Based on the panel data of 5 sub-sectors of high-tech industries in China from 2001 to 2007,a 3 input and 3 output model by Malmquist index is developed to measure the total factor productivity (TFP) growth of high-tech industries. The results show that there are notable difference on 5 sub-sectors’ TFP,and the growth of TFP of high-tech industries is instable,this is mainly caused by the variation of the technology progress.

The expended linear expenditure system model was employed to investigate the consumption expenditures, then the marginal propensity of consume, consumption multiplier, consumption demand and elasticity were discussed on different commodities of Shenzhen city. Considering the specific impact of hierarchical income and longitudinal factor, the Pane l Data model was also established to the analysis of the consumption expenditures structures.

本文主要从近年来深圳宏观经济发展状况、税收水平等方面利用 Logistic曲线判断深圳市未来合理的税收区间,对深圳现行宏观税负水平进行合理性判断.利用柯布-道格拉斯生产函数对 GDP和产业结构变化所对应的税收变动趋势进行判断.文章运用计量经济学软件 EViews结合大量深圳市宏观经济发展水平数据,运用定量分析的统计方法来对深圳市的宏观税负水平进行判断并且研究 GDP和产业结构变化所对应的税收变动趋势,从而得出合理结论.

近几年,深圳市出租车行业的基本特征是供给短缺,出租车成了风险最小、利润水平最高的行业之一.高额利润,诱使大量外地藉出租车涌入深圳,蓝牌车、套牌车非法营运,严重扰乱了出租车市场的正常秩序.同时,出租车营运牌照成了逐利的对象,引发众多非法转让、非法集资、重复质押等一系列复杂的社会问题及由此引起的纠纷,出租车行业成了社会各界关注的热点之一.笔者认为供求关系和谐是解决这些问题的关键之一,其中需求规模的把握又是关键中的关键.

介绍了磁性均相酶联免疫分析仪的测量原理,给出了仪器的整体设计、电路部分和软件框图.详细讨论了用样品吸光度计算样品浓度的方法.实验数据表明,仪器能满足临床检验的要求.

The quasi-likelihood estimation in analysis of covariance structure is investigated via a geometric approach. A dual geometry is introduced into the model. Some second-order asymptotic results of the quasi-likelihood estimate based on the dual geometry are obtained. The bias, covariance matrix and information loss of quasi-likelihood estimate are interpreted by the dual curvature. A limit theorem that reflects the relationship between the quasi-observed and the quasi-expected information is also established.

The estimation of model parameters in structural equation models with polytomous variables can be handled by several computationally efficient procedures. However, sensitivity or influence analysis of the model is not well studied. We demonstrate that the existing influence analysis methods for contingency tables or for normal theory structural equation models cannot be applied directly to structural equation models with polytomous variables; and we develop appropriate procedures based on the local influence approach of Cook (1986). The proposed procedures are computationally efficient, the necessary bits of the proposed diagnostic measures are readily available following an usual fit of the model. We consider the influence of an individual cell frequency with respect to three cases: when all parameters in an unstructured model are of interest, when the unstructured polychoric correlations are of interest, and when the structural parameters are of interest. We also consider the sensitivity of the parameters estimates. Two examples based on real data are presented for illustration.

In this paper, the generalized least-squares estimation of the covariance structure model is studied from a geometrical point of view. General definitions of the intrinsic curvature and the parameter-effect curvature are defined for the model. Based on the general result, the second-order approximations of the bias and the covariance matrix of the generalized least-squares estimator are established. The information loss of the estimator is also computed under the multivariate normal assumption.