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  • 1
    UID:
    almahu_9949544899702882
    Format: 1 online resource (496 p.) : , 115 line drawings, 64 tables
    ISBN: 9780226801391 , 9783110992823
    Series Statement: National Bureau of Economic Research Studies in Income and Wealth ; 79
    Content: 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.
    Note: Frontmatter -- , Contents -- , Prefatory Note -- , Introduction: Big Data for Twenty- First- Century Economic Statistics: The Future Is Now -- , I. Toward Comprehensive Use of Big Data in Economic Statistics -- , 1. Reengineering Key National Economic Indicators -- , 2. Big Data in the US Consumer Price Index -- , 3. Improving Retail Trade Data Products Using Alternative Data Sources -- , 4. From Transaction Data to Economic Statistics -- , 5. Improving the Accuracy of Economic Measurement with Multiple Data Sources -- , II. Uses of Big Data for Classification -- , 6. Transforming Naturally Occurring Text Data into Economic Statistics -- , 7. Automating Response Evaluation for Franchising Questions on the 2017 Economic Census -- , 8. Using Public Data to Generate Industrial Classification Codes -- , III. Uses of Big Data for Sectoral Measurement -- , 9. Nowcasting the Local Economy -- , 10. Unit Values for Import and Export Price Indexes -- , 11. Quantifying Productivity Growth in the Delivery of Important Episodes of Care within the Medicare Program Using Insurance Claims and Administrative Data -- , 12. Valuing Housing Services in the Era of Big Data -- , IV. Methodological Challenges and Advances -- , 13. Off to the Races -- , 14. A Machine Learning Analysis of Seasonal and Cyclical Sales in Weekly Scanner Data -- , 15. Estimating the Benefits of New Products -- , Contributors -- , Author Index -- , Subject Index , Mode of access: Internet via World Wide Web. , In English.
    In: EBOOK PACKAGE Business and Economics 2022 English, De Gruyter, 9783110992823
    In: EBOOK PACKAGE COMPLETE 2022 English, De Gruyter, 9783110993899
    In: EBOOK PACKAGE COMPLETE 2022, De Gruyter, 9783110994810
    In: EBOOK PACKAGE Economics 2022, De Gruyter, 9783110992922
    In: University of Chicago Complete eBook-Package 2022, De Gruyter, 9783110766509
    Language: English
    Subjects: Economics
    RVK:
    URL: Cover
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