Tests of trend versus random walk in macroeconomic time-series

This dissertation investigates unit-root tests in macroeconomic time series. If a time series is regressed on itself, lagged one period, a constant and a time trend, it is said to have a unit root if the coefficient on the lagged variable is equal to one. This is of interest because a shock to the series will persist over time, instead of dissipating.;The third chapter uses these corrected critical values to test the data set of Nelson and Plosser for unit roots. When an unrestricted estimate of the standardized coefficient of time trend is used, the Dickey-Fuller statistics reject the null hypothesis of a unit root more often than when restricted or unbiased estimates of the coefficient are used. Unit-root tests proposed by Ouliaris, Park and Phillips and by Schmidt and Phillips fail to reject the unit-root hypothesis for most series.;The fourth chapter derives two new test statistics and their asymptotic distributions. These take "level stationarity" or "trend stationarity" as their null hypotheses. For almost all of the Nelson-Plosser data set level stationarity can be rejected, but for many series trend stationarity cannot. This suggests that for many series the existence of a unit root is in doubt.;A final chapter summarizes findings and suggests some avenues for future research.;The first chapter is a general introduction to the subject. The second chapter provides extensive tabulations of two statistics proposed by Dickey and Fuller to test the null hypothesis of a unit root when a time trend is present. The critical values for these statistics depend on sample size and the standardized coefficient of time trend. These tabulations differ from those of Dickey and Fuller because they assumed the standardized coefficient of time trend was equal to zero in the data-generating process.