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Bright Lights, Big Cities : measuring national and subnational economic growth in Africa from outer space, with an application to Kenya and Rwanda

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  • Bundervoet,Tom
  • Maiyo,Laban
  • Sanghi,Apurva

Abstract

This paper uses the night lights (satellite imagery from outer space) approach to estimate growth in and levels of subnational 2013 gross domestic product for 47 counties in Kenya and 30 districts in Rwanda. Estimating subnational gross domestic product is consequential for three reasons. First, there is strong policy interest in how growth can occur in different parts of countries, so that communities can share in national prosperity and not get left behind. Second, subnational entities want to understand how they stack up against their neighbors and competitors, and how much they contribute to national gross domestic product. Third, such information could help private investors to assess where to undertake investments. Using night lights has the advantage of seeing a new and more accurate estimation of informal activity, and being independent of official data. However, the approach may underestimate economic activity in sectors that are largely unlit notably agriculture. For Kenya, the results of the analysis affirm that Nairobi County is the largest contributor to national gross domestic product. However, at 13 percent, this contribution is lower than commonly thought. For Rwanda, the three districts of Kigali account for 40 percent of national gross domestic product, underscoring the lower scale of economic activity in the rest of the country. To get a composite picture of subnational economic activity, especially in the context of rapidly improving official statistics in Kenya and Rwanda, it is important to estimate subnational gross domestic product using standard approaches (production, expenditure, income).

Suggested Citation

  • Bundervoet,Tom & Maiyo,Laban & Sanghi,Apurva, 2015. "Bright Lights, Big Cities : measuring national and subnational economic growth in Africa from outer space, with an application to Kenya and Rwanda," Policy Research Working Paper Series 7461, The World Bank.
  • Handle: RePEc:wbk:wbrwps:7461
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    References listed on IDEAS

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    1. J. Vernon Henderson & Adam Storeygard & David N. Weil, 2012. "Measuring Economic Growth from Outer Space," American Economic Review, American Economic Association, vol. 102(2), pages 994-1028, April.
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    Cited by:

    1. , Diego, 2017. "The Natural and Infrastructural Capital Elements of Potential Post-Electrification Wealth Creation in Kenya," SocArXiv ddnhz, Center for Open Science.
    2. Henning Krause & Anja Faße & Ulrike Grote, 2019. "Nutrient-Dense Crops for Rural and Peri-Urban Smallholders in Kenya—A Regional Social Accounting Approach," Sustainability, MDPI, vol. 11(11), pages 1-22, May.
    3. Francis Rathinam & Sayak Khatua & Zeba Siddiqui & Manya Malik & Pallavi Duggal & Samantha Watson & Xavier Vollenweider, 2021. "Using big data for evaluating development outcomes: A systematic map," Campbell Systematic Reviews, John Wiley & Sons, vol. 17(3), September.
    4. Douglas Barrios & Ana Grisanti & Jose Ramon Morales Arilla & Juan Obach & Johanna Ramos & Jorge Tapia & Miguel Angel Santos, 2018. "There is a Future after Cars: Economic Growth Analysis for Hermosillo," Growth Lab Working Papers 130, Harvard's Growth Lab.
    5. Majdi Debbich, 2019. "Assessing Oil and Non-Oil GDP Growth from Space: An Application to Yemen 2012-17," IMF Working Papers 2019/221, International Monetary Fund.
    6. World Bank, "undated". "South Asia Economic Focus, Fall 2017," World Bank Publications - Reports 28397, The World Bank Group.
    7. Syed Abul, Basher & Jobaida, Behtarin & Salim, Rashid, 2022. "Convergence across Subnational Regions of Bangladesh – What the Night Lights Data Say?," MPRA Paper 111963, University Library of Munich, Germany.
    8. Jesson A. Pagaduan, 2022. "Do higher‐quality nighttime lights and net primary productivity predict subnational GDP in developing countries? Evidence from the Philippines," Asian Economic Journal, East Asian Economic Association, vol. 36(3), pages 288-317, September.
    9. Nakamura, Shohei & Avner, Paolo, 2021. "Spatial distributions of job accessibility, housing rents, and poverty: The case of Nairobi," Journal of Housing Economics, Elsevier, vol. 51(C).
    10. Konno, Akio & Kato, Hironori & Takeuchi, Wataru & Kiguchi, Riku, 2021. "Global evidence on productivity effects of road infrastructure incorporating spatial spillover effects," Transport Policy, Elsevier, vol. 103(C), pages 167-182.
    11. Blankespoor,Brian & Ru,Yating & Wood-Sichra,Ulrike & Chambers,Thomas Timothy & You,Liangzhi & Kalvelagen,Erwin, 2022. "Estimating Local Agricultural GDP across the World," Policy Research Working Paper Series 10109, The World Bank.
    12. Stein, Merlin, 2021. "Re-evaluating RCTs with nightlights - An example from biometric smartcards in India," University of Tübingen Working Papers in Business and Economics 152, University of Tuebingen, Faculty of Economics and Social Sciences, School of Business and Economics.
    13. Abhishek Singhal & Sohini Sahu & Siddhartha Chattopadhyay & Abhijit Mukherjee & Soumendra N Bhanja, 2020. "Using night time lights to find regional inequality in India and its relationship with economic development," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-18, November.

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