@article{King:267423,
      recid = {267423},
      author = {King, Maxwell L. and Rankin, Mei Leng},
      title = {Pre-Test Strategies for Time-Series Forecasting in the  Linear Regression Model},
      address = {1993-11-01},
      number = {2012-2018-570},
      series = {Working Paper No. 17/93},
      pages = {27},
      year = {1993},
      abstract = {In linear time-series regression analysis, there is  typically uncertainty about which variables to include as  regressors and the exact form of the disturbance process.  This paper uses the Monte Carlo method to investigate the  predictive performance of nine different pretesting  strategies for misspecification. Data generating processes  used in the study include first-order autoregressive  (AR(1)) disturbances, first-order moving average  disturbances, an extra exogenous regressor and the lagged  dependent variable as an extra regressor. We find that  remarkably robust predictions for a range of misspecified  models result from applying the Durbin-Watson test for  autocorrelation and correcting for AR(1) disturbances when  the test is significant.},
      url = {http://ageconsearch.umn.edu/record/267423},
      doi = {https://doi.org/10.22004/ag.econ.267423},
}