Statistical agencies frequently publish microdata that have been altered to protect confidentiality. Such data retain utility for many types of broad analyses but can yield biased or Insufficiently precise results in others. Research access to de-identified versions of the restricted-use data with little or no alteration is often possible, albeit costly and time-consuming. We investigate the the advantages and disadvantages of public-use and restricted-use data from the American Community
Survey (ACS) in constructing a wage index. The public-use data used were Public Use Microdata Samples, while the restricted-use data were accessed via a Federal Statistical Research Data Center. We discuss the advantages and disadvantages of each data source and compare estimated CWIs and standard errors at the state and labor market levels.
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Who Values Human Capitalists' Human Capital? Healthcare Spending and Physician Earnings
July 2020
Working Paper Number:
CES-20-23
Is government guiding the invisible hand at the top of the labor market? We study this question among physicians, the most common occupation among the top one percent of income earners, and whose billings comprise one-fifth of healthcare spending. We use a novel linkage of population-wide tax records with the administrative registry of all physicians in the U.S. to study the characteristics of these high earnings, and the influence of government payments in particular. We find a major role for government on the margin, with half of direct changes to government reimbursement rates flowing directly into physicians' incomes. These policies move physicians' relative and absolute incomes more than any reasonable changes to marginal tax rates. At the same time, the overall level of physician earnings can largely be explained by labor market fundamentals of long work and training hours. Competing occupations also pay well and provide a natural lower bound for physician earnings. We conclude that government plays a major role in determining the value of physicians' human capital, but it is unrealistic to use this power to reduce healthcare spending substantially.
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SYNTHETIC DATA FOR SMALL AREA ESTIMATION IN THE AMERICAN COMMUNITY SURVEY
April 2013
Working Paper Number:
CES-13-19
Small area estimates provide a critical source of information used to study local populations. Statistical agencies regularly collect data from small areas but are prevented from releasing detailed geographical identifiers in public-use data sets due to disclosure concerns. Alternative data dissemination methods used in practice include releasing summary/aggregate tables, suppressing detailed geographic information in public-use data sets, and accessing restricted data via Research Data Centers. This research examines an alternative method for disseminating microdata that contains more geographical details than are currently being released in public-use data files. Specifically, the method replaces the observed survey values with imputed, or synthetic, values simulated from a hierarchical Bayesian model. Confidentiality protection is enhanced because no actual values are released. The method is demonstrated using restricted data from the 2005-2009 American Community Survey. The analytic validity of the synthetic data is assessed by comparing small area estimates obtained from the synthetic data with those obtained from the observed data.
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LEHD Data Documentation LEHD-OVERVIEW-S2008-rev1
December 2011
Working Paper Number:
CES-11-43
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Total Error and Variability Measures with Integrated Disclosure Limitation for Quarterly Workforce Indicators and LEHD Origin Destination Employment Statistics in On The Map
January 2017
Working Paper Number:
CES-17-71
We report results from the rst comprehensive total quality evaluation of five major indicators in the U.S. Census Bureau's Longitudinal Employer-Household Dynamics (LEHD) Program Quarterly Workforce Indicators (QWI): total employment, beginning-of-quarter employment, full-quarter employment, total payroll, and average monthly earnings of full-quarter employees. Beginning-of-quarter employment is also the main tabulation variable in the LEHD Origin-Destination Employment Statistics (LODES) workplace reports as displayed in OnTheMap (OTM). The evaluation is conducted by generating multiple threads of the edit and imputation models used in the LEHD Infrastructure File System. These threads conform to the Rubin (1987) multiple imputation model, with each thread or implicate being the output of formal probability models that address coverage, edit, and imputation errors. Design-based sampling variability and nite population corrections are also included in the evaluation. We derive special formulas for the Rubin total variability and its components that are consistent with the disclosure avoidance system used for QWI and LODES/OTM workplace reports. These formulas allow us to publish the complete set of detailed total quality measures for QWI and LODES. The analysis reveals that the five publication variables under study are estimated very accurately for tabulations involving at least 10 jobs. Tabulations involving three to nine jobs have quality in the range generally deemed acceptable. Tabulations involving zero, one or two jobs, which are generally suppressed in the QWI and synthesized in LODES, have substantial total variability but their publication in LODES allows the formation of larger custom aggregations, which will in general have the accuracy estimated for tabulations in the QWI based on a similar number of workers.
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LEHD Infrastructure Files in the Census RDC: Overview of S2004 Snapshot
April 2011
Working Paper Number:
CES-11-13
The Longitudinal Employer-Household Dynamics (LEHD) Program at the U.S. Census Bureau, with the support of several national research agencies, has built a set of infrastructure files using administrative data provided by state agencies, enhanced with information from other administrative data sources, demographic and economic (business) surveys and censuses. The LEHD Infrastructure Files provide a detailed and comprehensive picture of workers, employers, and their interaction in the U.S. economy. This document describes the structure and content of the 2004 Snapshot of the LEHD Infrastructure files as they are made available in the Census Bureau's Research Data Center network.
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Releasing Earnings Distributions using Differential Privacy: Disclosure Avoidance System For Post Secondary Employment Outcomes (PSEO)
April 2019
Working Paper Number:
CES-19-13
The U.S. Census Bureau recently released data on earnings percentiles of graduates from post secondary institutions. This paper describes and evaluates the disclosure avoidance system developed for these statistics. We propose a differentially private algorithm for releasing these data based on standard differentially private building blocks, by constructing a histogram of earnings and the application of the Laplace mechanism to recover a differentially-private CDF of earnings. We demonstrate that our algorithm can release earnings distributions with low error, and our algorithm out-performs prior work based on the concept of smooth sensitivity from Nissim, Raskhodnikova and Smith (2007).
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School 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.
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EXPANDING THE ROLE OF SYNTHETIC DATA AT THE U.S. CENSUS BUREAU
February 2014
Working Paper Number:
CES-14-10
National Statistical offices (NSOs) create official statistics from data collected from survey respondents, government administrative records and other sources. The raw source data is usually considered to be confidential. In the case of the U.S. Census Bureau, confidentiality of survey and administrative records microdata is mandated by statute, and this mandate to protect confidentiality is often at odds with the needs of users to extract as much information from the data as possible. Traditional disclosure protection techniques result in official data products that do not fully utilize the information content of the underlying microdata. Typically, these products take the form of simple aggregate tabulations. In a few cases anonymized public- use micro samples are made available, but these face a growing risk of re-identification by the increasing amounts of information about individuals and firms available in the public domain. One approach for overcoming these risks is to release products based on synthetic data where values are simulated from statistical models designed to mimic the (joint) distributions of the underlying microdata. We discuss re- cent Census Bureau work to develop and deploy such products. We discuss the benefits and challenges involved with extending the scope of synthetic data products in official statistics.
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Distribution Preserving Statistical Disclosure Limitation
September 2006
Working Paper Number:
tp-2006-04
One approach to limiting disclosure risk in public-use microdata is to release multiply-imputed,
partially synthetic data sets. These are data on actual respondents, but with confidential data
replaced by multiply-imputed synthetic values. A mis-specified imputation model can invalidate
inferences because the distribution of synthetic data is completely determined by the model used
to generate them. We present two practical methods of generating synthetic values when the imputer
has only limited information about the true data generating process. One is applicable when
the true likelihood is known up to a monotone transformation. The second requires only limited
knowledge of the true likelihood, but nevertheless preserves the conditional distribution of the confidential
data, up to sampling error, on arbitrary subdomains. Our method maximizes data utility
and minimizes incremental disclosure risk up to posterior uncertainty in the imputation model and
sampling error in the estimated transformation. We validate the approach with a simulation and
application to a large linked employer-employee database.
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LOOKING BACK ON THREE YEARS OF USING THE SYNTHETIC LBD BETA
February 2014
Working Paper Number:
CES-14-11
Distributions of business data are typically much more skewed than those for household or individual data and public knowledge of the underlying units is greater. As a results, national statistical offices (NSOs) rarely release establishment or firm-level business microdata due to the risk to respondent confidentiality. One potential approach for overcoming these risks is to release synthetic data where the establishment data are simulated from statistical models designed to mimic the distributions of the real underlying microdata. The US Census Bureau's Center for Economic Studies in collaboration with Duke University, the National Institute of Statistical Sciences, and Cornell University made available a synthetic public use file for the Longitudinal Business Database (LBD) comprising more than 20 million records for all business establishment with paid employees dating back to 1976. The resulting product, dubbed the SynLBD, was released in 2010 and is the first-ever comprehensive business microdata set publicly released in the United States including data on establishments employment and payroll, birth and death years, and industrial classification. This pa- per documents the scope of projects that have requested and used the SynLBD.
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