东北大学学报(社会科学版) ›› 2015, Vol. 17 ›› Issue (4): 390-397.DOI: 10.15936/j.cnki.1008-3758.2015.04.010

• 政治与公共管理研究 • 上一篇    下一篇

公众行贿意愿研究来自G省的调查数据

孙宗锋1,高洪成2   

  1. (1.中山大学政治与公共事务管理学院,广东广州510275;2.东北大学文法学院,辽宁沈阳110819)
  • 收稿日期:2015-03-18 修回日期:2015-03-18 出版日期:2015-07-25 发布日期:2015-11-10
  • 通讯作者: 孙宗锋
  • 作者简介:孙宗锋(1988-),男,山东临沂人,中山大学博士研究生,主要从事政府绩效评估与组织管理研究;高洪成(1978-),男,河北唐山人,东北大学副教授,管理学博士,主要从事政府绩效评估与科技政策研究。
  • 基金资助:
    国家社会科学基金重大资助项目(13&ZD011);辽宁省社会科学规划基金重点资助项目(L12AWJ003);教育部人文社会科学研究青年基金资助项目(11YJC810011)。

Study on the Publics Willingness to Pay BribesBased on the Survey Data of G Province

SUN Zong-feng1, GAO Hong-cheng2   

  1. (1. School of Government, Sun Yat-sen University, Guangzhou 510275, China; 2. School of Humanities & Law, Northeastern University, Shenyang 110819, China)
  • Received:2015-03-18 Revised:2015-03-18 Online:2015-07-25 Published:2015-11-10
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摘要: 长期以来,学术界对公众行贿导致公职人员腐败的实证研究乏善可陈。基于G省2014年公众腐败感知的问卷调查统计发现,为了办事方便,有30%~44%的公众愿意向公职人员行贿。试图从腐败容忍度、腐败感知程度和腐败经历三个维度来解释个体行贿意愿之间的差异。通过聚类Logit回归模型研究发现,在其他条件不变的情况下,腐败容忍度越高,公众行贿的几率越高;感知到的腐败程度越高,公众行贿的几率就越高;腐败经历显著地提高了公众的行贿几率。

关键词: 腐败感知, 腐败容忍, 腐败经历, 行贿意愿, 聚类Logit回归

Abstract: For a long time, there has been a scarcity of research on officials corruption due to the publics bribing. Based on a survey of G Province in 2014, it was found that for the sake of convenience in conducting business with the government, 30% to 44% people would like to pay bribes. To explore the differences of individuals willingness to pay bribes, three dimensions including corruption tolerance, corruption perception and past corruption experience were constructed. An analysis of the logit regression model found that all the other factors being equal, the higher the publics corruption tolerance is, the more likely they are to pay bribes; the more corruptions the public perceive, the more likely they are to pay bribes; and those who have more corruption experiences are more likely to pay bribes than those not.

Key words: corruption perception, corruption tolerance, corruption experience, willingness to pay bribes, logit regression model

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