基于多变量动态模型的产出缺口估算

 本文运用多变量动态模型系统下的Beveridge-Nelson分解方法和贝叶斯Gibbs抽样估计,估算了1985年1季度至2008年2季度期间中国的产出缺口,并且与传统的单变量估计方法测算的结果在统计属性和对货币政策调节的预测效果方面进行了比较。实证结果表明,不同产出缺口的统计属性存在差别,并且只有基于多变量系统测算的产出缺口对货币政策具有显著预测效果。这说明多变量模型估计出的产出缺口更全面地考虑了经济产出与其他相关变量的互动效应,含有的信息更为丰富,从而对宏观政策调整具有更重要的参考价值。     

需求模式变化的环境影响

 基于非竞争型投入产出模型和Dietzenbacher和Los提出的完全结构分解方法建立了最终需求模式变化及其环境影响的评价模型。在此基础上评价了中国最终需求模式变化对SO2排放的影响。结果表明,1987-2006年,中国的最终需求模式变化整体上是不利于减少SO2排放的,这一方面是因为最终需求中出口的份额大幅上升而消费的份额明显下降;另一方面则是因为SO2排放强度高的产品或服务在整个最终需求中的份额有所上升。不过,相对于需求总量和技术变化的影响而言,需求模式变化对SO2排放的影响很小。因此,未来中国要通过税收等灵活有效的激励措施加强或进一步推动需求管理,形成更具有可持续性的需求模式。     

A Bayesian discovery procedure

Summary.  We discuss a Bayesian discovery procedure for multiple-comparison problems. We show that, under a coherent decision theoretic framework, a loss function combining true positive and false positive counts leads to a decision rule that is based on a threshold of the posterior probability of the alternative. Under a semiparametric model for the data, we show that the Bayes rule can be approximated by the optimal discovery procedure, which was recently introduced by Storey. Improving the approximation leads us to a Bayesian discovery procedure, which exploits the multiple shrinkage in clusters that are implied by the assumed non-parametric model. We compare the Bayesian discovery procedure and the optimal discovery procedure estimates in a simple simulation study and in an assessment of differential gene expression based on microarray data from tumour samples. We extend the setting of the optimal discovery procedure by discussing modifications of the loss function that lead to different single-thresholding statistics. Finally, we provide an application of the previous arguments to dependent (spatial) data.     

Accelerated hazards mixture cure model

We propose a new cure model for survival data with a surviving or cure fraction. The new model is a mixture cure model where the covariate effects on the proportion of cure and the distribution of the failure time of uncured patients are separately modeled. Unlike the existing mixture cure models, the new model allows covariate effects on the failure time distribution of uncured patients to be negligible at time zero and to increase as time goes by. Such a model is particularly useful in some cancer treatments when the treat effect increases gradually from zero, and the existing models usually cannot handle this situation properly. We develop a rank based semiparametric estimation method to obtain the maximum likelihood estimates of the parameters in the model. We compare it with existing models and methods via a simulation study, and apply the model to a breast cancer data set. The numerical studies show that the new model provides a useful addition to the cure model literature.     

中国城市化与生态环境协调发展预警系统研究

本文构建了城市化与生态环境协调发展预警指标体系,并对1991～2010年中国城市化与生态环境的协调度进行了测算及预测,根据协调度建立了预警系统,并对90年代以来中国城市化与生态环境的协调发展进行了分析。结果表明,2007年以来,中国的生态环境不断恶化,城市化与生态环境的协调度不断下降,保护生态环境成为城市化进程中的重要问题。     

Likelihood-based and Bayesian methods for Tweedie compound Poisson linear mixed models

The Tweedie compound Poisson distribution is a subclass of the exponential dispersion family with a power variance function, in which the value of the power index lies in the interval (1,2). It is well known that the Tweedie compound Poisson density function is not analytically tractable, and numerical procedures that allow the density to be accurately and fast evaluated did not appear until fairly recently. Unsurprisingly, there has been little statistical literature devoted to full maximum likelihood inference for Tweedie compound Poisson mixed models. To date, the focus has been on estimation methods in the quasi-likelihood framework. Further, Tweedie compound Poisson mixed models involve an unknown variance function, which has a significant impact on hypothesis tests and predictive uncertainty measures. The estimation of the unknown variance function is thus of independent interest in many applications. However, quasi-likelihood-based methods are not well suited to this task. This paper presents several likelihood-based inferential methods for the Tweedie compound Poisson mixed model that enable estimation of the variance function from the data. These algorithms include the likelihood approximation method, in which both the integral over the random effects and the compound Poisson density function are evaluated numerically; and the latent variable approach, in which maximum likelihood estimation is carried out via the Monte Carlo EM algorithm, without the need for approximating the density function. In addition, we derive the corresponding Markov Chain Monte Carlo algorithm for a Bayesian formulation of the mixed model. We demonstrate the use of the various methods through a numerical example, and conduct an array of simulation studies to evaluate the statistical properties of the proposed estimators.     

农村居民消费增长比平稳更重要

 本文将消费习惯引入Lucas (1987)模型,采用农村五等份收入户的人均消费数据进行数值模拟,结果发现: 消费增长比消费平稳更重要,且收入等级越高,这种相对重要性就越突出。相对风险规避系数一定时,两类福利成本之比随习惯强度变化的轨迹呈倒U型; 习惯强度一定时,两类福利成本之比随相对风险规避系数的增大而递减。相对于其他等级的收入户,促进消费增长的经济政策为高收入户带来相对较多的福利,而平抑消费波动的经济政策能为低收入户带来较多的福利。因此,政府在促进农村居民消费增长的同时,也应重视消费波动给低收入群体造成的福利成本。     

Model-based confidence bands for survival functions

This paper focuses on a novel method of developing one-sample confidence bands for survival functions from right censored data. The approach is model-based, relying on a parametric model for the conditional expectation of the censoring indicator given the observed minimum, and derives its strength from easy access to a good-fitting model among a plethora of choices available for binary response data. The substantive methodological contribution is in exploiting a semiparametric estimator of the survival function to produce improved simultaneous confidence bands. To obtain critical values for computing the confidence bands, a two-stage bootstrap approach that combines the classical bootstrap with the more recent model-based regeneration of censoring indicators is proposed and a justification of its asymptotic validity is also provided. Several different confidence bands are studied using the proposed approach. Numerical studies, including robustness of the proposed bands to misspecification, are carried out to check efficacy. The method is illustrated using two lung cancer data sets.