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The European Central Bank (ECB) uses forecasting tools to make predictions about the Eurozone economy as a whole. The University of Leicester has worked with the ECB to modify its main forecasting tool to improve its ability to take effective and timely action to keep inflation low and minimise deflation.
Similarly, the United Nations prepares a submission to each G8 Summit which includes forecasting and policy analysis based on the economies of the 193 member states. The forecasting tool used to create this submission has also been created in collaboration with the University of Leicester. These modelling tools help the world's most powerful leaders - both political and financial - to make informed and timely decisions about issues affecting economic stability, global food security and international safety.
Research carried out by members of the Credit Research Centre (CRC) at the University of Edinburgh has changed the way that credit risk modelling teams in major multinational retail banks think about and model the probability that an applicant will default on a loan. Such models are used monthly to assess the risk associated with most of the 58 million credit cards in the UK and hundreds of millions of credit cards elsewhere in the world. The research has also changed the way banks model a crucial parameter in the amount of capital they have to hold to comply with international regulations, and has allayed their concerns about estimating models based on only samples of previously accepted applicants.
The School of Mathematics at Cardiff University has developed important statistical and mathematical models for forecasting consumer buying behaviour. Enhancements to classical models, inspired by extensively studying their statistical properties, have allowed us to exploit their vast potential to benefit the sales and marketing strategies of manufacturing and retail organisations. The research has been endorsed and applied by Nielsen, the #1 global market research organisation that provides services to clients in 100 countries. Nielsen has utilised the models to augment profits and retain their globally leading corporate position. This has led to a US$30 million investment and been used to benefit major consumer goods manufacturers such as Pepsi, Kraft, Unilever, Nestlé and Procter & Gamble. Therefore the impact claimed is financial. Moreover, impact is also measurable in terms of public engagement since the work has been disseminated at a wide range of national and international corporate events and conferences. Beneficiaries include Tesco, Sainsbury's, GlaxoSmithKline and Mindshare WW.
A series of econometric methods and software, designed by a team of econometricians at Oxford, have been adopted as standard by a large range of governmental bodies, international agencies and businesses. The econometric methods are designed to model and forecast high-dimensional, evolving economic processes facing multiple structural shifts, while the econometric software (PcGive) implements the resulting best-practice procedures. The application of these methods have resulted in more appropriate empirical models, improved robust forecasts, and, consequently, better decision making by these bodies.
Garratt's research on methods for quantifying the uncertainty surrounding macroeconomic forecasts, uncertainty which arises from not knowing the true model of the economy and from having to use inaccurate data, has been applied by Central Banks and national statistical agencies in their forecasting exercises and their analysis of policy interventions. Notably, Norges Bank (the central bank of Norway) has developed a system called the System for Averaging Models, which they use when they make macroeconomic forecasts and when they predict the effects of possible monetary policy actions, which incorporates Garratt's results.
Garratt's research provides new methods to allow for uncertainty about the 'true' model by using combinations of different possible models, when making forecasts. His research provides new procedures to take `data uncertainty' into account, when forecasts have to be based on real-time data (that is, inaccurate data which is available to the policymaker when a forecast is produced but which is revised later on). Garratt's research quantifies the effect of this uncertainty on forecasts by constructing probability density functions. Central banks and statistical agencies have applied his findings when making forecasts and undertaking policy analysis. Garratt's research has been disseminated through refereed journal articles, conference presentations, consultancy work with policy makers, and presentations to policy makers, including an invited presentation to HM Treasury.
Loudness is the subjective magnitude of a sound as perceived by human listeners and it plays an important role in many human activities. It is determined jointly by the physical characteristics of a sound and by characteristics of the human auditory system. A model for predicting the loudness of sounds from their physical spectra was developed in the laboratory of Professor Brian Moore with support from an MRC programme grant.
The model formed the basis for an American National Standard and is currently being prepared for adoption as a standard by the International Organization for Standardisation (ISO). In addition, the model has been widely used in industry worldwide for prediction of the loudness of sounds, for example: noise from heating, ventilation and air-conditioning; inside and outside cars, and from aircraft; and from domestic appliances and machinery.
Now-casting is the prediction of the present, the very near future, and the very recent past. It has been developed within a research programme led by Lucrezia Reichlin at LBS. It is relevant because key economic statistics, particularly quarterly measures such as GDP, are available only with a delay. Now-casting exploits information which is published early and at higher frequencies than the target variable and generates early estimates before the offb01cial fb01gures become available.
Now-casting has signifb01cant infb02uence and impact. The techniques reported in this case study are in widespread use by central banks and policy institutions. Furthermore, this research has achieved successful commercial impact via Now-Casting Economics Limited.
A two-dimensional flood inundation model called LISFLOOD-FP, which was created by a team led by Professor Paul Bates at the University of Bristol, has served as a blueprint for the flood risk management industry in the UK and many other countries. The documentation and published research for the original model, developed in 1999, and the subsequent improvements made in over a decade of research, have been integrated into clones of LISFLOOD-FP that have been produced by numerous risk management consultancies. This has not only saved commercial code developers' time but also improved the predictive capability of models used in a multimillion pound global industry that affects tens of millions of people annually. Between 2008 and 2013, clones of LISFLOOD-FP have been used to: i) develop national flood risk products for countries around the world; ii) facilitate the pricing of flood re-insurance contracts in a number of territories worldwide; and iii) undertake numerous individual flood inundation mapping studies in the UK and overseas. In the UK alone, risk assessments from LISFLOOD-FP clones are used in the Environment Agency's Flood Map (accessed on average 300,000 times a month by 50,000 unique browsers), in every property legal search, in every planning application assessment and in the pricing of the majority of flood re-insurance contracts. This has led to more informed and, hence, better flood risk management. A shareware version of the code has been available on the University of Bristol website since December 2010. As of September 2013, the shareware had received over 312 unique downloads from 54 different countries.
Research by Oxford econometricians provided the basis for innovative new methods for predicting periods of potential financial stress and providing protection for investors against extreme events. During periods of financial stress, equity funds tend to sharply lose value while volatility tends to increase. Adding some long volatility exposure to a standard equity portfolio can significantly improve the tail behaviour of a portfolio. However, it is expensive to continually hold volatility contracts due to the volatility risk premium. Researchers at Man Group have applied the Oxford research to create new strategies to protect against tail risk and these are incorporated in their Tail Protect fund launched in October 2009.
Neuberger, together with David McCarthy (Imperial), who, in their earlier work, had raised concerns about the sustainability of the Pensions Protection Fund (PPF), were commissioned by the Fund to conduct research on alternative levy structures. This led to the development of a new risk-based levy structure, which was implemented over the years 2012-2013. This research and its resulting impact have not only shaped how the PPF operates in ensuring the levy's burden is fairly shared, but has also benefited all UK holders of occupation based pensions and the taxpayer at large.