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COURSEWORK GUIDELINES

The coursework consists of an assessed empirical project of maximum 3,500 words. It requires students to critically apply, compare and utilise an array of theories and concepts discussed in both the lectures and tutorials to discuss a topic of their choice related to financial development in emerging economies or in comparative perspective with advanced or developing economies.

The requirement is an empirical exploration of a research question, ideally using the methods taught in quantitative research methods courses. The orientation of the course strongly suggests the use of quantitative-based methods, and most topics covered in the course favour such methods. Although students may choose a theoretical approach, such work also needs to contain at least some data analysis and the consultation with the module leader is essential.

Key guidelines

Below, you can find five general clusters with topic suggestions. This is a small, indicative selection and students are very welcome to submit a project on a relevant topic of their choice (subject to agreement with the module leader).

• You should undertake an empirical exploration of the chosen topic, using

databases/sources recommended below or any other widely available and recognised

datasets. Such sources are government agencies, international and national organisations, widely recognised institutions that specialise in relevant areas.

• Submit one-page coursework proposal by the end of Term 2 (25th of March 2026 at 3pm) on Moodle to allow for formative feedback.

• Submission of the final project should be done on Moodle and be comprised of three

files: (1) your project in a Word or PDF format; (2) your dataset in Stata based on which you have obtained the results; (3) a do file (if the analysis done in STATA) recording all sets of commands used to transform your data, present an exploratory analysis and run the regressions. If alternative software is used to undertake the analysis (e.g. R software package; Python), submit a syntax in the respective format. The requirement is that the data and estimation must be submitted in a clear and directly accessible manner (immediately executable files with detailed, step by step comments). It is essential that all three files are saved indicating the module code and your student number [CandidateNumber].

• The deadline for submission of the final coursework project is the 29th of April 2026 at 3pm.

Guidelines on the use of AI tools

This assessment is classified as UCL Category 2 type, implying that AI tools can be used in an assistive role only. For example, AI tools can be used to support the development of specific skills as required by the assessment. There will be some aspects of the assessment where the use of AI is inappropriate and/or not allowed. Students MUST follow UCL guidance on acknowledging use of AI and referencing AI.

Examples of acceptable use of AI for Category 2 assessments

• research assistance – suggesting authors and sources

• testing your understanding of various concepts and developing ideas

• stylistic polishing and spell checking

• proofreading content

• giving feedback on content and structure

• summarising basic concepts

Examples of unacceptable use of AI for Category 2 assessments

• asking AI to produce essay/dissertation outlines

• asking AI to suggest a theoretical framework/research project design

• asking AI to summarise specific texts3

• producing first drafts

• drafting and structuring content from scratch

• ghost-writing

• inputting the essay title into an AI platform as a prompt

Suggested structure of your coursework project

Title (to reflect your research question)

1. Introduction

• Clearly formulated research question

• Motivation behind your research question

• Summary of the results

• Structure of your paper

2. Literature review/theoretical framework

3. Data & Methodology

4. Empirical results

5. Conclusion and Discussion

Assessment rubric criteria

1. Research question and its motivation

• Relevance of a research question to the module

• Good motivation provided for examining this research question.

• A question should be answerable through the proposed empirical investigation with

findings discussed clearly to provide support/reject your hypotheses

2. Knowledge of the literature and structure of the argument

• Relevance of the literature discussion to research question

• Main theories and themes identified and explored to suggest a conceptual/theoretic

framework suitable for answering a research question

• Hypotheses are clearly formulated and backed by the relevant references

• Well organised structure, coherent and logical argument

3. Analysis and argument

• The data and methodology are clearly discussed

• Evidence of the use of primary/secondary data to support the argument

• A descriptive analysis of data is to be presented prior undertaking any more in-depth

quantitative work; this descriptive analysis would help you with formulating your

hypotheses

• Evidence of original analysis & clear explanation of the results contextualising them

within the literature

4. Presentation

• Clear expression

• Accurate grammar and syntax

• Referencing with bibliography4

Recommended Databases:

The Global Financial Development Database (builds on, updates, and extends previous efforts, in particular the data collected for the Database on Financial Development and Structure) (updated September 2022). The Global Financial Development Database is an extensive dataset of financial system characteristics for 214 economies. It contains annual data, starting from 1960 onwards.

The Global Financial Development Database is based on a “4x2 framework”. Specifically, it includes measures of (1) depth, (2) access, (3) efficiency, and (4) stability of financial systems.

Each of these characteristics captures both (1) financial institutions (banks, insurance companies, and so on), and (2) financial markets (such as stock markets and bond markets). It also provides other useful indicators, such as measures of concentration and competition in the banking sector, financial structure etc.

You can access the Global Financial Development Database via

https://www.worldbank.org/en/publication/gfdr/data/global-financial-development-database

For discussion of the dataset and empirical work done on it see the following sources:

Čihàk, Martin, Aslı Demirgüç-Kunt, Erik Feyen, and Ross Levine. 2013. “Financial

Development in 205 Economies, 1960 to 2010.” Journal of Financial Perspectives 1 (2): 17–36.

(Earlier version issued as Policy Research Working Paper 6175, World Bank, Washington, DC).

The IMF Financial Development-broad based index database,

https://data.imf.org/en/datasets/IMF.MCM:FDI

Based originally on Čihák et al. (2013) idea of measuring financial development, this dataset offers nine indices that summarize how developed financial institutions and financial markets are in terms of their depth, access, and efficiency. These indices are then aggregated into an overall index of financial development. With the coverage of more than 180 countries on annual frequency between 1980 onwards, the database offers a useful analytical tool for researchers and policy makers. Following the link above, you can also access the IMF paper that discusses the methodology for measuring Financial Development.

Svirydzenka, K. (2016) Introducing a New Broad-based Index of Financial Development, IMF Working Paper, WP/16/5, available from https://www.imf.org/external/pubs/ft/wp/2016/wp1605.pdf

Financial Inclusion database, World Bank, available from here https://www.worldbank.org/en/publication/globalfindex/download-data /

The Global Findex database provides in-depth data on how individuals save, borrow, make payments, and manage risks. It is the world’s most comprehensive database on financial inclusion that consistently measures people’s use of financial services across countries and over time. The Global Findex consists of over 100 indicators, also shown by gender, income, and age.

Collected in partnership with the Gallup World Poll and funded by the Bill & Melinda Gates

Foundation, the Global Findex is based on interviews with about 150,000 nationally representative and randomly selected adults (age 15+) in over 140 countries. It contains individual-level microdata data and country-level aggregated data.5

Financial Access Survey, IMF, available from https://data.imf.org/en/datasets/IMF.STA:FAS IMF provides an alternative Financial Inclusion database based on Financial Access Survey. The data coverage is better than in World Bank, covering the period from 2004 onwards.

Bank Regulation & Supervision Survey database

This database The Bank Regulation and Supervision Survey is a unique source of comparable economy-level data on how banks are regulated and supervised around the world. The most recent survey is available for the period of 2017-2019. 

https://www.worldbank.org/en/publication/gfdr/data/the-bank-regulation-and-supervision- survey

The Chinn-Ito index of financial integration (KAOPEN), which is constructed on the basis of the IMF data measuring the extent and intensity of capital controls, is publicly available and can be downloaded from http://web.pdx.edu/~ito/Chinn-Ito_website.htm. The Chinn-Ito index of financial integration covers over 180 countries from 1970 onwards.

The External Wealth of Nations provides annual estimates of countries’ external financial assets and liabilities, including foreign direct investment, portfolio investment, other investment, derivatives and reserves, allowing researchers to assess how financially integrated economies are with the rest of the world. It covers over 200 countries and territories from 1970 onward, and also yields each country’s net international investment position (assets minus liabilities), a key indicator of external financial integration and creditor/debtor status. The database is widely used to analyse trends in cross-border financial linkages, global imbalances and the evolution of international capital markets. It is available from https://www.brookings.edu/articles/the-

external-wealth-of-nations-database

OeNB Euro Survey - Oesterreichische Nationalbank (OeNB) is an annual international household survey conducted since 2007 in selected Central, Eastern and Southeastern European countries, focusing on euroization, monetary expectations, trust in institutions and financial behaviour. It provides harmonised, representative micro-level data that help policymakers and researchers understand the use of foreign currencies, attitudes toward euro adoption, and implications for financial stability and European integration.

ORBIS, a Moody’s (previously BvD) database of comparable financial information for public and private companies across Europe (available electronically through UCL library service – search via the databases tab).

Other data sources:

EBRD Banking Environment and Performance Survey (BEPS), https://www.ebrd.com/what-we-do/economic-research-and-data.html

EBRD-World Bank Business Environment and Enterprise Performance Survey (BEEPS)

- firm-level dataset which can be used for examining firm access to finance and firm capital structure, available from https://www.beeps-ebrd.com/6

World Bank World Development Indicators, available from https://databank.worldbank.org/source/world-development-indicators

IMF Financial Statistics, available from https://data.imf.org/?sk=4c514d48-b6ba-49ed-8ab9-52b0c1a0179b

Heritage Foundation, Index of Economic Freedom, https://indexdotnet.azurewebsites.net/index/explore (can be used for measuring institutions)

World Bank Enterprise Survey Data (WES)

This dataset is similar to BEEPS but its coverage is extended worldwide. It is available from https://www.enterprisesurveys.org/en/enterprisesurveys

Global Entrepreneurship Monitor (GEM) dataset, http://www.gemconsortium.org/data (individual-level dataset; can be used for exploring entrepreneurial finance).

Working papers (working papers show the most recent research in the area):

• European Bank for Reconstruction and Development Working Papers; https://www.ebrd.com/news/publications/working-papers.html

• Google Scholar

• National Bureau of Economic Research: http://papers.nber.org/

• Social Science Research Network Working Papers http://www.ssrn.com/

• Web of Science and Scopus literature search software accessible via UCL library