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The Influencing Factors of the Imbalance of Rural Long Tail Public Services

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Rural Long Tail Public Service and the Correction Mechanism

Abstract

This chapter examines the factors that influence the imbalance of rural long tail public services. The imbalance of rural long tail public services is caused by a series of complex factors, including many aspects of economy, society, culture and the institutional environment, with multi-subjectivity and dimensions. This chapter first describes the imbalance from both sides of supply and demand. Then, according to the different fields of rural long tail public services, empirical research is conducted from the perspectives of rural special education, special health, elderly care and finance. With regard to the demand side factors, the overall reason for the imbalance of rural long tail public service is that rural residents’ public demand is irrational, discrete, fragmented and atomized. The irrationality of rural residents’ long tail demand refers to the irrationality based on personal preferences and cognition when choosing the required public services. In particular, there is often an irrational side in the selection of the types of public services with information cost and human capital requirements. The indifference utility curve of farmers in terms of public service demand always tends to be extended, without considering the decision-making cost. The decision is related to the non-economic factors existing in the demand selection, which means the over-marginal cost expenditure of the supply curve is unable to measure the total cost, and this makes the demand cost deviate from the expected income. Of course, the irrational demand is related to the rational factors behind that demand, such as the decentralized management mode of farmers, as well as social system obstacles (such as the household registration system) in the marketization process. With regard to the factors that affect the supply side of rural long tail public services, this section intends to analyze the supply reasons and influencing factors of the imbalance from the following perspectives: government financial constraints, government rational choice deviation, immature NGOs, and the lack of a supply “market”. After summarizing the overall reasons for the imbalance in this section, the next three sections will show the results of an empirical regression analysis of specific rural long tail public services, including special education, special health, special elderly care, and special finance. Field-based reasoning and deduction will also be conducted with regard to the above-mentioned influencing factors.

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References

  • Abadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic control methods for comparative case studies: Estimating the effect of California’s tobacco control program. Journal of the American Statistical Association, 490(105), 493–505.

    Article  Google Scholar 

  • Abadie, A., & Gardeazabal, J. (2003). The economic costs of conflict: A case study of the Basque Country. American Economic Review, 93(1), 113–132.

    Article  Google Scholar 

  • Anderson, C. (2007). The long tail: How endless choice is creating unlimited demand. Random House.

    Google Scholar 

  • Baker, B. D., & Ramsey, M. J. (2010). What we don’t know can’t hurt us? Equity consequences of financing special education on the untested assumption of uniform needs. Journal of Education Finance, 245–275.

    Google Scholar 

  • Banks, J., Frawley, D., & McCoy, S. (2015). Achieving inclusion? Effective resourcing of students with special educational needs. International Journal of Inclusive Education, 19(9), 926–943.

    Article  Google Scholar 

  • Blackwell, J. L. (2005). Estimation and testing of fixed-effect panel-data systems. The STATA journal, 5(2), 202–207.

    Article  Google Scholar 

  • Brand, J. E., & Xie, Y. (2010). Who benefits most from college? Evidence for negative selection in heterogeneous economic returns to higher education. American Sociological Review, 75(2), 273–302.

    Article  Google Scholar 

  • Brownell, M. T., Bishop, A. M., & Sindelar, P. T. (2005). NCLB and the demand for highly qualified teachers: Challenges and solutions for rural schools. Rural Special Education Quarterly, 24(1), 9–15.

    Article  Google Scholar 

  • Buchanan, J. M. (1978). Cost and choice: an inquiry in economic theory. University of Chicago Press.

    Google Scholar 

  • Buchanan, J. M. (2014). Public finance in democratic process: Fiscal institutions and individual choice. UNC Press Books.

    Google Scholar 

  • Buchanan, J. M., & Musgrave, R. A. (1999). Public finance and public choice: two contrasting visions of the State. MIT press.

    Google Scholar 

  • Callaway, B., & Li, T. (2017). Quantile treatment effects in difference in differences models with panel data.

    Google Scholar 

  • Chen, Y., Ding, S., Xu, Z., Zheng, H., & Yang, S. (2019). Blockchain-based medical records secure storage and medical service framework. Journal of Medical Systems, 43(1), 1–9.

    Article  Google Scholar 

  • Cheng, J. Y., Ngok, K., & Zhuang, W. (2010). The survival and development space for China’s labor NGOs: Informal politics and its uncertainty. Asian Survey, 50(6), 1082–1106.

    Article  Google Scholar 

  • Collins, B. C., & Ludlow, B. L. (2018). Best practices for students with moderate and severe disabilities: a rural retrospective. Rural Special Education Quarterly, 37(2), 79–89.

    Article  Google Scholar 

  • Conlin, M., & Jalilevand, M. (2015). Systemic inequities in special education financing. Journal of Education Finance, 41(1), 83–100.

    Google Scholar 

  • Cullen, J. B. (2003). The impact of fiscal incentives on student disability rates. Journal of Public Economics, 87(7–8), 1557–1589.

    Article  Google Scholar 

  • Desai, M., Messer, L. B., & Calache, H. (2001). A study of the dental treatment needs of children with disabilities in Melbourne. Australia. Australian Dental Journal, 46(1), 41–50.

    Article  Google Scholar 

  • Dhuey, E., & Lipscomb, S. (2013). Funding special education by total district enrollment: advantages, disadvantages, and policy considerations. Education Finance & Policy, 8(3), 316–331.

    Article  Google Scholar 

  • DiMaggio, P. J., & Anheier, H. K. (1990). The sociology of nonprofit organizations and sectors. Annual Review of Sociology, 16(1), 137–159.

    Article  Google Scholar 

  • Edmonds, B. C., & Spradlin, T. (2010). What does it take to become a high-performing special education planning district? A study of Indiana’s special education delivery service system. Remedial and Special Education, 31(5), 320–329.

    Article  Google Scholar 

  • Fan, G., Wang, X., & Zhu, H. (2003). NERI index of marketization of China’s provinces. National Economic Research Institute.

    Google Scholar 

  • Fan, G., Wang, X. L., Zhang, L. W., & Zhu, H. P. (2003). Report on the relative progress of marketization in various regions of China. Economic Studies, 3, 9–18. (in Chinese).

    Google Scholar 

  • Feng, Y. (2012). Teacher career motivation and professional development in special and inclusive education: Perspectives from Chinese teachers. International Journal of Inclusive Education, 16(3), 331–351.

    Article  Google Scholar 

  • Feng, Z., Liu, C., Guan, X., & Mor, V. (2012). China’s rapidly aging population creates policy challenges in shaping a viable long-term care system. Health Affairs, 31(12), 2764–2773.

    Article  Google Scholar 

  • Franck, B., & Joshi, D. K. (2017). Including students with disabilities in education for all: Lessons from Ethiopia. International Journal of Inclusive Education, 21(4), 347–360.

    Article  Google Scholar 

  • Fungácová, Z., & Weill, L. (2015). Understanding financial inclusion in China. China Economic Review, 34, 196–206.

    Article  Google Scholar 

  • Glaser, J., Kuwayama, D., Stone, D., Schanzer, A., Eldrup-Jorgensen, J., Powell, R., … & Nolan, B. (2014). Factors that determine the length of stay after carotid endarterectomy represent opportunities to avoid financial losses. Journal of Vascular Surgery, 60(4), 966–972.

    Google Scholar 

  • Han, K. (2020). Development of China’s elderly welfare in the transitional period. In Social welfare in transitional China (pp. 187–219). Palgrave Macmillan.

    Google Scholar 

  • Horsfall, D., Noonan, K., & Leonard, R. (2012). Bringing our dying home: How caring for someone at end of life builds social capital and develops compassionate communities. Health Sociology Review, 21(4), 373–382.

    Article  Google Scholar 

  • Imbens, G. W., & Wooldridge, J. M. (2009). Recent developments in the econometrics of program evaluation. Journal of Economic Literature, 47(1), 5–86.

    Article  Google Scholar 

  • Johansson, S., Leonard, R., & Noonan, K. (2012). Caring and the generation of social capital: Two models for a positive relationship. International Journal of Social Welfare, 21(1), 44–52.

    Article  Google Scholar 

  • Jung, H. S., & Thorbecke, E. (2003). The impact of public education expenditure on human capital, growth, and poverty in Tanzania and Zambia: A general equilibrium approach. Journal of Policy Modeling, 25(8), 701–725.

    Article  Google Scholar 

  • Keimig, R. K. (2021). Growing old in a New China: Transitions in elder care. Rutgers University Press.

    Google Scholar 

  • Kim, Y. S., Joo, H. J., & Lee, S. (2018). School factors related to high school dropout. KEDI Journal of Educational Policy, 15(1), 59–80.

    Google Scholar 

  • Koutrouba, K., Vamvakari, M., & Steliou, M. (2006). Factors correlated with teachers’ attitudes towards the inclusion of students with special educational needs in Cyprus. European Journal of Special Needs Education, 21(4), 381–394.

    Article  Google Scholar 

  • Krug, G., & Eberl, A. (2018). What explains the negative effect of unemployment on health? An analysis accounting for reverse causality. Research in Social Stratification and Mobility, 55, 25–39.

    Article  Google Scholar 

  • Li, N., Pang, L., Du, W., Chen, G., & Zheng, X. (2012). Association between poverty and psychiatric disability among Chinese population aged 15–64 years. Psychiatry Research, 200(2–3), 917–920.

    Article  Google Scholar 

  • Li, S. K., & He, X. (2019). The impacts of marketization and subsidies on the treatment quality performance of the Chinese hospitals sector. China Economic Review, 54, 41–50.

    Article  Google Scholar 

  • Liu, Y., Ji, D., Zhang, L., An, J., & Sun, W. (2021). Rural financial development impacts on agricultural technology innovation: Evidence from China. International Journal of Environmental Research and Public Health, 18(3), 1110.

    Article  Google Scholar 

  • Lucas, A. M., & Mbiti, I. M. (2012). Access, sorting, and achievement: The short-run effects of free primary education in Kenya. American Economic Journal: Applied Economics, 4(4), 226–253.

    Google Scholar 

  • Lucas, H. (2008). Information and communications technology for future health systems in developing countries. Social Science & Medicine, 66(10), 2122–2132.

    Article  Google Scholar 

  • Ma, Z., Xue, Y., & Hu, G. (2019). Nonparametric analysis of income distributions among different regions based on energy distance with applications to China Health and Nutrition Survey data. Communications for Statistical Applications and Methods, 26(1), 57–67.

    Article  Google Scholar 

  • Mahitivanichcha, K., & Parrish, T. (2005). The implications of fiscal incentives on identification rates and placement in special education: Formulas for influencing best practice. Journal of Education Finance, 1–22.

    Google Scholar 

  • Marchenko, Y. V. (2005). Estimating variance components in Stata. State Journal, 6(1), 1–21.

    Google Scholar 

  • Mason-Williams, L. (2015). Unequal opportunities: A profile of the distribution of special education teachers. Exceptional Children, 81, 247–262.

    Article  Google Scholar 

  • Meyers, A. B., Tobin, R. M., Huber, B. J., Conway, D. E., & Shelvin, K. H. (2015). Interdisciplinary collaboration supporting social-emotional learning in rural school systems. Journal of Educational & Psychological Consultation, 25(2–3), 109–128.

    Article  Google Scholar 

  • Milligan, C. (2012). There’s no place like home: Place and care in an ageing society.

    Google Scholar 

  • Owusu-Antwi, G., & Antwi, J. (2010). The analysis of the rural credit market in Ghana. International Business & Economics Research Journal (IBER), 9(8).

    Google Scholar 

  • Pulkkinen, J., & Jahnukainen, M. (2016). Finnish reform of the funding and provision of special education: The views of principals and municipal education administrators. Educational Review, 68(2), 171–188.

    Article  Google Scholar 

  • Sahi, S. K. (2013). Demographic and socio‐economic determinants of financial satisfaction. International Journal of Social Economics.

    Google Scholar 

  • Schirmer, B. R., & McGough, S. M. (2005). Teaching reading to children who are deaf: Do the conclusions of the National Reading Panel apply? Review of Educational Research, 75(1), 83–117.

    Article  Google Scholar 

  • Serrano-Cinca, C., & Gutiérrez-Nieto, B. (2014). Microfinance, the long tail and mission drift. International Business Review, 23(1), 181–194.

    Article  Google Scholar 

  • Shields, N., Synnot, A. J., & Barr, M. (2012). Perceived barriers and facilitators to physical activity for children with disability: A systematic review. British Journal of Sports Medicine, 46(14), 989–997.

    Article  Google Scholar 

  • Sindelar, P. T., Pua, D. J., Fisher, T., Peyton, D. J., Brownell, M. T., & Mason-Williams, L. (2018). The demand for special education teachers in rural schools revisited: An update on progress. Rural Special Education Quarterly, 37(1), 12–20.

    Article  Google Scholar 

  • Smit, K., de Brabander, C. J., & Martens, R. L. (2014). Student-centred and teacher-centred learning environment in pre-vocational secondary education: Psychological needs, and motivation. Scandinavian Journal of Educational Research, 58(6), 695–712.

    Article  Google Scholar 

  • Tanaka, S. (2015). Environmental regulations on air pollution in China and their impact on infant mortality. Journal of Health Economics, 42, 90–103.

    Article  Google Scholar 

  • Temple, J. (1999). The new growth evidence. Journal of Economic Literature, 1, 112–156.

    Article  Google Scholar 

  • Thornton, P. M. (2013). The advance of the party: Transformation or takeover of urban grassroots society? The China Quarterly, 1–18.

    Google Scholar 

  • Tilak, J. B. (2002). Determinants of household expenditure on education in rural India (No. 88). National Council of Applied Economic Research.

    Google Scholar 

  • Tompkins, R. B. (2006). The challenges and opportunities facing rural America: Finding answers in our public schools. Book presented at the Research and Policy Workshop of the Economic Research Service of the U.S. Department of Agriculture. Washington, D.C.

    Google Scholar 

  • Tran, K. V. (2014). Exploring the experience of children with disabilities at school settings in Vietnam context. Springer plus, 3(1), 103.

    Article  Google Scholar 

  • Turvey, C. G., & Kong, R. (2010). Informal lending amongst friends and relatives: Can microcredit compete in rural China? China Economic Review, 21(4), 544–556.

    Article  Google Scholar 

  • Wang, L. (2018). Study on the modern senior care service and security system. In The development of security and whole care system for the aged in China (pp. 57–125). Springer.

    Google Scholar 

  • Wang, P., Liu, Q., & Qi, Y. (2014). Factors influencing sustainable consumption behaviors: A survey of the rural residents in China. Journal of Cleaner Production, 63, 152–165.

    Article  Google Scholar 

  • White III, S. (2018). Aging gracefully: Spiritual care for aging adults. WestBow Press.

    Google Scholar 

  • Wong, Y. C., & Leung, J. (2012). Long-term care in China: Issues and prospects. Journal of Gerontological Social Work, 55(7), 570–586.

    Article  Google Scholar 

  • Yang, Z., & Tian, X. (2009). The transition of state-peasants relationship: From the fiscal perspective in three decades of reform in China. China Agricultural Economic Review, 1(4), 382–394.

    Article  Google Scholar 

  • Yeoh, B. S., & Huang, S. (2009). Foreign domestic workers and home-based care for elders in Singapore. Journal of Aging & Social Policy, 22(1), 69–88.

    Article  Google Scholar 

  • Yin, Z., Kang, C., Wang, L., Geng, D., & Xiong, Z. (2017). Public security expenditure, education investment, and social stability: An empirical analysis based on provincial panel data from China. Revista De Cercetare Si Interventie Sociala, 59, 239.

    Google Scholar 

  • Zhang, L., Zeng, Y., Wang, L., & Fang, Y. (2020). Urban-rural differences in long-term care service status and needs among home-based elderly people in China. International Journal of Environmental Research and Public Health, 17(5), 1701.

    Article  Google Scholar 

  • Zhang, Y., & Qiu, Z. (2015). The Analysis of the risks faced by China’s social endowment insurance under the background of rapid aging population. Open Journal of Business and Management, 3(02), 185.

    Article  Google Scholar 

  • Zheng, X., Chen, G., Song, X., Liu, J., Yan, L., Du, W., & Zhang, J. (2011). Twenty-year trends in the prevalence of disability in China. Bulletin of the World Health Organization, 89, 788–797.

    Article  Google Scholar 

  • Zhu, H. (2015). Unmet needs in long-term care and their associated factors among the oldest old in China. BMC Geriatrics, 15(1), 1–11.

    Article  Google Scholar 

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Luo, J. (2021). The Influencing Factors of the Imbalance of Rural Long Tail Public Services. In: Rural Long Tail Public Service and the Correction Mechanism. Springer, Singapore. https://doi.org/10.1007/978-981-16-4023-0_4

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