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Do SBA Loans Create Jobs? Estimates from Universal Panel Data and Longitudinal Matching Methods

September 2012

Working Paper Number:

CES-12-27

Abstract

This pape reports estimates of the effects of the Small Business Administration (SBA) 7(a) and 504 loan programs on employment. The database links a complete list of all SBA loans in these programs to universal data on all employers in the U.S. economy from 1976 to 2010. Our method is to estimate firm fixed effect regressions using matched control groups for the SBA loan recipients we have constructed by matching exactly on firm age, industry, year, and pre-loan size, plus kernel-based matching on propensity scores estimated as a function of four years of employment history and other variables. The results imply positive average effects on loan recipient employment of about 25 percent or 3 jobs at the mean. Including loan amount, we find little or no impact of loan receipt per se, but an increase of about 5.4 jobs for each million dollars of loans. When focusing on loan recipients and control firms located in high-growth counties (average growth of 22 percent), places where most small firms should have excellent growth potential, we find similar effects, implying that the estimates are not driven by differential demand conditions across firms. Results are also similar regardless of distance of control from recipient firms, suggesting only a very small role for displacement effects. In all these cases, the results pass a "pre-program" specification test, where controls and treated firms look similar in the pre-loan period. Other specifications, such as those using only matching or only regression imply somewhat higher effects, but they fail the pre-program test.

Document Tags and Keywords

Keywords Keywords are automatically generated using KeyBERT, a powerful and innovative keyword extraction tool that utilizes BERT embeddings to ensure high-quality and contextually relevant keywords.

By analyzing the content of working papers, KeyBERT identifies terms and phrases that capture the essence of the text, highlighting the most significant topics and trends. This approach not only enhances searchability but provides connections that go beyond potentially domain-specific author-defined keywords.
:
economist, estimating, econometric, macroeconomic, financial, finance, financing, leverage, regression, lending, lender, borrower, loan, hiring, debt

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The model is able to label words and phrases by part-of-speech, including "organizations." By filtering for frequent words and phrases labeled as "organizations", papers are identified to contain references to specific institutions, datasets, and other organizations.
:
Small Business Administration, Service Annual Survey, Census Bureau Longitudinal Business Database, Longitudinal Business Database, Bureau of Labor, North American Industry Classification System, Centers for Disease Control and Prevention

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