The dataset they will use for their projects, and its detailed description, which is expected include:the source of the dataset
The list of the potential variables that will be used, their measurement units, units of observation, and description of the listed variables as provided by the source
summary statistics (min, max, mean, median, and standard deviation of the variables, and correlations in between all variables they will use for their analysis)
any problems or unexpected findings they see with the summary statistics and/or sample (if any) Where to find data? Some data sources that may help:
i. R package titled: “Wooldridge” has the datasets of our textbook, and you may use the ones that we don’t use for our homework assignments The datasets that you are not allowed to use for your projects are listed under the Canvas folder DATASETS. (An announcement will also be shared about this option, and the related Canvas assignments’ description sections will also list this information.)ii. IF you collect data outside the ones of our textbook; however, I may give you extra points for extra data effort (please also see below for further notes on grading of the final project report). For that, some sources that may help are:o https://www.aeaweb.org/resources/data/u s-other-datao https://libraryguides.unh.edu/Econ726 oFinal Project Report (80 pts)Students are expected to submit an electronic copy of their project reports, as well as the code and data that they used in their projects (via the related Canvas assignment as well as via email) latest by the stated deadline (see the Canvas course calendar for the related deadline).Please note that failure to successfully submit the final project reports, latest by the stated deadline, will result in the grade weight of project being added to that of the final (A full project grade of zero, mentioned at any point on this document, means that the grade weight of project being added to that of the final except for the case of plagiarism. In the case of plagiarism, student will get an F automatically, and further disciplinary action will be taken).
No extensions are going to be given. It is also absolutely the students’ responsibility to make sure that the instructor receives the correct copy of the final project report, on time. (Failed email deliveries for any reason, forgotten or incorrect attachments, non-readable assignments, etc. are all going to be considered as a no submission. Please also see the main syllabus for examples of unsuccessful submissions.)FINAL PROJECT REPORT (Deadline is listed on the Canvas calendar of the course)Min. 2000, max. ~5000 words (excluding figures, tables, etc.)
Project Report is required to include all of the following four sections, with each one explaining the listed at minimum, and it is expected to be one coherent paper that embodies all of these four sections. And, as an attachment to the project, students also are expected to share their code (or spreadsheets if they are using Excel), and the data that they used in estimation.
SECTION-1 (10 pts)Project report’s introduction
Research question and reasoning o Any research, and related reading
o Connection of the research question to Economics (or the related discipline), and reasoningData and model descriptiono Description of the variables, and the equation(s) to be estimated
Description and discussion of the dataset in connection with the research questiono Summary statistics and discussion of the data and the sample
Identification and discussion of unexpected/problematic data properties (if any), and proposed/applied solutions
SECTION-2 (10 pts)
Regression Analysis (at least one multiple linear regression model must be estimated to be able to get a grade above zero)
Interpretation of estimates/findings in connection with the research question, and discussion of the findings
Identification and discussion of unexpected/problematic results
SECTION-3 (40 pts)
Assumptions made for the methodology to work, given the research question and the related data
Any possible violations of these assumptions and their implications for the model and results
o Here you are expected to explain possible violations intuitively,i.e., explain what your expectations are (NOTE: Almost all of thedatasets at least have one problem, and usually more)o For each possible violation, you are expected to explain whatthat means for the estimators and estimates you useo Perform formal statistical tests, where possible/applicable, inthe Section 4 below.
SECTION-4 (20 pts)Discussion, and, where possible, application of (potential) solutions to the identified problems in sections 2 and 3, if any, and discussion of the related results (if any)
Significance tests per each coefficient estimated, and the discussion of these tests’ results
Any additional hypothesis in connection with the research question, and their tests. And, any other statistical tests, which are relevant for the project question, assumptions, and/or results. o For any tests conducted, students are required to state the hypotheses that are being tested, the statistic, related distribution or test’s name, as well as how they reach the decision.
Discussion of proposed solutions to the identified problems in sections 2 and 3, if any
Project report’s conclusionPoints possible for Final Project Report: 80 pts (+ max. 10 pts bonus possible) Grading Notes:
The biggest percentage of the points will depend on thecompleteness, and the quality and clarity of explanation of theitems listed per each section above and the relatedindependent econometric analysis required/used.
The following will also be checked, in general, while grading thesections listed above.Quality of the data and its source(s)
Replicability of (all of) the results in the project report using the code and data to be provided by the student latest by the stated deadline (points are going to be deducted if the provided code and data doesn’t replicate the results completely and clearly, without errors)
Quality, clarity, and use of research and relevant academic sources (i.e. academic journal articles, books).
Quality, clarity, and correct use of writing, tables, and figures
+5 pts (max) possible bonus for above and beyond work (if any)
+5 pts (max) possible bonus for extra data effort (if any) Notes:
Requirements:
