Inference of the Trend in a Partially Linear Model with Locally Stationary Regressors

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Abstract

In this article, we construct the uniform confidence band (UCB) of nonparametric trend in a partially linear model with locally stationary regressors. A two-stage semiparametric regression is employed to estimate the trend function. Based on this estimate, we develop an invariance principle to construct the UCB of the trend function. The proposed methodology is used to estimate the Non-Accelerating Inflation Rate of Unemployment (NAIRU) in the Phillips Curve and to perform inference of the parameter based on its UCB. The empirical results strongly suggest that the U.S. NAIRU is time-varying.

Original languageEnglish
Pages (from-to)1194-1220
Number of pages27
JournalEconometric Reviews
Volume35
Issue number7
DOIs
StatePublished - 2016 Aug 8

Keywords

  • Invariane principle
  • Local-stationarity
  • Nonparametric trend
  • Partially linear model
  • Phillips curve
  • Semiparametric regression
  • Time-varying NAIRU
  • Uniform confidence band

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