信息产业对我国经济增长影响的实证分析

采用1992～2005年中国GDP的数据,测算了同期中国信息产业增加值,利用Granger因果关系检验、协整检验与误差修正模型等计量方法,对信息产业与GDP的关系进行了检验,结果发现它们之间存在单向长期稳定的关系,信息产业的发展对GDP的增长起着明显的促进作用,而GDP对信息产业发展的促进作用不明显。     

Randomized response: Estimating mean square errors of linear estimators and finding optimal unbiased strategies

Summary General procedures are described to generate quantitative randomized response (RR) required to estimate the finite population total of a sensitive variable. Permitting sample selection with arbitrary probabilities a formula for the mean square error (MSE) of a linear estimator of total based on RR is noted indicating the simple modification over one that might be based on direct response (DR) if the latter were available. A general formula for an unbiased estimator of the MSE is presented. A simple approximation is proposed in case the RR ratio estimator is employed based on a simple random sample (SRS) taken without replacement (WOR). Among sampling strategies employing unbiased but not necessarily linear estimators based on RR, certain optimal ones are identified under two alternative models analogously to well-known counterparts based on DR, if available. Unlike Warner’s (1965) treatment of categorical RR we consider quantitative RR here.     

Asymptotic behavior for S-estimators in random design linear model with long-range-dependent errors

The asymptotic behavior of S-estimators in a random design linear model with long-range-dependent Gaussian errors is considered. It turns out that the S-estimators of regression parameter and error variance are strongly consistent under mild conditions. Furthermore, the asymptotic distribution of the S-estimator of regression parameter is normal if the design vectors are i.i.d. and is non-normal if the design vectors are long-range dependent Gaussian vectors. We also show that the asymptotic distribution of S-estimator of the error variance is non-normal since the errors are long-range dependent. Supported by National Natural Science Foundation of China (Grant No. 10571159) and Specialized Research Fund for the Doctor Program of Higher Education (Grant No. 2002335090).     

线形规划法在我国医药经销商遴选中的应用

目的 本文运用线性规划的方法对我国经销商遴选问题进行优化设计，实现在既定约束下，将利润最大化、方法线性规划法、比较静态分析，结果运用线性规划的遴选方法优于传统的单目标决策方法。     

基于时钟和地址的跳频序列的产生和性能分析

在一般跳频系统中，跳频序列是由递归算法产生的，如PN序列以及混沌序列、模糊序列等。本文介绍的基于时钟和地址的跳频序列提供了一种新的产生方法。这种序列是由长比特设备地址和不断变化的长比特时钟信息经过一系列运算而产生的，即基于时钟和地址和跳频序列，该序列具有理想的均匀频谱特性和很长的周期；序列线性跨距很长，不容易被智能干扰机干扰；序列的汉明相关特性也很好；这个特点在多址接入通信中非常有用。该序列另一个重要特征是硬件实现简单容易，事实上，这种序列巳成功应用于蓝牙跳频系统中。本文主要介绍这种跳频序列的设计产生过程，并对序列的各种性能进行分析。     

关于蓄电池充电器中的恒流源电路设计

论述了应用于蓄电池充电器中的线性恒流源、开关恒流源和集成恒流源电路的设计 ,并分析了它们的结构和特点     

Comparing solution methods for dynamic equilibrium economies

This paper compares solution methods for dynamic equilibrium economies. We compute and simulate the stochastic neoclassical growth model with leisure choice using first, second, and fifth order perturbations in levels and in logs, the finite elements method, Chebyshev polynomials, and value function iteration for several calibrations. We document the performance of the methods in terms of computing time, implementation complexity, and accuracy, and we present some conclusions based on the reported evidence.     

房价影响因素的实证分析——以青岛市为例

运用SPSS软件,以人口、人均GDP、住房销售面积和房地产开发投资为自变量,采用2000～2009年10年的数据,建立了多元线性回归模型,对青岛市房价这一因变量进行了模拟分析。模型通过各种检验,得出了影响青岛市住房价格最重要的因素是市区人口这一结论,说明青岛市有效的需求增大,是抬高住房价格十分重要的因素,这在一定层面上说明了青岛的住宅市场的价格是比较正常的价格。     

带未知异方差与半线性结构Tobit模型的半参数估计

本文将Tobit模型扩展至同时带未知条件异方差与半线性结构回归函数的场合,并提出一种计算简便的半参数二步估计法。该方法的关键之处在于连续两次施以成对相减变换,并先后消去第一步所得被解释变量非参数条件分位函数中的两类非线性冗余成分(非线性回归函数部分与未知异方差结构)。文章证明了估计量的n-一致性与渐近正态性,并通过Monte Carlo模拟研究了分位点对的选择、扰动项分布类型与样本删尾程度等因素对估计量小样本性质的影响。最后通过国内居民医疗服务利用不平等的实例验证了本文所提的方法。     

SECTORS MAY USE MULTIPLE TECHNOLOGIES SIMULTANEOUSLY: THE RECTANGULAR CHOICE-OF-TECHNOLOGY MODEL WITH BINDING FACTOR CONSTRAINTS

We develop the rectangular choice-of-technology model with factor constraints, or RCOT, a linear programming input–output model for analysis of the economy of a single region. It allows for one or more sectors to operate more than one technology simultaneously, with the relatively lowest-cost one supplemented by others if it encounters a binding factor constraint. The RCOT model solves for sector outputs, goods prices that are set by the highest-cost technologies in use, and scarcity rents that correspond to binding factor constraints experienced by the lower-cost technologies. The model is motivated by the fact that mineral deposits of different qualities may be exploited simultaneously, as may primary and recycled sources for the same materials or irrigated and rain-fed techniques for producing the same crop. RCOT generalizes Carter's square choice-of-technology model, in particular adding the factor constraints that allow several alternatives to operate simultaneously. The Appendix gives a numerical example.