Exploiting linear partial information for optimal use of forecasts: With an application to U.S. economic policy

Traditionally, the link between forecasting and decision making rests on the assumption of a known distribution for the future values of predicted variables. In practice, however, forecasts tend to offer little more than Linear Partial Information (LPI), typically of the form, ‘State 1 is more likely to prevail than state 2, and state 2 more likely to prevail than state 3, among five possible states’. This paper shows how such fuzzy LPI statements can be exploited in decision making. For an illustration, LPI analysis is used for determining (ex post) the optimal economic policy to be followed by the Carter Administration with a view to ensuring reelection in 1980. An optimal adaption of that policy occasioned by the fallible 1980 forecasts made by the Council of Economic Advisors is also derived.