146 0

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

Title
Inference of the Trend in a Partially Linear Model with Locally Stationary Regressors
Author
김건호
Keywords
Invariane principle; Local-stationarity; Nonparametric trend; Partially linear model; Phillips curve; Semiparametric regression; Time-varying NAIRU; Uniform confidence band
Issue Date
2016-04
Publisher
TAYLOR & FRANCIS INC
Citation
ECONOMETRIC REVIEWS, v. 35, NO 7, Page. 1194-1220
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.
URI
https://www.tandfonline.com/doi/full/10.1080/07474938.2014.976530http://hdl.handle.net/20.500.11754/52498
ISSN
0747-4938; 1532-4168
DOI
10.1080/07474938.2014.976530
Appears in Collections:
COLLEGE OF ECONOMICS AND FINANCE[S](경제금융대학) > ECONOMICS & FINANCE(경제금융학부) > Articles
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE