HAL VARIAN: Tools for Manipulating and Analyzing Big Data.

To HAL VARIAN, 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.

In essay Big Data: New Tricks for Econometrics (2014), HAL VARIAN promoting techniques that are more well-known in machine learning circles, than in econometrics or standard statistics, at least as understood by economists.

TO HAL VARIAN, the sheer size of the data involved may require more powerful data manipulation tools.

TO HAL VARIAN, the economists may have more potential predictors than appropriate for estimation, so we need to do some kind of variable selection.

TO HAL VARIAN, large datasets may allow for more flexible relationships than simple linear models. Machine learning techniques such as i) decision trees, ii) support vector machines, iii) neural nets, iii) deep learning, and so on may allow for more effective ways to model complex relationships.

Finally, ROB HYNDAMAN (2014) call attention to the technical challenges associated with the manipulation of such data are large, so some of them, even elementary, have not been overcome by Varian. Thus, the big data in the broad sense, constitute a new frontier of learning for economists.

BIBLIOGRAFIA

HYNDAMN, Rob., Varian on big data https://robjhyndman.com/hyndsight/varian-2014/1

VARIAN, Hal R. 2014. “Big Data: New Tricks for Econometrics.” Journal of Economic Perspectives, 2014, 28 (2):3–28. (Symposium: Big Data)http://people.ischool.berkeley.edu/~hal/Papers/2013/ml.pdf