Big Data for Twenty-First-Century Economic Statistics
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 adm...
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| Other Authors: | , , |
| Format: | eBook |
| Language: | English |
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Chicago
University of Chicago Press,
2022.
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| Series: | Studies in income and wealth.
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| Subjects: | |
| Online Access: | EBSCOhost Перейти в каталог НБ ТГУ |
Table of Contents:
- 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