Marginal Changes in Random Parameters Ordered Response Models with Interaction Terms

Marginal changes of interacted variables and interaction terms in random parameters ordered response models are calculated incorrectly in econometric softwares. We derive the correct formulas for calculating these marginal changes. In our empirical example, we observe significant changes not only in the magnitude of the marginal effects but also in their standard errors, suggesting that the incorrect estimation of the marginal effects of these variables as is commonly practiced can render biased inferences on the findings.     

Continuous Time Wishart Process for Stochastic Risk

Risks are usually represented and measured by volatility–covolatility matrices. Wishart processes are models for a dynamic analysis of multivariate risk and describe the evolution of stochastic volatility–covolatility matrices, constrained to be symmetric positive definite. The autoregressive Wishart process (WAR) is the multivariate extension of the Cox, Ingersoll, Ross (CIR) process introduced for scalar stochastic volatility. As a CIR process it allows for closed-form solutions for a number of financial problems, such as term structure of T-bonds and corporate bonds, derivative pricing in a multivariate stochastic volatility model, and the structural model for credit risk. Moreover, the Wishart dynamics are very flexible and are serious competitors for less structural multivariate ARCH models.     

Estimating multivariate autoregressive moving average models by fitting long autoregressions

Some simple methods for the estimation of mixed multivariate autoregressive moving average time series models are introduced. The methods require the fitting of a long autoregression to the data and the computation of consistent initial estimates for the parameters of the model. After these preliminaries the estimators of the paper are obtained by applying weighted least squares to a multivariate auxiliary regression model. Two types of weight matrices are considered. Both of them yield estimators which are strongly consistent and asymptotically normally distributed. The first estimators are also asymptotically efficient while the second ones are not fully efficient but computationally simple. A simulation study is performed to illustrate the behaviour of the estimators in finite samples.     

Quadratic perturbation expansions of certain functions of eigenvalues and eigenvectors and their application to sensitivity analysis in multivariate methods

Tanaka (1988) lias derived the influence functions, which are equivalent to the perturbation expansions up to linear terms, of two functions of eigenvalues and eigenvectors of a real symmetric matrix, and applied them to principal component analysis. The present paper deals with the perturbation expansions up to quadratic terms of the same functions and discusses their application to sensitivity analysis in multivariate methods, in particular, principal component analysis and principal factor analysis. Numerical examples are given to show how the approximation improves with the quadratic terms.     

First‐order bias correction for fractionally integrated time series

Most of the long memory estimators for stationary fractionally integrated time series models are known to experience non‐negligible bias in small and finite samples. Simple moment estimators are also vulnerable to such bias, but can easily be corrected. In this article, the authors propose bias reduction methods for a lag‐one sample autocorrelation‐based moment estimator. In order to reduce the bias of the moment estimator, the authors explicitly obtain the exact bias of lag‐one sample autocorrelation up to the order n⁻¹. An example where the exact first‐order bias can be noticeably more accurate than its asymptotic counterpart, even for large samples, is presented. The authors show via a simulation study that the proposed methods are promising and effective in reducing the bias of the moment estimator with minimal variance inflation. The proposed methods are applied to the northern hemisphere data. The Canadian Journal of Statistics 37: 476–493; 2009 © 2009 Statistical Society of Canada     

建国来我国婴幼儿照护服务政策：发展历程、演进逻辑与行动展望

回顾建国后婴幼儿照护服务政策的发展历程可为未来婴幼儿照护服务的发展提供历史镜鉴。梳理已有婴幼儿照护服务政策,可以发现婴幼儿照护服务遵循着以供需矛盾为表征的政策动力机制、以普惠公益为目标的政策服务定位、以责任分担为机制的政策服务路径等演进逻辑。未来应在理顺政府、市场及家庭的定位与职责的基础上增加婴幼儿照护服务的有效供给、加快顶层设计的同时明确婴幼儿照护服务的主管部门、完善政策配套实施的方式上激发婴幼儿照护服务内生发展动力,促进婴幼儿照护服务良性发展。     

改革开放下宏观调控作用于我国区域经济的历史演变与总结

改革开放以来,我国通过一系列的宏观调控手段对区域政策进行了干预。随着时间的推移,宏观调控对区域经济的演进不断地细化、改善,相应的成效也在各个区域经济中体现。新时期改革开放下,国家的宏观调控对区域政策的安排都有着新的思路与格局,这需要从历史演进中认真总结。     

我国土地制度演变及其绩效创造的经济学分析

论述了我国土地制度的发展过程,阐明了土地制度的变迁是农业经济生产效益的释放过程,同时对土地制度变迁产生的绩效进行了评析,指出在农业经济活动中由于农业本身的产业弱势,政策颁布与执行中存在一个博弈,只有博弈结果是有利于农户收益提高时政策才会有效推行。     

新中国科技政策的演进及特色

新中国科技政策的发展进程经历了奠基、成熟、停滞、变革等四个阶段,形成了注意发挥社会主义制度优越性发展科学技术、注意从中国国情出发发展科学技术、坚持自力更生走中国特色科技发展之路等特色。     

从日本禁忌风俗看女性社会地位的演变

禁忌是社会民俗现象 ,它表现在社会生活的各个方面。在历史上 ,日本女性的社会地位经历了剧烈的演变 ,其中女性禁忌发挥了极大的推动作用。本文拟从禁忌风俗着眼 ,审视日本女性社会地位的演变。