The analysis highlights the impact of cointegration on macroeconomic forecasting, suggesting areas for improvement in accuracy.
Originally written in 1991 to advance the formal analysis of macroeconomic forecasting models and methods following the development of cointegration, alternative forecasting devices, conditional and unconditional forecasts, and data accuracy are considered. Macro‐econometric model forecasts, forecast errors, and forecast variances are described. Forecast comparisons using mean square errors are criticised, as is pooling disparate forecasts, which violates forecast encompassing. The non‐stationarity of economic data is discussed in terms of unit roots, stochastic trends, cointegration, technical progress, and regime shifts. Sources of forecast error are delineated, concluding with evaluating its recommendations.
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David F. Hendry (2025) studied this question.
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