Econometrics¶

General textbooks¶

Thread about picking a textbook
Favorite introductory book: Peter Kennedy. A Guide To Econometrics
Very condensed synopsis of undergrad econometrics

Some well-known texts:

Greene
Dougherty
Stock and Watson
Hayashi
@Verbeek. A Guide to Modern Econometrics, in 5th edition in 2017. TOC and preface.

Open access:

Hansen. Econometircs

Cross Section and Panel Data¶

Wooldridge. Econometric Analysis of Cross Section and Panel Data
МНЕ, with criticisms by:
- Diebold: “sub-sub-sub-area of applied econometrics”
- J. Pearl

MHE is one of few books with excercises reproduced on github.

Criticism of MHE:

Rather, it’s a companion for a highly-specialized group of applied non-structural micro-econometricians hoping to estimate causal effects using non-experimental data and largely-static, linear, regression-based methods. It’s a novel treatment of that sub-sub-sub-area of applied econometrics, but pretending to be anything more is most definitely harmful, particularly to students, who have no way to recognize the charade as a charade.

https://fxdiebold.blogspot.com/2015/01/mostly-harmless-econometrics.html

Lecture Notes in Microeconometrics - nicely presented topics in econometrics for microeconomics from OLS to bootstrap, with guides to software.

Time Series¶

Heavyweight:

Hamilton

Other:

Diebold
Granger/Watson time series chapter in Handbook of Econometrics
Enders
Jeffrey Parker. Fundamental Concepts of Time-Series Econometrics in Theory and Practice of Econometrics. Reed College course

Macroeconomic time series:

John H. Cochrane. Time Series for Macroeconomics and Finance.
Eric Sims. Graduate Macro Theory II: Notes on Time Series
Lars Peter Hansen. Time Series Econometrics in Macroeconomics and Finance
Hilde C. Bjørnland and Leif Anders Thorsrud. Applied time series for macroeconomics. (not open source, but good table of contents and has MATLAB code)
Karl Whelan. Time Series and Macroeconomics. (also see RATS code and other lectures on the web site)

Вayesian Methods¶

Bayesian Methods for Hackers has programming-first approach.
SciPy 2019 Lecture on Bayesian Model Evaluation and Criticism.
A simple explanation of Naive Bayes Classification, an overwhelmingly popular StackOverflow answer.
Doing Bayesian Data Analysis in brms and the tidyverse
Statistical Rethinking A Bayesian Course with Examples in R and Stan (& PyMC3 & brms & Julia too)

Non-economics¶

Biostatistics¶

Regression modelling strategies with Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis by FE Harrell: