"Forecasting in the Presence of Structural Breaks and Policy Regime Shifts"
	
David F. Hendry
Nuffield College, Oxford OX1 1NF, UK.

and

Grayham E. Mizon
Economics Department, Southampton University, UK
	

Abstract: The value of selecting the best forecasting model as the basis for
empirical economic policy analysis is questioned.  When no model coincides with 
the data generation process, non-causal statistical devices may provide the
best available forecasts: examples from recent work include intercept 
corrections and differenced-data VARs.  However, the resulting models need 
have no policy implications.  A 'paradox' may result if their forecasts induce 
policy changes which can be used to improve the statistical forecast.  This 
suggests correcting statistical forecasts by using the econometric model's estimate
of the 'scenario' change, and doing so yields reduced biases.