An Analysis of Well-Being Determinants at the City Level in China Using Big Data

Yukun Zhao (), Feng Yu (), Bo Jing (), Xiaomeng Hu (), Ang Luo () and Kaiping Peng ()
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Yukun Zhao: Tsinghua University
Feng Yu: Xi’an Jiaotong University
Bo Jing: Tsinghua University
Xiaomeng Hu: Tsinghua University
Ang Luo: Weibo Inc
Kaiping Peng: Tsinghua University

Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, 2019, vol. 143, issue 3, No 4, 973-994

Abstract: Abstract Prior research shows mixed results on the relationship between well-being and economic growth, and the relationship between well-being and population size, yet consistent associations between well-being and green space. This paper aims to analyse the relationship between city residents’ well-being and three established indicators: economic growth (as measured by GDP per capita), population size, and green space. A Big Data approach based on the lexica used on social media was proposed to develop well-being indicators. Using the 2016 data of Weibo (i.e. the Chinese version of Twitter), this study finds that the relationship between residents’ well-being and GDP per capita and the relationship between residents’ well-being and population size both form inverted U-shaped curves. Specifically, for poor cities, levels of well-being increase as GDP per capita increases. But after peaking at around the median GDP per capita point, levels of well-being drop as the city’s economy continues to increase. Similarly, levels of well-being increase with population size for small cities, but decrease for those cities whose population sizes rank in the top quarter. In contrast, there is a positive relationship between well-being and the percentage of green space for all cities. Implications and future directions are discussed.

Keywords: Well-being; City level; Economic growth; Population size; Green space; Big Data; Chinese social media (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s11205-018-2015-z

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