Herd behavior in voluntary disclosure decisions: An examination of capital expenditure forecasts
Herd behavior in voluntary disclosure decisions: An examination of capital expenditure forecasts
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Date
2005-06-09
Authors
Brown, Nerissa Christine
Advisor
Gordon, Lawrence A.
Wermers, Russell R.
Wermers, Russell R.
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Abstract
This study documents behavior consistent with herding in voluntary disclosure decisions and investigates two possible reasons for this phenomenon. Based on theories of social learning and rational herds, herding in disclosure decisions may be due to managers' use of information reflected in the past disclosure decisions of other firms (informational herding), and/or managers' incentives to maintain or build a good reputation with investors (reputational herding). Employing a duration model for repeated events, I analyze the timing of capital expenditure forecasts for a broad sample of disclosing and nondisclosing firms. Results show that a firm's propensity to release capital expenditure forecasts is positively associated with the proportion of prior disclosing firms within its industry, thus, supporting arguments of herding. This association is significantly higher for less capital-intensive firms and firms operating in highly competitive industries which suggests that incentives to herd are greater for firms facing relatively high competition. To further distinguish between informational and reputational herding, I investigate whether the tendency to herd varies with the content and precision of other firms' forecasts, and with the level of managerial reputation. As predicted, I find that a firm's propensity to disclose increases with the precision of peer firms' forecasts and when peer forecasts signal a decrease in capital expenditures. Also, I find that herding is greater for managers that are comparably less reputable. Overall, the results confirm the existence of herd behavior in capital expenditure forecast decisions and that the behavior is driven partly by informational and reputational incentives. Extensive sensitivity analyses confirm the robustness of these results.