A Simple Panel Unit-Root Test with Smooth Breaks in the Presence of a Multifactor Error Structure PDF Download
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Author: Chingnun Lee
Publisher:
ISBN:
Category :
Languages : en
Pages : 62
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Book Description
This paper proposes a new simple panel unit-root test by extending the cross-sectionally augmented panel unit-root test (CIPS) developed by Pesaran et al. (2013) to allow for smoothing structural changes in deterministic terms, approximated by a Fourier series. The proposed statistic is the simple average of the individual statistics constructed from the breaks and cross-sectional dependence augmented Dickey-Fuller (BCADF) regression and is called the BCIPS statistic. We initially develop the tests by assuming that the number of factors in the model is known and show that the limiting distribution of the BCADF statistic is free of nuisance parameters. The nonstandard limiting distribution of the (truncated) BCIPS statistic is also shown to exist and its critical values are tabulated. Monte-Carlo experiments point out that the sizes and powers of the BCIPS statistic are generally satisfactory as long as T is greater than or equal to fifty and a hundred, respectively. By using two different methods to determine the number of factors, both the BCIPS and CIPS tests are applied to examine the validity of long-run purchasing power parity. The proposed test complements the panel unit-root tests with breaks using dummy variables.
Author: Chingnun Lee
Publisher:
ISBN:
Category :
Languages : en
Pages : 62
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Book Description
This paper proposes a new simple panel unit-root test by extending the cross-sectionally augmented panel unit-root test (CIPS) developed by Pesaran et al. (2013) to allow for smoothing structural changes in deterministic terms, approximated by a Fourier series. The proposed statistic is the simple average of the individual statistics constructed from the breaks and cross-sectional dependence augmented Dickey-Fuller (BCADF) regression and is called the BCIPS statistic. We initially develop the tests by assuming that the number of factors in the model is known and show that the limiting distribution of the BCADF statistic is free of nuisance parameters. The nonstandard limiting distribution of the (truncated) BCIPS statistic is also shown to exist and its critical values are tabulated. Monte-Carlo experiments point out that the sizes and powers of the BCIPS statistic are generally satisfactory as long as T is greater than or equal to fifty and a hundred, respectively. By using two different methods to determine the number of factors, both the BCIPS and CIPS tests are applied to examine the validity of long-run purchasing power parity. The proposed test complements the panel unit-root tests with breaks using dummy variables.
Author: William A. Barnett
Publisher: Emerald Group Publishing
ISBN: 1787564533
Category : Business & Economics
Languages : en
Pages : 320
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Book Description
This book features technical portrayals of today’s constantly developing banking issues; including stock market contagion, the impact of internet technology (IT) and financial innovation on stock markets, and a perspective on the loan puzzle in emerging markets.
Author: M. Hashem Pesaran
Publisher:
ISBN:
Category : Error analysis (Mathematics)
Languages : en
Pages : 54
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Book Description
Author: Paramsothy Silvapulle
Publisher:
ISBN:
Category : Monte Carlo method
Languages : en
Pages : 30
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Author: Ming Meng
Publisher:
ISBN:
Category : Electronic dissertations
Languages : en
Pages : 88
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Book Description
This dissertation is concerned with finding ways to improve the power of unit root tests. This dissertation consists of three essays. In the first essay, we extends the Lagrange Multiplier (LM) unit toot tests of Schmidt and Phillips (1992) to utilize information contained in non-normal errors. The new tests adopt the Residual Augmented Least Squares (RALS) estimation procedure of Im and Schmidt (2008). This essay complements the work of Im, Lee and Tieslau (2012) who adopt the RALS procedure for DF-based tests. This essay provides the relevant asymptotic distribution and the corresponding critical values of the new tests. The RALS-LM tests show improved power over the RALS-DF tests. Moreover, the main advantage of the RALS-LM tests lies in the invariance feature that the distribution does not depend on the nuisance parameter in the presence of level-breaks. The second essay tests the Prebisch-Singer hypothesis by examining paths of primary commodity prices which are known to exhibit multiple structural breaks. In order to examine the issue more properly, we first suggest new unit root tests that can allow for structural breaks in both the intercept and the slope. Then, we adopt the RALS procedure to gain much improved power when the error term follows a non-normal distribution. Since the suggested test is more powerful and free of nuisance parameters, rejection of the null can be considered as more accurate evidence of stationarity. We apply the new test on the recently extended Grilli and Yang index of 24 commodity series from 1900 to 2007. The empirical findings provide significant evidence to support that primary commodity prices are stationary with one or two trend breaks. However, compared with past studies, they provide even weaker evidence to support the Prebisch-Singer hypothesis. The third essay extends the Fourier Lagrange Multiplier (FLM) unit root tests of Enders and Lee (2012a) by using the RALS estimation procedure of Im and Schmidt (2008). While the F\LM type of tests can be used to control for smooth structural breaks of an unknown functional form, the RALS procedure can utilize additional higher-moment information contained in non-normal errors. For these new tests, knowledge of the underlying type of non-normal distribution of the error term or the precise functional form of the structure breaks is not required. Our simulation results demonstrate significant power gains over the FLM tests in the presence of non-normal errors.
Author: Junsoo Lee
Publisher:
ISBN:
Category : Autocorrelation (Statistics)
Languages : en
Pages : 304
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Book Description
Author: M. Hashem Pesaran
Publisher:
ISBN:
Category : Dependence (Statistics)
Languages : en
Pages : 45
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Author: Walter Enders
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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We develop a unit-root test based on a simple variant of Gallant's (1981) flexible Fourier form. The test relies on the fact that a series with several smooth structural breaks can often be approximated using the low frequency components of a Fourier expansion. Hence, it is possible to test for a unit root without having to model the precise form of the break. Our unit-root test employing Fourier approximation has good size and power for the types of breaks often used in economic analysis. The appropriate use of the test is illustrated using several interest rate spreads.
Author: Xuguang Simon Sheng
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
This paper proposes a simple panel unit root test based on Zaykin et al.'s (2002) truncated product method. The test is powerful in cases where there are only a few large p-values, and is robust to a certain degree of cross-section dependence. Monte Carlo evidence shows good size and power properties relative to existing p-value combination tests. Unlike the previous tests, the new test allows to make stronger claims in the event of rejection of the null hypothesis. The proposed test is applied to a panel of 27 OECD real exchange rate series as well as to a group of inflation density forecasts in the SPF data.
Author: Uwe Hassler
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
In this paper, several seasonal unit root tests are analysed in the context of structural breaks at known time and a new break corrected test is suggested. We show that the widely used HEGY test, as well as an LM variant thereof, are asymptotically robust to seasonal mean shifts of finite magnitude. In finite samples, however, experiments reveal that such tests suffer from severe size distortions and power reductions when breaks are present. Hence, a new break corrected LM test is proposed to overcome this problem. Importantly, the correction for seasonal mean shifts bears no consequence on the limiting distributions, thereby maintaining the legitimacy of canonical critical values. Moreover, although this test assumes a breakpoint a priori, it is robust in terms of misspecification of the time of the break. This asymptotic property is well reproduced in finite samples. Based on a Monte-Carlo study, our new test is compared with other procedures suggested in the literature and shown to hold superior finite sample properties.
