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The economic impact of conflict-related and policy uncertainty shocks: The case of Russia

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  • Diakonova, Marina
  • Ghirelli, Corinna
  • Molina, Luis
  • Pérez, Javier J.

Abstract

We show that policy uncertainty and conflict-related shocks impact the dynamics of economic activity (GDP) in Russia. We use alternative indicators of “conflict”, referring to specific aspects of this general concept: geopolitical risk, social unrest, outbreaks of political violence, and escalations into internal armed conflict. For policy uncertainty we employ the workhorse economic policy uncertainty (EPU) indicator. We use two distinct but complementary empirical approaches. The first is based on a time series mixed-frequency forecasting model: we show that the indicators provide useful information for forecasting GDP in the short run, even when controlling for a comprehensive set of standard high-frequency macro-financial variables. The second approach is a SVAR model. We show that negative shocks to the selected indicators yield economic slowdown, with a persistent drop in GDP growth and a short-lived but large increase in country risk.

Suggested Citation

  • Diakonova, Marina & Ghirelli, Corinna & Molina, Luis & Pérez, Javier J., 2023. "The economic impact of conflict-related and policy uncertainty shocks: The case of Russia," International Economics, Elsevier, vol. 174(C), pages 69-90.
  • Handle: RePEc:eee:inteco:v:174:y:2023:i:c:p:69-90
    DOI: 10.1016/j.inteco.2023.03.002
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    1. Dario Caldara & Matteo Iacoviello, 2022. "Measuring Geopolitical Risk," American Economic Review, American Economic Association, vol. 112(4), pages 1194-1225, April.
    2. 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.
    3. 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.
    4. Simon Johnson & John McMillan & Christopher Woodruff, 2002. "Property Rights and Finance," American Economic Review, American Economic Association, vol. 92(5), pages 1335-1356, December.
    5. 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.
    6. 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.
    7. 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.
    8. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    9. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    10. 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).
    11. Charemza, Wojciech & Makarova, Svetlana & Rybiński, Krzysztof, 2022. "Economic uncertainty and natural language processing; The case of Russia," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 546-562.
    12. Michael Zhemkov, 2021. "Nowcasting Russian GDP using forecast combination approach," International Economics, CEPII research center, issue 168, pages 10-24.
    13. 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.
    14. repec:hal:spmain:info:hdl:2441/4mupcmg7bt8iv8k3lhvbqr8p51 is not listed on IDEAS
    15. 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.
    16. Sergei Guriev & Nikita Melnikov, 2016. "War, Inflation, and Social Capital," American Economic Review, American Economic Association, vol. 106(5), pages 230-235, May.
    17. 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.
    18. Boeckelmann Lukas & Stalla-Bourdillon Arthur, 2021. "Structural Estimation of Time-Varying Spillovers: An Application to International Credit Risk Transmission," Working papers 798, Banque de France.
    19. Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2017. "Explaining the time-varying effects of oil market shocks on US stock returns," Economics Letters, Elsevier, vol. 155(C), pages 84-88.
    20. Sergei Guriev & Nikita Melnikov, 2016. "War, Inflation, and Social Capital," American Economic Review, American Economic Association, vol. 106(5), pages 230-235, May.
    21. 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.
    22. 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.
    23. Luis J. Álvarez & Florens Odendahl, 2022. "Data outliers and Bayesian VARs in the Euro Area," Working Papers 2239, Banco de España.
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    More about this item

    Keywords

    Russia; Forecasting; Social unrest; Social conflict; Policy uncertainty; 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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