Finance, Risk-Taking and Growth: Evidence from New U.S. Firm-Level Data

财务、风险承担和增长：来自美国企业级新数据的证据

• 批准号: 2018623
• 负责人: Sebnem Kalemli-Ozcan
• 金额: $ 26.6万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2018623&HistoricalAwards=false
• 关键词: Finance; Risk; Taking; Growth; Evidence

AbstractSmall and medium-sized enterprises (SMEs) are vital contributors to an economy. These companies are not listed, have less than 500 employees and account for more than 90 percent of all the U.S. employer firms. Despite their importance, there is limited knowledge about financing and capital structure of these firms. SMEs are considered to be dependent on bank loans for their largest source of financing based on survey data but there is limited knowledge on financing channels of these firms from administrative data. As SMEs are subject to different financial constraints than public firms, financing and investment decisions of these firms have important implications for economic growth and investment at the aggregate level. This research provides a coherent roadmap for advancing the development of firm-level data sets involving private and public firms’ real and financial outcomes. The project will use new data to bring evidence on firm-level financial constraints and implications of these for aggregate economic outcomes. The project has broader impact in understanding the role of SMEs in the economy.The research focuses on econometric analyses of firm dynamics, financial frictions and growth. These types of analyses are important since models of financial frictions with firm heterogeneity are increasingly being embedded into full scale dynamic stochastic general equilibrium models that inform monetary policy. Empirical evidence is lacking on such models due to unavailability of financial data on small private firms. The models rely on full firm size distribution and lack of data on small firms’ financing patterns hinders taking these models to the data. Small firms are important for the aggregate outcomes. This project advances the knowledge in this area by linking granular firm level data on public and private firms and by exploring the implications of financing and investment decisions on economic outcomes for a large set of firms.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

摘要中小企业是经济的重要贡献者。这些公司没有上市，员工不到500人，占美国所有雇主公司的90%以上。尽管它们很重要，但人们对这些公司的融资和资本结构的了解有限。根据调查数据，中小企业被认为依赖银行贷款作为其最大的融资来源，但从行政数据中对这些企业的融资渠道的了解有限。由于中小企业受到的资金约束与上市公司不同，中小企业的融资和投资决策对总体经济增长和投资具有重要影响。这项研究为推进涉及私营和上市公司实际和财务成果的企业层面数据集的发展提供了一个连贯的路线图。该项目将使用新的数据来证明企业层面的财务约束及其对总体经济结果的影响。该项目对了解中小企业在经济中的作用具有更广泛的影响。研究重点是企业动态、金融摩擦和增长的计量经济学分析。这些类型的分析很重要，因为具有企业异质性的金融摩擦模型越来越多地被嵌入到为货币政策提供信息的全尺度动态随机一般均衡模型中。由于缺乏小型私营公司的财务数据，因此缺乏这种模型的经验证据。这些模型依赖于完整的企业规模分布，缺乏关于小企业融资模式的数据阻碍了将这些模型应用到数据中。小企业对总体结果很重要。该项目通过将公共和私营企业的细粒度企业层面数据联系起来，并通过探索融资和投资决策对大量企业经济成果的影响，推进了这一领域的知识。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。