Led by experts from Esri, this 3-hour workshop focuses on strengthening analytical workflows through the use of spatial tools. The training is designed for researchers and practitioners interested in improving the efficiency and impact of their data analysis and reporting.

The workshop will highlight the use of Business Analyst Online (BAO) to support more efficient data access, integration, and visualization. Participants will be introduced to practical approaches for incorporating spatial context into analysis, enabling a more comprehensive understanding of economic and demographic patterns.

An overview of the ArcGIS environment will also be provided, with particular attention to ArcGIS StoryMaps as a platform for presenting findings. The session will demonstrate how StoryMaps can be used to communicate complex information in a structured and accessible format.

Given that many institutions already maintain access to these tools, the session emphasizes practical application and integration into existing workflows. Spatial analysis represents an opportunity to extend traditional approaches and provide additional depth to applied research and reporting.

What you’ll take away:

• Faster workflows for data access, analysis, and reporting in BAO.
• Practical techniques for enhancing data visualization outputs.
• A working understanding of StoryMaps for communicating research findings.
• Immediately applicable methods that complement your existing analytical approach.

Workshop Registration

• Select “Workshop” when registering for the conference.
• Workshop fee includes a boxed lunch, available Noon – 1:00 p.m.
• Discount for undergraduate and graduate students (must show student ID at check-in).

Kana Norimoto is a managing director of Asset Allocation Research in the Global Asset Allocation division at Fidelity Investments. Fidelity Investments is a leading provider of investment management, retirement planning, portfolio guidance, brokerage, benefits outsourcing, and other financial products and services to institutions, financial intermediaries, and individuals. GAA is an investment team within Fidelity’s Asset Management Solutions division, an investment organization that provides industry-leading multi-asset solutions to the retail and institutional marketplace.

In this role, Kana is responsible for leading the Asset Allocation Research Team, which conducts fundamental and quantitative research to develop asset-allocation recommendations for Fidelity’s portfolio managers and investment teams. AART generates insights on macroeconomic, policy, and financial market trends and their implications for strategic and active asset allocation.

Prior to assuming her current role, Kana was a macro research analyst in the Fixed Income division at Fidelity Investments. ln this role, Kana was responsible for analyzing economies of the U.S., China, and Japan through a fixed income lens with a focus on the monetary policies of central banks in these countries. She was also responsible for research on the credit cycle and understanding global capital flows that drive returns on fixed income assets.

Previously, Kana was a fixed income bank analyst covering UK, Japanese, and Singaporean banks in Fidelity’s London office. Before joining Fidelity, she worked as a research analyst covering European banks in developed and emerging markets for Citigroup in London from 2002 to 2008. Previously, she was based in Japan, covering the Japanese banks for Nikko Salomon Smith Barney from 1999 to 2002. Kana also worked as an associate analyst covering U.S. and Japanese banks for Salomon Brothers in New York from 1995 to 1999. Kana joined Fidelity in 2008 and has been in the financial industry since 1995.

Kana earned her Bachelor of Arts from Smith College and her Master of Arts from Columbia University.

Director of the Center for Business and Economic Development at the University of Nevada, Las Vegas, 1986-2009, where he was also Professor of Economics.

His academic work appeared in Annals of Regional Science, Journal of Applied Economics, and the Review of Regional Studies, among other journals.

Although he is best known for directing the Center at UNLV, Keith worked all over the country, including in Maryland, Oklahoma, Tennessee, Vermont, and Wyoming, and certainly, that breadth of experience informed his skill and dedication to applied economics and regional economic development.

His bi-annual Economic Outlook Conferences in Las Vegas were famous for being accurate but also enjoyable to attend.

He was among a handful of AUBER members attending the NABE fall meeting at the Marriott Hotel between the Twin Towers on 9/11.

Attended the Austin AUBER conference in October 2009, just two months before he lost his fight with cancer.

Keith was an AUBER Fellow, a Fall Conference Host, and a former AUBER President. He was so accomplished at so many of the things that AUBER directors and researchers are called to do in their communities: serve on state and local advisory boards and commissions; comment on local economic conditions in print media, radio, and television; and mentor others who are doing similar work. He was an important and generous mentor to so many AUBER members that we have dedicated our annual forecast keynote to his memory.

Paper by Niaoniao You, University of Arizona; Jacob Burton, University of Michigan; Gabriel Ehrlich, University of Michigan; Daniil Manaenkov, University of Michigan; Michael R. McWilliams, University of Michigan; Yinuo Zhang, University of Michigan

Regional economic data, such as metro-area-level inflation, arrives late and without seasonal adjustment, limiting its usefulness for real-time decision-making. This project addresses both problems for the Detroit Consumer Price Index, a metro-area measure published every two months with a one-month lag.  The project interpolates missing monthly observations and applies city-specific seasonal adjustment to produce a cleaner, higher-frequency series. Both methods are replicable across the roughly twenty other metro areas that share Detroit’s data limitations.

Paper by Scott Adams, UNC; Kyle Henson, UNC

The Kenan Institute of Private Enterprise at the University of North Carolina-Chapel Hill, is building a statewide resource for county-level economic nowcasts and forecasts to support more informed local and regional decision-making. The initiative addresses a gap in North Carolina’s data infrastructure by combining econometric forecasting models for all 100 counties in the state, along with public-facing dashboards, place-based indicators, and translational research products.

This session will share our model-building approach, stakeholder-driven design process, and lessons from translating economic forecasts into actionable tools for practitioners. We will highlight our county‑level forecasts for GDP, employment, and housing affordability.

Regional economic structures are undergoing dramatic change. In the last several decades, projections of economic growth in the Sunbelt led to forward-thinking investments in transportation and infrastructure; economic forecasting and analysis enabled many states and cities transform from manufacturing-based to service-based economies.

In an era of accelerating change and uncertainty, regions that invest in rigorous forecasting and policy analysis will be best positioned to anticipate challenges, evaluate trade-offs, and actively shape their economic future.

In 1976, the US Congress created the federal historic tax credit in an effort to preserve historic structures in the face of increasing population and economic development pressures.

Minnesota enacted a state historic rehabilitation tax credit in 2010. In the bill’s language, the legislature directed the State Historic Preservation Office (SHPO) to annually measure the economic impact of the tax credit. By 2025, nearly 200 historic rehabilitation projects had been completed in the state using the credit.

University of Minnesota Extension has partnered each year with SHPO to produce an economic impact study.

My paper will argue that a transfer tax is an effective revenue stream in seasonal communities, and can be implemented without intense distortion of the existing housing market. This will give municipal officials and planners in seasonal communities’ evidence to begin implementing similar taxes in their communities. The study will also be useful for communities that are less dependent on seasonal activity but still experience intense housing pressure. By unlocking new revenue streams, these communities will be able to support sustainable housing for year-round residents and workers.

The growth of the short-term rental (STR) market has generated concerns about increased housing prices and negative externalities in residential neighborhoods. I study Denver’s 2017 STR regulations, which introduced a primary residence requirement aimed at preventing landlords from developing STR investment portfolios. I use a Poisson differences-in-differences model to quantify the effect of Denver’s policy on Airbnb supply. Relative to a set of control cities, regulations decreased active listings by 24.3%, or 12 per zip code. Pre-existing listings were significantly more likely to exit the market, especially properties hosted by commercial hosts. Active enforcement of the policy through citations did not have an additional effect on supply. I suggest that relatively low fines did not deter non-compliance when hosts expect high revenue. Finally, the regulations caused, on average, a $30 reduction in long-term monthly rental prices, concentrated in Downtown Denver.

Paper by Manuel Reyes, University of Texas at Tyler; Cecilia Cuellar, University of Texas at Tyler

Childcare is commonly viewed as a household constraint influencing labor supply, yet its broader role in shaping local economic outcomes remains underexplored. Focusing on counties across Texas, the analysis examines whether childcare deserts—defined as areas where licensed childcare capacity falls short of the population of young children—generate uneven growth patterns across industries.

Overall, the study highlights childcare availability as a critical determinant of regional economic structure, with implications for workforce participation, sectoral composition, and long-term growth across Texas regions.

This study, conducted by the Center for Business and Economic Research at The University of Alabama, examines recent trends in incidence and prevention funding. Using data from NCANDS and state administrative sources, the analysis focuses on the 2023 cohort of first-time victims. Findings indicate that child maltreatment imposed over $8.0 billion in tangible economic costs in 2023, representing approximately 3.2% of Alabama’s GDP.

The findings highlight that strengthening investments in child maltreatment prevention is both a social priority and a strategic economic imperative, with strong potential to enhance long-term workforce productivity and reduce public expenditures.

This research project focuses on the availability of childcare in an eight-county rural and urban area in coastal Georgia. The Hyundai Motor Group Meta plant America is directly adding 8,500 jobs to this region, increasing the demand for labor in this area. Community leaders identified Childcare as a factor keeping people out of the labor market. This study establishes, for both rural and urban counties, the current and future supply of and demand for childcare in the region. It also identifies where gaps in care exist and strategies to address the challenge.

The Northwest Florida Forward Dashboard transforms economic data from across Northwest Florida’s 13 counties into actionable intelligence for business and policy leaders. This interactive resource consolidates key indicators on business growth, workforce and talent, and regional economic trends into a centralized platform. By making critical data easier to explore and understand, the dashboard equips economic development leaders with the insights needed to support informed decision-making and drive strategic regional growth.

Dashboard by Ripley Cleghorn, John Hall, Drew Rosebush, and Lindsey Elliot; Center on Rural Innovation

This presentation will walk through the cohesive ecosystem of datasets, packages, analysis and charts that form the foundation of our research. The Rural Dataverse will combine our expertise in data science, infrastructure and visualization. It will centralize many of the R packages we currently use and allow for different types of resources (data, reports, charts) to live in a single location. This ecosystem represents actual projects carried out by our research and data teams. We plan to walk through one of these projects as an example for how the Rural Dataverse can be used by individuals in their own specific areas of research.

This study examines how generative artificial intelligence (AI) is reshaping entry-level labor market opportunities for young workers in East Texas, with a focus on Smith County. Using American Community Survey (ACS PUMS) data matched with the AI Occupational Exposure Index (AIOE), the analysis measures the extent to which jobs held by workers aged 20–24 overlap with AI capabilities. Results indicate that nearly half of young workers are employed in moderately to highly AI-exposed occupations, while a significant share of entry-level job demand is concentrated in these same roles. Drawing on the distinction between automation and augmentation, the findings suggest that AI is compressing traditional entry-level pathways by reducing routine roles and transforming others.

The United States is undergoing a major demographic transition known as the “Gray Tsunami,” as the Baby Boomer generation steadily exits the workforce. This shift is reshaping labor markets by tightening labor supply and increasing old-age dependency ratios, particularly in regions with older populations such as East Texas. This study examines how aging demographics place structural pressure on regional economies through reduced workforce participation and a growing share of retirees. The analysis also explores how strategies such as flexible work arrangements and knowledge transfer can mitigate labor shortages and sustain economic growth. Understanding these dynamics is essential for helping policymakers and communities transform demographic change into economic opportunity rather than constraint.

Jeffrey P. Thompson is a vice president and economist in the Federal Reserve Bank of Boston Research Department, where he is the director of the New England Public Policy Center. Prior to joining the Boston Fed, Thompson was a principal economist at the Federal Reserve Board and a professor at the University of Massachusetts Amherst’s Political Economy Research Institute. He specializes in public and labor economics, household finance, applied microeconomics, income, wealth and consumption inequality, state and local taxes, and regional economics. Thompson earned his PhD in economics from Syracuse University. He joined the Boston Fed in 2018.

Paper by Daniel Centuriao, West Virginia University; Heather Stephens, West Virginia University

Broadband access is a critical input for economic and social participation, yet substantial disparities in availability persist across the United States. This paper uses the Broadband Serviceable Location Fabric (BSLF), a high-resolution georeferenced dataset, to examine the spatial distribution of broadband availability at the ZIP code level.

The results underscore the need for targeted policy interventions that address both the high fixed costs of rural expansion and the persistent gaps across communities with similar geographic access.

Paper by Xaioyin Li, West Virginia University; David Nason, West Virginia University and Florida Gulf Coast University; Heather Stephens, West Virginia University

How does the structure of a local labor market shape its resilience to technological shocks? This paper examines whether occupational connectivity, measured by skill-based relatedness across occupations, may help moderate the effects of AI exposure on labor force participation, employment, and population dynamics.

Our study contributes to the literature on local labor market impacts of technological change and provides policy insights by highlighting occupational connectivity as a previously underexplored, but potentially important, determinant of regional economic resilience.

The geography of AI adoption remains largely unobserved. Existing platform-based measures are reported at the state level, obscuring the local variation that is central to regional economic analysis and policy design.

Approximately 60% of counties exhibit lower-than-expected AI usage. The largest gaps are concentrated in the rural Midwest and in economically distressed areas of Appalachia and the Deep South, while only 13.2% of counties exceed the national average.

These findings suggest that AI adoption is not converging across space. Instead, it follows existing regional fault lines, with implications for how the benefits of technological change are distributed.

Using data on online job postings and county-level occupational employment patterns, this paper measures the exposure of U.S. commuting zones to national shifts in skill demand across five skill categories and uses a shift-share design to estimate how commuting zone exposure to skill-demand growth following the Great Recession affected local labor market outcomes.

This paper contributes to a growing literature on skill-biased demand shifts by shifting the unit of analysis from workers and occupations to place, highlighting how exposure to broader skill-demand growth can shape local labor market outcomes even for workers not employed in the occupations most directly affected.

Learn what’s new in the Bureau of Economic Analysis’ Regional program, including: (1) regional statistics under development and research initiatives currently underway and (2) presentational and publication changes to regional economic statistics.

The Federal Reserve Bank of Atlanta’s Opportunity Occupation Monitor provides an overview of jobs within a region that pay more than the national average and don’t require a college degree. A 2026 refresh of the tool provides updated information of good-paying jobs available to individuals without a four-year degree within individual metropolitan areas. The update will also highlight post-COVID national job posting trends. Finally, the updated Opportunity Occupation Monitor will link to the Federal Reserve’s Occupation Mobility Explorer and identify related occupations that provide opportunities for additional advancement.

Project by Diego Mendez-Carbajo, Federal Reserve Bank of St. Louis and Maria A. Arias, Federal Reserve Bank of St. Louis

FRED (Federal Reserve Economic Data) is a free economic database that contains over 845,000 US and international time series from over 110 sources.

The purpose of this presentation is to demonstrate new data and features added to FRED and its related ecosystem over the last 12 months. Members of the FRED team will guide session participants through data search and customization exercises combining the web portals of FRED, Archival FRED (ALFRED), the FRED Blog, and FRED accounts.

Session participants interested in certifying their existing FRED data skills, or developing new ones, can enroll in our free asynchronous micro-credential program: https://www.stlouisfed.org/education/digital-badges/fred-data-practitioner

Paper by Monica Haynes, University of Minnesota Duluth; Chris McIntosh, University of Minnesota Duluth; Neil Wilmot, University of Minnesota Duluth; Alison Hoxie, University of Minnesota Duluth; Ava Klennert, University of Minnesota.

How does a research team maintain momentum when the primary economic incentives being studied are suddenly thrown into question? This presentation examines a 2024–2026 research study conducted by the University of Minnesota Duluth’s Bureau of Business and Economic Research (BBER) in collaboration with several local community partners, including the City of Duluth’s sustainability office.

This session will provide a unique case study on what community-engaged economic research looks like during policy uncertainty.

Over the past two decades, there has been a steady decrease in the amount of private lands that allow public hunting access despite increases in state incentive payments. Potential causes for decreased participation include increased competition from lucrative private hunting leases, new landowners with different public values, and concerns about hunter behavior and legal liability.

BBER is cooperating with the MT Department of Fish and Wildlife on a survey of private landowners to determine their responsiveness to changes in incentive payments or other contract terms that could generate increased participation in public hunting access programs.

Paper by Morgan Holland, University of Wyoming and Reepa Das, University of Wyoming

Public lands make up more than 50% of Wyoming’s land surface, with additional public ownership of mineral resources. This project attempts to calculate the economic contribution of Wyoming’s public lands to the state’s economy as part of a broader conversation about the role of public lands, their value, and their future. For the first time, economic contributions from all federal and state agencies will be calculated using a unified methodology so that comparisons can be made between the contributions from different agencies and land uses. Such varied missions lead to distinct approaches to land use that all must be taken into consideration when assessing their economic contribution.

Paper by Matthew Fredriksson, West Virginia University and John Deskins, West Virginia University

Economic development incentives (EDI) are one of the most widely used policy tools by state and local governments to promote job creation and income growth within local economies. Using the Panel Database on Incentives and Taxes (PDIT), this study explores whether stronger human capital in an area affects the degree to which EDIs enhance various economic outcomes.

Final release of CBER’s White Paper on Entrepreneurship and Small Business creation

Paper by Amir Borges Ferreria Neto, Florida Gulf Coast University; Jamie Pavlik, Juan Sayago, Joao P. Bastos

The effect of place-based policies like enterprise zones has long been debated. Recent literature finds that even if the short-run effects of such policies are positive, the long-run effects tend to dissipate to zero. We argue that the lack of long-run effects is the failure to attract locally owned small businesses. We study the effects of enterprise zone designation on local business sorting in Florida. Utilizing a regression discontinuity design and establishment level NETS data, we find that enterprise zone designation reduces the likelihood of single-establishment local ownership, but it attracts firm headquarters.

This paper investigates the effect of New York City’s (NYC’s) congestion pricing program on emergency medical service (EMS) response times. The program imposes a 24-hour toll on vehicles entering southern Manhattan’s congestion relief zone (CRZ) and is intended to reduce traffic congestion while generating revenue. Reduced traffic within the CRZ may enable EMS responders to reach medical incidents more quickly. These results suggest that overall improvements in response times are driven largely by nighttime conditions, which occur when fewer drivers travel into or through the CRZ for daily activities and necessities.

This study investigates the impacts of natural disasters like wildfires on community recovery across the United States, focusing on how long it takes affected populations to return and rebuild. Linking geospatial fire data with socioeconomic indicators, this study provides new insights into the persistence of wildfire shocks and disparities in resilience across communities. The results will support more targeted disaster response and climate adaptation strategies, while also offering a replicable framework for monitoring recovery in the aftermath of climate-related disasters.

Paper by Michelle Jiang, UMass; Sumaya Bouadi, Yale

This paper provides a new approach to the classic social planner model. The current, dominant social planner model focuses exclusively on utility maximization, sometimes to absurdist results: sufficiently many cheap yachts could compensate for the absence of basic water access. We propose a modified social planner model, where utility is maximized subject to a floor function: that is, no one can starve, lack water, or lack housing. Firstly, it is a simple mathematical structure that can be easily applied. Secondly, it provides an intuitive framework for policy.  We illustrate the benefits of this model with an example of rent-control.

Details forthcoming.

At the Kem C. Gardner Policy Institute, Utah’s premier economic research institution, we pair rigorous analysis with robust communications policies and procedures to ensure research informs real-world decisions. The presentation will show participants how to harness a multitude of communication strategies to speak effectively and clearly with stakeholders.

Drawing on lessons learned at the Gardner Institute, the presentation will demonstrate a pragmatic framework for translating technical findings into compelling narratives, visualizations, and actionable recommendations. This will be an interactive, practice-focused workshop where participants will draft messages, receive feedback, and leave confident in applying communication systems to real policy challenges across sectors and regions.

Marcos Marrero is the Deputy Director and Senior Executive Vice President at MassDevelopment, which is the Commonwealth of Massachusetts’ development finance agency and land bank. Marrero was previously the Executive Vice President for Community Development. He has a background in policy and public projects in areas related to economic development, urban affairs and sustainability.

Before joining MassDevelopment, Marcos was the Director of Planning & Economic Development for the City of Holyoke, where he oversaw the implementation of the largest urban renewal plan in Massachusetts, Co-Chaired the Holyoke Innovation District and served as Executive Director to two public development corporations. Marcos has served in the Puerto Rico Governor’s Office as Deputy Adviser on Federal Affairs, Energy & Climate Change, and has served at the New York City Economic Development Corporation, the Pioneer Valley Planning Commission and the Puerto Rico Industrial Development Corporation. Marcos holds a dual Masters in Public Affairs and Urban & Regional Planning from the Woodrow Wilson School at Princeton University, and a BA in Economics and Political Science from the University of Puerto Rico. He lives in Center City.

• Michael J. Hicks, Shenandoah University & Director (retired), Center for Business and Economic Research, Ball State University
• Heather Stephens, Director, Regional Research Institute, West Virginia University
• Amanda Weinstein, Director of Research, Knowledge, and Evaluation, Center on Rural Innovation

This paper examines the speed of equilibrium adjustment using quality of life estimates from 1970-2019 developed in Hicks, Stephens and Weinstein (2026).  In this model, we have adapted the Rosen-Roback model of quality of life and seek to understand the pace and component of spatial adjustment using estimates of r* and w* in a classic speed of adjustment model (see Deller, et. al, 2011).  From these findings, we can determine the relative size and speed of changes to wages or rents in response to changes in household preferences and amenities. This question adds to the literature in helping parameterize adjustment processes, and provides policymakers a framework on the likely speed of household responses to policy interventions.

• Douglas White, Director, Center for Business and Economic Research, Louisiana State University Shreveport
• Tory McCoy, Graduate Student, Louisiana State University Shreveport

Using Census and American Community Survey data, we tracked demographic and economic change across 44 neighborhoods in Shreveport, LA. The long-term goal is to add this data to our neighborhood dashboard, so local nonprofits and governments have data to discuss how the city is changing.

• Maddy Oritt, Director of Public Finance Research, Kem C. Gardner Policy Institute, University of Utah
• Phil Dean, Chief Economist and Research Director, Kem C. Gardner Policy Institute, University of Utah

As the youngest state in the United States, Utah provides a unique lens into the fiscal implications of an aging U.S. population. Utah provides a case study to assess likely fiscal shifts from an aging population, highlighting that impacts may vary dramatically both between U.S. states and within states based on unique demographic situations. The paper highlights recent long-term demographic projections for Utah’s population and explores related public finance implications for state and local revenues and spending.

Across the United States, states and regions are increasingly recognizing the music industry as a driver of economic development, workforce retention, and place-based identity. Yet many rural and mid-sized states lack comprehensive data to inform policy and investment decisions. This presentation shares preliminary findings from the Idaho Music Census and an accompanying economic impact analysis designed to better understand the scope, structure, and potential of Idaho’s music ecosystem.

This work is conducted in partnership with industry and community stakeholders, aligning with community-engaged translational research approaches that prioritize co-produced knowledge and actionable outcomes. The presentation will conclude with implications for economic development policy, workforce development, and future research, including opportunities to scale this model across the Mountain West and other emerging music economies.

Social capital is widely recognized as a driver of rural economic resilience, but the physical infrastructure that generates it remains poorly understood and nearly impossible to measure at scale. This presentation introduces a new, publicly accessible dataset and interactive mapping tool that identifies and tracks “third places”—cafés, libraries, farmers’ markets, and other gathering spots outside of home and work—across the rural United States. Drawing on longitudinal business establishment data from the YourEconomy Time Series (YTS) database, the project applies a replicable, NAICS-based identification strategy to map the prevalence, diversity, and evolution of third places over time and across space. Designed for use beyond academia, the dataset and maps support planners, nonprofits, and economic development organizations in identifying, monitoring, and sustaining community third places, especially in rural areas.

Paper by Ann Ormsbee, Cambridge Economics; Dan Hodge, Cambridge Econometrics

Focusing on three shared-use path projects in New England, this presentation explores how trail investments can translate into local economic benefits. Cambridge Econometrics (CE) analyzes the potential visitation and spending associated with three trails, all of which are currently incomplete or in planning phases.

CE uses input-output modeling, including its proprietary REACT model, to estimate total economic impacts under completed-build scenarios. In some cases, the analysis is complemented by interviews with local businesses, offering on-the-ground perspectives on how improved trail connectivity can drive tourism, boost consumer spending, and expand access to commercial districts.

This study examines whether the 2018 escalation of the U.S.–China trade war reshaped global supply chains by redirecting foreign investment and manufacturing activity toward Vietnam. Using the Synthetic Control Method, we construct a counterfactual Vietnam from a weighted combination of comparable emerging economies to estimate the causal impact of the trade shock. The analysis relies on annual data from the World Bank’s World Development Indicators over the period 2005–2024, focusing on two key outcomes: foreign direct investment (FDI) net inflows and industrial value added.

Overall, the findings provide robust evidence that the U.S.–China trade conflict triggered supply chain reconfiguration, leading to significant capital reallocation and industrial expansion in Vietnam.

Paper by Kramer Winingham, NM State; Chris Erickson, NM State; Lucinda Vargas, NM State

The Santa Teresa Industrial Area in southern New Mexico has emerged as one of the fastest-growing industrial hubs along the U.S.-Mexico border. Employment in the Santa Teresa Industrial Park has expanded at a compound annual growth rate of 18.5% since 2019. However, the tariffs imposed in 2025 introduced substantial uncertainty into international trade, delaying or canceling planned investments in trade-related businesses and creating significant operational challenges for firms reliant on cross-border supply chains with Mexico and Asia. These impacts proved highly dynamic and uneven across sectors. This study attempts to quantify the economic consequences of the tariffs on a region deeply integrated into international trade networks.

The Center for Business Analytics and Economic Research (CBAER) at Georgia Southern University estimated the potential economic impact of the proposed and newly implemented tariffs as of late July 2025. The analysis covers Coastal Georgia, which contains the 10 counties studied. The impact analysis covers a two-year implementation cycle and is based on potential changes in disposable household income due to increasing household costs once the announced tariffs would have been fully implemented. The overall impact of these tariffs on the Coastal Region appears to be modest, as the total regional employment impact of the tariff policy is estimated to be equivalent to only 0.26 percent of total regional employment.

Paper by Amanda Weinstein, Center for Rural Innovation; Adam Dewbury, Olivia Galloway, Lindsey Elliot, Drew Rosebush

Rural communities are increasingly turning to entrepreneurship to build local wealth and economic resilience, yet little is known about which underlying community assets actually predict where robust entrepreneurship ecosystems take hold. This paper extends the Rural Entrepreneurship Index, a composite measure of county-level business dynamism, innovation and growth, and entrepreneurial capacity built using robust principal component analysis across eleven indicators. Results identify the capitals that most consistently predict higher rural entrepreneurship index scores across rural counties, offering an evidence-based answer to a question practitioners ask: where should a community invest to grow its entrepreneurial ecosystem? By connecting a validated outcome measure to a widely used framework for community assets, this research gives researchers and practitioners a practical, data-driven tool for benchmarking local conditions, prioritizing investment, and communicating the case for place-based strategy to local leaders and funders.

• Deniz Gevrek, Director, South Texas Economic Development Center, Texas A&M Corpus Christi
• David Hudgins, Professor, Department of Decision Sciences and Economics, Texas A&M Corpus Christi

University-based economic research centers are increasingly called upon to evaluate public investments that generate both immediate economic activity and long-term community benefits. Traditional economic impact studies primarily quantify short-term measures such as economic output, employment, labor income, gross domestic product (GDP), and tax revenues. However, public education investments also generate long-term workforce development and human capital benefits that are often excluded from conventional economic impact analyses. Using the Flour Bluff Independent School District’s 2025 Bond Program as a case study, this paper demonstrates an integrated approach that combines regional input-output modeling with human capital valuation to provide a more comprehensive assessment of public education investments. This study illustrates how university-based applied research can help school districts, policymakers, and economic development organizations make more informed decisions by considering both the immediate and enduring economic benefits of educational investments.

Presentation by Valorie Rice, Business Information Specialist; and Jennifer Pullen, Director, Economic and Business Research Center, University of Arizona.

The MAP Dashboard has been measuring Southern Arizona’s progress and providing context for more than a decade, becoming a trusted source of socio-economic data in the region. This presentation explores how the MAP Dashboard has continued to evolve and remain relevant over time.

Presentation by Komla Koumi, Assistant Research Professional; and Percy Taabazuing; Economic Researcher, Center for Business and Economic Research, University of Alabama.

In an era of uncertainty, accessible and transparent data tools are essential for evidence-based decision-making and building public trust. Alabama Economy Online, developed by the Center for Business and Economic Research (CBER) at the University of Alabama, is a comprehensive online platform that integrates county profiles and economic impact dashboards to support local governments, businesses, and community stakeholders. This integrated platform demonstrates how combining economic modeling with interactive dashboards enhances data accessibility, improves communication of economic evidence, and supports informed decision-making, particularly in underserved and rural communities. The presentation will highlight methodology, practical applications, and lessons learned, offering a scalable model for other regions seeking to leverage data for local economic development.

Eric Paley is the Secretary of Economic Development for the Commonwealth of Massachusetts. He joined the Healey-Driscoll Administration in September 2025. For more than 25 years prior to entering state government, Paley worked to shape the innovation economy as both a successful entrepreneur and a leading venture capitalist. As co-founder and managing partner of Founder Collective, Paley helped build one of the world’s highest-performing seed-stage venture capital funds. His investment portfolio includes groundbreaking technology companies across diverse sectors such as transportation, media, healthcare, consumer, advanced manufacturing and enterprise software, including Uber (NYSE), The Trade Desk (NSDQ), Omada Health, Whoop, Formlabs and Airtable. He served on the Board of Directors of The Trade Desk from its founding until 2023, including as a public director after the company’s IPO in 2016. At Founder Collective, Paley also launched Collective Future, an annual Boston conference bringing together Massachusetts’ most influential innovators across technology, government, media, cultural and non-profit sectors to collaboratively shape the future of the innovation economy.

Before Founder Collective, Paley founded and served as CEO of Brontes Technologies, a hard-tech startup that commercialized novel 3D imaging technology to enable advanced manufacturing in dentistry and that spun out of MIT. Paley continued to lead the company after its acquisition by 3M in 2006.

Paley holds an MBA from Harvard Business School and a bachelor’s degree from Dartmouth College. He lives in Cambridge with his wife and two children. He previously served on the Board of Directors of the YMCA of Greater Boston and has been engaged in philanthropic efforts primarily to alleviate food insecurity in Massachusetts.

Paper by Olivia Galloway, Center for Rural Innovation; Amanda Weinstein, Center for Rural Innovation; Adam Dewbury, Center for Rural Innovation; Lindsey Elliott, Center for Rural Innovation

Previous automation waves hit rural areas hardest, but AI exposure concentrates in metropolitan, white-collar labor markets—a pattern whose robustness depends on how exposure is measured. We compare three leading AI exposure measures and ask what they collectively reveal about rural labor markets: a pre-LLM structural index (Felten et al., 2021), an LLM-specific measure (Eloundou et al., 2024), and an observed measure incorporating actual AI usage data (Massenkoff and McCrory, 2026). We map national occupation-level scores onto county-level Lightcast employment data across more than 700 occupations. All three measures show a consistent rural AI exposure gap, with rural workers scoring roughly 20–25% of a standard deviation lower than nonrural workers.

These findings suggest the rural AI gap reflects structural features of rural economies rather than worker capacity or methodological artifact. Closing this gap requires expanding rural access to AI tools and training, broadening the occupational base available to rural workers, and ensuring rural communities shape how AI is applied to the challenges they know best.

In this presentation, Greg Blair will discuss the work Julius is doing to provide useful data in an era where technology means traditional data sources lag behind significantly in terms of useability. Topics include AI/ML jobs and how Julius is working to connect education & industry but also use traditional data sources.

As online surveys become more common, potential threats to data integrity have evolved. Online surveys are popular due to cost effectiveness and ease of participation, and often include incentives to increase participation rates. However, we propose that the availability of artificial intelligence accelerates bad actors’ ability to provide difficult to detect fraudulent responses. The following article describes our team’s experiences with a targeted survey to Washington’s licensed child care providers, which was flooded with fraudulent responses after being advertised on social media. Significant work was done to ensure the validity of our survey data, which shapes the recommendations in this presentation. This presentation synthesizes existing recommendations and best practices, as well as warning signs we believe are indicative of open-text responses generated using artificial intelligence.

Paper by Dan Hodge, Cambridge Econometrics; Ann Ormsbee, Cambridge Econometrics

Conducted for three regional planning agencies in Massachusetts, this presentation will focus on the economic impacts of proposed passenger rail service along the Northern Tier. This rail service would extend from Boston beyond Fitchburg (the current end of the commuter rail line) west to cities and towns such as Gardner, Athol, Greenfield and North Adams. The four-tiered economic study approach is centered on:

• Economic and demographic scenario analysis using a Population and Housing Model (PHM). This analysis considers how the rail service could curb declining population trends and change the demographic makeup of corridor communities.

• Transit-Oriented Development (TOD) market analysis for four communities along the corridor, considering the growth capacity and potential development opportunities in the cities and towns likely to have stations.

• Comparison rail corridor assessment profiling four existing passenger rail corridors with similar characteristics to assess economic impact precedents and ridership markets to draw lessons relevant to the Northern Tier Passenger Rail Service.

• Economic impact study of tourism spending, using an input-output model, this evaluation considers the economic impact of expanded tourism and visitation opportunities spurred by the passenger rail service.

This approach provides more in-depth estimates of the economic development benefits associated with the Northern Tier Passenger Rail Service beyond the 2024 MassDOT alternatives analysis, offering a broader perspective that considers a wide range of potential economic impact pathways and rail markets.

The presentation explains how tourism-driven economic research can help stakeholders understand and communicate the value of visitor spending. It highlights that nonresident visitor spending represents net new revenue for the state, injecting billions into the economy each year. In FY 2024, visitor expenditures in Utah totaled $10.6 billion, which translated into significant tax revenue across categories such as transportation, dining, retail, entertainment, and air travel.

Using IMPLAN economic modeling, the analysis shows that visitor activity generated $1.2 billion in tax revenue, split between $596 million in state taxes and $640 million in local taxes. The presentation details where these dollars ultimately flow. At the state level, 73% supports the General Fund, while earmarked portions go to transportation, water, Medicaid, and other designated uses. Local tax revenue primarily supports county and city general funds, with a substantial share—59%—benefiting local education. // The presentation also emphasizes the broader economic ripple effects of tourism, noting that indirect and induced impacts further expand total tax contributions. Finally, it illustrates how visitor-generated revenue supports major state program areas, including natural resources, public safety, transportation, and health and human services.

• Jenny H. Liu, Assistant Director, Northwest Economic Research Center (NERC), Portland State University
• Hyeoncheol Kim, PhD Student, Toulan School of Urban Studies and Planning, Portland State University

Transportation agencies increasingly require effective tools to evaluate projects and policies while communicating complex economic nuances to legislators and decision-makers. Building on the foundational synthesis of literature and best practices presented last year at AUBER, this presentation introduces the completed Oregon Multimodal Transportation Benefit-Cost Analysis (BCA) Framework and its accompanying decision-support calculator tool. The framework operationalizes BCA parameters, measurement methods, sensitivity analyses and distributional analysis utilizing Oregon-specific data sources. Central to this effort is an interactive, policymaker-facing calculator that feeds simple inputs such as changes in vehicle miles traveled (VMT) or bicycle miles into the Oregon BCA framework, and then translates estimated BCA outcomes into intuitive, standardized metrics including benefit per mile (in dollars), net present value (NPV) or benefit-cost ratio (BCR). The tool allows decision-makers to model diverse transportation modes, conduct sensitivity analysis across numerous dimensions, and evaluate equity-weighted BCA outcomes. We will demonstrate the tool’s architecture, and discuss the assumptions, design considerations and its practical applications.