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Extending Place-Based Innovation Policy to Rural Areas: Using Oaxaca-Blinder Decomposition to Identify Endowment Deficiencies
July 2026
Working Paper Number:
CES-26-48
Place-based policy is premised on the idea that productive investments that address endowment deficiencies may release latent comparative advantages, stimulating growth while reducing regional disparities. Extending place-based policy to the domain of innovation is conceptually challenging given conventional wisdom that settlement size is the principal determinant of agglomeration economies that fuels innovation. However, growing concern that more places are being left behind by the innovation economy has prompted greater interest in ways to expand the geography of innovation. Using confidential firm-level data from the 2018 Annual Business Survey, this study examines differences in self-reported innovation activity between firms in rural and urban counties to identify possible endowment deficiencies. We do this by employing the Oaxaca-Blinder decomposition method to quantify the urban-rural innovation gap to better understand the relative contributions of firm characteristics, owner characteristics, and county-level factors.
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Screening Out the Needy: the Effects of SNAP Work Requirements
July 2026
Working Paper Number:
CES-26-46
We examine the effectiveness of work requirements as a screening device in the Supplemental Nutrition Assistance Program (SNAP). Work requirements for 'able-bodied adults without dependents' were suspended after the Great Recession and gradually reinstated across counties and states in the 2010s. Using linked administrative SNAP and employment data from five states and a triple-differences design, we find that work requirements reduce SNAP participation by seven percent without increasing labor supply and disproportionately screen out low-income individuals. We develop a welfare framework to interpret these results and find that the social costs of work requirements exceed budget savings.
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Access to the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) at the State and Substate Levels: Meaning and Measurement
July 2026
Working Paper Number:
CES-26-44
This study estimates eligibility and access rates for the U.S. Department of Agriculture's (USDA) Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) administrative data linked with American Community Survey (ACS) data. This study is one result of a long-term research collaboration among USDA's Economic Research Service; the U.S. Department of Commerce, Bureau of the Census; USDA's Food and Nutrition Service (FNS); and participating state WIC agencies.'By analyzing WIC participation at the state and substate levels, the report provides insights into program reach and demographic differences. The findings confirm that the Census Bureau estimates meet high statistical reliability standards, providing valuable data for program officials and managers, and other stakeholders, to enhance program outreach and effectiveness. A key focus of the report is the comparison between Census Bureau and USDA, FNS estimates, which differ in methodology and measurement scope.
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Integrating Administrative and Survey Data to Estimate WIC Eligibility and Access
July 2026
Working Paper Number:
CES-26-43
The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) provides benefits to low-income, nutritionally at-risk women, infants, and children. To administer WIC, officials and program managers at the federal and state level want to understand who is eligible for the program, who among the eligible population chooses to participate, and who is not accessing the program despite their eligibility. Novel individual-level data linkages between restricted-use WIC Administrative Records and the American Community Survey provide WIC access rates estimated at the state and county levels, as well as estimates disaggregated by the demographic and socioeconomic characteristics of individuals and their households. These estimates are developed by the Census-FNS-ERS Joint Project, a research partnership among the U.S. Census Bureau, the US Department of Agriculture's Food and Nutrition Service and Economic Research Service, and state WIC agencies that provide the requisite WIC administrative data to the Census Bureau. This paper details and evaluates our current data linkage and estimation methods, reports results, and identifies areas for improvement and further research.
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Tip of the Iceberg: How Much Do Tips Bunch at Reporting Thresholds?
June 2026
Working Paper Number:
CES-26-40
We study the importance of bunching in the context of tip-income reporting by workers at full-service, single-unit restaurants in the United States. Using tax reports at both the individual and the employer levels, we show that reported tip income varies with minimum-wage laws that provide an incentive for tipped workers to report some, but not necessarily all, of their tips. As a result, reported tips bunch at the minimum required threshold. We quantify missing tips due to bunching at nearly $63 million per year in 2018 dollars, on average over the period 2005-2018. Bunching is stronger for jobs at small employers and in the earlier part of the time series and declined monotonically from 2010 to 2018. Using restaurant-level revenue data, we also estimate the total value of unreported tips assuming an average tip rate of 12%. We find that tips are missing throughout the distribution. All told, missing tips exceed $4 billion per year, implying that bunching explains only 1.5% of all missing tips.
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The Impact of Expanding Public Health Insurance on Safety Net Program Participation: Evidence From the ACA Medicaid Expansion
May 2026
Working Paper Number:
CES-26-32
We examine spillover effects from the ACA Medicaid expansion to public programs providing cash and food assistance. We consider program participation in contiguous county pairs crossing state borders, where one state took up the Medicaid expansion and the other did not, allowing us to better control for local economic trends that could affect program participation. We find that the Medicaid expansion increased participation in food assistance and one of the cash programs, with impacts mainly due to participation conditional on eligibility, rather than from labor supply responses. Our results demonstrate the potential for spillovers across safety net programs.
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Food Fight: U.S. Exporters' Adjustments to Russia's 2014 Agricultural Import Ban
December 2025
Working Paper Number:
CES-25-79
This paper examines the impact of Russia's 2014 food-import ban on U.S. firms that exported banned products to Russia. Using confidential customs transaction data, we implement triple-difference and dosage-response approaches to identify how firms adjust to the sudden loss of a market. Following the ban, treated firms experienced a 30 percentage-point decrease in the probability of exporting banned food to Russia relative to control firms. However, there is substantial heterogeneity by pre-ban reliance on the Russian market: heavily reliant firms were significantly less likely to survive once the ban was in place, and survivors experienced large reductions in revenue (19%) and total export value (49%) for each standard deviation increase in Russian market exposure. We find evidence of export redirection to neighboring countries, though it is insufficient to offset losses. Any negative impacts on survivors dissipate by five years post-ban.
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The Hidden Costs of Decline: Health Disparities in America's Diminishing Micropolitan Areas
September 2025
Working Paper Number:
CES-25-70
This study examines the relationship between long-term population change and health outcomes in U.S. micropolitan areas, with a focus on life expectancy and mortality disparities. Using a county typology based on the historical population trajectories of micropolitan cores from 1940 to 2020, this analysis reveals that health outcomes are substantially worse in places that experienced sustained decline. These disparities persist even after controlling for demographic and socioeconomic characteristics, suggesting that population loss itself is a key driver of poor public health. Declining micropolitan areas are older, less educated, and report high rates of behavioral risk factors, including smoking, excessive drinking, and physical inactivity. By linking historical demographic trends to tract-level data, this analysis highlights the distinct challenges facing the urban cores of shrinking micropolitan areas. Population decline emerges not only as a demographic trend, but as a marker of structural disadvantage with measurable consequences for community health.
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The Decline of Volunteering in the United States: Is it the Economy?
June 2025
Working Paper Number:
CES-25-41
This article investigates the complex interactions between local and national economic contexts and volunteering behavior. We examine three dimensions of local economic context'economic disadvantage (e.g., the percentage of families living in poverty), income inequality, and economic growth (e.g., the change in median household income) and the impact of a national/global economic jolt'the Great Recession. Analysis of data from the Current Population Survey's (CPS) Volunteering Supplement (2002-2015) reveals. Individuals who live in places characterized by economic disadvantage and economic inequality are less likely to volunteer than individuals in more advantaged, equitable communities. The recession had a dampening effect on volunteering overall, but it had the largest dampening effect on individual volunteering in communities with above average rates of income equality and higher rates of economic growth. While individuals living in rural communities were more likely to volunteer than their urban counterparts before the recession, rural/urban differences disappear after the recession.
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The Design of Sampling Strata for the National Household Food Acquisition and Purchase Survey
February 2025
Working Paper Number:
CES-25-13
The National Household Food Acquisition and Purchase Survey (FoodAPS), sponsored by the United States Department of Agriculture's (USDA) Economic Research Service (ERS) and Food and Nutrition Service (FNS), examines the food purchasing behavior of various subgroups of the U.S. population. These subgroups include participants in the Supplemental Nutrition Assistance Program (SNAP) and the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), as well as households who are eligible for but don't participate in these programs. Participants in these social protection programs constitute small proportions of the U.S. population; obtaining an adequate number of such participants in a survey would be challenging absent stratified sampling to target SNAP and WIC participating households. This document describes how the U.S. Census Bureau (which is planning to conduct future versions of the FoodAPS survey on behalf of USDA) created sampling strata to flag the FoodAPS targeted subpopulations using machine learning applications in linked survey and administrative data. We describe the data, modeling techniques, and how well the sampling flags target low-income households and households receiving WIC and SNAP benefits. We additionally situate these efforts in the nascent literature on the use of big data and machine learning for the improvement of survey efficiency.
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