Summer Schools Summer Schools

Summer Schools are a great way to gain an insight into frontier research through short intensive courses. All Summer Schools are free of charge for UEA registered PGR students and for PGR students from our potential DTP partners.  There will be a fee of £30 per full day for PGR students from other institutions and £60 per full day for all other attendees. Where programmes run for half a day, the fee will be reduced accordingly.

Contact Tom Cushan to express your interest.

The summer schools are held close to the time of a number of conferences co-organised with the School of Economics at UEA and which may be of interest:


CREED-CBESS-CEDEX (CCC) meeting: 17th-18th May 2018

Centre for Competition Policy (CCP) Annual Conference: 7th-8th June 2018

Contests: Theory and Evidence – Annual Conference: 25th-26th June 2018

Behavioural Game Theory Annual Workshop: 5th -6th July 2018 (dates are provisional)

PGR Summer Schools 2017-18 PGR Summer Schools 2017-18

This year we are holding Eight Summer Schools:

Big Data Econometrics using R

Dr Jack Fosten

14th-15th May (Mon-Tues); 10am-12pm and 2pm-4pm

Closing date for applications – 28th April

This course is an introduction to statistical methods used in analysing high-dimensional economic data, or ‘big data’, using the statistical program R. Nowadays it is often the case that economic researchers have access to data on hundreds or thousands of economic variables, making it difficult to specify an informative predictive model. This course addresses this issue, moving beyond standard regression techniques, such as Ordinary Least Squares (OLS), which break down in the face of big data. In the first day we will cover topics such as cross validation, stepwise selection and penalised regression (e.g. LASSO), all of which are sometimes referred to as ‘machine learning’ methods. In the second day we will focus on high dimensional time series methods such as forecast combination and dynamic factor models. Students will learn practical skills using R, and will be able to build econometric models on robust statistical grounds in situations where there may be many more variables than there are sample points. The morning sessions will be mostly theory and programming and the afternoon sessions will be practical sessions where students are challenged to replicate the results of cutting-edge research in big data econometrics.

Introduction to Data Visualisation using R 

Dr Jibonayan Raychaudhuri

16th May (Wed); 9am-12pm and 1pm-4pm

Closing date for applications – 28th April

The course is designed as an introduction to data visualization techniques using the R programming language. This is a “self-contained” course where we will first learn how to import (well–formatted) data into R.  We will then take a comprehensive look on how to plot data using R’s default graphics system, base graphics. Next, we will take a look at lattice – an R package which improves on the base R graphics package by providing us with an easy way of displaying multivariate relationships. Then we will learn about the ggplot2 package – a plotting system for R – based on the grammar of graphics, which provides a powerful model of graphics that makes it easy to produce complex multi-layered graphics. The course will finish with lab exercises where participants will learn how to create complex graphs by working out exercises. Participants should have access to a computer with administrative rights as

this course is meant to be interactive. Ideally, participants should already have R and R-Studio installed on their machines.

Analytical Methods for Competition Policy

Prof Eugenio Miravete

4th-6th June (Mon-Wed): 9am- 12pm

Closing date for applications – 28th April

This course reviews the difficulties that practitioners and research economists encounter when trying to apply economic models to data seeking to establish the market conduct and firm behaviour. Identification of market conduct is key to establish abuse of dominant position, collusion, damages, predatory behaviour, or anticompetitive effects of mergers among many others. This course is primarily targeted towards consultants in competition policy, but also open to graduate students interested in the subject

We will cover tools and concepts, ranging from simple to moderately complicated, that are used to evaluate empirically whether a market needs to be regulated, firms can be prosecuted, or damages can be claimed. In all those circumstances, equilibrium economic models are used in counterfactual analysis to determine by how much the current observed behaviour deviates from the efficient competitive outcome. Material will be presented in connection with summaries of empirical studies to illustrate the pros and cons of using different methods. The course can be complemented with the afternoon school on “Vertical restraints”.

Discrete Choice Methods in Demand Estimation

Dr Farasat Bokhari

4th-6th (Mon-Wed): 9am- 12pm

Closing date for applications – 28th April

Policy issues related to impact of introduction of new goods, taxation on imports or horizontal mergers often begin with careful estimation of demand for differentiated products, followed by counterfactual exercises using the estimated demand parameters. There is a large and growing literature on demand estimation. This short workshop will review some of the popular techniques of demand estimation in product and characteristics space approaches, and will then focus in on estimation details in discrete choice models. Topics covered will include logit estimation, an overview of the BLP method (Barry, Levinsohn & Pakes, 1995) and estimation of nested and random coefficients logit models. As part of the course we will also conduct merger analysis and simulations. The course can be complemented with the afternoon school on “Vertical restraints”.

Vertical Restraints

Prof Kai-Uwe Kühn

4th-6th June (Mon-Wed):  1pm - 4pm

Closing date for applications – 28th April

This 9 hours course provides an introduction to topics in vertical restraints: theories to generate anti and pro-competitive effects, Resale-Price Maintenance (RPM), Exclusive Dealing, vertical ‘most favoured nation’ clauses (MFNs). These topics have become a central focus of discussions on competition policy towards and regulatory intervention in the internet economy. The course presents the relevant theoretical framework, but is closely anchored in actual market behaviour and is geared towards an applied audience. The course applies the conceptual framework developed to an assessment of the most important internet cases.

Methods for competition policy evaluation

Dr Franco Mariuzzo

4th-6th June (Mon-Wed):  1pm - 4pm

Closing date for applications – 28th April

The objective of this module is to show how to conduct policy evaluations in competition policy. We will examine various types of methodologies that have been used within competition policy to evaluate policy outcomes. We will see which methodologies have been employed to evaluate mergers, cartels and abuse of dominant positions, and understand the way they operate and assumptions they rely on. There will be a discussion on methodologies more suitable for ex-ante and ex-post policy evaluations. We will try and emphasize advantages and disadvantages of each of the alternative methods available, and in the last part of the module we will see how methodologies have adapted and responded to new challenges to competition imposed by a more digital economy.

The module is structured in a way to cover the main methodologies from an introductory econometric perspective, view their application within competition policy and employ real world and simulated data to play around with the methodologies, as to gain deeper insight of the methods. Of course, given the key role of data, part of the discussion will be on the data that are needed to conduct proper applied analysis.

The module does not require pre-requisites in economics and econometrics and thus will be suitable to consultants and graduate students of any background. This module complements the course “Analytical Methods for Competition Policy” offered in the morning school by Professor Eugenio Miravete.

The expected learning outcomes are: familiarize with the many existing methods and gain insight on the way those work (pros and cons) and recognize when, and how, they should be applied.


Prof Peter Moffatt

18th –19th June, 9am - coffee; the course runs 9.30am – 6pm

Closing date for applications – 28th April

This workshop is divided into three parts. In the first part, non-parametric and parametric tests of experimental treatments will be covered. In the second part, the econometrics of theory testing in the context of auction experiments and market experiments will be considered. The final part will be concerned with the problem of estimation of social preference parameters using data from distribution experiments.

Behavioural Game Theory 

Prof David Cooper and Prof Enrique Fatas

3th – 4th July (Tues-Wed), 9am - coffee; the course runs 9.30am – 6pm (dates are provisional)

Closing date for applications – 28th April


Game theory, one of the most widely used mathematical tools in economics and the social sciences, is built on a foundation of strong assumptions about agent’s preferences and how agents make decisions.  Two decades of work by experimental economists has cast serious doubts on these assumptions.  Theorists and experimenters have responded by developing new theories that incorporate behavioral elements. The goal of this course is to familiarize you with research related to some of the most important topics of current research in behavioral game theory and to help you start thinking about potential research projects in this area.

Topics we will cover include other-regarding preferences, bounded rationality, infinitely repeated games, and coordination games. We will stress understanding how the various papers, both old and new, relate to current topics of research.  The main emphasis of the course will be on experiments related to behavioral game theory.  We will also go through some theory, but only to the degree that understanding the theory is necessary to understanding the experimental literature. 

The class will feature a mixture of lectures and group discussion.  You will be working in groups to develop and present a research idea.