To make high-quality research more accessible and easier to explore.

Fields:
2 results

Performance Targets and Ex Post Incentive Plan Adjustments†

Contemporary Accounting Research 2022 39(2), 863-892
ABSTRACT Performance evaluations are typically based on a formula that specifies in advance all performance measures, their relative incentive weights, and targets to be met. However, beginning‐of‐year performance targets can become outdated due to unforeseen events that call for ex post adjustments to formula‐based incentive plans to restore incentives. We discuss three types of ex post incentive plan adjustments—end‐of‐year subjective performance evaluation, changes in next‐year relative incentive weights, and changes in next‐year performance targets—and empirically examine the extent to which they are used to discourage failure to meet a target by a wide margin. Specifically, we use 2004–2015 data on formula‐based bonus plans, subjective performance evaluations, and performance in Korean state‐owned enterprises. Consistent with our predictions, we find that very low performance relative to target is associated with (i) low subjective evaluations and (ii) an increase in next‐year incentive weights, conditions that render areas with poor performance more important in future evaluations. These findings are more pronounced on performance dimensions of high importance and less pronounced when very low performance is due to an adverse uncontrollable shock. Finally, we find evidence that ex post incentive plan adjustments are associated with future performance improvements. Combined, our findings suggest that ex post incentive plan adjustments can be used to strengthen incentives when performance targets get outdated.

Information aggregation to form earnings expectations: Evidence from CEO networks and management forecast accuracy

Contemporary Accounting Research 2024 41(2), 1000-1030 open access
Abstract We investigate whether a larger CEO employment network provides access to information that improves firms' earnings forecasts and find a significantly positive relation between CEO employment network size and management earnings forecast accuracy. Our results suggest that firms use information obtained from CEO contacts to increase the accuracy of their earnings forecasts. Our conclusion is further supported by evidence of positive associations between CEO employment network size and the likelihood, frequency, and precision of management earnings forecasts. We also find that CEO employment network size is positively related to analysts' reactions to the forecast news and the accuracy of management earnings forecasts relative to analyst forecasts. Overall, our results are consistent with a larger CEO employment network generating external information that increases the accuracy of firms' earnings forecasts.