Who Hires Whom? Entrepreneurial Backgrounds and Labor Market Opportunities
July 2026
Working Paper Number:
CES-26-45
Abstract
What are the implications of unequal access to entrepreneurial careers for labor markets? Using data from the U.S. Census and LinkedIn profiles, we document that entrepreneurs are significantly more likely to hire workers from similar social backgrounds (gender, race, age, education, etc.). These effects are quantitatively large across several demographic dimensions. For example, female employee share at female-founded startups is 36.4pp higher after controlling for industry-by-metro area-by-cohort fixed effects, with corresponding estimates of 51.2pp for Blacks, 37.3pp for Hispanics, and 11.3pp for non-college individuals. Large effects are present in high-growth startups, across industries and occupations, and remain stable across new firm cohorts. In addition, we find that these differences persist out to at least 20 years. We use wage data and an AKM research design to untangle whether the relative differences are driven by labor demand or labor supply effects. We find that demand drives the differences: group-specific wage decompositions show that new firms pay higher relative wages to individuals from similar backgrounds to the entrepreneur. Using these estimates, we calibrate a model of entrepreneurship with heterogeneous ability and production functions, and assess the impacts on relative wage from reducing access barriers to entrepreneurship.
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.
:
employ,
entrepreneurial,
black,
entrepreneur,
entrepreneurship,
minority,
labor,
hispanic,
proprietor,
employment growth,
heterogeneity,
hiring,
hire,
socioeconomic,
earner
Tags
Tags are automatically generated using a pretrained language model from spaCy, which excels at
several tasks, including entity tagging.
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.
:
Metropolitan Statistical Area,
Bureau of Labor Statistics,
Center for Economic Studies,
Decennial Census,
Economic Census,
North American Industry Classification System,
Patent and Trademark Office,
Alfred P Sloan Foundation,
Longitudinal Employer Household Dynamics,
AKM,
NBER Summer Institute,
Census Bureau Disclosure Review Board,
Disclosure Review Board,
Federal Statistical Research Data Center
Similar Working Papers
Similarity between working papers are determined by an unsupervised neural
network model
know as Doc2Vec.
Doc2Vec is a model that represents entire documents as fixed-length vectors, allowing for the
capture of semantic meaning in a way that relates to the context of words within the document. The model learns to
associate a unique vector with each document while simultaneously learning word vectors, enabling tasks such as
document classification, clustering, and similarity detection by preserving the order and structure of words. The
document vectors are compared using cosine similarity/distance to determine the most similar working papers.
Papers identified with 🔥 are in the top 20% of similarity.
The 10 most similar working papers to the working paper 'Who Hires Whom? Entrepreneurial Backgrounds and Labor Market Opportunities' are listed below in order of similarity.
-
Working PaperCollege Majors and Earnings Growth
February 2026
Working Paper Number:
CES-26-14
We estimate major-specific earnings profiles using matched American Community Survey (ACS) and Longitudinal Employer-Household Dynamics (LEHD) data. Building on Deming and Noray (2020), we exploit a long earnings panel to overcome key limitations of cross-sectional approaches to lifecycle estimation. We find that engineering and computer science majors experience earnings growth that is comparable to or faster than that of other majors, a category including humanities, education, psychology, and similar fields. In contrast, Deming and Noray (2020) use a crosscohort approach and find that earnings for engineering and computer science majors decline relative to other fields over the lifecycle.View Full Paper PDF
-
Working PaperGarage Entrepreneurs or just Self-Employed? An Investigation into Nonemployer Entrepreneurship
October 2024
Working Paper Number:
CES-24-61
Nonemployers, businesses without employees, account for most businesses in the U.S. yet are poorly understood. We use restricted administrative and survey data to describe nonemployer dynamics, overall performance, and performance by demographic group. We find that eventual outcome ' migration to employer status, continuing as a nonemployer, or exit ' is closely related to receipt growth. We provide estimates of employment creation by firms that began as nonemployers and become employers (migrants), estimating that relative to all firms born in 1996, nonemployer migrants accounted for 3-17% of all net jobs in the seventh year after startup. Moreover, we find that migrants' employment creation declined by 54% for the cohorts born between 1996 to 2014. Our results are consistent with increased adjustment frictions in recent periods, and suggest accessibility to transformative entrepreneurship for everyday Americans has declined.View Full Paper PDF
-
Working PaperWhat Happens to Contractors After States Ban Affirmative Action?
July 2026
Working Paper Number:
CES-26-41
Using restricted Census business records, I explore how banning affirmative action in state contracting affects minority- and women-owned business enterprises (MWBEs). I find that ending affirmative action led MWBE contractors to gradually downsize, with the most pronounced reductions in force experienced by Black-owned businesses and larger MWBEs. Despite these workforce changes, existing MWBEs were no more likely to shut down than other businesses. New MWBEs were relatively less common after a state's ban, highlighting how bans can shift the demographic composition of new contractors. A calibrated model suggests bans are equivalent to considerable reductions in MWBE productivity and scrap values.View Full Paper PDF
-
Working PaperTechnology-Driven Market Concentration through Idea Allocation
December 2025
Working Paper Number:
CES-25-78
Using a newly-created measure of technology novelty, this paper identifies periods with and without technology breakthroughs from the 1980s to the 2020s in the US. It is found that market concentration decreases at the advent of revolutionary technologies. We establish a theory addressing inventors' decisions to establish new firms or join incumbents of selected sizes, yielding two key predictions: (1) A higher share of inventors opt for new firms during periods of heightened technology novelty. (2). There is positive assortative matching between idea quality and firm size if inventors join incumbents. Both predictions align with empirical findings and collectively contribute to a reduction in market concentration when groundbreaking technologies occur. Quantitative analysis shows the overall slowdown in technological breakthroughs can capture 95.9% of the rising trend in market concentration and the correlation between the model-generated and the actual detrended market concentration is 0.910.View Full Paper PDF
-
Working PaperThe Impact of Female Teachers on Female Students' Lifetime Well-Being
June 2026
Working Paper Number:
CES-26-39
We document an enduring influence of female primary school teachers on their female students in rural America circa 1940. Using historical US Census data linked to IRS records, later censuses, and death records, we find that exposure to female teachers significantly improved girls' educational attainment'particularly among those with poorly-educated parents and in areas with limited labor market opportunities for women. These educational gains translated into delayed marriage and childbearing, marriage matches to better-educated husbands and higher household income. We also find that exposure to female teachers increased longevity of women relative to men.View Full Paper PDF
-
Working PaperWhose Job Is It Anyway? Co-Ethnic Hiring in New U.S. Ventures
March 2021
Working Paper Number:
CES-21-05
We explore co-ethnic hiring among new ventures using U.S. administrative data. Co-ethnic hiring is ubiquitous among immigrant groups, averaging about 22.5% and ranging from 2% to 40%. Co-ethnic hiring grows with the size of the local ethnic workforce, greater linguistic distance to English, lower cultural/genetic similarity to U.S. natives, and in harsher policy environments for immigrants. Co ethnic hiring is remarkably persistent for ventures and for individuals. Co-ethnic hiring is associated with greater venture survival and growth when thick local ethnic employment surrounds the business. Our results are consistent with a blend of hiring due to information advantages within ethnic groups with some taste-based hiring.View Full Paper PDF
-
Working PaperThe Microstructure of AI Diffusion: Evidence From Firms, Business Functions, and Worker Tasks
April 2026
Working Paper Number:
CES-26-25
Using novel, nationally representative data from the 2026 AI supplement to the U.S. Census Bureau's Business Trends and Outlook Survey (BTOS), we characterize AI diffusion across three interconnected layers: overall firm use, deployment across business functions, and worker-task use. This multi-layered approach provides a nuanced picture of business AI adoption. During the supplement reference period (Nov 2025-Jan 2026), 18% of firms used AI in a business function, rising to 32% on an employment-weighted basis; adoption is expected to reach 22% within six months. AI use is substantially higher in large firms and knowledge-intensive sectors, with use rates reaching 50%-60% (60%-70%, employment-weighted) for very large firms in the Information, Professional Services, and Finance sectors. Among adopting firms, the scope of use remains limited: 57% of users integrate AI in three or fewer business functions, most commonly Sales and Marketing (52%), Strategy and Business Development (45%), and IT (41%). In 23% (41%, employment-weighted) of firms, workers use AI in work-related tasks. Writing, document analysis, and information search are the leading Generative AI use in tasks, though 65% of firms limit use to three or fewer tasks. The evidence points to both top-down and bottom-up diffusion channels: worker task use sometimes occurs without formal firm-level adoption, and firm-level adoption sometimes occurs without worker task use. Most users (66%) rely on AI solely to augment tasks, while AI-related employment decreases are rare, occurring in only 2% of firms. Regression analysis shows a robust positive correlation between firm commercial performance and the breadth of AI integration, including functional deployment, task-level use, and operational investment. A distinct divergence emerges, however, with respect to labor outcomes. Functional breadth and operational investment are positively associated with employment decreases, whereas worker-task integration shows no significant link to headcount reduction once functional integration and operational investment are taken into account.View Full Paper PDF
-
Working PaperSame Shock, Separate Channels: House Prices and Firm Performance in the Great Recession
January 2026
Working Paper Number:
CES-26-03
Combining confidential business-level microdata with housing and banking data, I document large and persistent effects of local house prices on employment at small businesses, and particularly young businesses, during the Great Recession. I show that the effect on entry is important for explaining the disproportionate effect on young businesses, while young firm exit is also disproportionately affected. I then explore the channels through which house prices affect business outcomes. I use survey data to show that reliance on either personal assets or home equity is associated with increased sensitivity to house prices. I then use local bank balance sheet information to show both young and old firms are sensitive to local credit shocks, with some evidence of a larger effect on young businesses. I develop a macroeconomic model that is consistent with these findings where house prices work through two channels: a bank credit supply channel and a housing collateral channel.View Full Paper PDF
-
Working PaperThe Adoption of Non-Rival Inputs and Firm Scope
April 2026
Working Paper Number:
CES-26-28
Custom software is distinct from other types of capital in that it is non-rival'once a firm makes an investment in custom software, it can be used simultaneously across its many establishments. Using confidential U.S. Census data, we document that while firms with more establishments are more likely to invest in custom software, they spend less on it as a share of total capital expenditure. We explain these empirical patterns by developing a model that incorporates the non-rivalry of custom software. In the model, firms choose whether to adopt custom software, the intensity of their investment, and their scope, balancing the cost of managing multiple establishments with the increasing returns to scope from the nonrivalrous custom software investment. Using the calibrated model, we assess the extent to which the decline in the rental rate of custom software over the past 40 years can account for a number of macroeconomic trends, including increases in firm scope and concentration.View Full Paper PDF
-
Working PaperENFORCING COVENANTS NOT TO COMPETE: THE LIFE-CYCLE IMPACT ON NEW FIRMS
June 2014
Working Paper Number:
CES-14-27
We examine the impact of enforcing non-compete covenants (CNC) on the formation and performance of new firms using matched employer-employee data on 30 US states. To identify the impact of CNC, we exploit the inter-state variation in CNC enforcement along with the fact that courts do not enforce such covenants between law firms and departing lawyers in any state. Using a difference-in-difference-in-difference specification with law firms and firms that are not withinindustry spinouts as the baseline, we find states with stricter CNC enforcement have fewer, but larger within-industry spinouts that are more likely to survive their nascent years, and conditional on survival, grow faster during those years. These results are consistent with CNC enforcement having a selection effect on within-industry spinouts. Particularly, with stricter enforcement, only founders with higher-quality ideas and resources choose to overcome CNC-related barriers, which reduces entry rate but increases observed short-term performance of these spinouts.View Full Paper PDF
