Management of the risk of wind damage in forestry: a graph-based Markov decision process approach

This study deals with the problem of including the risk of wind damage in long-term forestry management. A model based on Graph-Based Markov Decision Processes (GMDP) is suggested for development of silvicultural management policies. The model can both take stochastic wind events into account and be applied to forest estates containing a large number of stands. The model is demonstrated for a forest estate in southern Sweden. Treatment of the stands according to the management policy specified by the GMDP model increased the expected net present value (NPV) of the whole forest only slightly, less than 2%, under different wind-risk assumptions. Most of the stands were managed in the same manner as when the risk of wind damage was not considered. For the stands that were treated differently, however, the expected NPV increased by 3% to 8%.     

MULTIPLE USE VALUES AND OPTIMAL STEADY STATE AGE DISTRIBUTIONS

Forest management today, generally, focuses not only on wood values but also on the many other amenities and services provided by growing forests. The significance of these multiple use values was recognized by Hartman [1976] who derived a formula for the optimal rotation for a single stand when the services provided by the stand throughout its life are considered in addition to the value of the final harvest. Some more recent work has focused on the case of multiple stands where the amenity values at a point in time depend on the age distribution of the stands at that time. One approach to harvesting multiple stands for wood values alone is the forestry maximum principle developed by Heaps [1984] and Wan [1985]. It will be shown here how the forestry maximum principle can be modified to incorporate the amenity services provided by the growing forest. The optimal steady state age distributions for the multiple stand forest can then be identified and described with the help of Hartman's rotation formula.     

基于Hilbert-Huang变换的金融收益政策风险因子识别方法

针对政策可能对金融收益产生风险问题,提出了基于Hilbert-Huang变换方法的政策风险因子识别检测方法。通过经验模态分解,Hilbert-Huang频谱分析得到金融时间序列的时域和频域特征,通过与量化处理后的政策进行匹配得到政策产生的异常波动情况,从而实现对政策因子风险的识别与处理。研究结果对于探究宏观政策对金融收益的影响具有重要参考意义。最后以国家房地产调控政策与地产指数为算例,发现本研究提出的方法识别精度高,具有非常好的应用前景。     

FOREST BIOENERGY ADOPTION FOR A RISK‐AVERSE LANDOWNER UNDER UNCERTAIN EMERGING BIOMASS MARKET

Abstract This paper examines a land use problem where a risk‐averse representative landowner is uncertain about the timing and extent of a future biomass market emergence. The risk‐averse landowner is expected to maximize his or her expected utility of net present value from three land uses: agriculture, conventional forestry, and bioenergy forestry. Varying land quality, expected price jumps, and the timing of biomass market emergence are incorporated into the analysis. Under constant risk aversion, the simulation results show that the level of risk aversion has a significant influence on land allocation. The analysis also includes a discussion of how transaction costs affect land use change. The results offer insights into policy making for promoting forest bioenergy market development.     

SUSTAINABLE FOREST MANAGEMENT FOR OPTIMIZING MULTISPECIES WILDLIFE HABITAT: A COASTAL DOUGLAS-FIR EXAMPLE

Wildlife species viability optimization models are developed to convert a given set of initial forest conditions, through a combination of natural growth and management treatments, to a forest system which addresses the joint habitat needs of multispecies populations over time. A linear model of forest cover and wildlife populations is used to form a system of forest management control variables for wildlife habitat modification. The paper examines two objective functions coupled to this system for optimizing sustainable joint species viability. The first maximizes the product of periodic joint viabilities over all time periods, focusing management resources on long-term equilibria, with less emphasis on conversion strategy. The second iteratively maximizes the minimum periodic joint viability over all time periods. This focuses management resources on the most limiting time periods, typically the conversion phase periods. Both objective functions resulted in either point or cyclic equilibria, with cycle lengths equal to minimum forest treatment ages. A third objective, based on maximizing the minimum individual species periodic viability is used to examine single species emphasis. Examples are developed through a case study of 92 vertebrate species found in coastal Douglas-fir stands of northwestern California.     

Goal programming: Application in the management of the miombo woodland in Mozambique

Community-based management of natural resources (CBNRM) is a priority in Mozambique's policy on forestry and wildlife resources. In essence the government's policy is to manage the natural resources in partnership with the rural communities and the private sector. This represents a change in policy in the agricultural and natural resources sectors, and has potential for significant impact in economic development. This paper demonstrates the potential for employing goal programming as a planning tool in participatory natural resource management in Mozambique. The focus is on the miombo woodlands, which are the main natural forest resources in the country and which most of the local communities, the forestry and tourist industries depend on for a variety of forest products and services.     

基于PCA-VAR模型的房地产信贷政策调控效应分析

有效的房地产调控,既要实现稳定房价、控制房地产开发投资过快增长等调控目标,同时也不会对宏观经济带来过大的负面影响.在分析各类房地产调控政策传导机制的基础上,通过构建PCA-VAR模型,并综合运用了协整分析、Granger因果检验、方差分解和脉冲效应分析等方法,细致测算了房地产信贷政策对房地产市场和宏观经济的影响,据此为我国实施房地产调控提供政策建议.     

Optimal harvest strategy for even‐aged stands with price uncertainty and risk of natural disturbances

We present a reservation price model to examine the joint impacts of natural disturbances and stumpage price uncertainty on the optimal harvesting decision for even‐aged forest stands. We consider a landowner who manages a loblolly pine stand to produce timber and amenities, under age‐dependent risk of wildfires and uncertainty in future timber prices. We show that the incorporation of risk of wildfires decreases the optimal reservation prices. The inclusion of risk of wildfires leads to lower land values and reduces the mean harvest age compared with the case of no‐risk of wildfires. Higher economic gains are obtained with the reservation price strategy compared with the deterministic rotation age model—a difference in the land value of $2,326 ha^?1 (21%) between the two approaches. Recommendations for Resource Managers

• Our adaptive harvest strategy shows that the incorporation of risk of wildfires decreases the optimal reservation prices compared with the case of no‐risk of wildfires.
• Low reservation prices—a price that makes the landowner indifferent between harvesting or waiting longer—result in lower economic benefits for landowners and potential conversions of lands to nonforest use.
• Forest management practices oriented to reduce the effects of catastrophic disturbances, for example, creating a more complex forest structure with different stand densities, become imperative to ensure the sustainability of forestlands in the US South.
• Our analysis also suggests that the valuation of forestry investments should consider not only the risk of catastrophic events but also uncertainty in future timber prices. Higher appraisals of land value are obtained when timber price uncertainty is explicitly recognized, providing financial incentives for landowners to invest in forestry.

     

带有风能的智能电网多周期买电策略研究

本文研究带有风能随机供给的智能电网中传统能源的多周期买电问题,假设存在一个能源运营商集中负责智能电网传统能源的购买和消费。通过构建并求解动态规划模型,找到能源运营商在风能供给不确定性下的传统能源最优多周期买电策略。在最优买电策略下,能源运营商只有在当期电价足够小时才购买传统能源,其买电量与风能分布、价格信息和时间信息有关。在实际数据的基础之上,提供详实的数值实验对比研究了本文的最优买电策略和其他两种策略(实践中只考虑风能估计的策略和放弃利用风能的策略)在最小化总成本方面的效果,并验证了本文的最优买电策略在真实风能数据中的鲁棒性。     

Endangered species,real options,and forest management

We use a real option approach to determine optimally when a social planner has to stop or resume logging in situations where an endangered species relies on forest habitat for its survival, and that habitat evolves stochasticly. The model incorporates economic, ecological and social features, and is calibrated to generate an optimal forest management rule that balances the benefits from commercial forest exploitation with the risks of extinction facing the endangered species. For the reasonable parameters used in our application to the Rangifer tarandus caribou, an endangered species in Central Labrador (Canada), the policy of banning logging temporarily is quite attractive as it does not require long banning periods while it drastically reduces the extinction risk and increases forest value. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Carbon sequestration and land management under uncertainty

Uncertainty about the role of forestry and land-use change in mitigating global warming is addressed using a possibilistic linear programming model of forest and agricultural land management. The objective is to maximize the cumulative net discounted returns in the two sectors, while meeting specific carbon-uptake goals and maintaining stable flows of timber over the planning horizon. Because of ambiguity related to timber yield and carbon parameters, and vagueness of policy targets (economic returns, timber production and carbon-uptake), ordinal measures of uncertainty are applied. While ordinality entails loss of precision, it makes it possible to solve complex problems. This paper compares land-use policies in the boreal forest zone of Northeastern British Columbia under uncertainty with those from a more typical scenario that applies best-guess parameter values. Including uncertainty explicitly into the possibility analysis changes optimal land-use and forest management, and leads to different levels of projected timber supply, economic performance and carbon sequestration. The amount of carbon dioxide (CO₂) removed from the atmosphere and the economic cost of carbon uptake are sensitive to how the decision-maker tackles uncertainty.     

Dependence of the Optimal Risk Control Decisions on the Terminal Value for a Financial Corporation

The paper deals with the model of a firm which has a possibility to choose among a variety of production/business policies with different risk and profit potential. The objective is to find the policy which maximizes the expected total discounted dividend pay-out until the time of bankruptcy. The bankruptcy is defined as the time when the liquid assets of the company vanish. A typical example of such a corporation would be an insurance company whose different business activities correspond to choosing different levels of reinsurance.The main novelty of this model is in introduction of terminal value of the company at the time of the bankruptcy. This could be the value of non liquid assets (such as real estate or the rights to conduct business or the trade name), which at the time of bankruptcy are subject to sale with proceeds distributed among shareholders. We model the dynamics of the corporate liquid assets as a diffusion process with controllable drift and diffusion coefficients. Diffusion coefficient corresponds to risk, while drift represents potential profit. In our model the potential profit proportional to the risk. The dividend distribution is modeled by an increasing functional, which is also controllable. We show how to obtain solution for this problem starting with the solution to the problem with zero terminal value.     

基于MIV-BP型网络实验的房地产项目风险识别研究

为了更准确更客观地识别房地产项目中的风险,为房地产项目投资决策提供科学依据和参考,有效地规避风险,本研究在BP神经网络 (Back-Propagation Neural Network)建模的基础上,采取MIV(Mean Impact Value)算法对BP神经网络模型进行变量筛选的网络优化和改良,从而形成新的优化后的MIV-BP(Mean Impact Value Back-Propagation Neural Network)神经网络,并以此用于评价房地产项目中的风险度以及各因素在风险度中的影响作用大小;同时选取目前相关的房地产项目数据进行仿真实证分析和验证。验证实验结果表明,MIV-BP型神经网络对于房地产项目风险度识别具有良好的适应性和准确性,实验结果客观,达到专家评价的要求,并在风险因素作用度分析上具有良好的应用价值。     

A combined evaluation model for encouraging entrepreneurship policies

Initiating small and medium enterprises (SMEs) has become a major issue around the globe. There are many governmental factors that could influence entrepreneurship. To create a strong and energetic environment for new businesses, governments need to develop a spirit of business, remove a number of current obstacles, and provide various supports during the start-ups periods. Here, a critical question arises: how can the government effectively evaluate current policies and how much effort must they put into improving these policies in order to achieve the desired level of economic growth? This paper addresses this question by proposing a combined Multi-Criteria Decision-Making (MCDM) model, which integrates the Analytic Network Process (ANP) approach and the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. The former approach is used to construct interrelations among criteria and to obtain criteria weights; the latter method allows the decision maker to realize policy gaps and to rank them in order of magnitude so that large gaps can be reduced to an aspired level. Overall, the study findings show at present, every entrepreneurships policy in Taiwan stands in need of improvement. The proposed model cannot only help the government to evaluate the relative effectiveness of their policies, but it also provides worthwhile recommendations toward the constructing of an ideal policy.     

房地产开发活动均衡分析与过度开发行为控制

在把房地产投资开发项目看作为一种具有弱再生性经济资源的基点上,对房地产投资开发活动进行了均衡分析,讨论了房地产开发活动中的最优平衡解及其相互之间的制约关系,分析了税收和配额价格等经济参数对最优平衡解的影响,给出了抑制房地产过度投资开发行为的控制模型与方法,并得出了相应的政策启示.这些研究结果,可以推广应用于其他各种可再生资源的投资开发与管理当中去,有着广泛的应用前景.     

Optimal risk probability for first passage models in semi-Markov decision processes

This paper studies the risk minimization problem in semi-Markov decision processes with denumerable states. The criterion to be optimized is the risk probability (or risk function) that a first passage time to some target set doesn't exceed a threshold value. We first characterize such risk functions and the corresponding optimal value function, and prove that the optimal value function satisfies the optimality equation by using a successive approximation technique. Then, we present some properties of optimal policies, and further give conditions for the existence of optimal policies. In addition, a value iteration algorithm and a policy improvement method for obtaining respectively the optimal value function and optimal policies are developed. Finally, two examples are given to illustrate the value iteration procedure and essential characterization of the risk function.     

基于实物期权定价方法的林业碳汇项目投资决策仿真研究

文章针对林业碳汇项目投资决策的复杂性、动态性和不确定性过程,利用林业—碳汇共同经营决策模型计算林业碳汇项目在投资期内的期望价值,采用实物期权定价方法对不同阶段不同策略下的林业碳汇项目价值进行评估,同时提出了多主体仿真建模方法,利用NetLogo仿真软件对林业碳汇项目投资决策过程进行动态模拟。仿真系统中涉及到的主体有林地、CO₂和投资者,投资者主要是作为观察者的身份,在不同阶段会做出不同的投资策略。模拟仿真三种不同状态下投资者的决策变化:一是传统林业投资动态模拟,不包含碳汇和期权因素动态模拟;二是引入碳汇市场后的林业投资动态模拟;三是引入碳汇市场和期权后林业投资动态模拟。NetLogo仿真分析结果表明引入碳汇市场可以提高投资者的收益并改变投资者的经营策略,同时引入期权,不仅增加了投资者的积极性而进行扩张投资,还可以更好地发挥林木碳汇功能,体现林业的生态价值及经济价值。     

Return Policy Model of Supply Chain Management for Single-Period Products

A return policy is one of the major issues in supply chain management, particularly for managing single-period products that are characterized with short sales period and little salvage value. The value of the buyback price is important to ensure a stable supply chain. The role of the risk attitude of the retailer and supplier is also known as an essential factor to the decision in determining a return policy. In this paper, we present the result of our investigation into this problem. The aim of our work is to develop a model to determine optimal return policies for single-period products based on uncertain market demands and in the presence of risk preferences. The impact of the wholesale price and selling price is also investigated to determine the optimal order quantities and optimal buyback price for different types of risk attitudes.     

Piecewise affine approximations for the control of a one-reservoir hydroelectric system

We analyze the computation of optimal and approximately optimal policies for a discrete-time model of a single reservoir whose discharges generate hydroelectric power. Inflows in successive periods are random variables. Revenue from hydroelectric production is represented by a piecewise linear function. We use the special structure of optimal policies, together with piecewise affine approximations of the optimal return functions at each stage of dynamic programming, to decrease the computational effort by an order of magnitude compared with ordinary value iteration. The method is then used to obtain easily computable lower and upper bounds on the value function of an optimal policy, and a policy whose value function is between the bounds.