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, estimate their size and make predictions. As a first course in data analysis, this course will prepare the student for further study of econometrics and for other data analysis fields (e.g. machine learning).

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 in-class 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

references and software

textbooks

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