The objective of this course is to get you started doing empirical work with R. The skills that you will learn are useful for anyone who does data analysis, and should enhance your prospects of finding a good job.

At the end of the semester you will turn in a paper, written in the
format of the typical empirical paper in economics. The analysis must be
done in R. I need to approve the topic of your paper, and will ask for a
proposal by October 11. **Half of your grade will be based on the
quality of this paper**.

In preparing your proposal, you should first read some
ideas for term paper topics.pdf. The format of the paper is sketched
out in this MS Word Document: term
paper outline.docx. We will talk more about this later, but for now
I would like to point out that **the easiest way to write the
paper would be to use the term paper outline as a template, simply
filling in each section as you have time**.

- Monday, August 28, 2023 - first day of class
- Wednesday, October 11, 2023 - term paper proposal due
- Wednesday, December 6, 2023 (4:10 pm - 5:35 pm) - final exam
- Monday, December 13, 2023 (3:30 pm - 5:30 pm) - peer evaluation, term papers due

- Reading
and writing data

- Variable
selection

- Specification:
dummy variables; interaction terms; polynomials

- Data
cleaning; modifying variables; estimating a model

- Basic
mathematics of OLS

- Hypothesis
tests

- Multicollinearity

- Monte-Carlo
for omitted variable bias

- Influential
variables and observations

- Cobb-Douglas
Production Function

- Heteroskedasticity

- Endogeneity

- Spatial
Autocorrelation

- Granger
Causality

- Temporal
Autocorrelation

- Forecasting

- R web search Use this to hunt
for documentation for specific package or function

- Using R for Introductory
Econometrics can be read for free on
the web, or one
can purchase a hard copy for less than $30.

- Cheat
sheets

- coursera.org
offers classes in R programming

- All contributed
documentation is a list of documentation written by users.

- CRAN Task
Views introduces you to the most valuable packages, by topic.

- R meta-blog

- Quick-R: Home
Page

- Stackoverflow
questions on R

- Gallery of R graphs (with code)