In an unusual partnership of university and government researchers working together to link and analyze several very large firm-level databases, this project evaluates the growth and innovation effects of small business support programs. Adapting and extending labor market program evaluation methods, the researchers link administrative program data to universal long-panel data and to a variety of survey data. The main estimation method is based on longitudinal matching combined with regression, and besides estimating the basic average treatment effect on the treated, the project investigates treatment intensity (loan/grant size), analyze potential general equilibrium effects, and examine the heterogeneity of effects by type of program, loan conditions, type of firm, and economic context. The results will enable the first rigorous estimates of government program effects on firm-level innovation and growth.
Intellectual Merit:
In addition to its direct policy relevance, this project contributes to theoretical and empirical questions about small firms, growth, innovation, finance, and fiscal policy. Do small business support programs foster growth and innovation? Innovation is proxied in several ways: sales and employment growth, productivity, skill-biased employment change, patents, R&D personnel, and survey-based measures; the analysis distinguishes market-expanding from business-stealing effects. Results for loan programs will contribute to the growth-finance debate by analyzing specific policy interventions varying at the firm level, which avoids many of the econometric problems plaguing estimates based on aggregate data. Other issues concern the degree to which firms are financially constrained and the size of the government spending multiplier, for which the project uses firm level microdata to estimate the impact of government programs on small business growth (the first-stage effect), and how it varies over the business cycle.
Broader Impacts:
The broader impacts of this research appear, first, in the contribution to urgent policy debates. The question is not only whether the support programs on average increase growth and innovation at recipient firms, but whether these benefits are offset by negative spillovers (displacement effects) or enhanced by positive spillovers (e.g., shared innovation), and also whether they are more effective in some environments (e.g., after negative shocks), for some types of firms (e.g., young start-ups), or for some types of program design (e.g., eligibility criteria and loan terms). Romania is included to provide an international replication, because of the interest in microcredit and financial development in transition economies, and because of the excellent data available for analysis. The project also makes methodological contributions of broader usefulness: exploiting the long panel data to extend matching methods, introducing new types of multiple control groups for more credible identification, and developing new approaches for analyzing the general equilibrium effects of economic policies. The project advances the broad research agenda of linking and analyzing diverse sets of microdata, one of the most promising recent developments in empirical economics. The ideas and methods could serve as models for researchers analyzing other policies, both in the US and in many other countries where similar programs and data exist. The specific data generated by the project through linking of many large databases will have considerable value, and another broad impact may result from making the data available to other researchers. PhD students can and will benefit from learning to work with the data, participating in professional conferences, and writing dissertations on the basis of the data and project.
