Mini Paper
Managerial Economics
The objective of this assignment is to give you an introduction into conducting empirical research and presenting the results of that research in a professionally written paper. To carry out this research, you will identify an economic relationship (or a demand equation) between variables that are interesting to you. In your paper, you will describe this relationship and present a lucid argument for the importance of a better understanding of this relationship. And then, collecting appropriate data, you will empirically estimate this relationship along with all of the appropriate goodness of fit tests and statistics. Finally, you will analyze and report the results of your empirical estimation with particular emphasis on how these results are important and useful for a manager of a business enterprise or an economic agent faced with a choice. Your final report must contain the following sections:
a. Brief Introduction – Discuss and flesh out the motivation for the economic relationship you are estimating in this paper. While you do not have to go into lengthy discussions about the underlying economic theory, it should be sufficiently detailed so the relationship you are estimating is made clear to the reader. In this section, you should include a short discussion of the literature. Be sure to tell a story: why do you think your independent and dependent variables are related? While it does not need to be exhaustive, pick three to five papers to frame your research and show how it fits in with prior research. [One way to do this is to tie your hypotheses with prior scholarly research.]
b. Data Description – Give a brief discussion of the data and how/where they were collected. At the minimum, you should note the time range of the data, scales of the data (i.e., data in millions of dollars or thousands of tons, etc.), and any notable events that may be applicable to your data set (such as change in corporate ownership or natural disasters, etc.). Also, you should describe the institutional setting of your data. (E.g., you should discuss the business with an eye towards how some unique industry practices might have an impact on the specific data that you had collected.) Also include a table of basic descriptive statistics for your data. Your description of the data should be aided by carefully drawn, well-labeled charts and figures of your data, and summary statistics of your data.
c. Regression Model and Results – Carefully develop your regression model. You must support your model with a “story” of why the right hand side variables you include are important and/or with the support of the relevant economic theory (including your hypotheses). Report your regression results in an equation form (see the textbook for how this is done) and in table form. Be sure to report all relevant statistics: coefficient estimates, standard error, R2, various test statistics, etc.
d. Discussion and Diagnostic Tests – Carry out all appropriate “goodness of fit” tests and briefly discuss the “fit” of your regression equation. Which form is the preferred: linear or log-linear? Explain your conclusion. Finally, carefully describe what your empirical results are telling you about your hypothesized economic relationship that you had outlined in part a.
e. Conclusion – What does your regression tell you about the demand in the industry? What more can be done in the future?
While there will not be a hard page limit for this paper, overall, this mini report should be ten to twelve double spaced pages long with 1” margins, not including tables and figures.
Please keep in mind that the objective of this mini project is to get your hands dirty working with a data set that is interesting to you. As such, we are not looking to break new theoretical ground – just come up with a simple economic relationship and model it using a simple yet robust regression.
Style requirements: please use either APA or Chicago/Turabian citation styles. For additional citation information, see a librarian or the library’s website.
Due Dates:
4 October: One to two page proposal. This will contain a rough description of what you want to model along with what types of data will be required and how you will obtain them. Note that it is not necessary that you have the data in hand by this date.
1 November: One to two page progress report. By this time, you should have collected most, if not all, of your required data. Describe the data: means, variances, etc. Include a plot of the data.
Your report will, at the minimum, include the following:
Description of the model (including modifications that were suggested from the proposal).
Regression Equation of the model.
Table(s) that describes the data (means, variances, min, max, # of observations).
Figures/plots of the data.
For any data that has not been collected yet, a complete and detailed description of when and where the data will be collected (must include documentation, website, and/or contact information of the (potential) source).
13 December: Final papers are submitted via Chalk & Wire1. This report should contain the five sections described on page 1 along with:
a) Simple cover page
b) References (Three sources minimum, must be in proper format)
c) Appendix (at minimum include excel spreadsheet printout of the regression(s), other possibilities include data description, data sources, etc.)
Grading:
Only the Progress Report and the Final Paper will be graded. The Progress Report will make up 25% of the total Mini Paper Grade while the Final Paper will make up the remaining 75%. Please note that late submissions without prior approval of the instructor will incur a substantial late penalty. A grading rubric follows.
1 For those who are in the MIT program, you can turn in your paper in class.
1
2
3
4
Insufficient
Partially Proficient
Proficient
Excellent
Weight (max %)
Progress Report
Progress report is poorly written and missing multiple parts
Progress report missing a section
Progress report contains all parts but writing is difficult to read or does not contain detailed descriptions
Well written paper includes description of model, regression equation, tables of data, figures and plots, and a description of remaining data to be collected
25%
Data Description
Student does not clearly describe their data.
Data is poorly described and lacking supporting tables and figures.
Data is described, and includes figures, plots and tables. Parts of explanation may be missing
Data is well-written, and includes well-labeled figures, plots and tables as well as well-written descriptions
20%
Economic analysis
Displays clear lack of knowledge and understanding of economic theories and their interpretation.
Uses appropriate economic terminology to describe regression analysis, and diagnostic tests, but does not provide deep analysis.
Incomplete discussion of theories and economic relevance.
Displays superior knowledge of relevant economic theories as well as their interpretation relative to question asked. Places paper into context of the literature and provides the “story” behind the hypotheses. Discussion is supported by regression results, and diagnostic tests.
40%
Grammar
5 or more errors
Several errors (3-4)
Few errors
(1-2)
No errors in grammar, spelling or punctuation
5%
Organization
Paper is poorly organized and difficult to follow; missing multiple parts of assignment.
Paper is mostly organized but difficult to follow at points. Paper is missing multiple parts.
Paper is organized, but missing one part.
Paper is well organized with clear topic sentences and follows a cohesive train of thought; includes all parts outlined in assignment.
10%
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