990 resultados para policy simulation


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Simulation models (SMs) combine information from a variety of sources to provide a useful tool for examining how the effects of obesity unfold over time and impact population health. SMs can aid in the understanding of the complex interaction of the drivers of diet and activity and their relation to health outcomes. As emphasized in a recently released report of the Institute or Medicine, SMs can be especially useful for considering the potential impact of an array of policies that will be required to tackle the obesity problem. The purpose of this paper is to present an overview of existing SMs for obesity. First, a background section introduces the different types of models, explains how models are constructed, shows the utility of SMs and discusses their strengths and weaknesses. Using these typologies, we then briefly review extant obesity SMs. We categorize these models according to their focus: health and economic outcomes, trends in obesity as a function of past trends, physiologically based behavioural models, environmental contributors to obesity and policy interventions. Finally, we suggest directions for future research.

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This paper investigates the impacts of high interest rates for borrowed capital and credit restrictions on the structural development of four European regions. The method used is the model AgriPoliS which is a spatial-dynamic agent-based model. It is able to provide aggregated results at the regional level, but very individual results as well by considering farms as independent entities. Farms can choose between different investment options during the simulation. Several scenarios with different interest rates for borrowed capital on the one hand as well as with different levels of credit restrictions on the other hand are tested and compared. Results show that higher interest rates have less impact on declining production branches than on expanding ones. If they have the possibility farms invest in the most profitable production branch which relative profitability might have changed with high interest rates. Credit restrictions lead farms to choose smaller and cheaper investments than expensive and large ones. Results also show that income losses in both cases due to under-investment compared to the reference situation are partially compensated by lower rental prices. The impacts on structural change also differ depending on the region and the initial situation. In summary, credit subsidies or imperfections on credit markets might have indirect impacts on the type of dominant investment and therefore on the whole regional agricultural sector as well.

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Not surprisingly housing researchers and practitioners frequently call for more resources to be devoted to housing. But governments in recent years have devoted fewer resources to housing rather than more. One of the reasons is that housing expenditures have to be seen in terms of the overall resource constraints on the economy and in many instances this requires a macro‐economic perspective. This paper reviews the macro‐economic arguments for and against housing expenditures, particularly through the use of a quantitative policy simulation model.

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The “cotton issue” has been a topic of several academic discussions for trade policy analysts. However the design of trade and agricultural policy in the EU and the USA has become a politically sensitive matter throughout the last five years. This study utilizing the Agricultural Trade Policy Simulation Model (ATPSM) aims to gain insights into the global cotton market, to explain why domestic support for cotton has become an issue, to quantify the impact of the new EU agricultural policy on the cotton sector, and to measure the effect of eliminating support policies on production and trade. Results indicate that full trade liberalization would lead the four West African countries to better terms of trade with the EU. If tariff reduction follows the so-called Swiss formula, world prices would increase by 3.5%.

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To be useful for policy simulation in the current climate of rapid structural change, inverse demand systems must remain regular over substanstial variations in quantities. The distance function is a convenient vehicle for generating such systems. It also allows convenient imposition of prior ideas about the structure of preferences required for realistic policy work. While the distance function directly yields Hicksian inverse demand functions via the Shepard-Hanoch lemma, they are usually explicit in the unobservable level of utility (u), but lack a closed-form representation in terms of the observable variables. Note however that the unobservability of u need not hinder estimation. A simple one-dimensional numerical inversion allows the estimation of the distance function via the parameters of the implied Marshallian inverse demand functions. This paper develops the formal theory for using distance functions in this context, and reports on initial trials on the operational feasibility of the method.

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My article is a succinct overview of macro-Polish governments’ evolution over 25 years of political transformation. It is presented from the perspective of education for democracy, in a democracy and not about democracy. I explain how Poles, after they got rid of the monistic doctrine of the totalitarian state, have become subjected to a covert process of democratization of education and the school system. I analyze public education, mechanisms and structures for its management in a way that counteracts democratic change. The school is subjected to political game-makers. It becomes an institution which is painfully ineffective and without a face. This institution destroys tradition and causes intellectual regression. There are threats to educational reforms which lie not only in the sociopolitical mechanisms, but also and perhaps primarily within the education system, which has not created procedures to eliminate Pharisees of innovation from it. After 25 years of transformation, the Polish educational system is not only partially reprivatized but highly bureaucratic and fully involved in political parties.

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Nonpoint sources (NPS) pollution from agriculture is the leading source of water quality impairment in U.S. rivers and streams, and a major contributor to lakes, wetlands, estuaries and coastal waters (U.S. EPA 2016). Using data from a survey of farmers in Maryland, this dissertation examines the effects of a cost sharing policy designed to encourage adoption of conservation practices that reduce NPS pollution in the Chesapeake Bay watershed. This watershed is the site of the largest Total Maximum Daily Load (TMDL) implemented to date, making it an important setting in the U.S. for water quality policy. I study two main questions related to the reduction of NPS pollution from agriculture. First, I examine the issue of additionality of cost sharing payments by estimating the direct effect of cover crop cost sharing on the acres of cover crops, and the indirect effect of cover crop cost sharing on the acres of two other practices: conservation tillage and contour/strip cropping. A two-stage simultaneous equation approach is used to correct for voluntary self-selection into cost sharing programs and account for substitution effects among conservation practices. Quasi-random Halton sequences are employed to solve the system of equations for conservation practice acreage and to minimize the computational burden involved. By considering patterns of agronomic complementarity or substitution among conservation practices (Blum et al., 1997; USDA SARE, 2012), this analysis estimates water quality impacts of the crowding-in or crowding-out of private investment in conservation due to public incentive payments. Second, I connect the econometric behavioral results with model parameters from the EPA’s Chesapeake Bay Program to conduct a policy simulation on water quality effects. I expand the econometric model to also consider the potential loss of vegetative cover due to cropland incentive payments, or slippage (Lichtenberg and Smith-Ramirez, 2011). Econometric results are linked with the Chesapeake Bay Program watershed model to estimate the change in abatement levels and costs for nitrogen, phosphorus and sediment under various behavioral scenarios. Finally, I use inverse sampling weights to derive statewide abatement quantities and costs for each of these pollutants, comparing these with TMDL targets for agriculture in Maryland.

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XVIII IUFRO World Congress, Ljubljana 1986.

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XVIII IUFRO World Congress, Ljubljana 1986.

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We propose a simulation-based algorithm for computing the optimal pricing policy for a product under uncertain demand dynamics. We consider a parameterized stochastic differential equation (SDE) model for the uncertain demand dynamics of the product over the planning horizon. In particular, we consider a dynamic model that is an extension of the Bass model. The performance of our algorithm is compared to that of a myopic pricing policy and is shown to give better results. Two significant advantages with our algorithm are as follows: (a) it does not require information on the system model parameters if the SDE system state is known via either a simulation device or real data, and (b) as it works efficiently even for high-dimensional parameters, it uses the efficient smoothed functional gradient estimator.

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A Masters Thesis, presented as part of the requirements for the award of a Research Masters Degree in Economics from NOVA – School of Business and Economics

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Nowadays the changing environment becomes the main challenge for most of organizations, since they have to evaluate proper policies to adapt to the environment. In this paper, we propose a multi-agent simulation method to evaluate policies based on complex adaptive system theory. Furthermore, we propose a semiotic EDA (Epistemic, Deontic, Axiological) agent model to simulate agent's behavior in the system by incorporating the social norms reflecting the policy. A case study is also provided to validate our approach. Our research present better adaptability and validity than the qualitative analysis and experiment approach and the semiotic agent model provides high creditability to simulate agents' behavior.