The ECB’s QE: Time to break the doom loop between banks and their governments. CEPS Policy Brief No. 328, March 2015

The recent crises have shown that the eurozone countries’ government debt is not immune to default. Applying a large-exposure requirement also to eurozone government debt would be a logical measure towards breaking the bank-government doom loop, given the low probability and high loss-given government default. But what would be the impact of the application of the large-exposure requirement on the banking sector as well as on government funding? This CEPS Policy Brief presents the results of a simulation exercise performed for 109 systemic banks in the eurozone, showing that their eurozone government debt portfolios would have to decrease by 3.2% or €63 billion, if a 50% of own-funds cap would be applied on large exposures. The eurozone central banks’ demand for sovereign bonds under the extended asset purchase programme further creates momentum to start gradually implementing the restriction.

A simulation analysis of the market effect of the Australian Broadcasting Corporation

In this paper we utilise a stochastic address model of broadcast oligopoly markets to analyse the Australian broadcast television market. In particular, we examine the effect of the presence of a single government market participant in this market. An examination of the dynamics of the simulations demonstrates that the presence of a government market participant can simultaneously generate positive outcomes for viewers as well as for other market suppliers. Further examination of simulation dynamics indicates that privatisation of the government market participant results in reduced viewer choice and diversity. We also demonstrate that additional private market participants would not result in significant benefits to viewers.

Using simulation to assess the introduction of technology in a continuous operations process

Purpose – To investigate the role of simulation in the introduction of technology in a continuous operations process. Design/methodology/approach – A case-based research method was chosen with the aim to provide an exemplar of practice and test the proposition that the use of simulation can improve the implementation and running of conveyor systems in continuous process facilities. Findings – The research determines the optimum rate of re-introduction of inventory to a conveyor system generated during a breakdown event. Research limitations/implications – More case studies are required demonstrating the operational and strategic benefits that can be gained by using simulation to assess technology in organisations. Practical implications – A practical outcome of the study was the implementation of a policy for the manual re-introduction of inventory on a conveyor line after a breakdown event had occurred. Originality/value – The paper presents a novel example of the use of simulation to estimate the re-introduction rate of inventory after a breakdown event on a conveyor line. The paper highlights how by addressing this operational issue, ahead of implementation, the likelihood of the success of the strategic decision to acquire the technology can be improved.

Spatial aspects of MRSA epidemiology:A case study using stochastic simulation, kernel estimation and SaTScan

The identification of disease clusters in space or space-time is of vital importance for public health policy and action. In the case of methicillin-resistant Staphylococcus aureus (MRSA), it is particularly important to distinguish between community and health care-associated infections, and to identify reservoirs of infection. 832 cases of MRSA in the West Midlands (UK) were tested for clustering and evidence of community transmission, after being geo-located to the centroids of UK unit postcodes (postal areas roughly equivalent to Zip+4 zip code areas). An age-stratified analysis was also carried out at the coarser spatial resolution of UK Census Output Areas. Stochastic simulation and kernel density estimation were combined to identify significant local clusters of MRSA (p<0.025), which were supported by SaTScan spatial and spatio-temporal scan. In order to investigate local sampling effort, a spatial 'random labelling' approach was used, with MRSA as cases and MSSA (methicillin-sensitive S. aureus) as controls. Heavy sampling in general was a response to MRSA outbreaks, which in turn appeared to be associated with medical care environments. The significance of clusters identified by kernel estimation was independently supported by information on the locations and client groups of nursing homes, and by preliminary molecular typing of isolates. In the absence of occupational/ lifestyle data on patients, the assumption was made that an individual's location and consequent risk is adequately represented by their residential postcode. The problems of this assumption are discussed, with recommendations for future data collection.

Selection of simulation tools for improving supply chain performance

Simulation is an effective method for improving supply chain performance. However, there is limited advice available to assist practitioners in selecting the most appropriate method for a given problem. Much of the advice that does exist relies on custom and practice rather than a rigorous conceptual or empirical analysis. An analysis of the different modelling techniques applied in the supply chain domain was conducted, and the three main approaches to simulation used were identified; these are System Dynamics (SD), Discrete Event Simulation (DES) and Agent Based Modelling (ABM). This research has examined these approaches in two stages. Firstly, a first principles analysis was carried out in order to challenge the received wisdom about their strengths and weaknesses and a series of propositions were developed from this initial analysis. The second stage was to use the case study approach to test these propositions and to provide further empirical evidence to support their comparison. The contributions of this research are both in terms of knowledge and practice. In terms of knowledge, this research is the first holistic cross paradigm comparison of the three main approaches in the supply chain domain. Case studies have involved building ‘back to back’ models of the same supply chain problem using SD and a discrete approach (either DES or ABM). This has led to contributions concerning the limitations of applying SD to operational problem types. SD has also been found to have risks when applied to strategic and policy problems. Discrete methods have been found to have potential for exploring strategic problem types. It has been found that discrete simulation methods can model material and information feedback successfully. Further insights have been gained into the relationship between modelling purpose and modelling approach. In terms of practice, the findings have been summarised in the form of a framework linking modelling purpose, problem characteristics and simulation approach.

A simulation analysis of spoke-terminals operating in LTL Hub-and-Spoke freight distribution systems

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT The research presented in this thesis is concerned with Discrete-Event Simulation (DES) modelling as a method to facilitate logistical policy development within the UK Less-than-Truckload (LTL) freight distribution sector which has been typified by “Pallet Networks” operating on a hub-and-spoke philosophy. Current literature relating to LTL hub-and-spoke and cross-dock freight distribution systems traditionally examines a variety of network and hub design configurations. Each is consistent with classical notions of creating process efficiency, improving productivity, reducing costs and generally creating economies of scale through notions of bulk optimisation. Whilst there is a growing abundance of papers discussing both the network design and hub operational components mentioned above, there is a shortcoming in the overall analysis when it comes to discussing the “spoke-terminal” of hub-and-spoke freight distribution systems and their capabilities for handling the diverse and discrete customer profiles of freight that multi-user LTL hub-and-spoke networks typically handle over the “last-mile” of the delivery, in particular, a mix of retail and non-retail customers. A simulation study is undertaken to investigate the impact on operational performance when the current combined spoke-terminal delivery tours are separated by ‘profile-type’ (i.e. retail or nonretail). The results indicate that a potential improvement in delivery performance can be made by separating retail and non-retail delivery runs at the spoke-terminal and that dedicated retail and non-retail delivery tours could be adopted in order to improve customer delivery requirements and adapt hub-deployed policies. The study also leverages key operator experiences to highlight the main practical implementation challenges when integrating the observed simulation results into the real-world. The study concludes that DES be harnessed as an enabling device to develop a ‘guide policy’. This policy needs to be flexible and should be applied in stages, taking into account the growing retail-exposure.

Using discrete event simulation to investigate road delivery policies to UK retailers

Retail customers provide a number of significant challenges to the efficiency and effectiveness of distribution systems. These challengers include shorter delivery windows, fluctuating volumes and a wider product mix. This paper demonstrates the use of discrete-event simulation to investigate policy issues regarding the incorporation of retail customers in a road delivery network from the spoke terminal of a hub and spoke distribution system. In particular a comparison of a mixed (retail and non-retail) delivery policy with a dedicated retail delivery run is made.

The effect of climate change on the population of sycamore lace bug (Corythuca ciliata, Say) based on a simulation model with phenological response

Climate change affects on insect populations in many ways: it can cause a shift in geographical spread, abundance, or diversity, it can change the location, the timing and the magnitude of outbreaks of pests and it can define the phenological or even the genetic properties of the species. Long-time investigations of special insect populations, simulation models and scenario studies give us very important information about the response of the insects far away and near to our century. Getting to know the potential responses of insect populations to climate change makes us possible to evaluate the adaptation of pest management alternatives as well as to formulate our future management policy. In this paper we apply two simple models, in order to introduce a complex case study for a Sycamore lace bug population. We test how the model works in case the whether conditions are very different from those in our days. Thus, besides we can understand the processes that happen in present, we can analyze the effects of a possible climate change, as well.

The impacts of trade policy reforms on the Sri Lankan economy

This dissertation presents an analysis of the impacts of trade policy reforms in Sri Lanka. A Computable General Equilibrium (CGE) model is constructed with detailed description of the domestic production structure and foreign trade. The model is then used to investigate the effects of trade policy reforms on resource allocation and welfare.^ Prior to 1977, Sri Lanka maintained stringent control over its imports through rigid quantitative restrictions. A new economic policy reform package was introduced in 1977, and it shifted Sri Lanka's development strategy toward an export oriented policy regime. The shift of policy focus from a restrictive trade regime toward a more open trade regime is expected to have a significant impact on the volume of external trade, domestic production structure, allocation of resources, and social welfare.^ Simulations are carried out to assess the effects of three major policy reforms: (1) a devaluation of the Sri Lanka rupee, (2) a partial or a complete elimination of export duties, and (3) a devaluation-cum-removal of export duties.^ Simulation results indicate that the macroeconomic impact of a devaluation-cum-removal of export duties can be substantial. They also suggest that the resource-pull effects of a devaluation and a devaluation-cum-export duty removal policy are significant. However, the model shows that a devaluation combined with an export duty reduction is likely to be a superior strategy. ^

Interoperable resource brokering with policy-based provisioning and job allocation

The increasing needs for computational power in areas such as weather simulation, genomics or Internet applications have led to sharing of geographically distributed and heterogeneous resources from commercial data centers and scientific institutions. Research in the areas of utility, grid and cloud computing, together with improvements in network and hardware virtualization has resulted in methods to locate and use resources to rapidly provision virtual environments in a flexible manner, while lowering costs for consumers and providers. ^ However, there is still a lack of methodologies to enable efficient and seamless sharing of resources among institutions. In this work, we concentrate in the problem of executing parallel scientific applications across distributed resources belonging to separate organizations. Our approach can be divided in three main points. First, we define and implement an interoperable grid protocol to distribute job workloads among partners with different middleware and execution resources. Second, we research and implement different policies for virtual resource provisioning and job-to-resource allocation, taking advantage of their cooperation to improve execution cost and performance. Third, we explore the consequences of on-demand provisioning and allocation in the problem of site-selection for the execution of parallel workloads, and propose new strategies to reduce job slowdown and overall cost.^

A framework for policy based coordinated adaptation in mobile systems

Adaptation is an important requirement for mobile applications due to the varying levels of resource availability that characterizes mobile environments. However without proper control, multiple applications can each adapt independently in response to a range of different adaptive stimuli, causing conflicts or sub optimal performance. In this thesis we presented a framework, which enables multiple adaptation mechanisms to coexist on one platform. The key component of this framework was the 'Policy Server', which has all the system policies and governs the rules for adaptation. We also simulated our framework and subjected it to various adaptation scenarios to demonstrate the working of the system as a whole. With the help of the simulation it was shown that our framework enables seamless adaptation of multiple applications.

Modelling and analysing human behaviour in a department store using discrete event and agent based simulation

Discrete Event Simulation (DES) is a very popular simulation technique in Operational Research. Recently, there has been the emergence of another technique, namely Agent Based Simulation (ABS). Although there is a lot of literature relating to DES and ABS, we have found less that focuses on exploring the capabilities of both in tackling human behaviour issues. In order to understand the gap between these two simulation techniques, therefore, our aim is to understand the distinctions between DES and ABS models with the real world phenomenon in modelling and simulating human behaviour. In achieving the aim, we have carried out a case study at a department store. Both DES and ABS models will be compared using the same problem domain which is concerning on management policy in a fitting room. The behaviour of staffs while working and customers’ satisfaction will be modelled for both models behaviour understanding.

Investigating output accuracy for a discrete event simulation model and an agent based simulation model

In this paper, we investigate output accuracy for a Discrete Event Simulation (DES) model and Agent Based Simulation (ABS) model. The purpose of this investigation is to find out which of these simulation techniques is the best one for modelling human reactive behaviour in the retail sector. In order to study the output accuracy in both models, we have carried out a validation experiment in which we compared the results from our simulation models to the performance of a real system. Our experiment was carried out using a large UK department store as a case study. We had to determine an efficient implementation of management policy in the store’s fitting room using DES and ABS. Overall, we have found that both simulation models were a good representation of the real system when modelling human reactive behaviour.

The Potential of Tariff Policy for Climate Change Mitigation: Legal and Economic Analysis

This paper addresses a potential role that tariffs and tariff policy can play in encouraging countries to take part in a multilateral effort to mitigate climate change. It begins by assessing whether increasing tariffs on products from energy intensive or polluting industries amounts to a violation of WTO rules and whether protectionism in this case can be differentiated from genuine environmental concerns. It then argues that while lowering tariffs for environmental goods can serve as a carrot to promote dissemination of cleaner technologies, tariff deconsolidation is a legitimate stick to encourage polluting countries to move towards an international climate agreement. The paper further explores this view by undertaking a partialequilibrium simulation analysis to examine the impact of a unilateral unit increase in tariffs on the imports of the most carbon-intensive products from countries not committed to climate polices. Our results suggest that the committed importing countries would have to raise their tariffs only slightly to effect a significant decline in the imports of these products from the non-committed countries. For instance, a unit increase in the simple average applied tariffs on the imports of these carbon-intensive products in 2005 from our sample of non-committed exporting countries would reduce the imports of these products by an average 32.6% in Australia, 178% in Canada, 195% in the EU, 271% in Japan and 62% in the US, therebysuggesting the effectiveness of such a measure in pushing countries towards a global climate policy.

Knowing wildfire risk: scientific interactions with risk mitigation policy and practice in Victoria, Australia

Over the past decade, major landscape wildfires (or ‘bushfires’ in Australia) in fire-prone countries have illustrated the seriousness of this global environmental problem. This natural hazard presents a complex mesh of dynamic factors for those seeking to reduce or manage its costs, as ignitions, hazard behaviour, and the reactions of different human and ecological communities during and after hazard events are all extremely uncertain. But while those at risk of wildfire have been subject to significant research, the social dimensions of its management, including the role of science, have received little attention. This paper reports on a case study of the Barwon-Otway area of Victoria in Australia, a high wildfire risk area that has recently been a pilot site for a new risk mitigation strategy utilising the wildfire simulation model PHOENIX RapidFire. Against simple equations between ‘more science’ and ‘less uncertainty,’ this paper presents results from interviews and a workshop with practitioners to investigate how scientific research interacts with and informs both wildfire policy and practice. We suggest that attending to cultural and social specificities of the application of any technical innovation—such as next generation modelling—raises questions for future research about the roles of narrative, performance, and other knowledges in the sedimentation of science.