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Small Business Programs, Innovation, and Growth: Estimating Policy Effects Using Comprehensive Firm-Level Panel Data

小型企业计划、创新和增长：使用综合的企业级面板数据估计政策效果

基本信息

批准号：
1719201
负责人：
John Earle
金额：
$ 38.28万
依托单位：
George Mason University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-07-01 至 2022-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1719201&HistoricalAwards=false
关键词：
Small Business Programs Innovation Growth

项目摘要

This project investigates the growth of start-ups and young firms, which are generally believed to be the most important job-creators, and evaluates the probability of becoming a high-growth productivity leader in an industry. The project provides direct measures of innovation and research and development (R&D), firm-level labor and total factor productivity, the dispersion of firm productivity and performance, the growth of high- vs. low-productivity entrants and incumbents, and exit rates of under-performing firms. With a specific focus on the Small Business Administration (SBA) 7(a) and 504 loan facilities, the analysis provides evidence on the importance of financial constraints, and the degree to which they may be attenuated by major government programs. The results will shed light not only on direct program impacts but also consider the indirect effects on productivity-enhancing reallocation of resources. In particular the central issue as to whether the policy intervention promotes growth of productive but financially constrained businesses, or instead sustains low-productivity firms that should release their resources to superior uses. The results have policy implications for the growth, innovation, and productivity of the U.S. economy. The project relies on new concepts, methods, and data for estimating the effects of financial access and small business programs. Conceptually, the project draws on models of firm dynamics to analyze innovation as the result of experimentation by entrants and incumbents, thus as part of the creative destruction process. A fundamental insight is that the full distribution of outcomes is useful for revealing innovation, as experimentation raises dispersion and selection raises skewness. The empirical methods include a credible identification strategy based on panel-matching and instrumental variables capturing geographic variation in SBA loan access. Estimation includes not only average treatment effects for productivity and innovation measures but also other moments of the outcome distribution: overall dispersion and skewness, performance at top percentiles, and allocation and selection effects that work through growth and exit at different points in the distribution. The methods provide an original way to assess the impact of a government intervention on productivity-enhancing reallocation. The data work links SBA administrative data with Census Bureau universal data on all U.S. employers. Variables from the Business Register, Census of Manufacturers, and Annual Survey of Manufacturers are added to measure productivity. Linking to the new Annual Survey of Entrepreneurs permits direct measurement of innovation and R&D effort. The conceptual approach, identification strategy, methods of analysis, and data development of this project should have positive externalities for other research including the evaluation of other programs in the U.S. and around the world.

本项目调查被认为是最重要的就业创造者的初创企业和年轻企业的成长情况，并评估成为行业中高增长生产率领导者的可能性。该项目提供了创新和研发（R D）、企业层面劳动和全要素生产率、企业生产率和业绩的分散、高生产率与低生产率进入者和在位者的增长以及业绩不佳企业的退出率的直接衡量指标。特别关注小企业管理局（SBA）7（a）和504贷款设施，分析提供了证据的重要性，财政限制，以及在何种程度上，他们可能会被削弱的主要政府计划。结果不仅揭示了直接的计划影响，但也考虑了提高生产力的资源再分配的间接影响。特别是政策干预是促进生产率高但资金紧张的企业的增长，还是维持低生产率企业的增长，使其资源得到上级利用。研究结果对美国经济的增长、创新和生产率具有政策意义。该项目依赖于新的概念，方法和数据来估计金融准入和小企业计划的影响。从概念上讲，该项目利用企业动态模型来分析作为进入者和现任者实验结果的创新，从而作为创造性破坏过程的一部分。一个基本的见解是，结果的完全分布有助于揭示创新，因为实验提高了分散度，选择提高了偏斜度。实证方法包括一个可信的识别策略的基础上面板匹配和工具变量捕捉SBA贷款访问的地理差异。估计不仅包括生产力和创新措施的平均处理效果，而且还包括结果分布的其他时刻：总体分散和偏度，顶级企业的表现，以及通过增长和退出在分布中的不同点起作用的分配和选择效果。这些方法提供了一种评估政府干预对提高生产率的再分配的影响的新方法。这项数据工作将SBA的行政数据与人口普查局关于所有美国雇主的通用数据联系起来。从商业登记，制造商普查和制造商年度调查的变量被添加到衡量生产力。与新的企业家年度调查相联系，可以直接衡量创新和研发工作。该项目的概念方法、识别策略、分析方法和数据开发应该对其他研究具有积极的外部性，包括对美国和世界各地其他项目的评估。