| Unique | Missing Pct. | Mean | SD | Min | Median | Max | |
|---|---|---|---|---|---|---|---|
| gdp | 191 | 9 | 20.7 | 19.5 | 0.1 | 14.3 | 101.2 |
| pop | 208 | 0 | 147.7 | 288.4 | 3.6 | 56.9 | 1407.7 |
| gini | 64 | 62 | 33.2 | 4.7 | 24.9 | 33.2 | 42.4 |
| medals | 158 | 10 | 347.1 | 175.0 | 9.0 | 313.0 | 849.0 |
Final Project
All materials can be found at alexcardazzi.github.io.
Project Summary
Students will be expected to write a research paper with an econometric analysis on a topic of their choosing (and to be approved by the instructor). This project will test each student’s ability to both perform and communicate rigorous econometric analyses.
In terms of data, projects may use either cross sectional or panel data, but not time series data. In addition, students must have at least one outcome variable and at least three explanatory variables. See examples throughout.
Students will submit checkpoints throughout the semester to ensure they are on target. The due dates and expectations for the checkpoints are below.
Checkpoint 1
ePortfolio | Week 1 | 10 Points
For this checkpoint, students will create an outline of an ePortfolio. Maximally, you should think of your ePortfolio as a personal website. Minimally, your ePortfolio will act as an online resume where you can show off your work.
ODU supports student ePortfolios via the Office of Academic Success Initiatives & Support, and students are encouraged to explore these resources. I have personally used Google Sites in the past and found it to be intuitive and functional. Other faculty members might suggest websites such as Wix. The two major advantages of these services are that they are”point and click” softwares that require no coding and you can continue using them even after you graduate.
To receive full credit for this checkpoint, students must submit a working URL that navigates to an ePortfolio home page with a professional picture (or a placeholder image), their name, major, home town, graduation date, and small bio. In addition, students must upload/embed a placeholder HTML file for their final project.
Checkpoint 2
Topic(s) | Week 4 | 20 Points
To receive full credit, students must submit multiple research topics they’re interested in. Students are encouraged to submit multiple (3-5) topics to keep their options open. Some examples of topics include: air quality, housing prices, sports, education, the wage gap, crime, life expectancy / mortality, traffic fatalities, etc. Be sure to identify and/or discuss some potential data sources. Generally speaking, students seem to have the most success when using state by year level data. Full credit will be given to students with at least three topics accompanied with both data sources.
This might be a good opportunity to bounce some ideas off of AI. Tell AI that you need to write an econometrics paper and that you’re interested in XYZ. You could also ask AI where you might find some data for your project. In addition, you might want to do a preliminary search for your topics on Google Scholar so you can see what other people have done, find some inspiration, etc. Note that your topic(s) not need be novel, as a replication/extension of another paper would be perfectly sufficient. You might also want to think about current events, too.
An example topic proposal that would satisfy the requirements:
Example Materials
I am interested in looking at country-level success at the Olympics and country-level economic indicators. Specifically, my hypothesis is that the number of medals won by a country is related to the country’s economic characteristics such as GDP per capita, income inequality, and population. I believe stronger economies will perform better at the Olympics, but more income inequality will reduce success. As someone who is interested in both macroeconomics and sports, this seems like an exciting project. The number of Olympic Medals by year and country can be found here: http://www.olympedia.org/countries. I have not yet found GDP per capita nor income inequality, but I found some population data here: https://data.worldbank.org/indicator/SP.POP.TOTL?end=2022&start=1960&view=chart. I am working on getting this data to be in a country-by-year format (meaning each row represents a country in a given year), but I do not have it yet.
Once this topic is approved by the instructor, the student should look to continue their data collection (and manipulation).Checkpoint 3
Data | Week 7 | 20 Points
For this checkpoint, students should submit proof of project data via basic summary statistics, figures, etc. Full credit will be given to students with summary information for the minimum four variables (outcome + three explanatory). Students should expect to work with datasets that are a few hundred, if not a few thousand, rows. Students should submit something like the following (in addition to some writing about the data, their hypotheses, etc.). It would be a good idea to do this within the project template.
Example Materials
Data for this project come from a few sources. First, information regarding each country’s success at the Olympics comes from olympedia.org. Second, data for countries’ GDP per Capita, gini index, and population come from the World Bank. Data are collected for 13 countries over 63 years (1960 - 2022). However, since the Olympics only occur once every four years, I can only keep 16 of the years.
Summary statistics are presented in the table below…
The figure below displays the unconditional relationship between medals won in the Olympics and the GDP per Capita…
Checkpoint 4
Analysis | Week 12 | 20 Points
For this checkpoint, students should submit their written regression equation, estimated coefficients, and interpretations. Full credit will be awarded to students with these three requirements. An example would be as follows:
Example Materials
\[\log(\text{Medals}_{it}) = \beta_0 + \beta_1 \log(\text{GDP}_{it}) + \beta_2\log(\text{Population}_{it}) + \beta_3 \text{Gini}_{it} + \epsilon_{it}\]
- \(\beta_1\): A one percent increase in GDP per capita is associated with a \(\beta_1\)% increase in medals. I expect \(\widehat{\beta_1}\) to be a positive number since I hypothesize that richer countries will perform better at the Olympics.
- \(\beta_2\): …
| Olympic Medals | |
|---|---|
| log(GDP per Capita) | 0.153*** |
| (0.043) | |
| log(Population) | 0.222*** |
| (0.049) | |
| Gini Index | 0.023+ |
| (0.013) | |
| Constant | 3.825*** |
| (0.331) | |
| Num.Obs. | 79 |
| R2 | 0.589 |
The estimate of \(\beta_1\), or \(\widehat{\beta_1}\), is equal to 0.153, indicating an expected increase of 0.15% for each 1% increase in GDP per capita…
Final Project
Final projects must be rendered .html files that are uploaded to an ePortfolio. You may use this final project template to get started. In addition, for some guidance on what your project should look like, check out this sample paper by Dr. Tomas Dvorak. Be sure to include the following:
- Introduction: Motivate and introduce your topic. Convince the reader that this topic/question is important and that they should care. What data do you use? How do you model your outcome variable(s)? What do you find? What is learned from your analysis?
- Literature Review: What work has already been done on this topic by others? What are their conclusions? How is your work different? If your topic is time-sensitive or in the news, you may discuss current events here as well.
- Data: Where does your data come from? Why is this data good for answering your question? Be sure to create, and discuss, a summary statistics table and some plots.
- Empirical Model: Write down the model(s) you estimate. Explain your modeling choices (e.g. log(), etc.). List out your hypotheses and the rationales behind them.
- Results: Discuss the results of your analysis. Interpret the coefficients.
- Conclusion: Remind the reader of your topic, why it is important, and what you find. Be sure to include a discussion of the implications of your findings.
A way to make this project more “fun”: The goal of (most) academic papers is to ultimately answer a question. These papers are (again, mostly) written for an audience of other academics. As an academic myself, I understand that writing in this style probably feels dry or stiff. Students may find it a bit more fun to write their paper as if they were answering their question for a specific person or organization. For example, maybe my paper finds a negative relationship between gasoline taxes and air pollution. Then, I could write my paper like a report for the EPA or Virginia’s current Secretary of Transportation. All of the sections listed above would still need to appear in the final draft, but this might make it more appealing.
Project Rubric
Structure
0 - 20 Points
- The paper is organized into sections with appropriate (sub-)headings and free from formatting issues.
- Writing is free of spelling and grammar mistakes. The style of writing is professional and/or that of an academic article.
- Overall, the paper adheres to norms in the literature. Tables and figures are labeled, referenced works are cited appropriately, etc.
- The paper is uploaded to the student’s ePortfolio correctly and can be accessed easily.
Econometric Analysis
0 - 35 Points
- Data sources are provided and discussed.
- The data used is appropriate for addressing the research question.
- Summary statistics are presented and discussed.
- Visualizations are labeled, informative, and discussed.
- The econometric model should be written out with hypotheses for the coefficient signs given economic theory.
- Results are generated appropriately, and presented in either a table, figure, or both.
- Both the magnitudes and signs of the results should be interpreted. What are the weaknesses of the analysis?
- Technical concepts are effectively and efficiently communicated throughout the project.
Code
0 - 25 Points
- All code is present, easy to follow, commented/documented, and neatly folded. A reader could easily replicate the project using what is described in the text and the code supplied.