Abstract
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.
Highlights
Panel unit root and stationarity tests have become extremely popular and widely used over the last decade
Paralleling the above argument the Lagrange multiplier panel unit root test statistic is given by IP SLM,m(p, γ)
We summarize the dependency of the data generating process (DGP) upon these parameters notationally as
Summary
Panel unit root and stationarity tests have become extremely popular and widely used over the last decade. In our study we consider moving average roots in the set {0.2, 0.4, 0.8, 0.9, 0.95, 0.99} and include the case of no moving average root We investigate the performance of the tests for the two most common, and arguably for economic time series most relevant, specifications of deterministic variables These are intercepts in the data generating process (DGP) when stationary but no drifts when integrated (referred to as case 2), and intercepts and linear trends under stationarity and drifts when integrated (referred to as case 3).. Case 1 contains no deterministic components in both the stationary and the nonstationary case, case 2 allows for intercepts in the DGP when stationary but excludes a drift when integrated, and case 3 allows for intercepts and linear trends under stationarity and for a drift when a unit root is present
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