On the Specificity and Performance of Panel Unit Root Tests PDF Download
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Author: Steph De Silva
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 366
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Author: Steph De Silva
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 366
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Author: Janice Boucher Breuer
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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A unit root testing procedure is presented that exploits the well-established power advantages of panel estimation while rectifying a deficiency in other panel unit root tests. This test (called SURADF) is based on seemingly unrelated regressions applied to Augmented Dickey-Fuller (ADF) tests for a unit root. In contrast to extant panel unit root tests, our test allows for determination of which members of the panel reject the null hypothesis of a unit root and which ones do not. The power of the test is investigated with Monte Carlo simulation and demonstrated with application to several panels of real exchange rates. We find that when the contemporaneous cross-correlations of the residuals are high, our procedure has substantially more power to reject a unit root than the single equation Dickey-Fuller test.
Author: Jaroslava Hlouskova
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Badi H. Baltagi
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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This paper studies the performance of panel unit root tests when spatial effects are present that account for cross-section correlation. Monte Carlo simulations show that there can be considerable size distortions in panel unit root tests when the true specification exhibits spatial error correlation. These tests are applied to a panel data set on net real income from the 1000 largest French communes observed over the period 1985-1998.
Author: Laszlo Konya
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Using several different unit root/stationarity tests on single time series Konya (2000) found the logarithm of real GDP of most OECD countries behaving as a random walk during the last four decades. This outcome, however, might be due to the generally low power of these tests. The aim of this paper is to reconsider this issue by exploiting the extra information provided by the combination of the time-series and cross-sectional data and the subsequent power advantages of panel data unit root tests. We apply the tests advocated by Levin and Lin (1993), Im, Pesaran and Shin (1997) and Maddala and Wu (1999). The joint unit root null hypothesis cannot be rejected for the whole panel, however, after having dropped the least likely stationary series from the panel, the Im, Pesaran and Shin (1997) and Maddala and Wu (1999) tests can reject the null for the remaining sub-panels. Since these tests are not valid under cross-correlated error terms, we repeat them with data specific bootstrap critical values taking contemporaneous cross-correlation into account. This way, both tests can reject the unit root null hypothesis even for the whole panel. Yet, they cannot suggest how many and which particular panel members are stationary, so these results are not really informative. For this reason finally we apply the unit root test of Breuer, McNown and Wallace (1999) with bootstrap critical values. This procedure makes use of the panel data setting and seemingly unrelated regressions, but performs separate unit-root tests on each panel member. The results are markedly different from the conventional univariate Dickey-Fuller test results, and they support trend stationarity in the case of four countries: Australia, Japan, the Netherlands and Switzerland.
Author: L. Gutierrez
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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This paper deals with the finite-sample performance of a set of unit-root tests for cross-correlated panels. Most of the available macroeconomic time series cover short time periods. The lack of information, in terms of time observations, implies that univariate tests are not powerful enough to reject the null of a unit-root while panel tests, by exploiting the large number of cross-sectional units, have been shown to be a promising way of increasing the power of unit-root tests. We investigate the finite sample properties of recently proposed panel unit-root tests for cross-sectionally correlated panels. Specifically, the size and power of Choi's [Econometric Theory and Practice: Frontiers of Analysis and Applied Research: Essays in Honor of Peter C. B. Phillips, Cambridge University Press, Cambridge (2001)], Bai and Ng's [Econometrica (2004), Vol. 72, p. 1127], Moon and Perron's [Journal of Econometrics (2004), Vol. 122, p. 81], and Phillips and Sul's [Econometrics Journal (2003), Vol. 6, p. 217] tests are analysed by a Monte Carlo simulation study. In synthesis, Moon and Perron's tests show good size and power for different values of T and N, and model specifications. Focusing on Bai and Ng's procedure, the simulation study highlights that the pooled Dickey-Fuller generalized least squares test provides higher power than the pooled augmented Dickey-Fuller test for the analysis of non-stationary properties of the idiosyncratic components. Choi's tests are strongly oversized when the common factor influences the cross-sectional units heterogeneously.
Author: Hyungsik Roger Moon
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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This paper studies testing for a unit root for large n and T panels in which the cross-sectional units are correlated. To model this cross-sectional correlation, we assume that the data is generated by an unknown number of unobservable common factors. We propose unit root tests in this environment and derive their (Gaussian) asymptotic distribution under the null hypothesis of a unit root and local alternatives. We also show that these tests have no power against the same local alternatives when it is necessary to remove deterministic components. Through Monte Carlo simulations, we provide evidence on the finite sample properties of these new tests.
Author: G. S. Maddala
Publisher: Cambridge University Press
ISBN: 9780521587822
Category : Business & Economics
Languages : en
Pages : 528
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A comprehensive review of unit roots, cointegration and structural change from a best-selling author.
Author: Kristian Jönsson
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Abstract: In this paper, we investigate the performance of a panel data stationarity test when cross-sectional correlation is modelled by a time-specific factor. Size distortions, that occurs especially when the number of cross sections is small, are documented. To eliminate these distortions, a new set of critical values is supplied. When investigating the rejection frequency under the alternative hypothesis, it is found that the panel data stationarity test that uses the supplied critical values maintain good power characteristics even when only a subset of the cross-sectional units have a unit root
Author: Janice Boucher Breuer
Publisher:
ISBN:
Category :
Languages : en
Pages : 36
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