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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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IMMIGRANT ENTREPRENEURS AND INNOVATION IN THE U.S. HIGH-TECH SECTOR
February 2019
Working Paper Number:
CES-19-06
We estimate differences in innovation behavior between foreign versus U.S.-born entrepreneurs in high-tech industries. Our data come from the Annual Survey of Entrepreneurs, a random sample of firms with detailed information on owner characteristics and innovation activities. We find uniformly higher rates of innovation in immigrant-owned firms for 15 of 16 different innovation measures; the only exception is for copyright/trademark. The immigrant advantage holds for older firms as well as for recent start-ups and for every level of the entrepreneur's education. The size of the estimated immigrant-native differences in product and process innovation activities rises with detailed controls for demographic and human capital characteristics but falls for R&D and patenting. Controlling for finance, motivations, and industry reduces all coefficients, but for most measures and specifications immigrants are estimated to have a sizable advantage in innovation.
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Understanding the Quality of Alternative Citizenship Data Sources for the 2020 Census
August 2018
Working Paper Number:
CES-18-38R
This paper examines the quality of citizenship data in self-reported survey responses compared to administrative records and evaluates options for constructing an accurate count of resident U.S. citizens. Person-level discrepancies between survey-collected citizenship data and administrative records are more pervasive than previously reported in studies comparing survey and administrative data aggregates. Our results imply that survey-sourced citizenship data produce significantly lower estimates of the noncitizen share of the population than would be produced from currently available administrative records; both the survey-sourced and administrative data have shortcomings that could contribute to this difference. Our evidence is consistent with noncitizen respondents misreporting their own citizenship status and failing to report that of other household members. At the same time, currently available administrative records may miss some naturalizations and capture others with a delay. The evidence in this paper also suggests that adding a citizenship question to the 2020 Census would lead to lower self-response rates in households potentially containing noncitizens, resulting in higher fieldwork costs and a lower-quality population count.
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High-Growth Entrepreneurship
January 2017
Working Paper Number:
CES-17-53
We study the patterns and determinants of job creation for a large cohort of start-up firms. Analysis of the universe of U.S. employers reveals strong persistence in employment size from firm birth to age seven, with a small fraction of firms accounting for most employment at both ages, patterns that are little explained by finely disaggregated industry controls or amount of finance. Linking to data from the Survey of Business Owners on characteristics of 54,700 founders of 36,400 start-ups, and defining 'high growth' as the top 5% of firms in the size distribution at age zero and seven, we find that women have a 30% lower probability of founding high-growth entrepreneurships at both ages. A similar gap for African-Americans at start-up disappears by age seven. Other differences with respect to race, ethnicity, and nativity are modest. Founder age is initially positively associated with high growth probability but the profile flattens after seven years and even becomes slightly negative. The education profile is initially concave, with advanced degree recipients no more likely to found high growth firms than high school graduates, but the former catch up to those with bachelor's degrees by firm age seven, while the latter do not. Most other relationships of high growth with founder characteristics are highly persistent over time. Prior business ownership is strongly positively associated, and veteran experience negatively associated, with high growth. A larger founding team raises the probability of high growth, while diversity (by gender, age, race/ethnicity, or nativity) either lowers the probability or has little effect. More start-up capital raises the high-growth propensity of firms founded by a sole proprietor, women, minorities, immigrants, veterans, novice entrepreneurs, and those who are younger or with less education. Perhaps surprisingly, women, minorities, and those with less education tend to choose high growth industries, but fewer of them achieve high growth compared to their industry peers.
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Does Higher Productivity Dispersion Imply Greater Misallocation?A Theoretical and Empirical Analysis
January 2016
Working Paper Number:
CES-16-42
Recent research maintains that the observed variation in productivity within industries reflects resource misallocation and concludes that large GDP gains may be obtained from market-liberalizing polices. Our theoretical analysis examines the impact on productivity dispersion of reallocation frictions in the form of costs of entry, operation, and restructuring, and shows that reforms reducing these frictions may raise dispersion of productivity across firms. The model does not imply a negative relationship between aggregate productivity and productivity dispersion. Our empirical analysis focuses on episodes of liberalizing policy reforms in the U.S. and six East European transition economies. Deregulation of U.S. telecommunications equipment manufacturing is associated with increased, not reduced, productivity dispersion, and every transition economy in our sample shows a sharp rise in dispersion after liberalization. Productivity dispersion under central planning is similar to that in the U.S., and it rises faster in countries adopting faster paces of liberalization. Lagged productivity dispersion predicts higher future productivity growth. The analysis suggests there is no simple relationship between the policy environment and productivity dispersion.
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Job Creation, Small vs. Large vs. Young, and the SBA
September 2015
Working Paper Number:
CES-15-24
Analyzing a list of all Small Business Administration (SBA) loans in 1991 to 2009 linked with annual information on all U.S. employers from 1976 to 2012, we apply detailed matching and regression methods to estimate the variation in SBA loan effects on job creation and firm survival across firm age and size groups. The estimated number of jobs created per million dollars of loans within the small business sector generally increases with size and decreases in age. The results suggest that the growth of small, mature firms is least financially constrained, and that faster growing firms experience the greatest financial constraints to growth. The estimated association between survival and loan amount is larger for younger and smaller firms facing the 'valley of death.'
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The Nature of the Bias When Studying Only Linkable Person Records: Evidence from the American Community Survey
April 2014
Working Paper Number:
carra-2014-08
Record linkage across survey and administrative records sources can greatly enrich data and improve their quality. The linkage can reduce respondent burden and nonresponse follow-up costs. This is particularly important in an era of declining survey response rates and tight budgets. Record linkage also creates statistical bias, however. The U.S. Census Bureau links person records through its Person Identification Validation System (PVS), assigning each record a Protected Identification Key (PIK). It is not possible to reliably assign a PIK to every record, either due to insufficient identifying information or because the information does not uniquely match any of the administrative records used in the person validation process. Non-random ability to assign a PIK can potentially inject bias into statistics using linked data. This paper studies the nature of this bias using the 2009 and 2010 American Community Survey (ACS). The ACS is well-suited for this analysis, as it contains a rich set of person characteristics that can describe the bias. We estimate probit models for whether a record is assigned a PIK. The results suggest that young children, minorities, residents of group quarters, immigrants, recent movers, low-income individuals, and non-employed individuals are less likely to receive a PIK using 2009 ACS. Changes to the PVS process in 2010 significantly addressed the young children deficit, attenuated the other biases, and increased the validated records share from 88.1 to 92.6 percent (person-weighted).
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Do SBA Loans Create Jobs? Estimates from Universal Panel Data and Longitudinal Matching Methods
September 2012
Working Paper Number:
CES-12-27
This pape reports estimates of the effects of the Small Business Administration (SBA) 7(a) and 504 loan programs on employment. The database links a complete list of all SBA loans in these programs to universal data on all employers in the U.S. economy from 1976 to 2010. Our method is to estimate firm fixed effect regressions using matched control groups for the SBA loan recipients we have constructed by matching exactly on firm age, industry, year, and pre-loan size, plus kernel-based matching on propensity scores estimated as a function of four years of employment history and other variables. The results imply positive average effects on loan recipient employment of about 25 percent or 3 jobs at the mean. Including loan amount, we find little or no impact of loan receipt per se, but an increase of about 5.4 jobs for each million dollars of loans. When focusing on loan recipients and control firms located in high-growth counties (average growth of 22 percent), places where most small firms should have excellent growth potential, we find similar effects, implying that the estimates are not driven by differential demand conditions across firms. Results are also similar regardless of distance of control from recipient firms, suggesting only a very small role for displacement effects. In all these cases, the results pass a "pre-program" specification test, where controls and treated firms look similar in the pre-loan period. Other specifications, such as those using only matching or only regression imply somewhat higher effects, but they fail the pre-program test.
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Nature Versus Nurture in the Origins of Highly Productive Businesses: An Exploratory Analysis of U.S. Manufacturing Establishments
September 2011
Working Paper Number:
CES-11-26
This paper investigates the origins of productivity leaders, those that operate close to and help push out the production frontier. Do such businesses emerge as top performers from the very beginning of their lives, for example as the consequence of an outstanding founding idea, technology, or location? Or, at the other extreme, do they appear initially as completely average (or even underperformers) that exhibit gradual improvement as they learn and develop with age? To answer this question we draw upon five decades of U.S. Census of Manufacturing (CM) establishment-level data, tracing the productivity leaders of the most recent CM (2007) back over their observed life spans. We also examine possible industry-level correlates of variation in the extent of nature versus nurture that are suggested by theories of industry dynamics and economic growth.
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Entry, Growth, and the Business Environment: A Comparative Analysis of Enterprise Data from the U.S. and Transition Economies
September 2010
Working Paper Number:
CES-10-20
What role does new firm entry play in economic growth? Are entrants and young firms more or less productive than incumbents, and how are their relative productivity dynamics affected by financial constraints and the business environment? This paper uses comprehensive manufacturing firm data from seven economies (United States, Georgia, Hungary, Lithuania, Romania, Russia, and Ukraine) to measure new firm entry and the productivity dynamics of entrants relative to incumbents in the same industries. We contrast hypotheses based on 'leapfrogging,' in which entrants embody superior productivity, with an 'experimentation' approach, in which entrants face uncertainty and incumbents can innovate. The results imply that leapfrogging is typical of early and incomplete transition, but experimentation better characterizes both the US and mature transition economies. Improvements in financial markets and the business environment tend to raise both the entry rate and productivity growth, but they are associated with negative relative productivity of entrants and smaller contributions of reallocation to growth among both entrants and incumbents.
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