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.  The prices for each course are listed alongside the course details.

Fill out this registration form and send to 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:

These courses are suitable for PGR Students and Early Career Researchers. Our Industrial Organisation course is designed to also be of interest to Industry Professionals.

Centre for Competition Policy (CCP),  Annual Conference: June 2019

Contests: Theory and Evidence, Annual Conference: 27th-28th June 2019

Behavioural Game Theory, Annual Workshop: 11 - 12 July 2019

PGR Summer Schools 2018-19 PGR Summer Schools 2018-19

The Summer Schools we are holding this year are:


Introduction to Data Visualisation using R 

Dr Jibonayan Raychaudhuri

May 14 | 4 Hour Course, 9 – 12, 1 - 2
Closing Date for Applications: 28 April
This course is worth 1 PPD Credit
PGR Rate: £30
Early Career Researcher Rate: £60

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. 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.

This course will take place in a computer lab. If you wish to bring your own computer please ensure that you have administrative rights as this course is meant to be interactive. R is free software and you will be sent details of how to install R prior to the course. Please be aware charging facilities may be limited and it is advisable to ensure the battery for your personal device is fully charged.


Big Data Econometrics in R

Dr Michael Kummer

May 13 | 8 Hour Course, 9 - 5
Closing Date for Applications: 28 April
This course is worth 1 PPD Credit
PGR Rate: £30
Early Career Researcher Rate: £60

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 part we will revisit basic regression, and the issues of empirical identification and the classic sources of bias. We will learn how to distinguish between correlation, prediction and causal inference.

In the second part 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. Students will learn practical skills using R, and will be able to build econometric models on robust statistical and econometric 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 include a practical sessions where students are challenged to replicate the results of real research in big data econometrics.

This course will take place in a computer lab. If you wish to bring your own computer please ensure that you have administrative rights as this course is meant to be interactive. R is free software and you will be sent details of how to install R prior to the course. Please be aware charging facilities may be limited and it is advisable to ensure the battery for your personal device is fully charged.


Industrial Organisation

Prof Eugenio Miravete Marin, Dr Franco Mariuzzo, Dr Farasat Bokhari

28/29/30/31 May | Run Times Day 1 - 9:45 - 17:15, Day 2, 3, 4 - 8:15 - 16:00,

Closing Date for Applications: 28 April
This course is worth 3 PPD Credits
PGR Rate: £90
Early Career Researcher Rate: £180
Industry Rate: £250


This course is comprised of three modules:

  • Discrete Choice Methods in Demand Estimation – Dr Farasat Bokhari
  • Price Discrimination: Business and Regulation Issues – Prof Eugenio Miravete Marin
  • Causal methods for competition policy – Dr Franco Mariuzzo

Discrete Choice Methods in Demand Estimation

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 module 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 this module we will also conduct merger analysis and simulations.

Price Discrimination: Business and Regulation Issues

This module covers the basic elements of price discrimination both from a theoretical and empirical perspectives. Market segmentation and price targeting of specific individuals or groups of individuals are key business tools to increase profits and/or help to prioritize the use of capacity limits in regulated industries. This increase in profits generates potentially large redistribution effects among different consumer types. The fact that consumers do not pay the same price has attracted the attention of regulators to investigate whether these pricing practices are fair and if businesses are taking advantage of consumers beyond the commonly accepted quantity discounts. We will review the legal treatment of price discrimination, its theoretical foundations, and cover the latest empirical studies on zone pricing, advance purchase discounts, vertical integration, income redistribution through pricing, and behavioral models of tariff choice and tariff design covering industries such as home improvements, airlines, retailing, alcohol distribution, and health care.

Causal methods for competition policy

Causal analysis has recently been playing a more prominent role in competition policy than it had a few years ago. The reason for its wider implementation is that its methods are much simpler to master than structural ones. The linearity that often accompanies reduced-form causal analysis methods leads them to be preferred for ease of their interpretation, which is an appealing feature for Court decisions. Advancements in the causal analysis literature have brought tools that are more flexible, while preserving the simplicity of interpretation of results.

In this module, we will present the econometrics of causal analysis methods and see their many applications in competition policy. There will be plenty of examples from retrospective merger evaluations, cartel damages and more. We will also see how these methods can easily be implemented in Stata.


Experimetrics

Prof Peter Moffatt

13, 14 June | 9am - coffee; the course runs 9.30am – 6pm
Closing Date for Applications: 28 April
This course is worth 2 PPD Credits
PGR Rate: £60
Early Career Researcher Rate: £120

This course is divided into two parts. In the first part, non-parametric and parametric tests of experimental treatments will be covered.  There will be a focus on the use of power analysis,  with the principal objective of trying to find the required sample size for a planned experiment.  The power command in STATA will be used heavily.  The Monte Carlo method will also be taught, and applied to situations in which the power command cannot be used.  The second part of the course will be concerned with the problem of estimating social preference parameters using data from distribution experiments.


Behavioural Game Theory 

Prof David Cooper

8, 9, 10 July | Running times TBA
Closing Date for Applications: TBA
This course is worth 2 PPD Credits
PGR Rate: £60
Early Career Researcher Rate: £120

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.

Attendees at the Summer School on Behavioural Game Theory are invited to attend the Workshop on Behavioural Game Theory 11-12 July free of charge.