Discretionary databases in forecasting

Abstract Information for forecasting databases is often initially under the control of individuals who have no compelling reason to contribute, and who face various significant costs if they do. Such discretionary databases are subject to public goods problems, and are likely to be undersupplied, even when all participants agree that the overall benefits outweigh the overall costs. This paper explores the implications of this incentive structure for the existence, completeness and accuracy of forecasting databases. It also offers some hypotheses as to when the difficulties will be more and less severe, and outlines some directions for possible remedial strategies.