Harmonization and Quality Assurance of Income and Wealth Data: The Case of LIS.

Jorg Neugschwender; Teresa Munzi; Piotr Paradowski

Harmonization and Quality Assurance of Income and Wealth Data: The Case of LIS.

Abstract

Comparability of concepts in survey data harmonization is essential for scientific analyses. LIS – also known as the Luxembourg Income Study or LIS Cross-National Data Center in Luxembourg – acquires and harmonizes income and wealth microdata to provide the scientific community with a comparable database that is unique in the world in its growing temporal and geographic breadth. Over many decades, scholars worldwide have used the LIS and Luxembourg Wealth Study (LWS) databases to compare economic and social policies and their effects on outcomes, including poverty, income inequality, employment, gender inequality, and wealth portfolios. Since source data entering LIS differ substantially in terms of collection mode, type of information collected, level of detail, and structure of the data, this chapter elaborates on the various harmonization efforts at LIS, revolving around the ex-post aspect of harmonization. The discussion of core challenges of ex-post harmonization, LIS guiding principle of operational comparability, documentation, software tools, and quality assurance procedures set in place at LIS is enriched with practical examples. The last section concludes with key lessons learned from nearly 40-years of harmonization of microdata, pointing out to other significant factors, such as the importance of interaction with scholars, data providers, and other experts in the field in order to provide reliable data for cross-national, interdisciplinary research.

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Category:

Monographic publication

Type:

rozdział, artykuł w książce - dziele zbiorowym /podręczniku w języku o zasięgu międzynarodowym

Language:

English

Publication year:

2023

Bibliographic description:

Neugschwender J., Munzi T., Paradowski P.: Harmonization and Quality Assurance of Income and Wealth Data: The Case of LIS.// Survey Data Harmonization in the Social Sciences/ : , , s.269-284

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