Econometrics and statistics

This book develops the statistical foundations of econometrics and then uses them to study regression, panel data, parametric estimation, binary-choice models, and time series. Mathematical results are paired with simulations, empirical applications, and exercises. The material has been developed by Jean-Paul Renne.

The chapters are cumulative. The first three establish the probability and inference tools used later. The linear-regression chapter develops the central econometric framework; the chapters on panel regressions, estimation methods, and binary-choice models build on it. The time-series chapter introduces time-indexed data and forecasting. The appendix collects supporting results and longer proofs so that the main chapters can retain their narrative flow.

Definitions and propositions state the core results. Examples show how those results operate in data, while practice boxes point to exercises that reinforce the surrounding material. Readers who use the computational examples can inspect the R code in the HTML edition; the PDF can be rendered with or without that code.

The computational material uses various packages available from CRAN, as well as procedures and data from the companion package AEC. This package is available on GitHub. Installation instructions and the recorded package environment are described in the repository README.

Code 
install.packages("remotes")
remotes::install_github("jrenne/AEC@3245789138e77c2d7b591b40e8b6a3405e93cbf1")
library(AEC)

Useful R links: