MSc ECONOMICS AND DATA SCIENCE

This module focuses on various theoretical aspects within the linear regression framework using matrix algebra, complemented by simulations and applications to provide more intuition. A specialist econometrics software is used throughout, allowing a better understanding of the theoretical material using real world data and simulations. After a review of fundamental concepts in Econometrics, the module progresses to a detailed discussion of the multiple linear regression model (MLR), focusing on the theory of estimation, inference, and other important issues, such as, model misspecification and models that involve nonlinearities. The properties of the OLS estimator are discussed in detail, and simulated examples show all the adverse consequences on these properties if certain assumptions in the data or the population do not hold. Real world applications are considered, discussing whether these assumption hold in reality. For example, the presence and consequences of having non-spherical errors is discussed, focusing on the problem of heteroscedasticity. Moreover, special attention is paid on the problem of endogeneity, while the instrumental variable approach is presented as the main strategy to deal with it.

IN TAKING THIS MODULE YOU CANNOT TAKE ECO-7016B IT IS RECOMMENDED THAT STUDENTS TAKE ECO-7003A IN THE AUTUMN SEMESTER. The module is about modern macroeconomic theory where economies and not their parts are studied. The focus is consequently on the overall performance of the economy rather than on the functioning of particular parts of the economy. The module uses dynamic general equilibrium models where consumers, firms and governments are modelled as forward-looking agents who make the best of the economic environment they live in.

This module builds on econometrics material covered in earlier modules and is divided into two parts: 1) Time series methods (including ARIMA modelling, stationarity testing, ARCH/GARCH models, Volatility Spillover, VARs , Cointegration and VECMs) 2) Microeconometrics (including panel data methods, and models for binary response variables) There is an emphasis on the practical application of common estimation techniques, with the specialist econometric software package Stata used extensively.

This Autumn Semester module is intended to provide students with a grounding in the programming and data-analytic techniques that will be used in later modules and also in the dissertation. The main part of the module introduces students to programming methods in Python, including use of loops and lists, data cleaning and manipulation, methods of exploratory data analysis, data visualisation, web scraping, and methods for working with multiple data sets. Ethical issues faced when working with individual data will also be covered. The programming methods will then be applied to problems in policy evaluation, including applications of D-in-D and regression discontinuity methodology to naturally occurring data. The module ends with the use of web-search data in Economic Analysis.

The module aims to develop and reinforce in students appropriate skills that are required to tackle complex data science projects in economics using, the open source statistical software package, Python. The aim of this module is not to provide students with in-depth knowledge of any programming language per se. Rather, this module aims to teach students the fundamentals of programming, data management, data analysis, data visualization and machine learning techniques. These are techniques that students will find useful and relevant for the job market/any economic research involving data. The ability to solve problems using data and help students to “think with data” is the driving philosophy behind this module. This module will form an integral part of a two-module sequence involving the PGT module, Programming and Analytics for Behavioural Economists, ECO-7026A, or PABE. PABE will be a pre-requisite for EDS. Students will be taking PABE in Autumn followed by EDS in Spring. The aim of EDS will be to extend the knowledge students acquire in PABE, and focus on applications of the techniques to Economic problems. EDS will therefore build on and expand the breadth of skills acquired in PABE.

Economics Dissertation is the “icing on the cake” of an Economics MSc. It is a module that brings together the skills that you have learnt throughout your degree programme and applies these skills to study a particular topic of your interest. This module gives you an opportunity to spend a period of 2 or 3 months working exclusively on a topic of your own choice, at your own pace, with guidance from a supervisor. The module commences with a sequence of “dissertation training” lectures during the Spring Semester, including such themes as choosing a topic, accessing data, searching the literature, referencing, and qualitative data analysis. There are further dissertation training lectures during late June and early July, held in computer labs, with the objective of providing the types of econometric skills often required in dissertation research. The Econometric software STATA is used, the same as used in taught modules in Econometrics. At the end of the Spring semester, you will submit a research proposal stating the research question you would like to address and proposing a suitable methodology. You can also select to work on a dissertation topic either with a business, charity, or other organization. In all cases, it is your responsibility to come up with a research proposal although you are encouraged to speak with instructors and the PG Course Director for advice and guidance. On the basis of your proposal, a suitable supervisor will be allocated to you. At least three meetings with the supervisor should take place between May - July. The total contact time over these meetings should be at least three hours. At the first meeting, the research proposal is discussed. By the time of the third and final meeting, you should ideally have supplied a first draft of the dissertation for your supervisor to provide feedback on. The deadline for the dissertation is at the end of August and the word limit for dissertations is either 8,000 or 12,000, depending on which MSc you are taking. If you want to work on a dissertation topic with a business, charity, or other organization you must get your dissertation topic pre-approved by the PG Course Director.