DATA-ECONOMIST: BRINGING TOGETHER MACHINE LEARNING AND ECONOMICS

The goal of this resource is to bridge the gap between rapidly developing area of machine learning and artificial intelligence on one hand and economic science on the other. Historically machine learning and artificial intelligence appeared as subarea of computer science and focused on such issues as modelling image and text data, customer behavior etc. where data is abundant and quality of the models in most cases can be instantly verified by humans. By contrast, in macroeconomics researchers usually have only handful of relevant data for each problem and the models they devise cannot be verified by simply looking at the results or by conducting life tests or experiments. That’s why, while both areas build their knowledge body on common foundation of statistical insights, each of them developed its distinct set of tools and methods. At times the gap between machine-learning approaches and econometrics seems to be insurmountable and for the good reason but there is always a way. Here we try to find it.

On this page we collect links to relevant scientific papers and articles on machine learning and artificial intelligence as well as results of any attempts to apply them to various economic problems. We also suggest some educational resources and post views and opinions that we consider interesting. Welcome!