Dissertation/Thesis Abstract

Testing heterogeneity in panel data models with interactive fixed effects
by Chen, Qihui, M.Sc., Singapore Management University (Singapore), 2011, 73; 1501948
Abstract (Summary)

This paper proposes a test for the slope homogeneity in large dimensional panel data models with interactive fixed effects based on a measure of goodness-of-fit (R2). We first obtain, for each cross-sectional unit, the R2 from the time series regression of residuals on the constant and observable regressors and then construct the test statistic 2 as an equally weighted average of the cross- sectional R2's. 2 is close to 0 under the null hypothesis of homogenous slopes and deviates away from 0 otherwise. We show that after being appropriately centered and scaled, 2 is asymptotically normally distributed under the null and a sequence of Pitman local alternatives. To improve the finite sample performance of the test, we also propose a bootstrap procedure to obtain the bootstrap p-values and justify its validity. Monte Carlo simulations suggest that the test has correct size and satisfactory power, and is superior to a recent test proposed by Pesaran and Yamagata (2008) that neglects cross- sectional dependence in panel data models. We apply our tests to study the OECD economic growth model and the Fama-French three factor model for asset returns.

Indexing (document details)
Advisor: Su, Liangjun
Commitee: Jin, Sainan, Yang, Zhenlin
School: Singapore Management University (Singapore)
Department: School of Economics
School Location: Republic of Singapore
Source: MAI 50/03M, Masters Abstracts International
Subjects: Statistics, Economics
Keywords: Cross-sectional dependence, Goodness-of-fit, Heterogeneity, Interactive fixed effects, Large panels, Principal component analysis
Publication Number: 1501948
ISBN: 9781124996363
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