Using rich administrative tax data, we explore the effects of the introduction of online ridesharing platforms on entry, employment and earnings in the Taxi and Limousine Services industry. Ridesharing dramatically increased the pace of entry of workers into the industry. New entrants were more likely to be young, female, White and U.S. born, and to combine earnings from ridesharing with wage and salary earnings. Displaced workers have found ridesharing to be a substantially more attractive fallback option than driving a taxi. Ridesharing also affected the incumbent taxi driver workforce. The exit rates of low-earning taxi drivers increased following the introduction of ridesharing in their city; exit rates of high-earning taxi drivers were little affected. In cities without regulations limiting the size of the taxi fleet, both groups of drivers experienced earnings losses following the introduction of ridesharing. These losses were ameliorated or absent in more heavily regulated markets.
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The Effects of Occupational Licensing Evidence from Detailed Business-Level Data
January 2017
Working Paper Number:
CES-17-20
Occupational licensing regulation has increased dramatically in importance over the last several decades, currently affecting more than one thousand occupations in the United States. I use confidential U.S. Census Bureau micro-data to study the relationship between occupational licensing and key business outcomes, such as number of practitioners, prices for consumers, and practitioners' entry and exit rates. The paper sheds light on the effect of occupational licensing on industry dynamics and intensity of competition, and is the first to study the effects on providers of required occupational training. I find that occupational licensing regulation does not affect the equilibrium number of practitioners or prices of services to consumers, but reduces significantly practitioner entry and exit rates. I further find that providers of occupational licensing training, namely, schools, are larger and seem to do better, in terms of revenues and gross margins, in states with more stringent occupational licensing regulation.
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Don't Quit Your Day Job: Using Wage and Salary Earnings to Support a New Business
September 2013
Working Paper Number:
CES-13-45
This paper makes use of a newly constructed Census Bureau dataset that follows the universe of sole proprietors, employers and non-employers, over 10 years and links their transitions to their activity as employees earning wage and salary income. By combining administrative data on sole proprietors and their businesses with quarterly administrative data on wage and salary jobs held by the same individuals both preceding and concurrent with business startup, we create the unique opportunity to quantify significant workforce dynamics that have up to now remained unobserved. The data allow us to take a first glimpse at these business owners as they initiate business ventures and make the transition from wage and salary work to business ownership and back. We find that the barrier between wage and salary work and self-employment is extremely fluid, with large flows occurring in both directions. We also observe that a large fraction of business owners takeon both roles simultaneously and find that this labor market diversification does have implications for the success of the businesses these owners create. The results for employer transitions to exit and non-employer suggest that there is a 'don't quit your day job' effect that is present for new businesses. Employers are more likely to stay employers if they have a wage and salary job in the year just prior to the transitions that we are tracking. It is especially important to have a stable wage and salary job but there is also evidence that higher earnings from the wage and salary job makes transition less likely. For nonemployers we find roughly similar patterns but there are some key differences. We find that having recent wage and salary income (and having higher earnings from such wage and salary activity) increases the likelihood of survival. Having recent stable wage and salary income decreases the likelihood of a complete exit but increases the likelihood of transiting to be an employer. Having recent wage and salary income in the same industry as the non-employer business has a large and positive impact on the likelihood of transiting to being a non-employer business.
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Business Owners and the Self-Employed: 33 Million (and Counting!)
September 2025
Working Paper Number:
CES-25-60
Entrepreneurs are known to be key drivers of economic growth, and the rise of online platforms and the broader 'gig economy' has led self-employment to surge in recent decades. Yet the young and small businesses associated with this activity are often absent from economic data. In this paper, we explore a novel longitudinal dataset that covers the owners of tens of millions of the smallest businesses: those without employees. We produce three new sets of statistics on the rapidly growing set of nonemployer businesses. First, we measure transitions between self-employment and wage and salary jobs. Second, we describe nonemployer business entry and exit, as well as transitions between legal form (e.g., sole proprietorship to S corporation). Finally, we link owners to their nonemployer businesses and examine the dynamics of business ownership.
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Mom-and-Pop Meet Big-Box: Complements or Substitutes?
September 2009
Working Paper Number:
CES-09-34
In part due to the popular perception that Big-Boxes displace smaller, often family owned (a.k.a. Mom-and-Pop) retail establishments, several empirical studies have examined the evidence on how Big-Boxes' impact local retail employment but no clear consensus has emerged. To help shed light on this debate, we exploit establishment-level data with detailed location information from a single metropolitan area to quantify the impact of Big-Box store entry and growth on nearby single unit and local chain stores. We incorporate a rich set of controls for local retail market conditions as well as whether or not the Big-Boxes are in the same sector as the smaller stores. We find a substantial negative impact of Big-Box entry and growth on the employment growth at both single unit and especially smaller chain stores ' but only when the Big-Box activity is both in the immediate area and in the same detailed industry.
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Employer-to-Employer Flows in the United States: Estimates Using Linked Employer-Employee Data
September 2010
Working Paper Number:
CES-10-26
We use administrative data linking workers and firms to study employer-to-employer flows. After discussing how to identify such flows in quarterly data, we investigate their basic empirical patterns. We find that the pace of employer-to-employer flows is high, representing about 4 percent of employment and 30 percent of separations each quarter. The pace of employer-to-employer flows is highly procyclical, and varies systematically across worker, job and employer characteristics. Our findings regarding job tenure and earnings dynamics suggest that for those workers moving directly to new jobs, the new jobs are generally better jobs; however, this pattern is highly procyclical. There are rich patterns in terms of origin and destination of industries. We find somewhat surprisingly that more than half of the workers making employer-to-employer transitions switch even broadly-defined industries (NAICS supersectors).
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Local Labor Demand and Program Participation Dynamics
November 2016
Working Paper Number:
carra-2016-10
Estimates the effect of fluctuations in local labor conditions on the likelihood that existing participants are able to transition out of the Supplemental Nutrition Assistance Program (SNAP). Our primary data are SNAP administrative records from New York (2007-2012) linked to the 2010 Census at the person-level. We further augment these data by linking to industry-specific labor market indicators at the county-level. We find that local labor markets matter for the length of time individuals spend on SNAP, but there is substantial heterogeneity in estimated effects across local industries. While employment growth in industries with small shares of SNAP participants has no impact on SNAP exits, growth in local industries with creases the likelihood that recipients exit the program. We also observe corresponding increases in entries when these industries experience localized contractions. Notably, estimated industry effects vary across race groups and parental status, with Black Alone non-Hispanic, Hispanic, and mothers benefiting the least from improvements in local labor market conditions.
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The Long-Term Effects of Job Mobility on the Adult Earnings of Young Men: Evidence from Integrated Employer-Employee Data
June 2005
Working Paper Number:
CES-05-05
The paper follows a population of 18-year-old men to examine the impact that early job mobility has on their earnings prospects as young adults. Longitudinal employer-employee data from the state of Maryland allow me to take into consideration the endogenous determination of mobility in response to unobserved worker as well as firm characteristics, which may lead to spurious results. The descriptive portion of the paper shows that mobility patterns of young workers differ considerably with the characteristics of the firm; however, growth patterns are not significantly different on average. Workers employed in high-turnover firms (such as those in retail and services) experience more job turnover but similar rates of wage growth compared to workers employed in low turnover firms (such as those in manufacturing); however, their wage levels remain below and the wage gap actually increases over time. Regression results controlling for unobservable show that employers in the low-turnover sector discount earnings of workers who displayed early market mobility. By contrast, I find no evidence that mobility has negative effects for workers that remain employed in the high turnover sector.
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The Dynamics of Market Structure and Market Size in Two Health Services Industries
October 2007
Working Paper Number:
CES-07-26
The relationship between the size of a market and the competitiveness of the market has been of long-standing interest to IO economists. Empirical studies have used the relationship between the size of the geographic market and both the number of firms in the market and the average sales of the firms to draw inferences about the degree of competition in the market. This paper extends this framework to incorporate the analysis of entry and exit flows. A key implication of recent entry and exit models is that current market structure will likely depend upon history of past participation. The paper explores these issues empirically by examining producer dynamics for two health service industries, dentistry and chiropractic services. We find that the number of potential entrants and past number of incumbent firms are correlated with current market structure. The empirical results also show that as market size increases the number of firms rises less than proportionately, firm size increases, and average productivity increases. However, the magnitude of the correlations are sensitive to the inclusion of the market history variables.
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Occupation Inflation in the Current Population Survey
September 2012
Working Paper Number:
CES-12-26
A common caveat often accompanying results relying on household surveys regards respondent error. There is research using independent, presumably error-free administrative data, to estimate the extent of error in the data, the correlates of error, and potential corrections for the error. We investigate measurement error in occupation in the Current Population Survey (CPS) using the panel component of the CPS to identify those that incorrectly report changing occupation. We find evidence that individuals are inflating their occupation to higher skilled and higher paying occupations than the ones they actually perform. Occupation inflation biases the education and race coefficients in standard Mincer equation results within occupations.
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Unemployment Insurance, Wage Pass-Through, and Endogenous Take-Up
September 2025
Working Paper Number:
CES-25-59
This paper studies how unemployment insurance (UI) generosity affects reservation wages, re-employment wages, and benefit take-up. Using Benefit Accuracy Measurement (BAM) data, we estimate a cross-sectional elasticity of reservation wages with respect to weekly UI benefits of 0.014. Exploiting state variation in Pandemic Unemployment Assistance (PUA) intensity and the timing of federal supplements, we find that expanded benefits during COVID-19 increased reservation wages by 8'12 percent. Using CPS rotation data, we also document a 9 percent rise in re-employment wages for UI-eligible workers relative to ineligible workers. Over the same period, the UI take-up rate rose from roughly 30 to 40 percent; Probit estimates indicate that higher benefit levels, rather than changes in observables, account for this increase. A directed search model with an endogenous filing decision replicates these facts: generosity primarily operates through the extensive margin of take-up, which mutes the pass-through from benefits to wages.
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