Online Text and Notes in Econometrics
An archive of cheat sheets for different functions and packages of the R language, some of them contributed by the community of users. Topics covered include data import, data transformation, working with strings and working with dates.
Last revised in March 2021, this is a thorough textbook divided into 29 chapters. It is organised into six sections: Regression, Large Sample Methods, Multiple Equation Models, Dependent and Panel Data, Nonparametric Methods, and NonLinear Methods. Including appendices, there are more than 1,000 pages of content.
A set of course materials that can be configured as undergraduate- or graduate-level, based around Jupyter notebooks. It discusses setting up your own python programming environment, relevant software libraries and techniques, then works through many examples in economics. Each section of the material can be downloaded as a PDF using the buttons near the top of the text.
Freely downloadable as a 374-page PDF, this manual shows students how to use Gretl software to reproduce all the examples from Hill, Griffiths, and Lim's Principles of Econometrics, 5th edition. The data sets and script files used in the book are also freely downloadable. The current version dates from September 2018.
This is a short, very introductory article which takes the reader through a simple regression test in Excel. The given example involves testing whether Okun's Law applies to US data, and there is a downloadable Excel file used in the exercise.
A set of six cheat sheets for Stata from an open online course in Fundamentals of Data Analysis and Visualization. The topics are Basic Processing, Data Transformation, Creating Data Visualizations, Customizing Data Visualizations, Data Analysis, and Programming
Bayesian statistics and its application to econometrics - lecture slides and notes from a course that ran from 2013 to 2015. The Powerpoint presentation comprises nearly 100 slides.
This page has a great deal of illustrated text on optimization and linear programming with many related external links. It has been produced by Hossein Arsham of the University of Baltimore.
Subtitled "A guide for selecting statistical techniques for analysing survey data", this presents a tree of choices about your data and the hypotheses being tested, resulting in a recommended statistical test. It was created by the authors of the MicrOsiris statistical software. It is freeware that is downloaded with MicrOsiris.
Materials from a 2011/12 course for year 2 undergraduates with an existing grasp of matrix algebra and rudimentary statistical inference. The module aims "To deepen and consolidate knowledge of probability and statistics, with a focus on sampling and inference, as they pertain to Econometrics." Ten lecture handouts, separate lecture slides, and some assessment materials, all in PDF format.
Archived course materials from a 2011/12 module for year 2 undergraduates, including slides, 20 PDF lecture handouts, and exercises.
Six lecture PDFs, plus supplements and exercises, from an introductory Econometrics course. Topics include Matrix Algebra, Elementary and Multiple Regression, Serially Correlation Regression Disturbances, and Dynamic Regressions, totalling 75 pages of material.
A collection of introductory resources for learning Stata and R, usually in the form of sets of slides in PDF that step through basic tasks in statistical analysis.
Lecture notes and class exercises from an Intro to Stata course taught in 2010, based on a course previously taught by Michael McMahon.
Discrete choice methods with simulation is an online text written by Kenneth Train of University of California, Berkeley in 2003. It covers topics such as numerical maximization, simulation assisted estimation and Bayesian procedures. Each chapter is available as a PDF file to download, and the site also provides an index, bibliography and errata discovered since publication. Users can also download the whole text as a single zip file.
Updated materials from a course originally taught in Spring 2001, including a syllabus, video lectures (in quite a low resolution) and an electronic version of the 2009 textbook Discrete Choice Methods with Simulation. Topics include Advantages and Limitations of Logit, Numerical Maximization, and Hierarchical Bayes.
These pages give materials for the BA degree honours year Applied Econometrics class at the University of Strathclyde as taught by Roger Perman. Lecture notes and references notes in Word format are listed on this course home page. It covers topics such as Dynamic Econometric Modelling, Model misspecification and misspecification testing, Stochastic regressors, instrumental variables and weak exogeneity and Panel data analysis.
This is a course website for Introductory Econometrics as taught by Mike Abbott at Queen's University, Kingston (Australia). It includes extensive course materials, lecture notes, statistical tables, datasets and assignments and a number of past exams, going back to 1997, some with answers in separate files.
Online textbook with twenty PDF chapters, from Elementary regression analysis to Multivariate autoregressive moving-average models.
Available are notes from lectures, problem sets, and a sample exam. Lecture topics are: Discrete Response Models, Sampling and Selection, Generalized Method of Moments, Instrumental Variables, Systems of Regression Equations, Simultaneous Equations, and Robust Methods in Econometrics. From an Econometrics / statistics course as taught in 2001.
This Spring 2000 course page has brief notes from a series of 23 lectures on Economics, statistics and econometrics as taught by Andrew K. G. Hildreth of University of California, Berkeley. The site was taken down in 2017: this link goes to the Archive.org copy.
Fifteen detailed lecture handouts in PDF are archived here along with 11 exercise sheets with answers. The lecture topics are: Sets and Boolean Algebra, The Binomial Distribution, The Multinomial Distribution, The Poisson Distribution, The Binomial Moment Generating Function, The Normal Moment Generating Function, Characteristic Functions and the Uncertainty Principle, The Bivariate Normal Distribution, The Multivariate Normal Distribution, Conditional Expectations and Linear Regression, Sampling Distributions, Maximum Likelihood Estimation, Regression estimation via Maximum Likelihood, Cochrane's Theorem, and Stochastic Convergence.
This 1998 course page has seven sets of extensive lecture notes totalling more than 160 pages of explanatory material. There are also seven quizzes, also in PDF and PostScript formats. The course is an Introduction of Econometrics / Statistics as taught by Daniel McFadden, James Powell at University of California, Berkeley.
Various resources for learning statistical packages, including introductory learning modules, Frequently Asked Questions, example exercises from textbooks and examples of different kinds of analysis. Includes a one-page guide to choosing a statistical test, with guidance on performing each test in the four packages.
Online, freely-reproducible textbook with examples in R. The online layout makes it possible to bookmark individual chapters and sections. The main sections are 1: Basic Concepts in Time Series, 2: The Estimation of Mean and Covariances, 3: ARMA Processes, 4: Spectral Analysis.
The Nobel Foundation makes available a great deal of material on each of the Economics prize winners, including video of each Prize Lecture since Robert Mundell in 1999. As well as a lay introduction to each prize winner's research, there are "Advanced information" links giving a more technical explanation. This link is to the Economics Network's quick index of lecture videos and related materials on the site. Each video is a full lecture (usually between 40 and 60 minutes) with good audio and video quality, and pitched at a non-technical audience. Transcripts of each lecture are available.