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Customer satisfaction and financial analysts earnings forecast errors

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SSRN-id1348272.pdf (281.7Kb)
Date
2009
Publisher city
Paris
Publisher
Université Paris-Dauphine
Collection title
Working Papers Chaire Finance d'entreprise Dauphine - FBF
Collection Id
2009-1
Dewey
Contrôle de gestion Comptabilité
Sujet
Multilevel Modelling; Customer Satisfaction; Financial Analysts; Forecast Errors
JEL code
M31; M41
URI
https://basepub.dauphine.fr/handle/123456789/3185
Collections
  • DRM : Publications
Metadata
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Author
Ramond, Olivier
Casta, Jean-François
Ngobo, Paul Valentin
Type
Document de travail / Working paper
Item number of pages
48
Abstract (EN)
This paper examines the relevance of customer satisfaction for the financial analysts when preparing their earnings forecasts. We draw on theory in marketing to predict how customer satisfaction should be associated with earnings forecasts and forecast errors. We assembled a dataset of companies studied in the American Customer Satisfaction Index - ACSI (University of Michigan), which also appear on the Institutional Brokers Estimate System (I/B/E/S) files. We control for factors known to influence the earnings forecasts, such as firm profitability and risk, as well as potential unobservable factors using a Mixed-effects regression. We find that customer satisfaction has a negative association with the analysts’ forecast errors. More specifically, both levels and changes in ACSI are associated with higher levels of Actual Earnings per Share (EPS) and higher levels of analysts’ earnings forecasts, making the analysts’ forecasts to be closer to the business reality. The robust impact of customer satisfaction on forecast earnings and errors suggests that analysts who undervalue customer satisfaction information may deprive themselves of an important proxy of non-financial information.

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