Modern Data Analysis for Economics: Model Selection and Regularization (Part II)

Model Selection and Regularization

Topics: cross validation; information criteria; forward stepwise regression; regularization; ridge regression; lasso; elastic net; post-selection inference; smoothing splines

2019 Fall @ Xiamen University

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Modern Data Analysis for Economics

This course offers a unified introduction to the principles and methods of statistical modeling and causal inference – two areas essential to data analysis in economics. The first part of this course introduces learning theory and a number of modern machine learning methods used for pattern recognition and predictive modeling. The second part introduces the theory of causal inference and surveys frequently used econometric techniques for causal effect learning and program evaluation. Finally, we discuss structural estimation and offer a unified perspective on the use of reduced-form and structural econometric methods.

Course website: https://jiamingmao.github.io/data-analysis/

Видео Modern Data Analysis for Economics: Model Selection and Regularization (Part II) канала Jiaming Mao