Testing for Cointegration in the Presence of Moving Average Errors

 This study explores performance of the Johansen cointegration statistics on data containingnegative moving average (NMA) errors. Monte Carlo experiments demonstrate that the asymptoticdistributions of the statistics are sensitive to NMA parameters, and that using the standard 5%asymptotic critical values results in severe underestimation of the actual test sizes. We demonstratethat problems associated with NMA errors do not decrease as sample size increases; instead,they become more severe. Further we examine evidence that many U.S. commodity prices arecharacterized by NMA errors. Pretesting data is recommended before using standard asymptoticcritical values for Johansen’s cointegration tests