Econometrics
about this course
Econometrics is where theory meets data. Based on statistics and probability theory,
econometrics is the branch of economics that uses economic data to test theoretical
relationships and estimate their size.
This course builds on the measures and hypothesis tests that you learned in
statistics, using linear regression
to measure each source of influence on an dependent variable. Then this course explores
different types of datasets, how they may violate the regression model's assumptions
and how to account for those violations.
what you will learn
For inclass examples of regression analysis, this course explores the effect that
employment protections have on employment outcomes. By focusing on one single dataset,
we cover a lot of econometric theory.
But to learn econometrics, you must do econometrics, so this course provides
a few datasets
and some null hypotheses to help you learn how to conduct an analysis of the data.
And to help you more, one student produced a
video of me
exploring a dataset. I hope you enjoy it.

course outline
 background  statistics and probability
 lecture 1  ordinary least squares
 lecture 2  maximum likelihood
 lecture 3  hypothesis testing
 lecture 4  violations of the GaussMarkov assumptions
 Kennedy, chaps. 5, 6 and 7
 lecture 5  panel data
 Hill, Griffiths and Lim, chap. 15
 Kennedy, chap. 18
 lecture 6  heteroskedascity
 lecture 7  probability models
 Studenmund, chap. 13
 Hill, Griffiths and Lim, chap. 16
 Kennedy, chap. 16
 logit model,
(wxM)
 lecture 8  timeseries
references and software
 statistics
 statistical software
 mathematical software
textbooks
 recommendations:
 other suggestions:
Copyright © 20022019 Eryk Wdowiak
