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The Role of Economic Policy Uncertainty in Predicting Output Growth in Emerging Markets: A Mixed-Frequency Granger Causality Approach

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Listed:
  • Mehmet Balcilar

    (Eastern Mediterranean University, Famagusta, North Cyprus, via Mersin 10, Turkey and University of Pretoria, Pretoria, 0002, South Africa)

  • George Ike

    (Eastern Mediterranean University, Famagusta, North Cyprus, via Mersin 10, Turkey)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa)

Abstract

We employ time series data to empirically determine the causal relationship between economic policy uncertainty and the GDP growth rates of seven emerging market economies while controlling for the effect of oil price, interest rates and the CPI. Due to differences in sampling frequencies between the GDP series and other variables, a multi-horizon mixed frequency VAR model is employed. This model fully exploits the mixed frequency Granger causality test in order to circumvent the distorting effects of temporal aggregation. The empirical results show a strong statistical evidence for direct causality flowing from economic policy uncertainty (EPU) to GDP in Chile, India and Mexico while a weaker statistical evidence is found for Brazil, Colombia and Russia. For comparative analysis, the low frequency Granger causality test is also employed and strong statistical evidence of direct causality flowing from EPU to GDP in Brazil, Chile, India, Mexico and Russia is uncovered. Analyzing the causal patterns uncovered in both specifications show that the low frequency Granger causality results are less intuitively appealing than those that are obtained from the mixed frequency Granger causality test. The results have empirical as well as policy implications which are discussed.

Suggested Citation

  • Mehmet Balcilar & George Ike & Rangan Gupta, 2019. "The Role of Economic Policy Uncertainty in Predicting Output Growth in Emerging Markets: A Mixed-Frequency Granger Causality Approach," Working Papers 201975, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:201975
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    1. Mehmet Balcilar & Rangan Gupta & Clement Kyei & Mark E. Wohar, 2016. "Does Economic Policy Uncertainty Predict Exchange Rate Returns and Volatility? Evidence from a Nonparametric Causality-in-Quantiles Test," Open Economies Review, Springer, vol. 27(2), pages 229-250, April.
    2. Yang, Miao & Jiang, Zhi-Qiang, 2016. "The dynamic correlation between policy uncertainty and stock market returns in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 92-100.
    3. Dufour, Jean-Marie & Pelletier, Denis & Renault, Eric, 2006. "Short run and long run causality in time series: inference," Journal of Econometrics, Elsevier, vol. 132(2), pages 337-362, June.
    4. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    5. Saygin Sahinoz & Evren Erdogan Cosar, 2020. "Quantifying uncertainty and identifying its impacts on the Turkish economy," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(2), pages 365-387, May.
    6. Wang, Yizhong & Chen, Carl R. & Huang, Ying Sophie, 2014. "Economic policy uncertainty and corporate investment: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 26(C), pages 227-243.
    7. Ghysels, Eric & Hill, Jonathan B. & Motegi, Kaiji, 2016. "Testing for Granger causality with mixed frequency data," Journal of Econometrics, Elsevier, vol. 192(1), pages 207-230.
    8. Colombo, Valentina, 2013. "Economic policy uncertainty in the US: Does it matter for the Euro area?," Economics Letters, Elsevier, vol. 121(1), pages 39-42.
    9. Goncalves, Silvia & Kilian, Lutz, 2004. "Bootstrapping autoregressions with conditional heteroskedasticity of unknown form," Journal of Econometrics, Elsevier, vol. 123(1), pages 89-120, November.
    10. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    11. 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.
    12. Balcilar, Mehmet & Gupta, Rangan & Segnon, Mawuli, 2016. "The role of economic policy uncertainty in predicting U.S. recessions: A mixed-frequency Markov-switching vector autoregressive approach," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 10, pages 1-20.
    13. Tsung-Pao Wu & Shu-Bing Liu & Shun-Jen Hsueh, 2016. "The Causal Relationship between Economic Policy Uncertainty and Stock Market: A Panel Data Analysis," International Economic Journal, Taylor & Francis Journals, vol. 30(1), pages 109-122, March.
    14. Beckmann, Joscha & Czudaj, Robert, 2017. "Exchange rate expectations and economic policy uncertainty," European Journal of Political Economy, Elsevier, vol. 47(C), pages 148-162.
    15. Jian Chen & Fuwei Jiang & Guoshi Tong, 2017. "Economic policy uncertainty in China and stock market expected returns," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 57(5), pages 1265-1286, December.
    16. Rodrigo Cerda & Álvaro Silva & José Tomás Valente, 2018. "Impact of economic uncertainty in a small open economy: the case of Chile," Applied Economics, Taylor & Francis Journals, vol. 50(26), pages 2894-2908, June.
    17. Whitney K. Newey & Kenneth D. West, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(4), pages 631-653.
    18. Kang, Wensheng & Lee, Kiseok & Ratti, Ronald A., 2014. "Economic policy uncertainty and firm-level investment," Journal of Macroeconomics, Elsevier, vol. 39(PA), pages 42-53.
    19. Yu, Honghai & Fang, Libing & Sun, Wencong, 2018. "Forecasting performance of global economic policy uncertainty for volatility of Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 931-940.
    20. Goodness C. Aye & Rangan Gupta & Chi Keung Marco Lau & Xin Sheng, 2019. "Is there a role for uncertainty in forecasting output growth in OECD countries? Evidence from a time-varying parameter-panel vector autoregressive model," Applied Economics, Taylor & Francis Journals, vol. 51(33), pages 3624-3631, July.
    21. Chris Redl, 2018. "Macroeconomic Uncertainty in South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 86(3), pages 361-380, September.
    22. Pär Stockhammar & Pär Österholm, 2016. "Effects of US policy uncertainty on Swedish GDP growth," Empirical Economics, Springer, vol. 50(2), pages 443-462, March.
    23. Arouri, Mohamed & Estay, Christophe & Rault, Christophe & Roubaud, David, 2016. "Economic policy uncertainty and stock markets: Long-run evidence from the US," Finance Research Letters, Elsevier, vol. 18(C), pages 136-141.
    24. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    25. Clive, W.J. & Lin, Jin-Lung, 1995. "Causality in the Long Run," Econometric Theory, Cambridge University Press, vol. 11(3), pages 530-536, June.
    26. Aizenman, Joshua & Marion, Nancy P, 1993. "Policy Uncertainty, Persistence and Growth," Review of International Economics, Wiley Blackwell, vol. 1(2), pages 145-163, June.
    27. Khandokar Istiak & Apostolos Serletis, 2018. "Economic policy uncertainty and real output: evidence from the G7 countries," Applied Economics, Taylor & Francis Journals, vol. 50(39), pages 4222-4233, August.
    28. Nikolaos Antonakakis & Ioannis Chatziantoniou & George Filis, 2014. "Dynamic Spillovers of Oil Price Shocks and Policy Uncertainty," Department of Economics Working Papers wuwp166, Vienna University of Economics and Business, Department of Economics.
    29. Hernando Vargas, 2008. "The transmission mechanism of monetary policy in Colombia: major changes and current features," BIS Papers chapters, in: Bank for International Settlements (ed.), Transmission mechanisms for monetary policy in emerging market economies, volume 35, pages 183-211, Bank for International Settlements.
    30. Jae Sim & Egon Zakrajsek & Simon Gilchrist, 2010. "Uncertainty, Financial Frictions, and Investment Dynamics," 2010 Meeting Papers 1285, Society for Economic Dynamics.
    31. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Filis, George, 2014. "Dynamic spillovers of oil price shocks and economic policy uncertainty," Energy Economics, Elsevier, vol. 44(C), pages 433-447.
    32. Caggiano, Giovanni & Castelnuovo, Efrem & Figueres, Juan Manuel, 2017. "Economic policy uncertainty and unemployment in the United States: A nonlinear approach," Economics Letters, Elsevier, vol. 151(C), pages 31-34.
    33. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    34. Lorraine Lim, 2018. "Between Control and Disruption: News Media and Cultural Flows in Singapore and Hong Kong, China," Creative Economy, in: Nobuko Kawashima & Hye-Kyung Lee (ed.), Asian Cultural Flows, chapter 0, pages 59-73, Springer.
    35. Robert Krol, 2014. "Economic Policy Uncertainty and Exchange Rate Volatility," International Finance, Wiley Blackwell, vol. 17(2), pages 241-256, June.
    36. Li, Xiao-Ming & Peng, Lu, 2017. "US economic policy uncertainty and co-movements between Chinese and US stock markets," Economic Modelling, Elsevier, vol. 61(C), pages 27-39.
    37. Xiao-lin Li & Mehmet Balcilar & Rangan Gupta & Tsangyao Chang, 2016. "The Causal Relationship Between Economic Policy Uncertainty and Stock Returns in China and India: Evidence from a Bootstrap Rolling Window Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 52(3), pages 674-689, March.
    38. Granger, C. W. J., 1988. "Some recent development in a concept of causality," Journal of Econometrics, Elsevier, vol. 39(1-2), pages 199-211.
    39. Arouri, Mohamed & Estay, Christophe & Rault, Christophe & Roubaud, David, 2016. "Economic policy uncertainty and stock markets: Long-run evidence from the US," Finance Research Letters, Elsevier, vol. 18(C), pages 136-141.
    40. Afonso, José Roberto & Araújo, Eliane Cristina & Fajardo, Bernardo Guelber, 2016. "The role of fiscal and monetary policies in the Brazilian economy: Understanding recent institutional reforms and economic changes," The Quarterly Review of Economics and Finance, Elsevier, vol. 62(C), pages 41-55.
    41. Liyan Han & Mengchao Qi & Libo Yin, 2016. "Macroeconomic policy uncertainty shocks on the Chinese economy: a GVAR analysis," Applied Economics, Taylor & Francis Journals, vol. 48(51), pages 4907-4921, November.
    42. Karnizova, Lilia & Li, Jiaxiong (Chris), 2014. "Economic policy uncertainty, financial markets and probability of US recessions," Economics Letters, Elsevier, vol. 125(2), pages 261-265.
    43. Jean-Marie Dufour & David Tessier, 2006. "Short-Run and Long-Run Causality between Monetary Policy Variables and Stock Prices," Staff Working Papers 06-39, Bank of Canada.
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    Cited by:

    1. Eugene Msizi Buthelezi, 2023. "Dynamics of Macroeconomic Uncertainty on Economic Growth in the Presence of Fiscal Consolidation in South Africa from 1994 to 2022," Economies, MDPI, vol. 11(4), pages 1-24, April.
    2. Rasool Dehghanzadeh Shahabad & Mehmet Balcilar, 2022. "Modelling the Dynamic Interaction between Economic Policy Uncertainty and Commodity Prices in India: The Dynamic Autoregressive Distributed Lag Approach," Mathematics, MDPI, vol. 10(10), pages 1-21, May.
    3. Hong, Yanran & Xu, Pengfei & Wang, Lu & Pan, Zhigang, 2022. "Relationship between the news-based categorical economic policy uncertainty and US GDP: A mixed-frequency Granger-causality analysis," Finance Research Letters, Elsevier, vol. 48(C).

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    More about this item

    Keywords

    Economic policy uncertainty; mixed frequency; Granger causality; temporal aggregation; emerging market economies.;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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