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Nightlights as a Development Indicator: The Estimation of Gross Provincial Product (GPP) in Turkey

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  • Basihos, Seda

Abstract

For a while in Turkey, researchers dealing with spatial economics are unable to make detailed comparative and descriptive analysis on sub-national base due to lack of data. In particular, GDP, which is a basic indicator of economic activities, has not been published in Turkey at sub-national level since 2001. In this study, we use a different data source, night-time satellite imagery, to obtain sub-national GDP and GDP per capita series for the period between 2001 and 2013 at the level of provinces which is the basic administrative division of the Country. We also re-construct the series for the period between 1992 and 2001. For the estimation of sub-national GDP, we use Neural Network Algorithm.

Suggested Citation

  • Basihos, Seda, 2016. "Nightlights as a Development Indicator: The Estimation of Gross Provincial Product (GPP) in Turkey," MPRA Paper 75553, University Library of Munich, Germany, revised 09 Sep 2016.
    • Handle: RePEc:pra:mprapa:75553
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    References listed on IDEAS

    as
    1. Tilottama Ghosh & Sharolyn J. Anderson & Christopher D. Elvidge & Paul C. Sutton, 2013. "Using Nighttime Satellite Imagery as a Proxy Measure of Human Well-Being," Sustainability, MDPI, vol. 5(12), pages 1-32, November.
    2. Maxim Pinkovskiy & Xavier Sala-i-Martin, 2014. "Lights, Camera,... Income!: Estimating Poverty Using National Accounts, Survey Means, and Lights," NBER Working Papers 19831, National Bureau of Economic Research, Inc.
    3. Greg Tkacz & Sarah Hu, 1999. "Forecasting GDP Growth Using Artificial Neural Networks," Staff Working Papers 99-3, Bank of Canada.
    4. Feng, Lihua & Zhang, Jianzhen, 2014. "Application of artificial neural networks in tendency forecasting of economic growth," Economic Modelling, Elsevier, vol. 40(C), pages 76-80.
    5. Narayan, Paresh Kumar & Prasad, Arti, 2008. "Electricity consumption-real GDP causality nexus: Evidence from a bootstrapped causality test for 30 OECD countries," Energy Policy, Elsevier, vol. 36(2), pages 910-918, February.
    6. 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.
    7. Charlotta Mellander & José Lobo & Kevin Stolarick & Zara Matheson, 2015. "Night-Time Light Data: A Good Proxy Measure for Economic Activity?," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-18, October.
    8. Doll, Christopher N.H. & Muller, Jan-Peter & Morley, Jeremy G., 2006. "Mapping regional economic activity from night-time light satellite imagery," Ecological Economics, Elsevier, vol. 57(1), pages 75-92, April.
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    Cited by:

    1. 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.
    2. Najam, Rafiuddin, 2024. "Closing the gap: Effect of a gender quota on women’s access to education in Afghanistan," Economics of Education Review, Elsevier, vol. 99(C).

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    More about this item

    Keywords

    Nightlights; GDP; Gross Provincial Product; Economic Growth; Neural Network; Spatial Economics; Turkey;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development
    • O49 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Other
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

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