Papers Containing Tag(s): 'Disclosure Review Board'
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Viewing papers 21 through 30 of 166
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Working PaperHousehold Wealth and Entrepreneurial Career Choices: Evidence from Climate Disasters
July 2024
Working Paper Number:
CES-24-39
This study investigates how household wealth affects the human capital of startups, based on U.S. Census individual-level employment data, deed records, and geographic information system (GIS) data. Using floods as a wealth shock, a regression discontinuity analysis shows inundated residents are 7% less likely to work in startups relative to their neighbors outside the flood boundary, within a 0.1-mile-wide band. The effect is more pronounced for homeowners, consistent with the wealth effect. The career distortion leads to a significant long-run income loss, highlighting the importance of self-insurance for human capital allocation.View Full Paper PDF
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Working PaperPayroll Tax Incidence: Evidence from Unemployment Insurance
June 2024
Working Paper Number:
CES-24-35
Economic models assume that payroll tax burdens fall fully on workers, but where does tax incidence fall when taxes are firm-specific and time-varying? Unemployment insurance in the United States has the key feature of varying both across employers and over time, creating the potential for labor demand responses if tax costs cannot be fully passed through to worker wages. Using state policy changes and administrative data of matched employer-employee job spells, I study how employment and earnings respond to unexpected payroll tax increases for highly exposed employers. I find significant drops in employment growth driven by lower hiring, and minimal evidence of passthrough to earnings. The negative employment effects are strongest for young workers and single-establishment firms.View Full Paper PDF
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Working PaperUrban-Biased Growth: A Macroeconomic Analysis
June 2024
Working Paper Number:
CES-24-33
After 1980, larger US cities experienced substantially faster wage growth than smaller ones. We show that this urban bias mainly reflected wage growth at large Business Services firms. These firms stand out through their high per-worker expenditure on information technology and disproportionate presence in big cities. We introduce a spatial model of investment-specific technical change that can rationalize these patterns. Using the model as an accounting framework, we find that the observed decline in the investment price of information technology capital explains most urban-biased growth by raising the profits of large Business Services firms in big cities.View Full Paper PDF
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Working PaperMeasuring Income of the Aged in Household Surveys: Evidence from Linked Administrative Records
June 2024
Working Paper Number:
CES-24-32
Research has shown that household survey estimates of retirement income (defined benefit pensions and defined contribution account withdrawals) suffer from substantial underreporting which biases downward measures of financial well-being among the aged. Using data from both the redesigned 2016 Current Population Survey Annual Social and Economic Supplement (CPS ASEC) and the Health and Retirement Study (HRS), each matched with administrative records, we examine to what extent underreporting of retirement income affects key statistics such as reliance on Social Security benefits and poverty among the aged. We find that underreporting of retirement income is still prevalent in the CPS ASEC. While the HRS does a better job than the CPS ASEC in terms of capturing retirement income, it still falls considerably short compared to administrative records. Consequently, the relative importance of Social Security income remains overstated in household surveys'53 percent of elderly beneficiaries in the CPS ASEC and 49 percent in the HRS rely on Social Security for the majority of their incomes compared to 42 percent in the linked administrative data. The poverty rate for those aged 65 and over is also overstated'8.8 percent in the CPS ASEC and 7.4 percent in the HRS compared to 6.4 percent in the linked administrative data. Our results illustrate the effects of using alternative data sources in producing key statistics from the Social Security Administration's Income of the Aged publication.View Full Paper PDF
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Working PaperSchool Equalization in the Shadow of Jim Crow: Causes and Consequences of Resource Disparity in Mississippi circa 1940
May 2024
Working Paper Number:
CES-24-25
A school finance equalization program established in Mississippi in 1920 failed to help many of the state's Black students'an outcome that was typical in the segregated U.S. South (Horace Mann Bond, 1934). In majority-Black school districts, local decision-makers overwhelmingly favored white schools when allotting funds from the state's preexisting per capita fund, and the resulting high expenditures on white students rendered these districts ineligible for the equalization program. Thus, while Black students residing in majority-white districts benefitted from increased spending and standards for Black schools, those in majority-Black districts continued to experience extremely low'and even worsening'school funding. We model the processes that led the so-called equalization policy to create disparities in schooling resources for Black students, and estimate effects on Black children using both a neighboring-counties design and an IV strategy. We find that local educational spending had large impacts on Black enrollment rates, as reported in the 1940 census, with Black educational attainment increasing in marginal spending. Finally, we link the 1940 and 2000 censuses to show that Black children exposed to higher levels of school expenditures had significantly more completed schooling and higher income late in life.View Full Paper PDF
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Working PaperWhere Are Your Parents? Exploring Potential Bias in Administrative Records on Children
March 2024
Working Paper Number:
CES-24-18
This paper examines potential bias in the Census Household Composition Key's (CHCK) probabilistic parent-child linkages. By linking CHCK data to the American Community Survey (ACS), we reveal disparities in parent-child linkages among specific demographic groups and find that characteristics of children that can and cannot be linked to the CHCK vary considerably from the larger population. In particular, we find that children from low-income, less educated households and of Hispanic origin are less likely to be linked to a mother or a father in the CHCK. We also highlight some data considerations when using the CHCK.View Full Paper PDF
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Working PaperGrassroots Design Meets Grassroots Innovation: Rural Design Orientation and Firm Performance
March 2024
Working Paper Number:
CES-24-17
The study of grassroots design'applying structured, creative processes to the usability or aesthetics of a product without input from professional design consultancies'remains under investigated. If design comprises a mediation between people and technology whereby technologies are made more accessible or more likely to delight, then the process by which new grassroots inventions are transformed into innovations valued in markets cannot be fully understood. This paper uses U.S. data on the design orientation of respondents in the 2014 Rural Establishment Innovation Survey linked to longitudinal data on the same firms to examine the association between design, innovation, and employment and payroll growth. Findings from the research will inform questions to be investigated in the recently collected 2022 Annual Business Survey (ABS) that for the first time contains a Design module.View Full Paper PDF
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Working PaperTracking Firm Use of AI in Real Time: A Snapshot from the Business Trends and Outlook Survey
March 2024
Working Paper Number:
CES-24-16R
Timely and accurate measurement of AI use by firms is both challenging and crucial for understanding the impacts of AI on the U.S. economy. We provide new, real-time estimates of current and expected future use of AI for business purposes based on the Business Trends and Outlook Survey for September 2023 to February 2024. During this period, bi-weekly estimates of AI use rate rose from 3.7% to 5.4%, with an expected rate of about 6.6% by early Fall 2024. The fraction of workers at businesses that use AI is higher, especially for large businesses and in the Information sector. AI use is higher in large firms but the relationship between AI use and firm size is non-monotonic. In contrast, AI use is higher in young firms. Common uses of AI include marketing automation, virtual agents, and data/text analytics. AI users often utilize AI to substitute for worker tasks and equipment/software, but few report reductions in employment due to AI use. Many firms undergo organizational changes to accommodate AI, particularly by training staff, developing new workflows, and purchasing cloud services/storage. AI users also exhibit better overall performance and higher incidence of employment expansion compared to other businesses. The most common reason for non-adoption is the inapplicability of AI to the business.View Full Paper PDF
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Working PaperFamily Resources and Human Capital in Economic Downturns
March 2024
Working Paper Number:
CES-24-15
I study how recessions impact the human capital of young adults and how these effects vary over the parent income gradient. Using a novel confidential linked survey dataset from U.S. Census, I document that the negative effects of worse local unemployment shocks on educational attainment are strongly concentrated among middle-class children, with losses in parental home equity being potentially important mechanisms. To probe the aggregate implications of these findings and assess policy implications, I develop a model of selection into college and life-cycle earnings that comprises endogenous parental transfers for education, multiple schooling options, and uncertainty in post-graduation employment outcomes. Simulating a recession in the model produces a 'hollowing out the middle' in lifecycle earnings in the aggregate, and educational borrowing constraints play a key role in this result. Counterfactual policies to expand college access in response to the recession can mitigate these effects but struggle to be cost effective.View Full Paper PDF
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Working PaperExamining Racial Identity Responses Among People with Middle Eastern and North African Ancestry in the American Community Survey
March 2024
Working Paper Number:
CES-24-14
People with Middle Eastern and North African (MENA) backgrounds living in the United States are defined and classified as White by current Federal standards for race and ethnicity, yet many MENA people do not identify as White in surveys, such as those conducted by the U.S. Census Bureau. Instead, they often select 'Some Other Race', if it is provided, and write in MENA responses such as Arab, Iranian, or Middle Eastern. In processing survey data for public release, the Census Bureau classifies these responses as White in accordance with Federal guidance set by the U.S. Office of Management and Budget. Research that uses these edited public data relies on limited information on MENA people's racial identification. To address this limitation, we obtained unedited race responses in the nationally representative American Community Survey from 2005-2019 to better understand how people of MENA ancestry report their race. We also use these data to compare the demographic, cultural, socioeconomic, and contextual characteristics of MENA individuals who identify as White versus those who do not identify as White. We find that one in four MENA people do not select White alone as their racial identity, despite official guidance that defines 'White' as people having origins in any of the original peoples of Europe, the Middle East, or North Africa. A variety of individual and contextual factors are associated with this choice, and some of these factors operate differently for U.S.-born and foreign-born MENA people living in the United States.View Full Paper PDF
