Two year Master’s in Research

The following details reflect the proposed programme structure for our 2022 intake. Changes are subject to college approval. 

If you choose to specialise in the following research areas, you will embark on a two-year MRes:

  • Economics & Public Policy*
  • Finance*
  • Innovation and Entrepreneurship
  • Strategy and Organisational Behaviour

*Subject to college approval

You are required to complete the following during the two year MRes stage of the Doctoral programme.

Year one - compulsory introductory modules for all pathways 

Core introductory modules, designed to provide a foundation in research tools:

Data Analysis Tools

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.

Systematic Reviews

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.

Year one - compulsory modules by pathway

You will study the following research methods and specialist content modules:

Economics and Public Policy pathway*

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

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.

*Subject to college approval

Finance pathway*

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.

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.

*Subject to college approval

Innovation and Entrepreneurship pathway

Socialisation to 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.

Strategy & Organisational Behaviour pathway

Socialisation to 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.

Year one - elective modules

You will choose to study three electives, potential modules within the Business School could be:

Economics and Public Policy pathway*

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.

Topics in Environmental Resource Economics - In this PhD level course we explore key theoretical and empirical results in environmental and resource economics. The course will discuss both: classic papers as well as studies at the recent frontier of the field. While we will explore both theoretical and empirical work, there is a focus on applied empirical work. Students will be asked to replicate one recent empirical paper and explore modifications or extensions.

Topics in Health Economics - This is a PhD level course in Health Economics. It introduces the key topics studied by health economists and methods used in state-of-the-art research in these areas.  The course explores both theoretical and empirical contributions, including both classic papers and articles from research frontier.

Machine Learning for Economics Analysis - This module covers applications of machine learning in economics.  The main focus areas will be supervised learning and causal inference, and unsupervised learning and information retrieval from unstructured data. 

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 use a variety of econometric techniques. The module will cover these econometric tools in order to empirically address meaningful economic questions.

Topics in Household Finance – This course will examine how the combination of large administrative datasets of household decisions, empirical techniques including machine learning, and insights from behavioural finance can be used to diagnose inefficient household decisions and evaluate policies to help these decisions to be made more efficiently. Two broad areas that will be focused on in particular are the allocation of savings, especially in equities, and the choice, refinancing, and default decisions of households in mortgages and real estate, which are, respectively, the largest liability and the biggest asset in household portfolios

Topics in Empirical Banking - The main topics that we will discuss in the class relate to the foundations of intermediation. The course will be interactive with active participation being required from students.  The topics covered will include: Financial Fragility, depositor runs and deposit insurance. Contagion and network effects. Changing landscape of financial intermediation. Regulating banks. Interaction between banks and macroeconomics. Special attention will be given to the research methodologies and to the public policy implications, mainly macroprudential and monetary policy.

*Subject to college approval

The greatest opportunity I've had at Imperial is the ability to work with people who are at the top of their fields. Imperial has the whole package – it is great academically, located in a fantastic city and you feel like you have a chance to peek at the cutting edge of science in a range of disciplines, which is pretty exciting.
Doctoral student, Economics & Public Policy
Imperial Doctoral student Petra Sarapatkova

Year two - elective modules 

Students will choose specialist electives within their areas of interest and research focus. Potential modules within the Business School could be:

Economics and Public Policy pathway*

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.

Topics in Environmental Resource Economics - In this PhD level course we explore key theoretical and empirical results in environmental and resource economics. The course will discuss both: classic papers as well as studies at the recent frontier of the field. While we will explore both theoretical and empirical work, there is a focus on applied empirical work. Students will be asked to replicate one recent empirical paper and explore modifications or extensions.

Topics in Health Economics - This is a PhD level course in Health Economics. It introduces the key topics studied by health economists and methods used in state-of-the-art research in these areas.  The course explores both theoretical and empirical contributions, including both classic papers and articles from research frontier.

Machine Learning for Economics Analysis - This module covers applications of machine learning in economics.  The main focus areas will be supervised learning and causal inference, and unsupervised learning and information retrieval from unstructured data. 

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 use a variety of econometric techniques. The module will cover these econometric tools in order to empirically address meaningful economic questions.

Topics in Household Finance – This course will examine how the combination of large administrative datasets of household decisions, empirical techniques including machine learning, and insights from behavioural finance can be used to diagnose inefficient household decisions and evaluate policies to help these decisions to be made more efficiently. Two broad areas that will be focused on in particular are the allocation of savings, especially in equities, and the choice, refinancing, and default decisions of households in mortgages and real estate, which are, respectively, the largest liability and the biggest asset in household portfolios

Topics in Empirical Banking - The main topics that we will discuss in the class relate to the foundations of intermediation. The course will be interactive with active participation being required from students.  The topics covered will include: Financial Fragility, depositor runs and deposit insurance. Contagion and network effects. Changing landscape of financial intermediation. Regulating banks. Interaction between banks and macroeconomics. Special attention will be given to the research methodologies and to the public policy implications, mainly macroprudential and monetary policy.

*Subject to college approval

Finance pathway*

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

Machine Learning for Economics Analysis - This module covers applications of machine learning in economics.  The main focus areas will be supervised learning and causal inference, and unsupervised learning and information retrieval from unstructured data. 

Topics in Household Finance – This course will examine how the combination of large administrative datasets of household decisions, empirical techniques including machine learning, and insights from behavioural finance can be used to diagnose inefficient household decisions and evaluate policies to help these decisions to be made more efficiently. Two broad areas that will be focused on in particular are the allocation of savings, especially in equities, and the choice, refinancing, and default decisions of households in mortgages and real estate, which are, respectively, the largest liability and the biggest asset in household portfolios

Topics in Empirical Banking - The main topics that we will discuss in the class relate to the foundations of intermediation. The course will be interactive with active participation being required from students.  The topics covered will include: Financial Fragility, depositor runs and deposit insurance. Contagion and network effects. Changing landscape of financial intermediation. Regulating banks. Interaction between banks and macroeconomics. Special attention will be given to the research methodologies and to the public policy implications, mainly macroprudential and monetary policy.

*Subject to college approval

Innovation and Entrepreneurship pathway

Qualitative Methods II - This module focuses on the execution of qualitative research with the aim being to write a qualitative paper over the course of the term, with ample constructive feedback throughout the process.

Social Network Analysis - In this module you will learn to critically assess existing concepts that explain the structure and dynamics of networks and the position of individuals and organisations within them. You will learn to apply the toolkit of network theories, concepts and methods to design effective networks to research in your field of interest. By the end of the module you will be able to perform social network analysis to examine processes of tie formation, network dynamics and their impact on individual and organisational outcomes.

Interdisciplinary Research - This module will provide you with the skills you need to conduct interdisciplinary research with colleagues from other disciplines such as engineering, medicine and physical science. You will also learn to implement methodological approaches to your research and tackle the challenges and hurdles that come with it.

Social Data Science - By the end of this module you will be able to comfortably navigate open data; curate, combine and clean data sets to tackle new problems; and contribute to your proprietary data to open data repositories. You will also develop skills to use Python in Jupyter notebooks to transform, analyse, and visualise data.

Corporate Sustainability - This module will allow you to develop a good command of the core concepts and debates in the corporate sustainability literature. The module is organised with the initial stage dedicated to the debate on the theory of the firm. The module will then progress to a part related to the environmental and social impacts of firm activities, and engage students about alternative forms of capitalism that might be able to remedy and prevent the negative spillovers created by economic activity. The third stage will examine governance and strategic decision-making as critical elements of the firm that will require innovative solutions backed up by experimental evidence.  The final stage will examine how other functional and organisational elements of the firm have been and can be redesigned to develop a stakeholder-centred form of enterprise. 

Special Topics in Organisational Theory/Strategy - This module will guide and teach you to develop a range of perspectives on strategy with an emphasis on organisational theory strategy.

Advanced Topics in Organisational Behaviour - Those who are wanting to pursue organisational behaviour should take at least one more advanced module on a topic within organisational behaviour. This might be focused on micro organisational behaviour that focuses more on intra-personal processes, such as emotions and cognitions, or meso organisational behaviour focusing more on inter-personal processes. This could also be special topics in organisational behaviour, such as gender and diversity in organisations, or moral psychology applied to organisations.

Readings in Social Networks/Social Capital - After completing this module you will understand the foundations of social capital research and have developed an awareness of the key themes in the social capital literature, appreciating the frontier of research in these themes. You will be able to theorize about the antecedents and effects of social capital and social networks for a broad range of individual, group, organisational and societal outcome. You’ll be able to apply arguments and concepts from social capital theory to contemporary challenges in research in strategic management, organisational behaviour and innovation and entrepreneurship.

Readings in Digital Business - In this module you will undertake readings on technology in organisations and digital business.

Strategy & Organisational Behaviour pathway

Qualitative Methods II - This module focuses on the execution of qualitative research with the aim being to write a qualitative paper over the course of the term, with ample constructive feedback throughout the process.

Social Network Analysis - In this module you will learn to critically assess existing concepts that explain the structure and dynamics of networks and the position of individuals and organisations within them. You will learn to apply the toolkit of network theories, concepts and methods to design effective networks to research in your field of interest. By the end of the module you will be able to perform social network analysis to examine processes of tie formation, network dynamics and their impact on individual and organisational outcomes.

Interdisciplinary Research - This module will provide you with the skills you need to conduct interdisciplinary research with colleagues from other disciplines such as engineering, medicine and physical science. You will also learn to implement methodological approaches to your research and tackle the challenges and hurdles that come with it.

Social Data Science - By the end of this module you will be able to comfortably navigate open data; curate, combine and clean data sets to tackle new problems; and contribute to your proprietary data to open data repositories. You will also develop skills to use Python in Jupyter notebooks to transform, analyse, and visualise data.

Corporate Sustainability - This module will allow you to develop a good command of the core concepts and debates in the corporate sustainability literature. The module is organised with the initial stage dedicated to the debate on the theory of the firm. The module will then progress to a part related to the environmental and social impacts of firm activities, and engage students about alternative forms of capitalism that might be able to remedy and prevent the negative spillovers created by economic activity. The third stage will examine governance and strategic decision-making as critical elements of the firm that will require innovative solutions backed up by experimental evidence.  The final stage will examine how other functional and organisational elements of the firm have been and can be redesigned to develop a stakeholder-centred form of enterprise. 

Special Topics in Organisational Theory/Strategy - This module will guide and teach you to develop a range of perspectives on strategy with an emphasis on organisational theory strategy.

Advanced Topics in Organisational Behaviour - Those who are wanting to pursue organisational behaviour should take at least one more advanced module on a topic within organisational behaviour. This might be focused on micro organisational behaviour that focuses more on intra-personal processes, such as emotions and cognitions, or meso organisational behaviour focusing more on inter-personal processes. This could also be special topics in organisational behaviour, such as gender and diversity in organisations, or moral psychology applied to organisations.

Readings in Social Networks/Social Capital - After completing this module you will understand the foundations of social capital research and have developed an awareness of the key themes in the social capital literature, appreciating the frontier of research in these themes. You will be able to theorize about the antecedents and effects of social capital and social networks for a broad range of individual, group, organisational and societal outcome. You’ll be able to apply arguments and concepts from social capital theory to contemporary challenges in research in strategic management, organisational behaviour and innovation and entrepreneurship.

Readings in Digital Business - In this module you will undertake readings on technology in organisations and digital business.

Year two - Research Project

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