Econometrics is a very applied discipline by nature. As such, studying the theory is not the best way to learn it.
It is important to practice Econometrics in order to be able to grasp what we can learn from it, what we must
pay attention to, and what the potential challenges that may arise in practice are. With this in mind, a big part
of your grade for this class will be based on a term project.
You must form teams of 4-5 members and complete an empirical project. Each team must select a data set from
the list below and identify a related Economic question. Then you must try to provide an answer to the initial
question, based on the empirical findings resulting from the statistical analysis of the data. For this purpose you
must read and follow the guidelines from Chapter 11 in the textbook. The analysis must involve at least one
multiple regression and at least one hypothesis test. The selection of the model(s) and hypotheses must be well
justified by a theoretical analysis (it is not required to use a mathematical model, but some Economic intuition
must be provided). The project will be graded based on three outputs described ahead: a group report, a group
presentation, and an individual executive summary.
The companion website to Stock and Watson (2011) provides a collection of datasets corresponding to different
research papers. If you have problems coming up with research ideas, you may read the corresponding papers,
or the empirical exercises in Stock and Watson (2011). However I strongly encourage you to try to come up
with a research question and methodology on your own. The datasets and the reference to the corresponding
papers are available online at wps.aw.com/aw_stock_ie_3/178/45691/11696965.cw/index.html. You must
choose one of the following datasets:
• College distance – Cross-sectional dataset containing information on years of education, proximity to universities
and cost of tuition, as well as a number of demographic characteristics. The data is taken from a
survey of high school students.
• Current population survey – A large random cross-sectional sample containing data on the characteristics
of the national labor force in 1992 and 2008.
• Teacher ratings – Course evaluations and instructor characteristics (including a rating of physical appearance)
for a number of courses from the University of Texas at Austin.
• Growth – Average growth rates from 1960 to 1995, and macroeconomic characteristics for a sample of 65
• Guns – Crime incidence, demographic characteristics and gun regulations by state from 1977 to 1999.
• Fertility – Demographic characteristics, family characteristics and number and gender of kids for a large
sample of women in fertile ages.
• Names – Call backs to job applications by fake candidates with randomly selected names typically associated
with different racial groups.
• Report [50%] – Due in class on Monday, June 22nd
The report must be written in the format of a short research paper (no more than 10 pages, 1.5 spacing,
12pt font). The introduction must provide a background for the problem and describe the research question
and methodology. You must describe the dataset and present the numerical results using adequate tables
and graphs. Every figure and table must be discussed and referred to in the text. The paper must conclude
indicating how the analysis of the data helps to answer the proposed question. Be careful not to exaggerate
the conclusions that can be drawn from the data.
• Executive Summary [25%] – Due in class on Monday, June 22nd
Pretend that you work for a very important and busy person (say President Obama), and you must write
a short executive summary that will help him/her make an informed decision. Suppose that your boss has
little expertise on the subject, and only has a few minutes to read your report between meetings. The
executive summary must be short (no more than 1 page), and it must summarize the main findings and
implications of your extended analysis, in a concise and assertive way.