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To authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1467-8586.2009.00323.x Byline: Josep Lluis Carrion-i-Silvestre (*), Kaddour Hadri ([dagger]) Keywords: fixed time dimension; panel data unit root Abstract: ABSTRACT 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. Author Affiliation: (*)AQR-IREA Research Group, Department of Econometrics, Statistics and Spanish Economy, University of Barcelona, Spain ([dagger])Management School, Queen's University Belfast, UK Article note: Correspondence: Josep Lluis Carrion-i-Silvestre, AQR-IREA Research Group, Department of Econometrics, Statistics and Spanish Economy, University of Barcelona, Avinguda Diagonal 690, 08034 Barcelona, Spain. Tel: +34-93-402-4598; Fax: +34-93-402-1821; Email: carrion@ub.edu. Financial support is acknowledged from the Ministerio de Ciencia y Tecnologia under grant ECO2008-06241/ECON.

To authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1467-8586.2009.00327.x Byline: Yao Rao (*), Kaddour Hadri ([dagger]), Ruijun Bu (*) Keywords: heterogeneous panel data; model misspecification; stationarity test Abstract: ABSTRACT This paper investigates the performance of the tests proposed by Hadri and by Hadri and Larsson for testing for stationarity in heterogeneous panel data under model misspecification. The panel tests are based on the well known KPSS test (cf. Kwiatkowski et al.) which considers two models: stationarity around a deterministic level and stationarity around a deterministic trend. There is no study, as far as we know, on the statistical properties of the test when the wrong model is used. We also consider the case of the simultaneous presence of the two types of models in a panel. We employ two asymptotics: joint asymptotic, T, N [double right arrow][infinity] simultaneously, and T fixed and N allowed to grow indefinitely. We use Monte Carlo experiments to investigate the effects of misspecification in sample sizes usually used in practice. The results indicate that the assumption that T is fixed rather than asymptotic leads to tests that have less size distortions, particularly for relatively small T with large N panels (micro-panels) than the tests derived under the joint asymptotics. We also find that choosing a deterministic trend when a deterministic level is true does not significantly affect the properties of the test. But, choosing a deterministic level when a deterministic trend is true leads to extreme over-rejections. Therefore, when unsure about which model has generated the data, it is suggested to use the model with a trend. We also propose a new statistic for testing for stationarity in mixed panel data where the mixture is known. The performance of this new test is very good for both cases of T asymptotic and T fixed. The statistic for T asymptotic is slightly undersized when T is very small ([less than or equal to]10). Author Affiliation: (*)The University of Liverpool, Liverpool, UK ([dagger])Queen's University Belfast, Belfast, UK Article note: Correspondence: K. Hadri, 25 University Square, Queen's University Belfast, Belfast BT7 1NN, UK; Email: K.Hadri@QUB.ac.uk. The authors would like to thank the Editor and the referees for their valuable comments and suggestions which greatly helped to improve the paper. Any remaining shortcomings are ours.

To purchase or authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1468-0084.2008.00502.x Byline: Kaddour Hadri ([dagger]), Yao Rao ([double dagger]) Keywords: C12; C23; C52 Abstract: Abstract In this paper, we extend the heterogeneous panel data stationarity test of Hadri [Econometrics Journal, Vol. 3 (2000) pp. 148-161] to the cases where breaks are taken into account. Four models with different patterns of breaks under the null hypothesis are specified. Two of the models have been already proposed by Carrion-i-Silvestre et al. [Econometrics Journal, Vol. 8 (2005) pp. 159-175]. The moments of the statistics corresponding to the four models are derived in closed form via characteristic functions. We also provide the exact moments of a modified statistic that do not asymptotically depend on the location of the break point under the null hypothesis. The cases where the break point is unknown are also considered. For the model with breaks in the level and no time trend and for the model with breaks in the level and in the time trend, Carrion-i-Silvestre et al. [Econometrics Journal, Vol. 8 (2005) pp. 159-175] showed that the number of breaks and their positions may be allowed to differ across individuals for cases with known and unknown breaks. Their results can easily be extended to the proposed modified statistic. The asymptotic distributions of all the statistics proposed are derived under the null hypothesis and are shown to be normally distributed. We show by simulations that our suggested tests have in general good performance in finite samples except the modified test. In an empirical application to the consumer prices of 22 OECD countries during the period from 1953 to 2003, we found evidence of stationarity once a structural break and cross-sectional dependence are accommodated. Author Affiliation: ([dagger])Department of Economics & Finance, Durham Business School, 23/26 Old Elvet, Durham University, Durham DH1 3HY, UK(e-mail:kaddour.hadri@durham.ac.uk) ([double dagger])Department of Economics, Liverpool Business School, Chatham Street, Liverpool University, Liverpool L69 72H, UK (e-mail:coolyao@liv.ac.uk) Article History: Final Manuscript Received: July 2007

A number of countries have granted more autonomy to central banks in deciding interest rates and greater independence appears to be linked to improved macroeconomic performance. The political business cycle relates to such factors as seeking to 'bribe' the electorate prior to an election. An examination of data from 18 countries from the Organization for Economic Cooperation and Development (OECD) indicates a negative correlation between partiisan and electoral effects and the independence of the central bank.

This note reexamines the general class of Sargan densities analyzed by Goldfeld and Quandt (1981), Kafei and Schmidt (1985), and others in the context of approximating normal densities in certain econometric models. It suggests a third-order Sargan density which complies with the Goldfeld and Quandt criteria, is unimodal, and is the best approximation to the normal for orders less than or equal to 3. Some errors in Goldfeld and Quandt paper are corrected. Key words: Sargan densities; C.d.f. in a closed form; Nonnormal maximum likelihood estimation; Disequilibrium models JEL classification: C10; C13; C24; C34

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. [ABSTRACT FROM AUTHOR]

The bias of estimate parameters in autoregressive models is shown to increase as the sample size grows.

We propose a new approach for modeling nonlinear multivariate interest rate processes based on time-varying copulas and reducible stochastic differential equations (SDEs). In the modeling of the marginal processes, we consider a class of nonlinear SDEs that are reducible to Ornstein–Uhlenbeck (OU) process or Cox, Ingersoll, and Ross (1985) (CIR) process. The reducibility is achieved via a nonlinear transformation function. The main advantage of this approach is that these SDEs can account for nonlinear features, observed in short-term interest rate series, while at the same time leading to exact discretization and closed-form likelihood functions. Although a rich set of specifications may be entertained, our exposition focuses on a couple of nonlinear constant elasticity volatility (CEV) processes, denoted as OU-CEV and CIR-CEV, respectively. These two processes encompass a number of existing models that have closed-form likelihood functions. The transition density, the conditional distribution function, and the steady-state density function are derived in closed form as well as the conditional and unconditional moments for both processes. In order to obtain a more flexible functional form over time, we allow the transformation function to be time varying. Results from our study of U.S. and UK short-term interest rates suggest that the new models outperform existing parametric models with closed-form likelihood functions. We also find the time-varying effects in the transformation functions statistically significant. To examine the joint behavior of interest rate series, we propose flexible nonlinear multivariate models by joining univariate nonlinear processes via appropriate copulas. We study the conditional dependence structure of the two rates using Patton (2006a) time-varying symmetrized Joe–Clayton copula. We find evidence of asymmetric dependence between the two rates, and that the level of dependence is positively related to the level of the two rates. (JEL: C13, C32, G12) [ABSTRACT FROM AUTHOR]