Welfare Cost of Model Uncertainty in a Small Open Economy

This paper extends the canonical small open-economy real-business-cycle model, when considering model uncertainty. Domestic households have multiplier preferences, which leads them to take robust decisions in response to possible model misspecification for the economy’s aggregate productivity. Using perturbation methods, the paper extends the literature on real business cycle models by deriving a closed-form solution for the combined welfare effect of the two sources of uncertainty, namely risk and model uncertainty. While classical risk has an ambiguous effect on welfare, the addition of model uncertainty is unambiguously welfare-deteriorating. Hence, the overall effect of uncertainty on welfare is ambiguous, depending on consumers preferences and model parameters. The paper provides numerical results for the welfare effects of uncertainty measured by units of consumption equivalence. At moderate (high) levels of risk aversion, the effect of risk on household welfare is positive (negative). The addition of model uncertainty—for all levels of concern about model uncertainty and most risk aversion values—turns the overall effect of uncertainty on household welfare negative. It is important to remark that the analytical decomposition and combination of the effects of the two types of uncertainty considered here and the resulting ambiguous effect on overall welfare have not been derived in the previous literature on small open economies.     

基于不同社会责任承担模式的闭环供应链决策研究

供应链成员企业对不同社会责任承担模式有自己的偏好选择,探讨供应链成员企业承担的社会责任对供应链决策的影响.对于可能的任何一种社会责任承担模式,企业承担社会责任均会使产品销售价格降低、需求量增加、回收量增加.承担企业社会责任虽然会使自身收益减少,但其他成员和系统的收益却会增加,有利于增加消费者剩余,实现社会福利最大化.当承担的社会责任程度较大时,供应链成员企业能保持长期合作关系,使供应链正常运行.当承担的社会责任程度都较小时,由于供应链成员企业之间对社会责任承担模式的偏好存在矛盾将难以维持供应链合作,最终会导致供应链断链.     

Interpretable Multi-Head Self-Attention Architecture for Sarcasm Detection in Social Media

With the online presence of more than half the world population, social media plays a very important role in the lives of individuals as well as businesses alike. Social media enables businesses to advertise their products, build brand value, and reach out to their customers. To leverage these social media platforms, it is important for businesses to process customer feedback in the form of posts and tweets. Sentiment analysis is the process of identifying the emotion, either positive, negative or neutral, associated with these social media texts. The presence of sarcasm in texts is the main hindrance in the performance of sentiment analysis. Sarcasm is a linguistic expression often used to communicate the opposite of what is said, usually something that is very unpleasant, with an intention to insult or ridicule. Inherent ambiguity in sarcastic expressions make sarcasm detection very difficult. In this work, we focus on detecting sarcasm in textual conversations from various social networking platforms and online media. To this end, we develop an interpretable deep learning model using multi-head self-attention and gated recurrent units. The multi-head self-attention module aids in identifying crucial sarcastic cue-words from the input, and the recurrent units learn long-range dependencies between these cue-words to better classify the input text. We show the effectiveness of our approach by achieving state-of-the-art results on multiple datasets from social networking platforms and online media. Models trained using our proposed approach are easily interpretable and enable identifying sarcastic cues in the input text which contribute to the final classification score. We visualize the learned attention weights on a few sample input texts to showcase the effectiveness and interpretability of our model.     

TIMBER MARKETS AND FUEL TREATMENTS IN THE WESTERN U.S.

ABSTRACT. We developed a model of interrelated timber markets in the U.S. West to assess the impacts of large‐scale fuel reduction programs on these markets, and concomitant effects ofthe market on the fuel reduction programs. The linear programming spatial equilibrium model allows interstate and international trade with western Canada and the rest of the world, while accounting for price effects of introducing softwood logs to the market. The model maximizes area treated, given fire regime‐condition class priorities, maximum increases in softwood processing capacity, maximum rates of annual treatments, prohibitions on exports of U.S. and Canadian softwood logs from public lands and a fixed annual treatment budget. Results show that the loss to U.S. private timber producers is less than the gains for timber consumers (mills). States receiving more treatments when spending is not constrained by state proportions include Idaho, Montana, New Mexico and Oregon. When only the wildland‐urban interface is treated, California, Oregon and Washington receive more treatments. Utah and Colorado receive more treatments when low risk stands are included.     

On the structure of competitive societies

We model the dynamics of social structure by a simple interacting particle system. The social standing of an individual agent is represented by an integer-valued fitness that changes via two offsetting processes. When two agents interact one advances: the fitter with probability p and the less fit with probability 1-p. The fitness of an agent may also decline with rate r. From a scaling analysis of the underlying master equations for the fitness distribution of the population, we find four distinct social structures as a function of the governing parameters p and r. These include: (i) a static lower-class society where all agents have finite fitness; (ii) an upwardly-mobile middle-class society; (iii) a hierarchical society where a finite fraction of the population belongs to a middle class and a complementary fraction to the lower class; (iv) an egalitarian society where all agents are upwardly mobile and have nearly the same fitness. We determine the basic features of the fitness distributions in these four phases.     

对具有从属关系的社会选择函数进一步的探讨

分析了Hattori给出的三个条件的合理性，并建立了一个仅满足非限制域条件而不满足存在一个独裁与无关个人影响力独立性条件的具有从属关系的社会选择函数，使具有从属关系的社会选择函数族更加完备。