回归分析在土地估价中的应用

回归分析是一种统计学方法，在地价分析与测算中得到广泛应用。本文从统计学的角度阐明了回归分析的原理，并介绍了如何建立回归方程解决土地估价中出现的有关问题。     

Incentives to move up: Effects of pay gaps between levels on employee performance

Employees of a certain rank are motivated by the pay gap between them and the levels above (upward comparison), and the pay gap between them and the levels below (downward comparison). In some cases, employees face multiple upward comparisons such as immediate and subsequent upward comparisons. We hypothesise that upward comparison matters more than downward comparison, and in the case of multiple upward comparisons, the immediate one matters more than the subsequent ones. We also hypothesise that the pay gap effect resulting from the upward/downward comparison ought to be non‐linear in that performance increases with pay gap size at a decreasing rate. The results from two empirical studies, namely, a longitudinal field study and a laboratory experiment, largely support our hypotheses.     

基于熵理论的项目组织结构评价与选择

首先分析了系统结构对系统内信息流的影响,从信息的角度对项目组织结构的有序度进行评价,引入了信息流的时效和质量的概念。然后以熵理论为基础,建立了可以进行组织结构优化设计和进行定量评价的时效质量熵模型;并给出了效质有序度的详细计算步骤。最后运用此方法通过有序度来评价某工程公司的线性组织和矩阵组织两种组织形式。     

应用线性扰动模型做枯季河道流量预报

通过计算机技术，根据实测水文资料，应用线性扰动模型方法，对各种变化较明显的河道进行各种水文要素现象进行预报。     

浅议如何确定社会保障税的最优税率

社会保障制度是我国社会主义福利事业的一个重要组成部分。它不仅作为维持劳动力再生产的物质保证而构成促进社会再生产顺利进行的重要手段,而且是社会稳定机制的一个重要组成部分。目前已有140多个国家和地区建立了社会保障制度,其中有80多个国家和地区开征了社会保障税或类似税种。文中对我国如何确定社会保障税的最优税率进行了简单的分析。     

数字示波器中插值算法误差的分析

本文主要介绍了插值算法在数字存储示波器中的应用,通过编程和仿真分析了利用正弦插值对几种不同波形的恢复结果,计算和比较了相关的均方误差。     

考虑表皮的射孔水平井产能评价

射孔水平井中地层流体的流动是符合达西定律的,但水平井射孔工艺、完井方式以及井位等因素的影响,比垂直井复杂。本文将射孔后的流动看成线源,根据Newman乘积原理,用Green函数的方法得到井底压力解析解。在此基础上,将射孔时的地层压实和井壁污染用表皮来表示,并考虑井筒存储,得Laplace空间上的表达,最后用Laplace数值反演得到时空间上的解,利用该解可以有效预测水平井的产能。     

Estimating Demand Response with Panel Data

In this paper, we extend to panel data the iterated linear least squares estimator of Blundell and Robin (in J Appl Econometrics 14: 209–232 1999). It is shown to be consistent when total expenditure and regression residuals are correlated, either because of simultaneity or because of unobserved heterogeneity. We propose separate tests for these two effects. Monte Carlo experiments are then conducted and the estimator is applied to data drawn from a French Consumer Panel.     

Model selection for nonlinear time series

We investigate the finite-sample performance of model selection criteria for local linear regression by simulation. Similarly to linear regression, the penalization term depends on the number of parameters of the model. In the context of nonparametric regression, we use a suitable quantity to account for the Equivalent Number of Parameters as previously suggested in the literature. We consider the following criteria: Rice T, FPE, AIC, Corrected AIC and GCV. To make results comparable with other data-driven selection criteria we consider also Leave-Out CV. We show that the properties of the penalization schemes are very different for some linear and nonlinear models. Finally, we set up a goodness-of-fit test for linearity based on bootstrap methods. The test has correct size and very high power against the alternatives investigated. Application of the methods proposed to macroeconomic and financial time series shows that there is evidence of nonlinearity.First version received: September 2002/Final version received : October 2003I would like to thank Cees Diks, Cars Hommes and an anonymous referee for useful comments that significantly improved the paper.