ECON0050, 2023-24 Term 1
Individual Take-Home Essay
65% of module final mark, due Fri., 15 Dec. at 17:00 London Time
The essay is your chance to tie together themes from across the module and simultaneously
dive deeper into the real-world topics that most fascinate you. The best essays will support
their arguments by drawing on theoretical models from lectures and real-world examples as well
as the academic economics literature and our guest lectures. We hope this coursework will not
only be a chore you’re forced to complete but also an exciting chance to think about the real_xFFFE_world applicability (or lack thereof) of what we’ve taught you! Please read the entire instructions
carefully before beginning work on your essay.
Prompt
Please write an essay responding one of the following three questions. Do not attempt to
answer multiple questions in the same essay.
1. Economists often suggest the use of Pigouvian taxes or subsidies to correct, or
‘internalize,’ externalities. Choose one specific externality where governments have
considered implementing Pigouvian taxes or subsidies, other than the carbon emissions
case discussed in Tutorial 1. Then, answer the following question.
Should policymakers employ Pigouvian taxes, if a negative externality, or
subsidies, if a positive externality, to correct your chosen externality Might
another policy solution, such as those discussed in lecture, have greater real world benefits in your particular context
Carefully weigh the upsides and downsides of Pigouvian taxes/subsidies relative to other
solutions to formulate arguments in favour of your proposed solution. You should
consider both theoretical efficiency as well as practical considerations around
implementation, and your arguments should be supported by theoretical economic
analysis, literature references (in particular, to scholarly journals in economics), real world examples, and references to guest lectures.
2. As in many developed countries, income inequality in the UK has risen rapidly in recent
years; the massive inequalities in life expectancy and child poverty rates even within
London have further contributed to an explosion of interest in policy solutions to reduce
such disparities. The UK government currently funds large cash transfer programs in a
variety of areas and also provides public goods and in-kind transfers, ranging from the
NHS to public education to council housing. Yet, even these extensive efforts have not
stemmed the tide of rising inequality.
As a soon-to-be graduate of the 2024 UK University of the Year, policymakers have
approached you for your expertise to help solve these seemingly intractable problems.
Choose one form of inequality: income, health, or education and then answer the
following question. Based on economic theory and real-world evidence, which
Department of Economics
policies would most effectively reduce your chosen form of inequality Carefully
weigh the costs and benefits of the most promising policies, which could include, but are
not limited to, cash transfers, in-kind transfers, or changes in the provision of public
goods.
You should consider both theoretical efficiency as well as practical considerations around
implementation, and your arguments should be supported by theoretical economic
analysis, literature references (in particular, to scholarly journals in economics), real world examples, and references to guest lectures.
3. The estimated cost of the UK’s HS2 high-speed rail line, until recently planned to connect
London and Manchester by 2040, has risen over ￡100 billion. This staggering figure,
among other concerns, motivated Prime Minister Sunak’s decision to cancel the line’s
northern half between Birmingham and Manchester.
Economic theory, however, can provide range of justifications for why the government
should intervene to provide improved, or more environmentally-friendly, transport links.
Empirical research has linked transport improvements to poverty, inequality, health, and
educational outcomes. Consider such theoretical and empirical evidence and then
answer the following question: what are the most convincing (economics-based)
arguments in favour of the government reversing course and investing in the full
HS2 line from London to Manchester
You should consider both theoretical justifications for government intervention in
transport markets as well as how HS2’s construction could interact with other
government roles and affect environmental, health, or educational outcomes—this cross cutting topic asks you to take a broad view of the entire term. Your arguments should be
supported by theoretical economic analysis, literature references (in particular, to
scholarly journals in economics), real-world examples, and references to guest lectures.
Writing Tips
For many of you, this essay may be one of your first experiences with academic writing at the
university level. We thus encourage you to carefully read the UCL IOE Writing Centre’s
‘Organise, Structure and Edit’ guide to writing academic essays, which details the overall
structure which academic essays should follow and also provides a wealth of tips for each part
of the essay and stage of the writing process. You should also make sure to fully complete the
Essay Plan, to be introduced i
n Tutorial 3, before starting to write and to carefully consult the
marking criteria and sample marked essays, to be discussed in Tutorial 4. These materials are
posted on Moodle under Assessment/Essay (65%)/Essay Resources.
Word Count
Your essay should not exceed 1500 words in total. The word count includes footnotes and
any tables containing large amounts of text. The word count does not include figure or table
captions, figures themselves, mathematical formulas, in-text references, tables with reasonable
amounts of text, or the bibliography (reference list). Appendices may be used only for the
derivation of theoretical models but will not be included in the word count.
Unfortunately, we must reserve the right to apply the following penalties for over-length
essays: for coursework that exceeds the specified maximum length by less than 10%, the mark will
be reduced by five percentage points (i.e. 5 marks). For work that exceeds the maximum length by
10% or more, the mark will be reduced by ten percentage points (i.e. 10 marks). In no case will the
penalised mark be reduced below the pass mark. In the case of coursework that is submitted late and
is also over-length, the greater of the two penalties will apply.
Referencing and Academic Integrity
All outside sources must be referenced (cited) appropriately in-text and in the bibliography, or
reference list, at the end of your essay using Chicago author-date style. The UCL Library
provides extensive guidance on References, citations, and avoiding plagiarism, and it is your
responsibility to fully familiarize yourself with UCL guidance on academic integrity and
regulations on academic misconduct. In particular, there is zero tolerance for plagiarism of
any kind, and lack of familiarity with regulations does not constitute an excuse for academic
misconduct. If at all in doubt, please consult the teaching team.
AI Tools
According to UCL’s AI guidelines, this assignment falls under Category 2: AI tools can be
used in an assistive role. For this assignment, this means that you can use AI for assistance
in searching for evidence (models, literature references, examples), to help structure and outline
your essay, and to give feedback on or proofread content. However, you may not have AI tools
directly write your essay or generate tables or graphs; in other words, your submission should
not contain any language, tables, or figures written or created by an AI tool. Furthermore,
note that all arguments, models, statistics, and examples not taken from module material must
reference a scholarly source, and an AI tool does not constitute a scholarly source.
Please note that Generative AI can be a useful starting point to gather background information
on a topic, but be aware that:
Generative AI produces information that may be inaccurate, biased, or outdated.
Generative AI is not an original source of information: it reproduces information from
unidentified sources.
Generative AI may fabricate quotations and citations.
It is always best to refer to original and credible sources of information.
If you do choose to use generative AI tools, you must always:
Critically evaluate any output it produces.
Carefully check any quotations or citations it creates.
Correctly document your use of the tools so that it can be appropriately acknowledged,
according to UCL’s acknowledging and referencing AI guideline.
The use of AI tools that exceeds that permitted in the assessment brief constitutes Academic
Misconduct.
Submission
Deadline
Essays must be submitted at the TurnitIn link on Moodle by, at the latest, Fri., 15 Dec. at
17:00 London Time. Please plan to submit at least 1 hour in advance of the deadline in case
you encounter any technical difficulties. Once your submission has been accepted by TurnitIn,
take a screenshot in case any issues arise.
Format
All essays should be submitted as a single pdf file using a file name that includes your
candidate number1 and the number of the question you have answered. For example, if your
candidate number is ABC123 and you have answered Question 1, name your file
ABC123_Q1.pdf. Please also include your candidate number in the top left-hand corner of the
first page of your essay but, in line with UCL policies on anonymous marking, please do not
write your name anywhere in the document.
Technical Issues
If you experience issues with uploading your work, please contact IT Services, or, if the issue
cannot be resolved by IT or you accidentally upload the wrong file, reach out to the module
administrator, Rich Maskell ([email protected]), before the submission deadline.
Late or Missing Submissions
Late submission penalties will be applied according to the policies set out in UCL Academic
Manual 4.3.12. You will be awarded a mark of 0% if you do not attempt the essay or attempt so
little of the essay that it cannot be assessed.
SORA and Extenuating Circumstances
We will automatically apply any SORA arrangements. In the event that unavoidable
extenuating circumstances affect your ability to submit your work within the submission
deadline, you should submit an Extenuating Circumstances claim via the standard UCL
procedures.
1 You can find your candidate number in your Portico account under ‘My Studies’ and then the ‘Examinations’
container.