Volume 37 - Article 16 | Pages 493–526

Different places, different stories: A study of the spatial heterogeneity of county-level fertility in China

By Donghui Wang, Guangqing Chi

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Date received:17 Aug 2016
Date published:23 Aug 2017
Word count:5080
Keywords:China, fertility, geographically weighted regression, spatial heterogeneity
DOI:10.4054/DemRes.2017.37.16
 

Abstract

Background: China has been characterized by persistently low fertility rates since the 1990s. Existing literature has examined the relationship between fertility levels and social, economic, and policy-related determinants. However, the possible spatial variation in these relationships has not been investigated.

Objective: The purpose of this study is to examine the potential spatially varying relationships between county-level fertility rates and policy and socioeconomic factors in China.

Methods: Using geocoded 2010 county-level census data, this study adopts the geographically weighted regression (GWR) method to identify place-specific relationships between county-level total fertility rate (TFR) and socioeconomic and policy-related factors.

Conclusions: We find that relationships between TFR and widely used social, economic, and policy-related factors (rural Hukou, ethnic minority, female education, net migration rate, poor living standard, sex ratio at birth, fertility policy compliance ratio) vary spatially in terms of direction, strength, and magnitude. This spatial variation is largely due to differences in local characteristics. The differences between and the complexities of localities cannot be told by a single story of either government intervention or socioeconomic development.

Contribution: This study extends existing fertility research on China by explicitly recognizing the spatial heterogeneity in the impact of policy and socioeconomic factors on the local fertility rate. This study sets the stage for future research that will contextually analyze varying fertility rates at the subnational level in China and other countries.

Author's Affiliation

Donghui Wang - Pennsylvania State University, United States of America [Email]
Guangqing Chi - Pennsylvania State University, United States of America [Email]

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