The global linear trend with autocorrelated disturbances is a surprising omission from the M1 competition. This approach to forecasting is therefore evaluated using the 51 non-seasonal series from the competition. It is contrasted with a fully optimized version of Hoits trend corrected exponential smoothing. It is found that an adaptation of Holts method, in which the growth rate is restricted to be constant, performs almost as well as its traditional counterpart and usually out-performs the global linear trend with autoregressive disturbances. This therefore confirms the results from other studies which indicate that a long-term trend may be missing from many business and economic time series. An implication of this study is that business forecasters, when applying trend corrected exponential smoothing, should explore the possibility of eliminating the second smoothing constant.