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维护金融市场稳定、防控金融风险是我国经济建设的重要内容。基于Gelfand et al.(2006)提出的文化遵从度理论框架，本文以2008—2019年中国A股上市公司为样本，从股价崩盘风险的视角，探究了非正式制度对金融市场稳定的影响。研究发现：公司所在地的文化遵从度对公司未来股价崩盘风险存在显著影响，当地文化遵从度越高，公司的股价崩盘风险越低。进一步发现：(1)提高信息质量和选择四大审计，是文化遵从度影响公司股价崩盘风险的主要机制；(2)区分文化遵从度的作用强度后，文化遵从度对股价崩盘风险的影响在成立年限长、高管不具有海外经历的公司表现得更强烈；(3)结合公司治理的其他机制，在公司内外部治理机制较弱时，文化遵从度发挥了较强的治理作用；(4)比较公司所在地的文化遵从度与高管籍贯所在地，公司所在地的文化遵从度具有更强的影响作用，表明文化遵从度能够对个体产生“同化”影响。本文的研究揭示了非正式制度对公司股价崩盘风险的重要影响，对于维护金融市场的稳定、防范金融风险，具有一定的理论和现实启发。
Abstract：Maintaining the stability of the financial market and preventing and controlling financial risks are important contents of China's economic construction. Based on the theoretical framework of cultural tightness proposed by Gelfand et al.(2006), this paper uses the sample of Chinese A-share listed firms from 2008 to 2019, exploring the impact of informal institutions on financial market stability from the perspective of stock price crash risk. We find that the regional cultural tightness has a significant impact on the firm's future stock price crash risk. The higher the cultural tightness is, the lower the risk of stock price crash is. Further findings are as follows. First, improving information quality and choosing the Big 4 audits are the main mechanisms for cultural tightness to affect the risk of stock price crash. Second, after analyzing the effect strength of cultural tightness, the impact of cultural tightness on the firms' stock price crash risk is mainly reflected in older firms and firms whose managers do not have overseas experiences. Third, considering other mechanisms of corporate governance, the association between cultural tightness and future stock price crash risk is stronger when the firm's governance mechanisms are weaker. Last, comparing the cultural tightness of the firm's location with that of the manager's hometown shows that the association between cultural tightness of the firm's location and future stock price crash risk is stronger. It shows cultural tightness has “assimilation” effect on individuals. This paper reveals the important impact of informal institutions on the stock price crash risk, and has important theoretical and practical significance for preventing financial risks and maintaining the stability of financial markets.
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(1)Callen and Fang(2015)从非正式制度的角度探究了宗教传统对上市公司股价崩盘风险的影响。Callen and Fang(2015)认为宗教作为一套社会规范,有助于抑制管理者囤积负面消息的行为,研究发现公司所在地的宗教虔诚程度越高,公司的未来股价崩盘风险越低,并且当公司治理机制较弱时,宗教传统可以替代传统的治理机制来监督公司的信息管理活动。本文则关注非正式制度的不同维度——社会规范的强度,探究文化遵从度对公司未来股价崩盘风险的影响。
(2)Hofstede(Hofstede,1980;Hofstede et al.,1990)提出的五个文化维度:集体主义与个人主义(Collectivism and Individualism)、权力距离(Power Distance)、不确定性规避(Uncertainty Avoidance)、男性气质与女性气质(Masculinity and Feminity)和未来导向(Long term/ Short term Orientation)。Schwartz(1994)提出的六个文化维度:自主性(Autonomy)、保守性(Conservatism)、平等性(Egalitarianism)、层级性(Hierarchy)、和谐性(Harmony)和控制性(Mastery)。
(3)Chua et al.(2019)进行了为期3年的调查,沿用Gelfand et al.(2011)构建的文化遵从度调查量表,在2014年3月、2017年4月和2017年7月三个不同的时间点发放了三轮调查问卷,收集了11662名被调查者的数据,测度了中国各省份的文化遵从度水平。具体的调查内容包括以下6个项目:(1)在本地区,有很多社会规范需要遵守;(2)大多数情况下人们很清楚应该如何作为;(3)大多数情况下大家对什么是妥当或者不妥当的行为有很大程度的共识;(4)大多数情况下人们可以充分地自由决定作为;(5)如果有人在做出不妥的违规行为会受到来自其他人的强烈的反对;(6)人们几乎总是会遵守社会规范(其中,“社会规范”是指一些没有被明文规定的社会行为标准)。(Chua et al.(2019)详细说明调查细节的文档链接:https://www.pnas.org/doi/suppl/10.1073/pnas.1815723116.)
(4)R1_Cul_Tight、R2_Cul_Tight、R3_Cul_Tight分别是只使用第一轮(4863个被调查者数据)、第二轮(3304个被调查者数据)和第三轮(3495个被调查者数据)调查数据形成的文化遵从度。A1_Cul_Tight、A2_Cul_Tight、A3_Cul_Tight分别是只使用年龄小于30岁(5263个被调查者数据)、大于等于30岁但小于50岁(5902个被调查者数据)、大于或等于50岁的被调查者数据(497个被调查者数据)形成的文化遵从度。
(5)使用第三轮调查数据形成的文化遵从度(R3_Cul_Tight)相对较小。同时,参考Chua et al.(2019),本文对文化遵从度的数据进行了标准化的处理(Z-Score),并加3得到最终数值,因此不同计算方式形成的文化遵从度指标的均值(mean)为3,标准差(sd)为1。
(6)此处的文化遵从度的描述性统计结果是公司层面的,由于不同年度不同地区公司数量的不同,具体的描述性统计结果与表2的 Panel A的省级结果有所不同。
(7)本文认为,产生这一结果可能有两方面原因:第一,年龄大于等于50岁的被调查者数据较少,只有497个被调查者数据,由此形成的文化遵从度可能不够准确;第二,这个年龄段包含大于等于60岁的被调查者数据,而年龄大于等于60岁的人群使用互联网的比例较低,因此对这个年龄段进行线上问卷调查形成的结果可能有偏。
(8)单独使用不同轮次的调查数据生成的文化遵从度指标尽管没有全部得到显著的结果,但大多数的结果支持了本文的研究假设,可以在一定程度上证明文化遵从度指标的稳定性。
(9)Chua et al.(2019)指出,地区的资源越匮乏,人们面临的生存威胁越大时,更倾向于通过严格的规制约束个体的行为,从而增强抵御生存风险的能力;同时,文化遵从度越高,地区的城市化水平越高。以上两点都能够支持地区人口密度与文化遵从度的正相关关系。一方面,人口密度越高,地区的人均资源越少,生存压力越大;另一方面,在中国,城市化水平越高的地区,人口通常也越密集。
(10)在模型(6)中,Invest为新增投资,计算方式为Invest=(构建固定资产、无形资产及其他长期资产的支出+取得子公司及其他营业单位支付的现金净额-处置固定资产、无形资产和其他长期资产收回的现金净额-折旧)/资产总额。Growth是公司的营业收入增长率;Lev是资产负债率;Cash是现金及现金等价物除以总资产;Age是公司的上市年限;Size是公司规模;Return是公司的股票年度回报率,使用考虑现金红利再投资的年个股回报率进行度量。
(11)实际税率(ETR)具体的计算方式为:(所得税费用-递延所得税费用)/息税前利润。参考已有研究,剔除了税前利润总额小于等于0,实际税率大于1或小于0的样本。参考梁上坤等(2020),过度投资水平和避税程度,本文均取未来一期的值进行回归。
(12)其中,TCAi,t是公司在t年的流动性应计,TCAi,t=流动资产变化量-现金流变化量-流动负债变化量+短期借款变化量。CFOi,t-1、CFOi,t和CFOi,t+1分别是公司在前一年、当年和未来一年的经营活动现金流量净额。对模型进行分年度和行业的回归,得到回归的残差的绝对值为公司的盈余质量。
(13)信息透明度(Trans)的度量,将考评结果A、B、C、D分别赋值为4、3、2、1。
(14)分析师跟踪的分组回归结果与上述发现一致,限于篇幅未报告。
(15)高管籍贯所在地的数据有较多缺失,因此回归样本与前文存在差异。
基本信息:
DOI：
中图分类号:F832.51;G122
引用信息:
[1]梁上坤,张文婷,卢闯.文化遵从度与金融市场稳定——基于股价崩盘风险的视角[J].经济学报,2024,11(03):126-163.
基金信息:
国家自然科学基金面上项目（72272164、71872196）; 国家社会科学基金重大项目（23&ZD060、21&ZD145、19ZDA098）; 中央财经大学科研创新团队计划的资助