English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 56568/90363 (63%)
造訪人次 : 11872293      線上人數 : 78
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/92551

    題名: Corporate Governance, Earnings Management, and Firm Performance: An Endogenous Switching Regression Model
    作者: Tang, Hui-wen;Chang, Chong-Chuo
    貢獻者: 淡江大學保險學系
    日期: 2011-09-26
    上傳時間: 2013-10-18 12:28:42 (UTC+8)
    摘要: This paper employs an endogenous switching regression model (ESRM) to investigate the relation between earnings management and firm performance under different governance status. We find that both discretionary accruals (DA) and discretionary current accruals (DCA) have a significantly negative impact on ROA and Tobin’s Q for firms classified as into a weak governance regime. The results imply that these firms suffer severe agency problems and information asymmetry. Thus, corporate managers of the regime are likely to window dress earnings through accounting discretion, resulting in a reversal of operating performance and stock returns in subsequent periods. On the contrary, we find that DA and DCA are positive and significant associated with ROA and Tobin’s Q in the strong governance regime. These findings imply that the managers of a strong governance firm would select accounting policies that best reflect economic events, transactions and cash-flow. Therefore, the choice of accounting method under good corporate governance does not harm firm performance but increase firm value. It is also interesting to note that managers prefer to use DCA to window dress financial figures than DA, leading to a more serious reversal of firm value in the next period.
    關聯: World Business, Economics and Finance Conference
    顯示於類別:[風險管理與保險學系] 會議論文





    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回饋