A Quantitative Analysis of Distortions in Managerial Forecasts

This paper quantifies the economic costs of distortions in managerial forecasts. We match a business survey run by the Bank of Italy with administrative data on firms’ balance sheets and income statements. The resulting dataset allows us to observe a long panel of managerial forecast errors for a representative sample of Italian firms with at least 20 employees. We show that managerial forecast errors are positively and significantly autocorrelated. This persistence of forecast errors is consistent with managerial underreaction to new information. To quantify the economic significance of this forecasting bias, we estimate a dynamic equilibrium model with heterogeneous firms and distorted expectations. The estimated model matches not only the persistence of forecast errors, but also the empirical link between investment and managerial forecasts. Compared with a counterfactual with rational expectations, we find that managers exhibit large forecasting biases, which lead to significant distortions in firm-level investment. These distortions, however, imply limited loss in firm value. In general equilibrium, the estimated model leads to negligible aggregate efficiency losses from distorted forecasts