ABSTRACT. This study examines the impact of the Main Street Program (MSP) on housing markets in rural counties across ten U.S. states from 1990 to 2023. Using an event study design and a staggered Difference-in-Differences approach, the research analyzes the causal effects of MSP adoption on home prices and single-family housing construction. The findings reveal a significant and sustained increase in the county Home Price Index following MSP implementation, with effects peaking around eight years post-adoption. However, the study finds no statistically significant impact on single-family home building permits. These results suggest that while the MSP enhances property values and economic attractiveness in treated areas, its influence on new construction activity is limited. The research provides valuable insights for policymakers considering downtown revitalization as a strategy for stimulating rural housing markets and local economies, highlighting the need for complementary policies to address potential affordability concerns.

ABSTRACT. Despite growing emphasis on enhancing quality of life to attract residents as an economic development strategy, there is limited empirical evidence into which specific community characteristics households prioritize over others when making relocation decisions. This study investigates how a broad range of community attributes—identified through the Community Capitals Framework—influence household relocation decisions. Drawing on residential sorting models, this paper conceptualizes relocation as a utility-maximizing decision in which households weigh the expected utility of staying in their current location against that of moving to a new location. Households are assumed to relocate when the expected utility of the new location exceeds the utility of staying. Taking this conceptual framework to data, I model county-to-county migration flows based on differences in wages, housing costs, and local amenities of the destination and origin counties. Understanding which community attributes most influence relocation decisions is critical for policymakers and community leaders to effectively target investments that will attract new residents and foster community prosperity.

ABSTRACT. This paper examines quality of life in a modified Rosen-Roback model (Weinstein, Hicks and Wornell, 2023) spatial equilibrium model. The focus is on in Appalachian Regional Commission Counties from 1980 through 2019. We test the relative effect of quality of life on population change in Appalachian Counties, with a focus on more recent patterns of population adjustment, and offer evidence of differential effects of quality of life in Appalachian and non-Appalachian counties.

ABSTRACT. In recent years, the United States has experienced a significant rise in Hepatitis C virus (HCV) prevalence after a period of relative stability. Injecting drugs and sharing needles have been identified as key drivers of HCV transmission, with states reporting higher opioid and drug use consistently showing elevated rates of HCV infections. This research hypothesizes that buprenorphine dispensing affects HCV rates. Using zip code-level data from 2013 to 2022, the study pursues three objectives: (1) to analyze the spatial and temporal dynamics of HCV infections in relation to buprenorphine dispensing in Ohio; (2) to assess the association between buprenorphine dispensing and HCV infection over time in Ohio; and (3) to explore these associations within both rural and urban regions of the state.

ABSTRACT. Food insecurity remains a persistent public health concern in the United States. In 2023, 18 million US households experienced food insecurity at some point (Matthew et a. 2023). However, food insecurity extends beyond insufficient access to food as it is closely linked to adverse health outcomes (Gundersen & Ziliak, 2015). Yet, the causal relationships between food insecurity and health outcomes at the county level remain unknown. This study examines the causal effect of food insecurity on mental and physical distress using county-level data for 2016 and 2018. Data used is from various sources: the County Health Rankings & Roadmaps (CHRR), the Small Area Income and Poverty Estimates (SAIPE), and the County Business Patterns dataset. The relationship between food insecurity and health outcomes is bidirectional. Mental illness can reduce an individual’s employability and productivity in the labor market, leading to decreased earnings and fewer resources for food acquisition (Jensen et al., 2023). Moreover, individuals with mental illnesses may face barriers in accessing government assistance programs designed to improve food security. To address potential endogeneity, we employ an instrumental variable (IV) approach, using the number of grocery stores per county as an instrument for food insecurity. The results indicate that a 1% increase in the food-insecure population leads to a 16.2% increase in mental distress and a 31.7% increase in physical distress. Further, we conduct a robustness check by re-estimating the models using an alternative measure for health outcomes—the number of poor mental and physical health days—confirming that the effects remain statistically significant. Also, rural counties exhibit significantly higher distress levels than their urban counterparts. Access to exercise opportunities and social associations emerges as a mitigating factor, reducing distress levels. These results underscore the urgent need for policies aimed at reducing food insecurity, particularly in vulnerable communities. Expanding access to affordable food sources, increasing economic stability, and enhancing social and recreational infrastructure could play critical roles in improving food security and health outcomes.

ABSTRACT. A shortage of healthcare providers in the United States continues to overburden the healthcare system. This concern is especially pronounced in reproductive health, where delayed care can exacerbate preventable adverse outcomes. To expand the obstetric workforce in the short-run, Full Practice Authority (FPA) for Certified Nurse Midwives (CNMs) and Certified Midwives (CMs) has often been suggested as a viable solution to increase access in a safe and effective manner. This study examines the effects of FPA on maternal health outcomes, particularly for Medicaid beneficiaries. Using Medicaid claims data from 22 states (four treated states during the study period and 18 control states), I employ difference-in-differences and event study methodologies to estimate the causal impact of FPA on CNM/CM utilization and maternal outcomes. The findings show that FPA significantly increases CNMs/CMs utilization among Medicaid mothers and reduces cesarean section rates for low-risk singleton births. By enabling CNMs/CMs to practice independently, FPA policies has the potential to alleviate provider shortages, optimize resource allocation, and improve maternal healthcare quality. These results underscore the potential of FPA to reduce disparities, enhance maternal outcomes, and inform evidence-based policy decisions aimed at strengthening the maternal healthcare system.

ABSTRACT. The COVID-19 pandemic led to the closure of Social Security Administration (SSA) field offices, disrupting access to Social Security Disability Insurance (SSDI) and Supplemental Security Income (SSI). Despite the expansion of remote services, SSDI and SSI applications declined during the pandemic and remained below pre-pandemic levels. Using difference-in-differences and event study frameworks, this research analyzes the effects of field office closures on disability outcomes, leveraging variation in SSA field office accessibility across states. Initial findings indicate that SSA field office closures significantly reduced SSDI and SSI applications, determinations, and allowances. These results highlight the critical role of physical access in facilitating timely disability claims and underscore the vulnerability of administrative systems during crises.

ABSTRACT. Pharmacy plays a crucial role in the U.S. health care system and often goes beyond the traditional prescription services, as it can also provide vaccination, immunization, diagnostic, preventive and urgent care among others. Inspired by the urgent need for combating the COVID-19 pandemic, authorities are increasingly considering pharmacies as strategic community partners for promoting public health and handling health-related emergencies.

Although community pharmacies are large in number and distributed across broad geographical areas, there is evidence suggesting that their risk-adjusted accessibility to all U.S. residents are not equitable, when risk factors such as age, income, transportation, and health conditions are considered (Chen and Suen, 2023; Guadamuz et al., 2021; Pednekar and Peterson, 2018; Qato et al., 2014). In fact, researchers argue that disparities in accessing community pharmacies are worsening over time and could be an overlooked contributor to disparities in the public health outcomes. Therefore, there is a pressing need for research and development in accessibility to community pharmacy, and pharmacy deserts have emerged as a promising study.

This research uses Jefferson County, Kentucky as a case study to explore an enhanced Pharmacy Accessibility Index (PAI) by integrating additional socio-economic factors relevant to potential pharmacy users. Many existing measures of pharmacy accessibility heavily rely on distance metrics and demographic data at the neighborhood level (Guadamuz et al., 2021; Pednekar and Peterson, 2018). By employing these standardized accessibility measures, we identified non-pharmacy deserts in areas lacking quality pharmacy services in Jefferson County. Our enhanced PAI incorporates several key components: the spatial distribution of pharmacy services and potential users, the quality of pharmacy establishments assessed through Google reviews, and the actual usage of pharmacies based on smartphone location data from Placer.ai. This multifaceted approach allows for a more comprehensive assessment of pharmacy accessibility, considering not only geographic proximity but also service quality and user behavior.

References: Pednekar, P., & Peterson, A. (2018). Mapping pharmacy deserts and determining accessibility to community pharmacy services for elderly enrolled in a State Pharmaceutical Assistance Program. PloS one, 13(6), e0198173. Qato, D. M., Daviglus, M. L., Wilder, J., Lee, T., Qato, D., & Lambert, B. (2014). ‘Pharmacy deserts’ are prevalent in Chicago’s predominantly minority communities, raising medication access concerns. Health Affairs, 33(11), 1958-1965. Guadamuz, J. S., Alexander, G. C., Zenk, S. N., Kanter, G. P., Wilder, J. R., & Qato, D. M. (2021). Access to pharmacies and pharmacy services in New York City, Los Angeles, Chicago, and Houston, 2015-2020. Journal of the American Pharmacists Association, 61(6), e32-e41. Chen, Xueming and Suen I-shain (2023). Analysis of Spatial Disparity of Pharmacies in Virginia, USA. Journal of Urban & Regional Analysis, 15(1): 105-124.

Audience will learn two things. (1) The limitations of quantitative analysis: All quantitative measures, including accessibility indices, have inherent limitations. Applications of quantitative methods must consider local contexts and information that cannot be quantified. (2) Spatial inequity: This research provides another real-world example illustrating the presence of systemic inequity stemming from historical development and economic decision-making, which directly impacts public health.

ABSTRACT. This study investigates the impact of urban greenspace on worker wages, applying the compensating differentials framework to analyze greenspace as a utility-enhancing amenity within urban areas. To proxy for greenspace, we use two measures. The Normalized Difference Vegetation Index (NDVI) measures the level of greenspace vegetation derived from remote sensed top-down satellite images. We also use a novel data source – Google Street View images— to calculate the percentage of perceived greenspace in cities, reflecting the greenspace that individuals are likely to observe. Using data from 950 urban U.S. counties from 2010 to 2019, we find a significant negative relationship between greenspace and wages, indicating that workers may accept lower wages in exchange for improved access to greenspace, thereby maintaining overall utility. To address endogeneity concerns, we use historical land cover data as an instrumental variable, bolstering the robustness of our results. We also examine how greenspace contributes to urban economic dynamics by increasing city employment and fostering the establishment of new businesses. These findings emphasize greenspace’s economic value in shaping livable, attractive cities and provide actionable insights for urban planning and policy.

ABSTRACT. Cox’s Bazar City, Bangladesh's premier coastal tourist destination, has undergone substantial urban expansion and environmental transformation in recent decades. Monitoring these changes is critical for understanding the interactions between urbanization, land surface processes, and ecological sustainability. This study employs multi-temporal remote sensing data to quantify the spatiotemporal dynamics of land use/land cover (LULC), vegetation health (Normalized Difference Vegetation Index, NDVI), land surface temperature (LST), urban heat island (UHI) intensity, and built-up area expansion (Normalized Difference Built-up Index, NDBI). Landsat imagery from 1984 to 2025 is utilized to extract these indices, ensuring methodological consistency and comparability across time periods. The Global Human Settlement Layer (GHSL) dataset is integrated to improve built-up area classification. Advanced image processing techniques, including atmospheric correction, spectral index computation, and machine learning-based classification, are applied to generate high-accuracy change detection maps. The results are expected to reveal significant urban expansion, declining vegetation indices, and increasing surface temperatures, particularly in high-tourism areas. By linking geospatial patterns with urbanization trends, this study provides a comprehensive assessment of the environmental consequences of rapid urban growth in Cox’s Bazar City, offering critical insights for climate resilience and urban sustainability planning.

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 difference-in-differences specification, comparing the sales prices of HAB-impacted vs. not impacted properties observed during and outside of the HAB event windows (Banzhaf, 2021; Butts, 2023) for a 20-year panel of daily water quality, property, and HAB event data. This study makes two contributions to the literature: i) this study provides new evidence on how homeowners respond to concurrent environmental risks with similar characteristics but distinct impacts; and ii) 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. Broadband connectivity plays an increasingly pivotal role in shaping economic and social outcomes, including those in the healthcare sector. We investigate the relationship between broadband expansion and health outcomes, leveraging county-level panel data from all U.S. counties. Our results indicate that improved broadband access is associated with statistically significant increases in vaccination rates and reductions in smoking prevalence. Moreover, broadband expansion correlates with a decline in the share of individuals reporting poor or fair health. However, we also observe a modest rise in both the number of mentally unhealthy days and sexually transmitted infection rates. These findings suggest that while broadband infrastructure investments may enhance health literacy and access to preventive care, they may also introduce externalities related to mental and sexual health. Policymakers should account for these heterogeneous effects when formulating strategies to optimize the socio-economic returns to broadband expansion in the healthcare domain.

ABSTRACT. Broadband access is increasingly recognized as essential infrastructure for a range of critical functions, including business operations and entrepreneurship, necessary to connect consumers and producers in today’s economy. As such, it has the potential to have the largest impact on places that have been geographically separated from economic opportunities, namely rural and remote regions. Despite this latent potential in rural America, these geographies have largely lagged behind metropolitan areas in broadband infrastructure investments, exacerbating economic disparities. However, recent investments have significantly boosted rural broadband access and adoption. Our findings, using a propensity score matching technique, indicate that both higher broadband adoption rates and small, local internet service providers (ISPs) in rural counties are associated with faster growth in new businesses, increased self-employment (likely from opportunity rather than necessity entrepreneurship), and higher per capita incomes. We find evidence to suggest that existing residents are likely accruing these gains (as opposed to newcomers to town) and that broadband access may be reducing underemployment in rural areas and increasing entrepreneurship. Conversely, areas with the lowest broadband access experienced population losses, lower income growth, and were more likely to see a decline in the number of businesses.

ABSTRACT. Difference-in-differences (DID) estimation that identifies the capitalization of amenities through changes in housing prices has been widely used. However, there are concerns about how to interpret the estimates of capitalization from DID as changes in welfare. Here we show how this divergence between capitalization and welfare might arise. Following Banzhaf (2021), we estimate the capitalization of school redistricting in a DID framework that incorporates general equilibrium effects. When comparing estimates from our generalized DID model to the conventional DID model, we find significant differences in both the capitalization effects and welfare changes associated with the school redistricting.

ABSTRACT. There are many measures of place-based quality of life and much debate over what factors should go into such a measure. Yet there has been little consideration for the rigor and appropriateness of the method used to develop them with past studies most often using aspatial additive combinations of different place-based characteristics. We explore six different methods for developing a composite index of place-based quality of life. Specifically, we compare geographically weighted principal component analysis, spatial principal component analysis, and spatial Bayesian factor analysis with their aspatial counterparts using U.S. county-level data. We assess these methodologies, both conceptually focusing on their underlying assumptions and the context of their application focusing on commonality of results. Specifically, we compare and contrast county quality of life ranking across methods, rural-urban, and geographical regions. We find that quality of life measures are generally highly correlated across methods, but accounting for spatial dimensions greatly impacts the rankings of individual counties. Further, we find that the choice of method most greatly impacts quality of life measures in the most urban and rural counties. This study emphasizes the importance of sensitivity analysis, particularly in urban and rural environments, to effectively understand and address the nuanced factors influencing quality of life.

ABSTRACT. This study tests the effect of manufacturing decline on quality of life in five Rustbelt States (IL, IN, MI, OH and WI) from 1970 to 2019, using a modified Rosen-Roback model as described by Weinstein, Hicks and Wornell, 2023). The goal of the study is to identify whether declines in factory related disamenties affect quality of life over time, and whether these can be attributed to reductions in emissions (Kahn, 1999) or if there are other regional characteristics which correlate with changing manufacturing presence and quality of life.

ABSTRACT. In community development, the debate between “people follow jobs” and “jobs follow people” has gained substantial attention. Deller (2021) noted that enhancing a community’s livability to attract people can catalyze economic development—aligning with the “jobs follow people” hypothesis, and communities are increasingly shifting towards a people-centric strategy. However, traditional measures of livability often rely on outcome-based indicators such as life expectancy and poverty rates, which may fall short in capturing the dynamic interplay between community livability and individual decision-making. These measures also fail to adequately convey the connection between people’s actions in response to community attractiveness and the subsequent economic development. Our study proposes using Bayesian spatial factor analysis to construct a latent “livability” factor, which measures individuals’ desires to live, thrive, and commit to a community as indicated by their revealed preferences. We assume that the underlying livability of a community drives individuals to make decisions or take actions. To capture this, we consider a variety of revealed preference indicators: in-migration, out-migration, local and state attachment, commuting patterns, business dynamics, homeownership, and birth rates. Additionally, we account for the spatial correlation within communities, an aspect often overlooked in existing literature. Our findings highlight significant geographic variations in community livability across rural and urban areas in the U.S., revealing disparities that are vital for policymakers and community developers to consider. This beyond-growth measure of community livability offers a distinct perspective on why some communities thrive while others do not.

ABSTRACT. The intersection of agricultural biotechnology and rural economic development presents a unique opportunity to evaluate the potential economic benefits of gene-edited insulin production in rural communities. Advances in gene-editing technology now enable dairy cows to produce human proinsulin in milk, raising important questions about consumer acceptance, rural economic impact, and policy implications. This study investigates three questions: 1) How do rural and urban consumers differ in their willingness to adopt gene-edited insulin? 2) Does trust in agriculture influence adoption differently across rural and urban populations? 3) Could gene-edited insulin create new economic opportunities for rural agricultural communities?

Using a nationwide consumer survey (N≈400), ordinal, and mixed logit models, this research examines the influence of rural identity, trust in agriculture, and economic development considerations on perceptions of gene-edited insulin. Preliminary findings suggest that rural consumers who trust the agricultural sector are significantly more likely to perceive gene-edited insulin as safe. Economic development potential is also a key motivator for rural acceptance, suggesting a link between biotechnology adoption and rural economic diversification. Analyses using mixed logit models reveal that consumers exhibit strong price sensitivity, with a willingness to pay estimates ranging from $0.03 to $0.05 per unit for gene-edited insulin. While this premium is modest, it suggests an emerging market for gene-edited insulin, particularly among rural consumers with high trust in agriculture.

These results highlight the potential for rural job creation, farm diversification, and the integration of agricultural biotechnology into rural economies. By positioning gene-edited livestock as a biopharmaceutical resource, rural communities could benefit from new market opportunities and workforce expansion in biotechnology-driven agriculture. This research informs agricultural producers and policymakers by integrating rural economic perspectives into biotechnology policy discussions. It contributes to broader conversations on technology adoption, economic resilience, and the future of agricultural biotechnology in healthcare markets.

ABSTRACT. We estimate the causal effects of the expansion of Medicaid on rural households’ on-farm and off-farm labor supply, focusing on both the head and the spouse. The paper aims to determine the role that access to health insurance plays in shaping the labor supply of households in rural areas and their internal allocation between on-farm and off-farm jobs. Using a standard difference-in-difference approach, we find that the implementation of the ACA in states that expanded in 2014 significantly reduced the average weekly hours worked off-farm for producers compared to states that did not expand. The ACA had no significant impact on average weekly hours worked off-farm for the spouse of the producer. However, we found descriptive evidence that hours worked off-farm by the spouse have been trending downwards since 2015 in both expansion and non-expansion states, potentially driving the lack of results. While there was no statistically significant impact of the ACA expansion on the spouse’s off-farm hours of work, the proportion of spouses who report off-farm income significantly decreased after ACA in 2014 expansion states compared to non-expansion states. Similarly, the proportion of producers who report off-farm income significantly decreased after ACA in 2014 expansion states. These results appear to hold in a cohort DiD approach developed by Callaway and Sant’ Anna (2021), where we compute the standard errors as it is appropriate in the case of staggered adoption of a policy.

ABSTRACT. Historically the perception is that the economic well-being of rural communities is dependent upon a healthy farm economy. The implication for rural economic growth and development was clear: promote policies that ensure a healthy farm economy. Data from the USDA Agricultural Resource Management Survey (ARMS) clearly documents that the typical farm family in the US is highly dependent upon off-farm income. Considering all farms in the ARMS database over the 1996 to 2022 time period, the typical (average) farm household drew 84.5 percent of its income from off farms. Indeed, farms with less than $100,000 in sales, which is the dominate type of farm, a full 103.9 percent of household income came from off the farm. This means that for most farms off farm income supplemented the farm enterprise itself. The policy implication that a healthy rural economy is dependent on a healthy farm economy is essentially stood on its head. Indeed, to preserve the typical family farm, policies must be put in place to ensure access to off farm employment.

ABSTRACT. FEMA aid plays a crucial role in helping localities recover from natural disasters, yet its allocation is not always determined solely by objective measures of need. While some FEMA programs are formula-based and insulated from political influence, others allow for discretion in distribution, creating opportunities for political factors to shape outcomes. This paper examines the allocation of FEMA aid following hurricanes in Florida, analyzing the extent to which political considerations influence aid distribution. Specifically, we investigate whether swing districts receive more aid, whether districts represented by members of the president’s party benefit disproportionately, and how these patterns vary across different FEMA programs. Importantly, we incorporate detailed data on hurricane wind speeds and storm paths to assess the actual damage experienced, allowing us to identify instances where aid allocation appears inconsistent with the severity of the disaster. By combining data on FEMA declarations, aid allocations, storm impact, and the political characteristics of the areas, this study provides new insights into the extent to which disaster relief funding is shaped by electoral incentives rather than objective need. Understanding these dynamics is essential for improving the fairness and effectiveness of disaster response policies.

ABSTRACT. Hurricanes have been a major financial shock over the course of U.S. history. As of August 2023, the cumulative damage exceeded $1.3 trillion, with each hurricane causing enormous damage of $22.8 billion on average (NOAA Office for Coastal Management, 2023). In particular, empirical studies have been conducted on the increase in the frequency and intensity of hurricanes due to temperature rise, and it is predicted that the frequency and scale of hurricanes will become increasingly stronger in the future (Grinsted et al., 2013; Holland, 2012). As the scale and urgency of this threat increase, regions in future hurricane paths are likely to suffer not only direct property damage but also overall local economic impacts. In this study, we discuss the impact of the short-term impact of these hurricanes on the local economy at the county level. While some economic development officials in areas that have been at the center of larger hurricanes have identified these short-term economic impacts as positive due to the immediate response and recovery, these impacts may not be equally shared across all industries and in some industries, these impacts are actually negative. Specifically, this study aims to analyze the relationship between hurricane shocks and gross regional product (GRP) and changes in the share of employment in the agricultural sector in 17 states along the Atlantic Ocean and Gulf of Mexico from 2007 to 2022. For the analysis proposed in this study, a detailed specification of the independent variable , hurricane, is first necessary. If we simply assume that the presence or absence of a hurricane or the hurricane category experienced by a region is an external shock, it is difficult to properly capture changes in wind speed and magnitude of hurricanes, and it is difficult to measure the impact each region receives directly from the hurricane. In this study, we use the Atlantic hurricane database (HURDAT2) provided by the National Hurricane Center to create two types of explanatory variables that can reflect the characteristics of hurricanes as much as possible. Utilizing the maximum wind speed data hurricane damage index: The wind speed of each hurricane is calculated by interpolating the values of the center coordinates at 6-hour intervals using a spline function, and the hurricane damage index designed in previous studies (Strobl, 2012; Emanuel, 2011) is utilized. Second, we use two sets of data to capture the impact of hurricane treatment on the dependent variables, gross regional output (GRP) and employment. First, to obtain employment data by county, we refer to the Bureau of Labor Statistics (BLS). To make sense of the impact of employment after a hurricane shock, we use the average employment in the quarter or quarters following the hurricane. For gross regional product (GRP), the U.S. The Bureau of Economic Analysis (BEA)'s Gross Domestic Product by County and Metropolitan Area data was used, and as supplementary data, Core LMI US Gross Regional Product data was obtained using API from EMSI. Based on the data described, our study estimates the impact of hurricanes using a model that integrates the Staggered DID method and the event study. We measure the impact of exogenous shocks on different counties over multiple years and the impact of three periods before and three periods after the hurricane event on each industry. We include continuous variables (wind speed and pressure) in the regression model in addition to the presence or absence of a hurricane event to capture the impact of hurricane intensity on the regional economy. Lastly, we discuss the impact of hurricanes on county employment within the same state by comparing counties exposed to hurricanes with counties that were not exposed.

ABSTRACT. This paper extends the monocentric city model to incorporate endogenous house- hold automobile fuel choice and dwelling energy consumption. Electric vehicle (EV) tax credits lower direct energy consumption and emissions via commuting, but also cause important urban general equilibrium effects, including sprawl. This creates a substantial emissions rebound effect via larger homes, longer commutes, and greater consumption of the numeraire good, which reduces the cost-effectiveness of EV tax credits. Nevertheless, unless electricity production is heavily tilted towards coal, total household energy consumption and carbon emissions fall substantially

ABSTRACT. In this paper, we study inter-city competition between two cities A and B that use taxes to attract heterogeneous members of the creative class. Section 2 describes the theoretical framework in which there are three types of creative class members, and each type denotes a particular occupation. Irrespective of type, creative class members value local public goods (LPGs) and each city levies a tax to draw in as many members as possible by providing an apposite LPG. In this setting, we accomplish two tasks. Section 3 describes the equilibrium allocation, i.e., a tax rate for each city and an allocation of creative class members to the two cities. Section 4 compares this equilibrium allocation with the Pareto efficient allocation. Section 5 concludes and then suggests three ways in which the research described in this paper might be extended.

ABSTRACT. This study evaluates the effects of the Kansas tax experiment (2012-2017) on establishment-level payment practices as measured by the PayDex score. We use the Kansas City Metropolitan Statistical Area (MSA) as the study area because two Kansas cities are adjacent, one in Kansas and one in Missouri. Using data from the National Establishment Time Series (NETS) database, we apply a two-way fixed effects model and find that the Kansas tax experiment significantly improved timely payments at the establishment level. However, the policy effects were not long-lasting because they disappeared not long after the repeal of the tax cut in 2017.

ABSTRACT. Time zones represent an unexplored discontinuity in spatial equilibrium models in the form of increased barriers to the amenities that come with agglomeration economies. In this paper I show both theoretically and empirically that being on the "good" side of a time zone boundary is a productive amenity in a spatial equilibrium context. To show this empirically, I first exploit the change of Mercer County, North Dakota from Mountain Time to Central Time to show that there were gains in productivity by estimating the causal effect of changing time zones on individual performances in the Bismarck Marathon and Half-Marathon using a difference-in-differences framework. I find that changing from Mountain to Central Time caused a 3-4% improvement in race performance, i.e., a 3-4% improvement in productivity. To link time zones to rents, I use county-level ACS data and a regression discontinuity design approach to estimate differences in median monthly rent payments, a proxy for rents, across a time zone boundary. Here I find that rent payments are on average 2.5-3% higher on the "good" side of the boundary. Collectively these results imply that individuals living on the "bad" side of a time zone boundary can become more productive by moving to the "good" side of the boundary, but spatial equilibrium disincentives this movement via differences in rents.

ABSTRACT. Conceptualized after recent Supreme Court decisions, including the reversal of Roe V. Wade, which have devolved long-standing federal protections to the state-level, this research examines whether, and to what extent, the perceived political environment of states and localities impacts the residential decisions of college students. Using primary data collection (including surveys and in-depth semi-structured interviews with both undergraduate and graduate students) on one rural-serving college campus in the Midwest region of the United States, we find significant correlations between political ideology and a number of factors important to college students when thinking about where to live after graduation. We contextualize these findings with qualitative interview data and highlight the important policy implications of these findings.

ABSTRACT. This Study tests the effect of county level quality of life on business dynamism in the United States from 2010 to 2023. We extend Weinstein, Hicks and Wornell, 2023 to the role of quality of life in a modified Rosen-Roback model plays on business dynamics, with special focus on rural and metropolitan counties.

ABSTRACT. Prior research suggests that promoting entrepreneurship contributes to economic growth in distressed regions. While self-employment rates are generally high in non-metro areas, they are not uniform across space and demographic groups. However, research focusing on self-employment individuals in the rural U.S. remains limited. This study investigates the relationship between local social and economic factors and self-employment rates across groups, focusing on non-metro areas. Additionally, it further explores potential heterogeneity and variation among rural regions.

ABSTRACT. This paper investigates the role of broadband connectivity in driving local economic growth in Spain. Using municipal-level data from 8,023 municipalities between 2013 and 2020, we examine whether broadband availability positively impacts population and employment. The study makes two key contributions: first, it provides a comprehensive analysis over an extensive dataset, and second, it focuses on a country facing significant depopulation challenges in many regions. Employing fixed effects dynamic panel data models and spatial dynamic panel data models, we identify a positive relationship between high-speed broadband expansion and local growth. Specifically, our baseline regressions indicate that a 10% increase in broadband access leads to a 0.15% and 0.08% increase in local population and employment, respectively, in the short-term. Notably, this effect is more pronounced in small municipalities compared to larger cities. Spatial models confirm a modest but significant short-term impact of broadband on local growth, while the long-term analysis highlights differing spillover dynamics: broadband’s influence on employment is more localized, while its impact on population growth extends spatially. Our findings underscore the importance of tailoring broadband expansion policies to the specific outcomes being targeted: adopting a regional perspective for population growth and localized approach to boost local employment.

ABSTRACT. Lineberry’s underclass hypothesis suggests that areas within cities populated by people of lower socioeconomic status and/or by people of color will receive lower quality public services. Empirical tests of this hypothesis provide mixed results, with some studies finding evidence of bias in public service provision and others finding that service quality is “unpatterned” or influenced by considerations other than the race or status of community residents. Most these studies focus on a single city, raising questions about the generalizability of the results. It is often unclear whether the results indicate general patterns with respect to bias in service provision or reflect idiosyncratic aspects of service provision in a particular city.

This study draws on detailed street inventory and maintenance data from all 120 cities in Indiana covering the period from 2019 to 2022, focusing on 17 cities with the most complete data. In these data, collected according to standards set by the Indiana Department of Transportation (INDOT), street segments as short as a single block are rated for quality using a standard classification system and tagged with an indicator of the type of maintenance, repair, or repaving (if any) performed on it within a given year. Geographic data for the start and end points of each segment allow them to be matched to income, poverty, and race data at the Census Tract and/or Block Group level. These data are used to compute measures of street quality and maintenance effort at the city and census tract level and to derive measures of equity in street quality and maintenance effort for the selected Indiana cities.

An earlier version of this project, presented at the 2024 MCRSA, found evidence of class and race bias in street pavement ratings and maintenance effort when measures were computed at the Census tract level, but in many cases the direction of bias was in a direction contrary to Lineberry’s hypothesis. This version of the project conduct the analysis at the Block Group level and incorporates suggestions received at MCRSA.

ABSTRACT. The Southern Growth Policies Board in the 1970s advocated the used of substate districts as a means for development. The 1968 Virginia Area Development Act was unique in its approach, proposing a Planning District Commission that would be followed by an elected Service District Commission. Throughout the South, the substate districts were formed to align with Federal programs that encouraged regional approaches. The districts became useful to State administrations as well as the public and private sectors. The U.S. Census State Data Centers and Census planning used the organizations in each State. In 2024 the notion of a Geocode System was presented as a means of meeting the OMB Need for “a territorially exhaustive classification.” The Southern Rural Development Center territory matches the Southern Growth Policies Board territory,so it is a perfect case to consider the various ways substate districts are used by the States themselves. A Census data set based on substate districts would provide an intermediate single layer. A State would identify the substate districts, single or multi-county, which are most useful for their own purposes. Both States and Counties vary widely. The same would be expected for substate districts.

ABSTRACT. Growing world population and climate change have put increasing pressure on managing the food supply chain. Today, food production depends on inputs from many trade partners; therefore, a detailed understanding of the key components of the supply chain of agriculture and food is necessary to reduce costs, maintain a profitable production system, and anticipate potential disruptions such as the recent Trump threat to increase tariffs on Canada and Mexico. This paper applies a partial Hypothetical Extraction Method to investigate the consequences this policy would have on the supply chain of agrifood commodities in each North American country. The results indicate that, despite the former NAFTA and current USMCA trade agreements, the key links of the agrifood supply chain are mostly domestic, more especially for the USA. Supply chain linkages with USMCA trade partners do exist, but they are large for Mexico and Canada only and they converge towards the USA, especially in its financial and energy sectors. As such, new tariffs would hurt Canada and Mexico much more than the US. To reduce this market power imbalance, Canada and Mexico could create stronger supply chain linkages with other countries and with each other.

ABSTRACT. This study examines the extent to which Arizona’s agricultural production is consumed locally, addressing a critical question at the intersection of food systems, natural resource use, and economic sustainability. With a focus on 2021, we analyze the local value chains of three key commodity groups: fruit and vegetable specialty crops, feed crops, and dairy. Employing a value chain approach, we quantify local consumption across various sectors, including households, restaurants, schools, livestock, and industrial processes. Data from the USDA's National Agricultural Statistic Service, USA Trade Online, U.S. Bureau of Transportation Statistics, and the IMPLAN model inform our analysis. Findings reveal that Arizona’s production of these three commodity groups primarily met domestic demand, either through direct consumption or as inputs for value chains across the United States. These results provide insights into Arizona’s role in the national food supply chain and highlight the nuances of the "virtual" movement of resources, particularly water, embodied in domestic and international trade. This research emphasizes the importance of improved methodologies and data for understanding domestic agricultural trade, with implications for resource efficiency and sustainable food systems.

ABSTRACT. Despite the critical importance of domestic trade in agriculture, available information on sub-national trade at detailed spatial scales remains limited. In this paper, we first describe the features of available primary data sources on interstate trade and the challenges that arise in working with such data. We then develop an approach to imputing US bilateral county-to-county shipments of agricultural products based on a gravity modeling framework using interstate trade data and county-level supply and demand characteristics, taking care to account for the deficiencies in the primary trade data. Finally, we present benchmarks comparing our constructed county-to-county trade dataset to other recently available datasets describing the sub-national movement of agricultural products in the United States. In tracing the universe of US shipments of agricultural products at a fine geographical resolution, our dataset will enable researchers to address a wide assortment of research questions on important issues relating to domestic trade patterns and food supply chain vulnerability.

ABSTRACT. Congressional districts are political entities with heterogeneous trade policy preferences driven by their diverse economic structures. The representation of these interests in determining trade policy in Congress is missing in canonical models of the political economy of trade (e.g. Grossman and Helpman, 1994). We model the aggregation of diverse trade policy preferences of districts into a national trade policy. Our supply-side explanation for trade policy builds on the legislative bargaining model of Celik, Karabay and McLaren (2013).

ABSTRACT. The goal of this paper is to discuss the implications of using history as a method of establishing causation within economics. This paper begins by discussing reviewing the view propagated by Thorstein Veblen that economics should be an evolutionary science noting that the primary goal is to establish theory of explaining the causes of the development of various economics structures and practices. Next, this paper reviews criticism that the social sciences have sustained from the physical scientists, in particular Alan Sokal, that the willingness to consider the material effect of idea or believe on economic phenomena can devolve into a rejection of Cartesian thought in favor of Antifoundational thought. This paper notes how the joint work of George Lakoff and Mark Johnson can bridge this divide by adopting the framework of belief as systems of metaphor. Finally, this paper turns to the separate works of Stephen J. Gould and Judea Pearl who discuss how counterfactual speculation is the key to properly understanding cause and effect in scientific terms. The conclusion of this paper is ultimately that gaming out the results of counterfactual speculation is the key to establishing a system a metaphors that will allow for causal inference and thus establish economics as an evolutionary science

ABSTRACT. Ideological differences significantly shape how individuals perceive climate change and natural hazards, often leading to partisan divides in decisions related to these risks. Research consistently shows that Democrats are more likely to acknowledge human-caused climate change and support mitigation policies, whereas Republicans tend to express greater skepticism and resistance to such measures (Botzen et al., 2016; Long et al., 2020; Williams & Kay, 2024). These ideological differences also translate into observable behaviors: Republicans are up to 10% more likely to own homes in coastal areas vulnerable to sea-level rise (Bernstein et al., 2022).

Using voter registration data from Florida’s Division of Elections, we track over 13 million registered voters between 2022 and 2024 to examine partisan differences in natural hazard exposure. Each voter’s address is mapped to the FEMA natural hazards index, which measures expected annual economic losses at the census tract level. We then analyze how political affiliation, migration, and party registration changes affect the likelihood of residing in higher-risk areas using a fixed-effects regression framework, controlling for individual- and tract-level demographics.

Our findings reveal that, even after adjusting for relevant covariates, Republican and independent voters are more likely than Democrats to live in higher-risk census tracts. We also find notable heterogeneity across demographics: the partisan gap in risk exposure is wider among men and Black voters when comparing Democrats to independents and is larger among younger voters (under age 65) when comparing Democrats to Republicans. Furthermore, between 2022 and 2024, voters switching to Republican registration relocated to higher-risk areas, whereas those switching to Democrat moved to lower-risk areas. These patterns are especially pronounced among voters changing their affiliation between the two major parties.

Our study contributes to the growing literature on partisan ideology and geographic sorting (e.g., Brown & Enos, 2021; Bernstein et al., 2022), showing that partisan differences extend beyond climate beliefs to observable behaviors. These results highlight the role of political identity in shaping climate risk exposure, with implications for property and insurance markets, disaster relief policies, and long-term adaptation and resilience strategies.

ABSTRACT. Urban-rural disparities.

ABSTRACT. Urban Sprawl.

ABSTRACT. Quarry Fines

ABSTRACT. Superstar Employers.

ABSTRACT. Infrastructure and job accessibility

ABSTRACT. Organic Production.

ABSTRACT. Agritourism.

ABSTRACT. Parenthood and entrepreneurship.