This paper calculates response surface models for a large range of quantiles of the Leybourne (Oxf Bull Econ Stat 57:559-571, 1995) test for the null hypothesis of a unit root against the alternative of (trend) stationarity. The response surface models allow the estimation of critical values for different combinations of number of observations, T, and lag order in the test regressions, p, where the latter can be either specified by the user or optimally selected using a data-dependent procedure. The results indicate that the critical values depend on the method used to select the number of lags. An Excel spreadsheet is available to calculate the p-value associated with a test statistic.
