NE2249: Sustainable and Inclusive Rural Economic Development to Enhance Housing, Health, Entrepreneurship, and Equity

(Multistate Research Project)

Status: Active

NE2249: Sustainable and Inclusive Rural Economic Development to Enhance Housing, Health, Entrepreneurship, and Equity

Duration: 10/01/2022 to 09/30/2027

Administrative Advisor(s):

NIFA Reps:

Non-Technical Summary

Statement of Issues and Justification

The NE1749 group (Enhancing Rural Economic Opportunities, Community Resilience, and Entrepreneurship) formally requests consideration for a revision/replacement as its five-year term ends. The group is in its fifth incarnation (previously NE1049, NE1029, NE1011, and NE162), and was originally organized prior to the establishment of the new NIFA focus areas. This project will continue to improve the group’s efforts by extending and expanding previous areas of collaborative research, while also exploring new and understudied issues facing rural areas.


Rural communities are diverse, with some rural areas doing well and others facing a wide variety of barriers to economic development (Goetz et al. 2018). Some rural areas are dominated by agriculture, while others are more integrated with urban areas or feature natural resource development or outdoor recreation. The diversity of rural challenges and assets means that research to enhance rural economic development cover a number of interacting and overlapping topics. While entrepreneurship, equity, housing, and health, are of course all overlapping to some degree, to provide structure to our areas of focus, we group the objectives into “housing and health” and “entrepreneurship and equity,” within a unifying/overarching theme of “sustainable and inclusive” rural economic development. See figure 1 for an illustration.


Figure 1. Overlap of Focus Areas of this Proposal (see attachments)


Over the five-year terms of the past project (NE1749), aging population, changing industrial structure, and less consistent health care and public service provision were a focus, with many rural areas have continued to experience unsustainable population loss, particularly among young adults, but also with decreasing births. These trends have largely continued and populations with large shares of old, poor, or people of color have different needs for medical care, legal assistance, and social services, yet depopulating rural communities that lack amenities and quality schools and health care struggle to attract highly educated individuals to provide those professional services. The COVID-19 pandemic further highlighted the limitations of rural healthcare and risks of unhealthy behavior, with many rural communities facing high per capita rates of COVID-19 infection and mortality.

Nonetheless, the COVID-19 pandemic also highlights some areas for rural economic opportunity and population sustainability. Specifically, with increasing work location flexibility for many individuals and some viewing population density as a health risk, many rural areas experience booms of new residents, including highly educated individuals who could work remotely. Furthermore, many rural areas over the same period already had increasing population bases that were increasingly diverse. Specifically, rural areas are increasingly diverse, as jobs in construction, manufacturing, agriculture, and food processing brought an influx of immigrants. Are there opportunities to leverage this increasingly diverse population to enhance economic growth? How do we ensure rural economic development is inclusive to enhance immigrant equity? Are there historical sources of rural racial and ethnic inequality that can be measured or addressed?

Overlapping with issues of both healthcare and economic growth, U.S. military veterans are disproportionately represented in both rural areas and among rural entrepreneurs. Since 36 percent of veterans who use the Veteran’s Administration (VA) for health care live in rural areas, healthcare again poses a challenge. However, these veterans could also be an important resource for rural communities, bringing education, skills, and leadership experience. Are there opportunities to leverage veterans’ experiences to enhance rural economic growth? How can rural communities support rural veteran entrepreneurs and rural veterans in the workforce more generally?

In sum, considering rural health, causes of death including suicide, alcohol abuse, and drug (especially opioid) overdoses are relatively prevalent in rural communities. Disadvantages prevalent in rural areas related to low education levels, housing shortages, unemployment, poverty, age, mental and physical health, and isolation all combine to increase rural mortality and reduce life expectancy (Community Resilience Estimates, U.S. Census Bureau, 2021).

USDA’s Research, Education, and Economics (REE) Action Plan Progress Report (November, 2017; see also USDA Strategic Plan FY 2018 – 2022) presents a vision to support rural communities by using “Impact-driven agricultural science” to expand rural economic opportunity through innovation, promotion of sustainability and conservation, enhancing environmental quality, and improving quality of life for farmers, farm workers, and society. Of the seven goals identified in the REE plan and discussed in the progress report, five are relevant to the new proposal, along with their underlying issues and broadly defined research questions:

  1. Nutrition and Childhood Obesity. As noted above, the costs of poor health and nutrition are extensive in rural areas. The COVID-19 pandemic highlighted the importance of enhancing rural health and nutrition. Poor food environments in rural communities have led to the low quality of nutrition and nutrition-related disease. How can we effectively enhance rural health, healthcare, food environment, and nutrition?

  2. Responding to Climate and Energy Needs. Rural areas encounter a lower-carbon future and regional energy security. Everyone needs tools to help with greenhouse gas mitigation and adaptation, and this is especially true for agricultural and forestry producers, land managers, and other rural decision makers, who are having to deal with increasing temperatures and/or increasing climatic turbulence. Also, rural communities should have reliable and affordable access to energy systems and sources in the face of extreme weather events. What approaches can communities and community-members take to enhance rural climate resiliency?

  3. Rural-Urban Interdependence and Prosperity. Some rural communities have been able to take advantage of new economic opportunities during the COVID-19 pandemic by telework and distance education on a large scale and accelerated e-commerce. Many others, however, have continued to experience out-migration, stagnant labor markets, poverty, housing shortages, and/or declining healthcare availability. Communities will need to leverage diverse community members and entrepreneurs to exploit and grow their competitive advantages, including resources, skills, knowledge, and innovation, all of which are key to enhanced economic resiliency. Further, rural communities need to position themselves to take advantage of opportunities (e.g., local/regional/organic food supply chain, and new immigrants) and technologies (e.g., broadband, green technologies, and renewable energies). How do these constellations of factors interact to establish determinants of long-run rural economic opportunity?

  4. Sustainable Use of Natural Resources. Rural areas are disproportionately endowed with natural resources. These resources often require disparate prescriptions for sustainable use that still maximizes long-run economic growth, while also following the water-rights of Native Americans. How do we leverage these resources to maximize sustainable economic growth?

  5. Education and Science Literacy. Maintaining and growing rural economic opportunity will require increasing understanding and investments in science, technology, engineering, arts, and mathematics (STEAM) to enhance the competitiveness of the rural labor force, particularly for young people who often leave rural areas for better social and career options. What are the most effective investments in STEAM for long-run rural economic opportunity?

Overlapping with the goals outlined in the REE Action Plan Progress Report, is the White House’s plan to “Fundamentally Revitalize Rural Economies.” Specifically, the plan emphasizes the need for sustainable rural economic development by investing in their unique assets to “make sure wealth created in rural America stays in rural America.” Consistent with the needs and justification of this group, strategic goals listed in this plan include: fostering the development of regional food systems, partnering with farmers to reduce greenhouse emissions in agriculture and rural energy, effectively invest in rural broadband infrastructure, improve access to health care in rural communities, and prioritize persistent poverty communities for long-run economic growth. As the plan notes, approximately 85% of counties experiencing long-term persistent poverty in the U.S. are rural.

Recent and ongoing projects in these areas by the members of NE1749 include research related to local foods and sustainable agriculture, rural water and environmental issues, rural amenities and economic growth and development, rural housing shortages, agricultural tourism and recreation, rural access to information technology, links between broadband provision and entrepreneurship, rural military veteran and entrepreneurship, and long-run rural economic opportunity and causes rural racial inequity. Recent research has also examined rural-urban linkages, the impacts of the opioid crisis, and causes of rural population loss. In its 2021 annual meeting, the group identified these topics and linked them to the REE and Whitehouse goals for supporting rural economic development. Pursuant to developing the next iteration of the research project, we emphasize that while many of these areas remain similar to previous iterations of this group, these research topics are ongoing (hence their inclusion in new Whitehouse goals), and regional heterogeneity in rural needs and effective policy continue to uniquely evolve. For example, changes in rural labor market continue, due partly to declining and aging population and increasing diversity, may cause substantial shifts in long-run rural economic opportunity. In terms of rural climate resiliency, development of renewable energy sources like wind and solar also have the potential to cause changes in land use and economic structure in rural areas.

The researchers acknowledge that this proposal is exceptionally broad and multi-faceted, but so too are the evolving needs of rural economic development. The members of this multi-state research group are uniquely qualified to continue to provide collaborative leadership in the pursuit of the long-run rural economic development goals set out by USDA and the Whitehouse.

Related, Current and Previous Work

This proposed project’s team of researchers has a history studying the wide variety of issues surrounding entrepreneurship and resiliency and its predecessors NE1749, NE1049, NE1029, NE1011, and NE162. This section delineates past and current work by the proposed project’s members, emphasizing research related to the key rural economic development issues we have identified. Much of the work done by project members focused (and focuses) on the inequalities in growth, development, and the effects of the COVID-19 pandemic. Less work has been done on rural racial, ethnic, and gender disparities (in part due to data limitations), but we highlight some exceptional work. The team has also advanced theory related to regional economic development, which are not as well defined as the foundation for other areas of economics.

Among the commonly used tools for regional economic development research is examinations of the determinants of business location, relocation, creation, attraction, retention, expansion, or “firm demography” (Pellenbarg et al. 2002). Recent studies document the decline in establishments’ birth rates since the 1990s and examine the negative effects on economic growth therefrom (Gourio et al. 2016; Haltiwanger et al. 2013). This has spawned a wide variety of research on place-based policy research. For example, inward investment policy, also known as industrial recruitment, is an area of active research (Raganowicz 2018; Rutherford et al. 2018; Tewdwr-Jones & Phelps 2000; Xu et al. 2020).

Analytical perspectives include: (1) demand thresholds and (2) spatial monopsony, which both stem from central place theory (Berry & Garrison 1958a,b; Christaller 1966; Lösch 1954), (3) classical and neoclassical location-production models (Weber 1909), (4) New Economic Geography (Krugman 1991a,b, 1995), and (5) firm demography (van Dijk & Pellenbarg 2000). Firm demography includes 3 frameworks: (5.1) random profit maximization (McFadden 1973), (5.2) behavioral, and (5.3) institutional frameworks (Carpenter et al. 2021c).  While the latter two frameworks have historically received less attention, new data and empirical techniques make implementation increasingly feasible (Conroy et al. 2016; McCann 2002; Pellenbarg et al. 2002).

Project team members are active in this area with research across industries, such as agriculture (Goetz 1997; Van Sandt & Carpenter 2021), health services (Van Sandt et al. 2021b), manufacturing (Carpenter et al. 2021b; Conroy et al. 2016, 2017; Leatherman & Kastens 2009), finance (Van Sandt et al. 2021c), retail (Harris & Shonkwiler 1997; Harris et al. 2000; Shonkwiler & Harris 1993, 1996), and transportation and warehousing (Carpenter et al. 2021a; Mjelde et al. 2020). Project team members are also active (and have a history) in research across topics, including agglomeration (Carpenter et al. 2021b; Thilmany et al. 2005), business climate (Conroy et al. 2016, 2017), population characteristics (Goetz 1997; Harris et al. 2000), rurality (Coughlin & Segev 2000), and taxes/spending (Das & Skidmore 2018; Patrick & Stephens 2020).

Limitations related to regional economic data availability and quality are indeed substantial and project team researchers are actively involved in efforts to quantify these biases and examine alternatives (Carpenter et al. 2021d). A common issue with public U.S. data is the suppression of county-level industrial data. Resultantly, researchers often resort to imputing suppressed cells or using proprietary datasets (Autor et al. 2013; Glaeser et al. 1992; Porter 2003). While there is a history of efforts to improve and address cell suppression (Isserman & Westervelt 2006; Orr & Buongiorno 1989), more common in the economic literature are journal articles that use suppressed-cell estimated datasets without documenting methods used to produce the estimates (Anselin et al. 1997; Gerking & Isserman 1981; Isserman 2001; Markusen 1996) which may substantially bias coefficient estimates (Carpenter et al. 2021d). Additionally, researchers often resort to using relatively aggregated industries, due to disclosure limitations, which can cause aggregation bias (Carpenter et al. 2021e).

In terms of economic opportunity, in part due to data limitations, we do not know nearly as much about economic opportunity and intergenerational mobility in rural areas as we do about economic opportunity in urban areas. For example, while there are many studies documenting changes in economic opportunity in large cities (Chetty & Hendren 2015), we know little about how much economic opportunity varies by rurality (Li et al. 2018; Weber et al. 2017) and how this has changed over time. More strikingly, we do not know the extent to which racial disparities in economic opportunity – which are well documented in urban areas (Chetty et al. 2020) – also hold for rural areas. More specifically, while there is evidence, within a single generation, that childhood access to housing and education provides lifelong benefits (Bailey et al. 2020; Chetty et al. 2016; Chyn 2018) and of variation across the spectrum of rurality (Goetz et al. 2018; Li et al. 2018; Weber et al. 2017), data limitations have made it difficult to estimate interactive and intergenerational benefits, or break down effects by race, especially in rural areas. Thus, although it is well established that childhood conditions have a lasting influence on children’s wellbeing (Duncan et al. 1998), much of what we know comes from studies of urban children or national (public and smaller sample) databases, which are dominated by urban samples (Duncan and Magnuson 2013; Brooks-Gunn and Duncan 1997). Even recent and place-based economic opportunity databases suppress or aggregate rural areas (Chetty et al. 2020). Consequently, little is known about how rural socio-economic conditions are related to their long-term outcomes and if they pass down these effects to their children, which, for example, may create concentrations of extreme rural poverty (Crandall & Weber 2004) or inequality (Rahe et al. 2019). However, there have been some attempts to examine the drivers of the differences in life expectancy (Dobis et al. 2020) and wealth (Rahe & Hause 2020).

In sum, regarding the diverse issues covered in the previous work by NE1749 researchers, one of the major strengths of NE1749 (and its predecessors) has been the extent to which researchers have collaborated across state and regional boundaries to share research and expertise. The project team reviewed the extensive publication record during NE1749. Findings indicate that coauthorship across state lines is commonplace. Some of the areas of research where either direct or indirect (i.e. building directly on previous project work) collaboration has occurred includes understanding rural areas (Goetz et al. 2018), rural-urban interdependence (Détang-Dessendre et al. 2016; Harris & Shonkwiler 1997; Klein et al. 2017; Lee et al. 2009; Partridge et al. 2017, 2021; Tsvetkova et al. 2017; Wu et al. 2017), housing (Gemmell et al. 2017; Paredes & Skidmore 2017; Torrejón et al. 2020; Wang et al. 2020), health care outcomes including opioid and drug use (Cuthbertson et al. 2020; Dobis et al. 2020; Green et al. 2020; Joudrey et al. 2019; Shupp et al. 2020), minoritized racial and ethnic group entrepreneurship (Carpenter & Loveridge 2018, 2019a,b, 2020, 2021), gender and entrepreneurship (Conroy 2018; Conroy & Low 2021a; Conroy et al. 2019b), location theory (Carpenter & Fannin 2021; Carpenter et al. 2021c, b,a; Conroy et al. 2016, 2017; Van Sandt & Carpenter 2021; Van Sandt et al. 2021b), broadband development (Deller et al. 2021; Whitacre et al. 2014, 2018), oil drilling and natural resource extraction (Betz et al. 2015; Carpenter et al. 2019; Dorfman et al. 2011; Kelsey et al. 2016; Lobao et al. 2016; Munasib & Rickman 2015; Tsvetkova & Partridge 2016; Weinstein et al. 2017), local foods (Bauman et al. 2019; Cleary et al. 2019; Jablonski et al. 2019b,a, 2021; Low et al. 2020, 2021; O’Hara et al. 2021; Thilmany et al. 2021), and local financial services (Carpenter et al. 2018, 2020; Petach et al. 2021).

For emphasis, we note that that many of these previous (and forthcoming or proposed) research accomplishments feed directly into this project’s goals (as well as the priorities identified by USDA and the White House).


  1. Objective 1. Enhancing Rural Economic Development focusing on Housing and Health
    Comments: See Methods section for details.
  2. Objective 2. Enhancing Rural Economic Development focusing on Entrepreneurship and Equity
    Comments: See Methods section for details.


A primary motivation of this project is to continue and redirect the work performed under regional Research Project NE1749, reestablishing the multi-state research effort in the context of the USDA REE Action Plan and its vision of using impact-driven agricultural science to expand economic opportunity. NE2249 will continue to build on the many past and current outreach and multi-state activities. While the project has two, arguably broad, objectives, research questions and methods for each overlap and complements the other.

Two important forms of cross-state cooperation are evident in our proposed research. First, a large share of the research will be conducted collaboratively across states. Second, research methods and approaches that have been developed in one state have historically been subsequently employed by researchers in other states. Although many challenges are the same, states also differ. This interstate variation helps to identify general relationships between dependent and explanatory variables. Thus, interstate collaboration provides more suitable cross-section time-series databases. Multi-state collaboration also lends valuable support to innovation, which is by definition the application of an existing invention to a new purpose. We will build on our knowledge base, better use our resources through the synergies of collaboration, help create more efficient rural policy, and help improve the sustainability and vitality of rural communities. Additionally, rural areas in the United States are not homogeneous and the impact of policies may vary across regions. By conducting analysis in various types of rural regions using similar methods, we can improve our understanding of the impact of policies on various types of rural areas, which can be used to improve policymaking.

Researchers within the group have the expertise and are conducting research in each of the proposal's focus areas and are poised to extend this work. For example, members have and continue to work on issues such as rural entrepreneurship and rural economic development (Colorado, Idaho, Iowa,  Michigan, Missouri, Oklahoma,  Texas, West Virginia, West Virginia, Wisconsin, Wyoming); housing and infrastructure (Wisconsin, Missouri, New Hampshire, Ohio, Oklahoma, Oregon, Tennessee, West Virginia); and health and food (Colorado, Kentucky, Michigan, Oklahoma,  Tennessee, Texas, West Virginia, Wisconsin), and extend those issues in the perspective of equity (Michigan, Mississippi, Missouri, Texas, Wisconsin).  The researchers in the group will employ a variety of social science and statistical methods to address the research objectives, bringing to bear the appropriate methods for different topics, and allowing for triangulation across methods and states for broader interpretation of findings. Surveys, interviews, and focus groups allow for an in-depth examination of particular issues; for example, surveys of consumer behavior regarding local food purchases or broadband subscribers. Quantitative methods include parametric/non-parametric regression analysis, micro econometrics, input-output modeling and spatial econometrics. Expansion of the use of big data and GIS methods will allow the group to expand analysis of the spatial evolution of municipal government structures, of community capitals, and of workforce supports such as access to child care. The collaboration of researchers with research and Extension appointments will enhance cross-fertilization of ideas on methods and relevance to rural concerns. Examples of specific methods being used by project members are presented in the following two sub-sections.


Objective 1. Enhancing Rural Economic Development focusing on Housing and Health

Our objective here is to identify and analyze housing and health issues in rural areas and suggest policies and strategies contributing to the viability and resiliency of communities. Our focus is on long-run socio-economic sustainability and ability of communities to respond to changes and to develop economically. The challenges that communities have faced are poor health and nutrition, the lack of accessibility of health care and decent food, drug misuse, and the shortage of affordable, quality houses. Demographic changes, such as aging communities and the declining population that most rural communities are experiencing, are exacerbating those issues. For areas that have seen in-migrants escalate due to remote working during the COVID-19 induced economic crisis, housing shortages and increasing housing prices present new challenges for some rural areas. Members in this project are involved in studies related to the rural population, housing, food, and health from different directions.

Researchers in Texas, Wisconsin, Oklahoma, Oregon, Ohio, and West Virginia have examined the impact of natural resources, energy development, or physical capital, such as rural natural amenities (Chen et al. 2021), shale gas drilling (Carpenter et al. 2019; Keeler & Stephens 2020; Stephens & Weinstein 2019), or broadband (Deller & Whitacre 2019) on housing values in rural counties in the US, communities in Oregon, houses in amenity-rich regions in Colorado, and regions with historic resource development. They have applied various advanced econometric techniques, such as spatial three-stage least squares (spatial 3SLS), and difference-in-differences (DID).

Health issues are of special concern to rural communities and may affect their ability to plan for or react to external shocks. While drug misuse (or abuse) has received the most attention, health care accessibility and related issues have recently arisen during the COVID-19 pandemic. Researchers in Wisconsin, Tennessee, Oklahoma, Kentucky, Texas, West Virginia and Michigan are trying to provide empirical evidence of a relationship between access to healthcare and rural labor productivity, the locational determinants of nine categories of healthcare services, electronic health record adoption and rural health service business, the impact of digital information on health, the causes of differential levels of life expectancy (Dobis et al. 2020), and how overdoses are affecting population changes (Taylor et al. 2021) and immigration (Das & Das 2019) in rural areas.  These studies utilized various sources of data, such as restricted access federal establishment data, restricted access data on overdose deaths, secondary data (County Health Rankings published by the University of Wisconsin-Madison Population Health Institute), survey sample (American Hospital Association’s Annual Survey of Hospitals Information Technology Supplement), etc. This state-level effort is the type of project that has provided the basis for multistate-level collaboration to expand the study area via external funding.


Objective 2. Enhancing Rural Economic Development focusing on Entrepreneurship and Equity

Supporting the goals of USDA’s REE Action Plan, the methods employed to meet the research objectives of this project will increase understanding of the changing determinants of rural prosperity and develop indicators to measure specific community and regional assets and outcomes.

In our long-run sustainable regional economy focus we take an approach of regional development through restructuring industry and facilitating entrepreneurship focusing on the community in rural areas. Existing regional development theory generally focuses on spatial clusters or agglomeration. In the nature of the topic, most studies on industry, firm, or entrepreneurship concentrate on an urban setting, and the empirical results mostly discuss the Marshallian externalities (benefits of a large pool of skilled labor, easy access to local customers or suppliers and local knowledge spillovers) as the benefits of urban areas. However, the expansion of broadband and the COVID-19 pandemic reshape our daily life, for instance, telework, distance education, e-commerce, and telehealth, and the dependence and connectedness to the urban cores is started to lessen. Some rural communities have been able to take advantage from new economic opportunities during the COVID-19 pandemic, however, others have continued to experience out-migration, stagnant labor markets, poverty, housing shortages, and/or declining healthcare availability. Communities will need to understand key factors to the growth of their economy and leverage them to enhance economic resiliency. On-going research by researchers in Michigan, Missouri, Texas, West Virginia, and Wisconsin, along with other project members, quantify industrial and entrepreneurial advantages in the community by using various types of data and measures.

Some rural areas have been specialized in resource-based industries and businesses such as agriculture, forestry, fishing, mining, or natural amenity-based recreation, while for others, manufacturing establishments, mainly processing food, wood and mining products, have been becoming a key part of many rural economies (ERS 2020; Low et al. 2020). To address the mechanism of location choice of business, researchers in Missouri, Texas, and Michigan have examined the determinants of location choice of the food manufacturing (Low et al. 2020) and healthcare service sectors (Van Sandt et al. 2021a) suggesting the new factors which did not considered in the previous literature, such as food entrepreneurship ecosystem or the concentration of Medicare and Medicaid recipients. These studies use new types of data sets, which are rarely used in the previous studies, such as National Establishment Time-Series (NETS) data which include firm dynamics and restricted access federal establishment data.

Researchers from Texas, Michigan, Wyoming, Missouri and Colorado are actively examining on the placed-based factors related to industrial and regional economic growth (Carpenter et al. 2021c,b; Van Sandt et al. 2018, 2019). As part of a USDA-funded project, they are also helping to provide interactive information of county-level economic opportunities for businesses ( Researchers in Missouri and Wisconsin publish a series of extension reports related to entrepreneurship, business, and community development.

Researchers in Wisconsin, Texas, Missouri, Michigan, and West Virginia have been exploring entrepreneurship from various perspectives. One strand of research focuses on difference by gender, minoritized race, and ethnic group, and entrepreneurship related to regional and rural development using aggregate and microdata. Recently, research on women and minority entrepreneurship has been published (Carpenter & Loveridge 2019b, 2020, 2021; Conroy & Low 2021b). Also, researchers are trying to figure out (1) how regional assets (physical and social capital and amenities), for instance, broadband, immigration, etc., interact with entrepreneurship (Conroy & Deller 2020; Deller et al. 2021) and (2) how entrepreneurship is related to rural socio-economic factors such as migration, employment, etc. (Conroy & Low 2021a; Conroy et al. 2019a; Deller et al. 2019).

Measurement of Progress and Results


  • 1. Journal articles, extension publications, popular press articles, edited books, and book chapters. These publications and presentations will communicate research results to academic audiences and the public, synthesizing findings across themes and states.
  • 2. Integrated analyses of cross-cutting issues such as the interrelationships between community capitals or assets and residential choice, labor markets, businesses and economic growth.
  • 3. Timely information for policymakers to use in developing policy to deal with changes occurring in rural communities.

Outcomes or Projected Impacts

  • 1. Increased knowledge of the forces impacting rural communities in terms of health, housing, and diversity.
  • 2. Improved understanding among community leaders and citizens of the dynamics of labor markets and businesses and their impact on rural communities, and the role of entrepreneurship.
  • 3. Better understanding of the causes of local fiscal stress and the implications of tax and expenditure limitations on rural communities.
  • 4. Stronger synergies between participating rural development scholars via collaborative research and outreach activities.
  • 5. Economic and workforce development policies that account for recent economic structural and labor market changes and that may reduce rural poverty and improve economic outcomes for rural families.
  • 6. Better use of public resources.
  • 7. Better strategies to take advantage of non-agricultural development opportunities.
  • 8. Better understanding of the role of infrastructure in economic development, and the funding issues that accompany it.
  • 9. Better understanding of the impact of policies that affect rural areas on the range of types of rural communities.


(1):Organize the technical committee, develop and share specific research methodologies across states, identify data sources, and conduct preliminary analyses. At the first year technical meeting we will discuss and compare research methodologies for each objective and develop a framework for understanding local food markets and community capitals.

(2):(Years 2-4) Conduct analyses for each objective, with particular focus on producing results that are comparable across the participating states. Build stronger synergies across rural development scholars. Conduct research and outreach activities including input from stakeholders on objectives and results.

(4):Synthesize results across states and across objectives, complete comparative analyses, and identify policy implications and next steps. Continue outreach activities.

Projected Participation

View Appendix E: Participation

Outreach Plan

The project will engage in outreach to the scientific community, the policy community, and federal, state, and local stakeholders and decision makers. Project investigators will present the research results and seek professional input into their research at professional meetings of the Agricultural and Applied Economics Association and of regional science associations (Mid-Continent, Southern, Western, and North American Regional Science Associations), and through associated professional journals.

Outreach to the policy community will be facilitated by close affiliation of various project members with the four Rural Development Centers (Northeast, North Central, Southern, and Western), Rural Policy Research Institute, Rural Poverty Research Center, Farm Foundation, and increasing connections to the regional Federal Reserve Banks. Project investigators also have strong links to the Cooperative Extension System through the state and local offices of university Extension Services. Results will be summarized in publications like extension bulletins, policy briefs, and mass media to increase awareness and understanding of the forces impacting change in rural communities.


The project will be organized and governed in the standard way by a Technical Committee. Each participating state or agency will have an official representative appointed by the Experiment Station Director and an administrative advisor will be designated by the Experiment Station Directors. The Technical Committee will meet at least once per year, usually in the winter or early spring to coincide with professional association meetings (usually the Mid-Continent, Southern, or Western Regional Science Associations). The committee will evaluate work plans to ensure adherence to the project outline and accomplishment of projected outcomes. In the event that the meeting cannot take place at one of the regional science meetings (e.g., due to a pandemic), the technical committee will host the meeting online.

A chair and secretary will be elected annually by the Technical Committee. The secretary also serves as the chair-elect. The chair, in consultation with the administrative advisor, calls and presides over the meeting of the Technical Committee. The chair is responsible for preparing the annual report of the project. The secretary records and distributes the minutes and performs other duties as assigned by the Technical Committee.

Literature Cited

Anselin, L., A. Varga, and Z. Acs. 1997. “Local Geographic Spillovers between University Research and High Technology Innovations.” Journal of Urban Economics 42(3):422–448.

Autor, D.H., D. Dorn, and G.H. Hanson. 2013. “The China syndrome: Local labor market effects of import competition in the United States.” American Economic Review 103(6):2121–2168.

Bailey, M., B. Timpe, and S. Sun. 2020. “Prep School for Poor Kids: The Long-Run Impacts of Head Start on Human Capital and Economic Self-Sufficiency.”

Bauman, A., C. DePhelps, and D.T. McFadden. 2019. “Assessing a Local Food System: The Palouse-Clearwater Food Coalition Assessment Process.” Journal of Agriculture, Food Systems, and Community Development 8(C):107–118.

Berry, B.J.L., and W.L. Garrison. 1958a. “A Note on Central Place Theory and the Range of a Good.” Economic Geography 34(4):304.

Berry, B.J.L., and W.L. Garrison. 1958b. “Recent Developments of Central Place Theory.” Papers in Regional Science 4(1):107–120.

Betz, M.R., M. Partridge, M. Farren, and L. Lobao. 2015. “Coal mining, economic development, and the natural resources curse.” Energy Economics 50:105–116.

Brooks-Gunn, J., and G.J. Duncan. 1997. “The effects of poverty on children.” Future of Children 7(2):55–71.

Carpenter, C.W., D. Anderson, and R. Dudensing. 2019. “The Texas Drilling Boom and Local Human Capital Investment.” Journal of Agricultural and Applied Economics:1–20.

Carpenter, C.W., R.M. Dudensing, and A.T. Van Sandt. 2021. “Estimating Determinants of Transportation and Warehousing Establishment Locations Using U.S. Administrative Data.” REGION (Revise and resubmit).

Carpenter, C.W., and J.M. Fannin. 2021. “Back to the Future: Re-Incorporation of ‘Metropolitan Character’ in Core-Based Statistical Area Delineations.” Journal of Regional Analysis & Policy 51(2):67–81.

Carpenter, C.W., and S. Loveridge. 2019a. “A spatial model of growth relationships and Latino-owned business.” The Annals of Regional Science 63(3):541–557.

Carpenter, C.W., and S. Loveridge. 2020. “Business, Owner, and Regional Characteristics in Latino-owned Business Growth: An Empirical Analysis Using Confidential Census Microdata.” International Regional Science Review 43(3):254–285.

Carpenter, C.W., and S. Loveridge. 2021. “Can Latinx Entrepreneurship Help Rural America?” Choices 36(4):1–6.

Carpenter, C.W., and S. Loveridge. 2018. “Differences Between Latino-Owned Businesses and White-, Black-, or Asian-Owned Businesses: Evidence From Census Microdata.” Economic Development Quarterly 32(3):225–241.

Carpenter, C.W., and S. Loveridge. 2019b. “Factors Associated with Latino-Owned Business Survival in the United States.” The Review of Regional Studies 49(1):73–97.

Carpenter, C.W., F.C. Mencken, C.M. Tolbert, and M. Lotspeich. 2018. “Locally Owned Bank Commuting Zone Concentration and Employer Start-Ups in Metropolitan, Micropolitan and Non-Core Rural Commuting Zones from 1970-2010.” Discussion Papers 18-34, Center for Economic Studies, U.S. Census Bureau.

Carpenter, C.W., F.C. Mencken, C.M. Tolbert, and M. Lotspeich. 2020. “Locally Owned Bank Concentration and New Business Start-Ups in Metropolitan, Micropolitan and Non-Core Rural Counties from 1970-2010.” The Review of Regional Studies 50(1):17–42.

Carpenter, C.W., A.T. Van Sandt, R. Dudensing, and S. Loveridge. 2021. “Profit Pools and Determinants of Potential County-Level Manufacturing Growth.” International Regional Science Review.

Carpenter, C.W., A.T. Van Sandt, and S. Loveridge. 2021a. “Aggregation Bias and Size Measurement in Food and Agricultural Industry Locational Outcomes.” Working Paper (Under Review).

Carpenter, C.W., A.T. Van Sandt, and S. Loveridge. 2021b. “Empirical Methods in Business Location Research.” Regional Studies, Regional Science 8(1):344–361.

Carpenter, C.W., A.T. Van Sandt, and S. Loveridge. 2021c. “Measurement Error in U.S. Regional Economic Data.” Journal of Regional Science.

Chen, Y., D.J. Lewis, and B. Weber. 2021. “Natural amenities and skill sorting in rural communities: a case study of land conservation policy.” Annals of Regional Science 67(3):649–669.

Chetty, R., J.N. Friedman, N. Hendren, M.R. Jones, and S.R. Porter. 2020. “The Opportunity Atlas: Mapping the Childhood Roots of Social Mobility.” The National Bureau of Economic Research NBER Worki.

Chetty, R., and N. Hendren. 2015. “The impacts of neighborhoods on intergenerational mobility: Childhood exposure effects and county-level estimates.” Harvard University and NBER 133(3):1–145.

Chetty, R., N. Hendren, and L.F. Katz. 2016. “The effects of exposure to better neighborhoods on children: New evidence from the moving to opportunity experiment.” American Economic Review 106(4):855–902.

Christaller, W. 1966. “Central Places in southern Germany.” In Die Zentralen Orte in Süddeutschland. Englewood-Cliffs, NJ: Prentice Hall.

Chyn, E. 2018. “Moved to opportunity: The long-run effects of public housing demolition on children.” American Economic Review 108(10):3028–3056.

Cleary, R., S.J. Goetz, D.T. McFadden, and H. Ge. 2019. “Excess Competition among Food Hubs.” Journal of Agricultural and Resource Economics 44(1):141–163.

Conroy, T. 2018. “The kids are alright: working women, schedule flexibility and childcare.” Regional Studies 53(2):261–271.

Conroy, T., S. Deller, and M. Kures. 2019. “Entrepreneurship in Rural Employment in the US.” In Rural Policies and Employment. pp. 93–108.

Conroy, T., S. Deller, and A. Tsvetkova. 2017. “Interstate Relocation of Manufacturers and Business Climate.” Review of Urban & Regional Development Studies 29(1):18–45.

Conroy, T., S. Deller, and A. Tsvetkova. 2016. “Regional business climate and interstate manufacturing relocation decisions.” Regional Science and Urban Economics 60:155–168.

Conroy, T., S. Deller, and P. Watson. 2019. “Regional income inequality: a link to women-owned businesses.” Small Business Economics 2019 56:1 56(1):189–207.

Conroy, T., and S.C. Deller. 2020. “Regional level social capital and business survival rates.” Review of Regional Studies 50(2):230–259.

Conroy, T., and S.A. Low. 2021a. “Entrepreneurship, Broadband, and Gender: Evidence from Establishment Births in Rural America.” International Regional Science Review.

Conroy, T., and S.A. Low. 2021b. “Opportunity, necessity, and no one in the middle: A closer look at small, rural, and female-led entrepreneurship in the United States.” Applied Economic Perspectives and Policy (August):1–35.

Coughlin, C.C., and E. Segev. 2000. “Location Determinants of New Foreign-Owned Manufacturing Plants.” Journal of Regional Science 40(2):323–351.

Crandall, M.S., and B.A. Weber. 2004. “Local Social and Economic Conditions, Spatial Concentrations of Poverty, and Poverty Dynamics.” American Journal of Agricultural Economics 86(5):1276–1281.

Cuthbertson, C., A. Brennan, J. Shutske, L. Zierl, A. Bjornestad, K. Macy, P. Schallhorn, G. Shelle, J. Dellifield, J. Leatherman, E. Lin, and M. Skidmore. 2020. “Developing and Implementing Farm Stress Training to Address Agricultural Producer Mental Health:” Health Promotion Practice.

Das, A., and B. Das. 2019. “Economic and Fiscal Impacts of Refugees in Central Iowa: Opportunities for University Extension.” The Journal of Extension 2(57):2RIB3.

Das, B., and M. Skidmore. 2018. “Asymmetry in Muncipal Government Responses in Growing versus Shrinking Counties with Focus on Capital Spending.” Journal of Regional Analysis & Policy 48(4):62–75.

Deller, S., M. Kures, and T. Conroy. 2019. “Rural entrepreneurship and migration.” Journal of Rural Studies 66(January):30–42.

Deller, S., and B. Whitacre. 2019. “Broadband’s relationship to rural housing values.” Papers in Regional Science 98(5):2135–2156.

Deller, S., B. Whitacre, and T. Conroy. 2021. “Rural broadband speeds and business startup rates.” American Journal of Agricultural Economics.

Détang-Dessendre, C., M.D. Partridge, and V. Piguet. 2016. “Local labor market flexibility in a perceived low migration country: The case of French labor markets.” Regional Science and Urban Economics 58:89–103.

van Dijk, J., and P.H. Pellenbarg. 2000. “The Demography of Firms: Progress and Problems in Empirical Research.” In Demography of Firms: Spatial Dynamics of Firm Behaviour. Utrecht/Groningen: Netherlands Geographical Studies, pp. 325–337.

Dobis, E.A., H.M. Stephens, M. Skidmore, and S.J. Goetz. 2020. “Explaining the spatial variation in American life expectancy.” Social Science & Medicine 246:112759.

Dorfman, J.H., M. Partridge, and H. Galloway. 2011. “Do Natural Amenities Attract High-tech Jobs? Evidence From a Smoothed Bayesian Spatial Model.” Spatial Economic Analysis 6(4):397–422.

Duncan, G.J., J. Brooks-Gunn, W. Jean Yeung, and J.R. Smith. 1998. “How much does childhood poverty affect the life chances of children?” American Sociological Review 63(3):406–423.

Duncan, G.J., and K. Magnuson. 2013. “The Long Reach of Early Childhood Poverty.” In Springer, Dordrecht, pp. 57–70.

ERS. 2020. “Business & Industry.”

Gemmell, N., A. Grimes, and M. Skidmore. 2017. “Do Local Property Taxes Affect New Building Development? Results from a Quasi-Natural Experiment in New Zealand.” The Journal of Real Estate Finance and Economics 2017 58:2 58(2):310–333.

Gerking, S.D., and A.M. Isserman. 1981. “Bifurcation and the Pattern of Impacts in the Economic Base Model.” Journal of Regional Science 21(4):451–467.

Glaeser, E.L., H.D. Kallal, J.A. Scheinkman, and A. Shleifer. 1992. “Growth in Cities.” Journal of Political Economy 100(6):1126–1152.

Goetz, S.J. 1997. “State- and County-Level Determinants of Food Manufacturing Establishment Growth: 1987-93.” American Journal of Agricultural Economics 79(3):838–850.

Goetz, S.J., M.D. Partridge, and H.M. Stephens. 2018. “The economic status of rural America in the president trump era and beyond.” Applied Economic Perspectives and Policy 40(1):97–118.

Gourio, F., T. Messer, and M. Siemer. 2016. “Firm Entry and Macroeconomic Dynamics: A State-Level Analysis.” American Economic Review 106(5):214–218.

Green, B., K. Jones, R. Lyerla, W. Dyar, and M. Skidmore. 2020. “Stigma and behavioral health literacy among individuals with proximity to mental health or substance use conditions.” Journal of Mental Health 30(4):481–487.

Haltiwanger, J., R.S. Jarmin, and J. Miranda. 2013. “Who creates jobs? Small versus large versus young.” Review of Economics and Statistics 90(2):347–361.

Harris, T.R., and J.S. Shonkwiler. 1997. “Interdependence of Retail Businesses.” Growth and Change 28(4):520–533.

Harris, T.R., S.T. Yen, and S.C. Deller. 2000. “Estimation of minimum demand threshold: An application of count data procedure with the existence of excess zero observations.” Presented paper at the AAEA annual meeting.

Isserman, A.M. 2001. “Competitive advantages of Rural America in the next century.” International Regional Science Review 24(1):38–58.

Isserman, A.M., and J. Westervelt. 2006. “1.5 Million Missing Numbers: Overcoming Employment Suppression in County Business Patterns Data.” International Regional Science Review 29(3):311–335.

Jablonski, B.B.R., A. Bauman, and D. Thilmany. 2021. “Local Food Market Orientation and Labor Intensity.” Applied Economic Perspectives and Policy 43(3):916–934.

Jablonski, B.B.R., M. Carolan, J. Hale, D.T. McFadden, E. Love, L. Christensen, T. Covey, L. Bellows, R. Cleary, O. David, K.E. Jablonski, A.S. Jones, P. Meiman, J. Quinn, E.P. Ryan, M. Schipanski, H. Summers, and M. Uchanski. 2019. “Connecting Urban Food Plans to the Countryside: Leveraging Denver’s Food Vision to Explore Meaningful Rural–Urban Linkages.” Sustainability 2019, Vol. 11, Page 2022 11(7):2022.

Jablonski, B.B.R., M. Sullins, and D.T. McFadden. 2019. “Community-Supported Agriculture Marketing Performance: Results from Pilot Market Channel Assessments in Colorado.” Sustainability 2019, Vol. 11, Page 2950 11(10):2950.

Joudrey, P.J., E.J. Edelman, and E.A. Wang. 2019. “Drive Times to Opioid Treatment Programs in Urban and Rural Counties in 5 US States.” JAMA - Journal of the American Medical Association 322(13):1310–1312.

Keeler, Z.T., and H.M. Stephens. 2020. “Valuing shale gas development in resource-dependent communities.” Resources Policy 69:101821.

Kelsey, T.W., M. Partridge, and N.E. White. 2016. “Unconventional Gas and Oil Development in the United States: Economic Experience and Policy Issues.” Applied Economic Perspectives and Policy 38(2):191–214.

Klein, B.R., K. Allison, and C.T. Harris. 2017. “Immigration and Violence in Rural versus Urban Counties, 1990–2010.” The Sociological Quarterly 58(2):229–253.

Krugman, P.R. 1995. Development, Geography, and Economic Theory. Cambridge, MA: MIT Press.

Krugman, P.R. 1991a. Geography and Trade 1st ed. Cambridge, Massachusetts: The MIT Press.

Krugman, P.R. 1991b. “Increasing Returns and Economic Geography.” Journal of Political Economy 99(3):483–499.

Leatherman, J.C., and T.L. Kastens. 2009. “Modelling the probability of manufacturing in the Great Plains.” In S. J. Goetz, S. C. Deller, and T. R. Harris, eds. Targeting Regional Economic Development. New York, NY: Routledge, pp. 103–125.

Lee, M.R., M.O. Maume, and G.C. Ousey. 2009. “Social Isolation and Lethal Violence Across the Metro/Nonmetro Divide: The Effects of Socioeconomic Disadvantage and Poverty Concentration on Homicide*.” Rural Sociology 68(1):107–131.

Li, M., S.J. Goetz, and B. Weber. 2018. “Human Capital and Intergenerational Mobility in U.S. Counties.” Economic Development Quarterly 32(1):18–28.

Lobao, L., M. Zhou, M. Partridge, and M. Betz. 2016. “Poverty, Place, and Coal Employment across Appalachia and the United States in a New Economic Era.” Rural Sociology 81(3):343–386.

Lösch, A. 1954. The economics of location W. H. Woglom and W. F. Stolper, eds. New Haven: Yale University Press.

Low, S.A., M. Bass, D. Thilmany, and M. Castillo. 2020. “Local Foods Go Downstream: Exploring the Spatial Factors Driving U.S. Food Manufacturing.” Applied Economic Perspectives and Policy:aepp.13046.

Low, S.A., M. Bass, D. Thilmany, and M. Castillo. 2021. “Local Foods Go Downstream: Exploring the Spatial Factors Driving U.S. Food Manufacturing.” Applied Economic Perspectives and Policy 43(3):896–915.

Markusen, A. 1996. “Sticky places in slippery space: A typology of industrial districts.” Economic Geography 72(3):293–313.

McCann, P. 2002. Industrial Location Economics. Cheltenham, Glos: Edward Elgar Publishing.

McFadden, D. 1973. “Conditional logit analysis of qualitative choice behaviour.” In P. Zarembka, ed. Frontiers in Econometrics. New York, NY: Academic Press, pp. 105–142.

Mjelde, J.W., R.M. Dudensing, G. Battista, J. Brooks, M. Carrillo, B. Counsil, A. Giri, M.K. Kim, and V.D. Pyrialakou. 2020. “Rural Transportation Conference Participants’ Opinions and Concerns Pertaining to Transit for Older Adults:” Sage Open 10(2).

Munasib, A., and D.S. Rickman. 2015. “Regional economic impacts of the shale gas and tight oil boom: A synthetic control analysis.” Regional Science and Urban Economics 50:1–17.

O’Hara, J.K., M. Castillo, and D.T. McFadden. 2021. “Do Cottage Food Laws Reduce Barriers to Entry for Food Manufacturers?” Applied Economic Perspectives and Policy 43(3):935–951.

Orr, B., and J. Buongiorno. 1989. “Improving estimates of employment in small geographic areas.” Journal of Economic and Social Measurement 15(3–4):225–235.

Paredes, D., and M. Skidmore. 2017. “The net benefit of demolishing dilapidated housing: The case of Detroit.” Regional Science and Urban Economics 66:16–27.

Partridge, M., D.S. Rickman, M. Rose Olfert, Y. Tan, M.R. Olfert, and Y. Tan. 2017. “International trade and local labor markets: Do foreign and domestic shocks affect regions differently?” Journal of Economic Geography 17(2):375–409.

Partridge, M., A. Tsvetkova, and M. Betz. 2021. “Are the most productive regions necessarily the most successful? Local effects of productivity growth on employment and earnings.” Journal of Regional Science 61(1):30–61.

Patrick, C., and H.M. Stephens. 2020. “Incentivizing the Missing Middle: The Role of Economic Development Policy.” Economic Development Quarterly 34(2):154–170.

Pellenbarg, P.H., L.J.G. Van Wissen, and J. Van Dijk. 2002. Firm relocation: state of the art and research prospects. Groningen.

Petach, L., S. Weiler, and T. Conroy. 2021. “It’s a wonderful loan: local financial composition, community banks, and economic resilience.” Journal of Banking and Finance 126:106077.

Porter, M. 2003. “The Economic Performance of Regions.” Regional Studies 37(6–7):549–578.

Raganowicz, K. 2018. “Analysing the Cities’ Inward Investment Promotion Websites.” International Journal of Synergy and Research 6:149.

Rahe, M.L., and A. Hause. 2020. “Building rural wealth through a value chain approach.” Community Development 51(2):123–139.

Rahe, M.L., X. Wu, B. Weber, and M. Fisher. 2019. “Income Inequality and County Economic Resistance to Job Loss during the Great Recession.” The Review of Regional Studies 49:129–147.

Rutherford, T.D., G. Murray, P. Almond, and M. Pelard. 2018. “State accumulation projects and inward investment regimes strategies.” Regional Studies 52(4):572–584.

Van Sandt, A., C.W. Carpenter, R. Dudensing, and S. Loveridge. 2021. “Estimating determinants of healthcare establishment locations with restricted federal administrative data.” 2Health Economics 30(6):1328–1346.

Van Sandt, A., S.A. Low, B. Jablonski, and S. Weiler. 2019. “Place-Based Factors and the Performance of Farm-Level Entrepreneurship: A Spatial Interaction Model of Agritourism in the U.S.” The Review of Regional Studies 49(3):428–453.

Van Sandt, A., S.A. Low, and D. Thilmany McFadden. 2018. “Exploring Regional Patterns of Agritourism in the U.S.: What’s Driving Clusters of Enterprises?” Agricultural and Resource Economics Review 47:1–18.

Van Sandt, A.T., and C.W. Carpenter. 2021. “A Note on the Locational Determinants of the Agricultural Supply Chain.” U.S. Census Bureau CES-WP-21-(16).

Van Sandt, A.T., C.W. Carpenter, R.M. Dudensing, and S. Loveridge. 2021. “Estimating Determinants of Health Care Establishment Locations with Restricted Federal Administrative Data.” Health Economics 30(6):1328–1346.

Van Sandt, A.T., C.W. Carpenter, and C.M. Tolbert. 2021. “Decomposing Local Bank Impacts with Demand Thresholds.” Annals of Regional Science (Revise and resubmit).

Shonkwiler, J.S., and T.R. Harris. 1993. “A Non-Gaussian Time Series Analysis of Rural Retail Business Counts.” Journal of Regional Science 33(1):37–48.

Shonkwiler, J.S., and T.R. Harris. 1996. “Rural Retail Business Thresholds and Interdependencies.” Journal of Regional Science 36(4):617–630.

Shupp, R., S. Loveridge, M. Skidmore, B. Green, and D. Albrecht. 2020. “Recognition and stigma of prescription drug abuse disorder: personal and community determinants.” BMC Public Health 2020 20:1 20(1):1–9.

Stephens, H.M., and A.L. Weinstein. 2019. “Household valuation of energy development in amenity-rich regions.” Growth and Change 50(4):1375–1410.

Taylor, S., H.M. Stephens, and D. Grossman. 2021. “The Opioid Crisis and Economic Distress: Consequences for Population Change.” Journal of Regional Science (forthcoming).

Tewdwr-Jones, M., and N.A. Phelps. 2000. “Levelling the uneven playing field: Inward investment, interregional rivalry and the planning system.” Regional Studies 34(5):429–440.

Thilmany, D., E. Canales, S.A. Low, and K. Boys. 2021. “Local Food Supply Chain Dynamics and Resilience during COVID-19.” Applied Economic Perspectives and Policy 43(1):86–104.

Thilmany, D., N. McKenney, D. Mushinski, and S. Weiler. 2005. “Beggar-thy-neighbor economic development: A note on the effect of geographic interdependencies in rural retail markets.” The Annals of Regional Science 39(3):593–605.

Torrejón, C.A., D. Paredes, and M. Skidmore. 2020. “Housing demolition and property tax delinquency: Evidence from Detroit.” Journal of Urban Affairs 43(5):702–723.

Tsvetkova, A., and M. Partridge. 2016. “Economics of modern energy boomtowns: Do oil and gas shocks differ from shocks in the rest of the economy?” Energy Economics 59:81–95.

Tsvetkova, A., M. Partridge, and M. Betz. 2017. “Entrepreneurial and Employment Responses to Economic Conditions across the Rural-Urban Continuum:” The ANNALS of the American Academy of Political and Social Science 672(1):83–102.

Wang, J., M. Skidmore, Q. Wu, and S. Wang. 2020. “The impact of a tax cut reform on land finance revenue: Constrained by the binding target of construction land.”

Weber, A. 1909. Über den Standort der Industrien, translated by C.J. Friedrich (1929), Alfred Weber’s Theory of the Location of Industries. Chicago, IL: University of Chicago Press.

Weber, B., J.M. Fannin, S.M. Cordes, and T.G. Johnson. 2017. “Upward Mobility of Low-Income Youth in Metropolitan, Micropolitan, and Rural America.” The ANNALS of the American Academy of Political and Social Science 672(1):103–122.

Weinstein, A., M. Partridge, and A. Tsvetkova. 2017. “Follow the Money: How Does the Income Flow After an Energy Boom.” MPRA Paper No. 77336,

Whitacre, B., M.R. Alam, and B.J. Lobo. 2018. “Econometric error nullifies finding of the impact of broadband speed on county-level employment.” Information Economics and Policy 44:58–60.

Whitacre, B., R. Gallardo, and S. Strover. 2014. “Does rural broadband impact jobs and income? Evidence from spatial and first-differenced regressions.” Annals of Regional Science 53(3):649–670.

Wu, J., B.A. Weber, and M. Partridge. 2017. “Rural-Urban Interdependence: A Framework Integrating Regional, Urban, and Environmental Economic Insights.” American Journal of Agricultural Economics 99(2):464–480.

Xu, C., C. Jones, and M. Munday. 2020. “Tourism inward investment and regional economic development effects: perspectives from tourism satellite accounts.” Regional Studies 54(9):1226–1237.


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