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Management earnings forecast decisions in a regulated regime : evidence from China

Since 2000, China has required publicly listed firms to issue management earnings forecasts when they expect extreme changes in earnings or are likely to become loss-making. This study examines managers’ forecast decisions under this unique regulatory environment. I find an increase over time in the proportion of firms issuing voluntary earnings forecasts when they do not expect extreme changes in their earnings or losses. I also find an improvement in the quality—in terms of the precision, accuracy and bias—of both mandatory and voluntary forecasts over time. Further detailed analysis shows that the introduction of the regulation on management earnings forecasts is one of the underlying forces driving firms’ decisions to provide voluntary earnings forecasts. Specifically, I find that a firm is more likely to issue a voluntary forecast if the firm was required by regulation to issue an earnings forecast in the previous year. Peer pressure also explains firms’ decisions to issue voluntary forecasts. I then investigate the reasons underlying the improvement in the quality of management earnings forecasts. I find that learning effects and peer pressure are the driving forces behind the improvement. Specifically, I find that the forecasts issued by more experienced firms are more specific, accurate and conservative. Furthermore, the quality of a firm’s forecast is positively related to the quality of its peer firms. Overall, my results show that requiring some listed firms to issue management earnings forecasts in China might have built up a momentum that has promoted the issuance of voluntary forecasts and improved the quality of forecasts over time.

Identiferoai:union.ndltd.org:ln.edu.hk/oai:commons.ln.edu.hk:fin_etd-1011
Date25 August 2015
CreatorsYANG, Jingyu
PublisherDigital Commons @ Lingnan University
Source SetsLingnan University
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceTheses & Dissertations

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