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How effective are sanctions on North Korea? Popular DMSP night-lights data may bias evaluations due to blurring and poor low-light detection

Author

Listed:
  • John Gibson

    (University of Waikato)

  • Bonggeun Kim

    (Seoul National University)

  • Geua Boe-Gibson

    (University of Waikato)

Abstract

The effect of sanctions on economic activity in targeted countries is increasingly studied with satellite-detected night-lights data because conventional economic activity data for such countries are either unavailable or untrustworthy. Many studies use data from the Defense Meteorological Satellite Program (DMSP), designed for observing clouds for short-term weather forecasts rather than for long-run observation of economic activity on earth. The DMSP data are flawed by blurring, and bottom-coding due to poor low-light detection. These errors may bias evaluation of sanction effectiveness. To show this we use a difference-in-differences analysis of impacts on night-lights of the shutdown of the Kaesong Industrial Zone in North Korea, which South Korea closed in 2016 in response to North Korea's nuclear tests. We estimate impacts of about 50% declines in luminosity, depending on the choice of comparison region, and these effects are always precisely estimated if data from the accurate Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi-NPP satellite are used. Yet with the more widely used DMSP data, apparent impacts are imprecisely estimated and are far smaller. A decomposition suggests much of the attenuation in estimated treatment effects if DMSP data are used comes from false zeroes, which are also likely to matter to evaluations in other poorly lit places.

Suggested Citation

  • John Gibson & Bonggeun Kim & Geua Boe-Gibson, 2022. "How effective are sanctions on North Korea? Popular DMSP night-lights data may bias evaluations due to blurring and poor low-light detection," Working Papers in Economics 22/06, University of Waikato, revised 14 Nov 2022.
  • Handle: RePEc:wai:econwp:22/06
    as

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    File URL: https://repec.its.waikato.ac.nz/wai/econwp/2206.pdf
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    References listed on IDEAS

    as
    1. Bluhm, Richard & Krause, Melanie, 2022. "Top lights: Bright cities and their contribution to economic development," Journal of Development Economics, Elsevier, vol. 157(C).
    2. John Gibson, 2021. "Better Night Lights Data, For Longer," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 770-791, June.
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    7. John Gibson & Susan Olivia & Geua Boe‐Gibson, 2020. "Night Lights In Economics: Sources And Uses," Journal of Economic Surveys, Wiley Blackwell, vol. 34(5), pages 955-980, December.
    8. Jan Ditzen & Yiannis Karavias & Joakim Westerlund, 2021. "Testing and Estimating Structural Breaks in Time Series and Panel Data in Stata," Papers 2110.14550, arXiv.org, revised Oct 2021.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    DMSP; mean-reverting error; night lights; sanctions; VIIRS; North Korea;
    All these keywords.

    JEL classification:

    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • F51 - International Economics - - International Relations, National Security, and International Political Economy - - - International Conflicts; Negotiations; Sanctions
    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development

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