Schulze, M.-S. S. . M. (2003). Distribution dynamics: stratification, polarization, and convergence among oecd economies, 1870–1992. Explorations in Economic History, 40(1):78–97. Henderson, D. J. and Parmeter, C. F. (2015). Applied Nonparametric Econometrics. Cambridge University Press, Cambridge. Hyndman, R. J., Bashtannyk, D. M., and Grunwald, G. K. (1996). Estimating and visualizing conditional densities. Journal of Computational and Graphical Statistics, 5(4):315–336. Magrini, S. (2004). Regional (di) convergence. In Handbook of regional and urban economics, volume 4, pages 2741–2796. Elsevier. Magrini, S. (2009). Why should we analyse convergence using the distribution dynamics approach? Scienze Regionali, 8(1):5–34. Maza, A., Hierro, M., and Villaverde, J. (2012). Income distribution dynamics across european regions: Re-examining the role of space. Economic Modelling, 29(6):2632–2640. Menardi, G. and Azzalini, A. (2014). An advancement in clustering via nonparametric density estimation. Statistics and Computing, 24(5):753–767. Mendez-Guerra, C. (2017). Heterogeneous growth and regional (di)convergence in Bolivia: A distribution dynamics approach. Conjunctural Economics, 2(4):81–108. Mendez-Guerra, C. (2018). On the distribution dynamics of human development: Evidence from the metropolitan regions of Bolivia. Economics Bulletin, 38(4):2467–2475. Ministry of the Environment, Japan. (2013). The 3rd fundamental plan for establishing a sound material-cycle society. Phillips, P. C. and Sul, D. (2007). Transition modeling and econometric convergence tests. Econometrica, 75(6):1771–1855. Phillips, P. C. and Sul, D. (2009). Economic transition and growth. Journal of Applied Econometrics, 24(7):1153–1185. Quah, D. (1993). Galton’s fallacy and tests of the convergence hypothesis. The Scandinavian Journal of Economics, pages 427–443. Quah, D. T. (1996). Twin peaks: growth and convergence in models of distribu-tion dynamics. Economic Journal, pages 1045–1055. Quah, D. T. (1997). Empirics for growth and distribution: Stratification, polarization, and convergence clubs. Journal of Economic Growth, 2(1):27–59. Rey, S. J. and Le Gallo, J. (2009). Spatial analysis of economic convergence. In Palgrave handbook of econometrics, pages 1251–1290. Springer. Sala-i Martin, X. (1996). The classical approach to convergence analysis. Economic journal, pages 1019–1036. Tanikawa, H., Fishman, T., Okuoka, K., and Sugimoto, K. (2015). The weight of society over time and space: A comprehensive account of the construction material stock of japan, 1945–2010. Journal of Industrial Ecology, 19(5):778–791. Wand, M. P. and Jones, M. C. (1995). Kernel Smoothing. Chapman and Hall, London. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/92245 |