Econometrics

ECO 625: Final Project Document

Overview

Economists are called upon to apply mathematics and statistical methods to economic data in order to identify the effects of events, policies, or particular actions. In the previous econometrics course (ECO 620), you practiced using regression analysis, which is useful but has some serious limitations and is not appropriate in many settings. As an economist, you will often be asked to analyze data that has serious nonlinearity or is not normally distributed, and you must be able to rise to this challenge. In order to practice the skills involved, you will create a final project in which you will prepare an econometric analysis of a business, policy, or economic issue of your choice, utilizing advanced methods studied in this course (forecasting, nonparametric analysis, maximum likelihood, and so on). You should choose a topic of personal or professional interest to you. You may revisit the topic you selected in ECO 620 or choose a new topic. A literature review of peer-reviewed publications will be necessary in order to familiarize yourself with possible ways to address the issue empirically, using advanced econometric methods. You will build an empirical model to analyze the issue and use the data to conduct econometric analysis. You will then explain your findings to both technical and nontechnical audiences. The project is divided into two milestones, which will be submitted at various points throughout the course to scaffold learning and ensure quality final submissions. These milestones will be submitted in Modules Three and Six. The final project will be submitted in Module Nine.

Outcomes This assessment will evaluate your mastery with respect to the following course outcomes:

 Develop empirical strategies based on available data and limitations of related econometric regression models

 Defend the relevance of econometric technique selection when solving economic research questions

 Execute diagnostic and adjustment processes through statistical software that avoid common problems in advanced econometric techniques

 Interpret limitations of advanced econometric techniques for their effects on the validity of research results

 Produce actionable insights for addressing business issues based on statistical and economic significance of results in advanced econometric analysis

 Communicate empirical processes and results of advanced econometric models to technical and nontechnical audiences that inform future actions

Prompt This final project requires you to prepare an econometric analysis of a business, policy, or economic issue of your choice, utilizing advanced methods studied in this course. Specifically, the following critical elements must be addressed:

I. Description A. What issue are you addressing? Why is your research question relevant to the study of economics? B. Identify the target audience(s) for your paper. Is each audience technical or nontechnical? (For example, are they general readers, managers, or

political decision makers?) Why would your research be relevant for the audience(s)?

II. Literature Review A. What economic methods and techniques have been used to study this issue or a similar one? How has the issue been addressed

econometrically? Were these methods and techniques the most appropriate ones for this study? Why is regression unsuitable for this task? B. What are the hypotheses you plan to test? How do they translate to empirical models?

III. Data

A. What data will you use in your empirical work? What is the source of your data? Why is this particular data set appropriate for the study? B. What does your data look like (e.g., summary statistics, scatter plots, etc.)? What relationships can be gleaned by simple data screening? What

are the implications of these relationships? C. What limitations could your data impose on the choice of empirical method? What are the effects of these limitations?

IV. Empirical Approach

A. What empirical method(s) do you propose and why? Why is this method most appropriate and preferable to simpler models, such as regression? B. What are the limitations of your proposed empirical method? What are possible alternative advanced methods that can be used? Be sure to

address causes for these limitations, such as problems with the data or with interactions between variables. C. What is your model specification? What functional form of data do you use and why?

V. Results and Robustness

A. What are your preliminary results from baseline estimations in the statistical software? What is their relationship with the original hypothesis and research question? Is there a difference between the baseline estimation and the ultimate choice of the model? Discuss.

B. Which violations of the chosen model’s assumptions do you anticipate? Which diagnostic tests do you employ to check for presence of violations of model assumptions?

C. What are your secondary results from your test run through the statistical software? Interpret these test results and determine the presence or absence of problems.

D. Are your results affected by the corrections? Are they affected in a significant way (e.g., change of sign of coefficients or change in statistical significance)?

E. Are your results statistically significant? Are they economically significant? Are some variables more significant than others? How does this relate to the original hypotheses and research questions? Discuss.

VI. Conclusion and Recommendations A. What are your actionable insights and/or recommendations based on your results? Why was it necessary to use advanced techniques to

estimate them? B. What are the overall results of your study? Summarize any limitations, caveats, and possibilities for further actions by your audience. Remember

you are presenting this information to decision makers and other key stakeholders. Be sure to keep nontechnical audiences in mind.

Milestones Milestone One: Research Question, Literature Review, and Data In task 3-1, you will submit a two- to three-page paper on the research question, literature review, and data for your final project. This milestone will be graded with the Milestone One Rubric. Milestone Two: Approach and Results In task 6-1, you will submit a two- to three-page paper on the approach and results you will discuss in your final project. This milestone will be graded with the Milestone Two Rubric Final Project Submission: Econometric Analysis Paper In task 9-1, you will submit your final project. It should be a complete, polished artifact containing all of the critical elements of the final project. It should reflect the incorporation of feedback gained throughout the course. This submission will be graded using the Final Project Rubric.

Final Project Rubric Format: Your submission should be 10 to 12 pages in length (not including title page and references) and should use double spacing, 12-point Times New Roman font, one-inch margins, and citations in APA format.

Critical Elements Exemplary (100%) Proficient (90%) Needs Improvement (70%) Not Evident (0%) Value

Description: Relevance Meets “Proficient” criteria and provides compelling examples to illustrate the relevance of the issue

Outlines the issue in a clear manner, explaining how the topic is relevant to the study of economics

Outlines the issue and explains how the topic is relevant, but the issue is vaguely defined or explanation of why the issue is relevant to the study of economics lacks in detail

Does not outline the issue or does not explain how the topic is relevant to the study of economics

2

Description: Target Audience(s)

Meets “Proficient” criteria and describes the implications that the choice of audience will have on the structure of the paper

Identifies the target audience(s), the associated level of expertise, and why the research is relevant to each audience

Identifies the target audience(s) but fails to identify either the level of expertise or why the research is relevant to each audience

Does not Identify the target audience(s)

2

Literature Review: Methods and

Techniques

Meets “Proficient” criteria, and summary is comprehensively detailed

Summarizes economic methods and techniques used and how the methods were employed, and evaluates the model’s appropriateness, including why the regression model is unsuitable

Summarizes economic methods and techniques used and how the methods were employed but does not evaluate the model’s appropriateness and the unsuitableness of the regression model, or the summary does not adequately discuss the main feature of the models

Does not summarize economic methods and techniques used or does not define how the methods were employed

7

Literature Review: Hypotheses

Meets “Proficient” criteria and explains the translation by tying it back to the overall issue

Clearly sets up testable hypotheses and explains how they translate to empirical models

Sets up testable hypotheses but does not explain how they translate to empirical models

Does not set up testable hypotheses

5

Data: Source Meets “Proficient” criteria and discusses possible issues and biases in the data, based on the data source

Identifies the data and data source to be used in the study and explains the appropriateness of the data to this study

Identifies the data set but does not provide background on the data or does not explain the appropriateness of the data to this study

Does not identify the data set, or the identified data set is not usable

5

Data: Relationships Meets “Proficient” criteria and discusses what might be influencing the relationships observed and why these initial findings might be misleading

Summarizes the data utilized in the study, including the type of data, and details the relationships existing between main variables, as well as their implications

Summarizes the data utilized in the study, including the type of data, but does not detail the relationships existing between main variables or their implications

Does not summarize the data utilized in the study

6

Data: Limitations Meets “Proficient” criteria and supports discussion with scholarly research

Identifies limitations of the data structure on the choice of empirical methods and details the effects of these limitations

Identifies limitations of the data structure on the choice of empirical methods but does not detail the effects of these limitations, or discussion misses key limitations

Does not identify limitations of the data structure on the choice of empirical methods

6

Empirical Approach: Method

Meets “Proficient” criteria and explains the reasons for the superiority of the chosen method(s) over other methods

Proposes advanced empirical method(s) to use in the study and clearly defends method(s), stating the considerations leading to the choice, including why simpler models were not employed

Proposes advanced empirical method(s) to use in the study and defends these method(s) but does not address considerations leading to the choice, or defense of proposed methods is lacking in detail

Does not propose and defend advanced empirical method(s) to use in the study

7

Empirical Approach: Limitations

Meets “Proficient” criteria and supports discussion with scholarly research

Identifies limitations of the proposed model, delineating between issues with the data and interactions between variables, and addresses the appropriateness of alternative methods/models

Identifies limitations of the proposed model but does not delineate between issues with the data and interactions between variables or does not address the appropriateness of alternative methods/models

Does not identify limitations of the proposed model

5

Empirical Approach: Specification

Meets “Proficient” criteria, and justification is supported through research

Outlines the empirical approach in a clear manner, providing specifications in the form of an equation and justifying the transformation

Outlines the empirical approach but does not provide specifications in the form of an equation or does not justify the transformation

Does not outline the empirical approach

7

Results and Robustness:

Preliminary Results

Meets “Proficient” criteria and discusses any counterintuition in the results or possible inconsistencies

Utilizes statistical software to produce an initial report of results, details those results, and determines the relationship of the results to the hypothesis and research question, disclosing differences in baseline estimation and ultimate choice of model

Utilizes statistical software to produce an initial report of results but does not present those results beyond simple statements of fact or does not determine the relationship of the results to the hypothesis and research question

Does not utilize statistical software to produce an initial report of results

7

Results and Robustness: Violations

Meets “Proficient” criteria, and examination addresses the effects that identified ordinary least squares violations would have on results

Identifies violations and chooses appropriate statistical tests based on initial examination of results

Identifies violations but does not choose appropriate statistical tests to run or employ a complete battery of tests

Misinterprets results of the tests or uses inappropriate tests

8

Results and Robustness: Secondary

Results

Meets “Proficient” criteria, and interpretation is highly specific and detailed

Conducts, interprets, and reports results from secondary tests correctly and determines the presence or absence of problem(s)

Conducts and reports results from secondary tests, but interpretation of test results is limited/incorrect, or the presence/absence of problem(s) is not determined

Does not conduct or report results from secondary tests

8

Results and Robustness: Affected

Meets “Proficient” criteria and provides illustrative examples of impact of changes on overall conclusions

Determines the effects of corrective actions by noting changes (or lack thereof) and the magnitude in coefficients of these changes in statistical significance of key independent variables

Determines the effects of corrective actions but does not note changes (or lack thereof) or does not note the magnitude in coefficients of these changes in statistical significance of key independent variables, or the determination of effects is flawed

Does not determine the effects of corrective actions

5

Results and Robustness: Significance

Meets “Proficient” criteria and provides illustrative examples to underscore relationship of results to original research question(s)

 Evaluates the statistical significance and economic significance of the final results, clearly delineating important and less important variables and tying the results back to the original hypotheses and research question(s)

Evaluates the statistical and economic significance of the final results but does not clearly delineate important and less important variables or does not tie the results back to the original hypotheses and research question(s)

Does not evaluate the statistical and economic significance of the final results

5

Conclusion and Recommendations: Actionable Insights

Meets “Proficient” criteria and provides insight in a manner more relatable to readers, using meaningful changes in variables

 Provides comprehensive and detailed actionable insights or recommendations developed directly from the study’s results, detailing the necessity of using advanced techniques within their identification

Provides actionable insights or recommendations developed directly from results of the study, but insights are not adequately detailed and comprehensive or the necessity of using advanced techniques is not addressed

 Does not provide actionable insights or recommendations developed directly from results of the study

5

Conclusion and Recommendations:

Results

Meets “Proficient” criteria and provides compelling examples to illustrate the main point

Summarizes the overall results of the study, including limitations, caveats, and possibilities for future actions in a nontechnical voice

Summarizes the overall results of the study but does not include limitations, caveats, or possibilities for future actions, or summary is communicated in a technical voice

Does not summarize the overall results of the study

5

Articulation of Response

Submission is free of errors related to citations, grammar, spelling, syntax, and organization and is presented in a professional and easy to read format

Submission has no major errors related to citations, grammar, spelling, syntax, or organization

Submission has major errors related to citations, grammar, spelling, syntax, or organization that negatively impact readability and articulation of main ideas

Submission has critical errors related to citations, grammar, spelling, syntax, or organization that prevent understanding of ideas

5

Earned Total 100%