Testing for Common Trends in Semiparametric Panel Data Models with Fixed Effects
Liangjun Su and
Peter Phillips ()
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Yonghui Zhang: School of Economics, Singapore Management University
No 1832, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University
This paper proposes a nonparametric test for common trends in semiparametric panel data models with fixed effects based on a measure of nonparametric goodness-of-fit (R^2). We first estimate the model under the null hypothesis of common trends by the method of profile least squares, and obtain the augmented residual which consistently estimates the sum of the fixed effect and the disturbance under the null. Then we run a local linear regression of the augmented residuals on a time trend and calculate the nonparametric R^2 for each cross section unit. The proposed test statistic is obtained by averaging all cross sectional nonparametric R^2's, which is close to zero under the null and deviates from zero under the alternative. We show that after appropriate standardization the test statistic is asymptotically normally distributed under both the null hypothesis and a sequence of Pitman local alternatives. We prove test consistency and propose a bootstrap procedure to obtain p-values. Monte Carlo simulations indicate that the test performs well in finite samples. Empirical applications are conducted exploring the commonality of spatial trends in UK climate change data and idiosyncratic trends in OECD real GDP growth data. Both applications reveal the fragility of the widely adopted common trends assumption.
Keywords: Common trends; Local polynomial estimation; Nonparametric goodness-of-fit; Panel data; Profile least squares (search for similar items in EconPapers)
JEL-codes: C12 C14 C23 (search for similar items in EconPapers)
Pages: 24 pages
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-sea
Note: CFP 1368
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Published in Econometrics Journal (2012), 15: 56-100
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Journal Article: Testing for common trends in semi‐parametric panel data models with fixed effects (2012)
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