Are actual weather and perceived weather the same? Understanding perceptions of local weather and their effects on risk perceptions of global warming

I use one nationally representative sample from CBS News/New York Times Poll on Environment (2007), supplemented with monthly temperature and precipitation data from the United States Historical Climatology Network and extreme weather events data from National Climatic Data Center, to examine how different weather measures and individuals’ socio-demographic background, political predisposition, and beliefs about global warming affect the perception of local weather. Beliefs about global warming are found to play a dominant role in determining the perception of local weather. Specifically, people who view that global warming is causing an immediate impact, is serious, and needs to be a priority are much more likely to perceive a strange pattern of weather in the recent past. This finding conforms to motivated reasoning which refers to the tendency to interpret evidence to confirm the preexisting beliefs and predisposition. Among all the weather measures, the total number of extreme weather events in the past three years appears to be the only significant indicator of perceived weather. Specifically, individuals who have experienced more extreme weather events in their home counties are more likely than those elsewhere to perceive the weather is stranger than usual. I further examine how actual weather and perceived weather together affect perceptions of global warming. The results illustrate that the perception of local weather has stronger explanatory power than actual weather. People who perceive the strange weather patterns are much more likely than others to see the immediate impacts and priority of global warming. Future studies are needed to investigate the dynamic relationship between perceptions of global warming and perceptions of weather and climate. In addition, more studies are needed to further examine how the public forms their opinions toward various specific types of the local weather and climate.     

Probability Forecasts of Macroaggregates in the Turkish Economy

We provide probability forecasts of key Turkish macroeconomic variables such as inflation and output growth. The probability forecasts are derived from a core vector error correction model of the Turkish economy and its several variants. We use model and window averaging to address uncertainties arising from estimated models and possible structural breaks. The performances of the different models and their combinations are evaluated using relevant forecast accuracy tests in different pseudo out-of-sample settings. The results indicate that successful directional forecasts can be obtained for output growth and inflation. Averaging over both the models and the estimation windows improves the level of accuracy of the forecasts.     

The role of multivariate skew-Student density in the estimation of stock market crashes

By combining the multivariate skew-Student density with a time-varying correlation GARCH (TVC-GARCH) model, this paper investigates the spread of crashes in the regional stock markets. The regional index series of European, USA, Latin American and Asian markets are modeled jointly, and the maximum likelihood estimates show that a TVC-GARCH model with multivariate skew-Student density outperforms that with multivariate normal density substantially. Depending on the past information set, the conditional 1-day crash probabilities are computed, and the forecast performances of the TVC-GARCH model with both multivariate skew-Student and normal densities are evaluated. In both bilateral and global environments, multivariate skew-Student density has better predictive accuracy than normal density. In global crash probability forecasts, multivariate skew-Student density attains much higher hit rate and Kuipers score than multivariate normal density, thus it can be used to improve early-warning systems.     

供应商集中度影响管理层业绩预告行为吗？——基于业绩预告精确性及其预告态度的视角

基于中国企业间关系信任的历史禀赋与现实情境,以2010-2017年A股公司业绩预告为样本,考察供应商集中度对业绩预告精确性与预告态度的影响。研究发现：供应商集中度越高,管理层业绩预告的精确性越低,预告态度也越倾向乐观。进一步研究发现：供应商集中度对业绩预告的精确性负向影响在业绩预告修正情况下作用更明显,在业绩预告未修正时企业更倾向于乐观的业绩预告;同时企业在自愿披露业绩预告情况下,供应商集中度对业绩预告精确性的反向作用更为显著,企业越倾向于披露乐观的业绩预告。以上研究为理解外部利益相关者与企业未来盈利预测之间的关系提供了直接的经验证据,丰富和拓展了供应商关系型交易影响企业信息披露策略选择的研究。     

金融状况指数显示：经济低位增长，物价相对平稳

金融状况指数（FCI）是基于货币价格和资产价格等变量编制的综合性指标,以弥补货币供应量、利率等传统指标的不足。文章选取货币供应量、利率、汇率、股票指数和房地产价格等指标,采用主成分分析方法构建FCI。结果显示,从FCI本身的走势看,目前处在下行态势,低于近十年的平均值;从其领先经济指标的性质判断,未来经济增长将低位平稳运行,物价上行压力不大。     

风险偏好、监管强度与金融监管有效性——基于委托代理理论的博弈分析

监管博弈过程中不同参与主体的风险偏好影响其有效性,对不同经营效率的金融机构监管的有效性也有差异。监管机构宜引入审核和惩罚等机制,提高监管强度,提升金融监管有效性。对高效率金融机构,监管机构宜采取原则导向的监管,给予更多的自主权,激发其竞争力和活力;对低效率金融机构,应采取规则导向的监管。同时,监管行为可更具灵活性,根据不同的风险偏好采取不同对策。     

基于ARIMA模型预测我国2012年的货运量

本文的数据来源于《新中国60年统计资料汇编》、中华人民共和国国家统计局,根据《新中国60年统计资料汇编》里面0146.xls中1949-2008年全国货运量的数据、中华人民共和国国家统计局中2009、2010年月度与年度货运量数据,建立时间序列模型序列,运用ARIMA模型进行分析,主要包括时间序列分析、平稳化处理、模型的识别、模型的定阶和参数估计这四个主要步骤,运用Eviews6.0软件,对我国2011年和2012年的货运量进行了预测,为制定物流发展政策、确定物流基础设施建设规模、分析物流市场态势提供定量依据。     

基于交易三阶段的电子商务卖家信用评价模型研究

基于电子商务交易整体流程,分别总结电子商务交易前、交易中、交易后三阶段信用评价影响因素,利用因子分析法提取各阶段信用评价因子以及相应权重,得到基于交易三阶段的电子商务信用评价模型。通过代入案例数值将得到的电子商务信用评价模型与现有电子商务购物平台信用评价模型进行对比分析,其结果证明基于交易三阶段的电子商务信用评价模型更具有真实性及区分度,信用值计算方法更全面,对于现有电子商务信用评价方法的改进方面有一定的参考价值。     

中国货币政策效果区域不对称性探讨

探讨中国货币政策效果的区域差异对于研究完善货币政策传导机制具有较强的实践意义。文章通过数据的聚类分析和模型设计对中国货币政策效果的区域差异进行了实证分析,结果显示东部地区的传导效果最为显著。对此文章阐述了地区差异的形成原因,并提出了相应的治理方法。     

Bayesian comparison of several continuous time models of the Australian short rate

This paper provides an empirical analysis of a range of alternative single‐factor continuous time models for the Australian short‐term interest rate. The models are nested in a general single‐factor diffusion process for the short rate, with each alternative model indexed by the level effect parameter for the volatility. The inferential approach adopted is Bayesian, with estimation of the models proceeding through a Markov chain Monte Carlo simulation scheme. Discrimination between the alternative models is based on Bayes factors. A data augmentation approach is used to improve the accuracy of the discrete time approximation of the continuous time models. An empirical investigation is conducted using weekly observations on the Australian 90 day interest rate from January 1990 to July 2000. The Bayes factors indicate that the square root diffusion model has the highest posterior probability of all models considered.     

La loi de Pareto et la réassurance

Abstract

Nous allons étudier l'influence de la distribution des sommes assurées sur Ie risque mathématique d'une compagnie. Qu'il soit permis de développer tout d'abord notre vue générule sur Ie probleme du risque.     

公平信息披露与分析师预测精度——来自中国上市公司的经验证据

证券分析师是证券市场重要的信息加工者和传播者,他们的信息行为对中小投资者和市场效率有重要影响。本文基于2003~2009年分析师的年度盈利预测数据,运用面板计量模型实证检验了公平信息披露规则的实施对分析师预测精度的影响。研究结果表明:分析师预测精度在规则实施后显著下降了;而且,随着规则实施时间的推移,分析师预测精度进一步下降;另外,分析师对信息披露水平较差的上市公司的预测精度下降幅度更大。     

农业自然风险的金融管理：天气衍生品的兴起

天气衍生品是农业保险创新的产物，它将金融工具的理念用于自然灾害的风险管理，为农业生产者的风险转移提供了新途径。天气衍生品的推出可以增强保险公司和再保险公司分散风险的能力，有助于提高农业自然风险的管理水平。本文介绍了全球天气衍生品发展的产品与市场状况，并提出了相关的政策建议。     

我国财政支出结构的实证分析

基于2006-2011年我国31个省份一般财政支出数据,运用因子分析方法对我国不同时期各地的财政支出结构进行实证分析。结果发现：第一,一般公共服务、国防、公共安全、教育和科学技术等13个不同支出项目可以通过＂偏高级经济技术＂、＂偏社会保障服务＂、＂偏基本设施建设＂较好地反映;第二,地方政府活动的范围和方向以高级经济技术为中心,但逐渐转变为以基本设施建设为中心,后来又转变偏社会保障服务,充分反映不同时期政府政策的重点。最后,笔者分别从财政政策、政府管理模式、财政赤字、税收政策四个角度阐述这一财政支出变化的原因。