Welcome to Econometrics Navigator!


The Econometrics Navigator (EN) targets easier learning and coding for statistics and econometrics by doing two things:

  1. guide a learner through open access textbooks and community knowledge (reddit, Stack Overflow, Cross Validated, twitter threads)
  2. illustrate key topics with minimal code examples in Python, R, gretl or Julia.


v.0.0.4 (May 2019):

v.0.0.3 (April 2019) scraps several unfinished articles, including a section on applications (hard to fill it quickly). Three main parts in content established (own articles, textbook annotations and how to teach resources).

v.0.0.2 (November 2018) original version of EN nobody understood what it is good for, had sample articles on max likelihood, bootstrap, ANOVA.


1. Collection of own articles

The main body of Econometrics Navigator articles is Concepts and techniques section, organised alphabetically. Finished examples are:

2. Textbooks guide

Textbooks review attempts to sort out and annotate textbooks and reference texts by several categories.

For example, I praise Kennedy’s textbook and collect (constructive) criticisms of Mostly Harmless Econometrics there. The categories in econometrics are ‘general’ textbooks, cross-section/panel and time series texts.

3. Instructor resources

The backstage workings of the Navigator are History of econometrics, Ways to review econometrics and econometrics mindmap (draft).

These documents aim to organise thinking about better teaching of econometrics in terms of sequence of topics, better analogies for the learner and a faster bridge to coding from formulas.


So far twitter has been an enormously valuable source of demos, links and opinion for me. I keep a separate page with twitter posts, some of my favorites are:


Feel free to contact me @PogrebnyakE. I need help in shaping this guide. Some future steps outlined in roadmap.


The source of this publication is available at https://github.com/epogrebnyak/econometrics-navigator or https://tinyurl.com/emnavig