ABSTRACT. The Bureau of Economic Analysis (BEA) is constantly working to expand and improve its regional statistics. In this talk, I will discuss recent improvements and additions to BEA’s published regional statistics, I will also outline ongoing research, and I will present some experimental statistics.

ABSTRACT. BEA publishes statistics on government consumption and investment expenditures each quarter at the national level but does not publish similar statistics by state. I present the progress of a research program that is developing a methodology to produce experimental statistics on government consumption and investment expenditures by state. The effort involves the computation of various components – Federal and state and local employee compensation, purchases of goods and services (by type of good or service), investment expenditures (by type of investment), and consumption of fixed capital (by type of capital) – exclusive of the activities of government enterprises. Estimates of these components are constructed using a combination of administrative data (aggregates and micro data from the Quarterly Census of Employment and Wages, and Government Contract Spending data from Department of the Treasury), survey data from the US Census Bureau, and other sources. These statistics could be used by policymakers, businesses, and other organizations to provide valuable insights into the potential impacts of a variety government policies on states or regions.

ABSTRACT. In recent years, a growing interest in the topic of income inequality has fueled demand for information on the way in which the nation’s prosperity and growth are shared across households, as a complement to published data on total income and output. This presentation summarizes the experimental methodology that BEA has developed to compute the distributions of personal income (a primary economic indicator published by BEA) for states and the District of Columbia, and exhibits preliminary statistics. The methodology allocates detailed components of state personal income to households based on household data from the Current Population Survey supplemented with other sources. The household-level data are then aggregated to generate state-level bottom-up inequality statistics, including Gini coefficients, medians, and quintile shares of state personal income. I prevent various statistics on the distribution of income by state for 2018.

ABSTRACT. New Jersey voters approved legalized gambling for Atlantic City in a 1976 referendum, making it the second state to do so after Nevada in 1931. The state explicitly leveraged the city’s regional monopoly, which it held from 1978 through 1992, on casinos east of the Mississippi River as an economic development strategy to revive the blighted seaside resort town. The literature on the economic development effects of casinos suggests that sparsely populated areas without nearby competing gambling venues tend to benefit the most. Using a difference-in-differences approach, I model the economic impact of casino legalization on the Atlantic City Metropolitan Area (Atlantic County, NJ) across five-, ten-, and fifteen-year treatment horizons. I find a significant positive impact of legalized casinos on personal income and housing prices for only the five-year treatment horizon, and significant positive impacts for payroll employment and wages across all three treatment horizons.

ABSTRACT. Florida’s Nature Coast covers a large section of Florida’s Gulf Coast, spanning the Big Bend of Florida from Wakulla County in the Panhandle to Pasco County, just north of the Tampa Bay area. The Suwannee River is a key component of this region. This river contains more than 190 freshwater springs, which help sustain the river basin’s ecosystem health, and supports a variety of aquatic recreational activities, including swimming, kayaking, and fishing. Recreational activities often induce local spending and in turn, economic activity in the region. In 2019, recreational anglers in the West Coast of Florida spent approximately $1.8 billion, accounting for the highest total for any of the regions in the United States (NOAA, 2022). Thus, it is important to understand how such recreational activities, and in particular, saltwater recreational fishing, contribute to the regional economy of the Nature Coast and how this activity might change under future fish population scenarios. The present study will estimate the economic contributions of saltwater recreational fishing in the Nature Coast region of Florida. Expenditure data on recreational saltwater fishing disaggregated by expense category (e.g., fishing equipment, lodging or accommodations, food and beverages, fuel) was collected via mixed mode survey, which included in-person intercepts at boat ramps along the Nature Coast, and through an online survey of licensed recreational anglers that fished in the region. Data were collected between July and November 2022. The fishing trip effort and expenditure data are used to test different scenarios in recreational fish populations, resulting from hypothetical environmental changes (e.g., changes in water quality, salinity, or water temperature), using a multi-regional input-output model, IMPLAN. We hypothesize that the changes in fish population drive a change in the number of fishing trips taken by saltwater recreational anglers, and will in turn affect the expenditures and the regional economic activity. The combination of primary and secondary data supports analysis of individual behavior change and its effect on the regional economy, and is a pioneer study in Florida’s Nature Coast region. Our goal is to both assess the economic contributions of saltwater recreational fishing to the Nature Coast area and, complementarily, understand the economic contributions associated with the hypothetical environmental changes and resulting adjustments to the availability of recreational fish species. This work is expected to help decision-makers understand the relationship between recreational saltwater fishing and local spending (re-spending) as well as between the promotion of recreational saltwater fishing and economic growth in the region.

ABSTRACT. Harmful algal blooms (HABs) produce dangerous toxins that are detrimental to the plants, animals, people, and ecosystems in the affected areas. Several types of naturally occurring HABs exist in the Gulf of Mexico, including those caused by the marine dinoflagellate Karenia brevis, commonly known as red tide. During a red tide event, environmental and water quality, and aesthetic and safety factors are diminished due to the toxins produced by the bloom. The compromised environmental conditions can have significant repercussions for the state of Florida, which is the top destination for marine recreational fishing in the U.S. and globally. This paper addresses the adverse economic impacts in terms of change in recreational fishing activities associated with red tide occurrences along the coast of southwest Florida.

For our empirical analysis, we combine data from the HAB monitoring database available from the FWC's Fish and Wildlife Research Institute (FWRI) and the Marine Recreational Information Program (MRIP) datasets available from the NOAA’s National Marine Fisheries Service, based on calendar dates and geographic coordinates. We use the unbalanced panel data set consisting of data from 2003 through 2019 in the framework of a difference-in-differences model. The results indicate a significant negative causal relation between an ongoing red tide and change in monthly average number of total trips taken in coastal counties in southwest Florida. The longer the red tide persists, the more negative the impacts are on recreational fishing. We also analyze the heterogeneity in impacts across different modes of fishing. We find non-shore mode of fishing to be more vulnerable to red tide events. Trips associated with shore mode of fishing get affected only when red tide continues for more than a month. Using these estimates, we calculate the broader regional economic impacts that southwest Florida experiences following a red tide event. Our work provides important empirical evidence that can help policymakers frame the need for public expenditures on programs focused on mitigation of future red tide events.

ABSTRACT. This study investigates the effects of regional childcare policy on fertility, interregional demographics, and capital accumulation in a two-region OLG model with endogenous fertility and publicly provided childcare facilities. The key feature of the model is that one region has children who cannot enter the childcare facilities (waitlisted children), whereas the other region does not have these children. The use of childcare facilities is assumed to be assigned to parents with a positive probability that decreases with an increase in ``effective" supply of the publicly provided childcare facilities. We demonstrate that tax increases to expand the total supply of public childcare facilities in the region with waitlisted children may reduce the probability of becoming a waitlisted child, increase the fertility rate in the region with waitlisted children. However, this is not applicable in all cases. The key factor shaping variation in outcomes is the regional migration, which is induced by tax increases that have negative effect on labor demand and positive effect on residence choice. The regional migration changes the number of parents in the region with waitlisted children, which is an indirect effect of the taxation policy.

ABSTRACT. Since the 2000s, there has been a rapid increase in the population of unmarried people and single-person households in Japan. This trend is particularly prominent in large cities. These changes in demographic conditions are closely related to the urban structure. Using both theoretical models and empirical analysis, this study considers the relationship between the centralization of the population and changes in demographic structure. The results indicate that unmarried single-person households working in the central city of Tokyo have a strong propensity to live closer to their workplaces. This study finds that an increasing number of people marrying later in their lives or remaining unmarried contributes significantly to the reurbanization of the population.

ABSTRACT. The availability of remote work, which dramatically increased in response to the COVID-19 pandemic, may change the location decisions of workers who no longer need to live near their place of employment. We examine how the importance of quality of life in driving population growth changed in the wake of the pandemic and sudden rise of remote work. We use a Rosen-Roback model to estimate Willingness to Accept (WTA) lower wages and Willingness to Pay (WTP) higher housing prices for amenity-rich locations (places with high quality of life) using labor markets and housing markets. Across different specifications, we find the quality of life and WTP effects on population growth during the post-COVID period (2020-2021) are roughly double the pre-COVID values. These results are strongest in micropolitan and rural areas.

ABSTRACT. “Moriarty Graduate Paper Competition” This study investigates the impact of wildfire incidents on the regional economy and demographic composition in Oregon in light of the Rosen-Roback spatial equilibrium framework in the two margins. Wildfire shocks are increasing in the extensive margin, where more areas are exposed to wildfires, and the intensive margin, where locations are more frequently exposed to wildfires. We used the synthetic difference-in-differences method and inter-temporal difference-in-differences method to estimate those treatment effects, respectively, to mitigate potential endogeneity issues arising from spatial correlation. We found that the regions newly exposed to wildfires experienced a significant decline in housing prices, population, and the share of White and elderly residents. Regarding the intensive margin, we found a strong decrease in the share of skilled workers and housing prices but no evidence of real wage change, which implies a simultaneous decline in the demand side and the production side in the affected location. This is verified in our extended analysis of the productivity effect of wildfires using IV regression which found a significant decrease in firm productivity in the affected location. These results show that wildfire shocks are detrimental to both long-term regional economic development and environmental justice.

ABSTRACT. Traffic accidents involving motor vehicles are frequent in the daily life of cities and roads worldwide. Accidents cause economic damage both for those involved in the accidents and, in some cases, damage to public property. In addition, there is a large market for insurance, vehicle repair, and even health care which benefits positively from accidents. On the other hand, accidents can contribute to more traffic congestion which can be understood as a disamenity. However, there is limited research on the external factors that cause accidents, especially in the urban environment. In this paper, I use the case of New York City (NYC) to investigate how construction sites can affect the occurrence of motor vehicle crashes. A possible explanation is that areas close to construction sites may suffer from an increase in traffic due to the movement of people, machinery, and equipment to ensure the progress of the construction thus contributing to accidents. I use the Motor Vehicle Collisions - Crashes data available on the NYC Open Data portal and the permits provided by the Department of Buildings. Using these georeferenced data, I then examine the relationship between proximity to construction sites and the number and severity of crashes.

ABSTRACT. Despite an increased policy focus on urban density and compactness over the last decades, many cities still expand outward in a discontinuous fashion, leaving some land `leaped' over during the process, which fragments natural habitats and induces extra costs to society. We contribute the first leapfrog sprawl analysis spanning across all US metropolitan areas. We develop leapfrog indices and quantify the frequency of leapfrogs and the length of the leaps over the 29 million cells newly urbanised in 380 US MSAs from 2001 to 2019 (7 images at 30m resolution). We analyze the change of these indices over time and space, then test for potential sources of leapfrogging with models using both disaggregate and MSA scale variables. We find that city size tends to increase leapfrogging but reduces the length of the leaps. A quicker urbanization has the most effect on increasing leapfrog distances, which we relate to expectations for these leaps to be filled in later on. We also find contradicting effects of density at the city and local scales, suggesting higher density cities have a push effect encouraging leapfrogging while local clusters are attractive and eventually form after leapfrogging. We find no apparent effect of income growth nor inequality that would push households further away to find affordable land. While most leapfrogging appears to be temporary on a 20 years scale at 30m resolution, its periodic volume remains a concern as well as the fact it is a dynamic process that continuously creates a fragmented pattern at the fringe.

ABSTRACT. Our paper offers a cautionary tale about home ownership. We study the differences in labor prospects after job dismissals between homeowners and renters using two waves of the Survey of Income and Program Participation (SIPP) data from 2004 to 2013. We find that on average homeowners recovered more slowly from unemployment shocks than renters in terms of earnings and wages. These differences are large and persistent in the long run but are more heterogenous in the short run when they are more affected by macroeconomic conditions. We also find that homeowners with low or negative home equity, and workers with high housing expenses relative to household income, either in the form of rents or mortgage payments, get reemployed at higher earnings. To understand our empirical results, we build an island search model with housing and human capital accumulation to quantify the offsetting channels from home ownership: housing deters relocation to labor markets with better job prospects but can serve as collateral to smooth consumption after a job loss.

ABSTRACT. BEA publishes statistics on national Personal Consumption Expenditures (PCE) at annual, quarterly, and monthly frequencies, but PCE by state at an annual frequency only. In this presentation, I will discuss experimental statistics on quarterly PCE by state that the Analysis and Research Group within BEA’s Regional Economic Accounts Directorate has computed, covering the first quarter of 2012 to the third quarter of 2022. Survey and administrative data from various statistical government agencies as well as private sources – e.g., card transaction data – contribute to the calculation of these statistics. The method is consistent with quarterly PCE from the National Income and Product Accounts and with annual PCE by state. We compute statistics for 16 aggregate expenditure categories, e.g., food services, accommodation, or gasoline stations. Quarterly PCE by state statistics have the potential to complement quarterly state personal income and GDP statistics; to provide more timely data for policy making, economic analysis, and business decisions; and to satisfy growing demand for timely spending data at a granular geographic level.

ABSTRACT. The Bureau of Economic Analysis (BEA) in partnership with the National Center for Science and Engineering Statistics (NCSES) of the National Science Foundation is developing new regional statistics in a satellite account framework to track the regional distribution of economic activity associated with R&D performance and the contribution of the R&D sector to regional economies. BEA’s satellite accounts explore new methodologies and provide enhanced, complementary economic statistics that are consistent with BEA's core statistics such as gross domestic product (GDP) but focus on a particular aspect of the economy. BEA has prepared preliminary state-level statistics of R&D value added, compensation, and employment by R&D performing sector for the 2012–2020 period. The presentation will cover the methodology used for the preliminary statistics, a first look at some of the results, and a discussion of BEA’s plans for refining and extending the statistics.

ABSTRACT. Regional wage disparities in the United States have been a topic of research for decades (Segal 1961; Roback 1982; Krugman 1991; Partridge et al. 2015) and policy makers often develop strategies with the intent of raising wages in their region. These strategies, however, are hampered by a monolithic understanding of how wage differences can arise. While there are countless reasons for why average wages vary by region, a fundamental deductive distinction can be made between regions that are concentrated in higher than average paying sectors (i.e. an above average paying industry mix) and regions that pay above the national average wages for their respective industry mix (figure 1). Therefore, two disparate regions may have the same average wage for two very different reasons; region 1 may have a relatively low paying industry mix, but they pay above average wages for those relatively low paying sectors and region 2 may have an industry mix that is concentrated in relatively high paying sectors, however those sectors in the region pay below the national average for the respective sector. Even though the two hypothetical regions may have the same overall average wage, the underlying structure of the regions economies are likely very different. Similarly, a region’s low average wage could arise from these two very disparate structural problems to varying degrees. Furthermore, the policy prescriptions for the economic development of a given region are likely very different for regions which possess a relatively low paying industry mix than for region’s with a relatively high paying mix of industries, but for which the wages paid in the region are bellow national average wages for that region.

ABSTRACT. The onset of the COVID-19 pandemic represented an immediate and large negative shock to economic activity globally. Despite the widespread impact of the pandemic, the magnitude of the shock on local economies differed significantly across space. Building on regional resilience literature, we use county-level data to identify whether a local economy’s pre-pandemic endowment of occupational skills is a significant factor in explaining both the magnitude of the initial shock and the longer-term degree of recovery. First, we utilize a novel approach to link national occupation-level skill requirements with uncensored county-level employment by industry to characterize an industry’s skill requirements for cognitive, digital, motor, and people skills. These skill requirements are used to quantify a county’s employment share in high, medium, or low skilled industries for each respective category. Results suggest that counties with higher pre-pandemic employment shares in high cognitive skill industries initially lost fewer jobs at the onset of the pandemic but experienced larger job losses further into the pandemic. Counties with higher shares of high people skill intensive jobs faced larger job losses at the onset of the pandemic but had stronger and more rapid recoveries. However, both findings are driven by non-metro counties – occupational skills had no significant impact on employment resilience in metro counties.

ABSTRACT. The last several years has seen a renewed interest in the labor force participation rates (LFPR). Since the peak in 2000 LFPR have been declining in the U.S. In 1976, U.S. LFPR was 61.3 percent. It reached a peak in early 2000 at 67.3 percent. The U.S. LFPR has been declining ever since to a low of 60.1 percent in April of 2020 (COVID related) and now stands at 62.3 percent today. However, as volatile as the overall U.S. LFPR has been over the past four decades, the individual state LFPRs have been even more volatile and diverse. Today, state LFPRs range from 71.1 percent in the District of Columbia to 54.6 percent in Mississippi. This paper looks at both the cross-sectional disparity in state LFPRs and the over-time changes in state LFPRs. The paper will explain why states experience different levels of LFPRs and why state LFPRs have changed over-time.

ABSTRACT. Immigrant entrepreneurs are critical to regional and national economies. Immigrants in the USA have higher self-employment rates than natives, and immigrants have made outsized contributions as founders of numerous highly successful firms. However, we document that immigrant self-employment rates vary considerably across areas of the USA. Our main measure is the percentage of immigrant workers in an area who are self-employed; i.e., the self-employment rate for the foreign-born. Areas with colder winter temperatures have especially low self-employment rates among their immigrant populations compared to other areas of the USA. This relationship holds for numerous sub-samples of immigrants and is not driven by any particular group. The relationship persists after controlling for numerous individual and local area characteristics. The results have important implications about the location choices of immigrant entrepreneurs.

ABSTRACT. Alfred Marshall said that firms and people in close proximity created something “in the air” that spread ideas and innovation through cities. Rather than the air, historians have instead credited a place, the coffee houses of London, with sparking the age of enlightenment. These “third places” in communities are places not just to sip coffee or get your haircut but are also places to exchange ideas. Communities with high estimated quality of life have more third places that can increase the flow of ideas and business dynamism. Using a modification of the Rosen-Roback model, we find that counties with higher estimated quality of life are associated with higher growth in business establishments (in addition to higher employment growth). Policies to address declining business dynamism may need to focus less on the sector-specific fiscal incentives associated with traditional economic development policies and more on investing in quality of life.

ABSTRACT. Economic growth, energy-related issues, digital transformations, connectivity, urbanisation, climate change are considered emerging mega trends that shape the context for policy responses to social, economic and spatial inequalities within the European Union (ESSPIN, 2022). In accordance with the corresponding challenges, territorial cohesion aims to enable equal opportunities for citizens and enterprises, so as to make the most of their territorial potentials, and brings into the spotlight the territories and their people, offering a solid background for the idea of ‘spatial justice’. It creates a fertile seedbed for those territorial policies and plans open to holistic constructions, which combine place-based with people-based prosperity. Based on this vision, the IMAJINE project funded under the EU’s Horizon 2020 programme has sought to examine the patterns and dynamics of territorial inequalities in Europe in order to formulate new mechanisms for addressing more effectively these inequalities and for promoting cohesion and spatial justice at European, national and regional scale. One of the most challenging messages resulted from this project’s findings is that “the continuation of the European Social Model and current territorial cohesion principles is only one possibility, with alternatives including greater national and regional autonomy and policy divergence, an increased emphasis on broader social and environmental wellbeing beyond economic growth, or fragmentation under pressure from cultural and political polarization” (IMAJINE, 2022, p. 14). These possible transformations have been described by four scenarios elaborated by IMAJINE for Europe in 2048 along two axes, namely economic growth (H1)/ social and environmental wellbeing (H2) and solidary (V1) / territorial autonomy (V2). This paper explores the key features of the four scenarios (Silver Citadel (H1, V1), Green Guardian (H2, V1), Silicon Scaffold (H1, V2) and Patchwork Rainbow (H2, V2)) with a spotlight on transport and mobility sector and proposes as case study one of the EU member states from Eastern Europe, Romania. It is based on an in-depth analysis combined with the synthesis and interpretation of the findings of the workshop organised by the Bucharest University of Economic Studies team of the IMAJINE project (coordinated by the paper’s author), with the support of the workpackage responsible, which examined the developments of the four scenarios for the transport and mobility field with experts from governmental agencies and local authorities, city managers, researchers. They were invited to express their views with regards to the specific aspects gravitating around three main questions: 1. Can scenarios help envisage challenges for future planning? 2. How can spatial justice and IMAJINE scenarios be incorporated into work on local transport plans? 3. What model of spatial justice would be the most beneficial to your local area? The results indicate a convergence towards the so-called “Silver Citadel” scenario, which places the emphasis on economic growth and solidarity, spatial justice being viewed as the equitable distribution of wealth between regions, including transport and mobility purposes. However, some divergent views have been expressed as well, pointing to, for example, the so-called “Silicon Scaffold” scenario, which emphasizes the economic growth and territorial autonomy, with spatial justice being interpreted as regions being able to hold on the wealth they have created. From local transport viewpoint, this opinion is associated with an increasing power expected to be gained by the growth poles in Romania that will imply more resources invested in improving transport infrastructure, with real concerns for the green component as well, but at local scale, which might increase territorial inequalities. References ESSPIN (2022). Economic, Social and Spatial Inequalities in Europe in the Era of Global Mega-Trends. https://www.esspinhorizon.eu/ IMAJINE (2022). Policy Brief: Addressing Territorial Inequalities and Promoting Spatial Justice in Europe. IMAJINE-Integrative Mechanisms for Addressing Spatial Justice and Territorial Inequalities in Europe, Horizon 2020 project. http://imajine-project.eu

ABSTRACT. This paper uses a variety of statistical and GIS techniques to map lending institutions -- banks, credit unions, ag lenders, payday lenders, etc. -- throughout the United States. First, we identify regions that are "lending deserts," which we define as populated areas that are not served by some or all types of lenders. We then use a statistical model to identify the demographic, economic, and geographic factors associated with lending deserts' existence. Finally, we attempt to identify anomalous "lending oases," which are home to lending institution(s) despite our model predicting they would be lending deserts.

This trio of descriptive analyses sets the groundwork for exploring the relationship between access to physical brick-and-mortar lending institutions and local entrepreneurship. To understand the impact of brick-and-mortar lenders (and their potential closure in declining areas), we must first understand where such institutions are -- and are not -- located. An examination of the locational determinants of lending deserts provides possible insights into why some places are better served by lending institutions than others.

ABSTRACT. Spouses of military members move often, following their partner to new military stationing assignments. These ``trailing spouses'' tend to have worse labor market outcomes relative to their more stationary counterparts. After moving, employment decreases and the spouses who remain employed have lower earnings and work fewer hours (Cooke and Speirs 2005; Meadows et al. 2016). These labor market realities, in addition to the targeting of military bases by payday lenders, increased high-interest credit use by military members and their families. To protect military members, their spouses, and their dependents, the 2007 Military Lending Act (MLA) prohibited certain lending practices by capping the annual percentage rate (APR) on all close-ended loans at 36\%, with additional amendments in 2013 and 2017. The prohibition of these financial products has consequences for the labor market outcomes of the affected spouses. We use individual-level federal administrative data to identify military member spouses and their labor market outcomes. Using variation in the timing of the policy and the concentration of payday lenders near military bases, we find that restrictions in access to payday loans reduces the amount of hours worked by military spouses, but do not affect other labor market outcomes.

ABSTRACT. The proliferation of dollar stores across the United States has spurred considerable debate in the policy arena regarding the potential effects of dollar store growth on competition, food access, public health, and overall community economic development (Karpyn, 2019). Dollar stores may fill a market gap by opening a store in a community that has no other retail options. On the other hand, dollar store entry in some markets may increase competition with local grocery stores, causing their exit or inhibiting the entry of grocery stores (Aubrey, 2019; Hawks, 2022). In this paper, we study the impact of dollar stores on community food desert status at the block-group level across the United States from 2005 to 2020, a period in which dollar stores grew exponentially and increased the sales of food and household goods. The rapid growth of dollar stores and their transition into food retail implies that they may compete more directly with food retailers, and in turn, impact U.S. household food access.

Using a machine-learning imputation method to avoid the biases associated with two-way fixed-effect (TWFE) regression models when treatment is staggered and the causal impacts vary over time and units (Souza, 2019), we investigate the heterogeneous effects of dollar store entry over space (urban and rural areas), time (by year and relative treatment time), and across subgroups of the population (by race, income, and poverty status). Relative to similar imputation methods proposed in the literature (Borusyak, 2021, Gardner2022), the machine-learning imputation approach relies on using cross-validation with the untreated block groups to build and select the optimal machine learning model, allowing us to validate model assumptions and predictive accuracy.

Using an event-study approach, we show that dollar stores have minimal impact on rural block-group food desert status. The machine-learning counterfactual shares of rural-area food deserts in post-treatment periods align nearly perfectly with the actual shares of rural-area food deserts. On the other hand, we find evidence that dollar store entry increases food desert status in urban areas. In periods following the initial year of dollar store entry, the counterfactual share of urban-area food deserts indicates that, in the absence of treatment, the share of urban-area food deserts would be lower than the actual share of urban-area food deserts. The effect grows over time, though the effects are small, increasing the share of urban-area food deserts by approximately 0.001 to 0.014. Regionally, the effects are strongest in the Midwest, followed by the Northeast and South. Dollar stores increase block-group food desert status most in areas with high poverty rates and with a larger share of the population that is Black.

ABSTRACT. Local agriculture commodity marketing cooperatives can form grain-marketing alliances to combine the marketing activities of multiple cooperatives. CoMark Equity Alliance (CEA) was formed with the goal of enhancing the profitability of its members. Cooperative members are often concerned over how the alliance operations affect the local grain basis. The grain basis effect would need to be considered when measuring the success of the alliance structure in increasing the cooperative member’s profits. This research uses difference-in-difference methods to estimate the effects of joining a coop and its effect on the hard red winter wheat basis for cooperative members. Modeling challenges include controlling for the endogeneity of the treatment (a coop self-selects into the alliance) and correlation of the grain basis between cooperative members and non-members. These issues are addressed using an instrumental-variable approach.

ABSTRACT. Where people live affects a region's economy. Urban economists have long analyzed the effects of large and densely settled regions - urban agglomerations - on the local economy, finding that people and businesses in these places tend to benefit from low transportation costs, access to large labor and consumer markets, and knowledge spillovers. In this context, rural areas are largely considered to be the sparsely populated 'other'. However, our experiences suggest that population distribution varies across rural America, with people in some rural regions densely clustered in small towns while people in other regions are thinly spread across the countryside. In this study, we develop a measure of the rural population distribution - rural agglomeration - and examine how it varies across rural America and identify what factors contribute to high or low levels of rural agglomeration. We conclude by discussing the relevance of rural agglomeration to rural development issues such as broadband, the provision of public goods and services, and entrepreneurship.

ABSTRACT. PROBLEM STATEMENT: Located in Northeastern Nevada with approximately 72% of the county’s land administered by the federal government, public land grazing plays an important part in the local economy. Total permitted AUMs in Elko County are estimated to be approximately 847,058 with 85% of the total permitted AUMs on BLM lands and the remaining 15% on USFS land. Because ranching operations have economic linkages with other sectors in the county’s economy, changes in federal grazing will have implications throughout the economy of Elko County. Of interest to local and state decision makers is not only the exogenous output change impacts of public AUM grazing on the overall Elko County economy but also on county economies throughout the state. OBJECTIVES: The primary objective of this paper is to derive the multiregional exogenous output impacts of public land grazing in Elko County. Specific objectives are a) To apply analysis by parts to estimate Elko County range livestock expenditure impacts; b) To designate the various multi-regional economies of the state of Nevada; and c) To estimate the exogenous output change impacts of public land grazing changes in Elko County, Nevada on multi-regional economies in the state of Nevada. DATA and METHODS: To derive the exogenous output impacts the IMPLAN microcomputer input-output model is used. However as shown by Darden et al. (2001) and Taylor (2019) the IMPLAN production function must be adjusted to reflect production practices and their costs and returns in Elko County, Nevada. The University of Nevada, Reno Cooperative extension range cattle budget for Elko County (Curtis et al., 2008) is used to build a vector reflecting production practices in Elko County. Employing IMPLAN procedures of “Analysis-by-Parts” (IMPLAN 2018), the county level impacts of public land grazing in Elko County were derived. Procedures outlined by Seung and Waters (2013) will be followed to estimate impacts of exogenous output changes. To derive the multi-regional impacts of Elko County public land grazing across the state of Nevada, the IMPLAN multi-regional procedure was employed (IMPLAN, 2019). The state of Nevada was split between three Metropolitan Areas, six Micropolitan Areas, and the Balance of State. RESULTS or EXPECTED RESULTS: University of Nevada, Reno cooperative extension budget (2019) was used to account for the different production practices and their respective costs and returns in Elko County. Following procedures by Taylor et al. (2019), Willis and Holland (1997) and Holland and Beleiciks (2006), budget data was placed in proper economic sectors and cost data were import purged and margined. Also, PUMS data was used to place employee compensation and proprietor income into proper household income sectors. To derive exogenous output changes, procedures outlined by Seung and Waters (2013) were followed. Employing IMPLAN multi-regional input-output procedures, the economic, employment, and labor income impacts of public land grazing in Elko County can be derived not only for Elko County but also for the three Metropolitan Areas, the six Micropolitan Areas, and the Balance of State. Of interest will not only be the total economic, employment, and labor income impacts on other areas of Nevada but the individual economic sectors in other areas of the state that have greater linkages to the Rangeland Livestock Sector in Elko County, Nevada. IMPLICATIONS: This paper will expand procedures by Taylor et al. (2019) to complete rangeland cattle impacts by employing analysis by-parts and PUMS data as well as application of procedures for analyzing exogenous output changes as well as multi-regional interindustry analysis. This paper will provide information as to the application of multi-regional exogenous output interindustry procedures provided by IMPLAN and how results can be interpreted.

REFERENCES Curtis, K., E. Brough, R. Torell, and W. Riggs. 2008. “Elko County Cow-Calf Production Costs and Returns, 2006.” University of Nevada Cooperative Extension: reno, Nevada. Darden, T., N. Rimbey, A. Harp, and T. Harris. 2001. “Regional-Level Economic Impacts of Grazing Policy Changes: A Case Study for Owyhee County, Idaho”. Presented Paper at Annual Meeting of Society for Range Management, Kailua-Kona-Hawaii. Holland. D. and N. Beleiciks. 2006. “The Economic Impacts of Potatoes in Washington State”. Department of Agricultural Economics, Washington State University. Taylor, D., N. Rimbey, and J. Tanaka. 2019. “Economic Impact of Sage Grouse Management on Livestock Grazing in the Western United States”. Western Economics Forum, Vol. 17, Nos. 1, pp: 98-110. Willis, D. and D. Holland. 1991.”Translating Farm Enterprise Budgets into Input-Output Accounts: Another Example from Washington State”. Department of Agricultural Economics, Washington State University. IMPLAN. 2018. “Economic Impact Analysis for Planning”. Retrieved from http://www.implan.com/ IMPLAN. 2019. “Multi-Regional Input-Output: A Primer, How-to-Guide and Best Practices”. Retrieved from http://info.implan.com/micro-webinar-jan-2019. Seung, C-K and E. Waters. 2013. “Calculating Impacts of Exogenous Output Changes: Applications of a Social Accounting Matrix (SAM) Model to Alaska Fisheries”, Annals of Regional Science, 51:553-573.

ABSTRACT. The theoretical literature in local public finance has emphasized the difficulty that the mobility of workers imposes on local governments attempting to implement redistributive policies, as high income workers may move to other locations to avoid higher tax rates. This result, in turn, can lead to competition between localities to attract high-income workers by setting tax rates that are inefficiently low, generating a "race-to-the-bottom". In this paper we explore whether this result holds when agglomeration economies are present and there is congestion in housing. We develop a two-region model with mobile workers of heterogenous skills, in which regional governments have an incentive to impose progressive tax policies. There are agglomeration economies through the provision of a local public good that is financed by a skill specific income tax income tax. We have three main results: (1) agglomeration leads to more progressive tax policies in the larger region and less progressive policies in the smaller region, (2) there is a negative relationship between the tax rates in each region for workers of the same skill level, implying that there is not a "race-to-the-bottom", and (3) policies that reduce congestion lead to less progressive tax rates.

ABSTRACT. Property tax incentive programs are increasingly popular tools in the economic development toolkit for local governments. While much research has focused on commercial and industrial property tax incentives aimed at job creation or recruiting outside corporate investment into cities, less attention has been paid to residential property tax incentive programs focused on neighborhood revitalization and blight reduction. Existing studies examining how these programs impact home prices have largely either focused on energy efficiency improvements or have been primarily descriptive in nature and produced inconclusive results. Given the current post-pandemic environment of low supply and high housing prices in many regions of the United States, it is crucial to analyze the effect of these programs and whether they causally contribute to higher home prices and disproportionately benefit property owners while pricing low-income residents out of the market.

I combine parcel-level spatial tax abatement data from the county auditor with home transaction data, parcel characteristic data, and ACS demographic data to construct a dataset for 2014-2019 of residential home sales across the county. I utilize propensity score matching and an expected outcomes framework to match similar homes within neighborhoods and cities and within the same sale year to achieve identification. I then perform a series of hedonic regressions with time and spatial level fixed effects to estimate the causal effect of residential tax abatements on housing prices. I find the effect of active abatements, the spillover effects on immediate neighbors, and the option value of the abatement eligibility zones themselves to be positive and significant.

After a series of spatial robustness checks, including spatial boundary analysis and placebo analysis, these effects remain persistent. Price premiums and windfalls are especially large for properties sold by institutional holders, such as development companies, banks, and investment firms, and for properties that have been flipped within the preceding 24 months. Further, I find no evidence that the incentive program increases the probability that existing residents in the sample decide to remodel their home compared to residents who are not eligible for the program. I find descriptive evidence that the incentive zones may contribute to more rapidly increasing segregation and gentrification trends than the county at large, as higher prices could incentivize existing residents to sell to more affluent buyers. Finally, applying my point estimates to the entire county, I find that the overall dollar cost of the tax incentive program in foregone revenue for schools, parks, and other county services over time exceeds the estimated property value gains for landowners.

ABSTRACT. Using a panel (1990-2020) of Wisconsin general purpose government fiscal data we test if local taxation levels dampen rates of economic growth. General purpose local governments (cities, village, towns, counties) are the unit of analysis and three sets of models are explore: an expanded Carlino-Mills, variable parameter neoclassical growth, and business formation and churn models are explored. Results suggest that "old school" notions of taxes, business climate and economic growth are no longer valid and our thinking around taxes and economic growth from a policy perspective must be rethought.

ABSTRACT. There is relatively little research on the impacts of legalization of recreational marijuana on state economic outcomes. One reason is that the first states (Colorado and Washington) did not legalize sales until 2014 and there was insufficient time to assess the impacts and/or with such few cases, external validity would be questioned. This study examines the cases in which legalization took place in the 2014 to 2018 using a synthetic control approach or fixed effects regressions. The results suggest that states that legalized recreational cannabis sales experienced slight increases in population and a shift in population share to young adults. Moreover, there is evidence that home prices increased and median household income increased. Together these suggest that there were some increases in both productivity and quality of life in these states. Further evidence suggested that these gains seem to have been concentrated in parts of the states that "opted-in" towards allowing recreational sales.

ABSTRACT. Motivated by the controversial relationship between health and economic conditions, this paper examines the impact of positive economic shocks on adult health outcomes and behaviors in US states following the fracking boom, a large unexpected economic shock. Using detailed individual level survey data that include rich information on health status and behaviors from the Behavioral Risk Factor Surveillance System (BRFSS), we estimate two-way fixed effects models controlling for observable individual characteristics. We find preliminary evidence that increases in oil and gas employment and compensation improve mental and physical health as well as reduce risky health behavior like binge drinking. We will explore potential heterogeneous health effects across demographic groups.

ABSTRACT. The past 20 years have seen a remarkable growth in the rural disadvantage. In 1999, the nonmetropolitan U.S. had an age adjusted mortality rate that was 7% higher than the rate in large metropolitan areas (with 1 million+ residents). By 2019, that gap had increased to 26 percent. Part of the explanation may lie in a growing lack of rural access to health care services, But the growth in the rural-urban health gap was most pronounced in prime working age (ages 25-54) population, suggesting that more is involved than access. We find that higher county poverty and lower education explain part of the rural county health disadvantage, but the strongest measure is ambulatory disability. Low education is associated with poor health behavior, but the strength of the disability measure suggests the presence of a deeper problem that, consistent with recent health literature, adult problems such as chronic disease often stem from economic and health problems in childhood. Indeed, our measure of ambulatory disability is strongly associated with county child poverty in 1970, even controlling for present day poverty and low education.

ABSTRACT. Over the last three decades, China has witnessed remarkable growth in its private sector, and many factors have been revealed to explain the development of entrepreneurship. However, cultural diversity has received little attention in China and other developing countries, despite its essential importance in creating new businesses has been well-documented in developed countries. Using the instrumental variable based on Card's (2001) shift-share methodology, this study investigates the effects of cultural diversity on new private firm formation between 2000-2005 in prefecture-level cities. We find that cultural diversity can significantly promote new private firm formation in China. More specifically, the promotion effects of cultural diversity matter much for the service sector, the northern and coastal regions, and small-size new private start-ups. Furthermore, the results suggest that cultural diversity can promote new private firm formation by generating newly-generated knowledge, skill diversity, and commercial and social networks. The results are robust to using the first-different, and Lewbel IV approaches. The results suggest that even more seemingly modest forms of diversity brought about by internal migrants can still have significant promotion effects on entrepreneurship in developing countries.

ABSTRACT. This study examines the employment growth for firms with user entrepreneurs in comparison with conventional entrepreneurs or non-entrepreneurs. In contrast to conventional entrepreneurs who start businesses to develop new products or services for a business opportunity or to fill latent demands in the market, user entrepreneurs develop products to satisfy their own needs and only introduce products on the market after their value has been demonstrated in non-market settings. The literature on user entrepreneurship is growing but generalizable, quantitative research on the phenomenon is sparse. This study is the first one to examine the growth performance of firms with user entrepreneurs.

This study uses the data from the 2014 Rural Establishment Innovation Survey (REIS) conducted by US Department of Agriculture, Economic Research Services (USDA ERS). The REIS provides a nationally representative sample of the population of establishments with five or more employees in tradable nonfarm sectors that will allow a fuller assessment of the importance of user entrepreneurship to the U.S. economy. We link the single-unit establishments in the 2014 REIS with their records in the 1990-2019 Longitudinal Business Database (LBD), hosted at the Federal Statistical Research Data Center, to evaluate the long-run employment growth of firms with different types of entrepreneurs. However, during the long period from 1990-2019, macroeconomic, industrial, and technological environments changed dramatically, affecting the performance of newborn firms. To avoid such macro-level confounding factors, we separate the samples into three cohorts: 1990-1999, 2000-2009, 2010-2014, each of which consists of firms whose first year with positive employment falls into the respective interval.

This study uses two modeling methods to evaluate the long-run firm employment growth. The first model is a random coefficient growth model, i.e., a multi-level model with the firm-year observations being level 1 and individual firms being level 2. For the level-1 model, depending on the length of firm-year observations, we apply a cubic polynomial model of time to firms in cohorts 1 and 2 and a quadratic polynomial model to cohort 3. The level-2 models regress the parameters in the level-1 model onto the variables for entrepreneur types and other firm specific control variables. The results of random coefficient growth models suggest that for cohorts 1 and 2, firms with user entrepreneurs have higher growth rates in the first five years than those with conventional or non-entrepreneurs, although their differences are not statistically significant. The growth rates for all types of entrepreneurs in cohorts 1 and 2 fall into the negative territory after 12 or 9 years, respectively, roughly corresponding to the period of the Great Recession. For cohort 3, the growth rate of firms with conventional entrepreneurs is lower than other types, but the limited observations in this cohort put the validity of the results in question.

The second model in this study is a quantile regression model to examine if the difference in firm employment growth between user entrepreneurs and conventional entrepreneurs vary at the upper tail of the growth distribution, compared with at the mean or median location. The dependent variable is the 5-year annualized growth rates that is regressed against the types of entrepreneurship and firm-level control variables. The quantile regression models also indicate that firms with user entrepreneurs have higher growth rates than conventional entrepreneurs in the first 5-year period, which is especially significant at the 75th quantile model for cohorts 1 and 2. However, after the first period, firms with user entrepreneurs have lower growth rates than conventional entrepreneurs.

ABSTRACT. The COVID-19 pandemic offers a natural experiment for studying the effect of childcare on female self-employment. During the pandemic, many states imposed childcare closures and capacity restrictions such that parents, especially mothers, faced increased childcare responsibilities. The time and flexibility required for childcare impacted female employment incomes with many leaving the labor force entirely during the pandemic. Yet, self-employment may have been an attractive option for women needing to earn an income and have the flexibility to care for children. We use a quasi-experimental framework, where treated counties, those facing a childcare closure policy, are matched with an untreated control group of counties to identify the effect of closure on female entrepreneurship. Preliminary results suggest that treated counties saw an increase in both the number and rate of new female-owned businesses.

ABSTRACT. State governments devote nearly $50 billion annually to economic development initiatives. Cost benefit analyses associated with subsidized economic development efforts often struggle to adequately account for the impact such efforts have on local resident communities. Using data from the U.S. Census Bureau’s Flows Mapper combined with county-level data on economic development subsidies, this research attempts to more precisely account for those benefitting from economic subsidies. Constructing migration flows allows us to measure regional, state, and county constituent attrition, accounting for the economic and political realities for urban and rural populations. From a normative standpoint, this research aims to open a conversation about whether such subsidy programs might affirm – or erode – public trust in government economic stimulus efforts. The results obtained should allow for better accountability from both researchers and policymakers.

ABSTRACT. Along with supporting jobs and creating economic opportunities, power plants provide financial support to local communities and regions that host the power plant through paying public utility tangible personal property tax. Like the other U.S. states, Ohio is undergoing an energy transition and retiring its conventional power plants. Plant closures impose diverse social and economic challenges and generate significant consequences on different sectors of the local economy. The lost tangible personal property tax paid by power plants adversely affects local governments’ revenues. Local school district funding is impacted by power plant closures and thus they may face fiscal challenges. This study aims to evaluate the impacts of power plant closures through the channel of public utility tangible personal property tax on school districts and students' achievements in Ohio. The study utilizes 2006-2019 data and applies econometrics modeling to answer the research question.

ABSTRACT. This study takes advantage of U.S. Census micro data to evaluate the spatial agglomeration of talent across U.S. regions. We identify “talent” based on the academic field of the individuals’ undergraduate education, which started being reported in the ACS Public Use Microdata Sample (PUMS) data sets in 2009. Specifically, we investigate the agglomeration propensity of STEM fields (with a focus on the computer, natural, and engineering sciences fields) relative to everything else. Surprisingly, previous research has not looked into measuring the degree of talent agglomeration based on higher education fields such as STEM or the analysis of factors that may explain it. Recent studies that consider the impact of talent on regional economic development simply assert that such individuals sort themselves in more agglomerated cities with higher degrees of agglomeration without actually measuring the extent of and differences among clusters of academic fields. Thus, this study aims to fill the gap in the literature regarding the empirics of talent concentration. Further, we identify the individual-specific and location- specific characteristics contributing to the regional concentration of individuals with higher education degrees.

ABSTRACT. Previous research, especially in the United States, suggests that increases in urban sprawl are associated with increases in obesity and other associated negative health outcomes. However, it is an open question about whether or not this is true in fast-growing developing countries. Using data from 2008 to 2021, this research examines the association between urban sprawl (lower population density) and obesity in the municipalities of Brazil. To deal with the fact that population density is endogenous, I use the two-stage least square instrumental variables method. The instrumental variable exploits the exogeneity of the 1960s construction plan of the federal highway system during the transition of the country's capital to Brasilia. Initial results suggest that the number of obese people - with a BMI over 25 – and the number of overweight people decrease with lower population density/more urban sprawl. This pattern is the opposite of the existing literature, especially for the United States. It also suggests that the urbanization of cities in developing countries may actually be contributing to a decline in obesity.

ABSTRACT. It is well established in the health literature that females have a higher life expectancy than males. Differences in life expectancy are attributed to factors such as employment, rurality, poverty, race, environment, and geographic location. However, they can also be due to biological and social differences between sexes. The literature has established that the difference between male and female life expectancy has been decreasing. However, what is causing this change is yet to be studied. In this paper, we analyze which factors influence the difference between male and female life expectancy in the United States. While individual characteristics such as race, income, physical activity, and health are essential to understanding differences in life expectancy, community factors such as rurality, job composition, and food access also play a role. Using spatial econometrics and data from government and academic sources, we consider how both community and individual characteristics influence the difference between male and female life expectancy. Preliminary results indicate biological and health behavior factors are important in explaining the sex gap in life expectancy, while personal and economic factors have a small relationship to the sex gap. Only a few community factors were found to explain some of the sex gap: the social capital index and being surrounded by noncore counties increased the sex gap, while fast food establishments were associated with a decrease in the sex gap.

ABSTRACT. A number of research studies have used natural experiments to measure changes in geographic accessibility to abortion clinics in the US, have estimated causal effects of changes in accessibility to abortion providers. These impacts include reductions in the observed abortion rate, increases in births, teen marriages, and maternal mortality, impacts on educational and career outcomes, and likelihood of bankruptcy and other financial harm. The negative impacts on women’s lives from lack of access to abortions are normally found to be much larger in minority populations. This paper measures the road network distances and estimated travel times from each Census block group to the nearest abortion procedure provider before the repeal of Roe, as well as after under using the state regulations on abortion at the end of 2022. We use these changes in distances to estimate marginal effects for causal studies that have also measured marginal affects in terms of road network miles, and then summarize several other expected impacts using other studies that used less precise measurement of “access”. We discuss how the estimates found in this paper are often “worst case scenarios”, due to several expected market responses in the long run such as movement of existing clinics to new locations, and access to abortion in Canada and Mexico.

ABSTRACT. When house sale price is inversely related to the proportion of Black neighborhood residents, it may be inferred that people prefer—and are willing to pay more-- to live in neighborhoods without Black neighbors. The literature on neighborhood racial tipping presumes that White home buyers, compared to Black home buyers, are willing to pay less for houses in neighborhoods when the proportion of Black residents increases. We investigate whether preferences for living in neighborhoods with Black neighbors varies across the distribution of house prices within a single housing market and if the relationship is non-linear in relation to neighborhood minority share. We find that accounting for within-market variation in the relationship between neighborhood race and house price results in evidence for neighborhood racial bias in house prices in most housing markets and an additional economic penalty incurred by Black homeowners in the presence of neighborhood tipping. Price declines are larger in lower-priced segments of the housing market. If price discounts are interpreted as evidence for willingness to pay to avoid Black neighbors, our results suggest that this prejudicial behavior is widespread across US housing markets and may significantly impede the growth in housing wealth for residents of communities of Color. Results are discussed considering existing policies related to housing and economic mobility.

ABSTRACT. Previous work suggests that there are employment and compensation benefits to non-English speaking workers clustering together across the United States (Blake and Walter, 2021). This paper fuses such results on the effects of linguistic clustering with the popularized gravity literature that models, in a variety of contexts, how impacts diminish across geographic distance. We model the labor market effects of being a non-native English speaker as a function of the distance to the next nearest cluster of workers who speak the same language. Preliminary results provide support for our hypothesis that economic benefits stemming from one's linguistic network are stronger as distance to nearest other cluster rises, though this is not universally true. Our results add a layer of complexity to a non-English speaker's choice of location as economic benefits from linguistic networks rise with in-network size, but can rise or fall from this baseline given proximity to otherwise similar clusters.

ABSTRACT. This study contrasts the methodologies of two measures of school labor costs, the Comparable Wage Index for Teachers (CWIFT) and the Florida Price Level Index (FPLI). There are four main results. 1) Including all occupations as does the FPLI, not just those requiring a bachelor’s degree as does the CWIFT, improves accuracy. 2) Controlling for factors other than occupation, possible with the American Community Survey (ACS) data used by the CWIFT, improves accuracy. 3) Using the Occupational Employment and Wage Survey (OEWS) which covers many more workers than the ACS, as done by the FPLI, improves accuracy. 4) While it is not possible to simultaneously use the OEWS data and control for variables other than occupation, conditional on including all occupations the difference in accuracy between using the OEWS data and controlling only for occupation or using the ACS data and including additional controls is small.

ABSTRACT. The National Center for Science and Engineering Statistics and the Census Bureau are currently examining the feasibility of producing a synthetic public use microdata file that would preserve the statistical moments in the Annual Business Survey while maintaining confidentiality. This presentation will outline the threats to confidentiality that exist even with synthetic data in the form of re-identification of source respondents. These threats are unique to establishment data, which differ from the widely used PUMS files of individuals and households. Most critically, geographic specificity in combination with sector membership at levels of aggregation that would be analytically interesting (e.g., substate geography and a 2- or 3-digit NAICS) would likely present unacceptable levels of re-identification risk. An alternative approach would be to replace explicit geographic identifiers with a summary of place attributes that would make geolocating source respondents impossible. This raises the question: What place attributes should be prioritized for inclusion in a blue-sky differentially private public use microdata file of business establishments? Ideas from session participants will be solicited along with discussion of possible use cases.