ABSTRACT. This paper examines the effect of state incentives for data center development, specifically sales and use tax exemptions. Thirty-three states had adopted such exemptions by 2024 up from 18 in 2014 and 2 in 2004. The gradual introduction of the incentives offers an opportunity to evaluate their effects on data center development as measured by number, size, and energy usage. The paper uses staggered difference in differences design, including baseline results using the method of Callaway and SantAnna (2021) with various formulations and comparisons to other staggered difference in differences methods. The paper finds that sale and use exemptions had a positive effect on data centers as measured by square footage but not by other measures. This finding is relatively robust to method used. Further results from the analysis suggest a “but for” effect of the incentive of approximately 50%, possible first mover advantages, and weakening in incentive effectiveness in recent years.

ABSTRACT. This project examines the economic effects of new capital investment on neighborhood residents and businesses, leveraging the industry and geographic variation embedded within the New Markets Tax Credit (NMTC) Program. The NMTC has directed billions of dollars toward capital projects in economically distressed areas, offering a unique opportunity to study how such investments influence local labor markets, residential dynamics, and business activity. Using restricted-access longitudinal microdata from the U.S. Census Bureau—including the Longitudinal Employer-Household Dynamics (LEHD) and Longitudinal Business Database (LBD)—we distinguish between the outcomes of incumbent and entering economic agents. Employing a suite of complementary difference-in-differences methodologies, including staggered and instrumental variable designs, we estimate the causal effects of capital investment on three key dimensions: changes in average UI earnings and employment mobility among baseline workers; shifts in neighborhood-level conditions such as worker earnings, residential mobility, and local prices; and transformations in local industrial composition through establishment births and deaths by industry. This approach provides a detailed understanding of how capital investment shapes economic trajectories at the neighborhood level.

ABSTRACT. We explore the complex interaction between Tax Increment Financing (TIF) and school district funding using Oklahoma City as a case study. TIF is a widely used mechanism for funding local economic development projects. Some portion, possibly 100%, of the incremental growth in tax revenues collected in a designated geographic area is used to pay for authorized projects in the TIF district. The diversion of school taxes to TIF districts impacts school funding. Oklahoma’s school aid formula equalizes school funding by bringing districts to a minimum level of support. Some, but not all, ad valorem taxes count against districts in the state aid formula. However, if 100% of incremental revenues are captured by a TIF, then schools receive less funding. We estimate how much school tax revenue is diverted from the 17 TIF projects in OKC that overlap with three school districts. We collect detailed information about the ad valorem increment values, millage rates, and the TIF increment splits, allowing us to backout the value of school taxes that are in the increment for each TIF District and School District. We can give a rough estimate of the reduction in overall school funding and funding for each school district from OKC’s TIF projects. Understanding the extent to which TIF programs impact school funding is important for both school funding and TIF project assessment.

ABSTRACT. This paper examines the relationship between banking consolidation and innovation across U.S. states from 1994 to 2020. We find a nonlinear relationship between banking consolidation and innovation: marginal effects are positive at low to moderate levels of concentration but become negative at high levels. We also document substantial regional heterogeneity, with stronger effects in the Northeast and South and weaker effects in the Midwest and West. Finally, when distinguishing between types of innovation, we find that banking consolidation tends to foster incremental innovation rather than disruptive innovation, suggesting that greater concentration may inhibit more radical forms of technological progress.

ABSTRACT. Previous research shows the importance of entrepreneurship for sustained local economic development, especially for lagging remote regions (see, for example, Stephens and Partridge, 2011). This study examines the impact of rural higher education institutions on entrepreneurship in rural America - measured by business formation, self-employment, and venture capital flows - with special attention to rural Appalachian Regional Commission (ARC) counties. We also examine whether different types of rural higher education institutions have any spillover effects on the entrepreneurial ecosystems of neighboring counties. Findings reveal that the mere presence of a university does not consistently predict local entrepreneurship in the county or in neighboring counties. Instead, counties with higher levels of human capital and quality of life, factors often associated with college towns, experience significantly higher rates of entrepreneurial activity. This suggests that rural universities may support entrepreneurship through more indirect channels, such as boosting local amenities and educational attainment, than through direct startup generation for the local area. While public narratives often spotlight young tech founders, data show that most entrepreneurs are older, highlighting a disconnect between student populations and new business creation. We conclude that rural higher education institutions are vital for building the conditions that support entrepreneurship, but their presence alone is not sufficient. To fully leverage these institutions as engines of rural innovation, more targeted and nontraditional programs and policy interventions are needed to embed and connect them within broader entrepreneurial ecosystems locally.

ABSTRACT. This paper examines why U.S. consumer spending evolved so differently across states and industries following national shocks. Using weekly credit-card spending data from 2020 through 2024, we track spending dynamics across ten major consumption sectors, including groceries, restaurants, healthcare, and travel. We develop a dynamic empirical framework in which sectoral spending growth is driven by observed regional fundamentals alongside latent national factors that capture broad movements in real economic activity and macro-financial conditions. Our model combines three key features. First, national shocks evolve dynamically through persistent common factors. Second, sectoral spending growth follows a VAR(1) structure, allowing shocks to propagate across industries over time. Third, states’ exposures to national shocks are governed by sector-specific spatial factor loadings, reflecting geographic clustering in economic structure, labor markets, and balance-sheet conditions. This interaction between dynamic national forces, cross-sectoral transmission, and spatial dependence generates substantial heterogeneity in local spending responses to common shocks. Empirically, we show that the recovery in consumer spending was primarily driven by vaccine rollout and labor-market reattachment, which delivered large and persistent gains in sectors such as food services, transportation, and healthcare services. We also find that medical debt relief operated differently from direct stimulus payments. While debt relief reduced immediate spending on medical supplies, it increased spending on broader service categories, suggesting that alleviating balance-sheet stress encourages households to reallocate spending toward discretionary activities. Overall, our results demonstrate that uniform national policies can produce highly uneven local outcomes, with effects that depend critically on regional industry composition and spatial exposure to aggregate shocks.

ABSTRACT. The USDA, Economic Research Service’s Natural Amenities Scale is a measure of the physical characteristics of a county that enhance the location as a place to live. Though it has been widely used since its release in 1999, improvements in data availability and collection provide an opportunity for the Natural Amenities Scale to be updated for more modern research and policy uses. The updated Natural Amenity Scale enhances the original measure by incorporating high-resolution spatial and climate data, expanding coverage to Alaska and Hawaii, and possibly offering more geographically detailed data at the census tract or pixel levels. This new scale focuses on natural amenities, such as temperate climate, forest cover, and water access, using data from NASA, the Census Bureau, and the Forest Service. Designed to be flexible and transparent, it will support research and policy analysis on rural migration, infrastructure investment, and economic development, providing a more accurate and policy-relevant tool for understanding rural quality of life and residential preferences. Engagement and discussion from the SRSA audience will refine and enhance our contribution through input from researchers who might use the product.

ABSTRACT. There is broad agreement that spatial variation in rural net migration over the past 50 years has reflected the location of natural and outdoor amenities, with left-out areas subject to population outmigration as traditional rural industries (agriculture, mining, and manufacturing) shed jobs. Despite their importance, the measurement of local amenities has remained problematic, as what is an amenity is often assessed by its relation to migration or population change—essentially the dependent variable. Roback (1982, 1988) developed an argument that local amenity values are embedded in higher housing values and/or lower area earnings. In this paper we draw on the Census 2000 special tabulations of county owner-occupied single-unit houses with limited land and without business activities attached, regress this group’s median house value on its median homeowner income (both loge), and use the residual as the county’s relative amenity value. Among the findings are: migration to the South is not generally amenity migration; landscape (mountains, some forest, and water area) has a strong amenity value, but recreation employment does not; climate and landscape have strong correlations with amenity values and together explain 52% of the variance in home amenity value while other variables, including seasonal housing and recreation employment, add only 6% to the total.

ABSTRACT. Long-distance trail systems have become increasingly important drivers of rural tourism, recreation-based development, and regional economic vitality. International corridors such as Spain’s Camino de Santiago and the United Kingdom’s Way of St. Cuthbert, alongside major U.S. rail-trails such as Idaho’s Trail of the Coeur d’Alenes, demonstrate how connected trail infrastructure can attract visitors, generate sustained spending, and support employment growth in rural communities. Yet despite growing investment in trail expansion and connectivity, relatively little research has applied consistent, scalable methods to quantify the economic potential of long-distance trail systems across diverse regions. This research investigates the economic impacts of long-distance trails using a methodology adapted from recent national-scale impact assessments of the Great American Rail-Trail. Trail use will be estimated through a combination of observed infrared trail counter data and statistical interpolation models calibrated with counter networks from completed trail segments. Following established approaches, the analysis will distinguish between trips and individual users, apply empirically grounded visitor-share assumptions (defined as users traveling from at least 50 miles away), and estimate the proportion of overnight versus day-use visitors, recognizing that multiday trail users generate substantially higher expenditures. Methodologically, the project draws on regional impact modeling and recent advances in spatial econometrics to assess how trail-based tourism interacts with broader patterns of rural economic resilience. Because recreation economies vary widely in their dependence on visitor demand, the analysis will explore whether trail-oriented regions exhibit greater adaptability and recovery capacity during economic downturns and demand shocks. By integrating long-distance trails into contemporary debates on sustainable rural tourism and regional development strategy, this research provides evidence to guide policymakers, planners, and community organizations seeking to leverage trail corridors as enduring economic assets for rural prosperity. Visitor spending profiles are constructed from the trail economics literature and total visitor spending is entered into IMPLAN to estimate direct, indirect, and induced economic impacts in terms of jobs, labor income, GDP contribution (value-added), and state and local tax revenues. Particular emphasis is placed on evaluating the potential economic gains from expanding and improving the Trail of the Coeur d’Alenes as part of a broader long-distance heritage and recreation corridor. By combining comparative international trail examples with rigorous visitor estimation and input–output modeling, this project provides actionable evidence for policymakers, rural communities, and recreation planners seeking to leverage trail investments as enduring engines of rural tourism development and regional economic resilience.

ABSTRACT. As industrial policy drives new waves of foreign direct investment (FDI) into the U.S., rural areas are becoming key destinations. Using synthetic control, difference-in-differences, and propensity score matching, I examine whether rural FDI translates job growth into higher incomes. Evidence from Kia Motors’ \$1.2 billion investment in Troup County, Georgia, and a national panel of rural counties (1995–2019) shows that FDI raises employment—by 13–16\% locally and 3\% nationally—but has no average effect on income. Gains occur where housing and labor markets are strong, suggesting FDI must be paired with policies that improve housing supply, mobility, and absorptive capacity.

ABSTRACT. This paper provides the first systematic evidence on the local economic impacts of food manufacturing plant closures across Midwestern counties between 2010 and 2024. Using synthetic difference-in-differences, I find that a food plant closure reduces total county employment by about 8.1 percent for strongly treated counties, equivalent to an average loss of 528 jobs compared with an average layoff size of 418. Manufacturing employment falls as expected, and non-manufacturing employment erodes more gradually, suggesting spillover effects that accumulate over time. The unemployment rate spikes immediately after closures and remains elevated for several months. The effects are uneven, with employment losses disproportionately large among minority groups, especially Hispanic and Black workers. These groups also experience local population decline. Food manufacturing plant closures have important local economic impacts, including multiplier effects that extend beyond directly displaced workers and unequal burdens within and across rural and small-town counties.

ABSTRACT. This paper introduces a practical hybrid framework for forecasting population impacts of industrial projects in small rural counties. Population forecasting is inherently uncertain, and the challenge is vastly magnified in small areas, where even small migrations can substantially affect population levels. Nevertheless, large industrial projects require local governments to produce tangible population projections to guide infrastructure planning and service provision, yet no widely accepted framework exists for rural counties experiencing sudden economic shocks. To address this gap, the study integrates a Hamilton–Perry demographic baseline with a discrete migration component derived from an IMPLAN input–output model to translate project-induced employment into population change. Employment impacts are converted into scenario-based population projections using explicit assumptions, including resident capture rates, household multipliers, and adjustments for local employment trends. The framework is demonstrated in Lafayette County, Arkansas, where emerging lithium development is expected to generate substantial labor demand.

ABSTRACT. Land use and land cover (LULC) change plays an important role in shaping the food-energy-water (FEW) nexus in urban areas by altering resource demand, availability, and trade-offs. Despite increasing awareness of FEW interlinkage in achieving socio-economic and environmental goals, limited research has examined the tradeoff between LULC change and FEW outcomes across multiple spatial scales. This study assessed the influence of LULC change on FEW nexus in the Kentucky River Basin, over three decades (2002, 2012, and 2022). This study assessed the impacts of LULC change on the FEW nexus in the Kentucky River Basin over three decades (2002, 2012, and 2022). We employed Google Earth Engine to map LULC change, the InVEST Annual Water Yield model to assess hydrological dynamics and hydropower potential, and Multiscale Geographically Weighted Regression (MGWR) to analyze spatially varying relationships between land use, food availability, water yield, and energy potential. The results revealed spatial variability between LULC and food availability across the basin. The Bluegrass region exhibits a positive relationship between food availability, agricultural and developed areas, while the southern part of the basin shows a negative impact. Agricultural land use shows a significant negative relationship with water yield, suggesting that increased water use associated with agricultural activities reduces water yield. However, agricultural land contributes relatively little to hydropower potential, while developed and barren lands contribute immensely to potential energy generation. These findings highlight the spatially explicit trade-offs among food production, water resources, and energy potential driven by LULC change, underscoring the need for integrated land-use planning to enhance food security, diversify energy systems, and enhancing long-term water-resources sustainability

ABSTRACT. India is one of the few countries engaged in licit opium cultivation under strict government regulation and a structured licensing system in the three Indian states of Madhya Pradesh, Rajasthan, and Uttar Pradesh. As per the Central Bureau of Narcotics (CBN), an agency responsible for India's licit opium production through licensing, India is the only country authorized under the United Nations Single Convention on Narcotic Drugs (1961) to produce opium gum.

Numerous regulatory concerns have surrounded licit opium cultivation in India, foremost among them is the diversion of opium from legal production channels to illicit markets, where it can be processed into heroin and other narcotics. In response, the CBN adopted a forewarning policy in 1998 to reduce diversion risks and improve regulatory compliance. Under this policy, farmers were notified in advance that they would be required to meet a Minimum Qualifying Yield (MQY)—defined as a minimum quantity of opium (in kg/ha)—in order to remain eligible for a cultivation license in the subsequent year. In 2019–20, the MQY regime was formally replaced by a morphine-based criterion known as the Minimum Morphine Yield (MMY), which had been piloted alongside MQY in 2018–19. This policy shift aimed to align incentives with pharmaceutical objectives by encouraging higher morphine concentration in the harvested gum, rather than simply maximizing raw opium volume. This study presents the first empirical evaluation of the forewarning policy’s evolution—specifically, its impact on farmer productivity and its spatial spillover effects across villages.

We employ a stochastic frontier framework to estimate productive efficiency among Indian opium farmers across three distinct regulatory regimes: No Forewarning (NF, 1996–1997), MQY (1998–2017), and MMY (2018–2021). Each regime represents a different institutional configuration that likely shaped farmer behavior and production technology. The NF period lacked formal yield benchmarks, often leading to inefficiencies and uncertainty in procurement. The MQY regime introduced explicit yield thresholds to encourage compliance and productivity. The MMY regime, by contrast, reoriented incentives toward pharmaceutical quality by conditioning license eligibility on morphine content rather than total yield. Preliminary results indicate that the MMY period is associated with consistently higher technical efficiency compared to the two earlier regimes.

ABSTRACT. In this paper, we develop a new way of looking at the New Delhi, India, air pollution regulation problem that pays attention to both the ecological and the economic aspects of this problem. We first construct a theoretical model of air quality in New Delhi. We then show how the dynamic and stochastic properties of air quality in New Delhi can be used to derive two criterion functions for a regulator that are ecologically meaningful. Finally, using these two criteria, we discuss a probabilistic approach to the determination of the optimal length of time during which air quality regulations are in place. In our approach, the objective of the regulator is to maintain the ecological and economic viability of air quality in New Delhi in the long-run.

ABSTRACT. Harmful algal blooms (HABs) are naturally occurring events in both freshwater and marine environments, characterized by excessive algal growth that can negatively impact human and natural systems (Berdalet et al., 2016; Fleming et al., 2002; Reif et al., 2023; Stumpf et al., 2022; Turley et al., 2022). In Florida, red tide (Karenia brevis; occurs in coastal and marine environments) and blue-green algae (cyanobacteria; occurs in freshwater environments) events are common HABs, causing human health issues, changes in water quality, decreased property values, and significant economic losses across sectors such as accommodations, commercial fishing, and water-related recreation (e.g., Ferreira et al., 2023; Fleming et al., 2002; Watkins et al., 2008). In 2018, Southwest Florida experienced both a red tide event along the Gulf of Mexico coast and a blue-green algae event that initiated in Lake Okeechobee and spread to connected waterways (Di Liberto, 2018; Liu et al., 2022; Weisberg et al., 2019). This study estimates the economic impacts of these concurrent HAB events in Lee County, Florida by applying a hedonic property model using a semi-parametric approach. We apply our identification strategy leverages the distinct spatial and temporal patterns of these two bloom events to quantify their individual and interactive effects on property values. Our empirical specification uses a split sample approach specification, comparing the sales prices of HAB-impacted vs. not impacted properties based on both spatial and temporal treatments (Banzhaf, 2021; Butts, 2023; Zhang et al., 2022). This study makes two contributions to the literature. First, we will provide novel evidence on how homeowners respond to concurrent environmental risks with similar characteristics but distinct impacts. Second, we examine whether the interaction of multiple environmental risks leads to rational or irrational market responses. The results and methodology from our study can be applied outside of Florida to other regions that are subject to multiple types of HABs and other coastal and aquatic water quality impairments.

ABSTRACT. We study spatial variation in forestry activity across Oregon counties using a two-sector quantitative spatial equilibrium model that links local labor market outcomes and inter-county trade frictions to housing-market tightness, local productive capacities, and place-based attractiveness. The model combines a tractable geography of trade with a shared housing market and a smooth migration channel, so workers reallocate across counties in response to real income and local conditions without requiring knife-edge utility equalization. Using observed county-by-sector wages and employment together with trade-cost matrices, we invert the model to recover three sets of fundamentals: (1) county-by-sector productivity, (2) a quality-adjusted measure of housing-market tightness, and (3) sector-specific amenity shifters that capture persistent differences in county attractiveness beyond market outcomes. These recovered fundamentals are the core empirical output and provide a transparent decomposition of why forestry employment concentrates where it does. With them in hand, the model becomes a counterfactual engine that simulates forestry-relevant scenarios such as changes in trade costs, sector-specific demand or technology shifts, and housing or land-use constraints, quantifying impacts on wages and employment as well as spillovers to economically linked counties and reallocation between forestry and other work. This approach links place-based data to a general-equilibrium structure where impacts are inherently spatial and interconnected. The approach supports policy-relevant scenario analysis for natural resources, making it possible to quantify not only local effects but also cross-county spillovers and redistribution driven by trade linkages and worker sorting.

ABSTRACT. Higher electricity prices disproportionately burden low-income households because they consumer a larger share of their household income. This study examines the relationship between energy burden and income inequality in the United States. A Spatial Durbin model is applied to a cross-section of 3,144 counties in the U.S to analyze how changes in electricity bills impact various measures of inequality. The analysis controls for household income, education attainment and racial composition. Preliminary results indicate an inverse relationship between energy burden and the GINI coefficient, as well as a positive relationship between income inequality and the proportion of Black and Native American populations. By focusing on county-level disparities, this paper seeks to determine whether energy costs disproportionately burden lower-income households and contribute to widening inequality at the regional level. The findings offer insights into the economic consequences of energy affordability and provide policy implications on how energy pricing may impact social and economic disparities.

ABSTRACT. Geographic disparities in access to postsecondary education continue to shape workforce development outcomes in rural and underserved regions. This study examines how education deserts, defined as areas with limited proximity to public institutions of higher education, interact with broadband access to influence workers’ willingness to pay (WTP) for alternative workforce credentials. Using survey data and a discrete choice experiment from agricultural and food system workers across the United States (n=321), we estimate a mixed logit model to examine preferences for credential choice and to estimate individual-level WTP. We then regress WTP on key covariates to assess how digital infrastructure conditions modify credential preferences.

Results from the mixed logit model reveal strong overall preferences for full, industry-recognized, and stackable certificates, indicating substantial demand for high-commitment workforce credentials. However, regression analyses show that education desert status is associated with a large negative WTP discount for full, industry-recognized certificates relative to the base. Following model estimation, we computed predictive margins to examine the joint effects of education desert status and broadband access. Preliminary results show that in education deserts, predicted willingness to pay shifts from a discount of roughly 70 percent without high-speed internet to a premium exceeding 130 percent with high-speed broadband. In contrast, broadband access is not associated with statistically meaningful percentage differences in WTP among respondents outside education deserts.

These findings suggest that digital infrastructure can partially offset geographic barriers to education, but only where broadband access is sufficiently high-quality. Rather than serving as a universal substitute for proximity to educational institutions, broadband appears to generate its greatest economic value in regions where physical access constraints are most binding. The results highlight the importance of coordinating broadband investment and workforce credential design as complementary regional development strategies, particularly in education desert regions.

ABSTRACT. How does the industry in which people work affect their migration intentions? This question is central to regional economic development, as declining industries have long influenced the fortunes of rural communities by driving outmigration. We revisit this age-old issue with a novel, unique individual-level survey on people’s migration intentions conducted in 2024. We use t-tests and Ordinary Least Squares (OLS) to explore how sectoral differences in employment affect migration intentions over the 12-month period following the survey. Results indicate that, as expected, people employed in agriculture, mining, or utility sectors were more likely to intend to move; somewhat surprisingly, the same was true of working in the accommodation and food services sector, which generally are performing better than the extractive industries. Wholesale trade workers and those working for scientific, technical, or educational services were more attached to the current place of residence. Demographic characteristics like sex, age, household size, income, and educational attainment also played significant roles. To account for the heterogeneity in these demographic characteristics, we use Propensity Score Matching (PSM) to match workers across sectors with similar demographic profiles. With the matching estimation, sectoral employment was less likely to affect migration intentions, suggesting that demographic factors, rather than the sector differences of employment, primarily drive people’s migration intentions. These findings may be useful insights in designing place-based policies in the future.

ABSTRACT. This study investigates how population aging affects savings rates in Brazil, explicitly accounting for spatial interactions and the hypothesis of the second demographic dividend. Using municipal-level data from 2000 to 2010 and applying spatial econometric techniques, we examine whether aging processes in Brazilian microregions influence capital accumulation, while highlighting regional heterogeneity and potential spillover effects across neighboring municipalities. Contrary to the predictions of the traditional life-cycle hypothesis, the results indicate that population aging is associated with higher savings rates. This relationship is driven primarily by indirect spatial effects rather than by local demographic changes alone. Estimates from a Spatial Durbin Model (SDM) reveal that spillover effects from neighboring municipalities are substantial and, in many cases, exceed direct effects, suggesting the presence of social interaction and learning mechanisms consistent with behavioral approaches to saving behavior. These findings provide empirical support for the second demographic dividend hypothesis in a developing country context and underscore the importance of incorporating spatial dimensions into demographic–economic analyses. From a policy perspective, the results suggest that coordinated regional strategies may enhance the positive macroeconomic effects of population aging by amplifying savings and capital accumulation dynamics.

ABSTRACT. We study the role of traditional religion in the origins of private entrepreneurship in China. Our focus is on the historical and contemporary influence of a prominent regional Chinese wealth god, Wutong. We leverage the facts that (i) in traditional Chinese folklore, the God of Wealth governs the distribution of wealth, and (ii) a policy reform in 1895 eased restrictions on private enterprise establishment in China. We construct a unique dataset on temples devoted to the Wealth God to capture a more ingrained culture of wealth worship in some regions. Combining an instrumental variable approach with a difference-in-differences framework, we find that the 1895 liberalization reform led to a greater number of new private enterprises in prefectures with a Wealth God culture. Moreover, the influence of the Wealth God shows strong persistence. The Wealth God culture still affects the contemporary incidence of registered new businesses, occupational choice favoring entrepreneurship, and attitudes towards income and wealth across regions. This paper helps improve our understanding of the enduring impact of previously overlooked cultural and religious factors on entrepreneurship and regional disparities within China. It provides evidence on the role played by the regional-cultural context for the result of policy reforms.

ABSTRACT. Rural entrepreneurship is a critical driver of economic development, wealth-building, and community resilience, yet rural regions often lack standardized, data-driven frameworks to assess ecosystem health. This study introduces the Rural Entrepreneurship Index, a comprehensive diagnostic tool developed to measure entrepreneurial activity across three core pillars: business dynamism, innovation and growth, and entrepreneurial capacity. Integrating eleven indicators—including business entry and exit rates, patent intensity, venture capital per capita, and self-employment—the Index employs a robust principal component analysis (PCA) methodology.

ABSTRACT. Regional economic development strategies commonly treat a county's physical assets as the county's assets, implicitly assuming that local presence implies local benefit. This paper challenges that assumption by introducing the External Ownership Index (EOI), a parcel-level, value-weighted measure of the share of land and built assets owned by non-local entities. The EOI captures a structural condition shaping two central dimensions of regional development: local value retention and the availability of endogenous capital to support small business formation and growth. We illustrate the index using a two-county contrast in Washington State, Kittitas County, and Skagit County. These counties are selected because both are non-metropolitan counties located at similar distances from the Seattle metropolitan area, yet exhibit different ownership structures. Using descriptive indicators aligned with EOI mechanisms, we document patterns consistent with ownership-based effects: counties with higher external ownership display a larger disconnect between asset values and local earnings, income compositions suggestive of greater economic leakage, and weaker signatures of locally controlled entrepreneurial capital, such as proprietor income density and small-firm employment share. The comparison demonstrates the interpretability and policy relevance of ownership-based diagnostics. The EOI provides a replicable tool for regional scientists and planners to distinguish asset-rich regions from ownership-embedded regions, highlighting how development strategies that ignore ownership structure risk overstating local economic capacity.