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Citizenship Question Effects on Household Survey Response
June 2024
Working Paper Number:
CES-24-31
Several small-sample studies have predicted that a citizenship question in the 2020 Census would cause a large drop in self-response rates. In contrast, minimal effects were found in Poehler et al.'s (2020) analysis of the 2019 Census Test randomized controlled trial (RCT). We reconcile these findings by analyzing associations between characteristics about the addresses in the 2019 Census Test and their response behavior by linking to independently constructed administrative data. We find significant heterogeneity in sensitivity to the citizenship question among households containing Hispanics, naturalized citizens, and noncitizens. Response drops the most for households containing noncitizens ineligible for a Social Security number (SSN). It falls more for households with Latin American-born immigrants than those with immigrants from other countries. Response drops less for households with U.S.-born Hispanics than households with noncitizens from Latin America. Reductions in responsiveness occur not only through lower unit self-response rates, but also by increased household roster omissions and internet break-offs. The inclusion of a citizenship question increases the undercount of households with noncitizens. Households with noncitizens also have much higher citizenship question item nonresponse rates than those only containing citizens. The use of tract-level characteristics and significant heterogeneity among Hispanics, the foreign-born, and noncitizens help explain why the effects found by Poehler et al. were so small. Linking administrative microdata with the RCT data expands what we can learn from the RCT.
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How Big is Small? The Economic Effects of Access to Small Business Subsidies
June 2024
Working Paper Number:
CES-24-28
Industry size standards that determine eligibility for small business subsidies have vastly increased
over the past decade. We exploit quasi-random variation in the implementation of size standard
increases to study the effects on small firms, subsidy allocation, and industry outcomes using
Census Bureau microdata. Following size standard increases, revenues decline for an industry's
smallest firms, and they are less likely to survive. We link these effects to a reallocation of
government procurement contracts from smaller to larger firms. Consequently, industries become
more concentrated and growth declines. These findings highlight the broad economic effects of
changing eligibility for small business subsidies.
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Producing U.S. Population Statistics Using Multiple Administrative Sources
November 2023
Working Paper Number:
CES-23-58
We identify several challenges encountered when constructing U.S. administrative record-based (AR-based) population estimates for 2020. Though the AR estimates are higher than the 2020 Census at the national level, they are over 15 percent lower in 5 percent of counties, suggesting that locational accuracy can be improved. Other challenges include how to achieve comprehensive coverage, maintain consistent coverage across time, filter out nonresidents and people not alive on the reference date, uncover missing links across person and address records, and predict demographic characteristics when multiple ones are reported or when they are missing. We discuss several ways of addressing these issues, e.g., building in redundancy with more sources, linking children to their parents' addresses, and conducting additional record linkage for people without Social Security Numbers and for addresses not initially linked to the Census Bureau's Master Address File. We discuss modeling to predict lower levels of geography for people lacking those geocodes, the probability that a person is a U.S. resident on the reference date, the probability that an address is the person's residence on the reference date, and the probability a person is in each demographic characteristic category. Regression results illustrate how many of these challenges and solutions affect the AR county population estimates.
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Are Immigrants More Innovative? Evidence from Entrepreneurs
November 2023
Working Paper Number:
CES-23-56
We evaluate the contributions of immigrant entrepreneurs to innovation in the U.S. using linked survey-administrative data on 199,000 firms with a rich set of innovation measures and other firm and owner characteristics. We find that not only are immigrants more likely than natives to own businesses, but on average their firms display more innovation activities and outcomes. Immigrant owned firms are particularly more likely to create completely new products, improve previous products, use new processes, and engage in both basic and applied R&D, and their efforts are reflected in substantially higher levels of patents and productivity. Immigrant owners are slightly less likely than natives to imitate products of others and to hire more employees. Delving into potential explanations of the immigrant-native differences, we study other characteristics of entrepreneurs, access to finance, choice of industry, immigrant self-selection, and effects of diversity. We find that the immigrant innovation advantage is robust to controlling for detailed characteristics of firms and owners, it holds in both high-tech and non-high-tech industries and, with the exception of productivity, it tends to be even stronger in firms owned by diverse immigrant-native teams and by diverse immigrants from different countries. The evidence from nearly all measures that immigrants tend to operate more innovative and productive firms, together with the higher share of business ownership by immigrants, implies large contributions to U.S. innovation and growth.
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Noncitizen Coverage and Its Effects on U.S. Population Statistics
August 2023
Working Paper Number:
CES-23-42
We produce population estimates with the same reference date, April 1, 2020, as the 2020 Census of Population and Housing by combining 31 types of administrative record (AR) and third-party sources, including several new to the Census Bureau with a focus on noncitizens. Our AR census national population estimate is higher than other Census Bureau official estimates: 1.8% greater than the 2020 Demographic Analysis high estimate, 3.0% more than the 2020 Census count, and 3.6% higher than the vintage-2020 Population Estimates Program estimate. Our analysis suggests that inclusion of more noncitizens, especially those with unknown legal status, explains the higher AR census estimate. About 19.8% of AR census noncitizens have addresses that cannot be linked to an address in the 2020 Census collection universe, compared to 5.7% of citizens, raising the possibility that the 2020 Census did not collect data for a significant fraction of noncitizens residing in the United States under the residency criteria used for the census. We show differences in estimates by age, sex, Hispanic origin, geography, and socioeconomic characteristics symptomatic of the differences in noncitizen coverage.
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Estimating the U.S. Citizen Voting-Age Population (CVAP) Using Blended Survey Data, Administrative Record Data, and Modeling: Technical Report
April 2023
Authors:
J. David Brown,
Danielle H. Sandler,
Lawrence Warren,
Moises Yi,
Misty L. Heggeness,
Joseph L. Schafer,
Matthew Spence,
Marta Murray-Close,
Carl Lieberman,
Genevieve Denoeux,
Lauren Medina
Working Paper Number:
CES-23-21
This report develops a method using administrative records (AR) to fill in responses for nonresponding American Community Survey (ACS) housing units rather than adjusting survey weights to account for selection of a subset of nonresponding housing units for follow-up interviews and for nonresponse bias. The method also inserts AR and modeling in place of edits and imputations for ACS survey citizenship item nonresponses. We produce Citizen Voting-Age Population (CVAP) tabulations using this enhanced CVAP method and compare them to published estimates. The enhanced CVAP method produces a 0.74 percentage point lower citizen share, and it is 3.05 percentage points lower for voting-age Hispanics. The latter result can be partly explained by omissions of voting-age Hispanic noncitizens with unknown legal status from ACS household responses. Weight adjustments may be less effective at addressing nonresponse bias under those conditions.
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Black Entrepreneurs, Job Creation, and Financial Constraints
May 2021
Working Paper Number:
CES-21-11
Black-owned businesses tend to operate with less finance and employ fewer workers than those owned by Whites. Motivated by a simple conceptual framework, we document these facts and show they are causally connected using large firm-level surveys linked to universal employer data from the Census Bureau. We find that the racial financing gap is most pronounced at start-up and tends to narrow with firm age. At any age, Black-owned firms are less likely to receive bank loans, more likely to refrain from applying because they expect denial, and more likely to report that lack of finance reduces their profitability. Yet the observable characteristics of Black entrepreneurs are similar in most respects to Whites, and in some ways - higher education, growth-oriented motivations, and involvement in the business - would seem to imply higher, not lower, demand for finance. Concerning employment, we find that Black-owned firms have on average about 12 percent fewer employees than those owned by Whites, but the difference drops when controlling for firm age and other characteristics. However, when the analysis holds financial variables constant, the results imply that equally well-financed Black-owned rms would be larger than White-owned by about seven percent. Exploiting the credit supply shock of changing assignment to Community Reinvestment Act treatment through a Regression Discontinuity Design in a firm-level panel regression framework, we find that expanded credit access raises employment 5-7 percentage points more at Black-owned businesses than White-owned firms in treated neighborhoods.
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Determination of the 2020 U.S. Citizen Voting Age Population (CVAP) Using Administrative Records and Statistical Methodology Technical Report
October 2020
Authors:
John M. Abowd,
J. David Brown,
Lawrence Warren,
Moises Yi,
Misty L. Heggeness,
William R. Bell,
Michael B. Hawes,
Andrew Keller,
Vincent T. Mule Jr.,
Joseph L. Schafer,
Matthew Spence
Working Paper Number:
CES-20-33
This report documents the efforts of the Census Bureau's Citizen Voting-Age Population (CVAP) Internal Expert Panel (IEP) and Technical Working Group (TWG) toward the use of multiple data sources to produce block-level statistics on the citizen voting-age population for use in enforcing the Voting Rights Act. It describes the administrative, survey, and census data sources used, and the four approaches developed for combining these data to produce CVAP estimates. It also discusses other aspects of the estimation process, including how records were linked across the multiple data sources, and the measures taken to protect the confidentiality of the data.
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Do Cash Windfalls Affect Wages? Evidence from R&D Grants to Small Firms
February 2020
Working Paper Number:
CES-20-06
This paper examines how employee earnings at small firms respond to a cash flow shock in the form of a government R&D grant. We use ranking data on applicant firms, which we link to IRS W2 earnings and other U.S. Census Bureau datasets. In a regression discontinuity design, we find that the grant increases average earnings with a rent-sharing elasticity of 0.07 (0.21) at the employee (firm) level. The beneficiaries are incumbent employees who were present at the firm before the award. Among incumbent employees, the effect increases with worker tenure. The grant also leads to higher employment and revenue, but productivity growth cannot fully explain the immediate effect on earnings. Instead, the data and a grantee survey are consistent with a backloaded wage contract channel, in which employees of financially constrained firms initially accept relatively low wages and are paid more when cash is available.
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Predicting the Effect of Adding a Citizenship Question to the 2020 Census
June 2019
Working Paper Number:
CES-19-18
The addition of a citizenship question to the 2020 census could affect the self-response rate, a key driver of the cost and quality of a census. We find that citizenship question response patterns in the American Community Survey (ACS) suggest that it is a sensitive question when asked about administrative record noncitizens but not when asked about administrative record citizens. ACS respondents who were administrative record noncitizens in 2017 frequently choose to skip the question or answer that the person is a citizen. We predict the effect on self-response to the entire survey by comparing mail response rates in the 2010 ACS, which included a citizenship question, with those of the 2010 census, which did not have a citizenship question, among households in both surveys. We compare the actual ACS-census difference in response rates for households that may contain noncitizens (more sensitive to the question) with the difference for households containing only U.S. citizens. We estimate that the addition of a citizenship question will have an 8.0 percentage point larger effect on self-response rates in households that may have noncitizens relative to those with only U.S. citizens. Assuming that the citizenship question does not affect unit self-response in all-citizen households and applying the 8.0 percentage point drop to the 28.1 % of housing units potentially having at least one noncitizen would predict an overall 2.2 percentage point drop in self-response in the 2020 census, increasing costs and reducing the quality of the population count.
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