Uncertainty aversion and farmers' innovative seed adoption:Evidence from a field experiment in rural China

Based on the microdata of 705 wheat farmers in the Loess Plateau, this study empirically analyzes the impact of uncertainty on farmers' adoption of innovative seeds using a field experiment. The results indicate that farmers are generally ambiguity-averse and risk-averse. In addition, farmers with higher ambiguity aversion and risk aversion are less likely to adopt innovative wheat seeds, where their risk aversion plays a dominant role. Enhancing information access will alleviate the negative influence of ambiguity aversion on farmers' adoption of innovative seeds, and interlinked insurance and credit contracts will be beneficial to ease the adverse effect of risk aversion on the adoption of innovative wheat seeds. Meanwhile, heterogeneity analysis reveals that the inhibitory effects of ambiguity aversion and risk aversion on innovative seed adoption are more significant among farmers with lower education and household income.The government can establish both ex-ante and ex-post relevant guarantee mechanisms to help farmers preferably cope with various uncertainties in the production process, remitting farmers' ambiguity aversion and risk aversion to enhance new agricultural technology adoption rates.

Applications of the Aversion Order of Risks in Reinsurance

The aversion order is a way of ordering of risks. Is there the optimal in aversion order in reinsurance contracts of reinsurance？ This paper discusses these objects and gives some optimal reinsurance contracts in certain sets of feasible reinsurance contracts.

Value-at-risk under ambiguity aversion

This study explored the effects of ambiguity on the calculation of Value-at-Risk(VaR)using a mathematical model based on the theory of Choquet-Brownian processes.It was found that while a moderate degree of ambiguity aversion yields a higher value for VaR and Expected Shortfall(ES),the result can be reversed in a deeply ambiguous environment.Additionally,some sufficient conditions are provided for the preservation of this effect under various forms of risk aggregation.This study offers a new perspective to full awareness on capital requirement calculation as requested by international regulation.

Some Likelihood Based Properties in Large Samples: Utility and Risk Aversion, Second Order Prior Selection and Posterior Density Stability

The likelihood function plays a central role in statistical analysis in relation to information, from both frequentist and Bayesian perspectives. In large samples several new properties of the likelihood in relation to information are developed here. The Arrow-Pratt absolute risk aversion measure is shown to be related to the Cramer-Rao Information bound. The derivative of the log-likelihood function is seen to provide a measure of information related stability for the Bayesian posterior density. As well, information similar prior densities can be defined reflecting the central role of likelihood in the Bayes learning paradigm.

The risk aversion measures in Architectural Engineering Project Management

With the continuous development of the construction industry, the scale and volume of the construction project is expanding. And the project management of the construction project still has the big risk problem which influenced by many factors. These risks will not only bring unnecessary interference to the construction of the project, but also may jeopardize the safety of people＇s life and property. It is the focus of this article to do a good job in risk aversion in the management of construction projects.

Systematic Reform and Risk Aversion in the Interregional Flow of Chinese Rural Labor Force --Wuhan Case Study

Based on Wuhan city investigation, this paper makes a positive analysis to the uncertainty of shifting rural labors to urban areas, and put forward thoughts and countermeasures to avert the risk of the interregional flow of rural labors.

Time-varying impact of political risk on copper prices

Using the International Country Risk Guide(ICRG)index to represent countries’political risk,the time-varying effect of political risk on copper prices was examined based on the time-varying parameter structural vector autoregression with stochastic volatility(TVP-SVAR-SV)model.The empirical results show that the impact of political risk on copper prices is time-varying and has tended to increase gradually in recent years.There are significant country-level differences in the impact of political risk on copper prices.Political risk has a stronger and longer-lasting impact on copper prices in exporting countries.In terms of risk sources,external and internal conflicts contribute most to international copper price fluctuations in the sample period.The impact of political risk on copper prices reaches an extreme level during the international financial crisis,the European debt crisis,and the election of Donald Trump.

Optimal Portfolio Selection of Wind Power Plants Using a Stochastic Risk-Averse Optimization Model, Considering the Wind Complementarity of the Sites and a Budget Constraint

This work focuses on the best financial resources allocation to define a wind power plant portfolio, considering a set of feasible sites. To accomplish the problem formulation and solution, the first step was to establish a long-term wind series reconstruction methodology for generating scenarios of wind energy, applying it to study five different locations of the Brazilian territory. Secondly, a risk-averse stochastic optimization model was implemented and used to define the optimal wind power plant selection that maximizes the portfolio financial results, considering an investment budget constraint. In a sequence, a case study was developed to illustrate a practical situation of applying the methodology to the portfolio selection problem, considering five wind power plants options. The case study was supported by the proposed optimization model, using the scenarios of generation created by the reconstruction methodology. The obtained results show the model performance in terms of defining the best financial resources allocation considering the effect of the complementarity between sites, making it feasible to select the optimal set of wind power plants, characterizing a wind plant optimal portfolio that takes into account the budget constraint. The adopted methodology makes it possible to realize that the diversification of the portfolio depends on the investor risk aversion. Although applied to the Brazilian case, this model can be customized to solve a similar problem worldwide.

农村成长经历会影响城镇家庭储蓄率吗?——来自CHFS 2019的经验证据

由于城市与农村的经济金融环境存在显著差异,成年前在农村成长的城镇居民比在城市成长的城镇居民具有较高的风险厌恶程度和较低的金融知识水平,从而更加偏向低消费和高储蓄。采用中国家庭金融调查(CHFS)2019年数据,将“目前居住在城市地区且拥有非农业户口、18岁之前为农业户口”作为“拥有农村成长经历”的界定标准,实证检验城镇家庭户主的农村成长经历对其家庭储蓄率的影响,结果表明:户主拥有农村成长经历的城镇家庭比户主没有农村成长经历的城镇家庭有更高的储蓄率,风险态度和金融素养在其中发挥了中介作用,即拥有农村成长经历的户主会因较高的风险厌恶程度和较低的金融知识水平而导致其家庭储蓄率较高;农村成长经历对储蓄率的正向影响在户主受教育水平较高、家庭资产较少、经济发展水平较低地区(中西部地区)的家庭中更为显著。因此,需要从改善城市的经济金融状况(降低生活成本、增强社会保障、减少不确定性等)入手来释放城镇居民的消费需求,并通过改善风险态度、加强金融教育、缩小城乡差距等渠道来降低农村成长经历对城镇家庭储蓄率的正向影响。

基于条件风险价值的虚拟电厂参与能量及备用市场的双层随机优化

为充分发挥虚拟电厂的灵活性价值,提出了虚拟电厂参与电能量及备用辅助服务市场的双层随机优化模型。上层基于条件风险价值理论建立了虚拟电厂参与电能量及备用辅助服务市场的两阶段风险决策模型,其中,第一阶段考虑新能源不确定性的潜在风险,建立了虚拟电厂参与能量和备用辅助服务市场的投标报价模型,第二阶段针对不同场景下的新能源出力建立了以虚拟电厂期望运行成本最小为目标的分布式资源优化调度模型;下层在已知各市场主体的投标报价信息后,开展电能量市场及备用辅助服务市场的联合出清。仿真分析表明,所提方法能够有效指导虚拟电厂规避新能源不确定性的潜在风险,并通过将备用价格提高到下一个边际机组的报价从而增加自身利润。

消费者风险厌恶的运费险分担机制与供应链定价研究

考虑消费者的退货行为、风险厌恶态度和运费险价值敏感,建立零售商承担、消费者承担、零售商与消费者共同承担、零售商与制造商共同承担4种不同运费险承担方式的Stackelberg价格博弈模型,研究供应链的定价决策和在线零售商的最优退货运费险策略。研究表明:低退货率和高运费险敏感性有助于提高供应链的整体利润;低退货率时,在线零售商主动为消费者购买运费险优于消费者自行购买;运费险的分担机制不能实现供应链协调。

考虑消费者风险规避的供应链退货运费险与定价策略

针对线上买卖双方的退货运费承担纠纷,电商平台引入退货运费险来分摊商品退货风险,但宽松的退货政策又增加了消费者的退货行为。为此,将第三方保险公司引入制造商主导和网络零售商跟随的斯坦克尔伯格博弈中,考虑风险规避型消费者的退货行为和运费险敏感性,建立多方决策主体共同参与的卖家运费险、买家运费险和运费险共同分担等3种定价退货模型,研究网络零售商的定价决策和运费险策略。结果表明:消费者的风险规避态度有助于降低商品售价和运费险价格,提高市场需求和企业利润;运费险共同分担机制能够有效缓解客户流失;退货率较低时,消费者的运费险偏好有利于供应链总利润的增长。

基于信息不对称与风险规避的低碳闭环供应链定价决策研究

为确定闭环供应链的产品定价和碳减排率,同时考虑制造商的风险规避行为和零售回收运营成本信息的不对称性,构建以制造商为主导的Stackelberg博弈模型,分析对比信息对称和信息不对称两种情况下的最优决策,利用数值分析验证结论。研究表明:产品的销售价格、批发价格、碳减排率及制造商效用都将随着制造商风险规避程度的提高而降低,而市场需求与零售商效用将增加;当零售商谎报回收运营成本时,相较于坦白回收运营成本,产品转移价格与零售商效用均有所提升,产品回收价格、废旧产品回收量和制造商效用则降低,且风险规避和信息不对称均对碳减排产生消极影响。

供应中断下考虑风险规避的供应链采购决策

针对由一个零售商与两个供应商构成的两级供应链,讨论供应中断时采购量由需求函数分配或按比例分配两种不同情形下的考虑风险规避的供应链采购与定价决策。结果表明:零售商的采购量随中断风险的下降而减少,对供应能力较弱的供应商更敏感;供应商的定价决策更受竞争对手供应能力的影响。预先采购分配、额定比例的设置均会扰乱供应商定价,从而降低零售商的收益且不利于供应商提高自身供货能力的积极性;零售商的采购量会随风险规避系数的升高而增加,由此造成的自身囤货以及供应商抬价行为均会大幅降低零售商期望收益。研究结果可为真实市场中零售商面对供应中断风险时如何进行采购决策提供管理启示。

服务水平约束下基于看跌期权的风险规避零售商决策研究

针对消费电子行业需求不确定导致下游对新产品订货疲软的问题,本文在风险中性制造商和风险规避零售商之间设计了看跌期权契约,同时考虑服务水平约束的限制。通过比较以探讨看跌期权契约是否能激励风险规避零售商增加订货,并分析了零售商风险规避系数、服务水平约束和看跌期权契约参数对零售商决策和相关成员利润的影响。结果发现:零售商风险规避程度的增加会抑制其最优初始订单量的增加,但对制造商的期望利润存在正面影响;高服务水平有利于增加零售商的最优初始订单量和制造商的期望利润,但不利于增大零售商的最大条件风险值;看跌期权契约的存在对供应链成员均有好处。

风险规避下考虑碳期货的工程机械再制造企业生产决策研究

在碳限额与交易政策下,研究碳期货对风险规避型工程机械再制造企业生产决策的影响。分别构建无碳期货情形和考虑碳期货情形下风险规避型再制造企业的生产决策模型;利用Kuhn-Tucker条件对模型求解,比较两种情形下的最优解;通过算例分析碳期货和风险规避系数对产量、企业效用、消费者剩余和碳排放总量的影响。研究表明,在企业风险规避程度较高情形下,引入碳期货总是会增加新品产量和总产量,而再制品产量,在完全再制造策略下随之增加,部分再制造策略下随之减少。此外,企业风险规避程度较高时,考虑碳期货情形下的企业效用、消费者剩余和碳排放总量均高于不考虑碳期货情形。

政府补贴下考虑风险厌恶的双渠道绿色供应链运营决策及协调契约

在政府对绿色产品提供补贴的基础上,构建以制造商为主导的供应链博弈模型,利用均值方差法分析了在双方风险中性(RN)、双方风险厌恶(RA)、仅制造商风险厌恶(MRA)和仅零售商风险厌恶(RRA)4种模式下的双渠道绿色供应链决策及效用,并设计带有转移支付的成本分担契约以实现协调。研究发现:在RRA模式下,产品绿色度与风险厌恶程度正相关;而在MRA模式和RA模式下,产品绿色度与风险厌恶程度负相关;双方效用在4种模式下均与政府补贴正相关,且在RRA模式下制造商效用受政府补贴的影响最为显著;当研发成本系数较大时,在MRA模式和RRA模式下,一方的效用与另一方的风险厌恶程度正相关,而在RA模式下双方效用与风险厌恶程度负相关。此外,通过数值分析揭示了成本分担比例与风险厌恶程度负相关、与政府补贴正相关。以上结论可为双渠道绿色供应链的决策制定及协调管理提供参考。

产能约束下考虑风险规避的双渠道供应链决策研究

以一个产能约束制造商和一个零售商组成的两阶段双渠道供应链为对象,研究了制造商占主导地位且考虑风险规避时,随机需求下的供应链成员的决策与协调问题。构建供应链成员在集中决策和分散决策两种情形下的决策模型,并比较分析两种情形下产能约束、风险规避系数对供应链决策影响。研究结果表明:两种决策情形下,成员定价结果均与制造商风险规避呈负相关;由制造商主导的线上渠道的定价与决策情形无关;两种决策情形下,制造商产能均与风险规避系数呈正相关,且渠道偏好均对供应链收益起促进作用。

考虑消费者双重行为的农产品绿色供应链数字化策略

为探究消费者风险规避和绿色偏好行为对绿色供应链数字化发展的双重影响,构建产品绿色度和安全水平函数,运用Stackelberg博弈模型,构建农户和农产品零售商组成的两级绿色供应链博弈模型,分析两种行为对绿色供应链数字化策略的影响,对集中决策和分散决策下供应链成员决策进行对比分析,并设计考虑奖惩的供应链契约。最后对模型进行数值仿真,验证该契约的可行性。研究发现:无论是集中决策还是分散决策,消费者规避心理总不利于绿色供应链发展,绿色偏好与之相反;相比分散决策,集中决策最优解更优;奖惩系数在合理的区间内,考虑奖惩的农产品供应链契约实现了供应链参与者的双赢,农户和农产品零售商利润均得到帕累托改善。

数字政府大模型的自主性能力与风险规避

生成式人工智能技术是构建数字政府大模型的核心,可以辅助政府实现数据与模型算法驱动的政府治理现代化。在自主性技术理论视角下,数字政府大模型具有完整的数据自主性、学习自主性、决策自主性与服务自主性四种能力指向,分别表现为治理路径映射关系的重塑、知识结构适应性逻辑的优化、机器理性科学性趋向的重造与供给模式精细化结构的重组。然而,生成式人工智能的自主性也会导致数字政府大模型面临技术监管与引导主动性缺失的模型梦游、依赖与欲望内生性增长的模型命令、扭曲与定式反向性塑造的模型适应、偏见与歧视自主性扩张的模型无意识等自主性风险。因此,迫切需要加强对数字政府大模型的全生命周期监管,提升政务用户的大模型识读能力,科学设置政府大模型与政务业务的边界,构建政务数字化协同互动的生态体系以规避实践中可能产生的自主性风险,提高数字政府大模型的综合效能。