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Inflation as a global phenomenon - some implications for policy analysis and forecasting

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Abstract
We evaluate the performance of inflation forecasts based on the open-economy Phillips curve by exploiting the spatial pattern of international propagation of inflation. We model these spatial linkages using global inflation and either domestic slack or oil price fluctuations, motivated by a novel interpretation of the forecasting implications of the workhorse openeconomy New Keynesian model (Martnez-Garca and Wynne (2010), Kabukcuoglu and Martnez-Garca (2014)). We find that incorporating spatial interactions yields significantly more accurate forecasts of local inflation in 14 advanced countries (including the U.S.) than a simple autoregressive model that captures only the temporal dimension of the inflation dynamics.

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  • Ayse Kabukcuoglu & Enrique Martínez García, 2016. "Inflation as a global phenomenon - some implications for policy analysis and forecasting," Globalization Institute Working Papers 261, Federal Reserve Bank of Dallas.
    • Handle: RePEc:fip:feddgw:261
    DOI: 10.24149/gwp261
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    Cited by:

    1. Olalude, Gbenga Adelekan & Olayinka, Hammed Abiola & Ankeli, Uchechi Constance, 2020. "Modelling and forecasting inflation rate in Nigeria using ARIMA models," MPRA Paper 105342, University Library of Munich, Germany, revised Dec 2020.
    2. Olatunji A. Shobande & Oladimeji T. Shodipe & Simplice A. Asongu, 2019. "Global Shocks Alert and Monetary Policy Responses," Working Papers of the African Governance and Development Institute. 19/066, African Governance and Development Institute..
    3. Clara De Luigi & Florian Huber & Josef Schreiner, 2019. "The impact of labor cost growth on inflation in selected CESEE countries," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q4/19, pages 56-78.
    4. Dario Caldara & Etienne Gagnon & Enrique Martínez García & Christopher J. Neely, 2021. "Monetary Policy and Economic Performance Since the Financial Crisis," Review, Federal Reserve Bank of St. Louis, vol. 103(4), pages 425-460, October.
    5. Valery V. Bezpalov & Sergey A. Lochan & Dmitry V. Fedyunin & Irina V. Polozhentseva & Tatiana V. Gorina, 2022. "Relationship between Complex Integration Indices and Inflation Indicators and Their Impact on the Development of Regional Cooperation between Countries to Reduce the Level of Inflationary Risks: Case ," Risks, MDPI, vol. 11(1), pages 1-26, December.
    6. Nyoni, Thabani & Nathaniel, Solomon Prince, 2018. "Modeling rates of inflation in Nigeria: an application of ARMA, ARIMA and GARCH models," MPRA Paper 91351, University Library of Munich, Germany.
    7. Kose, M. Ayhan & Ha, Jongrim & Ohnsorge, Franziska, 2019. "Global Inflation Synchronization," CEPR Discussion Papers 13600, C.E.P.R. Discussion Papers.
    8. 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.
    9. Döpke, Jörg & Fritsche, Ulrich & Müller, Karsten, 2019. "Has macroeconomic forecasting changed after the Great Recession? Panel-based evidence on forecast accuracy and forecaster behavior from Germany," Journal of Macroeconomics, Elsevier, vol. 62(C).
    10. Kamber, Güneş & Wong, Benjamin, 2020. "Global factors and trend inflation," Journal of International Economics, Elsevier, vol. 122(C).
    11. Dario Caldara & Etienne Gagnon & Enrique Martinez-Garcia & Christopher J. Neely, 2020. "Monetary Policy and Economic Performance since the Financial Crisis," Working Papers 2020-026, Federal Reserve Bank of St. Louis, revised 02 Nov 2020.
    12. Ergemen, Yunus Emre, 2022. "Forecasting inflation rates with multi-level international dependence," Economics Letters, Elsevier, vol. 214(C).
    13. Dennis Bonam & Gabriele Galati & Irma Hindrayanto & Marco Hoeberichts & Anna Samarina & Irina Stanga, 2019. "Inflation in the euro area since the Global Financial Crisis," DNB Occasional Studies 1703, Netherlands Central Bank, Research Department.
    14. 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.

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    More about this item

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics
    • F62 - International Economics - - Economic Impacts of Globalization - - - Macroeconomic Impacts

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