Case Studies

Matthias Templ ()
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Matthias Templ: Zurich University of Applied Sciences (ZHAW), Institute of Data Analysis and Process Design (IDP), School of Engineering (SoE)

Chapter Chapter 8 in Statistical Disclosure Control for Microdata, 2017, pp 187-260 from Springer

Abstract: Abstract In this section, we show how to apply the concepts and methods introduced in the previous chapters using sdcMicro. Anonymized data are produced for the Family Income and Expenditure Survey (FIES), the Structural Earnings Survey (SES), International Income Distribution Database (I2D2), the Global Purchasing Power Parities and Real Expenditures data (P4), the so-called SHIP data, and the European Union Statistics on Income and Living Conditions (EU-SILC) data.

Keywords: Gini Coefficient; Local Suppression; Disclosure Risk; Hourly Earning; Synthetic Population (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-50272-4_8

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DOI: 10.1007/978-3-319-50272-4_8

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