936 resultados para ECONOMIC MODELS


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To assess the clinical effectiveness and cost-effectiveness of bariatric surgery for obesity. Seventeen electronic databases were searched [MEDLINE; EMBASE; PreMedline In-Process & Other Non-Indexed Citations; The Cochrane Library including the Cochrane Systematic Reviews Database, Cochrane Controlled Trials Register, DARE, NHS EED and HTA databases; Web of Knowledge Science Citation Index (SCI); Web of Knowledge ISI Proceedings; PsycInfo; CRD databases; BIOSIS; and databases listing ongoing clinical trials] from inception to August 2008. Bibliographies of related papers were assessed and experts were contacted to identify additional published and unpublished references. Two reviewers independently screened titles and abstracts for eligibility. Inclusion criteria were applied to the full text using a standard form. Interventions investigated were open and laparoscopic bariatric surgical procedures in widespread current use compared with one another and with non-surgical interventions. Population comprised adult patients with body mass index (BMI) > or = 30 and young obese people. Main outcomes were at least one of the following after at least 12 months follow-up: measures of weight change; quality of life (QoL); perioperative and postoperative mortality and morbidity; change in obesity-related comorbidities; cost-effectiveness. Studies eligible for inclusion in the systematic review for comparisons of Surgery versus Surgery were RCTs. For comparisons of Surgery versus Non-surgical procedures eligible studies were RCTs, controlled clinical trials and prospective cohort studies (with a control cohort). Studies eligible for inclusion in the systematic review of cost-effectiveness were full cost-effectiveness analyses, cost-utility analyses, cost-benefit analyses and cost-consequence analyses. One reviewer performed data extraction, which was checked by two reviewers independently. Two reviewers independently applied quality assessment criteria and differences in opinion were resolved at each stage. Studies were synthesised through a narrative review with full tabulation of the results of all included studies. In the economic model the analysis was developed for three patient populations, those with BMI > or = 40; BMI > or = 30 and < 40 with Type 2 diabetes at baseline; and BMI > or = 30 and < 35. Models were applied with assumptions on costs and comorbidity.

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Construction price forecasting is an essential component to facilitate decision-making for construction contractors, investors and related financial institutions. Construction economists are increasingly interested in seeking a more analytical method to forecast construction prices. Although many studies have focused on construction price modelling and forecasting, few have considered the impacts of large-scale economic events and seasonality. In this study, an advanced multivariate modelling technique, namely the vector correction (VEC) model with dummy variables, was employed. The impacts of global economic events and seasonality are factored into the model to forecast the construction price in the Australian construction market. Research findings suggest that both long-run and dynamic short-term causal relationships exist among the price and levels of supply and demand in the construction market. These relationships drive the construction price and supply and demand, which interact with one another as a loop system. The reliability of forecasting models was examined by the mean absolute percentage error (MAPE) and the Theil's inequality coefficient U tests. The test results suggest that the conventional VEC model and the VEC model with dummy variable are both acceptable for forecasting the construction price, while the VEC model considering external impacts achieves higher prediction accuracy than the conventional VEC model. © 2014 © 2014 Taylor & Francis.

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Coal comprises 70 per cent of China’s primary energy source and 80 per cent of China's electricity generation. This study investigates the long-run relationship between coal consumption-economic growth nexus considering both supply and demand side models in a multivariate framework over the period of 1978 and 2010. Our innovation in this paper is to include a coal-to-electricity efficiency indicator into the economic growth model ; and trade exposure in coal demand. Using Autoregressive Distributed Lag bounds testing approach, we find improvement in coal-to-efficiency indicator causes almost 35 per cent increase in real GDP in the long-run. The Toda-Yamamoto approach of causality test indicates unidirectional causality from coal consumption to economic growth; feedback effect both for coal-to-electricity efficiency indicator to economic growth and openness to coal consumption. For robustness check, using the generalised forecast error variance decomposition method we forecast the validity of causal relationships beyond the sample horizon. The paper suggests the role of advanced coal technologies will play a significant role along with other environmental and energy policies in maintaining sustainable economic growth in China .

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In this paper, we show that in the proposed models for economic growth, the financial system variables are generally nonparametric. We, thus, use a nonparametric panel data model to estimate the financial system-economic growth relationship. Our results suggest that as long as a country's domestic credit and private credit are above their cross-sectional mean they have a positive effect on GDP growth. We also discover that market capitalisation positively and significantly impacts GDP growth, while stocks traded (with the exception of OECD countries) has a statistically insignificant effect on GDP growth.

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The common starling (Sturnus vulgaris) has a proven invasion history in many countries, and at a continental scale in North America and Australasia. In Australia, starlings are firmly established throughout the eastern states and Tasmania. Incursions of starlings into Western Australia (WA) represent a significant threat to this State’s agricultural, public amenity and biodiversity assets. We present models of starling population dynamics that incorporate environmental and control effort variability. We incorporate knowledge of starling ecology with economic data to assess the potential economic cost of starlings establishing in WA, evaluating the cost–benefits for each management scenario. We calculated starling population size will approach carrying capacity in WA within as little as 30 years if left unchecked. A population of this size could cost the WA economy up to $43.7 million annually in 2011/2012 dollars. Over a 50 year horizon, the conservative benefit–cost ratio for ongoing detection and control at the current level of expenditure is 6.03:1. However, even under current levels of control, starling numbers are projected to increase to almost 11 million by 2061. Further improvements in the efficiency of starling detection and control and/or an increased level of expenditure on detection and control are required.

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In the last years extreme hydrometeorological phenomena have increased in number and intensity affecting the inhabitants of various regions, an example of these effects are the central basins of the Gulf of Mexico (CBGM) that they have been affected by 55.2% with floods and especially the state of Veracruz (1999-2013), leaving economic, social and environmental losses. Mexico currently lacks sufficient hydrological studies for the measurement of volumes in rivers, since is convenient to create a hydrological model (HM) suited to the quality and quantity of the geographic and climatic information that is reliable and affordable. Therefore this research compares the semi-distributed hydrological model (SHM) and the global hydrological model (GHM), with respect to the volumes of runoff and achieve to predict flood areas, furthermore, were analyzed extreme hydrometeorological phenomena in the CBGM, by modeling the Hydrologic Modeling System (HEC-HMS) which is a SHM and the Modèle Hydrologique Simplifié à I'Extrême (MOHYSE) which is a GHM, to evaluate the results and compare which model is suitable for tropical conditions to propose public policies for integrated basins management and flood prevention. Thus it was determined the temporal and spatial framework of the analyzed basins according to hurricanes and floods. It were developed the SHM and GHM models, which were calibrated, validated and compared the results to identify the sensitivity to the real model. It was concluded that both models conform to tropical conditions of the CBGM, having MOHYSE further approximation to the real model. Worth mentioning that in Mexico there is not enough information, besides there are no records of MOHYSE use in Mexico, so it can be a useful tool for determining runoff volumes. Finally, with the SHM and the GHM were generated climate change scenarios to develop risk studies creating a risk map for urban planning, agro-hydrological and territorial organization.

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In this article we study the growth and welfare effects of fiscal and monetary policies in economies where public investment is part of the productive process we present four different models that share the same technology with public infrastructure as a separate argument of the production function. We show that growth is maximized at positive levels of income tax and inflation. However, unless there are no transfers or public goods in the economy, maximization of growth does not imply welfare maximization we show that the optimal tax rate is greater than the rate that maximizes growth and the optimal rate of money creation is below the growth maximizing rate. With public infrastructure in the production function we no longer obtain superneutrality in the Sidrausky model.

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This work presents a fully operational interstate CGE model implemented for the Brazilian economy that tries to quantify both the role of barriers to trade on economic growth and foreign trade performance and how the distribution of the economic activity may change as the country opens up to foreign trade. Among the distinctive features embedded in the model, modeling of external scale economies, port efficiency and land-maritime transport costs provides an innovative way of dealing explicitly with theoretical issues related to integrated regional systems. In order to illustrate the role played by the quality of infrastructure and geography on the country‟s foreign and interregional trade performance, a set of simulations is presented where barriers to trade are significantly reduced. The relative importance of trade policy, port efficiency and land-maritime transport costs for the country trade relations and regional growth is then detailed and quantified, considering both short run as well as long run scenarios. A final set of simulations shed some light on the effects of liberal trade policies on regional inequality, where the manufacturing sector in the state of São Paulo, taken as the core of industrial activity in the country, is subjected to different levels of external economies of scale. Short-run core-periphery effects are then traced out suggesting the prevalence of agglomeration forces over diversion forces could rather exacerbate regional inequality as import barriers are removed up to a certain level. Further removals can reverse this balance in favor of diversion forces, implying de-concentration of economic activity. In the long run, factor mobility allows a better characterization of the balance between agglomeration and diversion forces among regions. Regional dispersion effects are then clearly traced-out, suggesting horizontal liberal trade policies to benefit both the poorest regions in the country as well as the state of São Paulo. This long run dispersion pattern, on one hand seems to unravel the fragility of simple theoretical results from recent New Economic Geography models, once they get confronted with more complex spatially heterogeneous (real) systems. On the other hand, it seems to capture the literature‟s main insight: the possible role of horizontal liberal trade policies as diversion forces leading to a more homogeneous pattern of interregional economic growth.

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The past decade has wítenessed a series of (well accepted and defined) financial crises periods in the world economy. Most of these events aI,"e country specific and eventually spreaded out across neighbor countries, with the concept of vicinity extrapolating the geographic maps and entering the contagion maps. Unfortunately, what contagion represents and how to measure it are still unanswered questions. In this article we measure the transmission of shocks by cross-market correlation\ coefficients following Forbes and Rigobon's (2000) notion of shift-contagion,. Our main contribution relies upon the use of traditional factor model techniques combined with stochastic volatility mo deIs to study the dependence among Latin American stock price indexes and the North American indexo More specifically, we concentrate on situations where the factor variances are modeled by a multivariate stochastic volatility structure. From a theoretical perspective, we improve currently available methodology by allowing the factor loadings, in the factor model structure, to have a time-varying structure and to capture changes in the series' weights over time. By doing this, we believe that changes and interventions experienced by those five countries are well accommodated by our models which learns and adapts reasonably fast to those economic and idiosyncratic shocks. We empirically show that the time varying covariance structure can be modeled by one or two common factors and that some sort of contagion is present in most of the series' covariances during periods of economical instability, or crisis. Open issues on real time implementation and natural model comparisons are thoroughly discussed.

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How do the liquidity functions of banks affect investment and growth at different stages of economic development? How do financial fragility and the costs of banking crises evolve with the level of wealth of countries? We analyze these issues using an overlapping generations growth model where agents, who experience idiosyncratic liquidity shocks, can invest in a liquid storage technology or in a partially illiquid Cobb Douglas technology. By pooling liquidity risk, banks play a growth enhancing role in reducing inefficient liquidation of long term projects, but they may face liquidity crises associated with severe output losses. We show that middle income economies may find optimal to be exposed to liquidity crises, while poor and rich economies have more incentives to develop a fully covered banking system. Therefore, middle income economies could experience banking crises in the process of their development and, as they get richer, they eventually converge to a financially safe long run steady state. Finally, the model replicates the empirical fact of higher costs of banking crises for middle income economies.

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Recent models of economic voting assume that citizens can discount exogenous factors when assessing government's economic performance. Yet there is evidence that Latin American voters do not behave in such way, and attribute to presidents outcomes that are beyond their control. This paper presents three survey experiments designed to explore mechanisms that could potentially correct such misattribution, and therefore contribute to debiasing individual behavior towards government evaluation. Our results provide individual-level evidence of the misattribution found in aggregate studies of electorate behavior, and reinforce psychologist's skepticism towards prospects of mental decontamination, as we found very scant evidence that providing information, raising awareness, or increasing motivation to correct biases infuenced individual's evaluation of president's performance.

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SILVA, Flávio César Bezerra da ; COSTA, Francisca Marta de Lima; ANDRADE, Hamilton Leandro Pinto de; FREIRE, Lúcia de Fátima; MACIEL, Patrícia Suerda de Oliveira; ENDERS, Bertha Cruz ; MENEZES, Rejane Maria Paiva de. Paradigms that guide the models of attention to the health in Brazil: an analytic essay. Revista de Enfermagem UFPE On Line., Recife, v.3,n.4, p.460-65. out/dez. 2009. Disponível em < http://www.ufpe.br/revistaenfermagem/index.php/revista/search/results >.

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Economic dispatch (ED) problems have recently been solved by artificial neural network approaches. Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. The ability of neural networks to realize some complex non-linear function makes them attractive for system optimization. All ED models solved by neural approaches described in the literature fail to represent the transmission system. Therefore, such procedures may calculate dispatch policies, which do not take into account important active power constraints. Another drawback pointed out in the literature is that some of the neural approaches fail to converge efficiently toward feasible equilibrium points. A modified Hopfield approach designed to solve ED problems with transmission system representation is presented in this paper. The transmission system is represented through linear load flow equations and constraints on active power flows. The internal parameters of such modified Hopfield networks are computed using the valid-subspace technique. These parameters guarantee the network convergence to feasible equilibrium points, which represent the solution for the ED problem. Simulation results and a sensitivity analysis involving IEEE 14-bus test system are presented to illustrate efficiency of the proposed approach. (C) 2004 Elsevier Ltd. All rights reserved.

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Economic Dispatch (ED) problems have recently been solved by artificial neural networks approaches. In most of these dispatch models, the cost function must be linear or quadratic. Therefore, functions that have several minimum points represent a problem to the simulation since these approaches have not accepted nonlinear cost function. Another drawback pointed out in the literature is that some of these neural approaches fail to converge efficiently towards feasible equilibrium points. This paper discusses the application of a modified Hopfield architecture for solving ED problems defined by nonlinear cost function. The internal parameters of the neural network adopted here are computed using the valid-subspace technique, which guarantees convergence to equilibrium points that represent a solution for the ED problem. Simulation results and a comparative analysis involving a 3-bus test system are presented to illustrate efficiency of the proposed approach.

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This paper deals with the joint economic design of (x) over bar and R charts when the occurrence times of assignable causes follow Weibull distributions with increasing failure rates. The variable quality characteristic is assumed to be normally distributed and the process is subject to two independent assignable causes (such as tool wear-out, overheating, or vibration). One cause changes the process mean and the other changes the process variance. However, the occurrence of one kind of assignable cause does not preclude the occurrence of the other. A cost model is developed and a non-uniform sampling interval scheme is adopted. A two-step search procedure is employed to determine the optimum design parameters. Finally, a sensitivity analysis of the model is conducted, and the cost savings associated with the use of non-uniform sampling intervals instead of constant sampling intervals are evaluated.