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Using satellite data to track socio-economic outcomes: a case study of Namibia

Author

Listed:
  • Thomas Ferreira

    (Department of Economics, Stellenbosch University)

Abstract
Efforts to improve the livelihoods of the poor in sub-Saharan Africa are hindered by data deficiencies. Surveys on socio-economic outcomes, for example, are generally conducted infrequently and are only statistically representative for relatively large geographic areas. To overcome these data limitations, researchers are increasingly turning to satellites which capture data for small areas at high frequencies. Night lights satellite data has particularly drawn interest and growth in lights have been shown to be a useful proxy for GDP growth (Henderson et al., 2012). However, in poor agricultural regions, night lights data might be less useful in explaining variation in socio-economic outcomes because such regions are generally under-electrified. Daytime satellite data measuring land use and vegetation quality, have been used to model socio-economic outcomes across regions, but no studies have explored whether daytime satellite data can be used to track welfare longitudinally. This paper argues that indicators of vegetation quality can be used to track welfare over time in agriculturally dominant areas. Such indicators are used extensively to predict agricultural yields and thus should correlate with welfare, as agriculture is an important source of income. This paper presents results from a small study in Namibia, that explores whether this is the case. Firstly, it is shown using classification of cropland, that daytime satellite data can identify areas of economic activity where night lights cannot. Secondly the relationship between vegetation quality and welfare is studied. Cross-sectionally, increases in vegetation quality correlate negatively with welfare. This is expected as the poor are more likely to live in rural areas. Within rural areas, however, vegetation quality correlates positively with welfare. This study thus supports the hypothesis that satellite based indicators of vegetative health can be used to track welfare over time in areas where night lights are not present.

Suggested Citation

  • Thomas Ferreira, 2018. "Using satellite data to track socio-economic outcomes: a case study of Namibia," Working Papers 12/2018, Stellenbosch University, Department of Economics.
    • Handle: RePEc:sza:wpaper:wpapers305
    as

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    File URL: https://www.ekon.sun.ac.za/wpapers/2018/wp122018/wp122018.pdf
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    References listed on IDEAS

    as
    1. Anthony Mveyange, 2015. "Night lights and regional income inequality in Africa," WIDER Working Paper Series 085, World Institute for Development Economic Research (UNU-WIDER).
    2. Klemens,Ben & Coppola,Andrea & Shron,Max, 2015. "Estimating local poverty measures using satellite images : a pilot application to Central America," Policy Research Working Paper Series 7329, The World Bank.
    3. Ziyang Cao & Zhifeng Wu & Yaoqiu Kuang & Ningsheng Huang & Meng Wang, 2016. "Coupling an Intercalibration of Radiance-Calibrated Nighttime Light Images and Land Use/Cover Data for Modeling and Analyzing the Distribution of GDP in Guangdong, China," Sustainability, MDPI, vol. 8(2), pages 1-18, January.
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    8. Sutton, Paul C. & Costanza, Robert, 2002. "Global estimates of market and non-market values derived from nighttime satellite imagery, land cover, and ecosystem service valuation," Ecological Economics, Elsevier, vol. 41(3), pages 509-527, June.
    9. Maxim Pinkovskiy & Xavier Sala-i-Martin, 2016. "Lights, Camera … Income! Illuminating the National Accounts-Household Surveys Debate," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(2), pages 579-631.
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    More about this item

    Keywords

    Satellites; Night Lights; Normalised Differenced Vegetation Index; Agriculture; Poverty; Namibia;
    All these keywords.

    JEL classification:

    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth

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