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ECON213 Econometrics II

Group Project Coursework

1 Requirements

The aim of this coursework assessment is for you (in groups) to investigate factors that may affect the level of income inequality using econometric tools learned in our module. Our week 03 notes is about doing empirical projects.

High marks are awarded for evidence of good understanding of our module materials (weeks 1-8 inclusive) via clear explanation and full justification; advanced econometric techniques are not expected.

We aim to return the marks within three weeks. Please appreciate that it takes time to read, understand, and grade the assessment, and the grades will also be moderated.

1.1 Topic

Explain income inequality using macroeconomic and other variables.

1.2 Format

The coursework will be an independent econometrics project for each group. Each group pro-duces a written group report and each group member completes a related individual online test. The coursework accounts for 30% of the module marks (20% group report plus 10% individual online test).

1.2.1 Report

❼ This is the result of group work - contribution from every member is expected.

❼ The group report must be submitted online through Assignments on Canvas.

❼ The deadline for the group report is by 2pm on Wednesday 20/03/2024 (i.e. academic Week 8).

❼ There is a report template (word file) on Canvas; it contains more information.

❼ The report must have no more than 2000 words, excluding contents page, footnotes, bib-liography and appendices.

❼ The Appendix is to be no more than 10 pages (single-sided, or 5 pages double-sided).

❼ STATA outputs should only appear in the Appendix. Include only the important ones.

❼ The main body of the report should contain summary tables, not raw STATA outputs. As an example, see Table V of Mankiw, Romer and Weil (1992).

❼ STATA outputs should not be included as picture files; they should be included as text.

❼ Equations should be typeset using Equation Editor (in Word) or similar, and not included as picture files.

❼ Effective use of graphs and tables, e.g. clear, informative, complete, consistent

❼ Citations and references are typically in Harvard Format; it is more important to maintain a consistent style throughout.

❼ Use font Arial, size 12

❼ Use double or 1.5 line space

❼ Number the pages

❼ Put footnotes at the bottom of the page

❼ Give full reference to the sources used

❼ Write in Microsoft Word (.docx); could convert it to a pdf file for easy uploading.

❼ Group members receive the same group marks.

1.2.2 Online Test

❼ This is a combined result of group work and individual performance.

❼ Each group member completes an online test independently.

❼ They are multiple choice questions.

❼ The questions are related to the group project and our module materials.

❼ The deadline for the online test is by 2pm on Saturday 23/03/2024 (i.e. academic Week 8).

❼ The test can be taken anytime from 2pm on Wednesday 20/03/2024 till 2pm on Saturday 23/03/2024 (i.e. academic Week 8), but it must be completed within one hour, once started.

❼ Group members receive individual marks.

1.3 Group Selection

❼ Arrange yourselves into self-selected groups.

❼ Each group consists of 5 individuals.

❼ Enter full names (First name Surname; e.g. Yuyi Li) of group members on Google Sheet.

❼ Anyone without a group will be randomly assigned to a group.

❼ Finish group allocations by end of week 3.

2 Guidance and Support

2.1 Variable Selection

❼ Gini coefficient is a typical measure of income inequality (dependent variable).

❼ Table 1 of Sarel (1997) provides examples of variables that may influence the level of income inequality or other aspects of the income distribution.

2.2 Econometric Modelling

❼ Use cross-sectional regression techniques covered in weeks 1-8 inclusive.

❼ Study our week 3 notes carefully and view Chapter 19 of Wooldridge (“Carrying out an Empirical Project”).

❼ Show evidence of understanding our module materials and researching around the topic.

❼ Literature review should be informative and relevant. Start by reading Sarel (1997), which discusses some of the literature and potentially important variables. Then search recent literature by key words (e.g. income inequality) using the search facility at Google Scholar or our university’s Library Search.

❼ Choose and explain the appropriate tools (model specification, estimation, diagnostic tests) with clarity and justification. For instance, if the Feasible Generalised Least Squares is used for estimation, we must clearly explain this procedure (especially the weighting) and justify this choice (e.g. heteroskedasticity).

❼ Diagnostic tests must be performed before checking the significance of individual parameter estimates. In particular, tests should be performed for heteroskedasticity (e.g. Breusch-Pagan test), and correctness of functional form (e.g. Ramsey’s RESET test).

❼ Carefully interpret the estimation and test results, and relate these results to relevant literature if relevant.

❼ Obtain data from Word Bank Data Bases.

❼ This example only demonstrates some important steps. Every group must go through this example, because this will help us start the project, and will also be relevant to our individual online test.

– Follow the world bank data bases link and select “World Development Indicator”

– Select all 217 countries (Country)

– Select variables (Series): Gini index; CO2 emissions (metric tons per capita); Employ-ment to population ratio, 15+, total (%) (modeled ILO estimate); Employment to population ratio, 15+, total (%) (national estimate); GDP per capita growth (annual %); Inflation, consumer prices (annual %); Inflation, GDP deflator (annual %); Net trade in goods and services (BoP, current US✩); Number of infant deaths; Number of deaths ages 20-24 years; Official exchange rate (LCU per US✩, period average); Population, total; Population ages 15-64, total; Unemployment, total (% of total la-bor force) (modeled ILO estimate); Unemployment, total (% of total labor force) (national estimate).

– Select year (Time) 2012.

– Download and save the data in an excel file.

– Remove countries with a missing Gini index (85 countries remain).

– Examine the data (e.g. data quality, basic statistics).

– Explore various models for Gini index (e.g. regressors, functional forms) and perform hypothesis tests (e.g. Breusch-Pagan, Ramsey’s RESET).

❼ Every group can freely choose among countries, series, and time to form our data set in the project.

2.3 Group Consultations

Each group may have one consultation (up to 30 minutes) with a supervisor.

❼ Queries about the coursework requirements, technical problems with the data or STATA software.

❼ No specific detailed advice/suggestions will be given about research avenues.

❼ No reading of drafts or confirming interpretation of results.

2.4 Discussion Board

Post questions and help each other on the Discussion Board on Canvas. I will monitor the discussions and participate when necessary.

3 Resources

❼ Sarel, M. 1997. How Macroeconomic Factors affect Income Distribution. IMF Working Pa-per WP/97/152 (November). Available online at https://www.imf.org/external/pubs/ft/wp/wp97152.pdf

❼ Mankiw, N. G., D. Romer, and D. N. Weil, 1992. A contribution to the empirics of economic growth. Quarterly Journal of Economics 107(May), 407-437.

❼ Google Scholar: http://scholar.google.co.uk

❼ University of Liverpool Library Search: https://libguides.liverpool.ac.uk/online/journals

❼ World Bank data bases: https://databank.worldbank.org/databases

❼ World Bank World Development Indicators (WDI): http://databank.worldbank.org/data/reports.aspx?source=world-development-indicators

❼ STATA official site: https://www.stata.com/

❼ STATA documentation: https://www.stata.com/features/documentation/

❼ STATA notes on Canvas.

4 Marking Rubric

4.1 Structure and presentation (15%)

4.1.1 Excellent

All findings of the report are clearly structured and presented. All arguments are inherently integrated to serve the main message of the report. The abstract is strong and effective, con-taining the essential points of the entire report and clarifying the main findings. All tables and figures included in the report are clearly structured and explained.

4.1.2 Good

The key findings of the report are clear. The abstract is good but not very informative – some key points are left out or the key points are ambiguous. Most tables and figures included in the report are clearly structured and explained.

4.1.3 Needs More Work

The key findings are unclear and the report is not well structured. The abstract is not informa-tive. Tables and figures included in the report are not clearly structured and explained.

4.2 Data analysis (25%)

4.2.1 Excellent

Data is downloaded from appropriate sources. Sufficient statistics for completing the research question are generated and presented in a professional manner. Adequate graphs are used to visualize complex data relationships and statistics. The data sources are clearly acknowledged and the steps of the data analysis are well explained.

4.2.2 Good

Data is downloaded from appropriate sources and necessary statistics for analyzing the research question are provided. Data visualization techniques are used to demonstrate complex data relationships and statistics. Basic explanations on the steps of the data analysis are provided.

4.2.3 Needs More Work

Data is downloaded from inappropriate sources and statistics generated for analysing the research question are insufficient. Some statistics are wrong and inappropriate. Explanations on the steps of the data analysis are very limited.

4.3 Economic models (25%)

4.3.1 Excellent

There are detailed explanations on each variable in the model. Appropriate diagnostic tests are carried out and the tests results are correctly interpreted. Adequate discussion of the model specification(s). Discussions of the model demonstrate a deep understanding of the model mech-anisms.

4.3.2 Good

There are explanations on how the model specification is chosen but reasoning is not adequate or accurate. Attempts on diagnostic test are made but unable to accurately interpret the tests results. Discussions of the model demonstrate an adequate understanding of the model mecha-nisms.

4.3.3 Needs More Work

Attempts are made to use a model to analyze income inequality. However, the results may be unreasonable due to a lack of understanding on the model mechanisms. No tests or inappropriate tests are carried out. There are no discussions on model specifications. The explanations on model mechanisms are very limited.

4.4 Interpretation of results (25%)

4.4.1 Excellent

A thorough discussion on the mechanism of the model and explanation of the underlying eco-nomic reasoning is provided. The assumptions and the limitations of the model are clearly explained. The discussion is able to go beyond the basic model interpretation and touch upon the other possible economic impacts. Students getting high marks are expected to provide policy implications, e.g. how policy can intervene income inequality.

4.4.2 Good

The discussion clearly explains the mechanism of the model and the underlying economic reason-ing. However, it is limited to basic model interpretation. The other possible economic impacts and how policy can intervene is not discussed.

4.4.3 Needs More Work

The discussion fails to explain the mechanism of the model and clarify the underlying economic consequences. There is no discussion on other possible economic impacts beyond the basic model interpretation and how policy can intervene is not discussed.

4.5 Reference to the literature (10%)

4.5.1 Excellent

References for the key findings and contributions in the relevant literature are provided. An in-depth comparison between the key results of the report and those found in the existing studies is discussed.

4.5.2 Good

Some discussions on the existing studies are included. Attempts to compare the results with those in the existing studies are made. While the comparison may not be very precise in some cases, the overall direction of the student’s interpretation is correct.

4.5.3 Needs More Work

No discussion on the existing literature. The references are either wrong or irrelevant.