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Inference and Forecasting Based on the Phillips Curve

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  • Kim, Kun Ho
  • Park, Suna

Abstract

In this paper, we conduct uniform inference of two widely used versions of the Phillips curve, specifically the random-walk Phillips curve and the New-Keynesian Phillips curve (NKPC). For both specifications, we propose a potentially time-varying natural unemployment (NAIRU) to address the uncertainty surrounding the inflation-unemployment trade-off. The inference is conducted through the construction of what is known as the uniform confidence band (UCB). The proposed methodology is then applied to point-ahead inflation forecasting for the Korean economy. This paper finds that the forecasts can benefit from conducting UCB-based inference and that the inference results have important policy implications.

Suggested Citation

  • Kim, Kun Ho & Park, Suna, 2016. "Inference and Forecasting Based on the Phillips Curve," KDI Journal of Economic Policy, Korea Development Institute (KDI), vol. 38(2), pages 1-20.
    • Handle: RePEc:zbw:kdijep:v:38:y:2016:i:2:p:1-20
    DOI: 10.23895/kdijep.2016.38.2.1
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    References listed on IDEAS

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    3. Robert J. Gordon, 1997. "The Time-Varying NAIRU and Its Implications for Economic Policy," Journal of Economic Perspectives, American Economic Association, vol. 11(1), pages 11-32, Winter.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Timevarying NAIRU; Randomwalk Phillips curve; NewKeynesian Phillips curve; Uniform confidence band; Model validation; Inflation forecasting;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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