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What luminosity data can and cannot reveal about South Africa’s urban economies

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Listed:
  • Takwanisa Machemedze

Abstract

Discussion Document 10 As novel types of data are becoming available, they can be incorporated into tracking economies’ progress towards achieving their goals. This paper provides an in-depth analysis on how nighttime light data can be used to analyse the dynamics of economic activity in South Africa. These lights leave a footprint of human activity […]

Suggested Citation

  • Takwanisa Machemedze, "undated". "What luminosity data can and cannot reveal about South Africa’s urban economies," Working Papers 10, Economic Research Southern Africa.
    • Handle: RePEc:rza:wpaper:10
    as

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    Citations

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    Cited by:

    1. Stan du Plessis & Ben Smit & Federico Sturzenegger, 2008. "Identifying Aggregate Supply and Demand Shocks in South Africa †," Journal of African Economies, Centre for the Study of African Economies, vol. 17(5), pages 765-793, November.
    2. Leonce Ndikumana, 2008. "Can macroeconomic policy stimulate private investment in South Africa? New insights from aggregate and manufacturing sector-level evidence," Journal of International Development, John Wiley & Sons, Ltd., vol. 20(7), pages 869-887.
    3. Stan Du Plessis & Ben Smit & Federico Sturzenegger, 2007. "The Cyclicality Of Monetary And Fiscal Policy In South Africa Since 1994," South African Journal of Economics, Economic Society of South Africa, vol. 75(3), pages 391-411, September.
    4. Jeffrey Frankel & Ben Smit & Federico Sturzenegger, 2006. "South Africa: Macroeconomic Challenges after a Decade of Success," CID Working Papers 133, Center for International Development at Harvard University.
    5. Wh Boshoff, 2005. "The Properties Of Cycles In South African Financial Variables And Their Relation To The Business Cycle," South African Journal of Economics, Economic Society of South Africa, vol. 73(4), pages 694-709, December.

    More about this item

    Keywords

    big data; rural development; South Africa; Spatial Models; Urbanisation;
    All these keywords.

    JEL classification:

    • C89 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods
    • R38 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Government Policy
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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