Robustifying Forecasts from Equilibrium-Correction Models
In a non-stationary world subject to structural breaks, where model and mechanism differ, equilibrium-correction models are a risky device from which to forecast. Equilibrium shifts entail systematic forecast failure, and indeed forecasts will tend to move in the opposite direction to the data. A new explanation for the empirical success of second differencing is proposed. We consider model transformations based on additional differencing to reduce forecast-error biases, as usual at some cost in increased forecast-error variances. The analysis is illustrated by an empirical application to narrow money holdings in the UK.
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