Berton Data-Driven Learning in the EU

Data-Driven Learning in the EU

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From Administrative Sources to Public Value

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Beschreibung

This Open Access book highlights the importance of administrative microdata sources. Administrative data presents several advantages, including wide coverage, low measurement error and collection costs, and interoperability with surveys.  Improved access would benefit many stakeholders: the research community would produce higher-quality and more numerous publications, policymakers and citizens would learn whether policies are effective, firms would benefit from greater market transparency, and trust in public institutions would increase. However, many barriers still exist. This book aims to address these issues. Focusing on the European Union, the book is organized into two parts. The first part analyzes the access regimes in each EU country. It provides data users with information on how to access administrative data and offers data holders best practices for combining access with data security. The second part documents the benefits of administrative data in key policy areas - society, the economy, and the environment - and identifies specific areas of intervention. Administrative data are the foundation for modern policy analysis. Berton and Paruolo’s exciting new book highlights state-of-the art applications of administrative data, offering practical advice on how to use the right data to learn “what works”. It also includes a valuable country-by-country overview of the administrative data in each EU country, curated by a who’s who list of experts.  A must-read for anyone looking to learn more about the prospects and potential for administrative data in the EU. David Card Co-winner of the 2021 Nobel Memorial Prize in Economics

This Open Access book highlights the importance of administrative microdata sources. Administrative data presents several advantages, including wide coverage, low measurement error and collection costs, and interoperability with surveys. 

Improved access would benefit many stakeholders: the research community would produce higher-quality and more numerous publications, policymakers and citizens would learn whether policies are effective, firms would benefit from greater market transparency, and trust in public institutions would increase. However, many barriers still exist. This book aims to address these issues.

Focusing on the European Union, the book is organized into two parts. The first part analyzes the access regimes in each EU country. It provides data users with information on how to access administrative data and offers data holders best practices for combining access with data security. The second part documents the benefits of administrative data in key policy areas - society, the economy, and the environment - and identifies specific areas of intervention.

"Administrative data are the foundation for modern policy analysis. Berton and Paruolo’s exciting new book highlights state-of-the art applications of administrative data, offering practical advice on how to use the right data to learn “what works”. It also includes a valuable country-by-country overview of the administrative data in each EU country, curated by a who’s who list of experts.  A must-read for anyone looking to learn more about the prospects and potential for administrative data in the EU."

David Card

Co-winner of the 2021 Nobel Memorial Prize in Economics


This book is open access, which means that you have free and unlimited access Highlights the value of access to administrative data and other sources of microdata in each EU country Presents best practices in data management to support evidence-based policy and cost-effective policymaking Features case studies from various EU countries

Autor*in

Fabio Berton

Themen in »Data-Driven Learning in the EU«

Open Access Administrative data Program evaluation Regulation European Union Data access Data protection Governance Public good Public policy Causality Credibility revolution Evidence-based policy Microdata Data-driven policymaking

Stimmen zu »Data-Driven Learning in the EU«

Details

ISBN: 9783031990311
Verlag: Springer International Publishing
Erscheinung: 17.09.2026

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