Econometrics is the application of statistical methods to economic data with the goal of examining relationships. This course introduces students to multiple regression methods for analyzing data. Extensions include regression with discrete random variables, instrumental variables regression, analysis of random experiments and quasi-experiments, and regression with time series data. The objective of the course is for the student to learn how to conduct – and how to critique – empirical studies in economics and related fields. Accordingly, the emphasis of the course is on empirical applications. Students should be familiar with basic concepts in probability theory and statistical inference.
Textbook:
Wooldridge, Introductory Econometrics, 5th edition. Find the pdf version here. The course covers one chapter per week, with deadlines on Sundays.
Course outline
- Basic tools – Wooldridge Appendix A
- Excel 2019 Beginner Tutorial
- HW1-doc
2. Probability – Wooldridge Appendix B
HW2 – doc
3. Econometrics and data – Wooldridge ch 1
- Ceteris Paribus – video
- HW3 – doc
4. Econometrics and data – Wooldridge Appendix C
- HW4- doc
5. Simple regression model– Wooldridge ch 2
- Regression refresher – 2min HBR
- Intro to Linear Regression
- Interpreting the Regression Line
- Outliers
- HW5 – doc and an Excel file with datasets for this HW
6. Multiple regression estimation– Wooldridge ch 3
- HW6 – doc
- HPRICE1 xls -dataset
7. Hypothesis tests- Wooldridge ch 4
- HW7 – doc – this HW is long
- DISCRIM.xls – dataset
8. Fitting and predictions – Wooldridge ch 6 (skip 5)
- HW8 – doc
- NBASAL.xls – dataset
9. Qualitative variables – Wooldridge ch 7
- HW9 – doc coming soon
- BEAUTY.xls – dataset
10. Heteroskedasticity – Wooldridge ch 8
- HW10 – doc
11. Specification – Wooldridge ch 9
- HW11 – doc
- JTRAIN.xls- dataset
Final Project
- Ask your own question and answer it using econometric analysis. Your question can be similar to those encountered in the homework problem sets. Find a dataset online, choose your sample, develop a hypothesis, estimate your regressions and test your hypotheses. Explain your main research question, your choice of variables, method of estimation and your results.
- For example, you may decide to test whether women really earn less than men in similar occupations. You may choose to estimate several regressions for various occupations or one large regression with interactions of gender and other variables. In that case your data can be drawn from IPUMS-CPS https://www.ipums.org/. IPUMS also has Census and other datasets.
Further readings & resources
- Econometrics videos – KeynesAcademy
- Econometrics course videos – Ben Lambert
- Lectures on econometrics – BurkeyAcademy
- Econometrics by Bruce Hanson -textbook, U of Wisconsin
- Ben Lambert’s page – including problem sets
- Econometrics MOOC – Erasmus Univ @Coursera
- Econometrics books – list
- Web pages that perform stat calculations -statpages.org
- Software gretl – free
- EasyReg software – free
- Oaxaca decomposition – world bank examples
- Decomposition cheat sheet – MF wage differential
- https://www.trialandstderror.com/differences/ – by Froeb