Cointegration and Long-Horizon Forecasting
发现，在长期预测中忽略协整关系并不会降低标准多变量预测精度，甚至简单单变量预测也同等准确，并指出标准预测精度指标忽视了变量间协整关系的维持，提出了替代指标。
Imposing cointegration on a forecasting system, if cointegration is present, is believed to improve long-horizon forecasts.Contrary to this belief, at long horizons nothing is lost by ignoring cointegration when the forecasts are evaluated using standard multivariate forecast accuracy measures.In fact, simple univariate Box-Jenkins forecasts are just as accurate.Our results highlight a potentially important deficiency of standard forecast accuracy measures-they fail to value the maintenance of cointegrating relationships among variables-and we suggest alternatives that explicitly do so.