Utilizing confidential microdata from the Census Bureau's new technology survey (technology module of the Annual Business Survey), we shed light on U.S. banks' use of artificial intelligence (AI) and its effect on their small business lending. We find that the percentage of banks using AI increases from 14% in 2017 to 43% in 2019. Linking banks' AI use to their small business lending, we find that banks with greater AI usage lend significantly more to distant borrowers, about whom they have less soft information. Using an instrumental variable based on banks' proximity to AI vendors, we show that AI's effect is likely causal. In contrast, we do not find similar effects for cloud systems, other types of software, or hardware surveyed by Census, highlighting AI's uniqueness. Moreover, AI's effect on distant lending is more pronounced in poorer areas and areas with less bank presence. Last, we find that banks with greater AI usage experience lower default rates among distant borrowers and charge these borrowers lower interest rates, suggesting that AI helps banks identify creditworthy borrowers at loan origination. Overall, our evidence suggests that AI helps banks reduce information asymmetry with borrowers, thereby enabling them to extend credit over greater distances.
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After the Storm: How Emergency Liquidity Helps Small Businesses Following Natural Disasters
April 2024
Working Paper Number:
CES-24-20
Does emergency credit prevent long-term financial distress? We study the causal effects of government-provided recovery loans to small businesses following natural disasters. The rapid financial injection might enable viable firms to survive and grow or might hobble precarious firms with more risk and interest obligations. We show that the loans reduce exit and bankruptcy, increase employment and revenue, unlock private credit, and reduce delinquency. These effects, especially the crowding-in of private credit, appear to reflect resolving uncertainty about repair. We do not find capital reallocation away from neighboring firms and see some evidence of positive spillovers on local entry.
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AI Adoption in America: Who, What, and Where
September 2023
Working Paper Number:
CES-23-48R
We study the early adoption and diffusion of five AI-related technologies (automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition) as documented in the 2018 Annual Business Survey of 850,000 firms across the United States. We find that fewer than 6% of firms used any of the AI-related technologies we measure, though most very large firms reported at least some AI use. Weighted by employment, average adoption was just over 18%. AI use in production, while varying considerably by industry, nevertheless was found in every sector of the economy and clustered with emerging technologies such as cloud computing and robotics. Among dynamic young firms, AI use was highest alongside more educated, more-experienced, and younger owners, including owners motivated by bringing new ideas to market or helping the community. AI adoption was also more common alongside indicators of high-growth entrepreneurship, including venture capital funding, recent product and process innovation, and growth-oriented business strategies. Early adoption was far from evenly distributed: a handful of 'superstar' cities and emerging hubs led startups' adoption of AI. These patterns of early AI use foreshadow economic and social impacts far beyond this limited initial diffusion, with the possibility of a growing 'AI divide' if early patterns persist.
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Locally Owned Bank Commuting Zone Concentration and Employer Start-Ups in Metropolitan, Micropolitan and Non-Core Rural Commuting Zones from 1970-2010
August 2018
Working Paper Number:
CES-18-34
Access to financial capital is vital for the sustainability of the local business sector in metropolitan and nonmetropolitan communities. Recent research on the restructuring of the financial industry from local owned banks to interstate conglomerates has raised questions about the impact on rural economies. In this paper, we begin our exploration of the Market Concentration Hypothesis and the Local Bank Hypothesis. The former proposes that there is a negative relationship between the percent of banks that are locally owned in the local economy and the rate of business births and continuations, and a positive effect on business deaths, while that latter proposes that there is a positive relationship between the percent of banks that are locally owned in the local economy and the rate of business births and continuations, and a negative effect on business deaths. To examine these hypotheses, we examine the impact of bank ownership concentration (percent of banks that are locally owned in a commuting zone) on business establishment births and deaths in metropolitan, micropolitan and non-core rural commuting zones. We employ panel regression models for the 1980-2010 time frame, demonstrating robustness to several specifications and spatial spillover effects. We find that local bank concentration is positively related to business dynamism in rural commuting zones, providing support to the importance of relational lending in rural areas, while finding support for the importance of market concentration in urban areas. The implications of this research are important for rural sociology, regional economics, and finance.
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Brighter Prospects? Assessing the Franchise Advantage using Census Data
January 2017
Working Paper Number:
CES-17-21
This paper uses Census micro data to examine how starting a business as a franchise rather than an independent business affects its survival and growth prospects. We first consider the factors that influence the business owner's decision about being franchised, and then use different empirical approaches to correct for selection bias in our performance analyses. We find that franchised businesses on average benefit from higher survival rates and faster initial growth relative to independent businesses. However, the effects are not large and, conditional on first-year survival, the differences basically disappear. We briefly discuss potential mechanisms to explain these results. U.S. Census Bureau. All results have been reviewed to ensure that no confidential information is disclosed. Support for this research at the Michigan Census Research Data Center is gratefully acknowledged.
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Spillovers From Costly Credit
March 2013
Working Paper Number:
CES-13-11
Recent research on the effects of credit access among low- and moderate-income households finds that high-cost payday loans exacerbate, rather than alleviate, financial distress for a subset of borrowers (Melzer 2011; Skiba and Tobacman 2011). In this study I find that others, outside the borrowing household, bear a portion of these costs too: households with payday loan access are 20% more likely to use food assistance benefits and 10% less likely to make child support payments required of non-resident parents. These findings suggest that as borrowers accommodate interest and principal payments on payday loan debt, they prioritize loan payments over other liabilities like child support payments and they turn to transfer programs like food stamps to supplement the household's resources. To establish this finding, the analysis uses a measure of payday loan access that is robust to the concern that lender location decisions and state policies governing payday lending are endogenous relative to household financial condition. The analysis also confirms that the effect is absent in the mid-1990s, prior to the spread of payday lending, and that the effect grows over time, in parallel with the growth of payday lending.
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Personal Bankruptcy Law and Entrepreneurship
January 2017
Working Paper Number:
CES-17-42R
We study the effect of debtor protection on firm entry and exit dynamics. We find that more lenient personal bankruptcy laws lead to higher firm entry, especially in sectors with low entry barriers. We also find that debtor protection increases firm exit rates and that this effect is independent of firm age. Our results overall indicate that changes in debtor protection affect firm dynamics.
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Job Creation, Small vs. Large vs. Young, and the SBA
September 2015
Working Paper Number:
CES-15-24
Analyzing a list of all Small Business Administration (SBA) loans in 1991 to 2009 linked with annual information on all U.S. employers from 1976 to 2012, we apply detailed matching and regression methods to estimate the variation in SBA loan effects on job creation and firm survival across firm age and size groups. The estimated number of jobs created per million dollars of loans within the small business sector generally increases with size and decreases in age. The results suggest that the growth of small, mature firms is least financially constrained, and that faster growing firms experience the greatest financial constraints to growth. The estimated association between survival and loan amount is larger for younger and smaller firms facing the 'valley of death.'
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Estimating the Impact of Low-Income Universal Service Programs
June 2013
Working Paper Number:
CES-13-33
This policy study uses U.S. Census microdata to evaluate how subsidies for universal telephone service vary in their impact across low-income racial groups, gender, age, and home ownership. Our demand specification includes both the subsidized monthly price (Lifeline program) and the subsidized initial connection price (Linkup program) for local telephone service. Our quasimaximum likelihood estimation controls for location differences and instruments for price endogeneity. The microdata allow us to estimate the effects of demographics on both elasticities of telephone penetration and the level of telephone penetration. Based on our preferred estimates, the subsidy programs increased aggregate penetration by 6.1% for low-income households. Our results suggest that Linkup is more cost-effective than Lifeline and that auto-enroll policies are important, which calls into question a recent FCC (2012) decision to reduce Linkup subsidies in favor of Lifeline. Our study can inform the evaluation of similar universal service policies for Internet access.
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Innovation and Appropriability: Revisiting the Role of Intellectual Property
March 2022
Working Paper Number:
CES-22-09
It is more than 25 years since the authors of the Yale and Carnegie surveys studied how firms seek to protect the rents from innovation. In this paper, we revisit that question using a nationally representative sample of firms over the period 2008-2015, with the goal of updating and extending a set of stylized facts that has been influential for our understanding of the economics of innovation. There are five main findings. First, while patenting firms are relatively uncommon in the economy, they account for an overwhelming share of R&D spending. Second, utility patents are considered less important than other forms of IP protection, like trade secrets, trademarks, and copyrights. Third, industry differences explain a great deal of the level of firms' engagement with IP, with high-tech firms on average being more active on all forms of IP. Fourth, we do not find any significant difference in the use of IP strategies across firms at different points of their life cycle. Lastly, unlike age, firms of different size appear to manage IP significantly differently. On average, larger firms tend to engage much more extensively in the protection of IP, and this pattern cannot be easily explained by differences in the type of R&D or innovation produced by a firm. We also discuss the implications of these findings for innovation research and policy.
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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
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.
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