Generation Panel Unit Root Tests Research Articles

Is the crisis treatment exacerbating cautiousness or risk-taking?

Using second generation Panel Unit Root Tests (PURT), panel cointegration tests and panel Granger causality tests we find that although the financial crisis may have increased risk aversion for investors, it did not make disappearing speculative behaviours on structured credit markets. On the contrary, support measures to the banking sector and fiscal stimulus packages have given the opportunity for some investors to speculate on sovereign debt through Credit Default Swap (CDS) vehicles. Thus this article supports ongoing initiatives to strengthen the prudential regulation undertaken in these markets under the Group of 20 (G20) or the Financial Stability Forum (FSF).

Homogenous panel unit root tests under cross sectional dependence: Finite sample modifications and the wild bootstrap

First generation panel unit root tests are known to be invalid under cross sectional dependence. Focussing on the subclass of homogenous tests, three extensions of existing approaches are proposed. First, a test based on a generalized variance estimator is suggested for panels with small time and relatively large cross sectional dimension. Second, the application of refined residuals in variance estimators is proposed to reduce finite sample biases. Third, the wild bootstrap is proved to be an asymptotically valid method of resampling homogenous panel unit root test statistics. A Monte Carlo study shows that the wild bootstrap yields unbiased inference, even in cases where existing procedures are biased. Most accurate results under the null hypothesis are obtained by resampling robust statistics while there is no, or minor, evidence of power loss invoked by the wild bootstrap. An empirical illustration underpins that the current account to GDP ratio is likely panel stationary.

Do hours worked contain a unit root? Evidence from panel data

The aim of the present paper is to provide cross country evidence of the non-stationarity of hours worked for OECD countries. For this purpose, panel unit root tests are employed to improve power against univariate counterparts. Since cross section correlation is a distinct feature of the underlying panel data, results are based on various second generation panel unit root tests, which account for cross section dependence among units. If an unobserved common factor model is assumed for generating the observations, there is indication for both a common factor and idiosyncratic components driving the non-stationarity of hours worked. In addition, taking these results together, there is no indication of cointegration among the individual time series of hours worked.

On PPP, unit roots and panels

In this paper we use a combination of time series unit root and cointegration analysis and the Bai and Ng (Econometrica 72:1127–1187, 2004) factor model approach to assess the purchasing power parity hypothesis for four real exchange rate panels. Our main findings are twofold: First, we find robust evidence for nonstationary common components in the real exchange rate panels and hence no evidence for PPP. Second, the presence of nonstationary common components is consistent with rejections of the unit root null hypothesis when applying a battery of first and second generation panel unit root tests, which are known to be adversely affected in the presence of common nonstationary components.

Heterogeneity and cross section dependence in panel data models: theory and applications introduction

AbstractThe papers included in this special issue are primarily concerned with the problem of cross section dependence and heterogeneity in the analysis of panel data models and their relevance in applied econometric research. Cross section dependence can arise due to spatial or spill over effects, or could be due to unobserved (or unobservable) common factors. Much of the recent research on non‐stationary panel data have focussed on this problem. It was clear that the first generation panel unit root and cointegration tests developed in the 1990's, which assumed cross‐sectional independence, are inadequate and could lead to significant size distortions in the presence of neglected cross‐section dependence. Second generation panel unit root and cointegration tests that take account of possible cross‐section dependence in the data have been developed, see the recent surveys by Choi (2006) and Breitung and Pesaran (2007). The papers by Baltagi, Bresson and Pirotte, Choi and Chue, Kapetanios, and Pesaran in this special issue are further contributions to this literature. The papers by Fachin, and Moon and Perron are empirical studies in this area. Controlling for heterogeneity has also been an important concern for empirical researchers with panel data methods promising better handle on heterogeneity than cross‐section data methods. The papers by Hsiao, Shen, Wang and Weeks, Pedroni and Serlenga and Shin are empirical contributions to this area. Copyright © 2007 John Wiley & Sons, Ltd.

The Performance of Panel Unit Root and Stationarity Tests: Results from a Large Scale Simulation Study

This paper presents results on the size and power of first generation panel unit root and stationarity tests obtained from a large scale simulation study. The tests developed in the following papers are included: Levin et al. (2002), Harris and Tzavalis (1999), Breitung (2000), Im et al. (19972003), Maddala and Wu (1999), Hadri (2000), and Hadri and Larsson (2005). Our simulation set-up is designed to address inter alia the following issues. First, we assess the performance as a function of the time and the cross-section dimensions. Second, we analyze the impact of serial correlation introduced by positive MA roots, known to have detrimental impact on time series unit root tests, on the performance. Third, we investigate the power of the panel unit root tests (and the size of the stationarity tests) for a variety of first order autoregressive coefficients. Fourth, we consider both of the two usual specifications of deterministic variables in the unit root literature.

Panel Tests for Unit Roots in Hours Worked

Hours worked is a time series of interest in many empirical investigations of the macroeconomy. Estimates of macro elasticities of labour supply, for example, build on this variable. Other empirical applications investigate the response of hours worked to a shock to technology on the basis of the real business cycle model. Irrespective of the problem being addressed, robust inference of empirical outcomes strongly hinges on the adequately modelling of the time series of hours worked. The aim of the present paper is to provide cross country evidence of the nonstationarity of hours worked for OECD countries. For these purposes, panel unit root tests are employed to improve power against univariate counterparts. Since cross section correlation is a distinct feature of the underlying panel data, results are based on various second generation panel unit root tests which account for cross section dependence among units. If an unobserved common factor model is assumed for generating the observations, there is indication for both a common factor and idiosyncratic components driving the non-stationarity of hours worked. In addition, taking these results together, there is no indication of cointegration among the individual time series of hours worked.

A Reappraisal of the Evidence on PPP: A Systematic Investigation into Ma Roots in Panel Unit Root Tests and Their Implications

Panel unit root tests of real exchange rates – as opposed to univariate tests – usually reject non-stationarity. These tests, however, could be biased if the real exchange rate contained MA roots. Indeed, two independent arguments claim that the real exchange rate, being a sum of a stationary and a non-stationary component, is possibly an ARIMA (1, 1, 1) process. Monte Carlo simulations show, how systematic changes in the parameters of the components, of the test equation and of the correlation matrix affect the size of first and second generation panel unit root tests. Two components of the real exchange rate, the real exchange rate of a single good and a weighted sum of relative prices, are constructed from the data for a panel of countries. Computation of the relevant parameters reveals that panel unit root tests of the real exchange rate are severely oversized, usually much more so than simple ADF tests. Thus, the evidence for PPP from panel unit root tests may be merely due to extreme size biases.