857 resultados para Real and nominal effective exchange rates
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Genetic assignment methods use genotype likelihoods to draw inference about where individuals were or were not born, potentially allowing direct, real-time estimates of dispersal. We used simulated data sets to test the power and accuracy of Monte Carlo resampling methods in generating statistical thresholds for identifying F-0 immigrants in populations with ongoing gene flow, and hence for providing direct, real-time estimates of migration rates. The identification of accurate critical values required that resampling methods preserved the linkage disequilibrium deriving from recent generations of immigrants and reflected the sampling variance present in the data set being analysed. A novel Monte Carlo resampling method taking into account these aspects was proposed and its efficiency was evaluated. Power and error were relatively insensitive to the frequency assumed for missing alleles. Power to identify F-0 immigrants was improved by using large sample size (up to about 50 individuals) and by sampling all populations from which migrants may have originated. A combination of plotting genotype likelihoods and calculating mean genotype likelihood ratios (D-LR) appeared to be an effective way to predict whether F-0 immigrants could be identified for a particular pair of populations using a given set of markers.
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This thesis focuses on the theoretical examination of the exchange rate economic (operating) exposure within the context of the theory of the firm, and proposes some hedging solutions using currency options. The examination of economic exposure is based on such parameters as firms' objectives, industry structure and production cost efficiency. In particular, it examines an hypothetical exporting firm with costs in domestic currency, which faces competition from foreign firms in overseas markets and has a market share expansion objective. Within this framework, the hypothesis is established that economic exposure, portrayed in a diagram connecting export prices and real exchange rates, is asymmetric (i.e. the negative effects depreciation are higher than the positive effects of a currency depreciation). In this case, export business can be seen as a real option, given by exporting firms to overseas customer. Different scenarios about the asymmetry hypothesis can be derived for different assumptions about the determinants of economic exposure. Having established the asymmetry hypothesis, the hedging against this exposure is analysed. The hypothesis is established, that a currency call option should be used in hedging against asymmetric economic exposure. Further, some advanced currency options stategies are discussed, and their use in hedging several scenarios of exposure is indicated, establishing the hypothesis that, the optimal options strategy is a function of the determinants of exposure. Some extensions on the theoretical analysis are examined. These include the hedging of multicurrency exposure using options, and the exposure of a purely domestic firm facing import competition. The empirical work addresses two issues: the empirical validity of the asymmetry hypothesis and the examination of the hedging effectiveness of currency options.
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Exchange rate economics has achieved substantial development in the past few decades. Despite extensive research, a large number of unresolved problems remain in the exchange rate debate. This dissertation studied three puzzling issues aiming to improve our understanding of exchange rate behavior. Chapter Two used advanced econometric techniques to model and forecast exchange rate dynamics. Chapter Three and Chapter Four studied issues related to exchange rates using the theory of New Open Economy Macroeconomics. ^ Chapter Two empirically examined the short-run forecastability of nominal exchange rates. It analyzed important empirical regularities in daily exchange rates. Through a series of hypothesis tests, a best-fitting fractionally integrated GARCH model with skewed student-t error distribution was identified. The forecasting performance of the model was compared with that of a random walk model. Results supported the contention that nominal exchange rates seem to be unpredictable over the short run in the sense that the best-fitting model cannot beat the random walk model in forecasting exchange rate movements. ^ Chapter Three assessed the ability of dynamic general-equilibrium sticky-price monetary models to generate volatile foreign exchange risk premia. It developed a tractable two-country model where agents face a cash-in-advance constraint and set prices to the local market; the exogenous money supply process exhibits time-varying volatility. The model yielded approximate closed form solutions for risk premia and real exchange rates. Numerical results provided quantitative evidence that volatile risk premia can endogenously arise in a new open economy macroeconomic model. Thus, the model had potential to rationalize the Uncovered Interest Parity Puzzle. ^ Chapter Four sought to resolve the consumption-real exchange rate anomaly, which refers to the inability of most international macro models to generate negative cross-correlations between real exchange rates and relative consumption across two countries as observed in the data. While maintaining the assumption of complete asset markets, this chapter introduced endogenously segmented asset markets into a dynamic sticky-price monetary model. Simulation results showed that such a model could replicate the stylized fact that real exchange rates tend to move in an opposite direction with respect to relative consumption. ^
Resumo:
Exchange rate economics has achieved substantial development in the past few decades. Despite extensive research, a large number of unresolved problems remain in the exchange rate debate. This dissertation studied three puzzling issues aiming to improve our understanding of exchange rate behavior. Chapter Two used advanced econometric techniques to model and forecast exchange rate dynamics. Chapter Three and Chapter Four studied issues related to exchange rates using the theory of New Open Economy Macroeconomics. Chapter Two empirically examined the short-run forecastability of nominal exchange rates. It analyzed important empirical regularities in daily exchange rates. Through a series of hypothesis tests, a best-fitting fractionally integrated GARCH model with skewed student-t error distribution was identified. The forecasting performance of the model was compared with that of a random walk model. Results supported the contention that nominal exchange rates seem to be unpredictable over the short run in the sense that the best-fitting model cannot beat the random walk model in forecasting exchange rate movements. Chapter Three assessed the ability of dynamic general-equilibrium sticky-price monetary models to generate volatile foreign exchange risk premia. It developed a tractable two-country model where agents face a cash-in-advance constraint and set prices to the local market; the exogenous money supply process exhibits time-varying volatility. The model yielded approximate closed form solutions for risk premia and real exchange rates. Numerical results provided quantitative evidence that volatile risk premia can endogenously arise in a new open economy macroeconomic model. Thus, the model had potential to rationalize the Uncovered Interest Parity Puzzle. Chapter Four sought to resolve the consumption-real exchange rate anomaly, which refers to the inability of most international macro models to generate negative cross-correlations between real exchange rates and relative consumption across two countries as observed in the data. While maintaining the assumption of complete asset markets, this chapter introduced endogenously segmented asset markets into a dynamic sticky-price monetary model. Simulation results showed that such a model could replicate the stylized fact that real exchange rates tend to move in an opposite direction with respect to relative consumption.
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Background: Given escalating rates of chronic disease, broad-reach and cost-effective interventions to increase physical activity and improve dietary intake are needed. The cost-effectiveness of a Telephone Counselling intervention to improve physical activity and diet, targeting adults with established chronic diseases in a low socio-economic area of a major Australian city was examined. Methodology/Principal Findings: A cost-effectiveness modelling study using data collected between February 2005 and November 2007 from a cluster-randomised trial that compared Telephone Counselling with a “Usual Care” (brief intervention) alternative. Economic outcomes were assessed using a state-transition Markov model, which predicted the progress of participants through five health states relating to physical activity and dietary improvement, for ten years after recruitment. The costs and health benefits of Telephone Counselling, Usual Care and an existing practice (Real Control) group were compared. Telephone Counselling compared to Usual Care was not cost-effective ($78,489 per quality adjusted life year gained). However, the Usual Care group did not represent existing practice and is not a useful comparator for decision making. Comparing Telephone Counselling outcomes to existing practice (Real Control), the intervention was found to be cost-effective ($29,375 per quality adjusted life year gained). Usual Care (brief intervention) compared to existing practice (Real Control) was also cost-effective ($12,153 per quality adjusted life year gained). Conclusions/Significance: This modelling study shows that a decision to adopt a Telephone Counselling program over existing practice (Real Control) is likely to be cost-effective. Choosing the ‘Usual Care’ brief intervention over existing practice (Real Control) shows a lower cost per quality adjusted life year, but the lack of supporting evidence for efficacy or sustainability is an important consideration for decision makers. The economics of behavioural approaches to improving health must be made explicit if decision makers are to be convinced that allocating resources toward such programs is worthwhile.
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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.
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A Networked Control System (NCS) is a feedback-driven control system wherein the control loops are closed through a real-time network. Control and feedback signals in an NCS are exchanged among the system’s components in the form of information packets via the network. Nowadays, wireless technologies such as IEEE802.11 are being introduced to modern NCSs as they offer better scalability, larger bandwidth and lower costs. However, this type of network is not designed for NCSs because it introduces a large amount of dropped data, and unpredictable and long transmission latencies due to the characteristics of wireless channels, which are not acceptable for real-time control systems. Real-time control is a class of time-critical application which requires lossless data transmission, small and deterministic delays and jitter. For a real-time control system, network-introduced problems may degrade the system’s performance significantly or even cause system instability. It is therefore important to develop solutions to satisfy real-time requirements in terms of delays, jitter and data losses, and guarantee high levels of performance for time-critical communications in Wireless Networked Control Systems (WNCSs). To improve or even guarantee real-time performance in wireless control systems, this thesis presents several network layout strategies and a new transport layer protocol. Firstly, real-time performances in regard to data transmission delays and reliability of IEEE 802.11b-based UDP/IP NCSs are evaluated through simulations. After analysis of the simulation results, some network layout strategies are presented to achieve relatively small and deterministic network-introduced latencies and reduce data loss rates. These are effective in providing better network performance without performance degradation of other services. After the investigation into the layout strategies, the thesis presents a new transport protocol which is more effcient than UDP and TCP for guaranteeing reliable and time-critical communications in WNCSs. From the networking perspective, introducing appropriate communication schemes, modifying existing network protocols and devising new protocols, have been the most effective and popular ways to improve or even guarantee real-time performance to a certain extent. Most previously proposed schemes and protocols were designed for real-time multimedia communication and they are not suitable for real-time control systems. Therefore, devising a new network protocol that is able to satisfy real-time requirements in WNCSs is the main objective of this research project. The Conditional Retransmission Enabled Transport Protocol (CRETP) is a new network protocol presented in this thesis. Retransmitting unacknowledged data packets is effective in compensating for data losses. However, every data packet in realtime control systems has a deadline and data is assumed invalid or even harmful when its deadline expires. CRETP performs data retransmission only in the case that data is still valid, which guarantees data timeliness and saves memory and network resources. A trade-off between delivery reliability, transmission latency and network resources can be achieved by the conditional retransmission mechanism. Evaluation of protocol performance was conducted through extensive simulations. Comparative studies between CRETP, UDP and TCP were also performed. These results showed that CRETP significantly: 1). improved reliability of communication, 2). guaranteed validity of received data, 3). reduced transmission latency to an acceptable value, and 4). made delays relatively deterministic and predictable. Furthermore, CRETP achieved the best overall performance in comparative studies which makes it the most suitable transport protocol among the three for real-time communications in a WNCS.
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Introduction Falls are the most frequent adverse event reported in hospitals. Approximately 30% of in-hospital falls lead to an injury and up to 2% result in a fracture. A large randomised trial found that a trained health professional providing individualised falls prevention education to older inpatients reduced falls in a cognitively intact subgroup. This study aims to investigate whether this efficacious intervention can reduce falls and be clinically useful and cost-effective when delivered in the real-life clinical environment. Methods A stepped-wedge cluster randomised trial will be used across eight subacute units (clusters) which will be randomised to one of four dates to start the intervention. Usual care on these units includes patient's screening, assessment and implementation of individualised falls prevention strategies, ongoing staff training and environmental strategies. Patients with better levels of cognition (Mini-Mental State Examination >23/30) will receive the individualised education from a trained health professional in addition to usual care while patient's feedback received during education sessions will be provided to unit staff. Unit staff will receive training to assist in intervention delivery and to enhance uptake of strategies by patients. Falls data will be collected by two methods: case note audit by research assistants and the hospital falls reporting system. Cluster-level data including patient's admissions, length of stay and diagnosis will be collected from hospital systems. Data will be analysed allowing for correlation of outcomes (clustering) within units. An economic analysis will be undertaken which includes an incremental cost-effectiveness analysis. Ethics and dissemination The study was approved by The University of Notre Dame Australia Human Research Ethics Committee and local hospital ethics committees. Results The results will be disseminated through local site networks, and future funding and delivery of falls prevention programmes within WA Health will be informed. Results will also be disseminated through peer-reviewed publications and medical conferences.
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Global cereal production will need to increase by 50% to 70% to feed a world population of about 9 billion by 2050. This intensification is forecast to occur mostly in subtropical regions, where warm and humid conditions can promote high N2O losses from cropped soils. To secure high crop production without exacerbating N2O emissions, new nitrogen (N) fertiliser management strategies are necessary. This one-year study evaluated the efficacy of a nitrification inhibitor (3,4-dimethylpyrazole phosphate—DMPP) and different N fertiliser rates to reduce N2O emissions in a wheat–maize rotation in subtropical Australia. Annual N2O emissions were monitored using a fully automated greenhouse gas measuring system. Four treatments were fertilized with different rates of urea, including a control (40 kg-N ha−1 year−1), a conventional N fertiliser rate adjusted on estimated residual soil N (120 kg-N ha−1 year−1), a conventional N fertiliser rate (240 kg-N ha−1 year−1) and a conventional N fertiliser rate (240 kg-N ha−1 year−1) with nitrification inhibitor (DMPP) applied at top dressing. The maize season was by far the main contributor to annual N2O emissions due to the high soil moisture and temperature conditions, as well as the elevated N rates applied. Annual N2O emissions in the four treatments amounted to 0.49, 0.84, 2.02 and 0.74 kg N2O–N ha−1 year−1, respectively, and corresponded to emission factors of 0.29%, 0.39%, 0.69% and 0.16% of total N applied. Halving the annual conventional N fertiliser rate in the adjusted N treatment led to N2O emissions comparable to the DMPP treatment but extensively penalised maize yield. The application of DMPP produced a significant reduction in N2O emissions only in the maize season. The use of DMPP with urea at the conventional N rate reduced annual N2O emissions by more than 60% but did not affect crop yields. The results of this study indicate that: (i) future strategies aimed at securing subtropical cereal production without increasing N2O emissions should focus on the fertilisation of the summer crop; (ii) adjusting conventional N fertiliser rates on estimated residual soil N is an effective practice to reduce N2O emissions but can lead to substantial yield losses if the residual soil N is not assessed correctly; (iii) the application of DMPP is a feasible strategy to reduce annual N2O emissions from sub-tropical wheat–maize rotations. However, at the N rates tested in this study DMPP urea did not increase crop yields, making it impossible to recoup extra costs associated with this fertiliser. The findings of this study will support farmers and policy makers to define effective fertilisation strategies to reduce N2O emissions from subtropical cereal cropping systems while maintaining high crop productivity. More research is needed to assess the use of DMPP urea in terms of reducing conventional N fertiliser rates and subsequently enable a decrease of fertilisation costs and a further abatement of fertiliser-induced N2O emissions.
Resumo:
Global cereal production will need to increase by 50% to 70% to feed a world population of about 9 billion by 2050. This intensification is forecast to occur mostly in subtropical regions, where warm and humid conditions can promote high N2O losses from cropped soils. To secure high crop production without exacerbating N2O emissions, new nitrogen (N) fertiliser management strategies are necessary. This one-year study evaluated the efficacy of a nitrification inhibitor (3,4-dimethylpyrazole phosphate—DMPP) and different N fertiliser rates to reduce N2O emissions in a wheat–maize rotation in subtropical Australia. Annual N2O emissions were monitored using a fully automated greenhouse gas measuring system. Four treatments were fertilized with different rates of urea, including a control (40 kg-N ha−1 year−1), a conventional N fertiliser rate adjusted on estimated residual soil N (120 kg-N ha−1 year−1), a conventional N fertiliser rate (240 kg-N ha−1 year−1) and a conventional N fertiliser rate (240 kg-N ha−1 year−1) with nitrification inhibitor (DMPP) applied at top dressing. The maize season was by far the main contributor to annual N2O emissions due to the high soil moisture and temperature conditions, as well as the elevated N rates applied. Annual N2O emissions in the four treatments amounted to 0.49, 0.84, 2.02 and 0.74 kg N2O–N ha−1 year−1, respectively, and corresponded to emission factors of 0.29%, 0.39%, 0.69% and 0.16% of total N applied. Halving the annual conventional N fertiliser rate in the adjusted N treatment led to N2O emissions comparable to the DMPP treatment but extensively penalised maize yield. The application of DMPP produced a significant reduction in N2O emissions only in the maize season. The use of DMPP with urea at the conventional N rate reduced annual N2O emissions by more than 60% but did not affect crop yields. The results of this study indicate that: (i) future strategies aimed at securing subtropical cereal production without increasing N2O emissions should focus on the fertilisation of the summer crop; (ii) adjusting conventional N fertiliser rates on estimated residual soil N is an effective practice to reduce N2O emissions but can lead to substantial yield losses if the residual soil N is not assessed correctly; (iii) the application of DMPP is a feasible strategy to reduce annual N2O emissions from sub-tropical wheat–maize rotations. However, at the N rates tested in this study DMPP urea did not increase crop yields, making it impossible to recoup extra costs associated with this fertiliser. The findings of this study will support farmers and policy makers to define effective fertilisation strategies to reduce N2O emissions from subtropical cereal cropping systems while maintaining high crop productivity. More research is needed to assess the use of DMPP urea in terms of reducing conventional N fertiliser rates and subsequently enable a decrease of fertilisation costs and a further abatement of fertiliser-induced N2O emissions.
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Workshop Research Data Management – Activities and Challenges 14-15 November 2011, Bonn The Knowledge Exchange initiative organised a workshop to highlight current activities and challenges with respect to research data management in the Knowledge Exchange partner countries and beyond. The workshop brought together experts from data centres, libraries, computational centres, funding organisations, publishing services and other institutions in the field of research and higher education who are working to improve research data management and encourage effective reuse of research data. A considerable part of the programme was dedicated to sharing perspectives from these communities, leading to the development of a roadmap of practical actions for the Knowledge Exchange initiative, partner organisations and other stakeholders to progress over the next two years. On the first day, principal investigators and project managers from a great variety of recent projects shared their insights on objectives and methods for improving data management ranging from discipline-specific to more general approaches. A series of short presentations of selected projects was followed by an extensive poster session that functioned as a “trade fair” of current trends and activities in the field of research data management. Moreover, the poster session offered ample network opportunities for participants. The second day was dedicated to intensive group discussions looking at a number of data management challenges. First the most important findings from the "Surfboard for 'Riding the Wave'" report were presented. This included the state of the art on activities and challenges in the field of research data management. The subgroups will concentrate on the following key themes: funding, incentives, training and technical infrastructure. These discussions culminated in the identification of practical recommendations for future cooperation on practical as well as on strategic levels that should be taken forward by the KE partner organisations and beyond. These activities aim to improve the sustainability of services and infrastructures at both national and international levels.
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Tagging experiments are a useful tool in fisheries for estimating mortality rates and abundance of fish. Unfortunately, nonreporting of recovered tags is a common problem in commercial fisheries which, if unaccounted for, can render these estimates meaningless. Observers are often employed to monitor a portion of the catches as a means of estimating reporting rates. In our study, observer data were incorporated into an integrated model for multiyear tagging and catch data to provide joint estimates of mortality rates (natural and f ishing), abundance, and reporting rates. Simulations were used to explore model performance under a range of scenarios (e.g., different parameter values, parameter constraints, and numbers of release and recapture years). Overall, results indicated that all parameters can be estimated with reasonable accuracy, but that fishing mortality, reporting rates, and abundance can be estimated with much higher precision than natural mortality. An example of how the model can be applied to provide guidance on experimental design for a large-scale tagging study is presented. Such guidance can contribute to the successful and cost-effective management of tagging programs for commercial fisheries.
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The electron self-exchange rates (k(ex)) of viologen and its derivatives are estimated by using microelectrode voltammetry in poly(ethylene glycol) films. The dependences of supporting electrolyte concentration and sizes of viologen and its derivatives on k(ex) and diffusion coefficients (D) are discussed. Results show that k(ex) increases with the decrease of supporting electrolyte concentration and sizes of reactants. (C) 2000 Elsevier Science S.A. All rights reserved.
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Consistent with the implications from a simple asymmetric information model for the bid-ask spread, we present empirical evidence that the size of the bid-ask spread in the foreign exchange market is positively related to the underlying exchange rate uncertainty. The estimation results are based on an ordered probit analysis that captures the discreteness in the spread distribution, with the uncertainty of the spot exchange rate being quantified through a GARCH type model. The data sets consists of more than 300,000 continuously recorded Deutschemark/dollar quotes over the period from April 1989 to June 1989. © 1994.
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We present a simple framework in which both the exchange rate disconnect and forward bias puzzles are simultaneously resolved. The flexible-price two-country monetary model is extended to include a consumption externality with habit persistence. Habitpersistence is modeled using Campbell Cochrane preferences with ‘deep’ habits along the lines of the work of Ravn, Schmitt-Grohe and Uribe. By deep habits, we mean habits defined over goods rather than countries. The model is simulated using the artificial economy methodology. It offers a neo-classical explanation of the Meese–Rogoff puzzle and mimics the failure of fundamentals to explain nominal exchange rates in a linear setting. Finally, the model naturally generates the negative slope in the standard forward market regression.