We investigate the effect of tick size, a key feature of market microstructure, on managerial learning from stock prices. Using a randomized controlled tick-size experiment, the 2016 Tick Size Pilot Program, we find that a larger tick size increases a firm's investment sensitivity to stock prices, suggesting that managers glean more new information from stock prices to guide their investment decisions as the tick size increases. Consistently, we also find that changes in managerial beliefs, as reflected in adjustments of forecasted capital expenditures, respond more strongly to market feedback under a larger tick size. Additional evidence suggests the following mechanism through which tick size affects managerial learning: a larger tick size reduces algorithmic trading, in turn encouraging fundamental information acquisition. Increased fundamental information acquisition generates incremental information about growth opportunities, macroeconomic factors, and industry factors, with respect to which the market has a comparative information advantage over management.

Using U.S. Department of Justice (DOJ) data on corruption convictions of government officials, we study the effect of public corruption on analyst forecast quality. We find that analyst earnings forecasts for firms headquartered in more corrupt states are less accurate. Our results are robust to endogeneity checks and several alternative corruption measures. In our cross-sectional analysis, we find that the negative effect of corruption on analyst forecast accuracy is more pronounced in government contractor firms and firms with weaker internal governance or external monitoring. We further identify two channels through which corruption negatively influences analyst forecast accuracy: Firms in more corrupt states exhibit lower earnings quality and issue less frequent management guidance.