Papers Containing Tag(s): 'Agriculture, Forestry'
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Viewing papers 1 through 10 of 14
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Working PaperSize Matters: Matching Externalities and the Advantages of Large Labor Markets
April 2025
Working Paper Number:
CES-25-22
Economists have long hypothesized that large and thick labor markets facilitate the matching between workers and firms. We use administrative data from the LEHD to compare the job search outcomes of workers originally in large and small markets who lost their jobs due to a firm closure. We define a labor market as the Commuting Zone'industry pair in the quarter before the closure. To account for the possible sorting of high-quality workers into larger markets, the effect of market size is identified by comparing workers in large and small markets within the same CZ, conditional on workers fixed effects. In the six quarters before their firm's closure, workers in small and large markets have a similar probability of employment and quarterly earnings. Following the closure, workers in larger markets experience significantly shorter non-employment spells and smaller earning losses than workers in smaller markets, indicating that larger markets partially insure workers against idiosyncratic employment shocks. A 1 percent increase in market size results in a 0.015 and 0.023 percentage points increase in the 1-year re-employment probability of high school and college graduates, respectively. Displaced workers in larger markets also experience a significantly lower need for relocation to a different CZ. Conditional on finding a new job, the quality of the new worker-firm match is higher in larger markets, as proxied by a higher probability that the new match lasts more than one year; the new industry is the same as the old one; and the new industry is a 'good fit' for the worker's college major. Consistent with the notion that market size should be particularly consequential for more specialized workers, we find that the effects are larger in industries where human capital is more specialized and less portable. Our findings may help explain the geographical agglomeration of industries'especially those that make intensive use of highly specialized workers'and validate one of the mechanisms that urban economists have proposed for the existence of agglomeration economies.View Full Paper PDF
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Working PaperMeasuring the Business Dynamics of Firms that Received Pandemic Relief Funding: Findings from a New Experimental BDS Data Product
January 2025
Working Paper Number:
CES-25-05
This paper describes a new experimental data product from the U.S. Census Bureau's Center for Economic Studies: the Business Dynamics Statistics (BDS) of firms that received Small Business Administration (SBA) pandemic funding. This new product, BDS-SBA COVID, expands the set of currently published BDS tables by linking loan-level program participation data from SBA to internal business microdata at the U.S. Census Bureau. The linked programs include the Paycheck Protection Program (PPP), COVID Economic Injury Disaster Loans (COVID-EIDL), the Restaurant Revitalization Fund (RRF), and Shuttered Venue Operators Grants (SVOG). Using these linked data, we tabulate annual firm and establishment counts, measures of job creation and destruction, and establishment entry and exit for recipients and non-recipients of program funds in 2020-2021. We further stratify the tables by timing of loan receipt and loan size, and business characteristics including geography, industry sector, firm size, and firm age. We find that for the youngest firms that received PPP, the timing of receipt mattered. Receiving an early loan correlated with a lower job destruction rate compared to non-recipients and businesses that received a later loan. For the smallest firms, simply participating in PPP was associated with lower employment loss. The timing of PPP receipt was also related to establishment exit rates. For businesses of nearly all ages, those that received an early loan exited at a lower rate in 2022 than later loan recipients.View Full Paper PDF
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Working PaperBlack Entrepreneurs, Job Creation, and Financial Constraints
May 2021
Working Paper Number:
CES-21-11
Black-owned businesses tend to operate with less finance and employ fewer workers than those owned by Whites. Motivated by a simple conceptual framework, we document these facts and show they are causally connected using large firm-level surveys linked to universal employer data from the Census Bureau. We find that the racial financing gap is most pronounced at start-up and tends to narrow with firm age. At any age, Black-owned firms are less likely to receive bank loans, more likely to refrain from applying because they expect denial, and more likely to report that lack of finance reduces their profitability. Yet the observable characteristics of Black entrepreneurs are similar in most respects to Whites, and in some ways - higher education, growth-oriented motivations, and involvement in the business - would seem to imply higher, not lower, demand for finance. Concerning employment, we find that Black-owned firms have on average about 12 percent fewer employees than those owned by Whites, but the difference drops when controlling for firm age and other characteristics. However, when the analysis holds financial variables constant, the results imply that equally well-financed Black-owned rms would be larger than White-owned by about seven percent. Exploiting the credit supply shock of changing assignment to Community Reinvestment Act treatment through a Regression Discontinuity Design in a firm-level panel regression framework, we find that expanded credit access raises employment 5-7 percentage points more at Black-owned businesses than White-owned firms in treated neighborhoods.View Full Paper PDF
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Working PaperNonemployer Statistics by Demographics (NES-D): Exploring Longitudinal Consistency and Sub-national Estimates
December 2019
Working Paper Number:
CES-19-34
Until recently, the quinquennial Survey of Business Owners (SBO) was the only source of information for U.S. employer and nonemployer businesses by owner demographic characteristics such as race, ethnicity, sex and veteran status. Now, however, the Nonemployer Statistics by Demographics series (NES-D) will replace the SBO's nonemployer component with reliable, and more frequent (annual) business demographic estimates with no additional respondent burden, and at lower imputation rates and costs. NES-D is not a survey; rather, it exploits existing administrative and census records to assign demographic characteristics to the universe of approximately 25 million (as of 2016) nonemployer businesses. Although only in the second year of its research phase, NES-D is rapidly moving towards production, with a planned prototype or experimental version release of 2017 nonemployer data in 2020, followed by annual releases of the series. After the first year of research, we released a working paper (Luque et al., 2019) that assessed the viability of estimating nonemployer demographics exclusively with administrative records (AR) and census data. That paper used one year of data (2015) to produce preliminary tabulations of business counts at the national level. This year we expand that research in multiple ways by: i) examining the longitudinal consistency of administrative and census records coverage, and of our AR-based demographics estimates, ii) evaluating further coverage from additional data sources, iii) exploring estimates at the sub-national level, iv) exploring estimates by industrial sector, v) examining demographics estimates of business receipts as well as of counts, and vi) implementing imputation of missing demographic values. Our current results are consistent with the main findings in Luque et al. (2019), and show that high coverage and demographic assignment rates are not the exception, but the norm. Specifically, we find that AR coverage rates are high and stable over time for each of the three years we examine, 2014-2016. We are able to identify owners for approximately 99 percent of nonemployer businesses (excluding C-corporations), 92 to 93 percent of identified nonemployer owners have no missing demographics, and only about 1 percent are missing three or more demographic characteristics in each of the three years. We also find that our demographics estimates are stable over time, with expected small annual changes that are consistent with underlying population trends in the U.S.. Due to data limitations, these results do not include C-corporations, which represent only 2 percent of nonemployer businesses and 4 percent of receipts. Without added respondent burden and at lower imputation rates and costs, NES-D will provide high-quality business demographics estimates at a higher frequency (annual vs. every 5 years) than the SBO.View Full Paper PDF
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Working PaperMaternal Labor Dynamics: Participation, Earnings, and Employer Changes
December 2019
Working Paper Number:
CES-19-33
This paper describes the labor dynamics of U.S. women after they have had their first and subsequent children. We build on the child penalty literature by showing the heterogeneity of the size and pattern of labor force participation and earnings losses by demographic characteristics of mothers and the characteristics of their employers. The analysis uses longitudinal administrative earnings data from the Longitudinal Employer-Household Dynamics database combined with the Survey of Income and Program Participation survey data to identify women, their fertility timing, and employment. We find that women experience a large and persistent decrease in earnings and labor force participation after having their first child. The penalty grows over time, driven by the birth of subsequent children. Non-white mothers, unmarried mothers, and mothers with more education are more likely to return to work following the birth of their first child. Conditional on returning to the labor force, women who change employers earn more after the birth of their first child than women who return to their pre-birth employers. The probability of returning to the pre-birth employer and industry is heterogeneous over both the demographics of mothers and the characteristics of their employers.View Full Paper PDF
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Working PaperReservation Nonemployer and Employer Establishments: Data from U.S. Census Longitudinal Business Databases
December 2018
Working Paper Number:
CES-18-50
The presence of businesses on American Indian reservations has been difficult to analyze due to limited data. Akee, Mykerezi, and Todd (AMT; 2017) geocoded confidential data from the U.S. Census Longitudinal Business Database to identify whether employer establishments were located on or off American Indian reservations and then compared federally recognized reservations and nearby county areas with respect to their per capita number of employers and jobs. We use their methods and the U.S. Census Integrated Longitudinal Business Database to develop parallel results for nonemployer establishments and for the combination of employer and nonemployer establishments. Similar to AMT's findings, we find that reservations and nearby county areas have a similar sectoral distribution of nonemployer and nonemployer-plus-employer establishments, but reservations have significantly fewer of them in nearly all sectors, especially when the area population is below 15,000. By contrast to AMT, the average size of reservation nonemployer establishments, as measured by revenue (instead of the jobs measure AMT used for employers), is smaller than the size of nonemployers in nearby county areas, and this is true in most industries as well. The most significant exception is in the retail sector. Geographic and demographic factors, such as population density and per capita income, statistically account for only a small portion of these differences. However, when we assume that nonemployer establishments create the equivalent of one job and use combined employer-plus-nonemployer jobs to measure establishment size, the employer job numbers dominate and we parallel AMT's finding that, due to large job counts in the Arts/Entertainment/Recreation and Public Administration sectors, reservations on average have slightly more jobs per resident than nearby county areas.View Full Paper PDF
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Working PaperReservation Employer Establishments: Data from the U.S. Census Longitudinal Business Database
January 2017
Working Paper Number:
CES-17-57
The presence of employers and jobs on American Indian reservations has been difficult to analyze due to limited data. We are the first to geocode confidential data on employer establishments from the U.S. Census Longitudinal Business Database to identify location on or off American Indian reservations. We identify the per capita establishment count and jobs in reservation-based employer establishments for most federally recognized reservations. Comparisons to nearby non-reservation areas in the lower 48 states across 18 industries reveal that reservations have a similar sectoral distribution of employer establishments but have significantly fewer of them in nearly all sectors, especially when the area population is below 15,000 (as it is on the vast majority of reservations and for the majority of the reservation population). By contrast, the total number of jobs provided by reservation establishments is, on average, at par with or somewhat higher than in nearby county areas but is concentrated among casino-related and government employers. An implication is that average job numbers per establishment are higher in these sectors on reservations, including those with populations below 15,000, while the remaining industries are typically sparser within reservations (in firm count and jobs per capita). Geographic and demographic factors, such as population density and per capita income, statistically account for some but not all of these differences.View Full Paper PDF
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Working PaperEstimating the Local Productivity Spillovers from Science
January 2017
Working Paper Number:
CES-17-56
We estimate the local productivity spillovers from science by relating wages and real estate prices across metros to measures of scienti c activity in those metros. We address three fundamental challenges: (1) factor input adjustments using wages and real estate prices, along with Shepards Lemma, to estimate changes metros' productivity, which must equal changes in unit production cost; (2) unobserved differences in metros/causality using a share shift index that exploits historic variation in the mix of research in metros interacted with trends in federal funding for specific fields as an instrument; (3) unobserved differences in workers using data on the states in which people are born. Our estimates show a strong positive relationship between wages and scientifc research and a weak positive relationship for real estate prices. Overall, we estimate high rate of return to research.View Full Paper PDF
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Working PaperTHE IMPACT OF LATINO-OWNED BUSINESS ON LOCAL ECONOMIC PERFORMANCE
January 2016
Working Paper Number:
CES-16-34
This paper takes advantage of the Michigan Census Research Data Center to merge limited-access Census Bureau data with county level information to investigate the impact of Latino-owned business (LOB) employment share on local economic performance measures, namely per capita income, employment, poverty, and population growth. Beginning with OLS and then moving to the Spatial Durbin Model, this paper shows the impact of LOB overall employment share is insignificant. When decomposed into various industries, however, LOB employment share does have a significant impact on economic performance measures. Significance varies by industry, but the results support a divide in the impact of LOB employment share in low and high-barrier industries.View Full Paper PDF
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Working PaperTHE DYNAMICS OF LATINO-OWNED BUSINESS WITH COMPARISIONS TO OTHER ETHNICITIES
January 2016
Working Paper Number:
CES-16-33
This paper employs the Michigan Census Research Data Center to merge three limited-access Census Bureau data sets by individual firm and establishment level to investigate the factors associated with the Latino-owned Business (LOB) location and dynamics over time. The three main LOB outcomes under analysis are as follows: (1) the probability of a business being Latino-owned as opposed to a business being Asian-owned, Black-owned, or White-owned; (2) the probability of new business entry and exit; and (3) LOB employment growth. This paper then compares these factors associated with LOB with past findings on businesses that are Asian-owned, Black-owned, and White-owned. Some notable findings include: (1) only Black business owners are less associated with using personal savings as start-up capital than Latinos; (2) the only significant coefficient on start-up capital source is personal savings and it increases the odds of survival of a Latino business by 4%; (3) on average, having Puerto Rican ancestry decreases the odds of business survival; and (4) LOB are relatively likely to start a business with a small amount of capital, which, in turn, limits their future growth.View Full Paper PDF
