Structural breaks and unit roots in Australian macroeconomic time series

We examine the unit root properties of 16 Australian macroeconomic time series using monthly data spanning the period 1960–2004. In addition to the standard Augmented Dickey Fuller (ADF) test, we implement one- and two-break endogenous structural break ADF-type unit root tests as well as one- and two-break Lagrange multiplier (LM) unit root tests. While the ADF test provides relatively little evidence against the unit root null hypothesis, once we allow for structural breaks we are able to reject the unit root null for just under half of the variables at the 10% level or better.

Electricity consumption, employment and real income in Australia evidence from multivariate Granger causality tests

This paper examines the relationship between electricity consumption, employment and real income in Australia within a cointegration and causality framework. We find that electricity consumption, employment and real income are cointegrated and that in the long-run employment and real income Granger cause electricity consumption, while in the short run there is weak unidirectional Granger causality running from income to electricity consumption and from income to employment.

A new unit root test with two structural breaks in level and slope at unknown time

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.

A modified LLC panel unit root test of the PPP hypothesis

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.

Testing for unit roots in panel time-series models with multiple level breaks

This paper proposes two new unit root tests that are appropriate in the presence of an unknown number of structural breaks in the level of the data. One is based on a single time series and the other is based on a panel of multiple series. For the estimation of the number of breaks and their locations, a simple procedure based on outlier detection is proposed. The limiting distributions of the tests are derived and evaluated in small samples using simulation experiments. The implementation of the tests is illustrated using as an example purchasing power parity.

Energy consumption at the state level: the unit root null hypothesis from Australia

In this paper, our goal is to examine the unit root null hypothesis in energy consumption for Australian states and territory. We consider sectoral energy consumption for Australia and its six states and one territory using time series data for the period 1973-2007. This is the first study that does this. Generally, except for some cases in South Australia, we find strong support that shocks to energy consumption have a temporary effect on energy consumption in Australia. © 2009 Elsevier Ltd. All rights reserved.

A unit root model for trending time-series energy variables

In this paper, we propose a GARCH-based unit root test that is flexible enough to account for; (a) trending variables, (b) two endogenous structural breaks, and (c) heteroskedastic data series. Our proposed model is applied to a range of time-series, trending, and heteroskedastic energy variables. Our two main findings are: first, the proposed trend-based GARCH unit root model outperforms a GARCH model without trend; and, second, allowing for a time trend and two endogenous structural breaks are important in practice, for doing so allows us to reject the unit root null hypothesis.

A note on the use of the LLC panel unit root test

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.

On the importance of the first observation in GLS detrending in unit root testing

First-differencing is generally taken to imply the loss of one observation, the first, or at least that the effect of ignoring this observation is asymptotically negligible. However, this is not always true, as in the case of generalized least squares (GLS) detrending. In order to illustrate this, the current article considers as an example the use of GLS detrended data when testing for a unit root. The results show that the treatment of the first observation is absolutely crucial for test performance, and that ignorance causes test break-down.

A factor analytical method to interactive effects dynamic panel models with or without unit root

In a recent study, Bai (Fixed-Effects Dynamic Panel Models, A Factor Analytical Method. Econometrica 81, 285-314, 2013a) proposes a new factor analytic (FA) method to the estimation of dynamic panel data models, which has the unique and very useful property that it is completely bias-free. However, while certainly appealing, it is restricted to fixed effects models without a unit root. In many situations of practical relevance this is a rather restrictive consideration. The purpose of the current study is therefore to extend the FA approach to cover models with multiple interactive effects and a possible unit root.

A unit root test based on partially adaptive estimation

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.