- 320 pages
- English
- PDF
- Available on iOS & Android
About this book
Tools from macroeconomics and finance to incorporate the central role that data plays in the economy
The most valuable firms in the global economy are valued largely for their data. Amazon, Apple, Google, and others have proven the competitive advantage of a good data set. And yet despite the growing importance of data as a strategic asset, modern economic theory neglects its role. In this book, Isaac Baley and Laura Veldkamp draw on a range of theoretical frameworks at the research frontier in macroeconomics and finance to model and measure data economies. Starting from the premise that data is digitized information that facilitates prediction and reduces uncertainty, Baley and Veldkamp uncover the ways that firm-level data choices resonate throughout the broader macroeconomic and financial landscapes.
With The Data Economy, Baley and Veldkamp put forward a broad research agenda with a formal yet accessible approach, offering an analysis of the data economy and its welfare effects that will be of interest to practitioners, researchers, and graduate students. The tools presented, many of them information-related methods from macroeconomics and finance, are theoretical but introduced with careful attention to how they can inform or enable measurement. Applications include assessing the economic worth of data and unraveling its influence on the structure of production, inflation, and pricing dynamics; firm and investor behavior; advertising; market power; and asset pricing. Baley and Veldkamp bring readers to the cutting edge of this novel research area, equipping them to formulate their own theoretical advances and policy analysis.
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Information
Table of contents
- Cover
- Contents
- List of Figures
- Acknowledgments
- 1. The Data Economy
- 2. Statistical Tools
- 3. Data Sources
- 4. Data-Driven Predictions and Aggregate Outcomes
- 5. Using Data in Strategic Settings
- 6. Using Data to Guide Investment
- 7. Data and Market Power
- 8. Data Markets and Data Platforms
- 9. Data in Production and the Data Feedback Loop
- 10. Data Measurement and Valuation
- 11. Data Policy and Welfare
- Conclusion
- A. Mathematical Appendix
- References
- Index