Posterior analysis,prediction and reliability in three-parameter weibull distributions

The paper develops Bayesian analysis in the context of samples from three-parameter Weibull distributions and shows how to tackle the problems of prediction and estimation of reliability curves. As Johnson, Kotz and Balakrishnan ( 1994 ) mentioned, the prediction problems for the three-parameter Weibull model seem to be unresolved and is certainly worth looking into (p.671). Posterior analysis organized around Gibbs sampling is shown to perform well. An application to stock returns is used to illustrate the potential of the approach.     

Regression Properties for Asymmetric Generalized Scale Mixtures of Multivariate Gaussian Variables

Analytical properties of regression and the variance–covariance matrix of asymmetric generalized scale mixture of multivariate Gaussian variables are presented. The analysis includes an in-depth analytical investigation of the first two conditional moments of the mixing variable. Exact computable expressions for the prediction and the conditional variance are presented for the generalized hyperbolic distribution using the inversion theorem for Fourier transforms. An application to financial log returns is demonstrated via the classical Euler approximation. The methodology is illustrated by analyzing the regression of intraday log returns for CISCO against the corresponding data from S&P 500.     

Portmanteau tests for linearity of stationary time series

This article considers the problem of testing for linearity of stationary time series. Portmanteau tests are discussed which are based on generalized correlations of residuals from a linear model (that is, autocorrelations and cross-correlations of different powers of the residuals). The finite-sample properties of the tests are assessed by means of Monte Carlo experiments. The tests are applied to 100 time series of stock returns.     

Asymptotic Distributions of Quasi‐Maximum Likelihood Estimators for Spatial Autoregressive Models

This paper investigates asymptotic properties of the maximum likelihood estimator and the quasi‐maximum likelihood estimator for the spatial autoregressive model. The rates of convergence of those estimators may depend on some general features of the spatial weights matrix of the model. It is important to make the distinction with different spatial scenarios. Under the scenario that each unit will be influenced by only a few neighboring units, the estimators may have ‐rate of convergence and be asymptotically normal. When each unit can be influenced by many neighbors, irregularity of the information matrix may occur and various components of the estimators may have different rates of convergence.     

中国商品期货回报与现货价格变化测度研究——基于便利收益模型的视角

本文基于便利收益模型(CYM)的视角推导出商品期限结构、期货回报并对期货回报进行分解。选取我国三个商品期货交易所相关数据作为样本,对我国商品期货回报与现货价格变化进行测度研究。研究发现,在样本期内,商品期货回报和现货价格变化之间不存在密切关系;以展期收益或预期现货价格变化为条件的商品风险溢价具有时变性;平均展期收益反映了现货价格变化对风险溢价的预期偏离;期货期限结构、便利收益和展期收益准确地预测了现货价格变化。上述研究结果为我国商品期货回报与现货价格变化的测度和管理以及商品期货投资决策设计提供了一些有帮助的理论借鉴和操作性较强的方法选择。     

中国上市公司资本结构调整能力的实证研究

以1992—2002年为观测区间,沪、深股市A股市场的所有上市公司为样本,采用FamaMacbeth方法研究我国上市公司资本结构的调整。我们发现,在短期(一年内),上市公司的资本结构变动有近三分之一的原因来自股票市场的波动,上市公司的资本结构会出现向历史比率温和调整的趋势;将观测区间延长至三年时,股票收益的波动对上市公司资本结构变动的影响减弱,资本结构向历史水平调整的力度明显加大。同时,在动态调整过程中,上市公司主动调整资本结构的手段只能依赖负债的主动调整。     

乡村振兴背景下农业产业化对农民收入的影响研究 ——基于S省M县调研数据

乡村振兴战略的提出为顺利解决农业经济发展问题、促进农业产业化进程和解决农民收入问题提供了政策参考的蓝本,也促使农业产业化成为解决农民增收问题的主要落脚点。该研究从农业产业化前、中、后期三阶段出发,综合考虑农民个人禀赋、政府政策、是否参加合作社及产后重点项目等维度,构建了农业产业化改善农民增收问题的理论框架,利用调研数据和二元logistic模型进行实证研究。结果表明：农业产业化能显著改善农民收入问题。作为农业产业化的典型代表,合作社在增加农民收入方面发挥着显著的积极作用,尤其是参与合作社产后重点项目这一农业产业化深化行为,更会促使农民增收。相对而言,文化程度较高、有技能、风险承受能力较强的农民收入增加的可能性较高。     

珠三角农业产业转型升级要素报酬变动趋势分析

通过佛山五区1992—2009年农业生产函数的估计,分析近20年来农业生产要素投入的变动规律和各要素的贡献占比,研究认为:农业要素报酬变动排序为:物质投入、科技进步、土地、劳动力;随时间变化科技进步贡献率的区域变化加大,要素投放的数量和质量变化都呈现"马太效应"。提出经济发达地区以巩固资本积累为前提大力提高农业科技投入,经济欠发达地区着力于发展报酬最高的物质要素投入实现经济增长的转型期对策。     

中部地区农民增收的内生动力研究

农民增收问题是解决中部地区三农问题的关键所在。研究表明:人力资本和科技进步是中部地区农民增收的内生动力。促进中部地区农民长效增收,应大力提升人力资本,加快科技进步,实施农村义务教育均衡发展、职业教育创业创新、劳动力转移培训和现代农业急需人才开发等四大工程,构建现代农业关键技术、科技创新、技术推广和网络服务等四大体系。