Spurious regressions between I(1) processes with long memory errors

Abstract

In this paper we develop the asymptotic distribution theory for spurious regression between I(1) processes with long‐memory stationary errors. Our result departs from the standard results of Phillips (Understanding spurious regression in econometrics. J. Economet. 33 (1986), 311–40) in two respects. First, the limit theory we apply is based on a functional central limit theorem for stationary linear processes whose spectral density at frequency zero may diverge or collapse to zero. Second, different limit distributions may apply depending on the form of long memory exhibited by the error term. We also discuss the extension of our analyis to spurious regression with fitted intercept.