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題名:The Impact of Reporting Goodwill and Impairments on the Market's Anticipation of Future Earnings
書刊名:臺大管理論叢
作者:林修葳 引用關係王全三 引用關係
作者(外文):Lin, Hsiou-weiWang, Chuan-san
出版日期:2015
卷期:25:2
頁次:頁23-52
主題關鍵詞:商譽公允價值會計盈餘反應係數FERCGoodwillFair value accountingFuture or Forward Earnings Response Coefficients
原始連結:連回原系統網址new window
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  • 被引用次數被引用次數:期刊(2) 博士論文(0) 專書(0) 專書論文(0)
  • 排除自我引用排除自我引用:2
  • 共同引用共同引用:0
  • 點閱點閱:11
本研究探討企業報導商譽及減損對資本市場預測併購者未來損益之影響。本研究使用未來盈餘反應係數(FERC)衡量資本市場預測未來損益之能力。依據Collins, Kothari, Shanken, and Sloan(1994),盈餘反應係數是當期股票報酬率與次期盈餘之間的迴歸係數。以公允價值報導商譽,將使併購者以公允價值分攤併購價格至取得之可辨認資產,並將併購效益之經濟租揭露為商譽。定期減損測試則代表併購者持續更新取得併購資產之公允價值,使可辨認資產折舊費用與公允價值相連結,可讓市場參與者自財務報表中獲得較攸關之損益資訊。我們的研究結果提出與上述論述一致的可靠證據,支持使用公允價值衡量商譽及減損之會計處理,能提供有用的財務資訊。
We investigate the effect of reporting goodwill and impairments on the stock market's ability to predict acquirers' future earnings, as captured by the Future Earnings Response Coefficient (FERC). Based on Collins, Kothari, Shanken, and Sloan (1994), the FERC is the association between current-year stock returns and next-year corporate earnings. Reporting goodwill reveals economic rents expected by the acquirers when they allocate purchase prices among purchased assets. This allocation assigns fair value to the book of identifiable assets acquired in business combinations. Periodical impairment tests update the fair value information. The information enables market participants to match post-merge revenue with depreciation expenses of the identifiable assets. Our results show robust evidence consistent with this argument, supporting the usefulness of fair value accounting for goodwill and impairments.
期刊論文
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17.Hayn, C.(1995)。The information content of losses。Journal of Accounting and Economics,20(2),125-153。  new window
18.Collins, D. W.、Kothari, S. P.、Shanken, J.、Sloan, R. G.(1994)。Lack of Timeliness and Noise as Explanations for the Low Contemporaneous Return-Earnings Association。Journal of Accounting and Economics,18(3),289-324。  new window
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圖書
1.Wooldridge, Jeffrey M.(2001)。Econometric Analysis of Cross Section and Panel Data。Cambridge, MA:Massachusetts Institute of Technology Press。  new window
 
 
 
 
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