Duration: 10/01/2024 to 09/30/2029

Administrative Advisor(s):

NIFA Reps:

Non-Technical Summary

Rural areas in the Northeast and nationally continue to struggle with recovery from Covid-19, which has compounded the long-term adverse impacts of globalization, technological change, job losses and population outmigration. Addressing these impacts is essential to ensure the sustainable growth of rural areas, which in turn are vital to the nation’s food supply and the stewardship of its natural resources. The Northeast Regional Center for Rural Development conducts original research with its partners and connects faculty and Extension educators in the region with one another and to national collaborators and resources, thereby creating synergies and reducing duplication of effort. Our five project goals are approved by the Center’s Board of Directors’ and are to: support rural economic development, innovation, and entrepreneurship; facilitate tourism development, including agritourism; address climate change and carbon levels; measure and promote food and nutrition security; and build regional capacity and facilitate the integration of research and outreach. The target audiences for our work range from farmers and other private businessowners to elected officials at the federal, state, and local levels. These individuals may benefit from this project by receiving research-based information to help guide the recurring decisions they have to make to remain profitable or to ensure sound and efficient uses of public expenditures. The activities proposed here will generate collaborative research findings, and through widespread dissemination of the results through presentations, working groups, factsheets, and other tools, we expect to reach all decisionmakers who may benefit from the project outputs.

Statement of Issues and Justification

The US Northeast’s agricultural and rural areas face challenges ranging from land use conflict to climate change, environmental concerns and lagging economic development, accentuated recently by the lingering effects of the Covid-19 pandemic. These regions also have significant opportunities to contribute to the nation’s prosperity and food supply, sustainability of the environment, and societal equity and justice (Mitchell et al., 2023), but more research is needed to identify specific, place-based feasible and sustainable strategies to realize these opportunities.

 

The Northeast Regional Center for Rural Development provides research-based information that helps create regional prosperity through entrepreneurial and cluster-based innovation, while assuring balanced uses of natural resources in livable communities in the northeastern United States. We carry out our mission by conducting original research with collaborators, pursuing strategic partnerships with public and private entities, and linking our stakeholders to opportunities and resources; we also compile and disseminate research-based outreach materials through a variety of formats. We serve as a hub that connects researchers and Extension educators across state borders and topic areas. Our work is motivated by the continuing challenges rural areas face both in the region as well as nationally. In essence, supporting NERCRD is an investment in the resilience and prosperity of the Northeast's rural populations, contributing to sustainable economic growth and improved quality of life for residents.

 

The need for the research proposed here has been indicated by stakeholders ranging from the leadership of the land grant universities in the Northeast to individual campus-based faculty and county-based educators, as well as by government and nonprofit or private sector partners. Specific sources of input include: the Center’s Technical Advisory Committee, which advises the Board of Directors; the results of comprehensive listening sessions on rural economic recovery from Covid-19 conducted by the four Regional Rural Development Centers on behalf of USDA-NIFA (Entsminger et al., 2023); the Northeast Agenda – A Joint Vision for the Future of the Northeast (Mitchell et al., 2023) prepared by the Northeastern Regional Association of State Agricultural Experiment Stations (NERA) and the Northeast Extension Directors (NEED); and other stakeholders including national program leaders at NIFA, the Economic Research and Forest Services, USDA Rural Development, and the NSF’s National Center for Science and Engineering Statistics.

 

Importance of the work: Providing research-based information to address the problems facing the Northeast is critical if taxpayer funds are to be put to their most cost-effective uses in addressing societal problems. If the work is not carried out communities and individuals will not have the opportunity to develop a complete and research-based understanding of the factors that support or impede growth of minority and female entrepreneurship, or the factors that support or impede tourism and agritourism development with sustainable beneficial impacts for the local communities where they are based; the factors that support decarbonization, innovation and the transition to renewable energy along with their impacts for different kinds of rural communities; historical crop production patterns and their shifts over time in order to predict future production prospects including implications for the spatial distribution of nutrient dense foods, with implications for population health.

 

Technical feasibility: as documented in the section below on Related, Current and Previous Work, the Northeast Regional Center for Rural Development has a proven track record of successfully completing the kinds of projects proposed here. As such, the feasibility of achieving the objectives is not in question.

 

Given the region-covering nature of the issues addressed, and limited faculty and educator resources at individual experiment stations in the region, taking a regional approach in a multi-state effort that draws on the expertise of collaborators in the different states represents a critical advantage.

 

Expected impacts of successful completion of this work include more-informed decision makers at all levels of government as well as individuals, farmers and businessowners throughout the region in different industries who make economic decisions about sustainable and profitable resource allocations every day. In turn, we expect to see more resilient, vibrant, and sustainable businesses, farms, and local economies over time, with more strategic federal and private investments that benefit from higher economic and social returns, including healthier populations and more equitable socioeconomic outcomes across different ethnic groups and across gender.

Related, Current and Previous Work

The Northeast Regional Center has a long history of contributing to the research and outreach needed to address the region’s current and emerging challenges. Selected highlights of the work undertaken by the Center include:

 

NERCRD staff use state-of-the-art research tools: We published the first application of artificial intelligence in the form of natural language processing to big data (Tweets) to predict where food supply chains were breaking down during Covid-19 (Goetz et al., 2023). This interdisciplinary research included faculty from the College of Information Sciences and Technology, and collaborators as far away as Doha, Qatar. Helping to train or support the next generation of scientists, the study also included two Ph.D. students, one postdoc and two junior faculty members.

 

The Center’s research (Tian et al., 2022) on the role of food pantries in reducing food insecurity early in the pandemic won an Outstanding Article Award from the Journal of Agricultural and Resource Economics and the 2023 High-Impact Research Publication in Nutritional and Food Security Award from the College of Agricultural Sciences at Penn State University.

NERCRD research has been used at the highest levels of the federal government: The 2019 Economic Report of the President, prepared by the Council of Economic Advisors (CEA), cited three scientific papers written by NERCRD staff and collaborating researchers (Goetz et al., 2018; Rupasingha and Goetz, 2013; and Goetz and Rupasingha, 2009); the older citations underscore the durability of the Center’s work. In an email, CEA Chairman K. Hassett wrote: “We found your research to be insightful and critical to the completion of the 2019 Economic Report of the President.”

 

NERCRD’s data resources have been used or cited in a variety of socioeconomic academic subdisciplines: The social capital data collection is recognized as the gold standard for measuring county-level social capital in numerous academic fields, with over 1,000 citations (Google Scholar). For example, it was used by economists at Harvard University and UC Berkeley in their groundbreaking study on rural and urban economic mobility (Chetty et al., 2014).

NERCRD's own research on intergenerational mobility has also been impactful. A News story about a NERCRD study of human capital and intergenerational mobility (Swayne, 2018) received more than 3,400 comments on Reddit, and more than 57,000 “upvotes,” signaling that the topic resonated with these users.

 

The Center has been instrumental in supporting the national recreation economy, a critical new engine of rural economic growth. Starting with its support of the National Extension Tourism Network (see, e.g., Extension Foundation, 2022), the Center assisted West Virginia University, Vermont, New Hampshire and Penn State faculty in securing an AFRI competitive grant, and also secured New Technologies in Agricultural Extension funding. This was followed by the establishment of a new regional Hatch project (NE2251, Tourism Resilience and Community Sustainability: Adaptation and Recovery of Rural Businesses and Destinations). Most recently, the Regional Rural Development Centers were charged by NIFA to help implement a Memorandum of Understanding between NIFA, the Forest Service and Rural Development (USDA, 2022).

 

In addition to training graduate students and postdoctoral students, the Center was instrumental in helping a total of seven faculty members secure six major NIFA grants, to the best of our knowledge, for the first time. The Center’s earlier $5mn local food systems grant connected extension educators at Penn State, Cornell and West Virginia State University and other land grants with faculty at Columbia, John Hopkins, and Tufts universities, among others.

 

As noted above, this proposal draws on a large body of ongoing, related and previous work that is guided by the Center’s Technical Advisory Committee and approved annually by a Board of Directors (land grant university administrators), and a large-scale listening session effort that the Center conducted in 2022 along with its three counterpart institutions in the North Central, Southern and Western regions on behalf of NIFA (Entsminger et al., 2023). This proposal also aligns closely with the three Key Priorities set forth in the Northeast Agenda document (Mitchell et al., 2023), as well as USDA-NIFA goals. The Center’s Board-approved broad priority areas currently are: 1. Economic development, resilience, and innovation; 2. Food systems, nutrition security, and agriculture; and 3. Capacity building and facilitation. Within these three broad priority areas, the five specific objectives listed in the next section are proposed over the next 5 years.

Objectives

1. Support rural economic development and entrepreneurship, and innovation. We will conduct research and outreach on the success factors, barriers and opportunities for entrepreneurs in the region, including the roles of access to credit, broadband and market information, as well as child and elder caregiving. We will also examine the barriers facing farmers using National Agricultural Statistics Service and related public data sets and seek to evaluate the role of policy levers in facilitating access to credit among other resources.
   
2. Facilitate tourism development, including agritourism. We will help to implement the new Memorandum of Understanding signed by NIFA, Rural Development and the U.S. Forest Service, with the goal of helping rural communities take better advantage of their natural resources, while managing them in a sustainable manner. In Northeast states without large forest stands, we will conduct research to help communities understand their tourism possibilities. We will conduct research on the role of clusters and other explanatory factors in supporting tourism expansion and resilience and develop research-based outreach materials to assist farmers seeking to expand their agritourism activities, taking advantage of synergies and proximity to urban consumers. The importance of infrastructure development, including broadband availability and physical accessibility as measured in the Economic Research Service’s new ruggedness index, will also be assessed.
   
3. Measure and promote food and nutrition security. We propose to build on the Center’s long history of work on local and regional foods systems by documenting the contribution of the region’s food system to the nation’s nutrient supply (lacking the masses of land needed to grow bulk commodities, the region nevertheless contributes disproportionately to the quality of the nation’s diet). This is important given the rise of obesity and malnourishment even in the presence of adequate food production levels. Part of the analysis will seek to document shifts in crop production at the state-level over time, including the roles of population pressure on land as well as shifting production belts. We will also examine changes in diet quality over time, and during economic shocks, such as Covid-19.
   

Methods

1. We will estimate state-of-the-art statistical models using confidential data from the Penn State Federal Research Data Center (RDC) on the growth characteristics, survival constraints and opportunities facing female and ethnic minority entrepreneurs in the Northeast region. Collaborating faculty in WV, ME, PA, at 1890 institutions and the Economic Research Service, among others, will be critical to carrying out the objective by providing guidance and model specification, analysis, publication and dissemination of results. The individual level data will be tied to specific counties allowing us to assess how both individual and contextual as well as spatial clustering factors affect entrepreneurial success. Typical regression models will be of the form Y = a + bX + cZ + e where Y is some outcome variable such as profit or employment growth, X is a set of county level characteristics such as the rural-urban continuum score or population density as measures of market access, natural amenities, existing business services and agglomeration factors, among others. Z denotes a set of entrepreneur-specific variables such as gender, age, ethnicity, education, industry sector and others. We will used appropriate statistical techniques such as limited dependent variables models or spatial error and spatial lag specifications as necessary. Also, as necessary we will explore the use of instrumental variables or synthetic control methods. Bayesian methods of analysis will be used in cases of modeling uncertainty (e.g., Gelman et al., 2013, Schmidt et al. 2024). In certain specifications we will also use data collected at different points in time, so that the dependent variable Y can be measured over time as a log or percent change (dY), and the initial or starting value of Y is included as a control variable among the regressors, allowing for explicit tests of convergence. This will allow us to assess the effect of economic and other shocks, such as recessions or the Covid-19 pandemic on food system and other entrepreneurs, including those operating breweries, wineries, distilleries or cideries. We will also explore the measurement and use of entrepreneurial ecosystem-type variables at the county level. This will include both labor force characteristics and the availability of services, such as bank branches, adult and childcare service facilities, or broadband availability. We will use caregiver data collected in collaboration with the North Central Regional Center for Rural Development and also use secondary public data such as that collected in the Household Pulse Survey. Institutional variables such as the Community Reinvestment Act designation will be considered as well in terms of their impact on outcome variables such as access to credit. Policy variables from the USDA’s Economic Research Service and natural indicators such as the Amenities Index and the new Ruggedness measure also will be considered.

2. In collaboration with the Outdoor Recreation Group, formed in response to the release of the USDA NIFA-RD-FS MOU, we will model and analyze barriers and constraints facing various tourism destination management organizations (DMOs), and also provide training for lagging regions that have not yet taken advantage of their natural resources, including agritourism opportunities. The primary methods of analysis will include county-level data over time, so that the impact of different shocks on resilience can be evaluated both in the short and long terms. In the initial phase we will conduct spatial analyses to assess overlap in the service areas of NIFA, the Forest Service, and Rural Development, in order to identify priority locations for interventions. Here collaborations with expert faculty in WV, ME, NH and VT among other states will be critically important to the successful implementation of the objective. In addition to using secondary data, we anticipate collecting primary survey data to specifically identify key challenges, priorities, and resource needs of DMOs. We will use appropriate stratifications in order allow comparisons among different tourism destination to facilitate the identification and sharing of best practices across different locations. For example, well-known destinations such as the Acadia National Park in Maine are challenged by over-tourism and need programs to better support tourists while managing visitor numbers in sustainable ways. Other locations, such as PA Wilds and selected individual counties such as Wyoming, PA in rural Pennsylvania (https://www.nicholsonheritage.org) do not yet have the scale needed to attract a large number of diverse tourists; in fact, they often face a chicken and egg situation where the services are not forthcoming because tourists are few in numbers, and the number of tourists is limited by a lack of attractions and leisure and hospitality services. Here the challenge is for individual counties and regions to collaborate and cluster in breaking out of the dilemma. With careful comparisons and models of different communities based on secondary data and custom surveys, we expect to be able to identify best practices to help different types of communities grow to scale. On the agritourism side, we will use secondary data analysis to evaluate the impact of agri-tourism on local community indicators. For example, we will estimate regression models of the form Y = a + bX + cZ + e where Y is some community level outcome such as farm income, local income, poverty or employment growth, X is set of county level economic or farm conditions (such as livestock vs. crop agriculture), broadband availability, ease of access, population density or distance to major metropolitan areas, which control for local context. In this specification, Z is a measure of agritourism, such as the number of farms offering such services, or the income earned from providing the services. Using time series data, it will be possible to assess the impact of different kinds of shocks on tourism revenues and resilience.

3. We plan to use secondary data, including input-output tables to begin to assess the potential for building green energy related supply chains in the northeast states, along with their impacts and the factors contributing to their emergence. Using state-level data on greenhouse gas (GHG) emissions over time available at U.S. Energy Information Administration (EIA, https://www.eia.gov/environment/emissions/state/), we will document how different states are managing the transition to green energy, along with the contributions of different industrial sectors to carbon dioxide emissions. The use of satellite-based carbon emission sites will also be explored, as a means of verifying and complementing the survey-based data. We propose to use existing public data, as well as the new Census Bureau’s Annual Business Survey (ABS) (https://www.census.gov/programs-surveys/abs.html), to identify barriers to and opportunities for firms both to adopt and to generate green energy in their production facilities. This modeling will include state, county and firm-level analyses of changing greenhouse gas emissions over time, including the impact on different racial groups and different business types, including farms. We will combine firm level and county level secondary data in the analysis. More specifically, identifying where carbon-intensive industrial activity occurs is critical for understanding possible routes to a low-carbon economy, and for identifying impacts on communities and workers. We propose to use microdata from the 2014, 2018 and 2022 Manufacturing Energy Consumption Survey (MECS) (EIA 2015, 2019 and 2023) to estimate the carbon performance of individual establishments across all manufacturing industries, examine the locational characteristics of these various establishments, and test hypotheses about the locational (community) characteristics most conducive to carbon-intensive activity. The MECS provides comprehensive data on all forms of energy used by manufacturing plants during the reference year. By applying an emissions factor – a coefficient produced by EPA that describes the rate at which a given energy type releases greenhouse gases into the atmosphere – to these data we can accurately estimate emissions from each plant (Boyd and Lee 2020). Normalizing carbon emissions by total revenue or employment allows comparisons of carbon performance across establishments. Employment and payroll data for the MECS firms will be merged with the Longitudinal Business Database (LBD) using firm specific identifiers. Revenue is not available in non-Economic Census years (2014 and 2018) but can be imputed using payroll to revenue ratios by detailed industry in the nearest Economic Census year. An OLS regression of carbon performance provides information on the factors contributing to carbon performance at the mean. However, testing hypotheses of factors associated with high emissions plants requires quantile regression that can examine associations throughout the carbon performance distribution. The hypothesis that disadvantaged areas are more likely to attract more polluting industries has been well researched in the environmental justice literature (Mohai et al. 2009; Goetz and Kemlage 1996) but the evidence with respect to rural areas is much thinner (Cohen 1997). Testing the effects of population density, land values, topography, and socio-economic disadvantage on carbon intensive activities will provide information on where the challenges and opportunities with respect to the low-carbon transition are greatest.

Logistic regression with bias correction for rare events as proposed by King and Zeng (2001) is well suited for estimating the probability of rare events, especially when the sample size is large as is the case here. In addition to 300,000 firm level observations in the 2022 American Business Survey (ABS), multi-unit firms have each of their establishments included in an establishment file with roughly 2.2 million observations. The establishment file contains only rudimentary information such as NAICS industry, location, and employment size. However, these data are sufficient to test the central hypotheses of the associations between location characteristics and reported renewable energy R&D and use at the firm level. We will use the 2022 ABS data to estimate the following logistical regression equation: Prob(Renewables R&D=1) = b0 + bX + e where suppressed index i and j denote firm and county, respectively and the X are the following regressors: establishment age, firm size, publicly held company status, intent to eliminate, replace or reduce carbon emissions, 2030–2050 decarbonization goals, environmental innovation, strategy failure risks, climate shock, FEMA climate shock, republican vote 2020, socio-economic level, population density, land value, natural amenity scale, solar energy potential, average wind speed, ruggedness, transmission access, airports, land cover, decarbonization actions, and industry fixed effects. A similar equation replaces R&D with renewable energy use as the dependent variable. As noted, a simple logistic model using maximum likelihood estimation for rare events is biased, so we use the bias-corrected approximate Bayesian estimator in King and Zeng (2001). We will use firm and county (X) controls to identify factors at each level that are correlated with R&D on renewables and the use of various forms of onsite renewable energy. Firm-level variables of interest include the industry (given by the NAICS code), firm size (question A.8), and revenue (question A.11). County-level controls will include factors that encourage or discourage renewable energy siting, many of which come from previous studies (e.g., Hitaj 2013) and ongoing work from Justin Winikoff at the ERS. Key variables will include transmission access, renewable (solar and wind) potential, land values and existing renewable energy development. Controls will also include key variables measuring rurality in various ways, such as population density and the amount of undeveloped land suitable for renewable energy. Critically important under this objective will be a collaboration with the National Extension Climate Initiative (NECI), currently chaired by Dr. David Kay of Cornell University. Successfully modeling the determinants and impacts of shifting to green energy also requires local, state-level knowledge of communities, preferences, and policies, for example in NY and NH, so that a multi-state approach is required.

4. Using public data, including from the Household Pulse Survey as well as other sources, we will examine how the food security and quality situation of different households stratified by ethnicity and income was affected by Covid and its aftermath, including the effect of public covid support payments. We will use agricultural Census and NASS historical data to document the production of different crops and related products over time and compare the region’s contributions to those of the nation. Shift share analysis will be used to identify the contribution of competitive factors in crop acreage growth or decline. We will use proprietary grocery store scanner data (IRI) to calculate household level diet qualities indices and public secondary data to model and assess differences in population health at the county-level.

Following Loveridge and Selting (1998) and Artige and van Neuss (2014) who discussed an assortment of variation in the shift-share formulation, we apply the most basic approach to computing shift-shares for crop production (Dunn Jr., 1960). The shift-share analysis decomposes the total change in crop production into three components: (1) a national growth effects: the amount of all crops of a state would have grown or decline if it had changed at the same rate as the nation; (2) a commodity mix effect: the amount of change attributable to differences in the commodity makeup of a state versus that of the nation (we use the term of commodity mix effect to replace the industry mix component in the original shift-share definition). (3) a competitive effect: the amount of local crop production changes not attributable to national growth or commodity mix effects. A positive competitive effect for a particular crop indicates competitive advantages in its production. With the crop-specific shift-shares, we can examine the comparative advantages in producing specific types of crops, for example, using the four-cell table analysis. To explore economic and natural drivers for the shifts in shares, we regress each component of the shift-share change for individual crops separately on the growth of personal income, population density as a proxy for land costs, precipitation and drought variables, and others.

5. This objective will be achieved though zoom meetings organized around specific topics corresponding to the different objectives, as well as a wide variety of outreach materials for peer reviewed research findings, including factsheets, infographics, bulletins, and short reports. In selected cases and for certain objectives, such as for the results that will be of interest to DMOs, we will prepare data dashboards containing information in as close to real time as possible. For county leaders we will also provide informational materials related to decarbonization and entrepreneurial growth conditions, some of which may be presented in the form of dashboards. Communicating the relevant research results generated both by the Center and collaborators both to the region and beyond, including policymakers, is a priority. A multi-state approach is essential not just for ensuring that state differences in policies and conditions are reflected in the research, but also for widespread distribution of results to where they are most needed.

Measurement of Progress and Results

Outputs

• The most common type of output will be in the form of peer-reviewed scientific publications, the results of which will be shared at conferences, workshops, and Congressional briefings, as appropriate, and once “translated” also serve as the basis of lay audience-friendly information and outreach materials, including webinars, factsheets, data dashboards and press releases. These outputs are expected to be of value to stakeholders or end users in making critical day-to-day decisions, whether they are in the public, nonprofit or private sectors, including on farming operations. Specific metrics include scholarly citation counts, audience members reached or attending webinars, media mentions, and references to the results in media such as newspapers or social networks, and invitations to present findings at conferences and selected audiences.
• In addition to curating and presenting publicly available state- and county-level data sets both in tabular and in mapped formats, we will make the deidentified data from the caregiving survey available on our website for others to use; this may include faculty, educators and graduate students interested in the conditions surrounding caregiving. In addition, we will present basic descriptive statistics from the survey, pending data cleaning and analysis. This and other data sets will benefit end user-stakeholders directly, and other products such as the maps will help end users visualize conditions over rural space and how these are changing over time.
• Another tangible output is the networks of researchers and educators convened around specific pressing problems and issues arising in the rural Northeast. One component of this capital will be the post docs and graduate students trained over the life of this project. Members of the networks will benefit directly from the network effects including the sharing of resources, insights, and information while the students will be better prepared to take on employment in academia or the private sectors. Metrics tracked here will include supplemental grant funds secured and other indicators that the results presented resonate with stakeholders (e.g., “upvotes” on Reddit). We will track emerging collaborations with faculty and educators in the Northeast region, as well as networks formed as a result of this work.

Outcomes or Projected Impacts

• One key set of projected impacts is the improved social and economic outcomes in rural communities, for both businesses and individuals. For example, Destination Management Organizations in congested tourist areas will better manage the influx of tourists, while communities that are unable to attract enough tourists to achieve a minimum efficient scale will collaborate with surrounding communities to develop a more viable tourist economy. Similarly, agritourism communities and related offerings such as beer or winery trails will be more economically vibrant. Areas known for high levels of greenhouse gas emissions will be moving towards a path of decarbonization, using the insights generated in this project from the analyses of secondary public data.
• Decisionmakers in the public and private sectors will have a better understanding of the various constraints facing small entrepreneurs, including across ethnic and gender lines. These are expected to reflect market and credit access, broadband and services such as child or adult daycare. They will be provided with the tools and resources needed to address these barriers.
• Ultimately, better physical and mental health outcomes, and lower poverty and higher, more equitable income growth over time as reflected in secondary, publicly available data, are key expected impacts of this project.

Milestones

(0):A first milestone will be reached when the data needed to carry out the statistical work under objectives 1 to 4 have been extracted, verified and compiled into appropriate software, such as Stata or R. In general, we expect this to take no more than one year for the publicly available data, although accessing the highly confidential data in the federal Research Data Center may take longer. In parallel, this first milestone will include the forming of objective-specific groups of multi-state collaborators.

(0):The second milestone will be reached once the data have been analyzed, written up in reports, and submitted for peer review to scientific journals. Across the three objectives, we expect this to take from two to four years. In parallel to this milestone, we will have formed networks of researchers and educators around specific objectives and sought additional funding to leverage, extend and deepen the work compiled to this date. We will also have started to disseminate peer-reviewed research results through various media by the time this milestone is reached.

(0):The last milestone will be reached after the outreach materials have been prepared, reviewed and distributed through various print and in-person venues through year 5 of the project.

Projected Participation

View Appendix E: Participation

Outreach Plan

As noted above, outreach is a critical objective (no. 5) of the project itself and includes various forms of printed materials as well as webinars providing further detailed information. Given the extensive networks that the Center already has in place, we expect the results to be defused widely, including to the stakeholders in the individual states of the Northeast U.S., for example through faculty and Extension educators. We also expect to share results with our key funders and elected representatives in Congress. The Center also produces an annual report and a quarterly newsletter (appearing with greater frequency, as needed).

Organization/Governance

The Center is funded through multiple sources including a directed or prime grant from NIFA, competitive grants, Hatch Multistate Research Funds (NERA funding), and state funds and, from to time, private foundation funds. This proposal is directly related to the Hatch MRF. The Center is led by a director who works closely with faculty and educators both in the region and, through the other RRDCs, nationally. In addition, The Center is guided by a technical advisory committee and is governed by a Board of Directors, comprised of Northeast land grant university Deans or Directors.

 

Collaborators

Technical Advisory Committee members (tbd)

David Abler, Ph.D., Prof. of Ag, Env. & Reg. Econ. and Demog., Interim Head, AESE PSU

Andrew Crawley, Ph.D., Assistant Professor, School of Economics, Univ. of Maine
Heather Stephens, Ph.D. (Chair), Assoc. Prof. and Director, RRI, West Virginia Univ.

Doug Arbogast, Ph.D., Rural Tourism Specialist, West Virginia University

Adam Hodges, CED Program Leader, West Virginia State University
David Kay, Senior Extension Assoc., CaRDI and Dept Development Sociology, Cornell U.
Shannon Rogers, Ph.D., Associate Extension Professor, Univ. of New Hampshire

Andy Wetherill, Adjunct Professor and Agribusiness Specialist, Delaware State Univ.

Peter Wulfhorst, ECD Educator, Penn State Extension, Pike County

 

Zheng Tian, Assistant Research Professor, NERCRD, AESE Penn State

Claudia Schmidt, Assistant Professor and Extension Specialist, AESE Penn State

 

Other faculty and educators in the region, as well as nationally, tbd.

Counterpart Regional Rural Development Centers and their staff (generally topic-specific)

 

Literature Cited

Artige, Lionel, and Leif van Neuss. 2014. A New Shift-Share Method. Growth and Change, 45 (4): 667–83. https://doi.org/10.1111/grow.12065.

 

Boyd, G.A. and J.M. Lee. 2020. Relative effectiveness of energy efficiency programs versus market based climate policies in the chemical industry. The Energy Journal, 41(3).

 

Chetty, Raj, Nathaniel Hendren, Patrick Kline, Emmanuel Saez. 2014. Where is the Land of Opportunity? The Geography of Intergenerational Mobility in the United States. Quarterly Journal of Economics 129(4): 1553-1623, June 2014.

 

Cohen, M.J., 1997. The spatial distribution of toxic chemical emissions: Implications for nonmetropolitan areas. Society & Natural Resources 10(1):17-41.

 

Cleary, R., Goetz, S. J., and Schmidt, C. 2022. Population Threshold Models for Local Alcoholic Beverage Manufacturing. Presented at the European Association of Wine Economists annual Meeting, Douro​, Portugal, May 19, 2022.

 

Devlin, Kristen. 2018. Study of Northeast Food System Advances Understanding of Regional Potential. Penn State News, October 18, 2018. https://www.psu.edu/news/research/story/study-northeast-food-system-advances-understanding-regional-potential/

 

Dunn Jr., Edgar S. 1960. A Statistical and Analytical Technique for Regional Analysis. Papers in Regional Science, 6 (1): 97–112. https://doi.org/10.1111/j.1435-5597.1960.tb01705.x.

 

Energy Information Agency. 2015. 2014 Manufacturing Energy Consumption Survey [Survey Instrument].  United States Department of Energy. https://unstats.un.org/unsd/environment/Censuses%20and%20Surveys/United%20States%20of%20America,%20Manufacturing%20Energy%20Consumption%20Survey,%202014.pdf

 

Energy Information Agency. 2019. 2018 Manufacturing Energy Consumption Survey [Survey Instrument].  United States Department of Energy. https://www.eia.gov/survey/form/eia_846/form_a.pdf

 

Energy Information Agency. 2023. 2022 Manufacturing Energy Consumption Survey [Survey Instrument].  United States Department of Energy. https://www2.census.gov/programs-surveys/mecs/technical-documentation/questionnaires/eia846.pdf

 

Entsminger, Jason, John Green, Rachel Welborn, Renee Wiatt, Z Bednarikova, Rianna Gayle, Yuxuan Pan and Stephan J. Goetz. 2023. Comprehensive Summary of National Rural Development Stakeholder Listening Sessions. Regional Rural Development Centers. https://www.usu.edu/rrdc/listening-sessions.

 

Extension Foundation, 2022. The NET Effect: Extension professionals help raise the bar in outdoor tourism and recreation industry, 1st edition, Kansas City, MO. Available: https://extension.org/portfolio-item/the-net-effect-members-of-the-national-extension-tourism-network-help-raise-the-bar-in-sustainable-tourism-and-outdoor-recreation/

 

Gelman, Andrew, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, and Donald B. Rubin. 2013. Bayesian Data Analysis. 3rd edition. Boca Raton London New York: Chapman and Hall/CRC.

 

Goetz, S.J. and A. Rupasingha. 2009. Determinants and Implications of Growth in Non-Farm Proprietorship Densities: 1990-2000. Small Business Economics. 32(4): 425-38.

 

Goetz, Stephan J., Connor Heaton, Muhammad Imran, Yuxuan Pan, Zheng Tian, Claudia Schmidt, Umair Qazi, Ferda Ofli, and Prasenjit Mitra. 2023. Food Insufficiency and Twitter Emotions during a Pandemic. Applied Economic Perspectives and Policy, April, aepp.13258. https://doi.org/10.1002/aepp.13258.

 

Goetz, S.J. and D.J. Kemlage. 1996. TSD Facilities Location and Environmental Justice. Review of Regional Studies 26 (Fall): 285-300.

 

Goetz, S.J., M. Partridge and H. Stephens. 2018. The Economic Status of Rural America in the President Trump Era. Applied Economic Policy Perspectives 40(1): 97-118.

 

Han, Yicheol, Stephan J. Goetz, and Claudia Schmidt. 2021. Visualizing Spatial Economic Supply Chains to Enhance Sustainability and Resilience. Sustainability 13 (3): 1512. https://doi.org/10.3390/su13031512.

 

Hitjaj, C. 2013. Wind Power Development in the United States. Journal of Environmental Economics and Management 65(3): 394-410.

 

King, G., and Zeng, L. 2001. Logistic Regression in Rare Events Data. Political Analysis, 9(2), 137–163. https://doi.org/10.1093/oxfordjournals.pan.a004868

 

Kolodinsky, Jane, and Stephan J. Goetz. 2021. Theme Overview: Rural Development Implications One Year after COVID-19. Choices Quarter 3 (July). https://www.choicesmagazine.org/choices-magazine/theme-articles/rural-development-implications-one-year-after-covid-19/theme-overview-rural-development-implications-one-year-after-covid-19.

 

Loveridge, Scott, and Anne C. Selting. 1998. A Review and Comparison of Shift-Share Identities. International Regional Science Review 21 (1): 37–58. https://doi.org/10.1177/016001769802100102.

 

Mitchell, A. et al. 2023. “Northeast Agenda 2023,” Northeast Research Association of State Agricultural Experiment Station Directors and Northeast Extension Directors, 24pp. See: https://www.nerasaes.org/_files/ugd/895599_a93391aa793e4c1688e4ac3f6b134c7b.pdf.

 

Mohai P, Pellow D, Roberts JT. 2009. Environmental justice. Annual review of environment and resources, 34, pp.405-43

 

National Academies of Sciences, Engineering, and Medicine. 2021. Accelerating Decarbonization of the U.S. Energy System. Washington, DC: The National Academies Press. https://doi.org/10.17226/25932.

 

Northeast Regional Center for Rural Development. 2019. NERCRD research cited in the 2019 Economic Report of the President. https://aese.psu.edu/nercrd/about/nercrds-impact/nercrd-research-cited-in-the-2019-economic-report-of-the-president-1

 

Rupasingha, A. and S.J. Goetz.  2013. Self-Employment and Local Economic Performance: Evidence from US Counties,” Papers in Regional Science. 92(1): 141-161.

 

Schmidt, Claudia, Stephan J. Goetz and Stephen C. Deller 2024 (in press) “Women farmers and community well-being under modeling uncertainty,” Applied Economic Perspectives and Policy.

 

Schmidt, Claudia, Sarah Cornelisse, and Harry Crissy. 2021a. Craft Beverage Trail Collaborations in Pennsylvania: A Resource for Breweries and Destination Marketing Organizations. Northeast Regional Center for Rural Development. Northeast Regional Center for Rural Development. https://bit.ly/3A0CN7h.

 

Schmidt, Claudia, Stephan J. Goetz, and Zheng Tian. 2021b. Female Farmers in the United States: Research Needs and Policy Questions. Food Policy 101 (May): 102039. https://doi.org/10.1016/j.foodpol.2021.102039.

 

Swayne, Matt. 2018. Investing in Public Education Earns High Marks for Greater Upward Mobility. Penn State News, March 28, 2018. https://news.psu.edu/story/511311/2018/03/28/research/investing-public-education-earns-high-marks-greater-upward-mobility.

 

Tian, Zheng, Claudia Schmidt, and Stephan J. Goetz. 2022. The Role of Community Food Services in Reducing U.S. Food Insufficiency in the COVID-19 Pandemic. Journal of Agricultural and Resource Economics. https://doi.org/10.22004/AG.ECON.313316.

 

United States Department of Agriculture. 2022. Memorandum of Understanding Among the United States Department of Agriculture Rural Development United States Forest Service and National Institute of Food And Agriculture on Supporting Outdoor Recreation Economy. https://www.fs.usda.gov/sites/default/files/USDA-Interagency-Outdoor-Recreation-Economy-Memorandum-of-Understanding.pdf

Attachments

Land Grant Participating States/Institutions

PA

Non Land Grant Participating States/Institutions

Pennsylvania - Pennsylvania State