Abstract
Improving the rural community management service level can effectively optimize the rural community living condition, provide a better social environment for rural residents to start up business and promote the living standard of rural residents. This paper presents quantitative research on the correlation between rural residents’ living standards and rural community management service levels on the basis of 16 municipalities’ data in Anhui province in 2015. The results of the study are as follows: road mileage per every ten thousand people, rural water improvement profitability and rural sanitary toilet penetration have a decisive influence on the improvement of living standards in Anhui rural areas; specifically, the first pair of canonical variables has a fairly accurate predictive ability in road mileage per every ten thousand people, rural water improvement profitability, rural sanitary toilets penetration, per capita disposable income and per capita consumption expenditure but has a poor predictive ability in the enrollment rate of the new rural cooperative medical system. Additionally, the first pair of canonical variables can explain and predict the corresponding variables quite well, and the rural community management service level has an evident interaction effect with the living standard of rural residents.
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Antle, J. M. (1983). Infrastructure and aggregate productivity: International evidence. Economic Development and Cultural Change, 31(3), 609–619.
Aulor, D., Levy, F., & Mumane, R. (2003). The Skill contents of recent technological change: An empirical exploration. Quarterly Journal of Economics, 118, 1279–1333.
Benjamin, D., Brandt, L., & Giles, J. (2005). The evolution of income inequality in rural China. Economic Development & Cultural Change, 53(4), 769–824.
Bertinelli, L., & Zou, B. (2008). Does urbanization foster human capital accumulation? Journal of Developing Areas, 41(2), 171–184.
Charlery, L. C., Qaim, M., & Smith-Hall, C. (2016). Impact of infrastructure on rural household income and inequality in Nepal. Journal of Development Effectiveness, 8(2), 1–21.
Chen, M. H., Wang, L., Sun, S. W., Wang, J., & Xia, C. Y. (2016). Evolution of cooperation in the spatial public goods game with adaptive reputation assortment. Physics Letters A, 380(1–2), 40–47.
Dessus, S., & Herrera, R. (2000). Public capital and growth revisited: A panel data assessment. Economic Development and Cultural Change, 48(2), 407–418.
Fan, S., Hazell, P., & Thorat, S. (2000). Government spending, growth and poverty in rural India. American Journal of Agricultural Economics, 82(4), 1038–1051.
Fleisher, B., Li, H., & Zhao, M. Q. (2010). Human capital, economic growth, and regional inequality in China. Journal of Development Economics, 92(2), 215–231.
Goh, C. C., Luo, X., & Zhu, N. (2009). Income growth, inequality and poverty reduction: A case study of eight provinces in China. Chinese Economic Review, 20(3), 485–496.
Henderson, J. V. (2010). Cities and development. Journal of Regional Science, 50(1), 515–540.
Im, S. B., Lee, S., Lee, J., & Kim, T. (2016). Contribution of Agricultural infrastructure to rural development in the Republic of Korea. Irrigation & Drainage, 65(S1), 40–47.
Lucas, R. E. (1988). On the mechanics of economic development. Journal of Monetary Economy, 22(1), 3–42.
Ma, Q. L., & Liu, Y. H. (2012). Analysis and construction of harmonious community development model in rural areas. Reform and Opening-up, 2, 142–143.
Moomaw, R. L., & Shatter, A. M. (1996). Urbanization and economic development: A bias toward large cities? Journal of Urban Economics, 40(1), 13–37.
Pan, X., Liu, Q., & Peng, X. (2015). Spatial Club convergence of regional energy efficiency in China. Ecological Indicators, 51(1), 25–30.
Park, K. (1996). Educational expansion and educational inequality on income distribution. Economics of Education Review, 15(1), 51–58.
Peng, H. F., & Huang, S. Q. (2014). Study on the coordinated development of the rural infrastructure and the rural economy. International English education research, 4, 45–47.
Shariff, A., & Azam, M. (2011). Income inequality in rural India: Decomposing the Gini by income sources. Social Science Electronic Publishing, 31(1), 739–748.
Wang, Z., & Sun, S. (2016). Transportation infrastructure and rural development in China. China Agricultural Economic Review, 8(3), 516–525.
Wang, C., Wang, L., Wang, J., Sun, S. W., & Xia, C. Y. (2017). Inferring the reputation enhances the cooperation in the public goods game on interdependent lattices. Applied Mathematics and Computation, 293, 18–29.
Wu, P., & Zhu, J. (2015). Influencing factors of resident income level and urban–rural and regional differences. Journal of China Agricultural University, 20(2), 251–258.
Yair, O., & Talmon, R. (2017). Local canonical correlation analysis for nonlinear common variables discovery. IEEE Transactions on Signal Processing, 65(5), 1101–1115.
Yang, L. J. (2015). Accelerating the construction of urbanization and promoting the development of regional economy. Agriculture and Technology, 15(35), 169–188.
Yang, D., & Liu, Z. (2012). Does farmer economic organization and agricultural specialization improve rural income? Economic Modelling, 29(3), 990–993.
Zhang, J. P. (2012). Rural community construction in the process of urbanization. Development, 12, 38–41.
Zhang, J., Giles, J., & Rozelle, S. (2012). Does it pay to be a cadre? Estimating the Returns to being a local official in rural China. Journal of Comparative Economics, 40(3), 337–356.
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The work is partially supported by the National Natural Science Foundation of China (No. 7153304) and the Project of Anhui Humanities and Social Sciences in Universities (No. SK2016A0114).
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Chen, D., Wang, L., Su, T. et al. Canonical Correlation Analysis Between Residents’ Living Standards and Community Management Service Levels in Rural Areas: An Empirical Analysis Based on Municipal Data in Anhui Province. Comput Econ 52, 1053–1068 (2018). https://doi.org/10.1007/s10614-017-9791-4
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DOI: https://doi.org/10.1007/s10614-017-9791-4