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Cost Behavior and Analysts’ Earnings Forecasts

The Accounting Review 2010 85(4), 1441-1471
This study examines how firms’ asymmetric cost behavior influences analysts’ earnings forecasts, primarily the accuracy of analysts’ consensus earnings forecasts. Results indicate that firms with stickier cost behavior have less accurate analysts’ earnings forecasts than firms with less sticky cost behavior. Furthermore, findings show that cost stickiness influences analysts’ coverage priorities and investors appear to consider sticky cost behavior in forming their beliefs about the value of firms. This study integrates a typical management accounting research topic, cost behavior, with three standard financial accounting topics (namely, accuracy of analysts’ earnings forecasts, analysts’ coverage, and market response to earnings surprises).

Do Earnings Targets and Managerial Incentives Affect Sticky Costs?

Journal of Accounting Research 2013 51(1), 201-224 open access
This study explores motivations underlying managers’ resource adjustments. We focus on the impact of incentives to meet earnings targets on resource adjustments and the ensuing cost structures. We find that, when managers face incentives to avoid losses or earnings decreases, or to meet financial analysts’ earnings forecasts, they expedite downward adjustment of slack resources for sales decreases. These deliberate decisions lessen the degree of cost stickiness rather than induce cost stickiness. The results suggest that efforts to understand determinants of firms’ cost structures should be made in light of the managers’ motivations, particularly agency‐driven incentives underlying resource adjustment decisions.

Extracting Forward-Looking Information from Security Prices: A New Approach

The Accounting Review 2008 83(4), 1101-1124
This paper proposes a new index to extract forward-looking information from security prices and infer market participants’ expectations of future earnings. The index, called market-adapted earnings (MAE), utilizes stock returns and fundamental accounting signals to estimate market expectations of future earnings at the firm level. MAE outperforms time-series models (e.g., random-walk) in predicting future earnings. Results demonstrate the usefulness of MAE for firms that have no analyst following.