On aposteriori error analysis of dG schemes approximating hyperbolic conservation laws

This contribution is concerned with aposteriori error analysis of discontinuous Galerkin (dG) schemes approximating hyperbolic conservation laws. In the scalar case the aposteriori analysis is based on the L1 contraction property and the doubling of variables technique. In the system case the appropriate stability framework is in L2, based on relative entropies. It is only applicable if one of the solutions, which are compared to each other, is Lipschitz. For dG schemes approximating hyperbolic conservation laws neither the entropy solution nor the numerical solution need to be Lipschitz. We explain how this obstacle can be overcome using a reconstruction approach which leads to an aposteriori error estimate.

The role of index trading in price formation in the grains and oilseeds markets

We use both Granger-causality and instrumental variables (IV) methods to examine the impact of index fund positions on price returns for the main US grains and oilseed futures markets. Our analysis supports earlier conclusions that Granger-causal impacts are generally not discernible. However, market microstructure theory suggests trading impacts should be instantaneous. IV-based tests for contemporaneous causality provide stronger evidence of price impact. We find even stronger evidence that changes in index positions can help predict future changes in aggregate commodity price indices. This result suggests that changes in index investment are in part driven by information which predicts commodity price changes over the coming months.

Time-variations in commodity price jumps

In this paper, we study jumps in commodity prices. Unlike assumed in existing models of commodity price dynamics, a simple analysis of the data reveals that the probability of tail events is not constant but depends on the time of the year, i.e. exhibits seasonality. We propose a stochastic volatility jump–diffusion model to capture this seasonal variation. Applying the Markov Chain Monte Carlo (MCMC) methodology, we estimate our model using 20 years of futures data from four different commodity markets. We find strong statistical evidence to suggest that our model with seasonal jump intensity outperforms models featuring a constant jump intensity. To demonstrate the practical relevance of our findings, we show that our model typically improves Value-at-Risk (VaR) forecasts.

The role of industry bodies in changing market practices through self-regulation: commercial property leasing in the UK

The UK government has sought to make changes to commercial property leasing practices. This has been the case since the recession of the 1990s. Industry self-regulation using an industry code of practice has been the vehicle for these changes. However, the code has had little direct success in changing practices. This is despite repeated threats of legislation as a constant backdrop to this initiative. The focus for this research is on the role of the industry bodies in the code initiative. They have been central to self-regulation in commercial leasing. Thus, the aim is to investigate the role of industry bodies in the process of institutional change. The context is industry self-regulation. The specific setting is commercial leasing. The main industry bodies in focus are the British Property Federation and Royal Institution of Chartered Surveyors. An existing model of institutional change forms the framework for the research. A chronological narrative is constructed from secondary data. This is analysed, identifying the actions of the industry bodies within the conceptual stages of the model. The analysis shows that the industry bodies had not acted as convincing agents of change for commercial leasing. In particular there was a lack of theorisation, a key stage in the process. The industry bodies did not develop a framework necessary to guide their members through the change process. These shortcomings of the industry bodies are likely to have contributed to the failure of the Code. However, the main conclusion is that, if industry self-regulation is led by government, then the state must work with industry bodies to harness their potential as champions and drivers of institutional change. This is particularly important in achieving change in institutionalised environments.

Location, location, location? Analysing property rents in medieval Gloucester

Although medieval rentals have been extensively studied, few scholars have used them to analyse variations in the rents paid on individual properties within a town. It has been claimed that medieval rents did not reflect economic values or market forces, but were set according to social and political rather than economic criteria, and remained ossified at customary levels. This paper uses hedonic regression methods to test whether property rents in medieval Gloucester were influenced by classic economic factors such as the location and use of a property. It investigates both rents and local rates (landgavel), and explores the relationship between the two. It also examines spatial autocorrelation. It finds significant relationships between urban rents and property characteristics that are similar to those found in modern studies. The findings are consistent with the view that, in Gloucester at least, medieval rents were strongly influenced by classical economic factors working through a competitive urban property market.

El Niño 2015/2016 impact analysis, monthly outlook November 2015

During the summer and autumn 2015, El Niño conditions in the east and central Pacific have strengthened, disrupting weather patterns throughout the tropics and into the mid-latitudes. For example, rainfall during this summer’s Indian monsoon was approximately 15% below normal. The continued strong El Niño conditions have the potential to trigger damaging impacts (e.g., droughts, famines, floods), particularly in less-developed tropical countries, which would require a swift and effective humanitarian response to mitigate damage to life and property (e.g., health, migration, infrastructure). This analysis uses key climatic variables (temperature, soil moisture and precipitation) as measures to monitor the ongoing risk of these potentially damaging impacts. The previous 2015-2016 El Niño Impact Analysis was based on observations over the past 35 years and produced Impact Tables showing the likelihood and severity of the impacts on temperature and rainfall by season. The current report is an extension of this work providing information from seasonal forecast models to give a more detailed monthly outlook of the potential near-term impacts of the current El Niño conditions by region. This information has been added to the Impact Tables in the form of a monthly outlook column. This monthly outlook is an indication of the average likely conditions for that month and region and is not a definite prediction of weather impacts.

El Niño 2015/2016 impact analysis, monthly outlook December 2015

During the summer and autumn 2015, El Niño conditions in the east and central Pacific have strengthened, disrupting weather patterns throughout the tropics and into the mid-latitudes. For example, rainfall during this summer’s Indian monsoon was approximately 15% below normal. The continued strong El Niño conditions have the potential to trigger damaging impacts (e.g. droughts, famines, floods), particularly in less-developed tropical countries, which would require a swift and effective humanitarian response to mitigate damage to life and property (e.g. health, migration, infrastructure). This analysis uses key climatic variables (temperature, soil moisture and precipitation) as measures to monitor the ongoing risk of these potentially damaging impacts. The previous 2015-2016 El Niño Impact Analysis was based on observations over the past 35 years and produced Impact Tables showing the likelihood and severity of the impacts on temperature and rainfall by season. The current report is an extension of this work providing information from observations and seasonal forecast models to give a more detailed outlook of the potential near-term impacts of the current El Niño conditions by region. This information has been added to the Impact Tables in the form of an ‘Observations and Outlook’ row. This consists of observational information for the past seasons of JJA 2015 and SON 2015, a detailed monthly outlook from 5 modeling centres for Dec 2015 and then longer-term seasonal forecast information from 2 modeling centres for the future seasons of JF 2016 and MAM 2016. The seasonal outlook information is an indication of the average likely conditions for that coming month (or season) and region and is not a definite prediction of weather impacts.

El Niño 2015/2016 impact analysis, monthly outlook January 2016

During the summer and autumn of 2015, El Niño conditions in the east and central Pacific have strengthened, disrupting weather patterns throughout the tropics and into the mid-latitudes. For example, rainfall during this summer’s Indian monsoon was approximately 15% below normal. The continued strong El Niño conditions have the potential to trigger damaging impacts (e.g., droughts, famines, floods), particularly in less-developed tropical countries, which would require a swift and effective humanitarian response to mitigate damage to life and property (e.g., health, migration, infrastructure). This analysis uses key climatic variables (temperature, soil moisture and precipitation) as measures to monitor the ongoing risk of these potentially damaging impacts. The previous 2015-2016 El Niño Impact Analysis was based on observations over the past 35 years and produced Impact Tables showing the likelihood and severity of the impacts on temperature and rainfall by season. The current report is an extension of this work providing information from observations and seasonal forecast models to give a more detailed outlook of the potential near-term impacts of the current El Niño conditions by region. This information has been added to the Impact Tables in the form of an ‘Observations and Outlook’ row. This consists of observational information for the past seasons of JJA 2015, SON 2015 and Dec 2015, a detailed monthly outlook from 4 modeling centres for Jan 2016 and then longer-term seasonal forecast information from 2 modeling centres for the future seasons of Feb 2016, MAM 2016 and Jun 2016. The seasonal outlook information is an indication of the average likely conditions for that coming month (or season) and region and is not a definite prediction of weather impacts.

El Niño 2015/2016 impact analysis, monthly outlook February 2016

During the summer and autumn of 2015, El Niño conditions in the east and central Pacific strengthened, disrupting weather patterns throughout the tropics and into the mid-latitudes. For example, rainfall during the summer’s Indian monsoon was approximately 15% below normal. The continued strong El Niño conditions have the potential to trigger damaging impacts (e.g., droughts, famines, floods), particularly in less-developed tropical countries, which would require a swift and effective humanitarian response to mitigate damage to life and property (e.g., health, migration, infrastructure). This analysis uses key climatic variables (temperature, soil moisture and precipitation) as measures to monitor the ongoing risk of these potentially damaging impacts. The previous 2015-2016 El Niño Impact Analysis was based on observations over the past 35 years and produced Impact Tables showing the likelihood and severity of the impacts on temperature and rainfall by season. The current report is an extension of this work, providing information from observations and seasonal forecast models to give a more detailed outlook of the potential near-term impacts of the current El Niño conditions by region. This information has been added to the Impact Tables in the form of an ‘Observations and Outlook’ row. This consists of observational information for the past seasons of JJA 2015, SON 2015 and DJ 2015/2016, a detailed monthly outlook from 5 modeling centres for Feb 2016 and then longer-term seasonal forecast information from 2 modeling centres for the future seasons of MAM 2016 and JJ 2016. The seasonal outlook information is an indication of the average likely conditions for that coming month (or season) and region and is not a definite prediction of weather impacts. This report has been produced by University of Reading for Evidence on Demand with the assistance of the UK Department for International Development (DFID) contracted through the Climate, Environment, Infrastructure and Livelihoods Professional Evidence and Applied Knowledge Services (CEIL PEAKS) programme, jointly managed by DAI (which incorporates HTSPE Limited) and IMC Worldwide Limited.

Flight to quality? An investigation of changing price spreads in commercial real estate markets

Purpose – The purpose of this paper is to investigate the effect of the crisis on the pricing of asset quality attributes. This paper uses sales transaction data to examine whether flight from risk phenomena took place in the US office market during the financial crisis of 2007-2009. Design/methodology/approach – Hedonic regression procedures are used to test the hypothesis that the spread between the pricing of low-quality and high-quality characteristics increased during the crisis period compared to the pre-crisis period. Findings – The results of the hedonic regression models suggest that the price spread between Class A and other properties grew significantly during the downturn. Research limitations/implications – Our results are consistent with the hypothesis of an increased price spread following a market downturn between Class A and non-Class A offices. The evidence suggests that the relationships between the returns on Class A and non-Class A assets changed during the period of market stress or crisis. Practical implications – These findings have implications for real estate portfolio construction. If regime switches can be predicted and/or responded to rapidly, portfolios may be rebalanced. In crisis periods, portfolios might be reweighted towards Class A properties and in positive market periods, the reweighting would be towards non-Class A assets. Social implications – The global financial crisis has demonstrated that real estate markets play a crucial role in modern economies and that negative developments in these markets have the potential to spillover and create contagion for the larger economy, thereby affecting jobs, incomes and ultimately people’s livelihoods. Originality/value – This is one of the first studies that address the flight to quality phenomenon in commercial real estate markets during periods of financial crisis and market turmoil.

El Niño 2015/2016 impact analysis, monthly outlook March 2016

During the summer and autumn of 2015, El Niño conditions in the east and central Pacific strengthened, disrupting weather patterns throughout the tropics and into the mid-latitudes. For example, rainfall during the summer’s Indian monsoon was approximately 15% below normal. The continued strong El Niño conditions have the potential to trigger damaging impacts (e.g., droughts, famines, floods), particularly in less-developed tropical countries, which would require a swift and effective humanitarian response to mitigate damage to life and property (e.g., health, migration, infrastructure). This analysis uses key climatic variables (temperature, soil moisture and precipitation) as measures to monitor the ongoing risk of these potentially damaging impacts. The previous 2015-2016 El Niño Impact Analysis was based on observations over the past 35 years and produced Impact Tables showing the likelihood and severity of the impacts on temperature and rainfall by season. The current report is an extension of this work, providing information from observations and seasonal forecast models to give a more detailed outlook of the potential near-term impacts of the current El Niño conditions by region. This information has been added to the Impact Tables in the form of an ‘Observations and Outlook’ row. This consists of observational information for the past seasons of JJA 2015, SON 2015 and DJF 2015/2016, a detailed monthly outlook from 5 modeling centres for Mar 2016 and then longer-term seasonal forecast information from 2 modeling centres for the future seasons of AM 2016 and JJA 2016. The seasonal outlook information is an indication of the average likely conditions for that coming month (or season) and region and is not a definite prediction of weather impacts. This report has been produced by University of Reading for Evidence on Demand with the assistance of the UK Department for International Development (DFID) contracted through the Climate, Environment, Infrastructure and Livelihoods Professional Evidence and Applied Knowledge Services (CEIL PEAKS) programme, jointly managed by DAI (which incorporates HTSPE Limited) and IMC Worldwide Limited.