Accept–reject Metropolis–Hastings sampling and marginal likelihood estimation

We describe a method for estimating the marginal likelihood, based on Chib (1995) and C hib and Jeliazkov (2001) , when simulation from the posterior distribution of the model parameters is by the accept–reject Metropolis–Hastings (ARMH) algorithm. The method is developed for one-block and multiple-block ARMH algorithms and does not require the (typically) unknown normalizing constant of the proposal density. The problem of calculating the numerical standard error of the estimates is also considered and a procedure based on batch means is developed. Two examples, dealing with a multinomial logit model and a Gaussian regression model with non-conjugate priors, are provided to illustrate the efficiency and applicability of the method.     

经济增长因素分析模型:对索洛模型的一个扩展

决定经济增长的两个直接因素分别是生产要素投入量的增长和全要素生产率的增长，索洛增长核算方程清晰而又简明地表达了这一思想，但其过于严峻的假设条件大大降低了该模型对经济增长事实的解释力和政策含义。本文对索洛模型的假设条件进行了分析和放松，并在借鉴内生增长理论的基础上对索洛模型进行扩展，从而得出一个具有较强适用性的经济增长因素分析模型。     

Of songs and men: a model for multiple choice with herding

We propose a generic model for multiple choice situations in the presence of herding and compare it with recent empirical results from a Web-based music market experiment. The model predicts a phase transition between a weak imitation phase and a strong imitation, ‘fashion’ phase, where choices are driven by peer pressure and the ranking of individual preferences is strongly distorted at the aggregate level. The model can be calibrated to reproduce the main experimental results of Salganik et al. (Science, 311, 854–856 (2006)); we show in particular that the value of the social influence parameter can be estimated from the data. In one of the experimental situation, this value is found to be close to the critical value of the model.     

规模报酬递增的增长模型——李约瑟之谜解释

本文建立了一个规模报酬递增的增长模型,用以解释李约瑟之谜,即“为什么工业革命没有发生在中国,而是发生在西欧”。模型结果显示,在农业社会,人口增长率越高,技术进步速率越快。不过,到工业革命前夕,技术进步内在机制发生变化,人口增长率与技术进步速率呈负相关关系,却与人口存量呈正相关关系。这一改变是李约瑟之谜的症结所在。     

汇率预测:一个新的非参数支持向量回归方法

本文利用一个新的非参数支持向量回归(SVR)方法来预测基于非线性ARI模型的汇率时序变量,并且与最大似然法(MLE)和人工神经网络(ANN)的预测结果进行比较。从理论上讲,MLE和ANN方法仅侧重于样本内拟合,而SVR方法则同时考虑了拟合和预测,因此,其预测能力在现有方法中是最强大的。本文选择中国、韩国、印度和瑞士四种货币的日汇率来进行预测检验,实证结果支持SVR方法具有最强的预测能力。     

手机产品顾客满意度研究与应用

激烈的市场竞争使企业越来越认识到争取市场份额、吸引并长期保持顾客的重要性。本文通过对费纳理论模型的研究,构建了手机产品顾客满意度评价指标,探讨了衡量、追踪调查、提高顾客满意度,从而提高顾客忠诚度的策略与方法,为增强我国手机生产企业的市场竞争力提供了有益的参考。     

企业自主创新与核心竞争力互动的螺旋上升模型

通过分析自主创新对核心竞争力的促进作用入手,建立了企业自主创新与核心竞争力互动的螺旋上升模型。运用该模型分析了自主创新与核心竞争力内在互动的机理,以及企业自主创新模式的跃进。     

Bayesian stochastic frontier analysis using WinBUGS

Markov chain Monte Carlo (MCMC) methods have become a ubiquitous tool in Bayesian analysis. This paper implements MCMC methods for Bayesian analysis of stochastic frontier models using the WinBUGS package, a freely available software. General code for cross-sectional and panel data are presented and various ways of summarizing posterior inference are discussed. Several examples illustrate that analyses with models of genuine practical interest can be performed straightforwardly and model changes are easily implemented. Although WinBUGS may not be that efficient for more complicated models, it does make Bayesian inference with stochastic frontier models easily accessible for applied researchers and its generic structure allows for a lot of flexibility in model specification.