Econometrics

Background and OLS

(posted: 31 Aug 2025)

This message outlines the lesson plans for our sessions on Tue 02 Sep and Thu 04 Sep as well as for our sessions on Tue 09 Sep and Thu 11 Sep.

After finishing our introductory discussions of the Octopus Test and the effect of the minimum wage, we will review some background on statistics and probability. And then we will discuss ordinary least squares.

To prepare, please read Studenmund, chaps. 1, 2 and 3. And please begin studying the problem set. We'll discuss problem #4 first, then return to #1. To assist you, I have provided my answers to #1.

Finally, for a practical example, we'll examine the effect that a change in law has on labor market outcomes. For that discussion, please read my Analysis of the "Biagi Law". To explain my choice, I wrote a page about Teaching with the "Biagi Law" Data.

links and files

course syllabus
message board

problem set (PDF)

monopsonist and minimum wage

answers

datasets

datasets for course project

my Analysis of the "Biagi Law" (PDF)
Teaching with the "Biagi Law" Data

Italian data: CSV file R script Gretl data
OECD data: CSV file R script Gretl data
Phillips Curve: wikipedia doviak.net

OECD Indicators of Employment Protection

EPL dataset description (PDF)

Wikipedia. Minimum Wage
Schmitt (CEPR, 2013). effect on employment

course outline

introductory discussions

statistics vs. machine learning
Bender and Koller (2020). "Climbing towards NLU"

the octopus test – notes on Bender and Koller's paper

Wdowiak. monopsonist and minimum wage
Wdowiak (2017). minimum wage, employment and annual pay

background -- statistics and probability

bivariate normal distribution, (wxM) (PDF)

lecture 1 -- ordinary least squares

Studenmund, chaps. 1, 2 and 3
notes on regression, (PDF)
OLS regression, (PDF)
OLS regression, (R script)
OLS regression, (wxM) (PDF)
problems #4 and #1

lecture 2 -- maximum likelihood

Kennedy, chaps. 1, 2 and 3
MLE mean-variance, (wxM) (PDF)
MLE regression, (wxM) (PDF)
MLE 2nd o.c., (wxM) (PDF)
problem #2

lecture 3 -- hypothesis testing

Studenmund, chaps. 4 and 5
Kennedy, chap. 4
MLE explanations, (wxM) (PDF)
distribution of beta hat, (R script)
problems #3 and #4

lecture 4 -- violations of the Gauss-Markov assumptions

Kennedy, chaps. 5, 6 and 7

lecture 5 -- panel data

Studenmund, chap. 16
Kennedy, chap. 18

lecture 6 -- heteroskedascity

Studenmund, chap. 10
Kennedy, chap. 8
heteroskedascity in the logit model

lecture 7 -- probability models

Studenmund, chap. 13
Kennedy, chaps. 16 and 17
logit model, (wxM) (PDF)

lecture 8 -- time-series

Studenmund, chaps. 9, 12 and 15
Kennedy, chaps. 10, 19 and 20
non-stationary residuals, (wxM) (PDF)

lecture 9 -- simultaneous equations

Studenmund, chap. 14
Kennedy, chap. 11

references and software

statistics

my statistics course
L.&H. Friedman's statistics course

statistical software

the R language

LearnEconometrics.com

mathematical software

Maxima and wxMaxima

wxMaxima installation instructions (U. New Haven)

Josef Leydold's Maxima for Economics
Zachary Hannan's wxMaxima for Calculus

textbooks

required:
- A.H. Studenmund. Using Econometrics: A Practical Guide.
- P. Kennedy. A Guide to Econometrics.
other suggestions:
- L. Adkins (2018). Using gretl for Principles of Econometrics.
- DeGroot and Schervish. Probability and Statistics.
- Pearce. The MIT Dictionary of Modern Economics.

Copyright © 2002-2025 Eryk Wdowiak