The Department of Economics at Birmingham has a long and distinguished history of research, with important advances in mathematical economics and econometrics being made here.
Members of the department are active in research in a broad range of topics in Economics. We actively collaborate with researchers in other schools of the university (including the Business School, Computer Science, Education, Engineering, Public Policy and Public Health) and with economists in other universities in the UK (including Warwick, Nottingham, York) and in other countries (USA, France, India to name a few).
Research within the department is organised into a number of research groups:
The Behavioural, Experimental and Data Science (BEADS) Lab is actively involved in the investigation of human decision-making and behaviour. We tackle challenges in decision research from multiple perspectives. Our research aims to:
- Verify and test theories of human behaviour
- Probe into the deep causes of empirical anomalies
- Offer cutting-edging solutions to improve decision-making quality
To become a participant in our studies, sign up at www.beadsnetwork.org.
The Department of Economics have recently obtained research funding from numerous funding bodies including:
- the British Academy,
- the Department of Education and Skills,
- the Economic and Social Research Council,
- the Engineering and Physical Sciences Research Council,
- the European Union,
- the Leverhulme Trust
- the World Bank
The research of the department has created substantial impact in policy and practice.
Members of the department lead research centres such as the Centre for Crime, Justice and Policing (Siddhartha Bandyopadhyay) and The Birmingham Centre for Environmental and Energy Economics and Management (David Maddison), which is part of the Birmingham Energy Institute. The National Audit Office – University of Birmingham Tax Centre is led by Kimberley Scharf.
Members of the department provide advice to the National audit office, police forces, charities and various think tanks and have in the recent past served in a senior capacity within the Bank of France (Anindya Banerjee) and as Commissioner on the Industry and Parliament Trust (IPT) Sustainability Commission (Matthew Cole).
Our impact work is diverse and encompasses research on such varied topics as estimating risk attitudes, valuing the present vs future, leadership success for business, evaluating interventions in the criminal justice system and the human aspects of cybersecurity.
Some key impact generating projects
Siddhartha Bandyopadhyay with Anindya Banerjee and Matthew Cole along with an interdisciplinary team from Psychology and Social Policy are looking at evaluating the impact of several policing interventions. These include building a solvability model for the police, understanding what determines victim satisfaction, assessing factors that lead to accidents and how they can be mediated by enforcement, engineering and educational initiatives. Several of our PhD students (Katharine Inglis, Ariana Matsa, Neha Prashar and Tong Zhang) are actively involved in such work. There is also a formative strand of work with Nathan Hughes and Joht Chandan on understanding an initiative by West Midlands Police to use their available intelligence to identify young people experiencing adversity.
Wider criminal justice sector interventions
Siddhartha Bandyopadhyay has analysed alternatives to custody, looking at both aggregate data (with his PhD student Juste Abramovaite) as well specific interventions focused on the area of intimate partner violence with his PhD student Aixa Garcia Ramos and colleagues from Psychology (Jessica Woodhams) and Social Policy (Surinder Guru).
The economic valuation of flood risk
David Maddison and Robert Elliott have been working on the economic valuation of flood risk. They utilise a common technique for valuing environmental risks – the idea that these risks are capitalised into house price differentials. Their meta-analysis provides a set of best estimates which could be used by potentially any agency anywhere in the world to value projects where there is a change in the risk of residential flooding. They have engaged with DEFRA and the Environmental agency as part of their work.
New Estimates of the Elasticity of Marginal Utility for the UK
David Maddison and his co-author survey and then create evidence on the elasticity of the marginal utility of income for the UK. This is an essential parameter for determining the social discount rate. This technique measures all of the costs and benefits of a project in monetary terms relative to some baseline in which the project is not implemented. They have shown that the best available evidence for the elasticity of marginal utility favours a 4.5 percent discount rate which declines to 4 percent in the very long term. This is contrary to what is now used for public sector projects.
Business Model Innovation in the Media Industry
Ganna Pogrebna and colleagues consider ways to improve business and economic modelling in the media industry. In a series of papers, they look at how consumer satisfaction in the media industry can be predicted using publicly available as well as private datasets. In a study “Windowing Television Content: Lessons for Digital Business Models” they use data from a large British media company to investigate whether and to what extent a strategy where content is made available to consumers through different channels over time, named Windowing business models, may be appropriate for releasing television programmes. By initially exposing consumers to a controlled quantity of free content greater value can be captured at later stages as 55% of these consumers are 13-20% more likely to become paying subscribers. Results confirm that there is a market for successful distribution of television content using a Windowing strategy. These results have been taken on board by the partner media company. In two subsequent papers, they mine data from IMDB web pages to explore the determinants of success for TV shows and films. We combine decision-theory modelling with machine learning algorithms to suggest new business models for media companies.
Expert Leadership: Exploring Leadership Success for Business
According to the expert leadership theory (Goodall, 2009), experts in a particular field make better leaders than professional managers. For example, the expert leadership theory suggest that top-published academics make more successful Vice Chancellors of universities and heads of departments in an academic setting. The same results were obtained in the health sector domain and the Formula 1 domain (see, e.g., Goodall and Pogrebna, 2015). Yet, it is not clear what factors influence leadership success. Goodall and Pogrebna (2015) use Formula 1 dataset to show that experts perform better than professional managers as F1 team principals (their teams reach more wins and podiums) and suggest that length of professional experience of the leader might be the single determining factor of success. This paper has generated impact in the F1 industry. A further study is currently being conducted where further data is collected and analysed to generate impact in further industries.
Human Aspects of Cybersecurity
In two recent papers Ganna Pogrebna and co-authors cybersecurity and risk/vulnerability perceptions. In the first paper, they develop a new domain-specific risk attitude scale for cybersecurity risks (CyberDOSPERT) and test this scale with a sample of American population. They find that individual perceptions of cybersecurity risks are correlated with individual perceptions of ethical risks. They also find significant heterogeneity in risk perceptions which vary by gender, political views, and other demographic characteristics. In the second paper, they conduct a large-scale international study measuring individual vulnerability towards cybersecurity risks in “lay” and “expert” population. They find that individual vulnerability towards cybersecurity risks depends on the type of data rather than on individual characteristics; although experts exhibit “reference risk bias” - when primed in terms of risk for a particular type of data, experts exhibit vulnerability to that type of data while neglecting potential vulnerabilities for other types of data. Results from these two papers have been presented to a number of large financial organisations and it is hoped that scales developed in the papers will be taken up by these organisations.