Bailouts, monitoring, and penalties: an integrated framework of government policies to manage the too-big-to-fail problem

This paper discusses optimal government bailout policy where the costs of systemic failures and moral hazard problems are considered. We find that a three-tiered bailout policy that includes an ex post monitoring and bailout scheme for financial institutions with large systemic impacts ('too big to fail') is optimal. The optimal policy also requires a randomized bailout for medium-impact institutions ('Constructive Ambiguity'), and no bailout for institutions that have only minimal systemic consequences ('too small to save'). However, in a volatile, innovative market environment where individual institutions may know more than the government regulator, monitoring error could contribute to risk taking, leaving the government regulator to always play a 'catch-up' role in revising policy. Moreover, the optimal bailout policy may not be time-consistent: institutions not deemed 'too big to fail' may still have an incentive to take excessive risks and expect to be bailed out in case of insolvency, primarily due to the short-term orientation of the government. Finally, because an institution's systemic cost affects the probability of a bailout, we show that the boundary of an institution may be extended by the government subsidy.

Review of vibration-based damage detection and condition assessment of bridge structures using structural health monitoring

As a part of vital infrastructure and transportation networks, bridge structures must function safely at all times. However, due to heavier and faster moving vehicular loads and function adjustment, such as Busway accommodation, many bridges are now operating at an overload beyond their design capacity. Additionally, the huge renovation and replacement costs always make the infrastructure owners difficult to undertake. Structural health monitoring (SHM) is set to assess condition and foresee probable failures of designated bridge(s), so as to monitor the structural health of the bridges. The SHM systems proposed recently are incorporated with Vibration-Based Damage Detection (VBDD) techniques, Statistical Methods and Signal processing techniques and have been regarded as efficient and economical ways to solve the problem. The recent development in damage detection and condition assessment techniques based on VBDD and statistical methods are reviewed. The VBDD methods based on changes in natural frequencies, curvature/strain modes, modal strain energy (MSE) dynamic flexibility, artificial neural networks (ANN) before and after damage and other signal processing methods like Wavelet techniques and empirical mode decomposition (EMD) / Hilbert spectrum methods are discussed here.

Smart buildings for healthy and sustainable workplace: scoping study report

Deficiencies in the design and operation of office buildings can give rise to high social, environmental and economic (triple bottom line) costs. As a result, there are significant pressures and incentives to develop ‘smart building’ technologies that can facilitate improved indoor environment quality (IEQ), and more energy efficient operation of office buildings. IEQ indicators include lighting, ventilation, thermal comfort, indoor air quality and noise. In response to this, the CRC for Construction Innovation commissioned a six-month scoping study (Project no. 2002-043) to examine how different technologies could be used to improve the ‘triple bottom line’ for office buildings. The study was supported by three industry partners, Bovis Lend Lease, Arup, and The Queensland Department of Public Works. The objective of the study was to look at the history, trends, drivers, new technologies and potential application areas related to the operation of healthy and efficient office buildings. The key output from the study was a recommendation for a prototype system for intelligent monitoring and control of an office environment, based on identified market, technical and user requirements and constraints.

Intelligent prognostics of machinery health utilising suspended condition monitoring data

The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

Optimal monitoring in family-owned companies? Evidence from Asia

Manuscript Type: Empirical Research Issue: We propose that high levels of monitoring are not always in the best interests of minority shareholders. In family-owned companies the optimal level of board monitoring required by minority shareholders is expected to be lower than that of other companies. This is because the relative benefits and costs of monitoring are different in family-owned companies. Research Findings: At moderate levels of board monitoring, we find concave relationships between board monitoring variables and firm performance for family-owned companies but not for other companies. The optimal level of board monitoring for our sample of Asian family-owned companies equates to board independence of 38%, separation of the Chairman and CEO positions and establishment of audit and remuneration committees. Additional testing shows that the optimal level of board monitoring is sensitive to the magnitude of the agency conflict between the family group and minority shareholders and the presence of substitute monitoring. Practitioner/Policy Implications: For policymakers, the results show that more monitoring is not always in the best interests of minority shareholders. Therefore, it may be inappropriate for regulators to advise all companies to follow the same set of corporate governance guidelines. However, our results also indicate that the board governance practices of family-owned companies are still well below the identified optimal levels. Keywords: Corporate Governance, Board Independence, Board of Directors, Family Firms, Monitoring.

Development of lifetime warranty policies and models for estimating costs

In today's fiercely competitive products market, product warranty has started playing an important role. The warranty period offered by the manufacturer/dealer has been progressively increasing since the beginning of the 20th Century. Currently, a large number of products are being sold with long-term warranty policies in the form of extended warranty, warranty for used products, service contracts and lifetime warranty policies. Lifetime warranties are relatively a new concept. The modelling of failures during the warranty period and the costs for such policies are complex since the lifespan in these policies are not defined well and it is often difficult to tell about life measures for the longer period of coverage due to usage pattern/maintenance activities undertaken and uncertainties of costs over the period. This paper focuses on defining lifetime, developing lifetime warranty policies and models for predicting failures and estimating costs for lifetime warranty policies.

Market access of Papua New Guinea bananas (Musa spp.) with particular respect to banana fly (Bactrocera musae (Tryon)) (Diptera: Tephritidae)

International market access for fresh commodities is regulated by international accepted phytosanitary guidelines, the objectives of which are to reduce the biosecurity risk of plant pest and disease movement. Papua New Guinea (PNG) has identified banana as a potential export crop and to help meet international market access requirements, this thesis provides information for the development of a pest risk analysis (PRA) for PNG banana fruit. The PRA is a three step process which first identifies the pests associated with a particular commodity or pathway, then assesses the risk associated with those pests, and finally identifies risk management options for those pests if required. As the first step of the PRA process, I collated a definitive list on the organisms associated with the banana plant in PNG using formal literature, structured interviews with local experts, grey literature and unpublished file material held in PNG field research stations. I identified 112 organisms (invertebrates, vertebrate, pathogens and weeds) associated with banana in PNG, but only 14 of these were reported as commonly requiring management. For these 14 I present detailed information summaries on their known biology and pest impact. A major finding of the review was that of the 14 identified key pests, some research information occurs for 13. The single exception for which information was found to be lacking was Bactrocera musae (Tryon), the banana fly. The lack of information for this widely reported ‘major pest on PNG bananas’ would hinder the development of a PNG banana fruit PRA. For this reason the remainder of the thesis focused on this organism, particularly with respect to generation of information required by the PRA process. Utilising an existing, but previously unanalysed fruit fly trapping database for PNG, I carried out a Geographic Information System analysis of the distribution and abundance of banana in four major regions of PNG. This information is required for a PRA to determine if banana fruit grown in different parts of the country are at different risks from the fly. Results showed that the fly was widespread in all cropping regions and that temperature and rainfall were not significantly correlated with banana fly abundance. Abundance of the fly was significantly correlated (albeit weakly) with host availability. The same analysis was done with four other PNG pest fruit flies and their responses to the environmental factors differed to banana fly and each other. This implies that subsequent PRA analyses for other PNG fresh commodities will need to investigate the risk of each of these flies independently. To quantify the damage to banana fruit caused by banana fly in PNG, local surveys and one national survey of banana fruit infestation were carried out. Contrary to expectations, infestation was found to be very low, particularly in the widely grown commercial cultivar, Cavendish. Infestation of Cavendish fingers was only 0.41% in a structured, national survey of over 2 700 banana fingers. Follow up laboratory studies showed that fingers of Cavendish, and another commercial variety Lady-finger, are very poor hosts for B. musae, with very low host selection rates by female flies and very poor immature survival. An analysis of a recent (within last decade) incursion of B. musae into the Gazelle Peninsula of East New Britain Province, PNG, provided the final set of B. musae data. Surveys of the fly on the peninsular showed that establishment and spread of the fly in the novel environment was very rapid and thus the fly should be regarded as being of high biosecurity concern, at least in tropical areas. Supporting the earlier impact studies, however, banana fly has not become a significant banana fruit problem on the Gazelle, despite bananas being the primary starch staple of the region. The results of the research chapters are combined in the final Discussion in the form of a B. musae focused PRA for PNG banana fruit. Putting the thesis in a broader context, the Discussion also deals with the apparent discrepancy between high local abundance of banana fly and very low infestation rates. This discussion focuses on host utilisation patterns of specialist herbivores and suggests that local pest abundance, as determined by trapping or monitoring, need not be good surrogate for crop damage, despite this linkage being implicit in a number of international phytosanitary protocols.

An economic case for systematic student monitoring and intervention in the first year in higher education

Previous work has established the effectiveness of systematically monitoring first year higher education students and intervening with those identified as at-risk of attrition. This nuts-and-bolts paper establishes an economic case for a systematic monitoring and intervention program, identifying the visible costs and benefits of such a program at a major Australian university. The benefit of such a program is measured in savings to the institution which would otherwise be lost revenue, in the form of retained equivalent full-time student load (EFTSL). The session will present an economic model based on a number of assumptions. These assumptions are explored along with the applicability of the model to other institutions.

Structural health monitoring : vibration-based damage detection and condition assessment of bridges

Structural health is a vital aspect of infrastructure sustainability. As a part of a vital infrastructure and transportation network, bridge structures must function safely at all times. However, due to heavier and faster moving vehicular loads and function adjustment, such as Busway accommodation, many bridges are now operating at an overload beyond their design capacity. Additionally, the huge renovation and replacement costs are a difficult burden for infrastructure owners. The structural health monitoring (SHM) systems proposed recently are incorporated with vibration-based damage detection techniques, statistical methods and signal processing techniques and have been regarded as efficient and economical ways to assess bridge condition and foresee probable costly failures. In this chapter, the recent developments in damage detection and condition assessment techniques based on vibration-based damage detection and statistical methods are reviewed. The vibration-based damage detection methods based on changes in natural frequencies, curvature or strain modes, modal strain energy, dynamic flexibility, artificial neural networks, before and after damage, and other signal processing methods such as Wavelet techniques, empirical mode decomposition and Hilbert spectrum methods are discussed in this chapter.

Scheduling coordination through negotiation between train service providers in an open railway access market

A schedule coordination problem involving two train services provided by different operators is modeled as an optimization of revenue intake. The coordination is achieved through the adjustment of commencement times of the train services by negotiation. The problem is subject to constraints regarding to passenger demands and idle costs of rolling-stocks from both operators. This paper models the operators as software agents having the flexibility to incorporate one of the two (and potentially more) proposed negotiation strategies. Empirical results show that agents employing different combination of strategies have significant impact on the quality of solution and negotiation time.

Householder experiences with resource monitoring technology in sustainable homes

The use of feedback technologies, in the form of products such as Smart Meters, is increasingly seen as the means by which 'consumers' can be made aware of their patterns of resource consumption, and to then use this enhanced awareness to change their behaviour to reduce the environmental impacts of their consumption. These technologies tend to be single-resource focused (e.g. on electricity consumption only) and their functionality defined by persons other than end-users (e.g. electricity utilities). This paper presents initial findings of end-users' experiences with a multi-resource feedback technology, within the context of sustainable housing. It proposes that an understanding of user context, supply chain management and market diffusion issues are important design considerations that contribute to technology 'success'.

Implementation of an embedded sensor network for the coordination of Slocum gliders for coastal monitoring and observation

Autonomous Underwater Vehicles (AUVs) are revolutionizing oceanography through their versatility, autonomy and endurance. However, they are still an underutilized technology. For coastal operations, the ability to track a certain feature is of interest to ocean scientists. Adaptive and predictive path planning requires frequent communication with significant data transfer. Currently, most AUVs rely on satellite phones as their primary communication. This communication protocol is expensive and slow. To reduce communication costs and provide adequate data transfer rates, we present a hardware modification along with a software system that provides an alternative robust disruption- tolerant communications framework enabling cost-effective glider operation in coastal regions. The framework is specifically designed to address multi-sensor deployments. We provide a system overview and present testing and coverage data for the network. Additionally, we include an application of ocean-model driven trajectory design, which can benefit from the use of this network and communication system. Simulation and implementation results are presented for single and multiple vehicle deployments. The presented combination of infrastructure, software development and deployment experience brings us closer to the goal of providing a reliable and cost-effective data transfer framework to enable real-time, optimal trajectory design, based on ocean model predictions, to gather in situ measurements of interesting and evolving ocean features and phenomena.

Essays on irrigation development, farm production and unaccounted costs : theory and empirical evidence

A review of the literature related to issues involved in irrigation induced agricultural development (IIAD) reveals that: (1) the magnitude, sensitivity and distribution of social welfare of IIAD is not fully analysed; (2) the impacts of excessive pesticide use on farmers’ health are not adequately explained; (3) no analysis estimates the relationship between farm level efficiency and overuse of agro-chemical inputs under imperfect markets; and (4) the method of incorporating groundwater extraction costs is misleading. This PhD thesis investigates these issues by using primary data, along with secondary data from Sri Lanka. The overall findings of the thesis can be summarised as follows. First, the thesis demonstrates that Sri Lanka has gained a positive welfare change as a result of introducing new irrigation technology. The change in the consumer surplus is Rs.48,236 million, while the change in the producer surplus is Rs. 14,274 millions between 1970 and 2006. The results also show that the long run benefits and costs of IIAD depend critically on the magnitude of the expansion of the irrigated area, as well as the competition faced by traditional farmers (agricultural crowding out effects). The traditional sector’s ability to compete with the modern sector depends on productivity improvements, reducing production costs and future structural changes (spillover effects). Second, the thesis findings on pesticides used for agriculture show that, on average, a farmer incurs a cost of approximately Rs. 590 to 800 per month during a typical cultivation period due to exposure to pesticides. It is shown that the value of average loss in earnings per farmer for the ‘hospitalised’ sample is Rs. 475 per month, while it is approximately Rs. 345 per month for the ‘general’ farmers group during a typical cultivation season. However, the average willingness to pay (WTP) to avoid exposure to pesticides is approximately Rs. 950 and Rs. 620 for ‘hospitalised’ and ‘general’ farmers’ samples respectively. The estimated percentage contribution for WTP due to health costs, lost earnings, mitigating expenditure, and disutility are 29, 50, 5 and 16 per cent respectively for hospitalised farmers, while they are 32, 55, 8 and 5 per cent respectively for ‘general’ farmers. It is also shown that given market imperfections for most agricultural inputs, farmers are overusing pesticides with the expectation of higher future returns. This has led to an increase in inefficiency in farming practices which is not understood by the farmers. Third, it is found that various groundwater depletion studies in the economics literature have provided misleading optimal water extraction quantity levels. This is due to a failure to incorporate all production costs in the relevant models. It is only by incorporating quality changes to quantity deterioration, that it is possible to derive socially optimal levels. Empirical results clearly show that the benefits per hectare per month considering both the avoidance costs of deepening agro-wells by five feet from the existing average, as well as the avoidance costs of maintaining the water salinity level at 1.8 (mmhos/Cm), is approximately Rs. 4,350 for farmers in the Anuradhapura district and Rs. 5,600 for farmers in the Matale district.

Evaluation of financial incentives as a quality improvement strategy in the public hospital context : clinician attitudes, design variables, and economic costs

In 2008, a three-year pilot ‘pay for performance’ (P4P) program, known as ‘Clinical Practice Improvement Payment’ (CPIP) was introduced into Queensland Health (QHealth). QHealth is a large public health sector provider of acute, community, and public health services in Queensland, Australia. The organisation has recently embarked on a significant reform agenda including a review of existing funding arrangements (Duckett et al., 2008). Partly in response to this reform agenda, a casemix funding model has been implemented to reconnect health care funding with outcomes. CPIP was conceptualised as a performance-based scheme that rewarded quality with financial incentives. This is the first time such a scheme has been implemented into the public health sector in Australia with a focus on rewarding quality, and it is unique in that it has a large state-wide focus and includes 15 Districts. CPIP initially targeted five acute and community clinical areas including Mental Health, Discharge Medication, Emergency Department, Chronic Obstructive Pulmonary Disease, and Stroke. The CPIP scheme was designed around key concepts including the identification of clinical indicators that met the set criteria of: high disease burden, a well defined single diagnostic group or intervention, significant variations in clinical outcomes and/or practices, a good evidence, and clinician control and support (Ward, Daniels, Walker & Duckett, 2007). This evaluative research targeted Phase One of implementation of the CPIP scheme from January 2008 to March 2009. A formative evaluation utilising a mixed methodology and complementarity analysis was undertaken. The research involved three research questions and aimed to determine the knowledge, understanding, and attitudes of clinicians; identify improvements to the design, administration, and monitoring of CPIP; and determine the financial and economic costs of the scheme. Three key studies were undertaken to ascertain responses to the key research questions. Firstly, a survey of clinicians was undertaken to examine levels of knowledge and understanding and their attitudes to the scheme. Secondly, the study sought to apply Statistical Process Control (SPC) to the process indicators to assess if this enhanced the scheme and a third study examined a simple economic cost analysis. The CPIP Survey of clinicians elicited 192 clinician respondents. Over 70% of these respondents were supportive of the continuation of the CPIP scheme. This finding was also supported by the results of a quantitative altitude survey that identified positive attitudes in 6 of the 7 domains-including impact, awareness and understanding and clinical relevance, all being scored positive across the combined respondent group. SPC as a trending tool may play an important role in the early identification of indicator weakness for the CPIP scheme. This evaluative research study supports a previously identified need in the literature for a phased introduction of Pay for Performance (P4P) type programs. It further highlights the value of undertaking a formal risk assessment of clinician, management, and systemic levels of literacy and competency with measurement and monitoring of quality prior to a phased implementation. This phasing can then be guided by a P4P Design Variable Matrix which provides a selection of program design options such as indicator target and payment mechanisms. It became evident that a clear process is required to standardise how clinical indicators evolve over time and direct movement towards more rigorous ‘pay for performance’ targets and the development of an optimal funding model. Use of this matrix will enable the scheme to mature and build the literacy and competency of clinicians and the organisation as implementation progresses. Furthermore, the research identified that CPIP created a spotlight on clinical indicators and incentive payments of over five million from a potential ten million was secured across the five clinical areas in the first 15 months of the scheme. This indicates that quality was rewarded in the new QHealth funding model, and despite issues being identified with the payment mechanism, funding was distributed. The economic model used identified a relative low cost of reporting (under $8,000) as opposed to funds secured of over $300,000 for mental health as an example. Movement to a full cost effectiveness study of CPIP is supported. Overall the introduction of the CPIP scheme into QHealth has been a positive and effective strategy for engaging clinicians in quality and has been the catalyst for the identification and monitoring of valuable clinical process indicators. This research has highlighted that clinicians are supportive of the scheme in general; however, there are some significant risks that include the functioning of the CPIP payment mechanism. Given clinician support for the use of a pay–for-performance methodology in QHealth, the CPIP scheme has the potential to be a powerful addition to a multi-faceted suite of quality improvement initiatives within QHealth.