Growth of the U.S. Latino population translates into policy interest of how business owner, firm, and local characteristics may be different for Latinos. To explore ethnicity and business ownership, this study merges restricted-access data from 11 million businesses. Multinomial logistic regression estimates how characteristics associate with the probability of the business being Latino-owned relative to White-owned, Black-owned, or Asian-owned. There are differences in the source and amount of start-up funds, gender, and the sector of the business. The differences depend on the group to which Latinos are being compared; for example, manufacturing firms are less likely to be Latino owned than White owned, but more likely to be Latino owned than Black owned. An exception is college education and rurality; Latino owners are consistently less likely to be college educated and more likely to locate in rural areas than the other ethnic minorities. The results should be helpful to groups attempting to improve Latino business outcomes.

Estimates of publicly suppressed and unrevised regional economic data produce error and potentially bias statistical inference. This article estimates measurement error in suppressed cell estimated data sets (SCEDs) relative to unsuppressed federal administrative data. In a cross section, coefficient estimates based on relatively aggregated SCEDs are attenuated by about 31%, increasing to 50% in panel data. Coefficient estimates based on less-aggregated SCEDs are not generally reliable. A review of the limited options for identification emphasizes both the systemic limitations suppression places on research inference and the value of retrospective revisions in confidential data, highlighting the

Access to financial capital is vital for the sustainability of the local business sector. Recent research on the restructuring of the financial industry from local owned banks to interstate conglomerates has raised questions about the impact on local economies, especially in rural areas. We examine the impact of bank ownership concentration on business formations, continuations, and deaths in metropolitan, micropolitan, and rural non-core U.S. counties. Using limited-access Census data, we find that local bank concentration is positively related to business births and deaths, or churn, in rural counties, but the opposite effects occur in metropolitan areas. We demonstrate robustness to several specifications and spatial spillover effects.

Researchers and citizens alike question the long-term impacts of the shale oil boom on local communities. Studies have considered the boom's effects on employment, income, mobility, and human capital acquisition. This research specifically builds on research considering shale effects on secondary schooling. Using county-level data from Texas, we investigate two questions: (1) Has the latest oil boom led to a reduction in local high school graduation? (2) Is this effect different for immigrants, a group potentially vulnerable to local wage effects? Findings indicate insignificant overall effects; however, local oil drilling increases immigrant high school dropout rates.

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Business location research often focuses on evaluating specific policies or explaining outcomes for a particular region. Further, the micro-foundations of random profit maximization supporting manufacturing location analysis often lack the intuitive nature of demand thresholds. While this article maintains these micro-foundations, it introduces a unifying concept of profit pools and examines how proximate supply/cost factors determine potential local manufacturing size. The approach avoids a number of limitations associated with other locational choice models. Restricted-access establishment-level data from the Longitudinal Business Database along with secondary data sources produce a model to estimate county-level contributors to outcomes of manufacturing establishment growth and consolidation. The analysis offers improved methods and accuracy for modeling establishment location outcomes, including accuracy in measuring industry size and methods for choosing among various count data distributions. The locational factors associated with county-level potential for manufacturing vary in magnitude and significance depending on the type of manufacturing, while affirming the importance of agglomeration across manufacturing types.

We model the locational determinants of nine categories of healthcare services in the contiguous United States using restricted access federal establishment data. These data enable close examination of rural health services, which are subject to suppression in publicly published data sources. After reviewing differences in public and unsuppressed restricted data and testing underlying data generation processes for each healthcare industry, including the Poisson, negative binomial, and their zero-inflated counterparts, we estimate marginal effects for four categories of independent variables: place-based factors, financial access, characteristics of population, and industry interdependencies.Findings show establishments are less likely to be found with high concentrations of Medicare and Medicaid recipients, while agglomerations are associated with more establishments. Nonemployer establishments serve a broader spectrum of people, but the rural poor still experience less access to health care. K E Y W O R D Scentral place theory, demand threshold, health care, hospital, Medicaid, microdata, physician, outpatient, regional economic development | INTRODUCTIONThe U.S. healthcare industry is increasingly gaining national policy attention as it consumes 17.9% of gross domestic product, as opposed to 9% in other rich countries (American Health Care, 2019). Adjustments in healthcare policy need to consider not only changes in demographics and advances in technology, but also costs and potentially unrealized efficiencies associated with the characteristics of the places where healthcare services are delivered. A better understanding of characteristics associated with the location of healthcare services may be part of the healthcare policy puzzle. Rural areas bear particular attention in policy debates due to population decline, aging population, and low patient densities per square mile, all of which may increase per patient costs. Rural health services may thus be more likely to be sparse or concentrated, with only one or two providers. Lack of competition may also play a role in costs.Rural healthcare services play an essential role in maintaining the physical and mental health of rural residents and are often major economic drivers in their local communities (Gaynor et al., 2015). However, the industrial organization of healthcare services has changed markedly over the past several decades, primarily due to rural depopulation and changes in healthcare policies starting in the early 1980s. This shift in the market structure of health services, including

A frequent theme in regional science is exploring the determinants of business establishment locations. We briefly review the theoretical perspectives motivating several frameworks underpinning locational determinant analyses. We summarize and review trade-offs involved in established and emerging econometric techniques that researchers use to analyse locational determinants. We conclude with opportunities for future research, including understudied frameworks, potential data sources and methodological developments.