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9 votes

The relation between econometrics and machine learning

I.) 2 Principles of econometrics can potentially be useful compared to Machine Learning. (see Hal R Varian 2014 Paper : https://pubs.aeaweb.org/doi/pdf/10.1257/jep.28.2.3) A.) As you suggest the ...
Benjamin Caudron's user avatar
4 votes

How to use panel data for a time series machine learning problem?

This is a question that crosses all over the place, each of these techniques are different. Here are some very loose guidelines. As a baseline, recall that in econometrics you may have performed ...
RegressForward's user avatar
4 votes

Big Data: New Tricks for Econometrics

This is a p-value. Varian writes the ctree "chooses the structure of the tree using a sequence of hypothesis tests". I don't know what those hypothesis tests are, but Varian cites Hothorn, ...
Michael Gmeiner's user avatar
3 votes

The relation between econometrics and machine learning

My view coincides with the introduction to your question. Namely, a) Econometrics is mostly concerned with causality b) Machine learning is mostly concerned with fit. But for the remaining part, our ...
Artem Kochnev's user avatar
1 vote

Big Data: New Tricks for Econometrics

In general, in research papers involving statistics, "p < 0.05" represents the fact that the results are statistically significant. "p" is the p-value. For example, "p < ...
krauuuus's user avatar
  • 105
1 vote

Propensity Score Matching

Could you define a new treatment variable that takes 8 values? E.g. $T=0$ if all three treatments are 0. $T=1$ if pills=1 and the other two are 0. $T=2$ if exercise = 1 and the other two are 0, ... $T=...
Michael Gmeiner's user avatar
1 vote

Propensity Score Matching

Interesting question that I hadn't thought about before. The most similar application I can think of is this paper using a control function estimator for two (mutually exclusive) treatments. https://...
Michael Ricks's user avatar
1 vote

Research in Applications of Machine Learning Techniques to Economics

The thing to remember is that a lot of econometrics is concerned with establishing causality between a variable of interest and the outcome ex-post. In this framework, establishing unbiased estimates ...
A. Miller's user avatar
  • 151
1 vote

Machine learning and Inflation forecasting

I am far from being an expert, but would say it is not the model but the data that can help you gain forecast accuracy in this case. Modern machine learning applications in macroeconomic forecasting ...
Richard Hardy's user avatar
1 vote

The relation between econometrics and machine learning

I think the essence of this question is actually asking the difference between statistics and econometrics. You can find some good answers here. Here is my try on a simple - and maybe abstract, but I ...
Alalalalaki's user avatar
  • 2,474
1 vote

The relation between econometrics and machine learning

Here is a basic answer for anyone too uninterested to read the long answers: 1) ML focuses on prediction and not on causality (as does metrics) 2) ML is powerful for parameter selection and model ...
123's user avatar
  • 2,911
1 vote

The relation between econometrics and machine learning

So you are right. It is extremely difficult to prove causality in economics. Using an instrumental variable is a good way to do so. I think you might be a little confused about the difference between "...
TheSaint321's user avatar

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