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The information content of conflict, social unrest and policy uncertainty measures for macroeconomic forecasting

Author

Listed:
  • Marina Diakonova

    (Banco de España)

  • Luis Molina

    (Banco de España)

  • Hannes Mueller

    (IAE-CSIC and BSE)

  • Javier J. Pérez

    (Banco de España)

  • Cristopher Rauh

    (University of Cambridge)

Abstract
It is widely accepted that episodes of social unrest, conflict, political tensions and policy uncertainty affect the economy. Nevertheless, the real-time dimension of such relationships is less studied, and it remains unclear how to incorporate them in a forecasting framework. This can be partly explained by a certain divide between the economic and political science contributions in this area, as well as by the traditional lack of availability of high-frequency indicators measuring such phenomena. The latter constraint, though, is becoming less of a limiting factor through the production of text-based indicators. In this paper we assemble a dataset of such monthly measures of what we call “institutional instability”, for three representative emerging market economies: Brazil, Colombia and Mexico. We then forecast quarterly GDP by adding these new variables to a standard macro-forecasting model in a mixed-frequency MIDAS framework. Our results strongly suggest that capturing institutional instability based on a broad set of standard high-frequency indicators is useful when forecasting quarterly GDP. We also analyse the relative strengths and weaknesses of the approach.

Suggested Citation

  • Marina Diakonova & Luis Molina & Hannes Mueller & Javier J. Pérez & Cristopher Rauh, 2022. "The information content of conflict, social unrest and policy uncertainty measures for macroeconomic forecasting," Working Papers 2232, Banco de España.
  • Handle: RePEc:bde:wpaper:2232
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    1. Oguzhan Cepni & I. Ethem Guney & Norman R. Swanson, 2020. "Forecasting and nowcasting emerging market GDP growth rates: The role of latent global economic policy uncertainty and macroeconomic data surprise factors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 18-36, January.
    2. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
    3. Asaf Zussman & Noam Zussman, 2006. "Assassinations: Evaluating the Effectiveness of an Israeli Counterterrorism Policy Using Stock Market Data," Journal of Economic Perspectives, American Economic Association, vol. 20(2), pages 193-206, Spring.
    4. Timothy Besley & Hannes Mueller, 2018. "Predation, Protection, and Productivity: A Firm-Level Perspective," American Economic Journal: Macroeconomics, American Economic Association, vol. 10(2), pages 184-221, April.
    5. Besley, Timothy & Ghatak, Maitreesh, 2010. "Property Rights and Economic Development," Handbook of Development Economics, in: Dani Rodrik & Mark Rosenzweig (ed.), Handbook of Development Economics, edition 1, volume 5, chapter 0, pages 4525-4595, Elsevier.
    6. Andres–Escayola, Erik & Berganza, Juan Carlos & Campos, Rodolfo G. & Molina, Luis, 2023. "A BVAR toolkit to assess macrofinancial risks in Brazil and Mexico," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(1).
    7. Hannes Mueller & Christopher Rauh, 2022. "Using past violence and current news to predict changes in violence," International Interactions, Taylor & Francis Journals, vol. 48(4), pages 579-596, July.
    8. Kuzin, Vladimir & Marcellino, Massimiliano & Schumacher, Christian, 2011. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the euro area," International Journal of Forecasting, Elsevier, vol. 27(2), pages 529-542.
    9. Timothy Besley & Hannes Mueller, 2012. "Estimating the Peace Dividend: The Impact of Violence on House Prices in Northern Ireland," American Economic Review, American Economic Association, vol. 102(2), pages 810-833, April.
    10. Acemoglu, Daron & Johnson, Simon & Robinson, James & Thaicharoen, Yunyong, 2003. "Institutional causes, macroeconomic symptoms: volatility, crises and growth," Journal of Monetary Economics, Elsevier, vol. 50(1), pages 49-123, January.
    11. Barrett, Philip & Appendino, Maximiliano & Nguyen, Kate & de Leon Miranda, Jorge, 2022. "Measuring social unrest using media reports," Journal of Development Economics, Elsevier, vol. 158(C).
    12. Dario Caldara & Matteo Iacoviello, 2022. "Measuring Geopolitical Risk," American Economic Review, American Economic Association, vol. 112(4), pages 1194-1225, April.
    13. Alberto Abadie & Javier Gardeazabal, 2003. "The Economic Costs of Conflict: A Case Study of the Basque Country," American Economic Review, American Economic Association, vol. 93(1), pages 113-132, March.
    14. Thu, Le Ha & Leon-Gonzalez, Roberto, 2021. "Forecasting macroeconomic variables in emerging economies," Journal of Asian Economics, Elsevier, vol. 77(C).
    15. Duncan, Roberto & Martínez-García, Enrique, 2019. "New perspectives on forecasting inflation in emerging market economies: An empirical assessment," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1008-1031.
    16. Claeskens, Gerda & Magnus, Jan R. & Vasnev, Andrey L. & Wang, Wendun, 2016. "The forecast combination puzzle: A simple theoretical explanation," International Journal of Forecasting, Elsevier, vol. 32(3), pages 754-762.
    17. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    18. 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.
    19. Tarek A Hassan & Stephan Hollander & Laurence van Lent & Ahmed Tahoun, 2019. "Firm-Level Political Risk: Measurement and Effects," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 134(4), pages 2135-2202.
    20. Domenico Giannone & Lucrezia Reichlin & David H. Small, 2005. "Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases," Finance and Economics Discussion Series 2005-42, Board of Governors of the Federal Reserve System (U.S.).
    21. Hadzi-Vaskov Metodij & Pienknagura Samuel & Ricci Luca Antonio, 2023. "The Macroeconomic Impact of Social Unrest," The B.E. Journal of Macroeconomics, De Gruyter, vol. 23(2), pages 917-958, June.
    22. Daron Acemoglu & Simon Johnson & James A. Robinson, 2001. "The Colonial Origins of Comparative Development: An Empirical Investigation," American Economic Review, American Economic Association, vol. 91(5), pages 1369-1401, December.
    23. Danilo Leiva-Leon & Gabriel Perez-Quiros & Eyno Rots, 2020. "Real-time weakness of the global economy: a first assessment of the coronavirus crisis," Working Papers 2015, Banco de España.
    24. Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
    25. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
    26. Konstantin Kuck & Karsten Schweikert, 2021. "Forecasting Baden‐Württemberg's GDP growth: MIDAS regressions versus dynamic mixed‐frequency factor models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 861-882, August.
    27. Ghirelli, Corinna & Pérez, Javier J. & Urtasun, Alberto, 2019. "A new economic policy uncertainty index for Spain," Economics Letters, Elsevier, vol. 182(C), pages 64-67.
    28. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," University of California at Los Angeles, Anderson Graduate School of Management qt9mf223rs, Anderson Graduate School of Management, UCLA.
    29. Hannes Mueller & Christopher Rauh, 2022. "The Hard Problem of Prediction for Conflict Prevention," Journal of the European Economic Association, European Economic Association, vol. 20(6), pages 2440-2467.
    30. Ángel Estrada & Luis Guirola & Iván Kataryniuk & Jaime Martínez-Martín, 2020. "The use of BVARs in the analysis of emerging economies," Occasional Papers 2001, Banco de España.
    31. Timothy Besley & Hannes Mueller, 2018. "Institutions, Volatility, and Investment," Journal of the European Economic Association, European Economic Association, vol. 16(3), pages 604-649.
    32. G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.
    33. Tahsin Saadi Sedik & Rui Xu, 2020. "A Vicious Cycle: How Pandemics Lead to Economic Despair and Social Unrest," IMF Working Papers 2020/216, International Monetary Fund.
    34. Le Ha Thu & Roberto Leon-Gonzalez, 2021. "Forecasting Macroeconomic Variables in Emerging Economies: An Application to Vietnam," GRIPS Discussion Papers 21-03, National Graduate Institute for Policy Studies.
    35. Simon Johnson & John McMillan & Christopher Woodruff, 2002. "Property Rights and Finance," American Economic Review, American Economic Association, vol. 92(5), pages 1335-1356, December.
    36. Philip Barrett & Mariia Bondar & Sophia Chen & Mali Chivakul & Deniz Igan, 2024. "Pricing protest: the response of financial markets to social unrest," Review of Finance, European Finance Association, vol. 28(4), pages 1419-1450.
    37. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    38. Gauvin, L. & McLoughlin, C. & Reinhardt, D., 2013. "Policy Uncertainty Spillovers to Emerging Markets - Evidence from Capital Flows," Working papers 435, Banque de France.
    39. Michael Zhemkov, 2021. "Nowcasting Russian GDP using forecast combination approach," International Economics, CEPII research center, issue 168, pages 10-24.
    40. Willard, Kristen L & Guinnane, Timothy W & Rosen, Harvey S, 1996. "Turning Points in the Civil War: Views from the Greenback Market," American Economic Review, American Economic Association, vol. 86(4), pages 1001-1018, September.
    41. Carrière-Swallow, Yan & Céspedes, Luis Felipe, 2013. "The impact of uncertainty shocks in emerging economies," Journal of International Economics, Elsevier, vol. 90(2), pages 316-325.
    42. Robert J. Barro, 2009. "Rare Disasters, Asset Prices, and Welfare Costs," American Economic Review, American Economic Association, vol. 99(1), pages 243-264, March.
    43. Ghysels, Eric & Kvedaras, Virmantas & Zemlys, Vaidotas, 2016. "Mixed Frequency Data Sampling Regression Models: The R Package midasr," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 72(i04).
    44. Kuzin, Vladimir N. & Marcellino, Massimiliano & Schumacher, Christian, 2009. "MIDAS versus mixed-frequency VAR: nowcasting GDP in the euro area," Discussion Paper Series 1: Economic Studies 2009,07, Deutsche Bundesbank.
    45. Claudia Foroni & Massimiliano Marcellino & Christian Schumacher, 2015. "Unrestricted mixed data sampling (MIDAS): MIDAS regressions with unrestricted lag polynomials," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(1), pages 57-82, January.
    46. JÖrg Breitung & Christoph Roling, 2015. "Forecasting Inflation Rates Using Daily Data: A Nonparametric MIDAS Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(7), pages 588-603, November.
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    More about this item

    Keywords

    forecasting; social unrest; social conflict; policy uncertainty; forecasting GDP; natural language processing; geopolitical risk;
    All these keywords.

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • D74 - Microeconomics - - Analysis of Collective Decision-Making - - - Conflict; Conflict Resolution; Alliances; Revolutions
    • N16 - Economic History - - Macroeconomics and Monetary Economics; Industrial Structure; Growth; Fluctuations - - - Latin America; Caribbean

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