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On the role of dependence in sticky price and sticky information Phillips curve: Modelling and forecasting

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  • Casarin, Roberto
  • Costantini, Mauro
  • Paradiso, Antonio

Abstract

Understanding the role of sticky price and sticky information for inflation dynamics is a key issue in economics. The literature has treated the two forms of stickiness as independent. This paper proposes a new dual stickiness Phillips curve based on dependence among the events of setting prices and updating information. Using US data over the period 1947Q1–2020Q1, the new model is scrutinized against a dual stickiness model without dependence, a pure sticky price model, and a pure sticky information model, through in- and out-of-sample analyses. The results show: (i) the new model outperforms the model without dependence in-sample; (ii) the dual stickiness models perform similarly out-of-sample; and (iii) the pure sticky models yield the worst forecasts. The results have some implications for policy makers and practitioners. A policy maker may consider the new model given its performance in- and out-of-sample, while a practitioner may prefer the model without dependence, given its lesser complexity and its competitive forecasting performance.

Suggested Citation

  • Casarin, Roberto & Costantini, Mauro & Paradiso, Antonio, 2021. "On the role of dependence in sticky price and sticky information Phillips curve: Modelling and forecasting," Economic Modelling, Elsevier, vol. 105(C).
  • Handle: RePEc:eee:ecmode:v:105:y:2021:i:c:s0264999321002339
    DOI: 10.1016/j.econmod.2021.105644
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    More about this item

    Keywords

    Phillips curve; Dual stickiness; Dependence; Bayesian analysis; Forecasting;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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