IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v6y2020i1d10.1057_s41599-020-0417-4.html
   My bibliography  Save this article

What do we know about poverty in North Korea?

Author

Listed:
  • Jesús Crespo Cuaresma

    (International Institute of Applied System Analysis (IIASA)
    Vienna University of Economics and Business (WU)
    Wittgenstein Center for Demography and Global Human Capital (IIASA, VID/OEAW, WU)
    Austrian Institute of Economic Research (WIFO))

  • Olha Danylo

    (International Institute of Applied System Analysis (IIASA))

  • Steffen Fritz

    (International Institute of Applied System Analysis (IIASA))

  • Martin Hofer

    (Vienna University of Economics and Business (WU)
    World Data Lab)

  • Homi Kharas

    (World Data Lab
    The Brookings Institution)

  • Juan Carlos Laso Bayas

    (International Institute of Applied System Analysis (IIASA)
    World Data Lab)

Abstract

Reliable quantitative information on the North Korean economy is extremely scarce. In particular, reliable income per capita and poverty figures for the country are not available. In this contribution, we provide for the first time estimates of absolute poverty rates in North Korean subnational regions based on the combination of innovative remote-sensed night-time light intensity data (monthly information for built areas) with estimated income distributions. Our results, which are robust to the use of different methods to approximate the income distribution in the country, indicate that the share of persons living in extreme poverty in North Korea may be larger than previously thought. We estimate a poverty rate for the country of around 60% in 2018 and a high volatility in the dynamics of income at the national level in North Korea for the period 2012–2018. Income per capita estimates tend to decline significantly from 2012 to 2015 and present a recovery since 2016. The subnational estimates of income and poverty reveal a change in relative dynamics since the second half of the 2012–2018 period. The first part of the period is dominated by divergent dynamics in income across regions, while the second half reveals convergence in regional income.

Suggested Citation

  • Jesús Crespo Cuaresma & Olha Danylo & Steffen Fritz & Martin Hofer & Homi Kharas & Juan Carlos Laso Bayas, 2020. "What do we know about poverty in North Korea?," Palgrave Communications, Palgrave Macmillan, vol. 6(1), pages 1-8, December.
    • Handle: RePEc:pal:palcom:v:6:y:2020:i:1:d:10.1057_s41599-020-0417-4
    DOI: 10.1057/s41599-020-0417-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-020-0417-4
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/s41599-020-0417-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Martin Ravallion, 2012. "Why Don't We See Poverty Convergence?," American Economic Review, American Economic Association, vol. 102(1), pages 504-523, February.
    2. Barrios, Salvador & Strobl, Eric, 2009. "The dynamics of regional inequalities," Regional Science and Urban Economics, Elsevier, vol. 39(5), pages 575-591, September.
    3. Warwick J. McKibbin & Jong Wha Lee & Weifeng Liu & Cheol Jong Song, 2018. "Modeling the Economic Impacts of Korean Unification," Asian Economic Journal, East Asian Economic Association, vol. 32(3), pages 227-256, September.
    4. 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.
    5. Jesús Crespo Cuaresma & Wolfgang Fengler & Homi Kharas & Karim Bekhtiar & Michael Brottrager & Martin Hofer, 2018. "Will the Sustainable Development Goals be fulfilled? Assessing present and future global poverty," Palgrave Communications, Palgrave Macmillan, vol. 4(1), pages 1-8, December.
    6. Jeremy Proville & Daniel Zavala-Araiza & Gernot Wagner, 2017. "Night-time lights: A global, long term look at links to socio-economic trends," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-12, March.
    7. Kim, Byung-Yeon & Kim, Suk Jin & Lee, Keun, 2007. "Assessing the economic performance of North Korea, 1954-1989: Estimates and growth accounting analysis," Journal of Comparative Economics, Elsevier, vol. 35(3), pages 564-582, September.
    8. Jinpei Ou & Xiaoping Liu & Xia Li & Meifang Li & Wenkai Li, 2015. "Evaluation of NPP-VIIRS Nighttime Light Data for Mapping Global Fossil Fuel Combustion CO2 Emissions: A Comparison with DMSP-OLS Nighttime Light Data," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-20, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Simone Cecchini & Giovanni Savio & Varinia Tromben, 2022. "Mapping poverty rates in Chile with night lights and fractional multinomial models," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(4), pages 850-876, August.
    2. Jeet Agnihotri & Subhankar Mishra, 2021. "Indian Economy and Nighttime Lights," Papers 2103.03179, arXiv.org.
    3. 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.
    4. Thornton, Philip & Dijkman, Jeroen & Herrero, Mario & Szilagyi, Lili & Cramer, Laura, 2022. "Viewpoint: Aligning vision and reality in publicly funded agricultural research for development: A case study of CGIAR," Food Policy, Elsevier, vol. 107(C).
    5. Ian McCallum & Christopher Conrad Maximillian Kyba & Juan Carlos Laso Bayas & Elena Moltchanova & Matt Cooper & Jesus Crespo Cuaresma & Shonali Pachauri & Linda See & Olga Danylo & Inian Moorthy & Myr, 2022. "Estimating global economic well-being with unlit settlements," Nature Communications, Nature, vol. 13(1), pages 1-8, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ian McCallum & Christopher Conrad Maximillian Kyba & Juan Carlos Laso Bayas & Elena Moltchanova & Matt Cooper & Jesus Crespo Cuaresma & Shonali Pachauri & Linda See & Olga Danylo & Inian Moorthy & Myr, 2022. "Estimating global economic well-being with unlit settlements," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    2. Yohan Iddawela & Neil Lee & Andrés Rodríguez-Pose, 2021. "Quality of Sub-national Government and Regional Development in Africa," Journal of Development Studies, Taylor & Francis Journals, vol. 57(8), pages 1282-1302, August.
    3. World Bank, "undated". "South Asia Economic Focus, Fall 2017," World Bank Publications - Reports 28397, The World Bank Group.
    4. Achten, Sandra & Lessmann, Christian, 2020. "Spatial inequality, geography and economic activity," World Development, Elsevier, vol. 136(C).
    5. Jesús Crespo Cuaresma & Stephan Klasen & Konstantin M. Wacker, 2022. "When Do We See Poverty Convergence?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(6), pages 1283-1301, December.
    6. Shapiro, Daniel & Oh, Chang Hoon & Zhang, Peng, 2023. "Nighttime lights data and their implications for IB research," Journal of International Management, Elsevier, vol. 29(5).
    7. Lessmann, Christian & Seidel, André, 2017. "Regional inequality, convergence, and its determinants – A view from outer space," European Economic Review, Elsevier, vol. 92(C), pages 110-132.
    8. Brock, Gregory & German-Soto, Vicente, 2017. "Regional industrial informality and efficiency in Mexico, 1990–2013," Journal of Policy Modeling, Elsevier, vol. 39(5), pages 928-941.
    9. Breinlich, Holger & Ottaviano, Gianmarco I.P. & Temple, Jonathan R.W., 2014. "Regional Growth and Regional Decline," Handbook of Economic Growth, in: Philippe Aghion & Steven Durlauf (ed.), Handbook of Economic Growth, edition 1, volume 2, chapter 4, pages 683-779, Elsevier.
    10. Jung, Woojin, 2023. "Mapping community development aid: Spatial analysis in Myanmar," World Development, Elsevier, vol. 164(C).
    11. Jeremy Proville & Daniel Zavala-Araiza & Gernot Wagner, 2017. "Night-time lights: A global, long term look at links to socio-economic trends," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-12, March.
    12. Kim, Kyoochul, 2022. "The North Korean economy seen by satellite: Estimates of national performance, regional gaps based on nighttime light," Journal of Asian Economics, Elsevier, vol. 78(C).
    13. McSharry, Patrick & Mawejje, Joseph, 2024. "Estimating urban GDP growth using nighttime lights and machine learning techniques in data poor environments: The case of South Sudan," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    14. Amavilah, Voxi Heinrich, 2017. "Artificial nighttime lights and the “real” well-being of nations: ‘Measuring economic growth from outer space’ and welfare from right here on Earth," MPRA Paper 79744, University Library of Munich, Germany.
    15. Thiemo Fetzer & Oliver Pardo & Amar Shanghavi, 2018. "More than an urban legend: the short- and long-run effects of unplanned fertility shocks," Journal of Population Economics, Springer;European Society for Population Economics, vol. 31(4), pages 1125-1176, October.
    16. Leonardo Monasterio, 2011. "The Regional Inequality Frontier: Brazil (1872-2000)," ERSA conference papers ersa10p353, European Regional Science Association.
    17. Hayakawa, Kazunobu & Keola, Souknilanh & Silaphet, Korrakoun & Yamanouchi, Kenta, 2022. "Estimating the impacts of international bridges on foreign firm locations: a machine learning approach," IDE Discussion Papers 847, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    18. Beyer, Robert C.M. & Franco-Bedoya, Sebastian & Galdo, Virgilio, 2021. "Examining the economic impact of COVID-19 in India through daily electricity consumption and nighttime light intensity," World Development, Elsevier, vol. 140(C).
    19. Yu Kun Wang & Li Zhang, 2022. "Tax Revenue, Night Lights and Underground Economy: Evidence from China," Journal of Tax Reform, Graduate School of Economics and Management, Ural Federal University, vol. 8(2), pages 186-198.
    20. Zhou, Yixiao & Tyers, Rod, 2019. "Automation and inequality in China," China Economic Review, Elsevier, vol. 58(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:palcom:v:6:y:2020:i:1:d:10.1057_s41599-020-0417-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: https://www.nature.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.