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The focus of this impact is the effect of the Global Vector Autoregressive (GVAR) project on international organisations such as the International Monetary Fund (IMF) and the European Central Bank (ECB) as well as its use by commercial organisations such as the Economist Intelligence Unit and the Asian Development Bank. The impact has enhanced the tools used by the ECB for communicating its policies. It has also allowed the IMF to demonstrate the effects of oil prices. The Economist Intelligence Unit found it an effective framework for assessing a wide-range of scenarios. The Asian Development Bank uses the GVAR model for forecasting in Asia.
University of Huddersfield research into knowledge engineering, domain modelling and machine learning has raised professional, industry and policymaker awareness of novel ways of designing more efficient, cost-effective and sustainable management networks. This is particularly the case in the field of transportation, where recognition of such techniques has significantly increased among stakeholders throughout the UK and across Europe. The research has been credited with informing a "step-change in thinking" and is now central to the £16m EPSRC Autonomous and Intelligent Systems Programme, which has attracted more than £4m in financial and in-kind support from hi-tech industries.
Economic models with adaptive learning developed in Mitra's research are increasingly being adopted by policy authorities and in the training of graduate students. The usual paradigm in economics, rational expectations (RE), unrealistically assumes complete knowledge on the part of policymakers and households. Mitra's work has emphasised informational limitations faced by policymakers and provides guidance for policies in these situations. Monetary policy is an area where different types of models are heavily used and their results are one input to the policy decisions. The impact of this case study should be seen by virtue of pioneering an approach that has come to be accepted by the economics profession as the realistic one to analyse macroeconomic policy changes under bounded rationality; this approach has led to a large outgrowth of applied models used in policy making in recent times. These policy oriented works have provided support for the aggressive monetary and fiscal stimulus packages that have been adopted in the wake of the financial crisis in 2007. They have been disseminated widely through presentations at numerous conferences sponsored by central banks in the presence of senior policymakers. The research has also influenced the teaching of macro and monetary economics; it is part of reading lists of leading MPhil/PhD programmes and has in part contributed to PhD students specialising in this broad area of research.
The world financial crisis and recession of 2007- 2009, and the continued stagnation of global economies, has raised the question of how governments and central banks should respond in deep recessions. Prof. Evans and colleagues have shown using macroeconomic models with adaptive learning that after large pessimistic shocks, a rapid switch to aggressive monetary easing is required and aggressive fiscal policy may be needed. To achieve policy impact this work has been presented in numerous central bank conferences, and it has caught the attention of several members of the US Federal Reserve Open Market Committee (FOMC). The policies of the FOMC since 2008 have been consistently aggressive, despite public criticism and even dissension within the FOMC itself. This research has provided important academic support for the application of these policies.
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.
The making of monetary policy requires accurate forecasts of key monetary variables, and in particular of the inflation rate. Research conducted by Charemza has led to the development of new methods of forecasting inflation. The relevant information is summarised in a Monetary Policy Indicator (MPI) that can be used to identify the optimal timing of active monetary policy. Since June 2006, the MPI has been applied by the Monetary Policy Council (MPC) of Poland in the process of deciding on the levels of monetary instruments (interest rates and reserve levels). The use of these methods has contributed to Poland's economic stability and helped to ensure unprecedented growth of the Polish economy in the last decade.
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.
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.
Following the global economic crisis of 2007, the question of how macroeconomic policies could be used to ameliorate its consequences has come to the fore. Research led by Professor Patrick Minford at Cardiff Business School (CBS) has promoted a shift in policy in the UK in a classical direction and away from the Keynesian demand management approach. CBS researchers from the Julian Hodge Institute of Applied Macroeconomics (JHIAM) have shown through economic modelling how a series of measures, for example, clear monetary rules which target inflation, could benefit the UK economy. The research has also been used both directly and indirectly, via MPs and intermediaries, to inform policy debates around such major issues as Britain's membership of the European Union (EU), as well as contributing to the wider public debate.