Papers Containing Tag(s): 'Ordinary Least Squares'
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Viewing papers 1 through 10 of 312
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Working PaperThe Real Effects of Bankruptcy Forum Shopping
May 2026
Working Paper Number:
CES-26-29
Many non-Delaware firms strategically file for bankruptcy in Delaware. Should this "forum shopping" be allowed? This question has motivated nine proposed congressional bills over decades of policy debate. Using a novel natural experiment and Census-Bureau microdata, we inform this debate. Comparing similar firms within a Delaware-adjacent state, we show that proximity to Delaware predicts forum shopping. Instrumenting with proximity, we find that forum shopping causally: (i) prevents closures'and liquidations, (ii) shortens bankruptcies, (iii) boosts creditor recovery, and (iv) increases post-bankruptcy employment by 24.8%. Proximity to Delaware is uncorrelated with growth for not-yet-bankrupt or never-bankrupt firms, validating the exclusion restriction.View Full Paper PDF
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Working PaperThe Microstructure of AI Diffusion: Evidence From Firms, Business Functions, and Worker Tasks
April 2026
Working Paper Number:
CES-26-25
Using novel, nationally representative data from the 2026 AI supplement to the U.S. Census Bureau's Business Trends and Outlook Survey (BTOS), we characterize AI diffusion across three interconnected layers: overall firm use, deployment across business functions, and worker-task use. This multi-layered approach provides a nuanced picture of business AI adoption. During the supplement reference period (Nov 2025-Jan 2026), 18% of firms used AI in a business function, rising to 32% on an employment-weighted basis; adoption is expected to reach 22% within six months. AI use is substantially higher in large firms and knowledge-intensive sectors, with use rates reaching 50%-60% (60%-70%, employment-weighted) for very large firms in the Information, Professional Services, and Finance sectors. Among adopting firms, the scope of use remains limited: 57% of users integrate AI in three or fewer business functions, most commonly Sales and Marketing (52%), Strategy and Business Development (45%), and IT (41%). In 23% (41%, employment-weighted) of firms, workers use AI in work-related tasks. Writing, document analysis, and information search are the leading Generative AI use in tasks, though 65% of firms limit use to three or fewer tasks. The evidence points to both top-down and bottom-up diffusion channels: worker task use sometimes occurs without formal firm-level adoption, and firm-level adoption sometimes occurs without worker task use. Most users (66%) rely on AI solely to augment tasks, while AI-related employment decreases are rare, occurring in only 2% of firms. Regression analysis shows a robust positive correlation between firm commercial performance and the breadth of AI integration, including functional deployment, task-level use, and operational investment. A distinct divergence emerges, however, with respect to labor outcomes. Functional breadth and operational investment are positively associated with employment decreases, whereas worker-task integration shows no significant link to headcount reduction once functional integration and operational investment are taken into account.View Full Paper PDF
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Working PaperUnemployment Insurance Extensions, Labor Market Concentration, and Match Quality
April 2026
Working Paper Number:
CES-26-24
I investigate whether the effects of UI extensions are different for workers exposed to higher levels of local labor market concentration, a potential source of employer market power. I exploit measurement error in state unemployment rates that led to quasi-random assignment of UI durations in the U.S. during the Great Recession. Using matched employer-employee data from the Longitudinal Employer-Household Dynamics program, I find that UI extensions lengthen nonemployment durations by one week and cause economically meaningful but not statistically significant increases in earnings. The UI-earnings effect is significantly lower at higher levels of concentration, while there is no difference in the UI-duration effect. The lower UI-earnings effect is driven by the extremes of the distribution of concentration. My results suggest that match improvements from UI are attenuated at higher levels of concentration.View Full Paper PDF
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Working PaperHow Do Neighborhoods and Firms Affect Intergenerational Mobility?
March 2026
Working Paper Number:
CES-26-18
We use data from the Longitudinal Employer Household Dynamics linked to the 2000 Census to study intergenerational earnings mobility in the United States. We augment the standard intergenerational transmission model relating children's log earnings to those of their parent with an additional term representing mean log parent earnings in the childhood neighborhood. The between-neighborhood intergenerational relationship is twice as strong as the within-neighborhood relationship, even after adjusting for measurement error in parents' earnings. Moreover, mean earnings of the parents in a neighborhood capture over 80% of the variation in unrestricted neighborhood effects that reflect differences in 'absolute mobility'. Next, we use an AKM framework to decompose parents', children's, and neighboring parents' earnings into person effects and establishment premiums. Children's person effects are mainly influenced by parents' and neighbors' person effects, whereas children's establishment premiums are mainly influenced by parents' and neighbors' establishment premiums. These patterns point to separate channels for human capital and access to jobs in the intergenerational transmission process. Finally, we explore the implications for the Black-white earnings gap. Neighborhoods explain 30% of the Black-white gap in children's earnings conditional on parents' earnings, operating largely through gaps in average person effects. Conditional on neighborhood average earnings, children from neighborhoods with higher Black shares achieve higher adult earnings.View Full Paper PDF
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Working PaperDid Foreigners Pay America's Tariffs? Quantity Discounts, Scale Economies and Incomplete Pass-Through
February 2026
Working Paper Number:
CES-26-17
Transaction-level quantity discounts are a pervasive feature of US trade, shaping both price variation and tariff incidence. Using administrative microdata, we show that these discounts reflect transaction-level scale economies rather than market power. Accounting for these micro-level economies resolves a key puzzle: while observed import prices rose one-for-one with 2018-2019 US tariffs, we show this was driven by the loss of scale economies as transaction sizes collapsed. Controlling for this scale effect, the strategic pass-through of tariffs to scale-free prices falls to 60 percent, implying foreign exporters absorbed a significant share of the burden through reduced markups.View Full Paper PDF
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Working PaperTrade and Welfare (across Local Labor Markets)
February 2026
Working Paper Number:
CES-26-16
What are the welfare implications of trade shocks? Theoretically, we provide a sufficient statistic that measures changes in welfare (to a first-order approximation) for the set of workers who start within a region, taking into account adjustment in frictional unemployment, labor force participation, the sectors to which workers apply for jobs, and the regions in which workers choose to live. Our theory is flexible; for instance, it allows for arbitrary heterogeneity in worker productivity and non-pecuniary returns (amenities) across unemployment, labor force non-participation, sectors, and regions. Empirically, we apply these insights to measure changes in welfare between 2000-2007 across workers who start in different commuting zones (CZs) in the U.S. in the year 2000. Finally, we identify the differential impact across CZs of a particular trade shock: granting China permanent normal trade relations.View Full Paper PDF
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Working PaperCollege Majors and Earnings Growth
February 2026
Working Paper Number:
CES-26-14
We estimate major-specific earnings profiles using matched American Community Survey (ACS) and Longitudinal Employer-Household Dynamics (LEHD) data. Building on Deming and Noray (2020), we exploit a long earnings panel to overcome key limitations of cross-sectional approaches to lifecycle estimation. We find that engineering and computer science majors experience earnings growth that is comparable to or faster than that of other majors, a category including humanities, education, psychology, and similar fields. In contrast, Deming and Noray (2020) use a crosscohort approach and find that earnings for engineering and computer science majors decline relative to other fields over the lifecycle.View Full Paper PDF
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Working PaperEstablishment-Level Life Cycle and Analysts' Forecasts
February 2026
Working Paper Number:
CES-26-12
This paper examines how multi-unit firms' life-cycle stages affect analyst forecast accuracy. While prior studies focus on the firm-level life cycle, we utilize the Census data and focus on the establishment level. We find that analyst forecast accuracy is lower for multi-unit firms whose establishments are in different life-cycle stages than those in the same life-cycle stage. This finding suggests that the forecasting difficulty of more diversified firms can be attributed to the different life-cycle stages of each establishment. We also find that for firms whose units are in different stages, analyst forecast accuracy is lower if the establishments in earlier stages are larger (i.e., generate more revenue) than those in later stages. As a comparison, we estimate the life-cycle stages using firms' segment classifications in their 10-K filings. We find that analysts' forecast accuracy is lower when firms report fewer segments than the number of establishments, suggesting that aggregating more establishments for segment reporting could complicate analysts' forecasting. To our knowledge, this is the first study that focuses on the establishment-level life cycle. This study highlights that firm-level life cycles should not be taken without caution, as aggregating multiple units' life cycles may be misleading. In order to provide better forecasts to investors, analysts should have a deeper understanding of firms' subunits, especially when the establishments are in different life-cycle stages.View Full Paper PDF
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Working PaperExpectations versus Reality in Business Formation
February 2026
Working Paper Number:
CES-26-11
Using administrative data on 17 million U.S. business applications linked to outcomes, we compare potential entrants' expectations about employer entry and first-year employment with realizations. On average, applicants overestimate employment, mainly because many expect to enter but do not. Among those who expect and achieve entry, employment is typically underestimated. Expected employment predicts entry and realized employment, but conditional on entry realized employment rises less than one-for-one with expectations. Expectation errors are highly heterogeneous and systematically related to application characteristics and local economic conditions, and they predict near-term employment outcomes. A parsimonious model with heterogeneous priors, learning, and pre-entry selection rationalizes these patterns.View Full Paper PDF
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Working PaperCreating High-Opportunity Neighborhoods: Evidence from the HOPE VI Program
January 2026
Working Paper Number:
CES-26-02
We study whether low-economic-mobility neighborhoods can be transformed into high-mobility areas by analyzing the HOPE VI program, which invested $17 billion to revitalize 262 distressed public housing developments. We estimate the program's impacts using a matched difference-in-differences design, comparing outcomes in revitalized developments to observably similar control developments using anonymized tax records. HOPE VI reduced neighborhood poverty rates by attracting higher-income families to revitalized neighborhoods, but had no causal impact on the earnings of adults living in public housing units. Children raised in revitalized public housing units earn more, are more likely to attend college, and are less likely to be incarcerated. Using a movers exposure design and sibling comparisons, we show that these improvements were driven by changes in neighborhoods' causal effects on children's outcomes. The improvements in neighborhood causal effects were driven in large part by changes in social interaction: HOPE VI increased interaction between public housing residents and peers in surrounding neighborhoods and increased earnings more for subgroups with higher-income peers. Many low-income families in the U.S. currently live in neighborhoods that are as socially isolated as the HOPE VI developments were prior to revitalization. We conclude that it is feasible to create high-opportunity neighborhoods and that connecting socially isolated areas to surrounding communities is a cost-effective approach to doing so.View Full Paper PDF
