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New perspectives on forecasting inflation in emerging market economies: An empirical assessment

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  • Duncan, Roberto
  • Martínez-García, Enrique

Abstract

We use a broad-range set of inflation models and pseudo out-of-sample forecasts to assess their predictive ability among 14 emerging market economies (EMEs) at different horizons (1–12 quarters ahead) with quarterly data over the period 1980Q1-2016Q4. We find, in general, that a simple arithmetic average of the current and three previous observations (the RW-AO model) consistently outperforms its standard competitors—based on the root mean squared prediction error (RMSPE) and on the accuracy in predicting the direction of change. These include conventional models based on domestic factors, existing open-economy Phillips curve-based specifications, factor-augmented models, and time-varying parameter models. Often, the RMSPE and directional accuracy gains of the RW-AO model are shown to be statistically significant. Our results are robust to forecast combinations, intercept corrections, alternative transformations of the target variable, different lag structures, and additional tests of (conditional) predictability. We argue that the RW-AO model is successful among EMEs because it is a straightforward method to downweight later data, which is a useful strategy when there are unknown structural breaks and model misspecification.

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  • 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.
  • Handle: RePEc:eee:intfor:v:35:y:2019:i:3:p:1008-1031
    DOI: 10.1016/j.ijforecast.2019.04.004
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    Cited by:

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    2. Dongchul Cho & Wankeun Oh, 2023. "Predictive Abilities of Inflation Expectations and Implications on Monetary Policy in Korea," Korean Economic Review, Korean Economic Association, vol. 39, pages 257-276.
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    4. Roberto Duncan & Enrique Martínez‐García, 2023. "Forecasting inflation in open economies: What can a NOEM model do?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 481-513, April.
    5. Sen Gupta, Abhijit & Iyer, Tara, 2019. "Quarterly Forecasting Model for India’s Economic Growth: Bayesian Vector Autoregression Approach," ADB Economics Working Paper Series 573, Asian Development Bank.

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    More about this item

    Keywords

    Inflation forecasting; Random walk; Emerging market economies; Policy credibility; Robust forecasts;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics
    • F42 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - International Policy Coordination and Transmission
    • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications

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