代做ECON5015 Growth And Development代做留学生Matlab编程

日期：2025-11-01 11:23

Assessment Brief 2025/26

Please ensure you read the assessment question or task carefully and fully understand what is being asked.

If anything is unclear or you have questions, please post them on the course Moodle Discussion Forum, and a member of the teaching team will respond directly there.

Assessment Information

Course Code	ECON5015
Course Title	Growth And Development
Assessment Weighting	40%
Question release date	27 October 2025
Submission date:	31 October 2025
Grades and Feedback to be released on:	21 November 2025

Word limit	2 A4 pages
Action to be taken if the word limit is exceeded	Marker will not take into consideration material beyond the 2 A4 pages.

1. QUESTION/ DESCRIPTION OF ACTIVITY

<For assessment other than in-course exams - Please include the full question in this section, ensuring alignment with the relevant course ILOs.>

Type of assessment (e.g., individual, group)	Individual
Assessment Method(s) (e.g., essay, presentation, journal, video, etc.)	Assignment to be completed within a week
ILOs assessment is evaluating	1, 2, 3

Assessment Question:

Growth convergence in theory and in the data

Choose 30 countries (including a mix of developed and developing countries) and calculate their average growth rate per capita over 1975-2024 and over 2015-2024 using the series GDP per capita growth (%) from the World Development Indicators (https://databank.worldbank.org/source/world-development-indicators#). Then present scatterplots of the growth rates for each of the two periods plotted against initial per capita GDP (for 1975 and 2015, respectively). Describe the emerging patterns of differences in growth rates between countries and between periods. Explain how growth models predicting convergence can help us understand these patterns and why these models may not be sufficient to provide a full explanation of the factors driving growth. Note that to answer this question, you will need to provide a critical summary of key model relationships and predictions. Briefly explain whether the empirical patterns capture causal factors that can underpin convergence and use your arguments to draw conclusions about whether the empirical exercise undertaken is a valid test of the theoretical mechanisms in the relevant models of convergence.

Notes and additional specifications.

1. The assignment should not be more than two sides of A4 paper. If you decide to use a computer for written parts of the assignment, make sure to use A4 paper, a font size 11 (14 for the title and student number, 10 for captions/notes to figures) and 2.54 cm margins on all sides.

2. The presentation of the figures is very important. They should provide the reader with all the necessary information on what is shown, without having to read the text. Thus, figure captions should include information on data sources, description of variables used and of relevant methods to construct the variables plotted. An informative title, axis labels and legends are also important.

3. When working with the growth rates, it is fine if there are missing years for some periods. Use the average over the available years per country. If the first year of GDP per capita is missing, use the closest year available.

4. You should only need to use Excel to prepare (i.e. to “clean”) the data and to make figures. If you want to use another piece of software, this is fine, but the same standards in terms of analysis and quality of presentation will apply.

5. Do not show the data that you have downloaded (but do keep them for your records). State clearly in the captions to figures which countries you have chosen and cite the data source.

6. Take screenshots of the final Excel spreadsheet, with the cleaned data, and containing only the data you use for the plots. Attach this screenshot at the end of your assignment. If you do not use Excel, make sure to attach equivalent screenshots.

7. You may find it useful to present key relevant equations of the relevant models in your presentation, but you are not required to do so. If you do, make sure to define all symbols and explain all quantities used.

8. You do not need to review/cite additional literature. Reading additional literature (examples of which are on the Reading List for the course) to help your understanding is fine and, if used to support your analysis, it should be cited. However, using/referring to the literature broadly will not improve the grade. References should be provided in a Reference List at the end of the document; this list counts towards the 2-page limit. You do not need to list the lecture notes or textbook as references.

9. Do not copy equations, figures or other material directly from any other source. Create your own version instead, explaining what is shown and how it is created.

10. On the use of AI. You should not need to use generative AI to support your work for this assignment. If you decide to use generative AI for any aspect of the assignment, there are specific requirements on its use that you need to follow.

1. You may want to use AI as a general support tool for understanding the material in lectures and tutorials, e.g. to help with understanding some concepts that appear in the assignment, or perhaps to provide you more context/background to aid understanding. However, using AI is not required and, if you do use AI in this way, you need to very carefully critically evaluate what is generated to ensure it is useful and relevant. You should be particularly careful because it will likely provide too broad material that may not be directly relevant to the specific questions you are asked to answer in your report. The analysis in the assignment is not a generic essay; instead, you should ensure that your written analysis addresses the very specific points described above. Broad and unfocused material that is not directly relevant (which AI is likely to produce) will negatively affect the relevance of your submission with respect to the parts in the report you need to address.

2. AI tools may also be used to improve your writing (check grammar and syntax, paraphrasing or shortening). AI tools need to be used with care because this process can lead to changes of substance to the text and you need to carefully check that key points have not been missed or distorted. Using AI tools in this way does not guarantee the required clarity in the context of the report.

3. Whenever, and for whatever reason, AI tools are used, it is required to acknowledge this use. Add a short description at the end of the report (within the 2-page limit) to briefly explain the use of AI, in which parts of the report and for what purpose.

4. Importantly, although you are asked to acknowledge AI tool use (if used), making a “reference” to an AI tool cannot serve to support the points that you make in your assignment, and must be provided only as an acknowledgement of the use of these tools. Specifically, the output from AI tools cannot be used as evidence directly, although it can be used to identify sources (e.g. research articles or books) that you can then use to support the points that you make. If you have developed/written an argument based on information you acquired from using AI tools (in addition to using lectures and textbook or other readings), then you need to explain the argument as you understand it, citing the relevant primary published sources. That is, you should not cite AI as evidence on a point you want to make, but instead find, read and cite the original sources.

In-Course Exams only, please enter the minimum assessment information in the table below. The format of the exam (e.g. MCQ; written) should be included in ‘Other Exam Preparation Advice. This data will be shared with students on receipt of this form. and in advance of the exam. The Exam Paper will not be shared with students prior to the exam date.>

In-Course Exam Assessment Information

Number of questions in exam (total)
Number of questions to be answered
Weighting of questions
Other Exam Preparation Advice

2. ADDITIONAL INFORMATION FOR GROUP ASSESSMENT

the groupwork policy. Please consult the Group Work Toolkit and include information regarding:>

Number of students per group	Pre-populated from the A&F Calendar
Arrangements for forming groups (random allocation or self-selection)	Pre-populated from the A&F Calendar
Is peer evaluation used? If so, when during the course, and for what purpose (e.g. assessing progress; formative feedback, or contributing to marking)
How will the group work be supported? (e.g. check-in points, formative feedback, scaffolding, student portfolios, required number of meetings with minutes, etc.)
How will teamwork skills (as distinct from group work output) be assessed?

3. ASSESSMENT RUBRIC/ CRITERIA

This document contains the dimensions that the assignment must address and a description of features of the answer that are excellent/very good/good/satisfactory/weak/poor with relevance to that dimension. This description is based on the Instructions accompanying the assignment topic.

Dimensions	Excellent features of the answer with respect to relevant dimension	Very Good features of the answer with respect to relevant dimension	Good features of the answer with respect to relevant dimension	Satisfactory features of the answer with respect to relevant dimension	Weak features of the answer with respect to relevant dimension	Poor features of the answer with respect to relevant dimension
Empirical analysis and presentation of results (20%)	Data are used correctly. The presentation of results is clear and as per instructions (including relevant captions). Data sources are cited, and datasets with calculations are included with the submission as screenshots as relevant and as per instructions.	Overall correct, with minor elements that are unclear or incorrect; presentation that needs improvements, captions do not provide all required information with sufficient clarity.	Partially correct, with elements that are unclear or incorrect; presentation that needs significant improvements, captions do not provide the required information with sufficient clarity, and/or include irrelevant material; choices regarding data not documented appropriately (e.g. data sources missing); and/or datasets and calculations not clearly shown in attached screenshots.	Overall analysis in the right direction, but with many and/or important incorrect elements; substantive failure to follow instructions properly; presentation that is of insufficient quality, not following instructions.	Minimal engagement with the dimension; fundamental errors; little relevance of the analysis for the dimension.	Very little to no engagement and relevance/correctness of the answer.
Description and interpretation of empirical results (15%)	The patterns seen in the data analysis are described correctly and interpretations of the empirical findings are relevant; the analysis is complete; the analysis is written with clarity. If used, AI tools are correctly used and acknowledged.	The patterns in the data are described with minor errors or not very clearly. The interpretation of the empirical findings, although overall correct, include points that are incorrect or incorrectly explained; while overall it is possible to follow the logic of the written analysis, writing should be improved. Minor problems with use/acknowledgment of AI tools.	The patterns in the data are described with small errors or without sufficient clarity. The interpretations of the empirical findings include points that are incorrect or incorrectly explained; the analysis and/or writing requires more clarity in terms of expression and structure. Problems with acknowledgment of AI tools; some incorrect use of sources/AI.	The patterns in the data are described with errors or omissions suggesting problems with understanding the relevant concepts. The interpretations of the empirical findings include errors or omissions demonstrating substantial problems with understanding the relevant concepts; better writing is essential. Substantial problems with use/acknowledgement of AI.	Minimal engagement with the dimension; fundamental errors; little relevance of the analysis for the dimension. Inappropriate use of AI.	Very little to no engagement and relevance/correctness of the answer.
Models of growth and convergence and comparison of their predictions relative to the data (45%)	The analysis uses and explains correctly the main theoretical predictions from relevant growth models predicting convergence and explains which aspects of the patterns in the data are consistent with them, which are not, and which might be better explained by different models. The analysis is complete and covers all relevant points. The analysis is written with clarity. If used, AI tools are correctly used and acknowledged.	Most arguments are correct and correctly explained; the analysis is incomplete or excessively long (including not directly relevant points); while overall it is possible to follow the logic of the written analysis, writing should be improved. Minor problems with use/acknowledgment of AI tools.	Some arguments are incorrect or incorrectly explained; the analysis is partial, missing key relevant points or providing insufficient explanations; writing requires more clarity in terms of expression and structure. Problems with acknowledgment of AI tools; some incorrect use of sources/AI.	Many arguments are incorrect or incorrectly explained, with errors or omissions demonstrating substantial problems with understanding the relevant concepts; the analysis misses key relevant points or states points instead of providing explanations. Substantial problems with use/acknowledgement of AI.	Minimal engagement with the dimension; fundamental errors; little relevance of the analysis for the dimension. Inappropriate use of AI.	Very little to no engagement and relevance/correctness of the answer.
Correlation or causation in the theory and in the data (20%)	The analysis explains correctly whether or not the empirical patterns likely reveal causal relationships and whether they can be considered a test for the theoretical predictions. The analysis is written with clarity and remains brief, focusing on arguments relevant to the specific problem. If used, AI tools are correctly used and acknowledged.	Most arguments are correct and correctly explained; the analysis is incomplete or excessively long (including not directly relevant points); while overall it is possible to follow the logic of the written analysis, writing should be improved. Minor problems with use/acknowledgment of AI tools.	Some arguments are incorrect or incorrectly explained; the analysis is partial, missing key relevant points or providing insufficient explanations, or rather vague and generic and not well focused; writing requires more clarity in terms of expression and structure. Problems with acknowledgment of AI tools; some incorrect use of sources/AI.	Many arguments are incorrect or incorrectly explained, with errors or omissions demonstrating substantial problems with understanding the relevant concepts; the analysis misses key relevant points or states points instead of providing explanations, or errs on a generic analysis of causality. Substantial problems with use/acknowledgement of AI.	Minimal engagement with the dimension; fundamental errors; little relevance of the analysis for the dimension. Inappropriate use of AI.	Very little to no engagement and relevance/correctness of the answer.

4. FEEDBACK METHOD

For this assessment, individual feedback will be provided via Moodle.  Generic (class-level) feedback and grade profiles will be posted on Moodle. Students can use academic staff office hours for additional feedback on your work.