Journal
JOURNAL OF ECONOMETRICS
Volume 202, Issue 2, Pages 286-305Publisher
ELSEVIER SCIENCE SA
DOI: 10.1016/j.jeconom.2017.06.023
Keywords
Panel data models; Fixed effect; Locally stationary; Local linear estimation; Hypothesis testing
Categories
Funding
- Shanghai University of Finance and Economics Innovation Fund for Graduate Student [CXJJ-2015-436]
- State Key Program in the Major Research Plan of NSFC [91546202]
- NSFC [11771268]
- Program for Innovative Research Team of SHUFE
- National Natural Science Foundation of China (NSFC) [11471203]
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We develop methods for inference in nonparametric time-varying fixed effects panel data models that allow for locally stationary regressors and for the time series length T and cross-section size N both being large. We first develop a pooled nonparametric profile least squares dummy variable approach to estimate the nonparametric function, and establish the optimal convergence rate and asymptotic normality of the resultant estimator. We then propose a test statistic to check whether the bivariate nonparametric function is time-varying or the time effect is separable, and derive the asymptotic distribution of the proposed test statistic. We present severalsimulated examples and two real data analyses to illustrate the finite sample performance of the proposed methods. (C) 2017 Elsevier B.V. All rights reserved.
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