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Measuring Labor Earnings Inequality Using Public-Use March Current Population Survey Data: The Value of Including Variances and Cell Means When Imputing Topcoded Values
November 2008
Working Paper Number:
CES-08-38
Using the Census Bureau's internal March Current Population Surveys (CPS) file, we construct and make available variances and cell means for all topcoded income values in the publicuse version of these data. We then provide a procedure that allows researchers with access only to the public-use March CPS data to take advantage of this added information when imputing its topcoded income values. As an example of its value we show how our new procedure improves on existing imputation methods in the labor earnings inequality literature.
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An Analysis of Key Differences in Micro Data: Results from the Business List Comparison Project
September 2008
Working Paper Number:
CES-08-28
The Bureau of Labor Statistics and the Bureau of the Census each maintain a business register, a universe of all U.S. business establishments and their characteristics, created from independent sources. Both registers serve critical functions such as supplying aggregate data inputs for certain national statistics generated by the Bureau of Economic Analysis. This paper examines key micro-level differences across these two business registers.
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Health-Related Research Using Confidential U.S. Census Bureau Data
August 2008
Working Paper Number:
CES-08-21
Economic studies on health-related issues have the potential to benefit all Americans. The approaches for dealing with the growth of health care costs and health insurance coverage are ever changing and information is needed on their efficacy. Research on health-related topics has been conducted for about a decade at the Census Bureau\u2019s Center for Economic Studies and the Research Data Centers. This paper begins by describing the confidential business and demographic Census Bureau data products used in this research. The discussion continues with summaries of nearly 30 papers, including how this work has benefited the Census Bureau and its research findings. Some focus on data linkages and assessing data quality, while others address important questions in the employer, public, and individual insurance markets. This research could not have been accomplished with public-use data. The newly available data from the Agency for Healthcare Research and Quality and National Center for Health Statistics, as well as additional Census Bureau data now available in the Research Data Centers are also discussed.
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Using Internal Current Population Survey Data to Reevaluate Trends in Labor Earnings Gaps by Gender, Race, and Education Level
July 2008
Working Paper Number:
CES-08-18
Most empirical studies of trends in labor earnings gaps by gender, race or education level are based on data from the public use March Current Population Survey (CPS). Using the internal March CPS, we show that inconsistent topcoding in the public use data will understate these gaps and inaccurately capture their trends. We create a cell mean series beginning in 1975 that provides the mean of all values above the topcode for each income source in the public use March CPS and better approximate earnings gaps found in the internal March CPS than was previously possible using publically available data.
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Consistent Cell Means for Topcoded Incomes in the Public Use March CPS (1976-2007)
March 2008
Working Paper Number:
CES-08-06
Using the internal March CPS, we create and in this paper distribute to the larger research community a cell mean series that provides the mean of all income values above the topcode for any income source of any individual in the public use March CPS that has been topcoded since 1976. We also describe our construction of this series. When we use this series together with the public use March CPS, we closely match the yearly mean income levels and income inequalities of the U.S. population found using the internal March CPS data.
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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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Using linked employer-employee data to investigate the speed of adjustments in downsizing firms
May 2006
Working Paper Number:
tp-2006-03
When firms are faced with a demand shock, adjustment can take many forms. Firms can adjust
physical capital, human capital, or both. The speed of adjustment may differ as well: costs of
adjustment, the type of shock, the legal and economic enviroment all matter. In this paper, we
focus on firms that downsized between 1992 and 1997, but ultimately survive, and investigate how
the human capital distribution within a firm influences the speed of adjustment, ceteris paribus. In
other words, when do firms use mass layoffs instead of attrition to adjust the level of employment.
We combine worker-level wage records and measures of human capital with firm-level characteristics
of the production function, and use levels and changes in these variables to characterize
the choice of adjustment method and speed. Firms are described/compared up to 9 years prior to
death. We also consider how workers fare after leaving downsizing firms, and analyze if observed
differences in post-separation outcomes of workers provide clues to the choice of adjustment speed.
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Confidentiality Protection in the Census Bureau Quarterly Workforce Indicators
February 2006
Working Paper Number:
tp-2006-02
The QuarterlyWorkforce Indicators are new estimates developed by the Census Bureau's Longitudinal
Employer-Household Dynamics Program as a part of its Local Employment Dynamics
partnership with 37 state Labor Market Information offices. These data provide detailed quarterly
statistics on employment, accessions, layoffs, hires, separations, full-quarter employment
(and related flows), job creations, job destructions, and earnings (for flow and stock categories of
workers). The data are released for NAICS industries (and 4-digit SICs) at the county, workforce
investment board, and metropolitan area levels of geography. The confidential microdata - unemployment
insurance wage records, ES-202 establishment employment, and Title 13 demographic
and economic information - are protected using a permanent multiplicative noise distortion factor.
This factor distorts all input sums, counts, differences and ratios. The released statistics are analytically
valid - measures are unbiased and time series properties are preserved. The confidentiality
protection is manifested in the release of some statistics that are flagged as "significantly distorted
to preserve confidentiality." These statistics differ from the undistorted statistics by a significant
proportion. Even for the significantly distorted statistics, the data remain analytically valid for
time series properties. The released data can be aggregated; however, published aggregates are
less distorted than custom postrelease aggregates. In addition to the multiplicative noise distortion,
confidentiality protection is provided by the estimation process for the QWIs, which multiply imputes
all missing data (including missing establishment, given UI account, in the UI wage record
data) and dynamically re-weights the establishment data to provide state-level comparability with
the BLS's Quarterly Census of Employment and Wages.
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Using Census Business Data to Augment the MEPS-IC
December 2005
Working Paper Number:
CES-05-26
This paper has two aims: first to describe methods, issues, and outcomes involved in matching data from the Insurance Component of the Medical Expenditure Panel Survey (MEPSIC) to other business microdata collected by the U.S. Census Bureau, and second to present some simple results that illustrate the usefulness of such combined data. We present the results of linking the MEPS-IC with data from the 1997 Economic Censuses (EC), but also discuss other possible sources of business data. An issue in any linkage is whether the linked sample remains representative and large enough to be useful. The EC data are attractive because, given the survey's broad coverage and large sample, most of the MEPS-IC sample can be matched to it. We use the combined EC/MEPS-IC data to construct productivity measures that are useful auxiliary data in examining employers' health insurance offering decisions.
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Networking Off Madison Avenue
October 2005
Working Paper Number:
CES-05-15
This paper examines the effect on productivity of having more near advertising agency neighbors and hence better opportunities for meetings and exchange within Manhattan. We will show that there is extremely rapid spatial decay in the benefits of having more near neighbors even in the close quarters of southern Manhattan, a finding that is new to the empirical literature and indicates our understanding of scale externalities is still very limited. The finding indicates that having a high density of commercial establishments is important in enhancing local productivity, an issue in Lucas and Rossi-Hansberg (2002), where within business district spatial decay of spillovers plays a key role. We will argue also that in Manhattan advertising agencies trade-off the higher rent costs of being in bigger clusters nearer 'centers of action', against the lower rent costs of operating on the 'fringes' away from high concentrations of other agencies. Introducing the idea of trade-offs immediately suggests heterogeneity is involved. We will show that higher quality agencies are the ones willing to pay more rent to locate in greater size clusters, specifically because they benefit more from networking. While all this is an exploration of neighborhood and networking externalities, the findings relate to the economic anatomy of large metro areas like New Yorkthe nature of their buzz.
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