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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: Ming Meng
Publisher:
ISBN:
Category : Electronic dissertations
Languages : en
Pages : 88
Get Book Here
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: Hyejin Lee
Publisher:
ISBN:
Category : Electronic dissertations
Languages : en
Pages : 102
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Book Description
The main focus of this dissertation is to find ways to improve the power in cointegration tests. This dissertation consists of three essays. In the first essay, a modified testing procedure for the Engle and Granger (1987; EG) cointegration test is suggested. Specifically, we suggest augmenting the usual EG testing regression with the first difference of the integrated regressors. The limiting distribution of this modified EG test under the null hypothesis will depend on the nuisance parameter, which reflects the signal-to-noise ratio. This essay shows that the nuisance parameter issue can be resolved when we follow the asymptotic distribution of the modified EG test, and use the relevant new sets of critical values corresponding to the estimated value of the nuisance parameter. It is found that the size and power properties of the modified EG test are fairly good. The modified EG test gains improved power rather than losing power as the signal-to-noise ratio increases. In the second essay, we examine whether non-linear unit root tests is robust with non-normal errors, which provides a motivation for the third essay. Especially, the second essay demonstrates how popular nonlinear unit root tests perform in the presence of non-normal errors. Non-normal errors normally do not pose a problem in usual linear unit root tests since the least squares estimator will still be the most efficient under certain ideal conditions regardless of normal or non-normal errors. The asymptotic properties of the popular linear Dickey-Fuller tests, for example, will be unaffected by non-normal errors. As such, the literature has not paid much attention to this issue. Nevertheless, whether similar results will carry over to nonlinear unit root tests with non-normal errors is a question that merits examination. To our surprise, the extant literature on nonlinear unit root tests has not examined this important question. We find that, in general, nonlinear unit root tests will suffer a loss of power in the presence of non-normal errors. In this regard, this essay brings out the neglected point that the obvious analogies of linear processes do not necessarily hold for nonlinear models. The third essay suggests new cointegration tests that are more powerful in the presence of non-normal errors. We use a two-step procedure based on the "residual augmented least squares" (RALS) method to make use of nonlinear moment conditions driven by non-normal errors. By utilizing this neglected information, we can make the existing tests more powerful. The suggested testing procedure is easy to implement. The underlying idea is similar to adding stationary covariates to improve the power of the test, but the suggested procedure does not require any new covariates outside the system. Instead, we can exploit the information on the non-normal error distribution that is already available but ignored in the usual cointegration tests. Our simulation results show significant power gains over existing cointegration tests.
Author: Kyung So Im
Publisher:
ISBN:
Category :
Languages : en
Pages : 31
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Book Description
This paper proposes new unit root tests that are more powerful when the error term follows a non-normal distribution. The improved power is gained by utilizing the additional moment conditions embodied in non-normal errors. Specifiđ“ŹŠlly, we follow the work of Im and Schmidt (2008), using the framework of generalized methods of moments (GMM), and adopt a simple two-step procedure based on the "residual augmented least squares" (RALS) methodology. Our RALS-based unit root tests make use of non-linear moment conditions through a computationally simple procedure. Our Monte Carlo simulation results show that the RALS-based unit root tests have good size and power properties, and they show significant efficiency gains when utilizing the additional information contained in non-normal errors information that is ignored in traditional unit root tests.
Author: Thomas B. Fomby
Publisher: Emerald Group Publishing
ISBN: 1784411825
Category : Political Science
Languages : en
Pages : 772
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Book Description
This volume honors Professor Peter C.B. Phillips' many contributions to the field of econometrics. The topics include non-stationary time series, panel models, financial econometrics, predictive tests, IV estimation and inference, difference-in-difference regressions, stochastic dominance techniques, and information matrix testing.
Author: Xiao Zhong
Publisher:
ISBN:
Category : Autoregression (Statistics)
Languages : en
Pages : 114
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Book Description
"Unit root tests are frequently employed by applied time series analysts to determine if the underlying model that generates an empirical process has a component that can be well-described by a random walk. More specifically, when the time series can be modeled using an autoregressive moving average (ARMA) process, such tests aim to determine if the autoregressive (AR) polynomial has one or more unit roots. The effect of economic shocks do not diminish with time when there is one or more unit roots in the AR polynomial, whereas the contribution of shocks decay geometrically when all the roots are outside the unit circle. This is one major reason for economists' interest in unit root tests. Unit roots processes are also useful in modeling seasonal time series, where the autoregressive polynomial has a factor of the form (1-[zeta][superscript s]), and s is the period of the season. Such roots are called seasonal unit roots. Techniques for testing the unit roots have been developed by many researchers since late 1970s. Most such tests assume that the errors (shocks) are independent or weakly dependent. Only a few tests allow conditionally heteroskedastic error structures, such as Generalized Autoregressive Conditionally Heteroskedastic (GARCH) error. And only a single test is available for testing multiple unit roots. In this dissertation, three papers are presented. Paper I deals with developing bootstrap-based tests for multiple unit roots; Paper II extends a bootstrap-based unit root test to higher order autoregressive process with conditionally heteroscedastic error; and Paper III extends a currently available seasonal unit root test to a bootstrap-based one while at the same time relaxing the assumption of weakly dependent shocks to include conditional heteroscedasticity in the error structure"--Abstract, page iv.
Author: Matei Demetrescu
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Christopher F. Parmeter
Publisher: Emerald Group Publishing
ISBN: 1837978751
Category : Business & Economics
Languages : en
Pages : 401
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Book Description
It is the editor’s distinct privilege to gather this collection of papers that honors Subhal Kumbhakar’s many accomplishments, drawing further attention to the various areas of scholarship that he has touched.
Author: G. S. Maddala
Publisher: Cambridge University Press
ISBN: 9780521587822
Category : Business & Economics
Languages : en
Pages : 528
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Book Description
A comprehensive review of unit roots, cointegration and structural change from a best-selling author.
Author: Yin-Wong Cheung
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 48
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Author: George Kapetanios
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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This paper proposes a simple direct testing procedure to distinguish a linear unit root process from a globally stationary three-regime self-exciting threshold autoregressive process. We derive the asymptotic null distribution of the Wald statistic, and show that it does not depend on unknown fixed threshold values. Monte Carlo evidence clearly indicates that the exponential average of the Wald statistic is more powerful than the Dickey-Fuller test that ignores the threshold nature under the alternative.
