​Econometric and Quantitative Methods Notes

Available Upon Request

Summary: The goal of these notes is to introduce and discuss different statistical methods used to conduct econometric analysis. The first part of these notes explains the concepts of probability theory, statistical modeling and inference in detail. I describe basic concepts as random variables, estimation, hypothesis testing, and confidence intervals. The second part of the notes describe linear models (OLS, Restricted Least Squares, GLS, Instrumental Variables, Panel Data, and Dynamic Panel Data). The third and fourth part discuss non-linear econometrics methods including but not limited to non-linear least squares, GMM, quantile regression, MLE and limited dependent variable models. The rest of the notes discuss causal inference and special topics as selection bias and truncated data, density estimation, Bayesian statistics, among others. The notes also cover machine learning methods as Lasso, Ridge, Random Forests and Neural Networks.

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