The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Big Data: New Tricks for Econometrics
Open accessAbstract
Computers are now involved in many economic transactions and can capture data associated with these transactions, which can then be manipulated and analyzed. Conventional statistical and econometric techniques such as regression often work well, but there are issues unique to big datasets that may require different tools. First, the sheer size of the data involved may require more powerful data manipulation tools. Second, we may have more potential predictors than appropriate for estimation, so we need to do some kind of variable selection. Third, large datasets may allow for more flexible relationships than simple linear models. Machine learning techniques such as decision trees, support vector machines, neural nets, deep learning, and so on may allow for more effective ways to model complex relationships. In this essay, I will describe a few of these tools for manipulating and analyzing big data. I believe that these methods have a lot to offer and should be more widely known and used by economists.
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Cites
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Why Are There Still So Many Jobs? The History and Future of Workplace Automation
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“Source: The table is based on that in Ley and Steel (2009); the data analyzed is from Sala-i-Martín (1997). Notes: We illustrate different methods of variable selection.”
BackgroundMethodInfluentialA few useful things to know about machine learning
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Cited by
Biau, G., & Scornet, E. (2016) · Test · doi:10.1007/s11749-016-0481-7 · Cited by 4,149
Why Are There Still So Many Jobs? The History and Future of Workplace Automation
Autor, D. H. (2015) · Journal of Economic Perspectives · doi:10.1257/jep.29.3.3 · Cited by 3,917
Angrist, J. D., & Krueger, A. B. (2001) · Journal of Economic Perspectives · doi:10.1257/jep.15.4.69 · Cited by 2,355
Machine Learning: An Applied Econometric Approach
Mullainathan, S., & Spiess, J. (2017) · Journal of Economic Perspectives · doi:10.1257/jep.31.2.87 · Cited by 1,989
Marketing Analytics for Data-Rich Environments
Wedel, M., & Kannan, P. K. (2016) · Journal of Marketing · doi:10.1509/jm.15.0413 · Cited by 1,261
Metadata
- Authors
- Varian, H. R.
- Venue
- Journal of Economic Perspectives
- Publisher
- American Economic Association
- Published
- 2014-05-01
- Volume
- 28
- Issue
- 2
- Pages
- 3-28
- ISSN
- 0895-3309 (ISSN-L)
- OpenAlex
- W2155419203
- Cited by
- 1,557
- References
- 12
- FWCI
- 184.85
- Type
- journal article
- Language
- en
- Open access
- bronze
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