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Discussion Paper

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Recently Perron (1989) has carried out tests of the unit root hypothesis against the alternative hypothesis of trend stationarity with a break in the trend occurring at the Great Crash of 1929 or at the 1973 oil price shock. His analysis covers the Nelson-Plosser macroeconomic data series as well as a post-war quarter real GNP series. His tests reject the unit root null hypothesis for most of the series. This paper takes issue with the assumption used by Perron that the Great Crash and the oil price shock can be treated as exogenous events. A variation of Perron’s test is considered in which the break point is estimated rather than fixed. We argue this test is more appropriate than Perron’s, since it circumvents the problem of data-mining. The asymptotic distribution of the “estimated break point” test statistic is determined. The data series considered by Perron are reanalyzed using this test statistic. The empirical results make use of the asymptotics developed for the test statistic as well as extensive finite sample corrections obtained by simulation. The effect on the empirical results of fat-tailed and temporally dependent innovations is investigated. In brief, by treating the break point as endogenous, we find that there is less evidence against the unit root hypothesis than Perron finds for many of the data series, but stronger evidence against it for several of the series, including the Nelson-Plosser industrial production, nominal GNP, and real GNP series.

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