Scotland as an Optimal Currency Area

Since the Scottish independence movement has reached the point that there will be a referendum on Scottish independence this September, the issue of whether the Scotland is optimal currency areas is very topical.In this paper we review the microeconomic foundations of an optimal currency area. We test these microeconomic foundations. We find that the UK, Scotland and the UK without Scotland meet the microeconomic criteria for a common currency area. While adopting a common currency is ultimately a political decision, these results imply that the broadest of these areas, the UK, is the optimal currency area in the sense of minimizing transactions costs.We do find differences in the UK less Scotland and Scotland economies in loan data. We further find that neither the euro bloc nor the euro bloc including Scotland meet the microeconomic criteria for a common currency area. In the event of a “yes” vote for Scottish independence, the immediate problem facing the Scottish government is to decide on an exchange rate regime that is seen as credible by the financial markets to avoid a flight of capital. How policymakers chooses between alternative exchange rate regimes is currently a topic for hot debate in central banking circles and the process of a monetary union breaking up is a fascinating area worthy of future research

Stock Market Volatility, Risk Attitude and the Demand for Money in the UK

Is stock market volatility an important determinant of money demand in the UK? If yes, what is the driving force behind that effect? In a cointegration framework, we find that volatility in share prices is an important positive determinant of money demand, alongside standard variables and the stock price level. By studying different stock market indexes effects, we find that the risk aversion of investors is an important force behind the effect, implying that the effect is due to investors’ flight to safer assets in times of volatile stock prices

Does money matter in inflation forecasting?.

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. In our forecasting experiment we use two non-linear techniques, namely, recurrent neural networks and kernel recursive least squares regression - techniques that are new to macroeconomics. Recurrent neural networks operate with potentially unbounded input memory, while the kernel regression technique is a finite memory predictor. The two methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a naive random walk model. The best models were non-linear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation

Evolution, recurrency and kernels in learning to model inflation

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. We use non-linear, artificial intelligence techniques, namely, recurrent neural networks, evolution strategies and kernel methods in our forecasting experiment. In the experiment, these three methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a naive random walk model. The best models were non-linear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation. There is evidence in the literature that evolutionary methods can be used to evolve kernels hence our future work should combine the evolutionary and kernel methods to get the benefits of both

Using Individualised Choice Maps to Capture the Spatial Dimensions of Value Within Choice Experiments

Understanding how the value of environmental goods and services is influenced by their location relative to where people live can help identify the economically optimal spatial distribution of conservation interventions across landscapes. However, capturing these spatial relationships within the confines of a stated preference study has proved challenging. We propose and implement a novel approach to incorporating space within the design and presentation of stated preference choice experiments (CE). Using an investigation of preferences concerning land use change in Great Britain, CE scenarios are presented through individually generated maps, tailored to each respondent’s home location. Each choice situation is generated in real time and is underpinned by spatially tailored experimental designs that reflect current British land uses and incorporate locational attributes relating to physical and administrative dimensions of space. To the best of our knowledge, this represents the first CE study to integrate space into both the survey design and presentation of choice tasks in this way. Presented methodology provides means for testing how presentation of spatial information influence stated preferences. We contrast our spatially explicit (mapped) approach with a commonly applied tabular CE approach finding that the former exhibits a number of desirable characteristics relative to the latter

Investigation of long-term hydrothermal stability of NANO 3YSZ at operation temperatures of SOFCS

The study of hydrothermal degradation of 3 mol% yttria partially stabilized zirconia was carried out on various grain sizes with the target to prove the long term stability of nano sized 3YSZ applied in solid oxide fuel cells (SOFC5). Samples with grain sizes lower than 100 nm (nano) and higher than 100 nm (submicron) were produced by uniaxial pressing and slip casting. Tests of their mechanical performance such as hardness, however, showed that the way of processing does not have significant impact to the sintered specimen. Therefore are the samples of either process valuable for hydrothermal ageing experiments, which proved so far a complete resistance against water exposure in an autoclave up to 21 days

Ultra high temperature ceramic composite materials

Ultra-high temperature ceramics (UHTCs) are materials that have been demonstrated to withstand temperatures up to around 3000°C, thermal fluxes of ~17 MWm-2 and gas velocities of around Mach 0.6. Thus, they offer potential for use in applications such as leading edges and engine parts for hypervelocity vehicles. Under the Domain 8 of the MCM-ITP (Materials and Components for Missiles – Innovation and Technology Partnership) programme, research has been carried out investigating UHTC composites consisting of carbon fibre (Cf) preforms impregnated with HfB2 powders. Whilst the initial impregnation route resulted in preforms with high and uniform powder loadings, this was not true for large samples. As a result, the mechanical properties showed a high degree of scatter. Nevertheless, samples with higher final densities showed higher strengths. Thus a new impregnation route has been developed that results in both higher and more homogeneous powder loading. This has led to higher strengths and even greater temperature and ablation resistance with the only penalty being an increase in component mass. A prototype jet vane has been successfully produced

Ultra-high temperature ceramic composite

The work carried out under the XMat research programme (Materials Systems for Extreme Environments, EPSRC Programme Grant number EP/K008749/1-2) in the field of ultra-high temperature ceramic matrix composites has been focused on the design, development and manufacture of complex shapes and large panels for use under extreme conditions. The composites are made from 2.5D woven carbon fibre preforms impregnated with HfB2 powders and with a pyrolytic carbon, PyC, matrix created using chemical vapour infiltration, CVI. More recently, the knowledge acquired during the development of these Cf-HfB2-C composites has been focused on shortening the densification time by moving from conventional CVI to Radio Frequency-heated CVI; the work has also switched to Cf-ZrB2-C composites. In addition, the use of 3D carbon fibre preforms has begun to be explored to improve the mechanical properties and also the replacement of PyC matrix with ZrB2 to reducing the oxidation of the composites at ultra-high temperature

Assessing extraterrestrial regolith material simulants for in-situ resource utilization based 3D printing

This research paper investigates the suitability of ceramic multicomponent materials, which are found on the Martian and Lunar surfaces, for 3D printing (aka Additive Manufacturing) of solid structures. 3D printing is a promising solution as part of the cutting edge field of future in‐situ space manufacturing applications. 3D printing of physical assets from simulated Martian and Lunar regolith was successfully performed during this work by utilising laser‐based powder bed fusion equipment. Extensive evaluation of the raw regolith simulants was conducted via Optical and Electron Microscopy (SEM), Visible‐Near Infrared/Infrared (Vis‐NIR/IR) Spectroscopy and thermal characterisation via Thermogravimetric Analysis (TGA) and Differential Scanning Calorimetry (DSC). The analysis results led to the characterisation of key properties of these multicomponent ceramic materials with regards to their processability via powder bed fusion 3D printing. The Lunar and Martian simulant regolith analogues demonstrated spectral absorbance values of up to 92% within the Vis‐NIR spectra. Thermal analysis demonstrated that these materials respond very differently to laser processing, with a high volatility (30% weight change) for the Martian analogue as opposed to its less volatile Lunar counterpart (<1% weight change). Results also showed a range of multiple thermal occurrences associated with melting, glass transition and crystallisation reactions. The morphological features of the powder particles are identified as contributing to densification limitations for powder bed fusion processing. This investigation has shown that – provided that the simulants are good matches for the actual regoliths – the lunar material is a viable candidate material for powder bed fusion 3D printing, whereas Martian regolith is not