Leseprobe
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High-quality and Timely Statistics
Marco Mingione (Hrsg.), Maurizio Vichi (Hrsg.), Giorgia Zaccaria (Hrsg.)
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Sozialwissenschaften, Recht, Wirtschaft / Methoden der empirischen und qualitativen Sozialforschung
Beschreibung
This book addresses a wide range of recent methodological aspects, applications and best practices of statistics production. It comprises a selection of peer-reviewed contributions of methodological and applied interest presented at the 4th Conference of European Statistics Stakeholders, CESS 2022, held in Rome, Italy, on October 20-21, 2022. The first part discusses statistical methods with applications to environmental risk assessment, sentinels data, surveillance systems during the Covid-19 pandemic, healthcare risk management, the analysis of regional or structural changes of scale, household distributional accounts, regional rental prices on municipalities, the network topology of the Euro area interbank market, tourism statistics and big data, statistical literacy, and Sustainable Development Goal composite indicators for EU countries. The second part focuses on statistical methodologies for complex data analysis, namely the optimal number of clusters to rank a model-based index, clustering methods for asymmetric data using spectral approaches, a family of parsimonious matrix-variate mixture models for heavy-tailed data, the importance of robust second-stage regressions for financial data, and on perturbation methods.
In view of the overarching theme “The European Data Ecosystem for the Statistical Information of the Digital Age” and the importance of statistical data for monitoring the progress of the United Nations’ Sustainable Development Goals, the CESS 2022 meeting provided a forum for discussion on methodologies, results, challenges and best practices among methodologists, producers, and users of European Statistics from academia, the national statistical offices and the institutions of the European Union.
Chapter Estimating regional rental prices on LAU 2 municipalities in North Rhine-Westphalia is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Kundenbewertungen
Statistical Literacy, Official Statistics, Social Statistics, European Statistics, Environmental Statistics, Data Collection, Complex Data Analysis, Data Analysis, Statistical Methods, Sustainable Development, European Data Ecosystem, Statistics Production, Economics Statistics, Statistical Information, Data Science