我国商业信用再配置的动机检验及其治理效应分析——来自上市公司信贷漏损的证据
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  • 英文篇名:The Motivaion of Trade Credit Redistribution and Governance Effect:Evidence from the Credit Leakage of the Chinese Listed Companies
  • 作者:于博 ; 植率
  • 英文作者:YU Bo;ZHI Shuai;School of Economics,Tianjin University of Finance & Economics;
  • 关键词:商业信用 ; 信贷漏损 ; 信贷再配置 ; 供应链 ; 供应商 ; 货币政策 ; 创新投资
  • 英文关键词:trade credit;;credit leakage;;credit redistribution;;supply chain;;supplier;;monetary policy;;innovation investment
  • 中文刊名:SONG
  • 英文刊名:Journal of Guangdong University of Finance & Economics
  • 机构:天津财经大学经济学院;
  • 出版日期:2017-07-28
  • 出版单位:广东财经大学学报
  • 年:2017
  • 期:v.32;No.153
  • 基金:教育部人文社会科学基金青年项目(14YJC630174)
  • 语种:中文;
  • 页:SONG201704006
  • 页数:12
  • CN:04
  • ISSN:44-1711/F
  • 分类号:59-70
摘要
以2008年~2014年A股制造业上市公司为样本,以供应商进行商业信用再配置信贷漏损行为为视角,证明了商业信用供给并非供应商根据自身信贷优势主动实施的逐利行为,而是在买方市场条件下因客户占据强势地位被动进行的授信行为,是强势买方对供应商实施的信用侵占;其次,证明了宽松的货币政策有助于降低强势买方的信用侵占意愿,弱化被动性再配置水平,即货币政策作为宏观调控手段具有缓解微观厂商之间商业信用侵占的能力;最后,证明了技术创新可以通过强化供应商产品市场竞争力来帮助其摆脱强势买方的商业信用侵占,进而降低被动性再配置水平,即鼓励企业实施创新驱动战略对扭曲型信贷漏损具有治理意义。
        Using a panel data of Chinese manufacturing firms over the period of 2008-2014,the paper makes a revisit on the motivation of trade credit redistribution from the perspective of supply chain relationship and finds that: trade credit extension is compulsively driven by buyer power rather than spontaneously driven by arbitrage motive; redistribution effect will increase with customer concentration only in tight monetary policy,which means that tight monetary policy has a positive impact on the degree of involuntary redistribution of trade credit; only for firms with lower R&D expenditure,the redistribution effect will increase with customer concentration,which means that investment in innovation will contribute to suppliers' competition ability,and in return it will hedge the buyer power and reduce compulsive provision. This finding introduces the innovation investment into the framework of efficiency analysis of capital reallocation.
引文
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    (1)模型(1)中“核心变量”及“控制变量”的具体定义及计量方式参见表1。
    (2)参照陆正飞和杨德明(2011)[35]的方法,计算得到2008年~2014年各季度的MP(M2增长率-GDP增长率-CPI增长率),该值表示货币政策的相对松紧水平。定义虚拟变量MP,将上述计算值最大的3年设定为货币政策宽松期(MP=1),最小的4年设定为货币政策紧缩期(MP=0)。根据计算结果,2008年~2014年的前3年为货币政策宽松期,后4年为货币政策紧缩期。
    (1)在创新投资的分组设计方面,本文以“研发支出/销售收入”来计算创新投资水平(Inno),并在此基础上定义虚拟变量InnoD ummy:当Inno大于行业均值时,InnoD ummy赋值为1,代表高创新投资分组;否则为0,代表低创新投资分组。
    (2)其来源参见Almeida等(2007)[39]。
    (1)时间截至2011年是为了保证每个样本企业的样本量大于3年。

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