Applied Econometrics Independent Research Project

Choose a topic and hypothesis of your choice, find an appropriate dataset, estimate a regression model,

and present your model and results in a short essay. Interpret your model in light of the assumptions

you are making when estimating regression models. You can choose any topic or dataset that might

interest you. If you need some inspiration, https://ourworldindata.org/ has fascinating long-run datasets,

there is also a list of many datasets already included in R here:

https://vincentarelbundock.github.io/Rdatasets/datasets.html, but you are welcome to use any data to

answer any question you are interested in (for example: does smoking affect babies’ birthweight? Does

rainfall increase ice cream sales? Has the introduction of airbags/seatbelts lowered car accident deaths?

Has the BC carbon tax lowered CO2 emissions? etc.).

Present your results in the form of a short written essay (maximum1 length of 2 pages + references).

The project has to be submitted via CourseSpaces by October 24th, 7pm, as a PDF document.

The essay should follow a coherent structure, such as the one suggested below. Sample Structure:

1) Introduction

Stating your hypothesis, explain why this topic is important and interesting and what related

literature already exists.

2) Data

Describe your data (including sources and descriptions of variables), perhaps including a

Figure.

3) Methods

Stating your estimated model (ideally as an equation), justify the functional form you choose

(log, etc.) and what assumptions you make.

4) Results

Showing your estimated model results in a Table including: coefficients, standard errors,

number of observations, and R-squared (see below for an example in Table 1). Interpret your

results carefully, conduct and interpret hypotheses tests (individual and perhaps joint).

Table 1: Estimation Results Dependent Variable = log(wage)

Intercept 1.02 (0.52)

Experience 0.55 (0.33)

Experience2 -0.05 (0.03)

Education 0.72 (0.23)

Number of Observations 342

R-Squared 0.76

Standard errors shown in parentheses.

5) Conclusion

Summarise your results and discuss what you conclude based on your findings.

6) References

References to the literature and data used.

1 Brevity is a skill – it is important to be able to convey ideas in a concise manner. Excessive length is therefore

discouraged and will be penalised by -5% per page over the limit.

2

The essay will be assessed based on the following criteria:

1. Structure & Presentation

a. Is the research questions clearly defined?

b. Is the paper clearly structured?

c. Are the results presented clearly, with standard errors reported, all Figures labelled,

are regression results shown in a Table?

2. Technical Correctness & Interpretation

a. Is the interpretation and estimation technically correct?

b. Are the results discussed and interpreted carefully?

3. References & Clarity

a. Are data and relevant literature properly referenced?

b. Is the paper written coherently?

4. Length:

a. Is the paper within the two-page limit (excluding references)? (-5% per page over

limit)

A note on plagiarism: this research project constitutes independent work. You must reference any

literature you cite and any data and methods you use. Review What is Plagiarism for the definition of

plagiarism. The consequences of plagiarism range from a failing grade for an assignment or course to

disciplinary probation or even expulsion from the university. UVic’s policy on academic integrity

provides more information about the consequences of plagiarism and other forms of cheating.

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