In this article I analyze the role of cooperation between firm divisions in the budgeting process. I study a setting in which cooperation is a necessary condition for information sharing among division managers, which in turn benefits the principal. The results in this article can help reconcile the differing views between practitioners and academic researchers on the desirability of cooperation in the budgeting process. The results also have implications for some common budgeting processes observed in practice, including bundling budgeting and bottom‐up budgeting.

Using both a linear regression method and a probability-based method, we find that on average, analysts place larger than efficient weights on (i.e., they overweight) their private information when they forecast corporate earnings. We also find that analysts overweight more when issuing forecasts more favorable than the consensus, and overweight less, and may even underweight, private information when issuing forecasts less favorable than the consensus. Further, the deviation from efficient weighting increases when the benefits from doing so are high or when the costs of doing so are low. These results suggest that analysts' incentives play a larger role in misweighting than their behavioral biases.

[The article shows that two measures of the amount of private information in stock price-price nonsynchronicity and probability of informed trading (PIN)-have a strong positive effect on the sensitivity of corporate investment to stock price. Moreover, the effect is robust to the inclusion of controls for managerial information and for other information-related variables. The results suggest that firm managers learn from the private information in stock price about their own firms' fundamentals and incorporate this information in the corporate investment decisions. We relate our findings to an alternative explanation for the investment-to-price sensitivity, namely that it is generated by capital constraints, and show that both the learning channel and the alternative channel contribute to this sensitivity.]

Applying a difference-in-differences approach to explore variations in the timing of bank mergers in the U.S. over the last two decades, we document an increase in borrowers’ disclosure when their banks engage in mergers and acquisitions. The effect is stronger among borrowers more reliant on services from the merging banks and when mergers cause larger changes in banks’ monitoring and financing of borrowers. These findings suggest an information spillover effect from bank mergers to the public financial markets, and have implications for how changes in banking markets affect the availability of public disclosure in the stock markets.

[The average cash holdings of Chinese-listed firms decreased significantly after the split share structure reform in China, which specified a process that allowed previously nontradable shares held by controlling shareholders to be freely tradable on the exchanges. The reduction in cash holdings is greater for firms with weaker governance and firms facing more financial constraints prior to the reform. The reform also significantly reduced the average corporate savings rate, as measured by cash-to-cash-flow sensitivity. These findings are consistent with the premise that the reform removed a significant market friction, which led to better incentive alignment between controlling shareholders and minority shareholders and relaxed financial constraints. Additional analyses show that the reform affects firms' cash management policies, investment decisions, dividend payout policies, and financing choices differently in private firms than in state-owned enterprises.]

Using both a linear regression method and a probability-based method, we find that on average, analysts place larger than efficient weights on (i.e., they overweight) their private information when they forecast corporate earnings. We also find that analysts overweight more when issuing forecasts more favorable than the consensus, and overweight less, and may even underweight, private information when issuing forecasts less favorable than the consensus. Further, the deviation from efficient weighting increases when the benefits from doing so are high or when the costs of doing so are low. These results suggest that analysts' incentives play a larger role in misweighting than their behavioral biases.

Bayesian learning implies decreasing weights on prior beliefs and increasing weights on the accuracy of the analyst's past forecast record, as the number of forecast errors comprising her forecast record (its length) increases. Consistent with this model of investor learning, empirical tests show that investors’ reactions to forecast news are increasing in the product of the accuracy and length of analysts’ forecast records. Moreover, the Bayesian learning predicted by our model is more descriptive of investor reactions than is a static model which predicts that investors’ responses condition only on the prior accuracy of the analyst.