In this paper, digital transformation is included in the heterogeneity model of firms. Based on a general equilibrium analysis, we find that under the effect of diminishing marginal productivity, digital transformation does not always have a positive impact on firms’ markups, but has an “inverted U-shaped” nonlinear influence, which first promotes and then inhibits markups. Firm innovation and firm productivity are the key micro-mechanisms for the above effects to play a role. Based on the analysis of typical facts and empirical data of listed companies, the measurement test yields the following results. First, digital transformation can significantly improve firms’ markups when it is below a specific threshold value, but it will have a negative impact when it exceeds this value. That is, there is an “inverted U-shaped” nonlinear relationship between digital transformation and firms’ markups. Second, the heterogeneity analysis shows that digital transformation has a greater effect on the markups of state-owned firms, export firms and technology-intensive firms than on the markups of other firms. Third, digital transformation has an impact on firms’ markups through two key mechanisms: firm innovation ability and production efficiency. The quantitative empirical results confirm the correctness of the theoretical expectations. Therefore, firms need to grasp the strategic opportunities brought by the progress of digital technology and accelerate the process of promoting the digital transformation. Firms should make proper choices in the selection and arrangement of key areas, as well as avoid possible problems such as “too much”. In this way, we can better consolidate the micro foundation of China’s high-quality economic development.
The emerging literature suggests that the accounting information disclosed by micro-enterprises is useful for macro forecasting.Previous studies have mainly analyzed the relevance of aggregate accounting information for predicting macroeconomic indicators,such as future GDP growth,job creation and destruction,monetary policy,and inflation(Konchitchki and Patatoukas,2014a;Crawley,2015;Luo et al.,2016;Shivakumar and Urcan,2017;Rouxelin et al.,2018;Ma and Zhang,2020;Ye et al.,2020;Hann et al.,2021).However,little is known about the usefulness of aggregate accounting information in predicting meso-level indicators,especially the credit risk of the regional banking industry. The non-performing loan ratio is a leading indicator of an impending banking crisis(Reinhart and Rogoff,2011)and can effectively reflect a bank's risk status(Fang,2015).Thus,this paper investigates the predictive value of changes in aggregate Ponzi Interests for the growth of non-performing loans in commercial banks.This study uses data from publicly listed companies to construct a measure of firm Ponzi Interests,considering the primary repayment source and subsequently aggregating this measure to the provincial level.We measure Ponzi Interests by tracking the financial sources of firms'interest payments over an extended period and separating the component of total cumulative interest payments covered by financing cash inflows. Consistent with our conjecture,we find that changes in aggregate Ponzi Interests effectively predict the subsequent growth of non-performing loans in commercial banks.We observe a significantly positive association between changes in aggregate Ponzi Interests and the subsequent growth of non-performing loans in commercial banks at the provincial level.This relationship is attributed to the fact that our Ponzi Interests indicator reflects the reliability of a firm's primary repayment source.Firms with a deepening degree of Ponzi Interests will have a higher operating risk and likelihood of experiencing financial distress.Furthermore,the increase in non-performing loans in commercial banks is primarily driven by firms experiencing a deterioration in their financing capacity and asset profitability as well as firms lacking affiliations with banks.Moreover,the findings of a cross-sectional analysis reveal that the forecasting power of the aggregate Ponzi Interests indicator is more pronounced in provinces where Ponzi financing sustainability is poorer and banks have less incentive and ability to conceal non-performing loans. Our paper contributes to the literature in three aspects.First,it introduces an innovative approach by constructing a regional aggregate Ponzi Interests indicator based on the primary repayment source of firms.In addition,this study establishes the relationship between changes in aggregate Ponzi Interests and the subsequent growth of non-performing loans in commercial banks.By delving into enterprise cash flow and the ability to pay interest,our paper extends the research on the meso and macro predictive value of accounting information(Konchitchki and Patatoukas,2014a;Crawley,2015;Luo et al.,2016;Shivakumar and Urcan,2017;Rouxelin et al.,2018;Ma and Zhang,2020;Ye et al.,2020;Hann et al.,2021). Second,this paper enhances the literature on the prediction of firms'financial distress and default risk.Previous studies in this field have mainly focused on the predictive value of financial indicators(Altman,1968),short-term cashflow(Aziz et al.,1988),and market return(Beaver,1966)information.Our study provides evidence that the Ponzi Interests indicator based on long-term cash flow information can be effectively used to predict corporate default risk. This paper complements the literature on bank risk-taking determinants.We examine how accounting information about the reliability of a firm's primary repayment source influences a bank's passive risk-taking,thereby affecting changes in non-performing loans.Given that the literature has mainly focused on the effects of macroeconomic conditions and bank characteristics on banks'passive risk-taking,this paper provides additional insights from the perspective of firms acting as loan demanders. This paper has crucial policy implications and practical relevance.Our results suggest that aggregate Ponzi Interests derived from micro-enterprises'accounting data contain valuable information regarding future credit risk and expected credit losses associated with bank credit assets.These findings imply that regulators should consider the Ponzi Interests indicator to enhance their credit supervision.In addition,commercial banks should incorporate the Ponzi Interests indicator in their specific loan approval procedures and expected credit loss models.
已有丰富的文献考察了消费信贷对家庭消费和投资行为的影响,但少有研究关注其对家庭人力资本投资的影响.家庭人力资本投资对于人力资本积累、经济高质量发展至关重要.基于此,本文考察了信用卡使用对家庭人力资本投资的影响及其影响机制,主要发现如下:信用卡使用显著增加了家庭人力资本投资,且这一效应具有长期动态影响并对城市、高收入、高教育程度家庭影响更为显著,这意味着信用卡消费信贷可能会增加入力资本不平等.进一步研究发现,家庭会增加劳动力供给来应对人力资本支出的增加.机制分析表明,信用卡使用主要通过增加家庭消费投资、促进消费升级、缓解家庭预算约束三种途径促进家庭人力资本投资.在风险可控的前提下,引导消费信贷流向有利于实体经济发展的领域,可助力于消费升级与人力资本积累,从而为经济发展提供新动能.
并购重组中基于内幕信息的知情交易行为既是监管重点,也是学术界关注的热点问题.本文以2006-2020年我国上市公司并购重组事件为样本,考察并购重组前的知情交易行为对并购公告收益的影响.研究发现:并购重组前的知情交易行为引发了主并公司股价的提前反应,从而降低了并购公告时的市场反应,这一现象是由内幕信息泄露引起,且内幕信息主要来源于包括员工在内的公司内部人,而非机构投资者.进一步分析表明,改善信息环境可以有效缓解并购重组的信息泄露问题,体现为知情购买交易的信息泄露效应受到分析师跟踪、审计质量和问询函制度的有效制约.本文研究深化了现有的并购重组内幕交易行为研究,为实施精准监管和防范内幕交易等政策提供了一定参考和依据.
本文研究企业在披露业绩数据和文本数据的多元信息环境下,管理层借助语调偏离业绩策略进行信息操控是否会误导投资者决策,进而提升企业股价和收益率.通过构建反映语调偏离业绩程度的量化指标、引入投资者的交叉验证策略,本文检验了偏离策略对投资者决策和股票价格的影响.主要发现有三点:(1)多元信息环境下,散户投资者会借助交叉验证机制进行理性投资决策,语调偏离策略会造成股票价格下跌;(2)当业绩数据可信度下降时,机构投资者也将采用交叉验证机制,此时语调偏离策略将引致更为显著的股价下跌;(3)整体而言,语调偏离程度的扩大会导致短期股票收益的显著下降.上述发现表明,面对管理层语调偏离策略,投资者决策整体上仍然是理性的,该策略实际上会对短期股价收益造成消极影响,多元信息环境下资本市场有效性仍成立.
