MPhil in Economics Course Structure

The course aims to provide students with a grounding in statistical and probability theory, econometric theory and methods, and empirical applications in economics, such that applied econometrics reported in the main economics journals can be read with a good understanding and a critical perspective. The subject has advanced rapidly over the last couple of decades, and is an essential element in every economist’s toolkit.

The course will cover a range of topics that are important for understanding empirical research in microeconomics and macroeconomics, likely including:

• Probability
• Statistical Inference
• Linear Regression
• Instrumental Variables
• Generalized Method of Moments
• Maximum Likelihood
• Limited Dependent Variables (discrete choice, censored regression, selection)
• Time Series (ARMA models, ARDL/ECM models, unit roots and cointegration)
• Panel Data (fixed effects, random effects, dynamic models)
• Causal Inference (treatment effects, matching, LATE, difference-in-differences, regression discontinuity designs)

This course covers a selection of methods that are widely used in modern econometric theory and practice. It aims to provide students with a grounding in statistical and probability theory, econometric theory and methods, such that students are able to do research using econometric techniques, as well as have the basis for undertaking research in econometric theory.

Most students will take this course in Year 2 after already having passed Core Econometrics in Year 1. Some students, who have enough background in economics (and only with the permission of GSC) can take the course in Year 1 instead of the Core course. This course thus assumes more previous knowledge than the Core course and advances faster.

The course will cover a range of topics that are important for applying, understanding and developing econometric tools, likely including:

• Principles of Statistical Inference
• Asymptotic Theory
• Model Selection, Shrinkage and Machine Learning
• Non-parametric and Semi-parametric Methods
• Simulation-based Methods
• Advanced Topics in Time Series
• Advanced Topics in Panel Data
• Advance Topics in Causal Inference

The objective of the course is to give students a thorough grounding in modern dynamic macroeconomic theory so that they can understand the modern macroeconomic literature and can perform macroeconomic analysis in a professional environment.

In particular, the course will likely cover the following topics:

• Introduction to dynamic optimization in economics (discrete and continuous time)
• Numerical methods for solution, calibration and estimation of models
• Models of economic growth & Real Business Cycle models
• Models with labor market rigidities & Models with financial frictions
• New Keynesian models
• Fiscal and monetary policy
• Unconventional policies
• Open economies models
• Models with heterogeneous agents

The objective of the course is to give students a thorough grounding in modern dynamic macroeconomic theory so that they can understand the modern macroeconomic literature and can perform macroeconomic analysis in an academic environment.

Most students will take this course in Year 2 after already having passed Core Macroeconomics in Year 1. Some students, who have enough background in economics (and only with the permission of GSC) can take the course in Year 1 instead of the Core course. This course thus assumes more previous knowledge than the Core course and advances faster.

In particular, the course will likely cover the following topics:

• Empirical methods for estimation and identification in macroeconomics
• Advanced numerical methods for macroeconomic models
• Open economy models, exchange rate and terms of trade
• Imperfect information in macroeconomics
• Labor market frictions and unemployment
• Heterogenous models for macroeconomic analysis
• Macroeconomics policies at the zero lower bound
• The role of communication for economic policy

The objective of the course is to give students a thorough grounding in microeconomics so that they can understand the modern microeconomic literature and can perform microeconomic analysis in a professional environment.

Topics covered in this course will be:

• Consumer and Producer Theory and Choice under Uncertainty
• General Equilibrium
• Game Theory
• Contracts, Bargaining, Theory of the Firm, and Auctions
• Welfare and Public Economics

The objective of the course is to give students a thorough grounding in microeconomics so that they can understand the modern microeconomic literature and can perform microeconomic analysis in an academic environment.

Most students will take this course in Year 2 after already having passed Core Microeconomics in Year 1. Some students, who have enough background in economics (and only with the permission of GSC) can take the course in Year 1 instead of the Core course. This course thus assumes more previous knowledge than the Core course and advances faster.

Topics covered in this course will be:

• Consumer and Producer Theory and Choice under Uncertainty
• General Equilibrium
• Game Theory
• Contracts, Bargaining, Theory of the Firm, and Auctions
• Welfare and Public Economics

This course will teach students how to investigate empirical research questions. Any relevant statistical theory will be reviewed briefly as required, but emphasis throughout will be on developing their ability to apply this knowledge, to interpret the results of empirical work and to on hands-on practical skills with data. 

The course will cover a range of methods and frameworks that are essential for applying and understanding empirical work in Economics. Topics will likely include:

• Data structures and sampling.
• The causes and consequences of measurement errors.
• The Rubin-Neyman causal model.
• Instrumental variables, partial identification, conditional independence, the Local Average Treatment Effects (LATE) framework.
• Practical analysis of causal effects.
• Structural versus reduced form methods.
• Applied examples in micro- and macro-econometrics.

This course is targeted at future DPhil/PhD students who want to use mathematical modelling in their research. This includes students who work purely on theoretical topics as well as students who want to combine theoretical models with empirical research. The course will focus on proof and modelling techniques, i.e., provide a toolkit. The course will rely on extensive reading assignments and problem sets and the lectures will be mostly used to discuss the topics and to answer questions.

Topics will likely include:

• Real Analysis
• Advanced Linear Algebra
• Multivariate Calculus  & Constrained Optimisation
• Differential and Difference Equations
• Choice under Uncertainty
• Advanced Probability & Random Processes
•  Measure Theory & Stochastic Calculus
• Optimal Control Theory & Dynamic Programming

This course covers a selection of methods that are widely used in modern econometric theory and practice. It aims to provide students with a grounding in statistical and probability theory, econometric theory and methods, such that students are able to do research using econometric techniques, as well as have the basis for undertaking research in econometric theory.

Most students will take this course in Year 2 after already having passed Core Econometrics in Year 1. Some students, who have enough background in economics (and only with the permission of GSC) can take the course in Year 1 instead of the Core course. This course thus assumes more previous knowledge than the Core course and advances faster.

The course will cover a range of topics that are important for applying, understanding and developing econometric tools, likely including:

• Principles of Statistical Inference
• Asymptotic Theory
• Model Selection, Shrinkage and Machine Learning
• Non-parametric and Semi-parametric Methods
• Simulation-based Methods
• Advanced Topics in Time Series
• Advanced Topics in Panel Data
• Advance Topics in Causal Inference

The objective of the course is to give students a thorough grounding in modern dynamic macroeconomic theory so that they can understand the modern macroeconomic literature and can perform macroeconomic analysis in an academic environment.

Most students will take this course in Year 2 after already having passed Core Macroeconomics in Year 1. Some students, who have enough background in economics (and only with the permission of GSC) can take the course in Year 1 instead of the Core course. This course thus assumes more previous knowledge than the Core course and advances faster.

In particular, the course will likely cover the following topics:

• Empirical methods for estimation and identification in macroeconomics
• Advanced numerical methods for macroeconomic models
• Open economy models, exchange rate and terms of trade
• Imperfect information in macroeconomics
• Labor market frictions and unemployment
• Heterogenous models for macroeconomic analysis
• Macroeconomics policies at the zero lower bound
• The role of communication for economic policy

The objective of the course is to give students a thorough grounding in microeconomics so that they can understand the modern microeconomic literature and can perform microeconomic analysis in an academic environment.

Most students will take this course in Year 2 after already having passed Core Microeconomics in Year 1. Some students, who have enough background in economics (and only with the permission of GSC) can take the course in Year 1 instead of the Core course. This course thus assumes more previous knowledge than the Core course and advances faster.

Topics covered in this course will be:

• Consumer and Producer Theory and Choice under Uncertainty
• General Equilibrium
• Game Theory
• Contracts, Bargaining, Theory of the Firm, and Auctions
• Welfare and Public Economics

Behavioural Economics is a blend of traditional neoclassical microeconomics and empirically motivated assumptions whose goal is a better understanding of economic behaviour. It can be divided into behavioural decision theory and behavioural game theory. Each subfield differs from its mainstream counterpart by paying particular attention to the psychological realism of behavioural assumptions and their consistency with empirical evidence. The goal is to identify empirically important deviations from traditional assumptions, use the alternative assumptions the evidence suggests to build tractable formal models, and use the models to reconsider standard microeconomic questions. (Much of the empirical evidence used is experimental, but this is not a course in experimental economics: Experimental methods are considered only as needed to interpret evidence; and connections with field evidence will be made whenever they are helpful.)

This course is designed to introduce you to major themes in the microeconomics of development, covering both empirical and theoretical methods. The course is taught in Michaelmas, and comprises 16 lectures, covering core development economics theory and discussing application of microeconometric methods to developing countries. Lectures are divided into four modules; in 2019-20, we plan to offer modules on (i) firms and development, (ii) organisations and development, (iii) households and development and (iv) cash, microfinance and development.

This course is designed to give you an opportunity to specialise in particular topics in development economics.  The course is normally divided into eight 4-week modules; each module is self-contained, and can be taken independently.  You are required to answer two questions on the exam, with at most one per module.  MPhil students are strongly recommended to attend at least three modules in order to have useful choice of questions on the exam.  Modules vary from year to year; in 2018-19, the following modules were offered: (1) firms and labour markets in low income countries; (2) openness and development; (3) applications of behavioural economics to the developing world; (4) microfinance, cash transfers and saving; (5) the political economy of economic development; (6) risk, disasters and insurance; (7) education, skills and development; and (8) structural transformation and growth; (9) gender development economics. Modules typically involve close reading of academic literature; some may also link to current discussions of development policy.

This course will provide an introduction to the sources and methods of quantitative economic history and review some of the major current debates of interest to economists. It aims to show both how economic analysis can sharpen our understanding of history and how historical research can be used to shed light on the current state of the economy. The first part of the course will focus on the Great Divergence of living standards between Europe and Asia, showing how recent quantitative work has sharpened our understanding of both the timing and the causes of the divergence. The second part concentrates on the period from the Industrial Revolution to the present, highlighting the roles of technology, geography and income distribution in shaping economic performance.

This course provides an introduction to the history of globalisation and to monetary and financial history. The first half of the course provides an introduction to the history of the international economy over the past two centuries and asks. What were the causes and consequences of globalisation and deglobalisation over the long run? The course will focus in particular on the period between 1870 and 1939 and special attention will be paid to the Great Depression and its consequences.

The second half of the course offers a mpore thematic approach to monetary and financial history, with successive lectures exploring money and the price level, business cycle,  financial crisis and the international monetary system. What provides the nominal anchor for an economy? Do fluctuations in nominal magnitudes have concequence for real activity? Can financial crisis be explained by weak economic fundamentals or are they self-fulfilling panics? How have balance of payments adjustment mechanisms worked in different exchange rate regimes?

The course is an introduction to major issues in asset pricing and market microstructure.  Topics covered may include the following: equilibrium in security markets, incomplete asset markets, options pricing, CAPM and APT, money and default, financial crisis and systemic risk, models in theoretical and empirical microstructure, prices and rational expectations equilibrium, strategic trading.

The course covers the major research themes in corporate finance. Theoretical topics include capital structure, the real effects of secondary security markets, long-term contracting and incomplete contracts, mechanism design and corporate insolvency. Lectures on empirical corporate finance will focus on identification and estimation issues related to research on governance and ownership structure.

This course will provide a solid theoretical foundation in machine learning. This will allow you to:

• Become critical consumers of machine learning research, including an understanding when new methods might or might not be used for empirical work in economics,
• Develop your own research agenda around importing ideas from machine learning into economic and econometric theory, and
• Speak to the machine learning literature, contributing ideas from economics.

The aim of the course is to give an overview of the recent literature in international macroeconomics and finance as well as to develop tools and ideas for writing research papers. The first part focuses on the real determinants of the current account. The second part studies international financial markets and business cycles. The last part looks at financial crises and monetary policy in open economy.

This course will introduce you to major themes in the modern analysis of labour markets, covering both empirical and theoretical methods. Part I, focuses on the flow approach to labour market analysis, covering job search, labour market matching models, and the use of equilibrium search models for policy analysis. Part 2, begins with the evidence on wages and inequality, then explores foundations for the explanation of wages – labour supply, human capital, and the task approach – before focusing on the particular implications of discrimination and international trade.

The course covers a number of topics relevant for modern empirical macroeconomic research: descriptive analysis and forecasting, identification and estimation of SVARs/DSGEs, nonlinearity and Bayesian inference (maybe). Aimed as macroeconomists who want to know how to use state-of-the-art methods in their applied work and econometricians who want to know why those methods work.

This course is aimed at graduate students in economics and related fields with the goals of:

• Exposing students to a range of overarching themes and specific topics in political economy
• Critically examining a broad range of empirical methods used in the field of political economy (and beyond)
• Helping students transition from studying the research of others doing their own. 

Students should leave the course with an appreciation of the myriad roles of political institutions and actors in shaping economic outcomes today and historically. They should have a sense of the frontier research questions regarding the interaction of economics and politics. And, they should have the ability to apply and evaluate research methods used in the field.

The course focuses on social insurance and the welfare state, in particular on how much governments protect individuals against risk, such as of becoming unemployed or of receiving low wages and on the impact of redistribution programs to reduce poverty. This naturally feeds into understanding the importance of uncertainty and inequality. The course combines empirical analysis with theoretical models and institutional knowledge of actual government programs. The course uses a life-cycle framework to model how individuals respond to social insurance and the welfare state.

This is a reading group style course which is intended to give an overview of the breadth of current frontier work in econometrics. The majority of weekly sessions will consist of student presentations, followed by group discussions.

The lectures will introduce three popular deviations from the assumption of full information rational expectations that is commonly made in macroeconomics. The first deviation is to assume that agents are in no better position than an econometrician as they attempt to learn the parameters and laws of motion of economy. We will use elements of stochastic approximation theory to examine the e-stability principle, which if satisfied allows agents to lean their way into a rational expectations equilibrium. The second deviation relaxes the assumption that agents are certain about the processes that generate data in the economy. Instead, they entertain multiple models and make decisions that are robust to potential model misspecification. We will see how this behaviour can rationalise apparently puzzling behaviour, for example in asset markets. Finally, the third deviation is to assume that agents have only limited ability to process information, in which case they have to decide what to pay attention to and what to leave to rational inattention. The implications of rational inattention for macroeconomic dynamics and individual decision making will be discussed.

The course covers advanced topics, with the aim of introducing students to the frontier of macroeconomics research and equipping them with the necessary skills to develop their own, independent research agenda. The course facilitates the transition from coursework to independent research, and the development of analytical frameworks to assess macroeconomic conditions.

The course will mix traditional lectures, aimed at introducing state-of-the-art topics, with student-led presentations and discussions. The format will provide a constructive and open environment to foster critical thinking.

Students will learn cutting-edge topics and techniques in macroeconomics to write an innovative dissertation at the frontier of knowledge, and develop an analytical approach to address macroeconomic issues. The course will also contribute to develop skills in discussing new ideas, presenting them in front of a critical audience, and write focused and critical reports and research proposals, The course will also facilitate discussions and cooperation among students.

Aims of this course:

• Gain exposure to 'cutting edge' topics in micro theory
• Understand some of the key questions and developments in Theory
• Learn tools and ideas for engaging in theoretical research

Topics covered:

• Mechanism Design
• Market Design

Topics covered:

• Decision theory and learning
• Information design and Repeated Games

This course covers some topics in probability theory with a focus on techniques to and asymptotic distributions. This course is targeted at students who want to use asymptotic methods in their research. This includes students who work purely on theoretical topics as well as students who want to gain further understanding of the asymptotic distribution theory underlying econometric modelling techniques.

The course will present an overview of the literature on spatial and urban economics.  A theory part will cover models of economic organisation within cities and also the distribution and organisation of cities within countries.  The theory part will loosely follow the book by Fujita, Krugman and Venables and recent extensions.  An empirical part will discuss recent empirical papers in the field, including on shock and recovery, factors behind urbanisation and the effects of various infrastructure programs on urban development.