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Implications of Cost Behavior for Analystss Earnings Forecasts

Authors: Mustafa Ciftci; Raj Mashruwala; Dan Weiss;

Implications of Cost Behavior for Analystss Earnings Forecasts

Abstract

ABSTRACT Recent work in management accounting offers several novel insights into firms' cost behavior. This study explores whether financial analysts appropriately incorporate information on two types of cost behavior in predicting earnings—cost variability and cost stickiness. Since analysts' utilization of information is not directly observable, we model the process of earnings prediction to generate empirically testable hypotheses. The results indicate that analysts “converge to the average” in recognizing both cost variability and cost stickiness, resulting in substantial and systematic earnings forecast errors. Particularly, we find a clear pattern—inappropriate incorporation of available information on cost behavior in earnings forecasts leads to larger errors in unfavorable scenarios than in favorable ones. Overall, enhancing analysts' awareness of the expense side is likely to improve their earnings forecasts, mainly when sales turn to the worse. JEL Classifications: M41; M46; G12.

Keywords

cost stickiness, cost variability, analysts’ earnings forecasts, expense forecasts, jel: jel:M41, jel: jel:G12

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
56
Top 10%
Top 10%
Average
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