ABSTRACT. Recent research finds that childhood neighborhoods affect adult economic outcomes, especially for children of low-income parents. Because places are shaped by both contemporary and historical factors, it is important to understand regional differences in opportunity both today and in the past. Using 1940 Census data linked to 1040 tax returns, we examine geographic differences in child outcomes experienced by cohorts born roughly 50 years apart – revealing how intergenerational persistence of status has changed over time both at the national level and at smaller geographic levels. In studying these changes, we hope to shed light on the causes of intergenerational persistence in status and inequality of opportunity.

ABSTRACT. This article investigates the contribution that federal transfer programs, such as Social Security, Medicare, and the EITC, make to reducing economic inequality between regions of the United States. Although these programs are not explicitly spatially targeted, they do have a distinct spatial footprint based on the geography of where recipients live. We show that the net effect of these programs is to make interregional inequality lower than it would otherwise be.

ABSTRACT. We study the impact of monetary policy on regional inequality using granular data on economic activity at the city- and county-level in Europe. We document pronounced heterogeneity in the regional patterns of monetary policy transmission. The output response to monetary policy shocks is stronger and more persistent in poorer regions, with the difference becoming particularly pronounced in the extreme tails of the distribution. Regions in the lower parts of the distribution exhibit hysteresis, consisting of long-lived adjustments in employment and labor productivity in response to the shocks. As a consequence, policy tightening aggravates regional inequality and policy easing mitigates it.

ABSTRACT. U.S. income inequality in the 21st century has surpassed previous historic highs from nearly a century ago. Given the corrosive social, economic, and political dynamics of inequality, it is essential to understand the underlying patterns that have driven the dramatic increase in income inequality in recent decades. We use public-use county summary files from the Decennial Census and American Community Survey to examine how patterns of inequality in rural/urban localities contribute to broader regional and national patterns in the United States. The research objectives of this paper are threefold. First, we provide a descriptive summary of county-level inequality trends by metropolitan/nonmetropolitan status and by U.S. region. Second, we conduct multivariate analyses to determine whether the factors that contribute to inequality vary between rural and urban counties. These models will focus on differences between rural/urban counties and will include variables representing economic, demographic, and geographic characteristics and processes, such as U.S. region and whether a county has experienced population decline or growth. Our third and final objective is to compare the results of our county-level analysis with a supplemental analysis of income inequality at the commuting zone level. This comparison will provide initial evidence about the segregation of the poor and affluent within rural and urban commuting zones. Ultimately, we seek to contribute to a broader literature on income inequality as it is measured and analyzed at various geographic scales, including U.S. counties, commuting zones, and regions.

ABSTRACT. The goal of this paper is to provide new statistics on income inequality by state, retaining consistency with Bureau of Economic Analysis (BEA) data on national and state personal income aggregates, and the national personal income distribution (Fixler, Gindelsky, Johnson, 2020). We distribute BEA State Personal Income to households to show how those with different income levels share in prosperity and growth, using CPS microdata as the principal source data. To address concerns about sample size at the state level, we use a three-year pooled sample of CPS households. We use a number of other data sources to improve the distribution for specific income components and the top of the income distribution, including the IRS Statistics of Income, the Survey of Consumer Finances, the Medical Expenditure Panel Survey, and the American Community Survey. Once allocators have been chosen for all BEA income components, in effect we have complete microdata for all CPS households, for all BEA income components. We can then generate bottom-up inequality statistics that are consistent with published and unpublished BEA aggregates of detailed personal income components, and permit examination of trends by state and over the 2007-2018 time period.

ABSTRACT. Corporate tax apportionment can play a significant role in determining the income tax liability of corporations with operations in multiple states. Over the last twenty years, most states have moved from an equal weighting of three factors (i.e., property value, payroll, and sales) to single sales factor (SSF) apportionment, which weights total national tax liability by the proportion of total firm sales occurring in the taxing state. This paper examines characteristics of firms that elected to use a new voluntary program of single sales apportionment for manufacturing in Virginia and compares them to other firms in manufacturing and other firms that received discretionary economic incentives from the state (e.g., targeting characteristics and estimated tax expenditure per job created). It also presents an ex post econometric analysis of policy adoption on firm employment, taking into consideration firm selection effects. Empirical results show that single sales election is related to corporate tax liability, firm size, and relative shares of sales in the state compared to property and payroll. Furthermore, single sales factor apportionment is positively related to subsequent firm employment. Because of its design, elective SSF is relatively well-targeted at high multiplier, export-base firms. However, its cost per job compared to other job creation economic incentive programs is also high.

ABSTRACT. When local property assessors do not equitably and accurately assess property, local funding for public services can suffer. Local property taxes make up a large share of funding in local government budgets in the U.S. and have historically funded local schools. Reliance on property wealth can reinforce school funding inequality in two ways. First, through actual differences in home values, which depend on market conditions and local amenities. Second, through measured differences in home values as determined by property assessments, which depend on local fiscal and institutional capacity. We analyze whether state government can intervene successfully to reduce chronic underassessment at the local government level as part of an education finance reform effort. We provide causal evidence on an understudied driver of school funding inequality: local fiscal capacity and corruption. We use difference-in-differences and county-level administrative data on assessments to find that the program boosted assessments by around 30 percent. The intervention also improved horizontal equity: The average coefficient of dispersion fell by 67 percent. Finally, the intervention increased local property revenues by 20 percent, as localities were constrained in their ability to offset the increased assessments by lowering tax rates. Our results suggest that state oversight can improve property assessments and provide another key channel to reduce inequality in local education finance.

ABSTRACT. This paper investigates the impact of e-government on corruption in the U.S. Our state-level analysis affords three benefit from (i) more direct measures of convictions (along with corruption perceptions) (ii) common institutional and history background, and (iii) panel estimation to control for unmeasured differences and endogeneity. We find that e-government raises corruption. Our results suggest that besides bringing transparency e-government can create new rent-seeking opportunities for corrupt officials.

ABSTRACT. In this paper, we examine the relationship between public libraries and local crime rates. Given that the annual cost of crime in the United States ranges anywhere from $650 billion to $3.4 trillion, it is important to investigate potential mitigating factors. Previous studies have looked at different factors that could account for changes in crime, but few have focused on cultural institutions as a primary factor. Crime data come from the Crime Open Database project, which contains geolocated crime data on several US cities. Library data comes from the Public Library Survey, considered to be the census of public libraries in the United States, and includes information on opening and closures of branches and their geolocation. By combining both datasets, we are able to explore how openings and closures of library branches affect local crime rate by leveraging the distance from crime occurrence to public library buildings. Therefore, we are able to investigate to what extent public libraries can help reduce local crime and potential heterogeneity across types of crime. We posit that public libraries should be negatively associated local crime rates. The reasons are threefold: i) public libraries are associated with higher literacy rates in the local community, and previous literature suggests that illiteracy is positively correlated with higher crime rates; ii) libraries are commonly considered as safe havens for vulnerable populations, and can result in more youth staying off the streets, resulting in a reduced likelihood to commit crime; and iii) libraries offer schooling and employment resources, and communities with lower unemployment rates are strongly correlated with having lower criminal rates.

ABSTRACT. Since the coronavirus (COVID-19) was first detected, the United States has experienced three distinct surges in cases and deaths. The first surge occurred primarily in metropolitan locations, while during the second two surges infection and death rates in nonmetropolitan locations eventually exceeded and remained higher than in metropolitan areas. Infection and death rates also varied across space, with hot and cool spots depending on exposure and vulnerability to the virus as well as ability to receive treatment. Demand for medical care due to COVID-19 is affected by the rate of infection, which depends on the character and frequency of interaction among people, as well as the severity of infection, which may depend on age and underlying health conditions. Supply of healthcare resources to treat COVID-19 includes the availability of both physical resources and personnel and must account for how patients receive the care, with those in very rural areas frequently travelling longer distances for medical care. In this paper, we use negative binomial count models to analyze how underlying population and location characteristics affect county-level COVID-19 cases, given the population size, and deaths, given the number of cases. We focus our analysis on cases and death in 2020, as infection and death rates are both affected by COVID-19 vaccines and no time-varying county-level information on vaccination rates currently exist.

ABSTRACT. Purpose: This study creates a COVID-19 susceptibility scale at the county level, describes its components, and then assesses the health and socioeconomic resiliency of susceptible places across the rural-urban continuum.

Methods: Factor analysis grouped 11 indicators into 7 distinct susceptibility factors for 3,079 counties in the conterminous US. Unconditional mean differences are assessed using a multivariate general linear model. Data from 2018 are primarily taken from the US Census Bureau and CDC.

Results: About 33% of rural counties are highly susceptible to COVID-19, driven by older and health compromised populations, and care facilities for the elderly. Major vulnerabilities in rural counties include fewer physicians, lack of mental health services, higher disability, and more uninsured. Poor Internet access limits telemedicine. Lack of social capital and social services may hinder local pandemic recovery. Meat processing facilities drive risk in micropolitan counties. Although metropolitan counties are less susceptible due to healthier and younger populations, about 6% are at risk due to community spread from dense populations. Metropolitan vulnerabilities include minorities at higher health and diabetes risk, language barriers, being a transportation hub that helps spread infection, and acute housing distress.

Conclusions: There is an immediate need to know specific types of susceptibilities and vulnerabilities ahead of time to allow local and state health officials to plan and allocate resources accordingly. In rural areas it is essential to shelter-in-place vulnerable populations, whereas in large metropolitan areas general closure orders are needed to stop community spread. Pandemic response plans should address vulnerabilities.

ABSTRACT. Decisions about when and how to conduct formal education under the conditions of the COVID-19 pandemic are complicated. One consideration involves the risk of COVID-19 spread in school environments. Some advocates for traditional, face-to-face learning have argued that school and classroom environments are safe. To support this claim, they note that the rate of COVID-19 transmission in open schools is as low - and often lower - than the rate of COVID-19 transmission in their local communities. Unfortunately, this simple comparison neglects that the population demographics of schools are different from those of their surrounding communities, particularly with regard to age. In this paper I argue that the relevant comparison should be between school rates of transmission and community rates of transmission in an age-matched cohort. Using data from several published papers that have been used to argue for school re-opening, I calculate an expected rate of transmission for school-aged cohorts from community-spread data. In many cases, the actual school COVID-19 rates exceed the expected COVID-19 rates for a matched age-group. The alleged safety of traditional, face-to-face learning is, therefore, much less clear than many have claimed. I will discuss the possibility that the safety claim is an example of motivated reasoning.

ABSTRACT. In early 2020 COVID-19 reached the United States. The rapid spread of the virus lead to states declaring states of emergency. Decisions were made to close businesses, limit the number of occupants in stores, and adapt business operations to safely provide goods and services to the population. These changes adversely effected retail, tourism, restaurant, and other service industries. This analysis determines the short-term effects COVID-19 had on the economy of Oklahoma. This input-output analysis is conducted using 2018 IMPLAN and its new annualized Quarter 2, 2020 data. Preliminary results find that compared to 2018 there was a loss of -100 thousand jobs (-5%), -$26 billion (-6%) in output and -16 billion (-7%) in total value added. The industries that exhibited the greatest losses were in entertainment and service sectors, while industries that experienced gains were messenger and courier services, financial services, and manufacturing. Government demand increased in all industries but one. Household spending decreased across all household groups when compared to 2018.

ABSTRACT. As incomes have risen, both in the US and around the world, demand for beef and other meats has also increased. However, the US beef industry currently faces a number of challenges, including the development of lab-grown meat and concerns over animal welfare, environmental responsibility, and the health impacts of red meat consumption, among others. Beef production is a fundamentally rural industry, which suggests that rural economies are among those most likely to be affected by declining beef consumption. In this analysis, I examine spatial autocorrelation in the US beef industry to determine which counties are potentially most vulnerable to downturns in the beef market. I use hotspot and cluster analysis to establish where US beef production is most highly spatially concentrated, and I also examine the economic base of selected counties within in beef production clusters in order to identify other dominant local industries. Assessing the spatial distribution of exposure to risks associated with changes in the beef industry is a necessary first step in designing effective policy interventions to mitigate some of these risks.

ABSTRACT. In the field of vegetable and fruit production, Strawberry is a niche product, a high value product, that shows potential economic impacts to the growers. In North Carolina, strawberry production has a strong growth potential, where most producers sell directly to consumers through pick-your-own and roadside stands, and some as commercial and industrial levels. This study attempts to understand and evaluate the economic potentials of the strawberry production in North Carolina, using data collected from the United States Department of Agriculture (USDA) and North Carolina Department of Agriculture and Consumer Sciences (NCDA&CS) for the period of 1980 – 2018. Further, the study conducts a case study analysis for a local strawberry farm in North Carolina, using the farm data for a period of 3 years to identify the economic differences of organic and conventional farming of strawberry at farm levels. Multiple regression analysis and cost benefit calculations were used for the analysis. The descriptive analysis shows how the industry has changed over the last three decades in North Carolina. The regression analysis indicates the significant relationships of production, price, yield per acre, and number of farms. The case study highlights the potential gains of organic farming of strawberry with increasing demand for organic products, the so-called niche products compared to the conventional strawberry farming.

ABSTRACT. In this paper, we seek to understand the factors influencing the location behavior of breweries in Pennsylvania. What are the community characteristics in locations with a high number of breweries and are there any characteristics associated with fewer breweries in a location? We collect data from a variety of data sources: We extract the location information of breweries and wineries from Reference U.S.A., obtain policy information regarding retail liquor sales from the Pennsylvania Liquor Control Board, calculate the distance to major roads and national parks from the shapefiles of National Atlas and U.S. National Parks Service, and gather socio-economic variables from the 2013-2017 American Community Survey

To examine the location determinants of breweries in Pennsylvania, we conduct the regression analysis at the census tract level in Pennsylvania. Two main features of the data drive our model specification. First, we assume that the number of breweries in a census tract follows a counting process, directing our model choice to the count data models, such as a Poisson model or a negative binomial model, and the test of overdispersion reject a Poisson model, leaving us a negative binomial model as a suitable choice. Second, the fact that most census tracts in PA do not have a brewery suggests that a zero-inflation negative binomial (ZINB) model be necessary, and the residual test confirms this necessity.

In the ZINB model, we use the socio-economic variables as regressors in the negative binomial part and use the variables for road conditions, restrictions on retail beer sales, and temperature in the logit model for zero inflation. Moreover, the location decision of breweries depends on not only the demographic and economic conditions in a local tract but also those in neighboring tracts because people can travel across the borders of tracts to visit their preferred breweries. Therefore, we expand the zero-inflated negative binomial model with the spatial lag of socio-economic variables to account for spatial spillover effects.

The logit model for the existence of breweries shows that easy access to highways and no restriction on retail beer sales contribute to the higher probability of the local presence of breweries. The count model shows that the number of breweries is mainly determined by local demographic conditions. The population size, higher education, non-Hispanic White population, and population of age 25-44 in local tracts all have positive effects, while their counterparts in neighboring tracts have either negative or insignificant effects. The number of breweries is also positively associated with local wineries and farm markets. Interestingly, we find that the percentage of married families and household ownership are two negative factors for the number of breweries.

ABSTRACT. The most recent report of the IPCC predicts a continued increase in the frequency and intensity of extreme weather events. Agriculture, the economic sector most sensitive to changes in weather conditions, will be greatly affected by such changes regardless of a country’s geographical location. Because of concerns about food security, a growing literature has investigated the capacity of international trade to act as a major adaptation mechanism to climate change. In this paper, we rely on a difference-in-difference setting with endogenous trade interactions to assess how the trade of wheat, a crop grown across 89 countries, and its production respond to drought. Based on fine spatial and temporal resolution drought data, our panel data results indicate that a drought promotes export when it takes place in the importing country, but it discourages export when it occurs in the exporting country. As a result, the true marginal effect of a drought on wheat production is based on a combination of its local impact and its impact abroad. Projections based on future weather and drought data by 2038-2070 challenge the estimates of the current climate impact literature by revealing that international trade is capable of mitigating the impact of adverse weather events on yield.

ABSTRACT. We investigate the relationship between broad-based merit aid programs sponsored by U.S. state-level governments and the retention of college graduates. The impact of these programs is still debated and research in this field is limited. Using a unique data set for the 1988-2018 period and employing a difference-in-differences approach, with adjustments for endogeneity bias, we find that: 1) states offering merit aid have higher workforce retention rates of college graduates, 2) the effect is strongest immediately after graduation and decreases over time, and 3) states with larger-spending on merit aid have weaker average retention rates of graduates compared with lower-spending states.

ABSTRACT. The skill-biased technological change literature has been silent on two key channels regarding how it affects labor supply: skilled migration and demand for college education. Through these two channels, innovation influences the divergence in wages, skills, and productivity between urban areas. Using patents as a measure of skill-biased technological change, we find that the local demand for college education played a greater role in explaining skill divergence between U.S. urban counties. Our findings suggest that local government should increasingly focus on investing in new innovation and education and should reduce the focus on attracting high-skilled workers from other regions.

ABSTRACT. A lacuna in the extant literature and our desire to contribute to the theoretical literature on how tax/subsidy policies can be used by regions to attract the creative class together provide the motivation for this paper. The paper’s basic contribution is that it is the first to theoretically analyze competition between two regions (1 and 2) for mobile creative capital, the key attribute possessed by the creative class. Both regions produce a final good using creative and physical capital. In the first case, physical capital is immobile and only region 2 uses tax policy to attract the mobile creative capital. We compute the equilibrium returns to creative and physical capital, we specify a key condition for creative capital in the aggregate economy, and we show which of three tax policies gives region 2 the highest income. In the second case, creative and physical capital are mobile and both regions pursue tax policies to attract mobile creative capital. Once again, we compute the equilibrium returns to creative and physical capital and then describe the optimal taxes for the two regions given that they wish to maximize regional income.

ABSTRACT. Several studies assess the impact of collegiate programs (e.g. sports, clubs, extracurriculars, etc.) on the number of applications that schools receive. Our paper contributes to this larger literature by adding availability of recreational marijuana (RMJ) to the amenity package that prospective students observe. Using data provided through the Integrated Postsecondary Education Data System, we analyze how RMJ availability affected the largest public collegiate programs in the states of Colorado, Washington, and Oregon. As the first three states to make RMJ available for sale, we hypothesize that the well-known schools would observe structural increases in the number and quality of applications, typically through increases to out-of-state applications. Preliminary results from regression discontinuity design models suggest that only CU Boulder observed a significant structural increase in applications and applicant quality, while improving graduation outcomes for all schools. Our results inform present debates about RMJ policy and indicate that RMJ legalization provides benefits to some schools through larger applicant pools and more qualified students, without negatively affecting student graduation rates.

ABSTRACT. This research explores how pedestrian safety has been impacted during the COVID-19 pandemic. The role of walking in local communities has evolved in response to changes in daily routines, fewer entertainment options, stay-at-home orders, and social distancing mandates. Many cities have accommodated the increase in walking and need to social distance by enacting initiatives that make more space for pedestrians on roadways. Examples of these initiatives include closing streets to thru-traffic, creating shared streets, closing lanes/shoulder to make more room for outdoor dining, and installing pop-up bike lanes and walkways. We ask if these efforts have impacted pedestrian safety outcomes during the pandemic when compared to the previous baseline. We use Miami, Florida as a case study for this research. Florida routinely has some of the worst pedestrian outcomes in the nation, but has also enacted some pandemic-era street changes. We explore how walking safety has been impacted in the context of this era and these changes.

ABSTRACT. We focus on a poor region and analyze the connections between health interventions undertaken by a regional authority (RA) and this region’s resilience in the presence of a pandemic such as Covid-19. First, we show how a health intervention by the RA stochastically impacts an appropriately defined health indicator for this region. Second, we compute the probability that the health status of this region’s population falls below a minimum acceptable level in the presence of the health intervention. Third we solve an optimization problem in which the RA maximizes the likelihood that the health status of this region’s population stays above a minimum acceptable level at a given economic cost. Finally, we discuss the nexus between a health intervention, our region’s health status, and its resilience by presenting two applications of our theoretical framework.

ABSTRACT. Amidst COVID-19-related stay-at-home orders, over 60% of employed adults teleworked from home in mid-April, according to a Gallup Poll. Simultaneously, the U.S. unemployment rate spiked to historic levels. As the economy moved largely online broadband internet became more important than ever to the functioning economy. Therefore, this paper explores the relationship between broadband in rural counties and employment rates during April and May 2020. Two broadband measures are used: availability data obtained from the December 2019 Federal Communications Commission Form 477, and adoption data obtained from the 2018 five-year American Community Survey. We use an instrumental variable approach to address potential endogeneity, and control for socioeconomic, demographic, and pandemic-related factors – including COVID-19 case counts and mask usage. Preliminary results suggest counties with higher rates of broadband adoption had higher employment rates, ceteris paribus; there is some evidence this is the case for broadband availability as well, but this result does not appear to be as robust. Results will highlight the importance of digital access in rural areas during the COVID-19 pandemic and may build the case for increasing digital adoption and fluency going forward.

ABSTRACT. The number of family farms in the U.S. has been declining for the past few decades, giving rise to concerns with lagging rural development and poverty issues. On the other hand, the number and the share of farms with women principal operators have increased over the past three decades. However, the characteristics and potential broader, economy-wide effects of female operated farms have not been studied. In this paper, we explore the contribution of female-operated farms to the growth of farmer proprietor employment.

The main regression model is a two-ways fixed effects panel data model with the data at the county level for four time periods. The dependent variable is the annualized growth rate of farm proprietor employment, of which the data is from the Bureau of Economic Analysis (BEA). To mitigate the concerns of endogeneity, we use two main regressors in separate models. One main regressor is the lagged share of female operated farms, a level variable, and the other regressor is the lagged growth rate of female operated farms, a differenced variable, of which the data is from the Census of Agriculture from 2002 to 2017. In the two-ways fixed effects model, the county dummy variables control the unobserved local factors, and the time dummy variables control the macroeconomic conditions, e.g., the Great Recess during the 2007-2012 period, and a change in the definition of female principal operators of the 2017 Census of Agriculture. We also include control variables that account for factors regarding farm operations, non-farm labor market, and local socio-economic conditions. Furthermore, given that the presence of female-operated farms is spatially clustered, we expand the panel data model with the spatially lagged regressors. But we reject a spatial Durbin model with the spatially lagged dependent variable. Both the lagged level variable and the growth variable of female-operated farms, as well as their spatial lagged variables, have positive effects on the growth rate of farm proprietor employment.

ABSTRACT. Global changes in macroeconomic variables such as net output, Gross Value Added (GVA), and employment can occur due to distinct local, global, or even sectoral shifts. The input-output based technique known as structural decomposition analysis (SDA) allows for the decomposition of changes in the aforementioned macroeconomic variables to distinct effects driven by changes in production technology, changes in foreign and domestic trade, changes in final demand, changes in global production, and changes in value added and/or labor productivity. To quantify the specific contribution of each of these factors in a global context, a global multi-regional input output database can be used, however, the tables must first be transformed to constant prices and same-year exchange rates to eliminate any effects associated with distinct inflation and variations in currency across countries and time. In this study, the 15 inter-country World Input-Output Database (WIOD) tables are first transformed to constant 2010 $US Dollars. We then present an innovative structural decomposition analysis that decomposes the changes in national industry output into six components: two associated with changes in the Leontief multipliers and four related with changes in final demand. In the case of GVA and employment the changes are further decomposed into seven components as they also include the changes in value-added coefficients and labor coefficients, respectively. Results presented focus on changes in two important food system sectors, “Crop and animal production, hunting and related service activities” and “Manufacture of food products, beverages and tobacco products”. A detailed description of the evolution of global macroeconomic indicators in these markets is performed. The methodology presented can be generalized to other sectors and is applicable at the national, regional and local level, meaning that the data and insights provided from such analyses can be important components of informed decision-making at all levels.

ABSTRACT. This paper analyzes consumer willingness to support farmer adoption of pasture, riparian buffers, and pasture-riparian buffer practices. The goal of the practices is to improve the water quality of the Ft. Cobb (Oklahoma) watershed, a multiuse area for agriculture, residential water, and recreation. The analysis uses the Oklahoma Meso-Scale Integrated Sociogeographic Network survey (M-SISNet) to conduct a contingent valuation analysis of willingness to pay a one-time tax to support the promote farmer adoption of these practices. Consumer heterogeneity is modeled using beta-binomial regression. We find that consumer support for the referendum is stronger for riparian buffers and the pasture-riparian buffer system, with WTP ranging between $230 and $690 for both systems. Support for the pasture-riparian buffer program is lower for households located further way from the watershed. Willingness to support decreases by $2.92 for every additional mile a household is located from the watershed. Other variables informing the potential targeting of the referendum include frequency of visits to the recreational area, familiarity with the reservoir, and concern for the state's commercial sectors. Consumer confidence in the survey objectives also influences estimates.

ABSTRACT. The current crisis in US agriculture has seen a growing number of farm bankruptcies. The result has been a “hollowing out” of the middle in the distribution of farm size, with growth in the number of both very large farms and small farms. What are some implications of these changes for the well-being of rural communities? Using US nonmetropolitan (rural) county level data, we explore how the changing size of farms has affected community well-being as understood through five diverse measures. In general, we find conflicting evidence on the impact of farm size on community well-being. In the end our results suggest that the logical conclusion of what has become known as the Goldschmidt hypothesis line of thinking that the movement to fewer and larger farms will necessarily harm the well-being of the larger community is not supported by the data.

ABSTRACT. The transmission of pollution across countries has been studied through the lens of atmospheric chemical transport or through its content in international trade, but only a handful of studies consider both channels concurrently. Yet, the rare exceptions do not highlight the economic sector(s) at the origin of the problem and thus fail to identify effective abatement strategies. In this paper, we integrate environmentally extended input-output trade linkages with physical pathways of carbon monoxide atmospheric transport to uncover the key drivers of the changes in intercountry pollution transmission. Based on a five-region model, the results indicate that most of the CO experienced in a country comes from its own production, whether it is destined for the domestic or foreign markets, but the role of pollution due to a large upwind CO producer is not negligible. As such, we provide new insights into the sources of the health care costs associated to air pollution and the impact of adopting greener technologies which, through trade and atmospheric channels, have the potential to reduce global emissions.

ABSTRACT. In February 2021, Norman, Oklahoma experienced a period of unusually cold weather which destabilized the electricity grid. There were both rolling and unanticipated power outages throughout the city. The local utility company appealed to residents to conserve energy to help keep the grid functioning. We conducted a poll using social media to analyze attitudes and responses to the situation. Which recommended actions, if any, did individuals take in the common interest? This paper summarizes our findings and informs the discussion about how to strategically manage demand in response to supply disruptions.

ABSTRACT. Algal blooms occur when natural algae in lakes, rivers, and coastal zones are stimulated to grow out of control by elevated levels of nutrients in the water. Algal blooms that produce dangerous toxins that are detrimental to the plants, animals, people, and ecosystems in the affected areas are known as harmful algal blooms (HABs). Several types of naturally occurring HABs exist in the Gulf of Mexico, including those caused by the marine dinoflagellate Karenia brevis (K. brevis), commonly known as red tide. These events often occur in the ocean and nearshore coastal waters as K. brevis thrives in high-salinity waters. Excessive use of fertilizer in agriculture, anthropogenic change in land-use, combustion of fossil fuels, and discharge of human waste are all potential causes of nutrient enrichment, i.e. increase in concentrations of nitrogen (N) and phosphate (P), in coastal areas that can increase the intensity and longevity of HABs (Heisler et al., 2008). Red tide can cause respiratory distress and skin irritation in humans and marine animals, contaminate shellfish, cause fish kills, create dead zones in the water, and reduce economic activity associated with commercial and recreational fishing, other marine industries, and tourism (Adams et al, 2018).

This paper uses in situ observations of K. Brevis abundance and a quasi-experimental, difference in difference (DID) model to measure the adverse economic impacts of changes in recreational fishing activity associated with red tide occurrences along Florida’s western coast. We combine data from the Florida Fish and Wildlife Conservation Commission's Fish and Wildlife Research Institute (FWRI) harmful algal bloom (HAB) monitoring database and the Marine Recreational Information Program (MRIP) data published by the National Oceanic and Atmospheric Administration (NOAA) Fisheries to compare the average change in number of trips taken to fishing sites that have experienced a red tide event nearby, with number of trips taken in appropriate comparison sites. This paper attempts to provide quantitative evidence on the local impact of a red tide event on recreational fishing, by considering the implied cost in terms of reduced number of fishing trips. This method produces a credible counterfactual for determining the causal effect of red tide events on recreational fishing, providing results relevant for informed decision-making regarding the prevention or mitigating of red tide events.

ABSTRACT. "Moriarty Graduate Paper Competition" The recurring hurricane damage redefines the spatial equilibrium by altering the productivity and amenity-adjusted land and by inducing individuals and firms to relocate to maximize their utility. To understand the impact of the disaster in the affected region, spatial interaction is an important aspect to consider. Using the quantitative spatial framework and the county-level disaster damage data for the US coastal counties in the Gulf of Mexico and the Atlantic, this paper investigates the effect of hurricanes on the local economy. This paper shows an application of the quantitative spatial model to identify the unobserved productivity and amenity-adjusted land by establishing a link between the observed data and the structural model. The result shows that disaster-induced changes in local productivity and amenity can explain the variation in wages and employment. The variation in labor and wage due to hurricanes depends on the intensity of the hurricane, and the size and initial conditions of the economy. It is also found that hurricane-damage reduces the overall welfare by 0.3 percent.