Finite sample multivariate structural change tests with application to energy demand models

This paper considers finite sample motivated structural change tests in the multivariate linear regression model with application to energy demand models, in which case commonly used structural change tests remain asymptotic. As in Dufour and Kiviet [1996. Exact tests for structural change in first-order dynamic models. Journal of Econometrics 70, 39–68], we account for intervening nuisance parameters through a two-stage maximized Monte Carlo test procedure. Our contributions can be classified into five categories: (i) we extend tests for which a finite-sample theory has been supplied for Gaussian distributions to the non-Gaussian context; (ii) we show that Bai et al. [1998. Testing and dating common breaks in multi-variate time series. The Review of Economic Studies 65 (3), 395–432] test severely over-rejects and propose exact variants of this test; (iii) we consider predictive break test approaches which generalize tests in Dufour [1980. Dummy variables and predictive tests for structural change. Economics Letters 6, 241–247] and Dufour and Kiviet [1996. Exact tests for structural change in first-order dynamic models. Journal of Econometrics 70, 39–68]; (iv) we propose exact (non-Bonferonni based) extensions of the multivariate outliers test from Wilks [1963. Multivariate statistical outliers. Sankhya Series A 25, 407–426] to models with covariates; (v) we apply these tests to the energy demand system analyzed by Arsenault et al. [1995. A total energy demand model of Québec: forecasting properties. Energy Economics 17 (2), 163–171]. For two out of the six industrial sectors analyzed over the 1962–2000 period, break and further goodness-of-fit and diagnostic tests allow to identify (and correct) specification problems arising from historical regulatory changes or (possibly random) industry-specific effects. The procedures we propose have potential useful applications in statistics, econometrics and finance (e.g. event studies).     

Hölder continuity of the policy function approximation in the value function approximation

We show that given a value function approximation V of a strongly concave stochastic dynamic programming problem (SDDP), the associated policy function approximation is Hölder continuous in V.     

Job satisfaction and gender: Why are women so happy at work?

By most objective standards, women's jobs are worse than men's, yet women report higher levels of job satisfaction than do men. This paper uses a recent large-scale British survey to document the extent of this gender differential for eight measures of job satisfaction and to evaluate the proposition that identical men and women in identical jobs should be equally satisfied. Neither the different jobs that men and women do, their different work values, nor sample selection account for the gender satisfaction differential. The paper's proposed explanation appeals to the notion of relative well-being, especially relative to workers' expectations. An identical man and woman with the same jobs and expectations would indeed report identical job satisfaction, but women's expectations are argued to be lower than men's. This hypothesis is supported by the finding that the gender satisfaction differential disappears for the young, the higher-educated, professionals and those in male-dominated workplaces, for all of whom there is less likely to be a gender difference in job expectations.     

Seasonality and non-linear price effects in scanner-data-based market-response models

Scanner data for fast moving consumer goods typically amount to panels of time series where both N and T are large. To reduce the number of parameters and to shrink parameters towards plausible and interpretable values, Hierarchical Bayes models turn out to be useful. Such models contain in the second level a stochastic model to describe the parameters in the first level.     

智能车辆流量检测器的设计与实现

本文介绍了利用单片机如何实现智能环形线圈车辆检测器，讨论了此类检测器的软硬件设计要点。给出了相应的接口电路。     

Estimating a generalized correlation coefficient for a generalized bivariate probit model

In this paper we consider semiparametric estimation of a generalized correlation coefficient in a generalized bivariate probit model. The generalized correlation coefficient provides a simple summary statistic measuring the relationship between the two binary decision processes in a general framework. Our semiparametric estimation procedure consists of two steps, combining semiparametric estimators for univariate binary choice models with the method of maximum likelihood for the bivariate probit model with nonparametrically generated regressors. The estimator is shown to be consistent and asymptotically normal. The estimator performs well in our simulation study.     

B2C电子商务物流配送中心选址模型研究

分析了B2C电子商务的发展趋势、发展瓶颈即物流配送成本,为优化物流成本,构建了基于不同路段运输单价不同的最优运输费用的物流配送中心选址模型.     

高校网上招生系统的后续开发与研究

针对目前院校端网上招生录取系统存在的局限性,文章详细介绍了高校网上招生后续开发管理系统的功能,讨论了系统实现中的关键技术及实现方法,指出该系统采用分布式计算技术,建立基于组件的3层C/S模型的体系结构,具有高效性、可伸缩性、开发周期短、安全性高的特点。     

Java语言的特点与C^＋＋语言的比较

Java语言是一门很优秀的语言,具有面向对象、与平台无关、安全、稳定和多线程等优良特性,是目前软件设计中极为健壮的编程语言.Java已成为网络时代最重要的语言之一.与C++语言比较,Java是一种更纯粹的面向对象程序设计语言.     

将Python嵌入到C/C++应用程序中的编程方法

Python是一种面向对象的语言.本文介绍了怎样在不同的层次上将Python编译器作为一种扩展语言嵌入到用C/C++编写的应用程序之中.嵌入了Python的C/C++应用程序可以完成某些Python特有的功能.文章也讲述了如何扩展嵌入的Python使其获得应用程序本身的功能.最后,讲述了怎样使链接到静态库的应用程序获得动态扩展.