基于FAHP太阳能发电设备制造企业技术创新能力评价模型

21世纪国家竞争力的核心和动力是国家科技竞争力,而形成国家科技竞争力的主体是企业技术创新能力。因而,评价和分析企业技术创新能力具有重要的理论和现实意义。对于新能源发电设备制造企业来说,技术创新能力是企业的核心竞争力。本文通过建立太阳能发电设备制造企业技术创新能力的评价指标,采用FAHP方法确定各个指标的权重,并利用加权模糊逻辑推理法建立综合评价模型。     

西方产业组织学最新研究方法综述

西方产业组织学作为现代经济学的一个重要组成部分,有其稳定的分析框架和研究方法。本文从研究方法角度对其进行了梳理,分析了推理学派与实证学派各自研究方法的最新进展,研究表明:在推理学派中,其静态模型已普遍使用了推测变差方法,而其动态博弈模型已成为主流推导方法;在实证学派中,非参数检验、非线性回归以及实验经济学的广泛使用是其新特点。     

Asymptotic consequences of neglected dynamics in individual effects models*

We assess the asymptotic consequences of estimating static models based on cross-section or panel data, when in reality the data are generated by a dynamic relationship, involving lagged dependent and current and lagged exogenous variables as well as individual effects. If the exogenous variable follows a stationary process, then the static estimators usually underestimate its long-run effect. This inconsistency is less severe, the higher the autocorrelation of the exogenous variable. If the exogenous variable follows a random walk with or without individual-specific drift, then the estimators are found to be consistent for the long-run effect.     

Bayesian inference in time series models using kernel quasi likelihoods

The paper takes up Bayesian inference in time series models when essentially nothing is known about the distribution of the dependent variable given past realizations or other covariates. It proposes the use of kernel quasi likelihoods upon which formal inference can be based. Gibbs sampling with data augmentation is used to perform the computations related to numerical Bayesian analysis of the model. The method is illustrated with artificial and real data sets.     

Estimation methods for stochastic volatility models: a survey

Abstract.  Although stochastic volatility (SV) models have an intuitive appeal, their empirical application has been limited mainly due to difficulties involved in their estimation. The main problem is that the likelihood function is hard to evaluate. However, recently, several new estimation methods have been introduced and the literature on SV models has grown substantially. In this article, we review this literature. We describe the main estimators of the parameters and the underlying volatilities focusing on their advantages and limitations both from the theoretical and empirical point of view. We complete the survey with an application of the most important procedures to the S&P 500 stock price index.