IDEAS home Printed from https://ideas.repec.org/p/cpr/ceprdp/13748.html
   My bibliography  Save this paper

The Hard Problem of Prediction for Conflict Prevention

Author

Listed:
  • Mueller, Hannes Felix
  • Rauh, Christopher

Abstract

There is a growing interest in better conflict prevention and this provides a strong motivation for better conflict forecasting. A key problem of conflict forecasting for prevention is that predicting the start of conflict in previously peaceful countries is extremely hard. To make progress in this hard problem this project exploits both supervised and unsupervised machine learning. Specifically, the latent Dirichlet allocation (LDA) model is used for feature extraction from 3.8 million newspaper articles and these features are then used in a random forest model to predict conflict. We find that forecasting hard cases is possible and benefits from supervised learning despite the small sample size. Several topics are negatively associated with the outbreak of conflict and these gain importance when predicting hard onsets. The trees in the random forest use the topics in lower nodes where they are evaluated conditionally on conflict history, which allows the random forest to adapt to the hard problem and provides useful forecasts for prevention.

Suggested Citation

  • Mueller, Hannes Felix & Rauh, Christopher, 2019. "The Hard Problem of Prediction for Conflict Prevention," CEPR Discussion Papers 13748, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:13748
    as

    Download full text from publisher

    File URL: http://www.cepr.org/active/publications/discussion_papers/dp.php?dpno=13748
    Download Restriction: CEPR Discussion Papers are free to download for our researchers, subscribers and members. If you fall into one of these categories but have trouble downloading our papers, please contact us at subscribers@cepr.org
    ---><---

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

    Other versions of this item:

    References listed on IDEAS

    as
    1. Jon Kleinberg & Jens Ludwig & Sendhil Mullainathan & Ziad Obermeyer, 2015. "Prediction Policy Problems," American Economic Review, American Economic Association, vol. 105(5), pages 491-495, May.
    2. Antonio Ciccone, 2018. "International Commodity Prices and Civil War Outbreak: New Evidence for Sub-Saharan Africa and Beyond," Working Papers 1016, Barcelona Graduate School of Economics.
    3. Christopher Blattman & Julian C. Jamison & Margaret Sheridan, 2017. "Reducing Crime and Violence: Experimental Evidence from Cognitive Behavioral Therapy in Liberia," American Economic Review, American Economic Association, vol. 107(4), pages 1165-1206, April.
    4. Stelios Michalopoulos & Elias Papaioannou, 2016. "The Long-Run Effects of the Scramble for Africa," American Economic Review, American Economic Association, vol. 106(7), pages 1802-1848, July.
    5. Olivier J. Blanchard & Daniel Leigh, 2013. "Growth Forecast Errors and Fiscal Multipliers," American Economic Review, American Economic Association, vol. 103(3), pages 117-120, May.
    6. Ralph Sundberg & Erik Melander, 2013. "Introducing the UCDP Georeferenced Event Dataset," Journal of Peace Research, Peace Research Institute Oslo, vol. 50(4), pages 523-532, July.
    7. Samuel Bazzi & Robert A. Blair & Christopher Blattman & Oeindrila Dube & Matthew Gudgeon & Richard Peck, 2019. "The Promise and Pitfalls of Conflict Prediction: Evidence from Colombia and Indonesia," Boston University - Department of Economics - The Institute for Economic Development Working Papers Series dp-328, Boston University - Department of Economics.
    8. Graham Elliott & Allan Timmermann, 2016. "Economic Forecasting," Economics Books, Princeton University Press, edition 1, number 10740, April.
    9. Oeindrila Dube & Juan F. Vargas, 2013. "Commodity Price Shocks and Civil Conflict: Evidence from Colombia," Review of Economic Studies, Oxford University Press, vol. 80(4), pages 1384-1421.
    10. Johannes Hörner & Massimo Morelli & Francesco Squintani, 2015. "Mediation and Peace," Review of Economic Studies, Oxford University Press, vol. 82(4), pages 1483-1501.
    11. Samuel Bazzi & Christopher Blattman, 2014. "Economic Shocks and Conflict: Evidence from Commodity Prices," American Economic Journal: Macroeconomics, American Economic Association, vol. 6(4), pages 1-38, October.
    12. Susan Athey & Guido W. Imbens, 2019. "Machine Learning Methods That Economists Should Know About," Annual Review of Economics, Annual Reviews, vol. 11(1), pages 685-725, August.
    13. Celiku,Bledi & Kraay,Aart C., 2017. "Predicting conflict," Policy Research Working Paper Series 8075, The World Bank.
    14. Stock, James H. & Watson, Mark W., 2006. "Forecasting with Many Predictors," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 10, pages 515-554, Elsevier.
    15. Barbara Rossi & Tatevik Sekhposyan, 2015. "Macroeconomic Uncertainty Indices Based on Nowcast and Forecast Error Distributions," American Economic Review, American Economic Association, vol. 105(5), pages 650-655, May.
    16. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, Oxford University Press, vol. 131(4), pages 1593-1636.
    17. Joan Esteban & Laura Mayoral & Debraj Ray, 2012. "Ethnicity and Conflict: An Empirical Study," American Economic Review, American Economic Association, vol. 102(4), pages 1310-1342, June.
    18. Michael D Ward & Brian D Greenhill & Kristin M Bakke, 2010. "The perils of policy by p-value: Predicting civil conflicts," Journal of Peace Research, Peace Research Institute Oslo, vol. 47(4), pages 363-375, July.
    19. Mueller, Hannes & Rauh, Christopher, 2018. "Reading Between the Lines: Prediction of Political Violence Using Newspaper Text," American Political Science Review, Cambridge University Press, vol. 112(2), pages 358-375, May.
    20. Giglio, Stefano & Kelly, Bryan & Pruitt, Seth, 2016. "Systemic risk and the macroeconomy: An empirical evaluation," Journal of Financial Economics, Elsevier, vol. 119(3), pages 457-471.
    21. Adam Meirowitz & Massimo Morelli & Kristopher W. Ramsay & Francesco Squintani, 2019. "Dispute Resolution Institutions and Strategic Militarization," Journal of Political Economy, University of Chicago Press, vol. 127(1), pages 378-418.
    22. Svensson, Lars E.O., 2017. "Cost-benefit analysis of leaning against the wind," Journal of Monetary Economics, Elsevier, vol. 90(C), pages 193-213.
    23. Larsen, Vegard H. & Thorsrud, Leif A., 2019. "The value of news for economic developments," Journal of Econometrics, Elsevier, vol. 210(1), pages 203-218.
    24. Sendhil Mullainathan & Jann Spiess, 2017. "Machine Learning: An Applied Econometric Approach," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 87-106, Spring.
    25. Arnaud Costinot & Dave Donaldson & Cory Smith, 2016. "Evolving Comparative Advantage and the Impact of Climate Change in Agricultural Markets: Evidence from 1.7 Million Fields around the World," Journal of Political Economy, University of Chicago Press, vol. 124(1), pages 205-248.
    26. Malcolm Chalmers, 2007. "Spending To Save? The Cost-Effectiveness Of Conflict Prevention," Defence and Peace Economics, Taylor & Francis Journals, vol. 18(1), pages 1-23.
    27. G. Elliott & C. Granger & A. Timmermann (ed.), 2013. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 2, number 2.
    28. Christopher Blattman & Jeannie Annan, 2015. "Can Employment Reduce Lawlessness and Rebellion? A Field Experiment with High-Risk Men in a Fragile State," NBER Working Papers 21289, National Bureau of Economic Research, Inc.
    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. Mark Musumba & Naureen Fatema & Shahriar Kibriya, 2021. "Prevention Is Better Than Cure: Machine Learning Approach to Conflict Prediction in Sub-Saharan Africa," Sustainability, MDPI, Open Access Journal, vol. 13(13), pages 1-18, July.

    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. Stoop, Nik & Verpoorten, Marijke & van der Windt, Peter, 2019. "Artisanal or industrial conflict minerals? Evidence from Eastern Congo," World Development, Elsevier, vol. 122(C), pages 660-674.
    2. Verme, Paolo & Schuettler, Kirsten, 2021. "The impact of forced displacement on host communities: A review of the empirical literature in economics," Journal of Development Economics, Elsevier, vol. 150(C).
    3. Samuel Bazzi & Robert A. Blair & Christopher Blattman & Oeindrila Dube & Matthew Gudgeon & Richard Merton Peck, 2019. "The Promise and Pitfalls of Conflict Prediction: Evidence from Colombia and Indonesia," NBER Working Papers 25980, National Bureau of Economic Research, Inc.
    4. Cervellati, Matteo & Esposito, Elena & Sunde, Uwe & Valmori, Simona, 2016. "Malaria Risk and Civil Violence," CEPR Discussion Papers 11496, C.E.P.R. Discussion Papers.
    5. Adhvaryu, Achyuta & Fenske, James & Khanna, Gaurav & Nyshadham, Anant, 2021. "Resources, conflict, and economic development in Africa," Journal of Development Economics, Elsevier, vol. 149(C).
    6. Gehring, Kai & Langlotz, Sarah & Kienberger, Stefan, 2018. "Stimulant or depressant? Resource-related income shocks and conflict," Working Papers 0652, University of Heidelberg, Department of Economics.
    7. Camille Laville, 2018. "The econometrical causal analysis of internal conflicts: The evolutions of a growing literature [L’analyse économétrique des conflits internes par l’approche causale : les évolutions d’une littérat," Working Papers hal-01940461, HAL.
    8. Leander Heldring, 2019. "The Origins of Violence in Rwanda," HiCN Working Papers 299, Households in Conflict Network.
    9. Cemal Eren Arbatlı & Quamrul H. Ashraf & Oded Galor & Marc Klemp, 2020. "Diversity and Conflict," Econometrica, Econometric Society, vol. 88(2), pages 727-797, March.
    10. Ang, James B. & Gupta, Satyendra Kumar, 2018. "Agricultural yield and conflict," Journal of Environmental Economics and Management, Elsevier, vol. 92(C), pages 397-417.
    11. Bryan T. Kelly & Asaf Manela & Alan Moreira, 2019. "Text Selection," NBER Working Papers 26517, National Bureau of Economic Research, Inc.
    12. Eoin McGuirk & Marshall Burke, 2020. "The Economic Origins of Conflict in Africa," Journal of Political Economy, University of Chicago Press, vol. 128(10), pages 3940-3997.
    13. Jasmien De Winne & Gert Peersman, 2021. "The Impact of Food Prices on Conflict Revisited," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 547-560, March.
    14. Arthur Blouin & Julian Dyer, 2021. "How Cultures Converge: An Empirical Investigation of Trade and Linguistic Exchange," Working Papers tecipa-691, University of Toronto, Department of Economics.
    15. Fenske, James & Kala, Namrata, 2017. "1807: Economic shocks, conflict and the slave trade," Journal of Development Economics, Elsevier, vol. 126(C), pages 66-76.
    16. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti, 2019. "Macro-Financial Linkages in the High-Frequency Domain: The Effects of Uncertainty on Realized Volatility," CESifo Working Paper Series 8000, CESifo.
    17. James Fenske & Igor Zurimendi, 2017. "Oil and ethnic inequality in Nigeria," Journal of Economic Growth, Springer, vol. 22(4), pages 397-420, December.
    18. McKenzie, David J. & Sansone, Dario, 2017. "Man vs. Machine in Predicting Successful Entrepreneurs: Evidence from a Business Plan Competition in Nigeria," CEPR Discussion Papers 12523, C.E.P.R. Discussion Papers.
    19. Manotas-Hidalgo, Beatriz & Pérez-Sebastián, Fidel & Campo-Bescós, Miguel Angel, 2021. "The role of ethnic characteristics in the effect of income shocks on African conflict," World Development, Elsevier, vol. 137(C).
    20. Arinze Nwokolo, 2018. "Oil Price Shocks and Civil Conflict: Evidence from Nigeria," HiCN Working Papers 274, Households in Conflict Network.

    More about this item

    Keywords

    Armed Conflict; Forecasting; Machine Learning; Newspaper Text; Random Forest; Topic Models;
    All these keywords.

    JEL classification:

    • F51 - International Economics - - International Relations, National Security, and International Political Economy - - - International Conflicts; Negotiations; Sanctions
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:cpr:ceprdp:13748. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://www.cepr.org .

    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: (email available below). General contact details of provider: https://www.cepr.org .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.