Basic Econometrics (Economics 205) Davidson College Jan – May 2008
Regression Analysis Paper
In this semester-long project, you will apply regression analysis, the most commonly used tool of
empirical economics, to a topic of your choice. The goal is to develop and estimate an econometric
model of the causal effect which an explanatory variable of interest has on a dependent variable,
controlling for relevant other factors.
The due dates and relative weights for the regression analysis paper (30% of course grade) are as follows:
Initial Proposal & Lit Review Monday, February 4, 09:00 0 points
Data Description Friday, March 14, 16:00 10 points
Intro & Lit Review Friday, March 14, 16:00 15 points
Model development & Predictions Friday, April 11, 16:00 15 points
Model estimation not to be formally turned in 10 points
Final paper Thursday, May 8, 17:00 50 points
Please submit your final paper by sending an email to me (mafoley@davidson.edu) with the subject line
“205 Final Paper userid.” There should be only one document attached to the email; the appendices
should not be in a separate document.
Model Estimation and Conclusion
This is intended to be a section of your final paper. Please write and format it accordingly. For
the final paper you should combine this part with the previous parts. Do not simply cut and
paste. Create a coherent overall paper, by following the “roadmap” you set up earlier, and
including appropriate transitional phrases from one section to the next.
In this section, you must:
1. Estimate the model and conduct the hypothesis tests you proposed
in the previous section. You may of course amend these for the
final paper.
2. Create a results table (or tables if necessary) like Table 8.3 (page
292), Table 10.1 (page 368), and Table 11.2 (page 403).
3. Discuss the table in detail. Take your cues from our textbook’s
discussions of results and from your literature review articles’
discussions of results. Keep your eye on the ball!
In the previous section, you developed specific hypotheses about
the signs of the variables’ marginal influences and/or elasticities.
Interpret the signs and values of the estimated marginal influences
and/or elasticities, which you will need to calculate , in the
appropriate context and compare them to those theoretical
