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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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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The Rise of Industrial AI in America: Microfoundations of the Productivity J-curve(s)
April 2025
Working Paper Number:
CES-25-27
We examine the prevalence and productivity dynamics of artificial intelligence (AI) in American manufacturing. Working with the Census Bureau to collect detailed large-scale data for 2017 and 2021, we focus on AI-related technologies with industrial applications. We find causal evidence of J-curve-shaped returns, where short-term performance losses precede longer-term gains. Consistent with costly adjustment taking place within core production processes, industrial AI use increases work-in-progress inventory, investment in industrial robots, and labor shedding, while harming productivity and profitability in the short run. These losses are unevenly distributed, concentrating among older businesses while being mitigated by growth-oriented business strategies and within-firm spillovers. Dynamics, however, matter: earlier (pre-2017) adopters exhibit stronger growth over time, conditional on survival. Notably, among older establishments, abandonment of structured production-management practices accounts for roughly one-third of these losses, revealing a specific channel through which intangible factors shape AI's impact. Taken together, these results provide novel evidence on the microfoundations of technology J-curves, identifying mechanisms and illuminating how and why they differ across firm types. These findings extend our understanding of modern General Purpose Technologies, explaining why their economic impact'exemplified here by AI'may initially disappoint, particularly in contexts dominated by older, established firms.
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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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MICROENTERPRISE AS AN EXIT ROUTE FROM POVERTY:* RECOMMENDATIONS FOR PROGRAMS AND POLICY MAKERS
November 1998
Working Paper Number:
CES-98-17
The objective of this study is to shed light on whether and how microenterprise programs can be used as an economic development strategy to enable low-income people to achieve self-sufficiency through self-employment. Our findings provide little support for the notion that hard work and a small loan are sufficient ingredients for business success. Viable small firms are usually headed by well-educated owners and/or those possessing specific skills that serve as a basis for successful business creation and operation. Potential entrepreneurs lacking assets, skills, and support networks are unlikely to support themselves through self-employment earnings alone. As a poverty alleviation strategy, microenterprise is not a panacea. Nevertheless, programs targeting the poor who do have skills, resources, and support networks can be useful vehicles for helping some to escape poverty.
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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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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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Information Technology, Capabilities and Asset Ownership: Evidence from Taxicab Fleets
November 2009
Working Paper Number:
CES-09-39
We examine how information technology (IT) influences asset ownership through its impact on firms' and agents' capabilities. In particular, we propose that when IT is a substitute for agents' industry-specific human capital, IT adoption leads to increased vertical integration. We test this prediction using micro data on vehicle ownership patterns from the Economic Census during a period when computerized dispatching systems were first adopted by taxicab firms. The empirical tests exploit exogenous variation in local market conditions, to identify the impact of dispatching technology on firm asset ownership. The results show that firms increase the proportion of taxicabs owned by 12% when they adopt new computerized dispatching systems. The findings suggest that firms increasingly vertically integrate when they acquire resources that substitute for their agents' capabilities.
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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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