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

被引:4
作者
Kim, Kun Ho [1 ]
机构
[1] Hanyang Univ, Dept Econ & Finance, 222 Wangsimri Dong Ro, Seoul 133791, South Korea
关键词
Invariane principle; Local-stationarity; Nonparametric trend; Partially linear model; Phillips curve; Semiparametric regression; Time-varying NAIRU; Uniform confidence band; TIME-SERIES MODELS; CONFIDENCE BANDS; NAIRU; DEVIATIONS; VARIANCE;
D O I
10.1080/07474938.2014.976530
中图分类号
F [经济];
学科分类号
02 ;
摘要
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.
引用
收藏
页码:1194 / 1220
页数:27
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