The Politics of Forecast Bias: Forecaster Effect and Other Effects in New York City Revenue Forecasting




This paper examines the impact of forecasters, horizons, revenue categories, and forecast timing in relation to decision making on forecast bias or accuracy. The significant findings are: for the most part forecasters tend to report forecasts that are similar rather than competitive. Forecast bias (underforecasting) increases over longer horizons; consequently claims of structural budget deficit are suspect, as an assertion of structural deficit requires that a reliable forecast of revenue shows continuous shortfall compared with a reliable forecast of expenditures. There is an overforecasting bias in property tax, possibly reflecting demand for services. There is an underforecasting forecast bias in two revenue categories, all other taxes and federal categorical grants, resulting in a net total underforecasting bias for the city's revenue. There appears to be a period effect (forecasts in June are substantially biased), but this effect requires further study. The study suggests further examination of the bias associated with revenue categories, time within the budget cycle, and forecast horizon.