presentation - VirtualRDC @ Cornell - Cornell University

More documents

Recommendations

Info

Quality of the disclosed data ■ The confidentiality-protected data must be inference-valid for a well-defined set of analyses ■ We show that ✦ the theoretical properties of the disclosure-proofing mechanism are designed to maintain analytical validity for trend analysis; ✦ in practice, the disclosure-proofed data are not biased; ✦ in practice, the time-series properties of the disclosure-proofed data remain intact. August 10, 2005 - p. 5/31
Three-layer confidentiality protection in QWI (I) ■ Layer 1: Multiplicative noise-infusion at the establishment level, with three very important properties 1. every establishment-level data item is distorted by some minimum amount 2. distortion amount and direction are time-invariant: data are always distorted in the same direction (increased or decreased) by the same percentage amount in every period. 3. when estimates are aggregated, the effects of the distortion cancel out for the vast majority of the estimates August 10, 2005 - p. 6/31
Page 1 and 2: GoBack
Page 3 and 4: Introduction ■ We will describe t
Page 5: Protection provided ■ In general,
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

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?