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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


  • Deyou Chen

    (Hefei University of Technology)

  • Lei Wang

    () (Hefei University of Technology
    Anhui Polytechnic University)

  • Tao Su

    (Anhui Polytechnic University)

  • Youtao Zhang

    (University of Pittsburgh)


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.

Suggested Citation

  • Deyou Chen & Lei Wang & Tao Su & Youtao Zhang, 2018. "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," Computational Economics, Springer;Society for Computational Economics, vol. 52(4), pages 1053-1068, December.
  • Handle: RePEc:kap:compec:v:52:y:2018:i:4:d:10.1007_s10614-017-9791-4
    DOI: 10.1007/s10614-017-9791-4

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    Cited by:

    1. Malin Song & Ron Fisher, 2018. "How to Apply Advanced Statistical Analysis to Computational Economics: Methods and Insights," Computational Economics, Springer;Society for Computational Economics, vol. 52(4), pages 1045-1052, December.

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