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Working PaperThe 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.View Full Paper PDF
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Working PaperOptimal Stratified Sampling for Probability-Based Online Panels
September 2025
Working Paper Number:
CES-25-69
Online probability-based panels have emerged as a cost-efficient means of conducting surveys in the 21st century. While there have been various recent advancements in sampling techniques for online panels, several critical aspects of sampling theory for online panels are lacking. Much of current sampling theory from the middle of the 20th century, when response rates were high, and online panels did not exist. This paper presents a mathematical model of stratified sampling for online panels that takes into account historical response rates and survey costs. Through some simplifying assumptions, the model shows that the optimal sample allocation for online panels can largely resemble the solution for a cross-sectional survey. To apply the model, I use the Census Household Panel to show how this method could improve the average precision of key estimates. Holding fielding costs constant, the new sample rates improve the average precision of estimates between 1.47 and 17.25 percent, depending on the importance weight given to an overall population mean compared to mean estimates for racial and ethnic subgroups.View Full Paper PDF
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Working PaperDouble-Pane Glass Ceiling: Commercial Engagement and the Female-Male Earnings Gap for Faculty
September 2025
Working Paper Number:
CES-25-68
I use administrative data from universities (UMETRICS) linked to the universe of confidential W-2 and 1040-C tax records to measure faculty commercial engagement and its role in female-male earnings gaps. Female faculty are 20 percentage points less likely to engage commercially, with the entire gap driven by self-employment. The raw earnings gap is $63,000 on a base of $162,000 and non-university earnings account for $18,000 (29 percent) of this total. Thus, while university pay explains most of the gap, commercial engagement substantially amplifies it. Earnings gaps appear in all components of non-university pay ' self-employment, and work for incumbent, young/startup, high-tech, and non-high-tech firms ' and remain large, though attenuated, after controlling publications, patents, field, university, scientific resources, age, marital status, childbearing, and demographics. Gaps widen as faculty move up the earnings distribution, and commercial engagement becomes a larger contributor. Men and women engage with similar industries, but men earn more in all shared industries.View Full Paper PDF
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Working PaperManufacturing Dispersion: How Data Cleaning Choices Affect Measured Misallocation and Productivity Growth in the Annual Survey of Manufactures
September 2025
Working Paper Number:
CES-25-67
Measurement of dispersion of productivity levels and productivity growth rates across businesses is a key input for answering a variety of important economic questions, such as understanding the allocation of economic inputs across businesses and over time. While item nonresponse is a readily quantifiable issue, we show there is also misreporting by respondents in the Annual Survey of Manufactures (ASM). Aware of these measurement issues, the Census Bureau edits and imputes survey responses before tabulation and dissemination. However, edit and imputation methods that are suitable for publishing aggregate totals may not be suitable for estimating other measures from the microdata. We show that the methods used dramatically affect estimates of productivity dispersion, allocative efficiency, and aggregate productivity growth. Using a Bayesian approach for editing and imputation, we model the joint distributions of all variables needed to estimate these measures, and we quantify the degree of uncertainty in the estimates due to imputations for faulty or missing data.View Full Paper PDF
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Working Paper'Class of Customer' Question from the US Economic Census
September 2025
Working Paper Number:
CES-25-66
The Economic Census (EC) collects detailed information on the class of customers served by establishments'for example, the share of an establishment's sales to other businesses or to government entities'for a subset of sectors in the economy. In this paper, we evaluate the data from the 'Class of Customer' question from the EC, with a particular focus on sales to the government. These data have seldom been used in empirical research and are unique in that they enable researchers to link establishment-level Census data with information on government procurement. We compile and analyze large volumes of publicly available tabulated data about the class of customer question over time. Using these data, we document three main findings. First, total sales to government from establishments covered by the class of customer question account for approximately 4 percent of GDP'just under half of total government procurement as measured in the national accounts. Second, the sectoral distribution of government expenditure is significantly different from that of private sector spending. Certain industries, such as Construction and Professional, Scientific, and Technical Services, account for a much larger share of government expenditure relative to private sector expenditure. Third, sales to the government make up a substantial portion of total sales in several sectors'for instance, 70 percent in Facilities Support Services, 30 percent in Waste Treatment and Disposal, and 17 percent in Construction. Finally, we use the microdata to examine nonresponse rates to the class of customer question across establishments based on the number of employees.View Full Paper PDF
