PhD

This course provides students with a basic foundation in mathematics and statistics required to undertake further quantitative research methods courses. This course consists of two parts, statistics and mathematics. Topics covered include: matrix algebra; optimization; differential equations; random variables and probability distributions; moments of a random variable; probability distributions; joint, marginal and conditional distributions; functions and transformation of a random variable; hypothesis testing; univariate regression.

When starting new research, the first step is usually a literature review: scanning what is already known about a given topic and figuring out where the gaps are. However, novice researchers tend to be anything but systematic in their literature review: they have no method for scanning the literature, and they usually have little idea of what is relevant and what is not. The Systematic Review method opens a way to create research syntheses that add real value and novel insight – in a way that is potentially publishable in its own right.

Optimisation

Stochastic Processes - This module introduces you to basic tools for modelling stochastic phenomena. The focus of the module is the theory of stochastic processes, but applications will be drawn from operations research, analytics / ML, and finance to illustrate the usage of the models for studying real-world business problems

Machine Learning for Analytics - This module gives you an overview of machine learning methods for analytics. Applications in the module will be drawn from various sources including medical applications (e.g. patient discharge from hospitals), recommender systems and the Netflix prize, advertising and marketing, estimating scofflaw rates, reputations systems and Google's PageRank algorithm, filtering, text mining, sports analytics etc.

Decision Making Under Uncertainty - This module gives you an overview of different paradigms of decision making in dynamic uncertain environments, including dynamic programming, stochastic optimisation and robust optimisation. Along with theory, applications in operations management and analytics will be introduced, with the aim of preparing you for research in these areas.

Industrial Organisation

Sustainable Behaviour - This module aims to provide you with an in-depth exposure to the emerging academic field of sustainable behaviour. You will be presented with the main methodological tool used in behavioural research (lab and field experiments) as well with the multiple articles and journals which have published cutting-edge experimental research on sustainable behaviour across a wide variety of contexts.

Consumer Behaviour - This module aims to give you a robust foundation in consumer behaviour and how it relates to marketing. The module covers topics such as how consumers process marketing communications, how consumer involvement affects decision making, and how external factors impact consumer behaviour.

Microeconomics 1

Microeconomics 2

Applied Microeconometrics

Applied Microeconometrics 2

Econometrics 1

Econometrics 2

Qualitative Methods 1

Qualitative Methods 2

Quantitative Methods 2

You can choose from a range of elective modules relevant to your pathway.

Advanced Finance 1

Advanced Finance 2

Asset Pricing Theory 

Corporate Finance

Consumer Behaviour

Empirical Asset Pricing

Entrepreneurship 

Financial Economics of Climate Sustainability

Foundations in Asset Pricing

Industrial Organisation

Machine Learning for Analytics

Machine Learning for Economic Analysis

Macroeconomics 1

Macroeconomics 2

Macro-Finance

Micro Development Economics

Organisational Behaviour

Organisation Theory 

Research Project

Strategy

Topics in Empirical Banking 

Topics in Environmental Resource Economics 

Topics in Health Economics

Topics in Household Finance 

Business Models and Intellectual Property*

Contemporary Topics in Health Policy*

Digital Marketing Analytics*

Healthcare and Medical Analytics*

Logistics and Supply Chain Analytics*

Optimisation and Decision Models*

Retail and Marketing Analysis*

Workforce Analytics*

*These modules are available subject to capacity and timetabling constraints in other faculties and are differently weighted to the MRes Business electives

This course provides students with a basic foundation in mathematics and statistics required to undertake further quantitative research methods courses. This course consists of two parts, statistics and mathematics. Topics covered include: matrix algebra; optimization; differential equations; random variables and probability distributions; moments of a random variable; probability distributions; joint, marginal and conditional distributions; functions and transformation of a random variable; hypothesis testing; univariate regression.

When starting new research, the first step is usually a literature review: scanning what is already known about a given topic and figuring out where the gaps are. However, novice researchers tend to be anything but systematic in their literature review: they have no method for scanning the literature, and they usually have little idea of what is relevant and what is not. The Systematic Review method opens a way to create research syntheses that add real value and novel insight – in a way that is potentially publishable in its own right.

Applied Microeconometrics I - This module will provide an introduction to the practice of applied microeconometrics. Students will learn the standard empirical methods in current use by applied researchers and be exposed to a handful of frontier approaches. The focus will be on implementation beyond simply estimating a parameter of interest: getting the standard errors right, validation and conducting appropriate robustness exercises, and adapting methods to fit new contexts.

Applied Microeconometrics II - This module will be an introduction to some of the most important themes for students wishing to conduct their own research in Empirical Corporate Finance. For other students, this module will help students gain a better understanding of research related to your own field. Topics covered include: regression refresher, causality and randomized experiments, instrumental variables, difference-in-difference, regression discontinuity, standard errors, event studies, discrete response models, matching methods, and non-parametric methods

Econometrics I - The module has the objective to provide the students with econometric tools necessary to conduct their empirical research and discuss fundamentals of econometric theory behind them. Students will learn how to conduct - and how to critique - empirical studies in finance, economics and related fields.

Macroeconomics - This course covers research issues that arise in the intersection of macroeconomics and finance. Topics include portfolio choice, general equilibrium models with heterogeneous agents and dynamic asset pricing models.

Microeconomics I - The module covers the main tools of microeconomic theory and focuses on preferences, consumer theory, choice under uncertainty, producer theory, and game theory. Time permitting, it introduces general equilibrium in competitive markets. The emphasis is on economic intuition as well as techniques. The fundamental concepts of microeconomic theory are discussed.

Microeconomics II - This module covers competitive equilibrium, markets with imperfect, competition and asymmetric information, general equilibrium, Social choice and mechanism design

Research Experience – This module is intended to give students practical experience of research preparation for their dissertation the following year.  They will undertake research tasks under the supervision of a faculty member on a topic chosen by the faculty member.  Students can select those projects that fit their research interests.

Empirical Corporate Finance - This module will provide an introduction to the practice of applied microeconometrics. Students will learn the standard empirical methods in current use by applied researchers and be exposed to a handful of frontier approaches. The focus will be on implementation beyond simply estimating a parameter of interest: getting the standard errors right, validation and conducting appropriate robustness exercises, and adapting methods to fit new contexts.

Econometrics II   - This module will be an introduction to some of the most important themes for students wishing to conduct their own research in Empirical Corporate Finance. For other students, this module will help students gain a better understanding of research related to your own field. Topics covered include: regression refresher, causality and randomized experiments, instrumental variables, difference-in-difference, regression discontinuity, standard errors, event studies, discrete response models, matching methods, and non-parametric methods. 

Econometrics I - The module has the objective to provide the students with econometric tools necessary to conduct their empirical research and discuss fundamentals of econometric theory behind them. Students will learn how to conduct - and how to critique - empirical studies in finance, economics and related fields.

Macroeconomics - This course covers research issues that arise in the intersection of macroeconomics and finance. Topics include portfolio choice, general equilibrium models with heterogeneous agents and dynamic asset pricing models.

Microeconomics I - The module covers the main tools of microeconomic theory and focuses on preferences, consumer theory, choice under uncertainty, producer theory, and game theory. Time permitting, it introduces general equilibrium in competitive markets. The emphasis is on economic intuition as well as techniques. The fundamental concepts of microeconomic theory are discussed.

Corporate Finance - This module is taught in two parts, starting with a historical background, and then considering the theory of investment decisions, capital structure, financial innovation, and corporate governance.

Asset Pricing Theory - The first part of this module deals with representative investors, portfolio choice and dynamic securities markets in discrete time before covering portfolio choice in continuous time and option pricing. The second part starts from the asset pricing implications of a general equilibrium Lucas-tree economy. Then, it discusses the main asset pricing puzzles implied by these economies. Finally, we will explore optimal portfolio choice, multiple trees economies and some of the latest attempts in the asset pricing literature to solve some of these puzzles.

Empirical Asset Pricing - The module is intended for students with a prior knowledge of asset pricing theory, capital markets and econometrics, and will concentrate on discrete-time methods and use a variety of econometric techniques. The module will cover these econometric tools in order to empirically address meaningful economic questions.

Research Experience - This module is intended to give students practical experience of research preparation for their dissertation the following year.  They will undertake research tasks under the supervision of a faculty member on a topic chosen by the faculty member.  Students can select those projects that fit their research interests.

Introduction to the Practice of Research - This module will introduce you to the craft of research. You will develop the skills and knowledge you need to effectively produce research questions and hypotheses, ensuring consistency between theory, research design, methods and measures, and developing a clear and compelling argument.

Qualitative Methods I - This module covers research methods required in qualitative research. You will develop skills in all aspects of the research process, including research design, data collection, data analysis, theory building, writing up as well as reviewing papers and responding to referees. The module is essential for those who wish to author qualitative research but will also be useful for quantitative researchers.

Quantitative Methods I - This module provides an overview of the primary quantitative methods employed in management research. It will enable you to develop the ability to interpret the results of your own research as well as to critically assess the findings presented in other studies. The emphasis will be on the practical application of different estimation models using STATA rather than on the econometrics and mathematical specification.

Organisational Behaviour - In this module you will be introduced to a selection of most seminal papers in organisational behaviour with a particular focus on classic and contemporary theories, ongoing controversies, and ground-breaking empirical studies. The emphasis is on providing a foundational overview of the field.

Organisation Theory - This module will expose you to the major theoretical perspectives and issues studied in organisation theory research. You will also be exposed to a set of approaches to understanding how and why organisations form, survive and grow.

Strategy - In this module you will develop the fundamentals of strategy including the theories of competitive advantage, industry analysis, understanding of resource based view/knowledge based view, and corporate strategy.

Innovation Management - This module will offer a thorough theoretical understanding of the key themes of innovation research, combined with practical insights into the challenges of innovation management in organisations. You will address topics ranging from technological change, creativity, the role of networks in innovation, and appropriability/value capture from innovation.

Entrepreneurship - This module introduces students to the major theoretical threads and debates in the field of entrepreneurship. Students will learn to make connections between theory and empirical research, practice critiquing and identifying insight in research, engage with fundamental debates in the field and formulate directions how the field may be further advanced.

Research Experience – This module is intended to give students practical experience of research preparation for their dissertation the following year.  They will undertake research tasks under the supervision of a faculty member on a topic chosen by the faculty member.  Students can select those projects that fit their research interests.

Introduction to the Practice of Research - This module will introduce you to the craft of research. You will develop the skills and knowledge you need to effectively produce research questions and hypotheses, ensuring consistency between theory, research design, methods and measures, and developing a clear and compelling argument.

Qualitative Methods I - This module covers research methods required in qualitative research. You will develop skills in all aspects of the research process, including research design, data collection, data analysis, theory building, writing up as well as reviewing papers and responding to referees. The module is essential for those who wish to author qualitative research but will also be useful for quantitative researchers.

Quantitative Methods I - This module provides an overview of the primary quantitative methods employed in management research. It will enable you to develop the ability to interpret the results of your own research as well as to critically assess the findings presented in other studies. The emphasis will be on the practical application of different estimation models using STATA rather than on the econometrics and mathematical specification.

Organisational Behaviour - In this module you will be introduced to a selection of most seminal papers in organisational behaviour with a particular focus on classic and contemporary theories, ongoing controversies, and ground-breaking empirical studies. The emphasis is on providing a foundational overview of the field.

Organisation Theory - This module will expose you to the major theoretical perspectives and issues studied in organisation theory research. You will also be exposed to a set of approaches to understanding how and why organisations form, survive and grow.

Strategy - In this module you will develop the fundamentals of strategy including the theories of competitive advantage, industry analysis, understanding of resource based view/knowledge based view, and corporate strategy.

Innovation Management - This module will offer a thorough theoretical understanding of the key themes of innovation research, combined with practical insights into the challenges of innovation management in organisations. You will address topics ranging from technological change, creativity, the role of networks in innovation, and appropriability/value capture from innovation.

Entrepreneurship - This module introduces students to the major theoretical threads and debates in the field of entrepreneurship. Students will learn to make connections between theory and empirical research, practice critiquing and identifying insight in research, engage with fundamental debates in the field and formulate directions how the field may be further advanced.

Research Experience – This module is intended to give students practical experience of research preparation for their dissertation the following year.  They will undertake research tasks under the supervision of a faculty member on a topic chosen by the faculty member.  Students can select those projects that fit their research interests.

Advanced Econometrics

Advanced Finance 1

Advanced Finance 2

Advanced Macroeconomics

Advanced Microeconomics

Asset Pricing Theory

Behavioral Foundations of Strategy

Consumer Behaviour

Corporate Finance

Development Economics 

Decision Making Under Certainty

Econometrics I

Econometrics II 

Economic Foundations of Strategy 

Empirical Asset Pricing

Financial Economics of Climate and Sustainability

Foundations in Asset Pricing

International Economics 

Industrial Organisation

Labour and Public Economics

Machine Learning for Economics Analysis

Macroeconomics I

Macroeconomics II

Macro-Finance

Microeconomics I

Microeconomics II 

Micro Development Economics

Optimisation

Sustainable Behaviour

Topics in Empirical Banking

Topics in Environmental Resource Economics

Topics in Health Economics

Topics in Household Finance

Topics in Macroeconomics

Advanced Econometrics

Advanced Finance 1

Advanced Finance 2

Advanced Macroeconomics.

Advanced Microeconomics

Behavioral Foundations of Strategy

Consumer Behaviour

Decision Making Under Certainty

Development Economics

Econometrics I

Econometrics II

Economic Foundations of Strategy

Financial Economics for Climate Sustainability

Industrial Organisation

International Economics

Foundations in Asset Pricing

Labour and Public Economics

Macroeconomics I

Macroeconomics II

Macro-Finance

Microeconomics I

Microeconomics II

Micro Development Economics

Optimisation

Sustainable Behaviour

Topics in Household Finance

Topics in Empirical Banking

Topics in Macroeconomics

Advanced Econometrics

Advanced Finance 1

Advanced Finance 2

Advanced Macroeconomics

Advanced Microeconomics

Advanced Topics in Organisational Behaviour

Behavioral Foundations of Strategy

Consumer Behaviour

Corporate Sustainability

Decision Making Under Certainty

Development Economics

Econometrics I

Econometrics II

Economic Foundations of Strategy

Financial Economics of Climate and Sustainability

Foundations in Asset Pricing

Industrial Organisation

Interdisciplinary Research

International Economics

Labour and Public Economics

Macroeconomics I

Macroeconomics II

Macro-Finance

Microeconomics I

Microeconomics II

Micro Development Economics

Optimisation

Qualitative Methods II

Readings in Digital Business

Readings in Social Networks/Social Capital

Social Network Analysis

Social Data Science

Special Topics in Organisational Theory/Strategy

Sustainable Behaviour

Topics in Macroeconomics

Advanced Econometrics

Advanced Finance 1

Advanced Finance 2

Advanced Macroeconomics

Advanced Microeconomics 

Advanced Topics in Organisational Behaviour 

Behavioral Foundations of Strategy

Corporate Sustainability

Consumer Behaviour

Decision Making Under Certainty

Development Economics

Econometrics I

Econometrics II

Economic Foundations of Strategy

Financial Economics of Climate and Sustainability

Foundations in Asset Pricing

Industrial Organisation

Interdisciplinary Research

International Economics

Labour and Public Economics

Macroeconomics I

Macroeconomics II

Macro-Finance

Microeconomics I

Microeconomics II

Micro Development Economics

Optimisation

Qualitative Methods II

Readings in Digital Business

Readings in Social Networks/Social Capital

Social Data Science

Social Network Analysis 

Special Topics in Organisational Theory/Strategy

Sustainable Behaviour

Topics in Macroeconomics

During the second year, students work on their MRes project which is formally assessed and counts towards the overall MRes mark. Students are expected to approach potential supervisors from within the department’s academic staff. Students submit their proposed research project title and a brief outline by the end of September of Year two. Students submit a Progress Report in February, outlining their progress to date with the thesis. During the Summer Term, students will submit their MRes dissertation. This will be followed by an oral exam

When you progress from the MRes to the PhD, you will work with your supervisors, chosen based on your research interests. Your supervisors will help you develop your research question, identify research and teaching opportunities and support you through your studies and the academic job application process.  

Being part of the School’s inspirational research community is a crucial aspect of the doctoral experience – as is gaining familiarity with cutting edge research from world-leading academics. Each department runs seminars where internal and external academics discuss their latest work.  

As well as providing insight into yet-to-be-published research, the seminars offer networking opportunities and visiting academics often lead special topic workshops for research students. The Doctoral programme also supports the participation of research students in international conferences where you can present your own research and participate in doctoral consortia. 

The Early Stage Assessment (ESA) takes place in the summer of year one of the PhD and is assessed by a panel of faculty. The ESA outlines the research question, the work you have done to date and the future research activities to be carried out to complete the project. 

It consists of a written report and presentation to which all PhD students and research department faculty are invited. The purpose of the ESA is not only to assess your personal progress but it also gives you the opportunity to discuss your work at its early stages and get feedback and ideas from faculty to improve your research. 

Armed with feedback from the Early Stage Assessment, you will work intensely on your thesis, focusing on the collection and analysis of empirical data and developing theoretical frameworks. Under the guidance of your supervisors, the thesis gives you the opportunity to conduct a substantial piece of original research. 

The Late Stage Review (LSR) takes place in the summer of year two of the PhD and follows the same principle as the Early Stage Assessment, in that its purpose is to assess your progress and provide you with feedback and advice on the direction and scope of your research.