Reservation Nonemployer and Employer Establishments: Data from U.S. Census Longitudinal Business Databases
December 2018
Working Paper Number:
CES-18-50
Abstract
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.
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.
:
data census,
employee,
proprietorship,
entrepreneurship,
sector,
establishment,
agriculture,
rural,
warehousing,
farm,
population,
indian,
geography,
use census,
geographic,
nonemployer businesses
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.
:
Service Annual Survey,
Federal Reserve Bank,
Longitudinal Business Database,
Federal Reserve System,
Retail Trade,
Department of Agriculture,
Wholesale Trade,
Geographic Information Systems,
Educational Services,
North American Industry Classification System,
American Community Survey,
Technical Services,
Public Administration,
Integrated Longitudinal Business Database,
Arts, Entertainment,
Accommodation and Food Services,
Agriculture, Forestry,
Health Care and Social Assistance
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 'Reservation Nonemployer and Employer Establishments: Data from U.S. Census Longitudinal Business Databases' are listed below in order of similarity.
-
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
-
Working PaperA Note on the Locational Determinants of the Agricultural Supply Chain
July 2021
Working Paper Number:
CES-21-16
Over the past several decades, an increasing share of the agricultural supply chain is located beyond the farmgate, implying that some set of economic factors are influencing the location decisions of food and agricultural establishments. We explore the location decisions of several food and agricultural industries for employer and non-employer establishments by expanding on the empirical implications of Carpenter et al. (2021)'s demand threshold models. While Carpenter et al. (2021) focus on methods to estimate these industries' demand thresholds using restricted access data, we focus on expanding the interpretations of their empirical research and explore additional industries along the agricultural supply chain using their refined methods. Results highlight the influential role of the Land Grant University system for specific establishment types, the importance of diverse industries within local economies, and the changing rurality of the agricultural supply chain.View Full Paper PDF
-
Working PaperBusiness Dynamics on American Indian Reservations: Evidence from Longitudinal Datasets
November 2020
Working Paper Number:
CES-20-38
We use confidential US Census Bureau data to analyze the difference in business establishment dynamics by geographic location on or off of American Indian reservations over the period of the Great Recession, and subsequent recovery (2007-2016). We geocoded U.S. Census Bureau's Longitudinal Business Database, a dataset with records of all employer business establishments in the U.S. for location in an American Indian Reservation and used it to examine whether there are differences in business establishment survival rates over time by virtue of their location. We find that business establishments located on American Indian reservations have higher survival rates than establishments located in comparable counties. These results are particularly strong for the education, arts and entertainment, wholesale and retail, and public administration industries. While we are not fully able to explain this result, it is consistent with the business establishments being positively selected with respect to survival given the large obstacles necessary to start a business on a reservation in the first place. Alternatively, there may be certain safeguards in a reservation economy that protect business establishments from external economic shocks.View Full Paper PDF
-
Working PaperMom-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.View Full Paper PDF
-
Working PaperCivic Community in Small-Town America: How Civic Welfare is Influenced by Local Capitalism and Civic Engagement
December 2001
Working Paper Number:
CES-01-19
The aims of this paper are twofold: first, to gain a fuller understanding of factors that foster community cohesion and contribute to the residents' social and economic well-being; and, second, to move beyond previous research that used larger spatial units such as states, counties, or aggregates of counties and to focus instead on American small towns (population 2,500-20,000). The data on small towns are drawn from public-use files and from confidential microdata from various economic censuses. From these sources we construct measures of locally oriented firms, self-employment, business establishments that serve as gathering places, and associations. The local capitalism and civic engagement variables generally perform as hypothesized; in some cases they are related quite strongly to civic welfare outcomes such as income levels, poverty rates, and nonmigration rates. We discuss the advantages and disadvantages of working with place-level data and suggest some strategies for subsequent work on small towns and other incorporated places.View Full Paper PDF
-
Working PaperPast Experience and Future Success: New Evidence on Owner Characteristics and Firm Performance
September 2010
Working Paper Number:
CES-10-24
Because the ability of entrepreneurs to start their own businesses is key to the success of the U.S. economy and to the economic mobility of many disadvantaged demographic groups, understanding why entrepreneurship activity varies across groups and geography is an increasingly important issue. As a step in this direction we employ a novel set of metrics of business success to the growing literature and find great variation across groups and metrics. For example, we find that black-owned firms grow slower than white or Asian-owned firms. However, once we condition on firm survival, the differences disappear. Interestingly, we also find differences across groups in their start-up histories. For example, Asian-owned firms are less likely than white-owned firms to have started-out as nonemployers but firms owned by all other minority groups, as well as women-owned firms, are more likely to start-out without employees.View Full Paper PDF
-
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
-
Working PaperEndogenous Growth and Entrepreneurial Activity in Cities
January 2003
Working Paper Number:
CES-03-02
Recent theories of economic growth have stressed the role of externalities in generating growth. Using data from the Census Bureau that tracks all employers in the whole U.S. private sector economy, we examine the impact of these externalities, as measured by entrepreneurial activity, on employment growth in Local Market Areas. We find that differences in levels of entrepreneurial activity, diversity among geographically proximate industries, and the extent of human capital are positively associated with variation in growth rates, but the manufacturing sector appears to be an exception.View Full Paper PDF
-
Working PaperSpatial Mismatch or Racial Mismatch?
June 2007
Working Paper Number:
CES-07-16
We contrast the spatial mismatch hypothesis with what we term the racial mismatch hypothesis - that the problem is not a lack of jobs, per se, where blacks live, but a lack of jobs into which blacks are hired, whether because of discrimination or labor market networks in which race matters. We first report new evidence on the spatial mismatch hypothesis, using data from Census Long-Form respondents. We construct direct measures of the presence of jobs in detailed geographic areas, and find that these job density measures are related to employment of black male residents in ways that would be predicted by the spatial mismatch hypothesis - in particular that spatial mismatch is primarily an issue for low-skilled black male workers. We then look at racial mismatch, by estimating the effects of job density measures that are disaggregated by race. We find that it is primarily black job density that influences black male employment, whereas white job density has little if any influence on their employment. This evidence implies that space alone plays a relatively minor role in low black male employment rates.View Full Paper PDF
-
Working PaperSmall Business Pulse Survey Estimates by Owner Characteristics and Rural/Urban Designation
September 2021
Working Paper Number:
CES-21-24
In response to requests from policymakers for additional context for Small Business Pulse Survey (SBPS) measures of the impact of COVID-19 on small businesses, we researched developing estimates by owner characteristics and rural/urban locations. Leveraging geographic coding on the Business Register, we create estimates of the effect of the pandemic on small businesses by urban and rural designations. A more challenging exercise entails linking micro-level data from the SBPS with ownership data from the Annual Business Survey (ABS) to create estimates of the effect of the pandemic on small businesses by owner race, sex, ethnicity, and veteran status. Given important differences in survey design and concerns about nonresponse bias, we face significant challenges in producing estimates for owner demographics. We discuss our attempts to meet these challenges and provide discussion about caution that must be used in interpreting the results. The estimates produced for this paper are available for download. Reflecting the Census Bureau's commitment to scientific inquiry and transparency, the micro data from the SBPS will be available to qualified researchers on approved projects in the Federal Statistical Research Data Center network.View Full Paper PDF
