-
'Oh, Give Me a Home (Trade Share)': Differential Import Price Inflation and Gains from Trade Across U.S. Households
July 2025
Working Paper Number:
CES-25-47
Consumers are differentially exposed to trade based on their expenditures, but there is little data on how such trade exposure differs across consumer groups and over time. In this paper, we construct 'home trade shares' that vary by age, race, marital status, education, and urban status, and use these to analyze differences in inflation and welfare gains from trade for U.S. demographic groups over the years 1996'2018. We show that over this time period, import prices (inclusive of the effects of taste change) held down overall inflation for all groups. For the typical group, more than a quarter of the gains from trade relative to autarky accrued in our time period. Welfare gains from trade over our time period are largest for rural households, and smallest for Black households. Adding taste change to the typical welfare gains from trade formula boosts the gains for every group relative to the standard formula.
View Full
Paper PDF
-
Credit Access in the United States
July 2025
Working Paper Number:
CES-25-45
We construct new population-level linked administrative data to study households' access to credit in the United States. These data reveal large differences in credit access by race, class, and hometown. By age 25, Black individuals, those who grew up in low-income families, and those who grew up in certain areas (including the Southeast and Appalachia) have significantly lower credit scores than other groups. Consistent with lower scores generating credit constraints, these individuals have smaller balances, more credit inquiries, higher credit card utilization rates, and greater use of alternative higher-cost forms of credit. Tests for alternative definitions of algorithmic bias in credit scores yield results in opposite directions. From a calibration perspective, group-level differences in credit scores understate differences in delinquency: conditional on a given credit score, Black individuals and those from low-income families fall delinquent at relatively higher rates. From a balance perspective, these groups receive lower credit scores even when comparing those with the same future repayment behavior. Addressing both of these biases and expanding credit access to groups with lower credit scores requires addressing group-level differences in delinquency rates. These delinquencies emerge soon after individuals access credit in their early twenties, often due to missed payments on credit cards, student loans, and other bills. Comprehensive measures of individuals' income profiles, income volatility, and observed wealth explain only a small portion of these repayment gaps. In contrast, we find that the large variation in repayment across hometowns mostly reflects the causal effect of childhood exposure to these places. Places that promote upward income mobility also promote repayment and expand credit access even conditional on income, suggesting that common place-level factors may drive behaviors in both credit and labor markets. We discuss suggestive evidence for several mechanisms that drive our results, including the role of social and cultural capital. We conclude that gaps in credit access by race, class, and hometown have roots in childhood environments.
View Full
Paper PDF
-
An Anatomy of U.S. Establishments' Trade Linkages in Global Value Chains
June 2025
Working Paper Number:
CES-25-44
Global value chains (GVC) are a pervasive feature of modern production, but they are hard to measure. Using confidential microdata from the U.S. Census Bureau, we develop novel measures of the linkages between U.S. manufacturing establishments' imports and exports. We find that for every dollar of exports, imported inputs represent 13 cents in 2002 and 20 cents by 2017. Examining GVC trade flows in a gravity framework, we find that these flows are higher within 'round-trip' (input and output market is the same) linkages, regional trade agreements, and multinational firm boundaries. The strong complementarities between input and output markets are muted by the proportionality assumptions embedded in global input-output tables. Finally, with an off-the-shelf model, we show the round-trip results can be obtained when firm-specific sourcing and exporting fixed costs are linked.
View Full
Paper PDF
-
Aggregation Bias in the Measurement of U.S. Global Value Chains
September 2024
Working Paper Number:
CES-24-49
This paper measures global value chain (GVC) activity, defined as imported content of exports, of U.S. manufacturing plants between 2002 and 2012. We assesses the extent of aggregation bias that arises from relying on industry-level exports, imports, and output to establish three results. First, GVC activity based on industry-level data underestimate the actual degree of GVC engagement by ignoring potential correlations between import and export activities across plants within industries. Second, the bias grew over the sample period. Finally, unlike with industry-level measures, we find little slowdown in GVC integration by U.S. manufacturers.
View Full
Paper PDF
-
The Impact of Immigration on Firms and Workers: Insights from the H-1B Lottery
April 2024
Working Paper Number:
CES-24-19
We study how random variation in the availability of highly educated, foreign-born workers impacts firm performance and recruitment behavior. We combine two rich data sources: 1) administrative employer-employee matched data from the US Census Bureau; and 2) firm level information on the first large-scale H-1B visa lottery in 2007. Using an event-study approach, we find that lottery wins lead to increases in firm hiring of college-educated, immigrant labor along with increases in scale and survival. These effects are stronger for small, skill-intensive, and high-productivity firms that participate in the lottery. We do not find evidence for displacement of native-born, college-educated workers at the firm level, on net. However, this result masks dynamics among more specific subgroups of incumbents that we further elucidate.
View Full
Paper PDF
-
Who's Most Exposed to International Shocks? Estimating Differences in Import Price Sensitivity across U.S. Demographic Groups
March 2023
Working Paper Number:
CES-23-13R
Differences in consumption patterns across demographic groups mean that international price shocks differentially affect such groups. We construct import price indexes for U.S. households that vary by age, race, marital status, education, and urban status. Black households and urban households experienced significantly higher import price inflation from 1996-2018 compared to other groups, such as white households and rural households. Sensitivity to international price shocks varies widely, implying movements in exchange rates and foreign prices, both during our sample and during the Covid-19 pandemic, drove sizable differences in import price inflation ' and total inflation ' across households.
View Full
Paper PDF
-
The Long-run Effects of the 1930s Redlining Maps on Children
December 2022
Working Paper Number:
CES-22-56
We estimate the long-run effects of the 1930s Home Owners Loan Corporation (HOLC) redlining maps by linking children in the full count 1940 Census to 1) the universe of IRS tax data in 1974 and 1979 and 2) the long form 2000 Census. We use two identification strategies to estimate the potential long-run effects of differential access to credit along HOLC boundaries. The first strategy compares cross-boundary differences along HOLC boundaries to a comparison group of boundaries that had statistically similar pre-existing differences as the actual boundaries. A second approach only uses boundaries that were least likely to have been chosen by the HOLC based on our statistical model. We find that children living on the lower-graded side of HOLC boundaries had significantly lower levels of educational attainment, reduced income in adulthood, and lived in neighborhoods during adulthood characterized by lower educational attainment, higher poverty rates, and higher rates of single-headed households.
View Full
Paper PDF
-
Investment and Subjective Uncertainty
November 2022
Working Paper Number:
CES-22-52
A longstanding challenge in evaluating the impact of uncertainty on investment is obtaining measures of managers' subjective uncertainty. We address this challenge by using a detailed new survey measure of subjective uncertainty collected by the U.S. Census Bureau for approximately 25,000 manufacturing plants. We find three key results. First, investment is strongly and robustly negatively associated with higher uncertainty, with a two standard deviation increase in uncertainty associated with about a 6% reduction in investment. Second, uncertainty is also negatively related to employment growth and overall shipments (sales) growth, which highlights the damaging impact of uncertainty on firm growth. Third, flexible inputs like rental capital and temporary workers show a positive relationship to uncertainty, demonstrating that businesses switch from less flexible to more flexible factor inputs at higher levels of uncertainty.
View Full
Paper PDF
-
Trade Liberalization and Labor-Market Outcomes: Evidence from US Matched Employer-Employee Data
September 2022
Working Paper Number:
CES-22-42
We use matched employer-employee data to examine outcomes among workers initially employed within and outside manufacturing after trade liberalization with China. We find that exposure to this shock operates predominantly through workers' counties (versus industries), that larger own industry and downstream exposure typically reduce relative earnings, and that greater upstream exposure often raises them. The latter is particularly important outside manufacturing: while we find substantial and persistent predicted declines in relative earnings among manufacturing workers, those outside manufacturing are generally predicted to experience relative earnings gains. Investigation of employment reactions indicates they account for a small share of the earnings effect.
View Full
Paper PDF
-
Finding Needles in Haystacks: Multiple-Imputation Record Linkage Using Machine Learning
November 2021
Working Paper Number:
CES-21-35
This paper considers the problem of record linkage between a household-level survey and an establishment-level frame in the absence of unique identifiers. Linkage between frames in this setting is challenging because the distribution of employment across establishments is highly skewed. To address these difficulties, this paper develops a probabilistic record linkage methodology that combines machine learning (ML) with multiple imputation (MI). This ML-MI methodology is applied to link survey respondents in the Health and Retirement Study to their workplaces in the Census Business Register. The linked data reveal new evidence that non-sampling errors in household survey data are correlated with respondents' workplace characteristics.
View Full
Paper PDF
