ESSNET on Statistical Disclosure Control Daniela Ichim ESSNET

  • Slides: 15
Download presentation
ESSNET on Statistical Disclosure Control Daniela Ichim ESSNET Data Integration - Rome, January 2010

ESSNET on Statistical Disclosure Control Daniela Ichim ESSNET Data Integration - Rome, January 2010

Outline 1. ESSNET SDC 2. Record linkage and SDC 3. Statistical matching and SDC

Outline 1. ESSNET SDC 2. Record linkage and SDC 3. Statistical matching and SDC ESSNET Data Integration - Rome, January 2010

ESSNET SDC • Pilot ESSnet, 2008 -2009 • 12 Participants: CBS (coordinator), Istat, Destatis,

ESSNET SDC • Pilot ESSnet, 2008 -2009 • 12 Participants: CBS (coordinator), Istat, Destatis, ONS, Statistics Sweeden, Statistics Austria, Statistics Norway, Portugal INE, …. • 3 sub-contractors: University Rovira I Virgili , University of Naples, IAB Germany • Web-site: http: //neon. vb. cbs. nl/casc/ ESSNET Data Integration - Rome, January 2010

Before ESSNET SDC • 4 rd Framework SDC-project (1996 -1998) • 5 th Framework

Before ESSNET SDC • 4 rd Framework SDC-project (1996 -1998) • 5 th Framework CASC project (2000 -2003) • CENEX project (2006) Aim: enhance the development in the field of statistical confidentiality 1. methodological 2. software 3. practice, … ESSNET Data Integration - Rome, January 2010

Before ESSNET SDC Outputs: 1. Argus software 2. Handbook on SDC 3. Conferences (PSD)

Before ESSNET SDC Outputs: 1. Argus software 2. Handbook on SDC 3. Conferences (PSD) 4. Methodological papers • web-site • International journals ESSNET Data Integration - Rome, January 2010

ESSNET SDC Main goal: raise the level of knowledge and skills to a higher

ESSNET SDC Main goal: raise the level of knowledge and skills to a higher level 1. 2. 3. 4. promotion of the results achieved so far make SDC tools more easily applicable Involvement of “new” NSIs Coordination at ESS level Main outputs: 1. Improved versions of Argus/handbook 2. Dissemination Training courses Reports and case studies ESSNET Data Integration - Rome, January 2010

Record linkage and SDC Link: MICRODATA SDC: I. measure the disclosure risk II. release

Record linkage and SDC Link: MICRODATA SDC: I. measure the disclosure risk II. release of microdata files (PUF, MFR) ESSNET Data Integration - Rome, January 2010

I. Standard disclosure scenario Assumptions: 1. The intruder has access to an external register

I. Standard disclosure scenario Assumptions: 1. The intruder has access to an external register (E) 2. E covers the whole population 3. E and D share a set of (key) variables, measured without error 4. The intruder uses record linkage to match a unit in the sample to one in the population using only the key variables 5. … Risk Measures: 1. Number of “linked” units 2. Probability of correct identification = Probability of correct linkage ESSNET Data Integration - Rome, January 2010

I. RL used in SDC 1. Distance-based RL (Domingo-Ferrer) – linking each record d

I. RL used in SDC 1. Distance-based RL (Domingo-Ferrer) – linking each record d in file D to its nearest record e in file E – Mainly for continuous variables (business data) 2. Probabilistic RL (Skinner) – Classical framework – Mainly for categorical variables (social data) ESSNET Data Integration - Rome, January 2010

I. RL and Risk QUALITY 1. External register – – – Coverage Misclassification errors

I. RL and Risk QUALITY 1. External register – – – Coverage Misclassification errors Which variables? Which registers? . . . 2. Disseminated microdata file – – Misclassification errors (known pattern, known protection parameters, etc. ) Usage (in RL) of the publicly available information: a) b) c) d) Sampling design (stratification, survey weights) Known population characteristics (M/F) Hierarchical file structure (HH, enterprise-local unit) Ideal (worst) case: true whole population – a (unique) correct link exists …. ESSNET Data Integration - Rome, January 2010

II. RL and Release Integrate THEN Disseminate Grant access to composite microdata covering a

II. RL and Release Integrate THEN Disseminate Grant access to composite microdata covering a wider range of variables – More careful management of the risks of disclosure (+ the previous slide + the increased confidentiality/sensitivity of integrated data sets) – Impact on analyses ESSNET Data Integration - Rome, January 2010

Statistical Matching and SDC (Y, X) (X, Z) X ESSNET Data Integration - Rome,

Statistical Matching and SDC (Y, X) (X, Z) X ESSNET Data Integration - Rome, January 2010 (Y, X, Z)

Statistical Matching and SDC B b 1 A C b 2 c 1 c

Statistical Matching and SDC B b 1 A C b 2 c 1 c 2 c 3 a 1 a 2 b. 1 Frechèt Bounds b. 2 1 A A a 1 a 1 a 1 a 2 1 B B b 1 b 1 b 1 b 2 b 2 b 2 b 1 c. 2 C C c 1 c 2 c 3 c 1 … … … … ? ? ? ? … … … … a 2 b 1 c 3 … ? … a 2 b 2 c 1 … ? … a 2 b 2 c 2 … ? … a 2 b 2 c 3 … ? … … ? UB b 1 c 2 LB a 2 ESSNET Data Integration - Rome, January 2010 b 1 c. 1 … c. 3

Statistical Matching and Release How to use a released microdata file in a statistical

Statistical Matching and Release How to use a released microdata file in a statistical matching procedure? Issues: 1. Use protection/perturbation information to improve the statistical matching performance 2. Impact on statistical analyses. ESSNET Data Integration - Rome, January 2010

Conclusions 1. Change (improve/adapt) the DI process to account for microdata files with (some)

Conclusions 1. Change (improve/adapt) the DI process to account for microdata files with (some) known properties 2. Change (improve/adapt) the SDC process to account for the latest methodological and technological DI developments 3. PRACTICE Step-by-step approach!!! ESSNET Data Integration - Rome, January 2010

DISCLOSURE DISCLOSURE DISCLOSURE TIME IS MYOCARDIUM TIME ISDISCLOSURE DISCLOSURE DISCLOSURE TIME IS MYOCARDIUM TIME IS
ESSnet CORE Common Reference Environment ESSnet workshop inESSnet CORE Common Reference Environment ESSnet workshop in
Eurostat ESSnet facilitation team ESSnet Workshop 3 4Eurostat ESSnet facilitation team ESSnet Workshop 3 4
ESSnet workshop Cologne 27 28 October ESSnet ProjectsESSnet workshop Cologne 27 28 October ESSnet Projects
ESSnet DCSS ESSnet on Data Collection for SocialESSnet DCSS ESSnet on Data Collection for Social
ESSnet DCSS ESSnet on Data Collection for SocialESSnet DCSS ESSnet on Data Collection for Social
ESSnet on Data Warehousing Overall handbook SDWH ESSnetESSnet on Data Warehousing Overall handbook SDWH ESSnet
Control Charts Statistical Process Control Statistical process controlControl Charts Statistical Process Control Statistical process control
Statistical Disclosure Limitation Releasing Useful Data for StatisticalStatistical Disclosure Limitation Releasing Useful Data for Statistical
Statistical Disclosure Limitation Releasing Useful Data for StatisticalStatistical Disclosure Limitation Releasing Useful Data for Statistical
Statistical Control Regression research designs Statistical Control isStatistical Control Regression research designs Statistical Control is
Statistical Process Control What is Statistical Process ControlStatistical Process Control What is Statistical Process Control
Software Tools for Statistical Disclosure Control by ComplementarySoftware Tools for Statistical Disclosure Control by Complementary
WP 19 Assessment of Statistical Disclosure Control MethodsWP 19 Assessment of Statistical Disclosure Control Methods