Testing for Structural Change of a Time Trend Regression in Panel Data

Center for Policy Research, Maxwell School, Syracuse University
SSRN Electronic Journal 04/2000; 2. DOI: 10.2139/ssrn.1808001
Source: RePEc


In this paper we propose two classes of test statistics for detecting a break at an unknown date in panel data models with time trend. The first one is the fluctuation test of Ploberger-Kramer-Kontrus (1989). The second one is based on the mean and exponential Wald statistics of Andrew and Ploberger (1994) and maximum Wald statistic of Andrew (1993). We derive the limiting distributions of the proposed test and tabulate the critical values. Asymptotic results were derived I(0), I(1) and nearly I(1) error terms. We also show that these tests have non-trivial local power only when the error terms are I(0).

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Available from: Chihwa Kao
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    • "Like in time series, this test statistic captures the distance between the estimators of parameters of two di¤erent regimes. Following the similar steps as in Theorem 2 in Emerson and Kao (2001), we could derive the limiting distribution of W (k) in (4) under the null of no change point and the results will be reported in a di¤erent paper. "
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    ABSTRACT: This paper studies a panel data regression setting, where a break occurs at a unknown common date. In this paper, we establish the consistency and rate of convergence of the change point estimator. The break date can be estimated consistently both in …xed time horizon and large panels, which indicates that the structural change can be well detected even in short panels. Furthermore, the limiting distribution is derived without the assumption of shrinking magnitude of break. These two features are dierent from the time series change point literature. Monte Carlo simulations are presented to investigate the …nite sample properties of the panel change point estimator.
    Preview · Article · Jan 2008
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    • "A recent annals volume of the Journal of Econometrics published in 2005 entitled \Modelling structural breaks, long memory and stock market volatility" (edited by Anindya Banerjee and Giovanni Urga, 2005) and Perron (2006) ooer the most recent comprehensive reviews on the topic. In contrast, scarce is the literature on the issues (estimation and testing) of structural changes in panel models, e.g., Han and Park (1989), Joseph and Wolfson (1992, 1993), Joseph et al. (1997), Hansen (1999), Chiang et al. (2002), Emerson and Kao (2001, 2002), Wachter and Tzavalis (2004) and Bai (2006). The estimation and testing for structure change in panels have many applications in economics, For example, scal/monetary policies may aaect every unit in the economy ((rms/regions), stock market crashes in the US may also cause the chain reaction in other stock markets in the world. "
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    ABSTRACT: In this paper, we propose an estimation and testing framework for parameter instability in cointegrated panel regressions with common and idiosyncratic trends. We develop tests for structural change for the slope parameters under the null hypothesis of no structural break against the alternative hypothesis of (at least) one common change point, which is possibly unknown. The limiting distributions of the proposed test statistics are derived. Monte Carlo simulations examine size and power of the proposed tests. We are grateful for discussions with Robert De Jong, Long-Fei Lee, Zongwu Cai, and Yupin Hu. We would also like to thank participants in the International Conferences on "Common Features in London" (Cass, 16-17 December 2004), 2006 New York Econometrics Camp and Breaks and Persistence in Econometrics (Cass, 11-12 December 2006), and econometrics seminars at Ohio State University and Academia Sinica for helpful comments. Part of this work was done while Chihwa Kao was visiting the Centre for Econometric Analysis at Cass (CEA@Cass). Financial support from City University 2005 Pump Priming Fund and CEA@Cass is gratefully acknowledged. Lorenzo Trapani acknowledges financial support from Cass Business School under the RAE Development Fund Scheme.
    Full-text · Article · Apr 2007 · SSRN Electronic Journal
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    • "The second direction follows steps already taken by the cointegration literature in the early '90's, tackling the issues of testing (i) cointegration allowing for breaks and (ii) the stability of a cointegrating relationship. In this stream of the literature, the first problem seems to have received more attention (e.g., Banerjee and Carrion-i-Silvestre, 2004 and 2006, Gutierrez, 2005, Westerlund , 2006) than the second (to the best of our knowledge, only Emerson and Kao, 2001, 2005, for trend regressions, Kao and Chiang, 2000, for homogenous panel regressions). This is somehow surprising, as stability tests with unknown break points may have very low power with even medium sample sizes. "
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    ABSTRACT: Stability tests for cointegrating coefficients are known to have very low power with small to medium sample sizes. In this paper we propose to solve this problem by extending the tests to dependent cointegrated panels through the stationary bootstrap. Simulation evidence shows that the proposed panel tests improve considerably on asymptotic tests applied to individual series. As an empirical illustration we examined investment and saving for a panel of European countries over the 1960-2002 period. While the individual stability tests, contrary to expectations and graphical evidence, in almost all cases do not reject the null of stability, the bootstrap panel tests lead to the more plausible conclusion that the long-run relationship between these two variables is likely to have undergone a break. --
    Full-text · Article · Jan 2007 · SSRN Electronic Journal
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