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Ресурс содержит несколько файлов.Big Data for Twenty-First-Century Economic Statistics
База данных: Каталог библиотеки СФУ (330.0727 B57)
Библиографическое описание: Abraham, Katharine G. . Big Data for Twenty-First-Century Economic Statistics / Katharine G. Abraham, Jarmin, Ron S., Moyer, Brian C., Shapiro, Matthew D. - Электрон. текстовые дан. - Chicago : : University of Chicago Press,, 2022. - 1 online resource (502 p.). - Загл. с титул. экрана. - ISBN 022680139X. - ISBN 9780226801391. - Текст : электронный. Description based upon print version of record. Примечания о происхождении: Коллекция цифровых книг Ebsco ebook (централизованная подписка 2023 г., бессрочный доступ)., НБ СФУ
Аннотация: The papers in this volume analyze the deployment of Big Data to solve both existing and novel challenges in economic measurement. The existing infrastructure for the production of key economic statistics relies heavily on data collected through sample surveys and periodic censuses, together with administrative records generated in connection with tax administration. The increasing difficulty of obtaining survey and census responses threatens the viability of existing data collection approaches. The growing availability of new sources of Big Data--such as scanner data on purchases, credit card transaction records, payroll information, and prices of various goods scraped from the websites of online sellers--has changed the data landscape. These new sources of data hold the promise of allowing the statistical agencies to produce more accurate, more disaggregated, and more timely economic data to meet the needs of policymakers and other data users. This volume documents progress made toward that goal and the challenges to be overcome to realize the full potential of Big Data in the production of economic statistics. It describes the deployment of Big Data to solve both existing and novel challenges in economic measurement, and it will be of interest to statistical agency staff, academic researchers, and serious users of economic statistics.
Год издания: 2022
Издательство: University of Chicago Press,, Chicago :
Количество экземпляров:
Издание имеется только в электронном виде
Рубрики: Big data,
Economics / Statistical methods / Data processing,
Données volumineuses,
Économie politique / Méthodes statistiques / Informatique,
BUSINESS & ECONOMICS / General
Economics / Statistical methods / Data processing,
Données volumineuses,
Économie politique / Méthodes statistiques / Informatique,
BUSINESS & ECONOMICS / General
Классификационные коды: УДК 330.0727
ISBN: 022680139X
Идентификаторы: полочный индекс 330.0727 B57, шифр /B57-033409053