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What Helps Forecast U.S. Inflation?—Mind the Gap!

Author

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  • Ayse Kabukcuoglu

    (Koc University)

  • Enrique Martínez-García

    (Federal Reserve Bank of Dallas and SMU)

Abstract

The Phillips curve, which posits a relationship between inflation and domestic economic activity, introduces a crucial trade-off between real and nominal objectives for the central bank. Atkeson and Ohanian (2001), among others, present evidence that forecasts of U.S. inflation from Phillips curve-based models tend to underperform relative to naïve forecasts. We propose that globalization can be an important factor in explaining the poor performance of forecasts under a closed-economy Phillips curve. To illustrate that, we empirically evaluate the performance of open-economy Phillips curve-based forecasts constructed with global variables, such as G7 credit growth, G7 money supply growth, terms of trade, and the real effective exchange rate. These global variables perform significantly better than domestic variables, and serve as proxies for poorly-measured indicators of global slack. Moreover, we show that forecasts using simulated data from a workhorse open-economy New Keynesian model support our empirical findings on the open economy Phillips curve and also suggest that better monetary policy and aspects of the Great Moderation have improved the forecast accuracy of open-economy models.

Suggested Citation

  • Ayse Kabukcuoglu & Enrique Martínez-García, 2016. "What Helps Forecast U.S. Inflation?—Mind the Gap!," Koç University-TUSIAD Economic Research Forum Working Papers 1615, Koc University-TUSIAD Economic Research Forum.
  • Handle: RePEc:koc:wpaper:1615
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    Cited by:

    1. 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.
    2. Enrique Martínez-García, 2019. "Good Policies or Good Luck? New Insights on Globalization and the International Monetary Policy Transmission Mechanism," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 419-454, June.
    3. Kabukçuoğlu, Ayşe & Martínez-García, Enrique, 2018. "Inflation as a global phenomenon—Some implications for inflation modeling and forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 87(C), pages 46-73.
    4. Kamber, Güneş & Wong, Benjamin, 2020. "Global factors and trend inflation," Journal of International Economics, Elsevier, vol. 122(C).
    5. Roberto Duncan & Enrique Martínez García, 2015. "Forecasting local inflation in Open Economies: What Can a NOEM Model Do?," Globalization Institute Working Papers 235, Federal Reserve Bank of Dallas, revised 21 Dec 2022.

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    More about this item

    Keywords

    Global Slack; New Open-Economy Phillips Curve; Open-Economy New Keynesian Model; Forecasting.;
    All these keywords.

    JEL classification:

    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics
    • F44 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - International Business Cycles
    • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • F62 - International Economics - - Economic Impacts of Globalization - - - Macroeconomic Impacts

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