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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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  • Mehmet Balcilar
  • George Ike
  • Rangan Gupta
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 specified. This model fully exploits the recently developed mixed frequency Granger causality test in order to circumvent the distorting effects of temporal aggregation. The empirical results show a strong statistical evidence for causality flowing from EPU to GDP in Brazil, Chile, and India in the mixed frequency case while weak statistical evidence is found for Colombia, Mexico, and Russia. For comparative analysis, the low-frequency Granger causality test is also employed and strong statistical evidence of causality flowing from EPU to GDP in Brazil, Chile, India, Mexico 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 specifications. The results have empirical as well as policy implications which are discussed.

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  • Mehmet Balcilar & George Ike & Rangan Gupta, 2022. "The Role of Economic Policy Uncertainty in Predicting Output Growth in Emerging Markets: A Mixed-Frequency Granger Causality Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 58(4), pages 1008-1026, March.
    • Handle: RePEc:mes:emfitr:v:58:y:2022:i:4:p:1008-1026
    DOI: 10.1080/1540496X.2020.1860747
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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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    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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