 Improving Phillips Curve’s Inflation Forecasts under MisspecificationJournal for Economic Forecasting, 2017, issue 3, 54-76 Abstract: The Philips Curve (PC) is empirically criticized as falling short on many occasions in its predictability power of inflation due to an inherent deficiency in its specification features. This study is an attempt to improve the accuracy of Philips Curve forecasts. It considers various econometric specifications and estimation methods and different measures of the business cycle. In addition to the traditional New Keynesian open economy PC, we analyze some augmented versions with other information which incorporates the monetary variables such as the price gap. Additionally, we propose two different identifications for PC with time varying coefficients: the Time-Varying Coefficients with Random Walk (TVCR) coefficients and the Time Varying Coefficient (TVC). TVC allows us to confront directly specification biases and spurious relationships; this is usually the case for PC under the traditional estimation approaches. Moreover, we employ some static and dynamic forecast combination techniques. We find that PC with TVC provides the most accurate forecasts. Keywords: forecasting inflation; Phillips Curve; misspecification; time-varying coefficients; model averaging, business cycles (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:rjr:romjef:v::y:2017:i:3:p:54-76 Access Statistics for this article Journal for Economic Forecasting is currently edited by Lucian Liviu Albu and Corina Saman More articles in Journal for Economic Forecasting from Institute for Economic Forecasting Contact information at EDIRC. |
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