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Predicting US CPI-Inflation in the presence of asymmetries, persistence, endogeneity, and conditional heteroscedasticity

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  • Afees A. Salisu

    () (Centre for Econometric and Allied Research, University of Ibadan)

  • Kazeem Isah

    () (Centre for Econometric and Allied Research, University of Ibadan)

Abstract

In this paper, we construct a multi-predictor framework for US inflation by augmenting the traditional Phillips curve-based inflation model with symmetric and asymmetric oil price changes. We show that the underlying predictors of US inflation exhibit persistence, endogeneity and conditional heteroscedasticity effects which have implications on forecast performance. Thus, we employ the Westerlund and Narayan (WN hereafter) (2014) estimator which allows for these effects in the predictive model. Also, we follow the linear multi-predictor set-up by Makin et al. (2014) which is an extension of the bivariate predictive model of WN (2014). Thereafter, we extend the former in order to construct a nonlinear multi-predictor model that allows for asymmetries based on Shin et al. (2014) approach. Using historical quarterly data for relevant variables ranging from 1957 to 2017, we demonstrate that US inflation is better modelled with the proposed multi-predictor model suggesting the significance of oil price in the predictive model for US inflation. In addition, we find that the US inflation forecast is episodic and asymmetric. Among the competing multi-predictor variants, the positive oil price-based variant outperforms all other variants both for in-sample and out-of-sample forecasts. The proposed model also outperforms the autoregressive process for a longer out-of-sample period. Our results are robust to different measures of inflation, multiple in-sample periods and forecast horizon.

Suggested Citation

  • Afees A. Salisu & Kazeem Isah, 2017. "Predicting US CPI-Inflation in the presence of asymmetries, persistence, endogeneity, and conditional heteroscedasticity," Working Papers 026, Centre for Econometric and Allied Research, University of Ibadan.
  • Handle: RePEc:cui:wpaper:0026
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    1. repec:eee:eneeco:v:70:y:2018:i:c:p:334-356 is not listed on IDEAS
    2. Afees A. Salisu & Umar B. Ndako, 2017. "A new look at the stock price-exchange rate nexus," Working Papers 031, Centre for Econometric and Allied Research, University of Ibadan.
    3. Afees A. Salisu & Oluwatomisinn Oyewole & Ismail O. Fasanya, 2017. "Modelling Return and Volatility Spillovers in Global Foreign Exchange Markets," Working Papers 030, Centre for Econometric and Allied Research, University of Ibadan.
    4. Afees A. Salisu & Wasiu Adekunle & Zachariah Emmanuel & Wasiu A. Alimi, 2018. "Predicting exchange rate with commodity prices: The role of structural breaks and asymmetries," Working Papers 055, Centre for Econometric and Allied Research, University of Ibadan.
    5. Afees A. Salisu & Lateef O. Akanni & Ahamuefula Ephraim Ogbonna, 2018. "Forecasting CO2 emissions: Does the choice of estimator matter?," Working Papers 045, Centre for Econometric and Allied Research, University of Ibadan.
    6. Salisu, Afees A. & Ademuyiwa, Idris & Isah, Kazeem O., 2018. "Revisiting the forecasting accuracy of Phillips curve: The role of oil price," Energy Economics, Elsevier, vol. 70(C), pages 334-356.

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    Keywords

    OECD; Phillips curve; Asymmetries; Inflation forecasts; Forecast evaluation;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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