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Quality Indicators for Statistical Disclosure Methods: A Case Study on the Structure of Earnings Survey Cover

Quality Indicators for Statistical Disclosure Methods: A Case Study on the Structure of Earnings Survey

By: Matthias Templ  
Open Access
|Dec 2015

References

  1. Alfons, A. and M. Templ. 2013. “Estimation of Social Exclusion Indicators from Complex Surveys: The R package laeken.” Journal of Statistical Software 54: 1–25.10.18637/jss.v054.i15
  2. Alfons, A., S. Kraft, M. Templ, and P. Filzmoser. 2011. “Simulation of Close-to-Reality Population Data for Household Surveys with Application to EU-SILC.” Statistical Methods & Applications 20: 383–407. doi:10.1007/s10260-011-0163-2.10.1007/s10260-011-0163-2
  3. Alfons, A., M. Templ, and P. Filzmoser. 2013. “Robust Estimation of Economic Indicators from Survey Samples Based on Pareto Tail Modeling.” Journal of the Royal Statistical Society Series C 62: 271–286.10.1111/j.1467-9876.2012.01063.x
  4. Beblot, M., D. Beniger, A. Heinze, and F. Laisney. 2003. Methodological Issues Related to the Analysis of Gender Gaps in Employment, Earnings and Career Progression. Final Project Report, European Commission Employment and Social Affairs DG.
  5. Belfield, R. 1999. Pay Inequalities and Economic Performance: A Review of the UK Literature. Technical Report PiEP Report, Centre for Economic Performance, London School of Economics.
  6. Bowles, S., H. Gintis, and M. Osborne. 2001. “The Determinants of Earnings: a Behavioral Approach.” Journal of Economic Literature 39: 1137–1176.10.1257/jel.39.4.1137
  7. Brand, R. 2004. “Microdata Protection through Noise Addition.” In Privacy in Statistical Databases. Lecture Notes in Computer Science, edited by J. Domingo-Ferrer. 347–359. New York: Springer.
  8. Bruch, C., R. Münnich, and S. Zins. 2011. Variance Estimation For Complex Surveys. Research Project Report WP3–D3.1, FP7-SSH-2007-217322 AMELI. Available at: http://ameli.surveystatistics.net (accessed December 2013)
  9. Caju, P., C. Fuss, and L. Wintr. 2009a. “Understanding Sectoral Differences in Downward Real Wage Rigidity: Workforce Composition, Institutions, Technology and Competition.” Working Paper Series no. 1006, European Central Bank. Available at: http://www.ecb.int/pub/pdf/scpwps/ecbwp1006.pdf (accessed December 2013)
  10. Caju, P., F. Rycx, and I. Tojerow. 2009b. “Inter-industry Wage Differentials: How Much Does Rent Sharing Matter?” Journal of the European Economic Association 79: 691–717.10.1111/j.1467-9957.2010.02173.x
  11. Caju, P., F. Rycx, and I. Tojerow. 2010. “Wage Structure Effects of International Trade: Evidence From a Small Open Economy.” Working Paper Series no. 1325, European Central Bank. Available at: http://www.ecb.int/pub/pdf/scpwps/ecbwp1325.pdf (accessed December 2013)
  12. Carlson, M. 2002. “Assessing Microdata Disclosure Risk Using the Poisson-inverse Gaussian Distribution.” Statistics in Transition 5: 901–925.
  13. Casali, S. and V. Alvarez. 2010. 17% of Full-time Employees In the EU Are Low-wage Earners. Statistics in focus. Research Report. KS-SF-10-003-EN-N, Eurostat/European Commission. Available at: http://epp.eurostat.ec.europa.eu/cache/ITY_OFFPUB/KS-SF-10-003/EN/KS-SF-10-003-EN.PDF (accessed December 2013)
  14. Dell’Aringa, C., P. Ghinetti, and C. Lucifora. 2000. “Pay Inequality and Economic Performance in Italy: a Review of the Applied Literature.” In Proceedings of the LSE conference, November 3–4, 2000. 1–28. London.
  15. Deville, J.-C. and C.-E. Särndal. 1992. “Calibration Estimators in Survey Sampling.” Journal of the American Statistical Association 87: 376–382.10.1080/01621459.1992.10475217
  16. Deville, J.-C., C.-E. Särndal, and O. Sautory. 1993. “Generalized Raking Procedures in Survey Sampling.” Journal of the American Statistical Association 88: 1013–1020.10.1080/01621459.1993.10476369
  17. Domingo-Ferrer, J. and V. Torra. 2001. “A Quantitative Comparison of Disclosure Control Methods for Microdata.” Confidentiality, Disclosure and Data Access: Theory and Practical Applications for Statistical Agencies, edited by P. Doyle, J. Lane, J. Theeuwes, and L. Zayatz. 111–134, Eurostat.
  18. Domingo-Ferrer, J., J.M. Mateo-Sanz, and T. Torra. 2001. “Comparing sdc Methods for Microdata on the Basis of Information Loss and Disclosure.” Proceedings of ETKNTTS 2001: Eurostat, Luxembourg June 18–20, 2001. 807–826. Luxembourg: Eurostat.
  19. Dupray, D., H. Nohara, and P. Béret. 1999. Pay Inequality and Economic Performance: a Review of the French Literature. Technical Report PiEP Report, Centre for Economic Performance, London School of Economics
  20. Dupré, D. 2010. “The Unadjusted Gender Pay Gap in the European Union.” In Joint UNECE/Eurostat Work Session on Gender Statistics, Geneva April 14–16, 2010. Available at: http://www.unece.org/fileadmin/DAM/stats/documents/ece/ces/ge.30/2010/1.e.pdf (accessed November 2015)
  21. Dybczak, K., and K. Galuscak. 2010. “Changes in the Czech Wage Structure: Does Immigration Matter?” Working Paper Series no. 1242, European Central Bank. Available at: http://www.ecb.int/pub/pdf/scpwps/ecbwp1242.pdf (accessed December 2013)10.2139/ssrn.1671612
  22. Edwards, C. 2010. “Public Sector Unions and the Rising Costs of Employee Compensation,” Cato Journal 30: 87–115.
  23. Efron, B. and R.J. Tibshirani. 1993. An Introduction to the Bootstrap. New York: Chapman & Hall.10.1007/978-1-4899-4541-9
  24. EU-SILC. 2004. Common Cross-sectional EU Indicators Based on EU-SILC: the Gender Pay Gap. EU-SILC 131-rev/04, Working Group on Statistics on Income and Living Conditions (EU-SILC). Luxembourg: Eurostat.
  25. EU-SILC. 2009. Algorithms to Compute Social Inclusion Indicators Based On EU-SILC and Adopted under the Open Method of Coordination (OMC). EU-SILC LCILC/39/09/ENrev.1, Directorate F: Social and Information Society Statistics Unit F-3: Living Conditions and Social Protection, European Commission. Luxembourg: Eurostat.
  26. Fitzenberger, B., K. Kohn, and A. Lembcke. 2006. Union Wage Effects in Germany: Union Density Or Collective Bargaining Coverage? Research Report FSP 1169, DFG research programme, The London School of Economics and Political Sciences, London.
  27. Franconi, L. and S. Polettini. 2004. “Individual Risk Estimation in μ-Argus: a Review.” In Privacy in Statistical Databases: Lecture Notes in Computer Science, edited by J. Domingo-Ferrer. 262–272. New York: Springer.10.1007/978-3-540-25955-8_20
  28. Franconi, L., D. Ichim, and M. Templ. 2011. First Steps to Define a Framework For Comparable Dissemination of the European Structure of Earning Survey. Deliverable d1.1-a. Task 1: Harmonisation of Microdata Release in Multiple Countries. Essnet Project on Common Tools and Harmonised Methodologies for SDC in the ESS. Available at: http://neon.vb.cbs.nl/casc/..%5Ccas%5CESSNet2%5Cdeliverable%201%20full%20august2012.pdf (accessed November 2015)
  29. Frick, B., and K. Winkelmann. 1999. Pay Inequalities and Economic Performance: A Review in Literature, Technical Report Research Report HPSE-CT-1999-00040, Ernst-Moritz-Arndt-Universität Greifswald.
  30. Geissberger, T. 2009. Verdienststrukturerhebung 2006, Struktur und Verteilung der Verdienste in Oösterreich. Vienna: Statistik Austria.
  31. Geissberger, T. 2010. Frauenbericht. Teil 4: Sozioökonomische Studien, Technical Report 4, Federal Ministry for Women and the Civil Service of Austria.
  32. Geissberger, T. and K. Knittler. 2010. “Niedriglöhne und Atypische Beschäftigung in Österreich.” Statistische Nachrichten 6: 448–461.
  33. Gini, C. 2012. “Variabilità e Mutabilità: Contributo Allo Studio delle Distribuzioni e delle Relazioni Statistiche.” Studi Economico-Giuridici della R. Università di Cagliari 3: 3–159.
  34. Gomatam, S. and A. Karr. 2003. Distortion Measures for Categorical Data Swapping. Report no. 131, National Institute of Statistical Sciences (NISS).
  35. Gouweleeuw, J., P. Kooiman, L. Willenborg, and P-P. De Wolf. 1998. “Post Randomisation for Statistical Disclosure Control: Theory and Implementation.” Journal of Official Statistics 14; 463–478.
  36. Graf, M., A. Alfons, C. Bruch, P. Filzmoser, B. Hulliger, R. Lehtonen, B. Meindl, R. Münnich, T. Schoch, M. Templ, M. Valaste, A. Wenger, and S. Zins. 2011. State-of-the-art of laeken Indicators. Research Project Report WP1–D1.1, FP7-SSH-2007-217322 AMELI. Available at: http://ameli.surveystatistics.net (accessed December 2013)
  37. Groshen, E. 1991. “The Structure of the Female/Male Wage Differential.” Journal of Human Resources 26: 455–472.
  38. Hundepool, A., J. Domingo-Ferrer, L. Franconi, S. Giessing, E. Schulte Nordholt, K. Spicer, and P.-P. de Wolf. 2012. Statistical Disclosure Control. New York: Wiley.10.1002/9781118348239
  39. Ichim, D. and L. Franconi. 2007. “Disclosure Scenario and Risk Assessment: Structure of Earnings Survey.” In Joint UNECE/Eurostat Work Session on Statistical Data Confidentiality, Manchester, December 17–19, 2007. Doi: 10.2901/Eurostat.C2007.004
  40. Ichim, D. and L. Franconi. 2010. “Strategies to Achieve sdc Harmonisation at European Level: Multiple Countries, Multiple Files, Multiple Surveys.” Privacy in Statistical Databases ‘10, edited by J. Domingo-Ferrer and E. Kajkos, Springer, New York. 284–296.
  41. Karr, A.F., C.N. Kohnen, A. Oganian, J.P. Reiter, and A.P. Sanil. 2006. “A Framework for Evaluating the Utility of Data Altered to Protect Confidentiality.” The American Statistician 60: 224–232. Doi: 10.1198/000313006X124640.10.1198/000313006X124640
  42. Kolb, J.-P., R. Münnich, S. Beil, A. Chatziparadeisis, and J. Seger. 2011. Policy Use of Indicators on Poverty and Social Exclusion. Research Project Report WP9–D9.1, FP7-SSH-2007-217322 AMELI, 2011. Available at: http://ameli.surveystatistics.net (accessed December 2013)
  43. Lorenz, M.O. 1905. “Methods of Measuring the Concentration of Wealth.” Publications of the American Statistical Association 9: 209–219.10.2307/2276207
  44. Manning, A.M., D.J. Haglin, and J.A. Keane. 2008. “A Recursive Search Algorithm For Statistical Disclosure Assessment.” Data Mining and Knowledge Discovery 16: 165–196. Doi: 10.1007/s10618-007-0078-6.10.1007/s10618-007-0078-6
  45. Marsden, D. 2010. Pay Inequalities and Economic Performance, Technical Report PiEP Final Report V4, Centre for Economic Performance, London School of Economics. London: London School of Economics. Available at: http://www.ist-world.org/ProjectDetails.aspx?ProjectID=fa5bb4adfff74d60aeca90b56441a601&SourceDatabaseID=9cd97ac2e51045e39c2ad6b86dcelac2.
  46. Messina, J., M. Izquierdo, P. Caju, C.F. Duarte, and N.L. Hanson. 2010. “The Incidence of Nominal and Real Wage Rigidity: an Individual-based Sectoral Approach.” Journal of the European Economic Association 8: 487–496.10.1111/j.1542-4774.2010.tb00519.x
  47. Mittag, J. 2005. Gross Earnings In Europe. Main Results of the Structure of Earnings Survey 2002. Statistics in Focus. Research Report. KS-NK-05-012-EN-N, European Communities. Available at: http://epp.eurostat.ec.europa.eu/cache/ITY_OFFPUB/KS-NK-05-012/EN/KS-NK-05-012-EN.PDF (accessed December 2013)
  48. Muralidhar, K. and R. Sarathy. 2006. “Data Shuffling – a New Masking Approach for Numerical Data.” Management Science 52: 658–670.10.1287/mnsc.1050.0503
  49. Nolan, B. and H. Russel. 2001. Pay Inequality and Economic Performance In Ireland: a Review of the Applied Literature. Technical Report PiEP Report, The Economic and Social Research Institute, Dublin.
  50. Oganian, A. and A.F. Karr. 2006. “Combinations of sdc Methods for Microdata Protection.” In Privacy in Statistical Databases, edited by J. Domingo-Ferrer and L. Franconi. 102–113. Berlin: Springer. Doi: 10.1007/11930242_10.10.1007/11930242_10
  51. Pointner, W., and A. Stiglbauer. 2010. “Changes In the Austrian Structure of Wages.” Working Paper Series no. 1268, European Central Bank. Available at: http://www.ecb.int/pub/pdf/scpwps/ecbwp1268.pdf (accessed December 2013)
  52. Reiter, J.P. 2012. “Statistical Approaches to Protecting Confidentiality For Microdata and their Effects on the Quality of Statistical Inferences.” Public Opinion Quarterly 76: 163–181. Doi: 10.1093/poq/nfr058.10.1093/poq/nfr058
  53. Research Center for Education and the Labour Market at Maastricht University. 2009. “Development of Econometric Methods to Evaluate the Gender Pay Gap Using Structure of Earnings Survey Data.” Research paper no. ks-ra-09-011-en-n, European Commission. Available at: http://www.ecb.int/pub/pdf/scpwps/ecbwp1006.pdf (accessed December 2013)
  54. Reuter, W. 2010. Establishing an Infrastructure for Remote Access to Microdata at Eurostat. Bachelor’s thesis., Vienna Univesity of Economics.10.1007/978-3-642-15838-4_22
  55. Reuter, W. and J-M. Museux 2010. “Establishing an Infrastructure for Remote Access to Microdata at Eurostat.” In Privacy in Statistical Databases: Lecture Notes in Computer Science, edited by J. Domingo-Ferrer. 249–257. New York: Springer.10.1007/978-3-642-15838-4_22
  56. Rinott, Y. 2003. “On Models for Statistical Disclosure Risk Estimation.” In Proceedings of the Joint ECE/Eurostat Work Session on Statistical Data Confidentiality. April 7–9, 2003. 275–285, United Nations Statistical Commission, Geneva.
  57. Shlomo, N. 2008. “Releasing Microdata: Disclosure Risk Estimation, Data Masking and Assessing Data Utility.” In Section on Survey Research Methods, JSM. August 3–7, 2008, Denver, Colorado, USA. 229–240. Available at: https://www.amstat.org/sections/srms/proceedings/y2008/Files/300242.pdf (accessed November 2015)
  58. Simón, H. 2010. “International Differences in Wage Inequality: A New Glance with European Matched Employer-Employee Data.” British Journal of Industrial Relations 48: 310–346.10.1111/j.1467-8543.2008.00708.x
  59. Stephan, G. and K. Gerlach. 2005. “Wage Settlements and Wage Settings: Evidence from a Multilevel Model.” Applied Economics 37: 2297–2306.10.1080/00036840500366429
  60. Stockinger, S. 2010. Frauenbericht 2010. Technical report, Federal Ministry for Women and the Civil Service of Austria. Vienna: Available at: http://www.bka.gv.at/site/6811/default.aspx (accessed December 2013)
  61. Sweeney, L. 2002. “k-Anonymity: a Model for Protecting Privacy.” International Journal on Uncertainty, Fuzziness and Knowledge-based Systems 10: 557–570.10.1142/S0218488502001648
  62. Templ, M. 2008. “Statistical Disclosure Control for Microdata Using the R-package sdcMicro.” Transactions on Data Privacy 1: 67–85.
  63. Templ, M. 2011a. Estimators and Model Predictions from the Structural Earnings Survey for Benchmarking Statistical Disclosure Methods. Research Report CS-2011-4, Department of Statistics and Probability Theory, Vienna University of Technology, Vienna, Austria.
  64. Templ, M. 2011b. “Comparison of Perturbation Methods Based on Pre-defined Quality Indicators.” In Joint UNECE/Eurostat work session on statistical data confidentiality, 26–28 October, 2011, Tarragona, Spain, 1–10. Unece, Geneva, Italy.
  65. Templ, M. and A. Alfons. 2011. Variance Estimation of Social Inclusion Indicators Using the R Package laeken. Research Report CS-2011-3, Department of Statistics and Probability Theory, Vienna University of Technology. Available at: http://www.statistik.tuwien.ac.at/forschung/CS/CS-2011-3complete.pdf (accessed December 2013)
  66. Templ, M. and P. Filzmoser. 2014. “Simulation and Quality of a Synthetic Close-to-Reality Employer-Employee Population.” Journal of Applied Statistics, 41: 1053–1072.10.1080/02664763.2013.859237
  67. Templ, M. and B. Meindl. 2010. “Practical Applications in Statistical Disclosure Control Using R.” In Privacy and Anonymity in Information Management Systems: Advanced Information and Knowledge Processing, edited by J. Nin and J. Herranz. 31–62. London: Springer.10.1007/978-1-84996-238-4_3
  68. Templ, M. A. Kowarik, and B. Meindl. 2015. “Statistical Disclosure Control for Micro-Data Using R Package sdcMicro.” Journal of Statistical Software. 67: 1–36.10.18637/jss.v067.i04
  69. Weinberg, D.H. 2007. “Earnings by Gender: Evidence from Census 2000.” Monthly Labor Review Online 130: 26–34.
  70. Winter-Ebmer, R. and J. Zweimüller. 1999. “Firm Size Wage Differentials in Switzerland: Evidence from Job Changers.” American Economic Review 89: 89–93.10.1257/aer.89.2.89
  71. Woo, M., J.P. Reiter, A. Oganian, and A.F. Karr. 2009. “Global Measures of Data Utility for Microdata Masked for Disclosure Limitation.” Journal of Privacy and Confidentiality 1: 111–124.10.29012/jpc.v1i1.568
Language: English
Page range: 737 - 761
Submitted on: Oct 1, 2012
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Accepted on: Jan 1, 2015
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Published on: Dec 16, 2015
Published by: Sciendo
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2015 Matthias Templ, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.