Small 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.
