Gaussian normal error assumption is a basic assumption for
co-integration tests. Ordinary Least Squares (OLS) based regression
techniques are also widely used together with the normality
assumption. To consider the heavy-tailed structure observed in many
economic and financial time series, new residual-based
co-integration tests are developed and analyzed via Monte Carlo
simulations. The new tests are based on Least Absolute Deviation
(LAD) regressions, whose error structure follows the
infinite-variance stable distribution. Empirical applications on
Forward Rate Unbiasedness Hypothesis (FRUH) and Purchasing Power
Parity (PPP) verify the need to make use of the infinite-variance
stable distributions as the error distributions.
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