127 resultados para game-theoretical models of monetary policy


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In this paper, Bond Graphs are employed to develop a novel mathematical model of conventional switched-mode DC-DC converters valid for both continuous and discontinuous conduction modes. A unique causality bond graph model of hybrid models is suggested with the operation of the switch and the diode to be represented by a Modulated Transformer with a binary input and a resistor with fixed conductance causality. The operation of the diode is controlled using an if-then function within the model. The extracted hybrid model is implemented on a Boost and Buck converter with their operations to change from CCM to DCM and to return to CCM. The vector fields of the models show validity in a wide operation area and comparison with the simulation of the converters using PSPICE reveals high accuracy of the proposed model, with the Normalised Root Means Square Error and the Maximum Absolute Error remaining adequately low. The model is also experimentally tested on a Buck topology.

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Cognitive models of obsessive compulsive disorder (OCD) have been influential in understanding and treating the disorder in adults. Cognitive models may also be applicable to children and adolescents and would have important implications for treatment. The aim of this systematic review was to evaluate research that examined the applicability of the cognitive model of OCD to children and adolescents. Inclusion criteria were set broadly but most studies identified included data regarding responsibility appraisals, thought-action fusion or meta-cognitive models of OCD in children or adolescents. Eleven studies were identified in a systematic literature search. Seven studies were with non clinical samples, and 10 studies were cross-sectional. Only one study did not support cognitive models of OCD in children and adolescents and this was with a clinical sample and was the only experimental study. Overall, the results strongly supported the applicability of cognitive models of OCD to children and young people. There were, however, clear gaps in the literature. Future research should include experimental studies, clinical groups, and should test which of the different models provide more explanatory power.

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The contraction of a species’ distribution range, which results from the extirpation of local populations, generally precedes its extinction. Therefore, understanding drivers of range contraction is important for conservation and management. Although there are many processes that can potentially lead to local extirpation and range contraction, three main null models have been proposed: demographic, contagion, and refuge. The first two models postulate that the probability of local extirpation for a given area depends on its relative position within the range; but these models generate distinct spatial predictions because they assume either a ubiquitous (demographic) or a clinal (contagion) distribution of threats. The third model (refuge) postulates that extirpations are determined by the intensity of human impacts, leading to heterogeneous spatial predictions potentially compatible with those made by the other two null models. A few previous studies have explored the generality of some of these null models, but we present here the first comprehensive evaluation of all three models. Using descriptive indices and regression analyses we contrast the predictions made by each of the null models using empirical spatial data describing range contraction in 386 terrestrial vertebrates (mammals, birds, amphibians, and reptiles) distributed across the World. Observed contraction patterns do not consistently conform to the predictions of any of the three models, suggesting that these may not be adequate null models to evaluate range contraction dynamics among terrestrial vertebrates. Instead, our results support alternative null models that account for both relative position and intensity of human impacts. These new models provide a better multifactorial baseline to describe range contraction patterns in vertebrates. This general baseline can be used to explore how additional factors influence contraction, and ultimately extinction for particular areas or species as well as to predict future changes in light of current and new threats.

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This article investigates fiscal policy responses to the Great Recession in historical perspective. We explore general trends in the frequency, size and composition of fiscal stimulus as well as the impact of government partisanship on fiscal policy outputs during the four international recessions of 1980-81, 1990-91, 2001-02 and 2008-09. Encompassing 17-23 OECD countries, our analysis calls into question the idea of a general retreat from fiscal policy activism since the early 1980s. The propensity of governments to respond to economic downturns by engaging in fiscal stimulus has increased over time and we do not observe any secular trend in the size of stimulus measures. At the same time, OECD governments have relied more on tax cuts to stimulate demand in the two recessions of the 2000s than they did in the early 1980s or early 1990s. Regarding government partisanship, we do not find any significant direct partisan effects on either the size or the composition of fiscal stimulus for any of the four recession episodes. However, the size of the welfare state conditioned the impact of government partisanship in the two recessions of the 2000s, with Left-leaning governments distinctly more prone to engage in discretionary fiscal stimulus and/or spending increases in large welfare states, but not in small welfare states.

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Existing theoretical models of house prices and credit rely on continuous rationality of consumers, an assumption that has been frequently questioned in recent years. Meanwhile, empirical investigations of the relationship between prices and credit are often based on national-level data, which is then tested for structural breaks and asymmetric responses, usually with subsamples. Earlier author argues that local markets are structurally different from one another and so the coefficients of any estimated housing market model should vary from region to region. We investigate differences in the price–credit relationship for 12 regions of the UK. Markov-switching is introduced to capture asymmetric market behaviours and turning points. Results show that credit abundance had a large impact on house prices in Greater London and nearby regions alongside a strong positive feedback effect from past house price movements. This impact is even larger in Greater London and the South East of England when house prices are falling, which are the only instances where the credit effect is more prominent than the positive feedback effect. A strong positive feedback effect from past lending activity is also present in the loan dynamics. Furthermore, bubble probabilities extracted using a discrete Kalman filter neatly capture market turning points.

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This paper presents an open-source canopy height profile (CHP) toolkit designed for processing small-footprint full-waveform LiDAR data to obtain the estimates of effective leaf area index (LAIe) and CHPs. The use of the toolkit is presented with a case study of LAIe estimation in discontinuous-canopy fruit plantations. The experiments are carried out in two study areas, namely, orange and almond plantations, with different percentages of canopy cover (48% and 40%, respectively). For comparison, two commonly used discrete-point LAIe estimation methods are also tested. The LiDAR LAIe values are first computed for each of the sites and each method as a whole, providing “apparent” site-level LAIe, which disregards the discontinuity of the plantations’ canopies. Since the toolkit allows for the calculation of the study area LAIe at different spatial scales, between-tree-level clumpingcan be easily accounted for and is then used to illustrate the impact of the discontinuity of canopy cover on LAIe retrieval. The LiDAR LAIe estimates are therefore computed at smaller scales as a mean of LAIe in various grid-cell sizes, providing estimates of “actual” site-level LAIe. Subsequently, the LiDAR LAIe results are compared with theoretical models of “apparent” LAIe versus “actual” LAIe, based on known percent canopy cover in each site. The comparison of those models to LiDAR LAIe derived from the smallest grid-cell sizes against the estimates of LAIe for the whole site has shown that the LAIe estimates obtained from the CHP toolkit provided values that are closest to those of theoretical models.