presentation - VirtualRDC @ Cornell - Cornell University

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Core problem ■ Disclosure proofing is required to protect the information about individuals and businesses that contribute to ✦ (confidential) unemployment insurance (UI) wage records ✦ (confidential) Quarterly Census of Employment and Wages (QCEW, also known as ES-202) reports ✦ as well as information from Census Bureau demographic data that have been integrated with these sources. ■ Primary concern of the confidentiality protection mechanism is thus with small cells, i.e., cells that reflect data on few individuals or few firms. August 10, 2005 - p. 3/31
Protection provided ■ In general, data are considered protected when aggregate cell values do not closely approximate data for any one respondent in the cell (Cox and Zayatz, 1993, pg. 5) ■ In the QWI confidentiality protection scheme, confidential micro-data are considered protected by noise infusion if 1. any inference regarding the magnitude of a particular respondent’s data differs from the confidential quantity by at least c% even if that inference is made by a coalition of respondents with exact knowledge of their own answers or 2. any inference regarding the magnitude of an item is incorrect with probability no less than y%, where c and y are confidential but generally large August 10, 2005 - p. 4/31
Page 1 and 2: GoBack
Page 3: Introduction ■ We will describe t
Page 7 and 8: Three-layer confidentiality protect
Page 9 and 10: Three-layer confidentiality protect
Page 11 and 12: Distribution of Fuzz Factors 0 0 2
Page 13 and 14: Distorting ratios Ratios are distor
Page 15 and 16: Item suppression ■ Some disclosur
Page 17 and 18: Protection by Weighting ■ QCEW 1,
Page 19 and 20: Protection Table 1: Small Cells: B,
Page 21 and 22: Protection Table 3: Small Cells: B,
Page 23 and 24: Distribution of the Error in the Fi
Page 29 and 30: Cross-sectional unbiasedness: B Fra
Page 31 and 32: Conclusion ■ First large-scale im

presentation - VirtualRDC @ Cornell - Cornell University

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