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Using the hybrid Phillips curve with memory to forecast US inflation

Author

Listed:
  • Chu Shiou-Yen

    (Department of Economics, National Chung Cheng University, 168, University Rd., Min-Hsiung, Chia-Yi 62102, Taiwan, Phone: +886-5-2720411 ext. 34168, Fax: 886-5-2720816)

  • Shane Christopher

    (Institute of Economics, National Sun Yat-sen University, Kaohsiung 80424, Taiwan)

Abstract

This paper adopts the Caputo fractional derivative to re-specify the hybrid Phillips curve as a dynamic process of inflation with memory. The Caputo fractional derivative contains a non-integer differencing order, providing the same insight for persistence as emphasized in the Autoregressive Fractionally Integrated Moving Average (ARFIMA) time series models. We utilize the hybrid Phillips curve with memory to forecast US inflation during 1967–2014. The results indicate that our model performs well against a traditional hybrid Phillips curve, an integrated moving average model and a naive random walk model in quasi-in-sample forecasts. In out-of-sample forecasts based on Consumer Price Index (CPI) and Personal Consumption Expenditure (PCE) data, we find that the forecasting performance of Phillips curve models depends on the sample period. Our model with CPI data can outperform others in out-of-sample forecasts during and after the most recent financial crisis (2006–2014).

Suggested Citation

  • Chu Shiou-Yen & Shane Christopher, 2017. "Using the hybrid Phillips curve with memory to forecast US inflation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(4), pages 1-16, September.
    • Handle: RePEc:bpj:sndecm:v:21:y:2017:i:4:p:16:n:5
    DOI: 10.1515/snde-2016-0088
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    More about this item

    Keywords

    autoregressive fractionally integrated moving average; inflation persistence; out-of-sample forecasting; quasi in-sample forecasting;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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