Abstract
This paper enlarges on Gutierrez’s results on the power of panel cointegration tests. By a comparison of power of panel cointegration tests, we show how the choice of most powerful test depends on the values of the sample statistics. Country-by-country and panel stationarity and cointegration tests are performed on a panel of 20 OECD countries over the period 1971-2004. Residual-based tests and a cointegration rank test in the system of health care expenditure and GDP are used to test cointegration. Asymptotic normal distribution of these tests allows a straightforward comparison for some values of the sample statistics, residual-based and rank tests are not directly comparable as the power of the residual-based tests oscillates; for other values of the sample statistics, the rank test is more powerful than the residualbased tests. This suggests that a clear-cut conclusion on the most powerful test cannot be reached a priori.
Highlights
This paper offers an alternative way to compare power of panel tests of cointegration based on the comparison between values of the sample statistics and statistics associated to the data generating process (DGP)
The choice of the most powerful test depends on the values of the sample statistics
The 1%, 5% and 10% critical values are for the panel tests 2.326, 1.645 and 1.282
Summary
The main reason for this change of interests is the extended use of panel data starting from the 1990s [2,3,13]. Advantages and concerns relative to the use of panel data are discussed in various papers [15,22]. One of the main issues raised by the use of panel data is the problem of cointegration of non-stationary variables. Various papers have tried to solve such issue but have reached inconclusive evidence on the matter both on country-by-country and panel tests [6,12,14,23]. We first verify the existence of a cointegrating vector of non-stationary health care expenditure and GDP and we compare the power of three panel cointegration tests to assess which is the most powerful
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