[ISPRS International Journal of Geo-Information] Do Charitable Foundations Spend Money Where People Need It Most? A Spatial Analysis of China

publications

Yongze Song 1,* and Linyun Fu 2,*

1 Australasian Joint Research Centre for Building Information Modelling, School of Built Environment, Curtin University, Perth, WA 6845, Australia
2 George Warren Brown School of Social Work, Washington University in St. Louis, St. Louis, MO 63130, USA

* Correspondence: yongze.song@postgrad.curtin.edu.au (Y.S.); fulinyun@wustl.edu (L.F.); Tel.: +61-8-9266-9059 (Y.S.)

Abstract: Charitable foundations are a critical part of public services. However, there is a large gap between the locations and expenditures of charitable foundations and the real population needs for most nations. Three types of Chinese local charity foundations, i.e., those for poverty, education and medical assistance, are used as examples to explore the distinct gaps. The spatial distributions of local charity foundations are characterized by spatial scan statistics and spatial autocorrelation models. The local population needs of charitable assistance for poverty, education and medical services are quantified with their respective weighted proxy indexes of the current conditions. Thus, the nonlinear relationships between population needs and the expenditures of local charitable foundations are described with generalized additive models. The results show that both the participation rate and the charity expenditures of the foundations are highly clustered within a few cities where the population needs are relatively small and are furthermore rare among the other cities. The charity expenditures of local foundations are nonlinearly correlated with the current conditions of socioeconomic development, education and medical levels due to the diverse development stages of the cities. This study provides quantitative evidence for local authorities and charitable foundations to make targeted and constructive decisions to gradually reduce the distinct gaps.

Keywords: social science; charitable foundations; NGOs; spatial analysis; spatial autocorrelation; spatial scan statistics; generalized additive model

Fulltext (Open Access): http://www.mdpi.com/2220-9964/7/3/100

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