The use of geographically weighted regression to improve information from satellite night light data in evaluating the economic effects of the 2010 FIFA World Cup

Thierry Yerema Coulibaly, Mihoko Tegawa Wakamatsu, Shunsuke Managi

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Developing countries lack subnational data to assess mega-events. Accordingly, an economic proxy is developed to quantify city-level income growth of economies of the South African cities that hosted the 2010 FIFA World Cup by performing a geographically weighted regression between night light data and total city-level income and using it to predict total income from 1992 to 2013. A panel data comparison of income growth in host and non-host cities revealed similar income growth. However, the cities that invested the most in building or renovating their stadia experienced 9% lower income growth than other host cities, suggesting the limited ability of the World Cup to stimulate economic growth and the presence of inefficient investment.

Original languageEnglish
Pages (from-to)463-481
Number of pages19
JournalArea Development and Policy
Volume7
Issue number4
DOIs
Publication statusPublished - 2022

All Science Journal Classification (ASJC) codes

  • Geography, Planning and Development
  • Sociology and Political Science
  • Urban Studies
  • Public Administration
  • Nature and Landscape Conservation

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