967 resultados para Unit root test


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The consideration of the limit theory in which T is fixed and N is allowed to go to infinity improves the finite-sample properties of the tests and avoids the imposition of the relative rates at which T and N go to infinity.

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This paper proposes the use of an improved covariate unit root test which exploits the cross-sectional dependence information when the panel data null hypothesis of a unit root is rejected. More explicitly, to increase the power of the test, we suggest the utilization of more than one covariate and offer several ways to select the ‘best’ covariates from the set of potential covariates represented by the individuals in the panel. Employing our methods, we investigate the Prebish-Singer hypothesis for nine commodity prices. Our results show that this hypothesis holds for all but the price of petroleum.

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In this article, we examine the issue of a levels relationship and stability of the US money demand function over the period 1959:01 to 2004:02. We use the Lagrange multiplier structural break unit root test and the bounds testing approach to a long-run relationship in levels of the variables, namely real money demand, nominal interest rate and real income. We find greater evidence for a long-run relationship in levels and stability of the US money demand function when we use M2 as a proxy for money demand. However, we find little evidence for a long-run relationship between M1 and M2 with their determinants for the recent period, spanning the last decade or so.

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In this paper, we propose a new augmented Dickey–Fuller-type test for unit roots which accounts for
two structural breaks. We consider two different specifications: (a) two breaks in the level of a trending data series and (b) two breaks in the level and slope of a trending data series. The breaks whose time of occurrence is assumed to be unknown are modeled as innovational outliers and thus take effect gradually. Using Monte Carlo simulations, we showthat our proposed test has correct size, stable power, and identifies the structural breaks accurately.

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When testing for a unit root in a time series, in spite of the well-known power problem of univariate tests, it is quite common to use only the information regarding the autoregressive behaviour contained in that series. In a series of influential papers, Elliott et al. (Efficient tests for an autoregressive unit root, Econometrica 64, 813–836, 1996), Hansen (Rethinking the univariate approach to unit root testing: using covariates to increase power, Econometric Theory 11, 1148–1171, 1995a) and Seo (Distribution theory for unit root tests with conditional heteroskedasticity, Journal of Econometrics 91, 113–144, 1999) showed that this practice can be rather costly and that the inclusion of the extraneous information contained in the near-integratedness of many economic variables, their heteroskedasticity and their correlation with other covariates can lead to substantial power gains. In this article, we show how these information sets can be combined into a single unit root test.

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In a recent study, Westerlund (Empir Econ 37:517–531, 2009) shows that the performance of the popular LLC (Levin et al., J Econ 108:1–24, 2002) panel unit root test depends critically on the choice of lag truncation used when correcting for serial correlation, and that it is only when this parameter is set as a function of time that the power raises above size. The purpose of the current paper is to propose a modified test that does not suffer from this drawback. The new test is not only simpler to compute but also superior in terms of small-sample performance, which is illustrated using an example purchasing power parity for less developed countries.

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One of the single most cited studies within the field of nonstationary panel data analysis is that of LLC (Levin et al. in J Econom 98:1 - 24, 2002), in which the authors propose a test for a common unit root in the panel. Using both theoretical arguments and simulation evidence, we show that this test can be misleading unless it is based on the same bandwidth selection rule used by LLC. © Springer-Verlag 2008.

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The CADF test of Pesaran (J Appl Econ 22:265–312, 2007) are among the most popular univariate tests for cross-section correlated panels around. Yet, the existing asymptotic analysis of this test statistic is limited to a model in which the errors are assumed to follow a simple AR(1) structure with homogenous autoregressive coefficients. One reason for this is that the model involves an intricate identification issue, as both the serial and cross-section correlation structures of the errors are unobserved. The purpose of the current paper is to tackle this issue and in so doing extend the existing analysis to the case of AR((Formula presented.)) errors with possibly heterogeneous coefficients.

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This paper constructs a unit root test baseei on partially adaptive estimation, which is shown to be robust against non-Gaussian innovations. We show that the limiting distribution of the t-statistic is a convex combination of standard normal and DF distribution. Convergence to the DF distribution is obtaineel when the innovations are Gaussian, implying that the traditional ADF test is a special case of the proposed testo Monte Carlo Experiments indicate that, if innovation has heavy tail distribution or are contaminated by outliers, then the proposed test is more powerful than the traditional ADF testo Nominal interest rates (different maturities) are shown to be stationary according to the robust test but not stationary according to the nonrobust ADF testo This result seems to suggest that the failure of rejecting the null of unit root in nominal interest rate may be due to the use of estimation and hypothesis testing procedures that do not consider the absence of Gaussianity in the data.Our results validate practical restrictions on the behavior of the nominal interest rate imposed by CCAPM, optimal monetary policy and option pricing models.

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This paper proposes an IV-based panel unit root test that is general enough to accommodate general error serial and cross-section dependence, and a potentially nonlinear deterministic trend function. These allowances make the new test one of the most general around. It is also very simple to implement. Indeed, the IV statistic is asymptotically invariant to not only to all nuisance parameters characterizing the dependence of the errors and the true trend function, but also the deterministic specification of the fitted test regression.

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We extend the class of M-tests for a unit root analyzed by Perron and Ng (1996) and Ng and Perron (1997) to the case where a change in the trend function is allowed to occur at an unknown time. These tests M(GLS) adopt the GLS detrending approach of Dufour and King (1991) and Elliott, Rothenberg and Stock (1996) (ERS). Following Perron (1989), we consider two models : one allowing for a change in slope and the other for both a change in intercept and slope. We derive the asymptotic distribution of the tests as well as that of the feasible point optimal tests PT(GLS) suggested by ERS. The asymptotic critical values of the tests are tabulated. Also, we compute the non-centrality parameter used for the local GLS detrending that permits the tests to have 50% asymptotic power at that value. We show that the M(GLS) and PT(GLS) tests have an asymptotic power function close to the power envelope. An extensive simulation study analyzes the size and power in finite samples under various methods to select the truncation lag for the autoregressive spectral density estimator. An empirical application is also provided.

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There is a plethora of studies that investigate evidence for the behaviour of stock prices using univariate techniques for unit roots. Whether or not stock prices are characterised by a unit root have implications for the efficient market hypothesis, which asserts that returns of a stock market are unpredictable from previous price changes. The extant literature has found mixed evidence on the integrational properties of stock prices. In this paper, for the first time, we provide evidence on the unit root hypothesis for G7 stock price indices using the Lagrangian multiplier panel unit root test that allows for structural breaks. Our main finding is that stock prices are stationary processes, inconsistent with the efficient market hypothesis.

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Testing for the behaviour of visitor arrivals has important implications for policy, for if visitor arrivals are stationary processes then it implies that shocks to visitor arrivals are transitory. However, if visitor arrivals are found to be characterised by a unit root then this implies that shocks to visitor arrivals are permanent. In this paper we provide the first evidence on the unit root hypothesis for visitor arrivals to Australia using a suite of recently developed panel unit root tests. Our main finding is that visitor arrivals to Australia from twenty tourist source markets and from the G7 markets are mean reverting. implying that any shocks will have only a transitory effect. However; visitor arrivals from eight Asian countries are characterised by a unit root. implying that shocks will have a permanent effect on this market.

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The paper examines the stationarity of India’s real exchange rate vis-a` -vis 16 of its major trading partner countries for the period 1960–2000. Application of the conventional ADF unit root test, the Lagrange multiplier (LM) unit root test with one structural break, and the LM unit root test with two structural breaks provides evidence that India’s exchange rate vis-a` -vis 15 out of 16 countries is stationary, implying support for purchasing power parity.