Asymmetric Forecast Densities for U.S. Macroeconomic Variables from a Gaussian Copula Model of Cross-Sectional and Serial Dependence

Most existing reduced-form macroeconomic multivariate time series models employ elliptical disturbances, so that the forecast densities produced are symmetric. In this article, we use a copula model with asymmetric margins to produce forecast densities with the scope for severe departures from symmetry. Empirical and skew t distributions are employed for the margins, and a high-dimensional Gaussian copula is used to jointly capture cross-sectional and (multivariate) serial dependence. The copula parameter matrix is given by the correlation matrix of a latent stationary and Markov vector autoregression (VAR). We show that the likelihood can be evaluated efficiently using the unique partial correlations, and estimate the copula using Bayesian methods. We examine the forecasting performance of the model for four U.S. macroeconomic variables between 1975:Q1 and 2011:Q2 using quarterly real-time data. We find that the point and density forecasts from the copula model are competitive with those from a Bayesian VAR. During the recent recession the forecast densities exhibit substantial asymmetry, avoiding some of the pitfalls of the symmetric forecast densities from the Bayesian VAR. We show that the asymmetries in the predictive distributions of GDP growth and inflation are similar to those found in the probabilistic forecasts from the Survey of Professional Forecasters. Last, we find that unlike the linear VAR model, our fitted Gaussian copula models exhibit nonlinear dependencies between some macroeconomic variables. This article has online supplementary material.     

基于熵权法的财务危机预警指标选择研究

合理选择财务指标是财务危机预警研究中的重要内容,用定性和定量相结合的方法进行选择是科学有效的方法之一。首先根据初选原则对财务指标进行了初步选择,然后提出了一种基于熵权的变量选择方法,对初选的财务指标进行定量筛选,进行实证研究,最终确定了应用于财务危机预警的财务指标。     

基于灰色聚类的企业伦理能力评价研究

分析了企业伦理能力测度理论现状,提出了企业伦理能力评价指标体系。运用灰色聚类理论建立了相应的企业伦理能力评价模型,并运用该模型对海尔集团企业伦理现状进行了定量分析。     

对我国全面取消农业税的几点思考

政府全面取消农业税这一重要举措有其深刻的背景,虽然对全面取消农业税的必要性已成基本共识,但还是有人对取消农业税产生疑虑,因此要理性看待全面取消农业税。我国免征农业税后要走出“先减后升”的怪圈,免征农业税关键是要减轻农民的“灰色负担”,减免农业税后还要做好相应配套的工作。     

实物资金流量表的预测方法研究

资金流量表是国民经济核算体系中的重要组成部分。然而,由于在编制过程中需要采集大量的数据,通常情况下,很多国家的资金流量表都会有较长时间的滞后。在编制实物资金流量表的延长表时,已有方法通常是基于基期与预测期交易收支结构保持不变的假定条件。然而,经济结构发生显著变化时,该类方法就会失效。基于上述问题,研究弱化模型的假设条件,并提出了新的实物资金流量表预测方法( 简称 FPTF方法)。根据表中元素必须满足的约束条件,该方法通过建立数学模型解除约束,其次基于历史数据的动态趋势,采用适当的时间序列分析方法来预测目标年份的实物资金流量表。通过仿真分析,验证了所提方法的有效性和稳定性。此外,基于中国1992年～2014 年的实物资金流量表数据进行实例分析,取得了满意的分析结果。     

基于灰粗集属性知识简约算法的海运规则发现

海运市场运营规则能够帮助海运企业找到盈利增长点,针对海运市场营运规则难于被发现的问题,将灰色系统理论和粗糙集理论进行融合,针对知识约简中分辨函数范式转化过程中的逻辑推演难题,提出了一种基于灰色粗集融合属性的改进约简算法,选取2007年、2010年、2013年、2015年典型年份作为样本年份,应用灰色系统、粗糙集和基于灰粗集知识约简算法分别进行海运市场盈运规则发现实证分析,通过比较证明了该算法的时效性,同时发掘出了当前海运市场的船型、货品、航线、运价、运力间的营运管理规则。     

Forecasting obesity trends in England

Summary.  Forecasts of trends in obesity in England for 2010 are produced by treating the available data, which contain the proportions of the population, categorized by age and sex, falling into different body mass index ranges, as compositional data sets, so that the implicit simplex restrictions are automatically satisfied. Forecasts are calculated by using linear trend models for the log-ratio transformations and are accompanied by prediction regions. The advantages of treating data on proportions compositionally are emphasized and compared with forecasts that have been obtained by ignoring this restriction.     

Bootstrap forecast intervals for asymmetric volatilities via EGARCH model

Bootstrap forecast intervals are developed for volatilities having asymmetric features, which are accounted for by fitting EGARCH models. A Monte-Carlo simulation compares the proposed forecast intervals with those based on GARCH fittings which ignore asymmetry. The comparison reveals substantial advantage of addressing asymmetry through EGARCH fitting over ignoring it as the conventional GARCH forecast. The EGARCH forecast intervals have empirical coverage probabilities closer to the nominal level and/or have shorter average lengths than the GARCH forecast intervals. The finding is also supported by real dataset analysis of Dow–Jones index and financial times stock exchange (FTSE) 100 index.     

中国制造业碳排放影响因素灰色关联动态分析

中国制造业经济总量和碳排放双双增长迅速。本文使用1995-2010年中国制造业相关数据,采用灰色关联分析方法动态分析了制造业发展程度、产业结构、能源结构、能源强度、城镇化率和研发强度等6个因素对中国制造业碳排放的影响程度。主要结论为：中国制造业CO2边际排放波动上升;城镇化率和产业结构是对制造业碳排放影响程度最大的两个因素,其次是能源结构、能源强度和发展程度;从时序来看,城镇化率、能源强度和发展程度对碳排放的影响逐渐增强,而产业结构和能源结构的影响比较稳定;研发强度对碳排放的影响不明显。以上结论为我国制定和完善节能减排政策提供了参考依据。     

封闭人群生存人数整体预测--以Lee-Carter模型为例

由不同组别人群组成封闭人群整体生存人数的预测是相关经济、社会问题研究的基础。现有文献在研究相关问题时,使用的方法为：首先根据动态死亡率模型对其中具有相同特征不同部分的生存人数进行预测,之后通过加总得到整体人数的预测（简称现有方法）。由于现有方法忽略了不同特征人群死亡率变动间相关性的影响,会低估生存人数的波动性。本文使用Lee?Carter模型,在将封闭人群按性别分组的基础上,给出了构建生存人数整体预测模型的过程和实例。并通过理论分析和数值模拟两个视角对现有方法和新方法做了比较。比较结果指出：在死亡率波动具有广泛相关性的现实世界中,只有在均值预测时,现有方法才可以达到预期效果,因此笔者建议在对整体人数（特别是涉及方差和分布函数）预测时,使用本文介绍的整体生存人数预测模型。