How does the effect of pre-play suggestions vary with group size? Experimental evidence from a threshold public-good game

Numerous studies have examined factors influencing the likelihood of cooperative outcomes in nonzero-sum games, but there has been little study of the interaction between two of the most important: group size and pre-play cheap talk. We report results from an experiment in which groups of size between 2 and 15 play a one-shot multi-player threshold public-good game. In our random leader treatment, all group members select a suggestion (e.g., “Everyone should choose X”), with one randomly chosen to be broadcast to the group. In a choice only treatment, subjects choose suggestions but none is sent, and in a baseline treatment, there are no suggestions at all. We find a negative interaction between group size and this kind of communication: the beneficial effect of both suggestions overall and cooperative suggestions on cooperation, cooperative outcomes, and payoffs decreases sharply as the group size increases. We find a similar negative interaction in a follow-up treatment in which all group members’ suggestions are broadcast to the group. Our results suggest that care should be taken in generalising conclusions from small-group experiments to large groups.     

乡村振兴战略下农村产业融合、人力资本与农民增收*——以浙江省为例

［目的］乡村振兴战略是贯彻新发展理念，建设现代化经济强国的重大战略之一。农村产业兴旺，农民生活富裕是乡村振兴战略的重要目标。农村一、二、三产业融合发展是实现乡村产业振兴，农民增收的重要途径。农村人力资本状况关系到农村产业融合的人才建设，关系到农民增收的实现。文章力图探究乡村振兴战略下农村产业融合、人力资本与农民增收间的相互作用关系，以期为乡村振兴战略的实现提供政策建议。［方法］以浙江省为例进行实证分析，通过建立PVAR模型，采用格兰杰因果关系及面板数据模型进行检验。［结果］农村产业融合及人力资本构成农民增收的格兰杰因果关系，两者都对农民增收产生显著影响，且人力资本影响效应更大。农民增收及人力资本对农村产业融合没有起到相应的促进作用。［结论］在实证分析的基础上，从加大人力资本投入、培育农村产业融合复合型人才及加强宣传引导工作等方面提出相应的政策建议促进农村产业融合。     

城市造林工程农户行为意向影响因素研究——以北京市平原造林工程为例

以北京市平原造林工程为例,利用典型项目区调查数据建立结构方程模型,探讨影响退耕农户行为意向的主要因素。结果表明:农户综合素质、家庭经济基础和农户土地依赖性对农户满意度和农户行为意向具有显著正向影响;同时,农户综合素质、家庭经济基础和农户土地依赖性还会通过农户满意度对农户行为意向产生影响。据此,后续城市造林过程中应进一步加强对农户满意度的服务工作,同时根据个体农户特征,对被征地农户在再就业、技能培训、农地补偿等方面开展更具针对性的服务工作。     

Dynamic decision and coordination in a low-carbon supply chain considering the retailer's social preference

We establish dynamic game models in a low-carbon supply chain consisting of a single manufacturer and a single retailer with social preference. This study investigates the complex dynamic characteristics of pricing decision and carbon abatement strategy in the supply chain and focuses on the impact of the retailer's social preference on pricing decision, carbon emission abatement strategy, profits, supply chain coordination, and complexity of dynamic models. We find that adjustment parameters of pricing and carbon emission abatement should be maintained in a certain range; otherwise, the system will be unstable and even chaotic through period double bifurcation or wave shape chaos. A higher social preference of the retailer is always beneficial to carbon abatement and the manufacturer and helps maintain the stability of the supply chain system. However, the impact on the long-term profitability of the supply chain is related to the state of the system. Compared with the setting of a centralized decision, the optimal carbon abatement strategy and supply chain profit in a decentralized decision are always less than those in a centralized setting, regardless of whether the retailer has social preference. Therefore, a side-payment self-executing contract is designed to coordinate the supply chain and achieve Pareto improvement. The coordination mechanism proposed in this study not only leads to Pareto improvement but also increases the stability of the supply chain system. Finally, this study enlightens management in operating a low-carbon supply chain.     

Nowcasting and forecasting GDP in emerging markets using global financial and macroeconomic diffusion indexes

This paper contributes to the nascent literature on nowcasting and forecasting GDP in emerging market economies using big data methods. This is done by analyzing the usefulness of various dimension-reduction, machine learning and shrinkage methods, including sparse principal component analysis (SPCA), the elastic net, the least absolute shrinkage operator, and least angle regression when constructing predictions using latent global macroeconomic and financial factors (diffusion indexes) in a dynamic factor model (DFM). We also utilize a judgmental dimension-reduction method called the Bloomberg Relevance Index (BRI), which is an index that assigns a measure of importance to each variable in a dataset depending on the variable’s usage by market participants. Our empirical analysis shows that, when specified using dimension-reduction methods (particularly BRI and SPCA), DFMs yield superior predictions relative to both benchmark linear econometric models and simple DFMs. Moreover, global financial and macroeconomic (business cycle) diffusion indexes constructed using targeted predictors are found to be important in four of the five emerging market economies that we study (Brazil, Mexico, South Africa, and Turkey). These findings point to the importance of spillover effects across emerging market economies, and underscore the significance of characterizing such linkages parsimoniously when utilizing high-dimensional global datasets.     

Optimal dividend strategies with time-inconsistent preferences

This paper studies the optimal dividend strategies of an insurance company when the manager has time-inconsistent preferences. We consider the problem for a naive manager and a sophisticated manager, and analytically derive the optimal dividend strategies when claim sizes follow an exponential distribution. Our results show that the manager with time-inconsistent preferences tends to pay out dividends earlier than her time-consistent counterpart and that the sophisticated manager is more inclined to pay out dividends than the naive manager. Furthermore, we extend these results to the case with claim sizes following a mixed exponential distribution, and provide a numerical analysis to reveal the sensitivity of the optimal dividend strategies to changes in the premium, claims and surplus volatility.     

职业技能培训对农民阶层地位获得影响的实证研究

我国在由计划经济向社会主义市场经济转型的过程中,个人自致性因素对阶层地位获得的影响日益突出。在众多的个人自致性因素中,职业技能培训是最重要的个人自致性因素之一,其对阶层地位获得发挥着举足轻重的作用。笔者通过实证研究证实：职业技能培训对农民阶层地位的获得存在显著影响。为了更好地推进农民的职业技能培训,一方面要充分发挥政府、企业、社会组织和农民个人等各个方面在农民职业技能培训中的作用,建立社会协同培训的格局;另一方面,在开展农民职业技能培训内容的设计和实施时,必须充分考虑到不同培训对象的不同需求,增加职业技能培训的针对性。     

基于实验人文地理学的旅游目的地选择行为研究

文章基于实验经济学和计算机实验人文地理学的方法思想,以旅游目的地选择行为研究为案例。首先设定研究目标,进而提出了实验的前提假设。采用地理信息科学和网络服务技术,构建旅游目的地选择行为实验平台,展开实例研究,研究结果表明:(1)进行大尺度旅游目的地选择时,被试者表现出不断追求旅游效益最大化这一目标,且与旅游目的地的资源类型无关。(2)被试者经过一定实验学习后,总体上呈现出不断追求个人收益最大化的趋势。然而,有些情况下,也可能出现决策失误。案例研究的成功进一步表明,实验人文地理学思想方法和研究手段对于典型人文地理学问题进行研究是可行的。文章为正在发展的实验人文地理学发展提供了案例指导。     

新型煤炭企业物资供应人才内涵与选用标准

介绍了新型煤炭企业物资供应人才的内涵,构建了安全效益、经济效益和管理效益3个维度;分析了选用新型煤炭企业物资供应人才的3大标准,提出了从道德品质、素质能力、态度观念等方面着手的观点,对实践具有重要指导和参照意义。     

An information-theoretic approach for forecasting interval-valued SP500 daily returns

We develop an iterative and efficient information-theoretic estimator for forecasting interval-valued data, and use our estimator to forecast the SP500 returns up to five days ahead using moving windows. Our forecasts are based on 13 years of data. We show that our estimator is superior to its competitors under all of the common criteria that are used to evaluate forecasts of interval data. Our approach differs from other methods that are used to forecast interval data in two major ways. First, rather than applying the more traditional methods that use only certain moments of the intervals in the estimation process, our estimator uses the complete sample information. Second, our method simultaneously selects the model (or models) and infers the model’s parameters. It is an iterative approach that imposes minimal structure and statistical assumptions.