Papers Containing Tag(s): 'Census Bureau Disclosure Review Board'
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Authors
John Voorheis - 21
Lucia Foster - 20
John Haltiwanger - 16
John M. Abowd - 14
Nathan Goldschlag - 12
Viewing papers 291 through 297 of 297
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Working PaperWHY IMMIGRANTS LEAVE NEW DESTINATIONS AND WHERE DO THEY GO?
June 2013
Working Paper Number:
CES-13-32
Immigrants have a markedly higher likelihood of migrating internally if they live in new estinations. This paper looks at why that pattern occurs and at how immigrants' out-migration to new versus traditional destinations responds to their labor market economic and industrial structure, nativity origins and concentration, geographic region, and 1995 labor market type. Confidential data from the 2000 and 1990 decennial censuses are used for the analysis. Metropolitan and non-metropolitan areas are categorized into 741 local labor markets and classified as new or traditional based on their nativity concentrations of immigrants from the largest Asian, Caribbean and Latin American origins. The analysis showed that immigrants were less likely to migrate to new destinations if they lived in areas of higher nativity concentration, foreign-born population growth, and wages but more likely to make that move if they were professionals, agricultural or blue collar workers, highly educated, fluent in English, and lived in other new destinations. While most immigrants are more likely to migrate to new rather than traditional destinations that outcome differs sharply for immigrants from different origins and for some immigrants, particularly those from the Caribbean, the dispersal process to new destinations has barely started.View Full Paper PDF
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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 PaperResolving the Tension Between Access and Confidentiality: Past Experience and Future Plans at the U.S. Census Bureau
September 2009
Working Paper Number:
CES-09-33
This paper provides an historical context for access to U.S. Federal statistical data with a primary focus on the U.S. Census Bureau. We review the various modes used by the Census Bureau to make data available to users, and highlight the costs and benefits associated with each. We highlight some of the specific improvements underway or under consideration at the Census Bureau to better serve its data users, as well as discuss the broad strategies employed by statistical agencies to respond to the challenges of data access.View Full Paper PDF
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Working PaperDiscretionary Disclosure in Financial Reporting: An Examination Comparing Internal Firm Data to Externally Reported Segment Data
September 2009
Working Paper Number:
CES-09-28
We use confidential, U.S. Census Bureau, plant-level data to investigate aggregation in external reporting. We compare firms' plant-level data to their published segment reports, conducting our tests by grouping a firm's plants that share the same four-digit SIC code into a 'pseudo-segment.' We then determine whether that pseudo-segment is disclosed as an external segment, or whether it is subsumed into a different business unit for external reporting purposes. We find pseudo-segments are more likely to be aggregated within a line-of-business segment when the agency and proprietary costs of separately reporting the pseudo-segment are higher and when firm and pseudo-segment characteristics allow for more discretion in the application of segment reporting rules. For firms reporting multiple external segments, aggregation of pseudo-segments is driven by both agency and proprietary costs. However, for firms reporting a single external segment, we find no evidence of an agency cost motive for aggregation.View Full Paper PDF
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Working PaperConsistent 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.View Full Paper PDF
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Working PaperAccess Methods for United States Microdata
August 2007
Working Paper Number:
CES-07-25
Beyond the traditional methods of tabulations and public-use microdata samples, statistical agencies have developed four key alternatives for providing non-government researchers with access to confidential microdata to improve statistical modeling. The first, licensing, allows qualified researchers access to confidential microdata at their own facilities, provided certain security requirements are met. The second, statistical data enclaves, offer qualified researchers restricted access to confidential economic and demographic data at specific agency-controlled locations. Third, statistical agencies can offer remote access, through a computer interface, to the confidential data under automated or manual controls. Fourth, synthetic data developed from the original data but retaining the correlations in the original data have the potential for allowing a wide range of analyses.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
