Quantifying Qualitative Survey Data: New Insights on the (Ir)Rationality of Firms' Forecasts

Abstract

Using a novel dataset that contains qualitative firm survey data on sales forecasts as well as balance-sheet data on realized sales, we document that only major forecast errors are predictable and display autocorrelation. This result is a particular violation of the Full Information Rational Expectations hypothesis that requires explanation. In contrast, minor forecast errors are neither predictable nor autocorrelated. To arrive at this result, we develop a novel methodology to quantify qualitative survey data on firm forecasts. It is generally applicable when quantitative information, e.g. from balance sheets, is available on the realization of the forecasted variable. Finally, we provide a model of rational inattention that explains our empirical results. Firms optimally limit their degree of attention to information when operating in market environments where information processing is more costly. This results in major forecast errors that are predictable and autocorrelated.