The key points of conducting the coursework:
It will entail an empirical investigation of a research question, and the result will be a computer based written assignment. The Software: R (www.r-project.org/) should be used to analyze data and run regressions. The paper will involve an “original” empirical work, as well as a critical reading of a few pertinent references related to the research question.
It must not exceed 1,000 words in length, everything inclusive. Make sure to use double-spacing and font 12 throughout. The Appendix, if applicable, is counted within the word limit, and should only contain auxiliary information that is not essential for the report. The marking of the report will be based on the main text. The R codes may be checked, but will not be marked. The paper structure must conform to the requirements (to be discussed in detail below).
Your data, research question and tasks
Please download and open the ZIP file named “Data_Allocation.ZIP” from the “Resource” area of the Course website. Then extract and use the data file whose name is the same as your student ID number to do your coursework. Note that every student has a unique dataset. The meanings of variables in your dataset are explained in the data description file named “data_description.xlsx” in the Resource area.
You are given a random subsample of the data collected from a survey of second year university students’ life. The information contained in the data is extracted from the survey questions, from which you are able to see how each variable is defined:
• Personal information;
• Life style;
• Family background;
• Academic related information;
• Other information.
You are free to choose areas or topics to conduct your empirical analysis according to what interests you and where your background knowledge may lie about student’s life. Whatever you choose, the final report should have a coherent idea or story, supported by the evidence you will produce using the given data. For example, you may want to investigate how students’ first year performance is determined. You may also want to examine a specific aspect of the performance determination, such as the relationship between one’s academic performances with his life style, or how one’s academic effort may affect his final results. Fully discuss your empirical findings, compare your findings with literature (either theoretical predictions or empirical results from previous research), and draw implications based on your results.
To score top marks, the research questions need to be clearly stated and well motivated, the modeling framework should be well explained; the econometric specification should be well justified; the discussion of the data set should be sensible; the econometric estimates should be correctly interpreted and statistical inferences need to be discussed; the relevant regression diagnostics should be conducted, potential econometric issues need to be considered and tested, and the empirical implications of the results should be carefully discussed. Finally the limitation of your research and future research direction should also be pointed out. Put simply, a high standard of an empirical analysis is expected.
Writing guideline of an econometric analysis project
In the following paragraphs a general guideline as to how the written work can be organized is given. Below each section title, examples of what might be included are listed. You are expected to follow this structure, but small variations are allowed.
Section I: Introduction
• Briefly describe the purpose of the study by specifying your research question(s) and focus, and how you intend to conduct it.
• Try to convince the reader why your work is interesting/worth doing and your research findings are important and relevant.
• Relate your work to some existing study if you can find any, or describe how it fits into the existing literature.
• Outline the structure of the paper.
Section II: The Conceptual framework
• Discuss in detail the theories or rationales that underlie the relationship you wish to study.
• Review some of the relevant literature (theoretical or empirical or anecdotal).
• Provide the background of the study you are conducting if necessary. For example, since the sample is taken from the university students, is there anything specific about this cohort that may be relevant to your analysis?
• Describe your prediction of the relationship that you are studying.
Section III: The Data and methodology
• Describe the source(s) of the data and how each variable is measured. Discuss the ways important variables can be defined.
• Provide an exploratory data analysis. Point out any salient features of the data, and describe any interesting pattern or correlation of different groups in the data. Provide summary statistics and discuss your findings.
• Specify the regression model, and discuss why such a specification is adopted, for example, why each of the explanatory variables is included, and describe their anticipated effect (either based on theory, previous empirical work, or your rationale). A formal presentation of an empirical model with full explanation of your notation is useful.
• Discuss the estimation strategy you adopt, the potential econometric issues that may be relevant and how you plan to deal with them. Also discuss any estimator, tests and approaches you intend to apply to support your arguments in your analysis.
Section IV: Econometric results
• Discuss any estimation issues that are encountered in your estimation process, if not previously mentioned.
• Present properly the econometric estimates, and evaluate the model performance in terms of goodness of fit and diagnostic tests.
• Interpret the estimated coefficients, and describe whether they correspond to your expectations?
• Discuss the results of other specification tests, hypothesis tests, robustness analysis (if you have conducted any) and report your findings.
• Does the estimated equation support the theory on which it is based or the rationale in your mind? What explains any discrepancy between theory and empirics?
• How do the results compare with existing findings? What new insights your results have added?
• Note that original R outputs are NOT allowed to appear in your written report. If you would like to present the results from the R software, you should make your own table, only keeping relevant information, and you should explain explicitly what you wish to demonstrate in the table.
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