33936 LM Econometrics
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Assignment Remit
Programme Title |
MSc Economics, MBF, Financial Economics |
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Module Title |
LM Econometrics |
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Module Code |
33936 |
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Assignment Title |
Econometrics – Empirical Project |
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Level |
LH |
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Weighting |
25% |
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Lecturers |
Dr Marco Barassi & Dr Yi Liu |
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Hand Out Date |
30/11/2023 |
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Due Date & Time |
07/12/2023 |
12pm |
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Feedback Post Date |
19/01/2024 |
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Assignment Format |
Essay |
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Assignment Length |
2500 words |
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Submission Format |
Online |
Individual |
General information
• This coursework accounts for 25% of your final mark.
• The coursework is an individual piece of work. You are required to write your own answers and cannot work jointly. All submissions will be routinely checked for plagiarism. [Plagiarism Policy]
• The deadline for the submission of the coursework is 7th December 2023 by 12:00:00 (12 noon).
• The coursework must be submitted via Canvas in pdf format.
• The coursework should not be longer than 2,500 words.
• Figures do not count towards the word limit. Copying and pasting Stata output (except for graphs and figures) is not acceptable. You should create properly formatted tables.
• An Appendix should be attached at the end of the essay that will contain the Stata commands used to obtain the results. The Appendix does not count towards the word limit.
How to do well
• Perform the appropriate quantitative analysis. Investigate the structure of your data set and think carefully which methodology and which variables you are going to use.
• Perform statistical tests to support your results and empirical approach if needed.
• You might use tables and graphs to develop and justify your empirical strategy.
• Present your tables clearly, provide a detailed and thorough analysis of all the findings (without going over the word limit) and discuss whether they are precise or not.
• Submit a well organised and detailed Stata code.
• Submit a piece of work that is well written, with no typographical or grammatical mistakes, well organised and well formatted.
Assignment
A The effect of Seat Belt Use in the United States. [50%]
The data set SeatBelts.dta contains a panel of data from 50 US states for the years 1983 to 1997. Develop an empirical strategy to explain the effect of seat belt use on fatalities in this sample. Explain and justify your strategy carefully, then implement the strategy. Present tables with your results and discuss your findings.
B Inflation Rates. [50%]
The data set Quarterly_Macro_US.dta contains multiple macroeconomic variables for the United States at a quarterly basis between 1963 and 2017. Develop an empirical strategy for explaining inflation based on the price index for personal consumption expenditures. Based on the sample period of 1963Q1 and 2017Q4, use your model to forecast inflation in the first quarter of 2018. Explain and justify your strategy carefully in the light of the underlying theory of Time Series Econometrics, then implement the strategy. Present tables with your results and discuss your findings.
Module Learning Outcomes:
LO 1. Demonstrate systematic knowledge and understanding of econometric methods and tools and their application to specific problems.
LO 2. Conduct complex empirical econometric investigations and interpret their results.
Grading Criteria:
A first-class mark will be awarded to students who:
• Perform the appropriate quantitative analysis in each of the problems.
• Provide a detailed and thorough analysis of the quantitative analysis and all the findings, without going over the word limit.
• Submit a well organised and detailed Stata code.
• Submit a piece of work that is well written, with no typos or grammatical mistakes, organised and well formatted.
Feedback to Students:
Both Summative and Formative feedback is given to encourage students to reflect on their learning that feed forward into following assessment tasks. The preparation for all assessment tasks will be supported by formative feedback within the tutorials/seminars. Written feedback is provided as appropriate. Please be aware to use the browser and not the Canvas App as you may not be able to view all comments.
Plagiarism:
It is your responsibility to ensure that you understand correct referencing practices. You are expected to use appropriate references and keep carefully detailed notes of all your information sources, including any material downloaded from the Internet. It is your responsibility to ensure that you are not vulnerable to any alleged breaches of the assessment regulations. More information is available at https://intranet.birmingh am.ac.uk/as/studentservices/conduct/misconduct/plagiarism/index.aspx.
2023-12-04