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Test of Hypotheses in a Time Trend Panel Data Model with Serially Correlated Error Component Disturbances

Badi Baltagi (), Chihwa Kao () and Long Liu ()
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Long Liu: UTSA

Working Papers from College of Business, University of Texas at San Antonio

Abstract: This paper studies test of hypotheses for the slope parameter in a linear time trend panel data model with serially correlated error component disturbances. We propose a test statistic that uses a bias corrected estimator of the serial correlation parameter. The proposed test statistic which is based on the corresponding ?xed e¤ects feasible generalized least squares (FE-FGLS) estimator of the slope parameter has the standard normal limiting distribution which is valid whether the remainder error is I(0) or I(1). This performs well in Monte Carlo experiments and is recommended. Length: 41 pages

Keywords: Panel Data; Generalized Least Squares; Time Trend Model; Fixed Effects; First Difference; Nonstationarity. (search for similar items in EconPapers)
JEL-codes: C23 C33 (search for similar items in EconPapers)
Date: 2015
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http://interim.business.utsa.edu/wps/eco/0010ECO-661-2015.pdf Full text (application/pdf)

Related works:
Chapter: Test of Hypotheses in a Time Trend Panel Data Model with Serially Correlated Error Component Disturbances (2014) Downloads
Working Paper: Test of Hypotheses in a Time Trend Panel Data Model with Serially Correlated Error Component Disturbances (2014) Downloads
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