Machine Learning: An Applied Econometric Approach
Harvard University · Harvard University Press
Abstract
Machines are increasingly doing “intelligent” things. Face recognition algorithms use a large dataset of photos labeled as having a face or not to estimate a function that predicts the presence y of a face from pixels x. This similarity to econometrics raises questions: How do these new empirical tools fit with what we know? As empirical economists, how can we use them? We present a way of thinking about machine learning that gives it its own place in the econometric toolbox. Machine learning not only provides new tools, it solves a different problem. Specifically, machine learning revolves around the problem of prediction, while many economic applications revolve around parameter estimation. So applying…
Citation impact
- FWCI
- 86.10
- Percentile
- 100%
- References
- 36
Authors
2Topics & keywords
- Toolbox
- Python (programming language)
- Machine learning
- Computer science
- Artificial intelligence
- Face (sociological concept)
- Empirical research
- Mathematics
- Decent work and economic growth