Papers written by Author(s): 'Bryce Stephens'
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Viewing papers 1 through 5 of 5
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Working PaperDynamically Consistent Noise Infusion and Partially Synthetic Data as Confidentiality Protection Measures for Related Time Series
July 2012
Working Paper Number:
CES-12-13
The Census Bureau's Quarterly Workforce Indicators (QWI) provide detailed quarterly statistics on employment measures such as worker and job flows, tabulated by worker characteristics in various combinations. The data are released for several levels of NAICS industries and geography, the lowest aggregation of the latter being counties. Disclosure avoidance methods are required to protect the information about individuals and businesses that contribute to the underlying data. The QWI disclosure avoidance mechanism we describe here relies heavily on the use of noise infusion through a permanent multiplicative noise distortion factor, used for magnitudes, counts, differences and ratios. There is minimal suppression and no complementary suppressions. To our knowledge, the release in 2003 of the QWI was the first large-scale use of noise infusion in any official statistical product. We show that the released statistics are analytically valid along several critical dimensions { measures are unbiased and time series properties are preserved. We provide an analysis of the degree to which confidentiality is protected. Furthermore, we show how the judicious use of synthetic data, injected into the tabulation process, can completely eliminate suppressions, maintain analytical validity, and increase the protection of the underlying confidential data.View Full Paper PDF
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Working PaperConfidentiality 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.View Full Paper PDF
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Working PaperThe LEHD Infrastructure Files and the Creation of the Quarterly Workforce Indicators
January 2006
Working Paper Number:
tp-2006-01
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. Beginning in 2003 and building on this infrastructure, the Census Bureau has published the Quarterly Workforce Indicators (QWI), a new collection of data series that offers unprecedented detail on the local dynamics of labor markets. Despite the fine detail, confidentiality is maintained due to the application of state-of-the-art confidentiality protection methods. This article describes how the input files are compiled and combined to create the infrastructure files. We describe the multiple imputation methods used to impute in missing data and the statistical matching techniques used to combine and edit data when a direct identifier match requires improvement. Both of these innovations are crucial to the success of the final product. Finally, we pay special attention to the details of the confidentiality protection system used to protect the identity and micro data values of the underlying entities used to form the published estimates. We provide a brief description of public-use and restricted-access data files with pointers to further documentation for researchers interested in using these data.View Full Paper PDF
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Working PaperWage Dispersion, Compensation Policy and the Role of Firms
November 2005
Working Paper Number:
tp-2005-04
Empirical work in economics stresses the importance of unobserved firm- and person-level characteristics in the determination of wages, finding that these unobserved components account for the overwhelming majority of variation in wages. However, little is known about the mechanisms sustaining these wage di'er- entials. This paper attempts to demystify the firm-side of the puzzle by developing a statistical model that enriches the role that firms play in wage determination, allowing firms to influence both average wages as well as the returns to observable worker characteristics. I exploit the hierarchical nature of a unique employer-employee linked dataset for the United States, estimating a multilevel statistical model of earnings that accounts for firm-specific deviations in average wages as well as the returns to components of human capital - race, gender, education, and experience - while also controlling for person-level heterogeneity in earnings. These idiosyncratic prices reflect one aspect of firm compensation policy; another, and more novel aspect, is the unstructured characterization of the covariance of these prices across firms. I estimate the model's variance parameters using Restricted (or Residual) Maximum Likelihood tech- niques. Results suggest that there is significant variation in the returns to worker characteristics across firms. First, estimates of the parameters of the covariance matrix of firm-specific returns are statistically significant. Firms that tend to pay higher average wages also tend to pay higher than average returns to worker characteristics; firms that tend to reward highly the human capital of men also highly reward the human capital of women. For instance, the correlation between the firm-specific returns to education for men and women is 0.57. Second, the firm-specific returns account for roughly 9% of the variation in wages - approximately 50% of the variation in wages explained by firm-specific intercepts alone. The inclusion of firm-specific returns ties variation in wages, otherwise attributable to firm-specific intercepts, to observable components of human capital.View Full Paper PDF
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Working PaperThe LEHD Infrastructure Files and the Creation of the Quarterly Workforce Indicators
March 2002
Working Paper Number:
tp-2002-05