Big Data: New Tricks for Econometrics

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 r...

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Bibliographic Details
Published in:The Journal of economic perspectives Vol. 28; no. 2; pp. 3 - 27
Main Author: Varian, Hal R.
Format: Journal Article
Language:English
Published: Nashville American Economic Association 01.04.2014
Subjects:
Academic publications
Big Data
Computer science
Computers
Data analysis
Data processing
Datasets
Daten
Decision making
Decision trees
Deep learning
Econometrics
Economic forecasting models
Economic models
Economic statistics
Economic theory
Economists
Feature selection
Graduate students
Linear analysis
Linear models
Linear regression
Machine learning
Machinery
Manipulation
Modeling
Mortgage loans
Queries
Relational data bases
Scientists
Search engines
SQL
Statistical analysis
Structured Query Language-SQL
Studies
Support vector machines
Symposia: Big Data
Transactions
Trees
Ökonometrie
ISSN:0895-3309, 1944-7965
Online Access:Get full text
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Summary: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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ISSN:0895-3309
1944-7965
DOI:10.1257/jep.28.2.3