Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Based on a large international panel of surveyed GDP forecasts I analyze the frequency of forecast revisions and the factors that influence the likelihood of forecast revisions. I find that each month on average 40%–50% of forecasters revise their forecasts. In addition, I find that the likelihood of forecast revisions significantly depends on a number of factors such as the forecast horizon, the business-cycle, or strategic interactions between forecasters. My results suggest that a realistic modeling of expectations/forecasts of agents has to take into account cross-sectional heterogeneity, strategic interaction between agents, and effects of the economic environment—features that existing models such as the sticky information framework are missing.