Towards Uniformly Efficient Trend Estimation Under Weak/Strong Correlation and Non‐stationary Volatility

In this paper, we consider the deterministic trend model where the error process is allowed to be weakly or strongly correlated and subject to non‐stationary volatility. Extant estimators of the trend coefficient are analysed. We find that under heteroskedasticity, the Cochrane–Orcutt‐type estimator (with some initial condition) could be less efficient than Ordinary Least Squares (OLS) when the process is highly persistent, whereas it is asymptotically equivalent to OLS when the process is less persistent. An efficient non‐parametrically weighted Cochrane–Orcutt‐type estimator is then proposed. The efficiency is uniform over weak or strong serial correlation and non‐stationary volatility of unknown form. The feasible estimator relies on non‐parametric estimation of the volatility function, and the asymptotic theory is provided. We use the data‐dependent smoothing bandwidth that can automatically adjust for the strength of non‐stationarity in volatilities. The implementation does not require pretesting persistence of the process or specification of non‐stationary volatility. Finite‐sample evaluation via simulations and an empirical application demonstrates the good performance of proposed estimators.     

Efficient Estimation in Heteroscedastic Partially Linear Varying Coefficient Models

This article considers statistical inference for the heteroscedastic partially linear varying coefficient models. We construct an efficient estimator for the parametric component by applying the weighted profile least-squares approach, and show that it is semiparametrically efficient in the sense that the inverse of the asymptotic variance of the estimator reaches the semiparametric efficiency bound. Simulation studies are conducted to illustrate the performance of the proposed method.     

Conditional time-dependent nonparametric estimators with an application to healthcare production function

ABSTRACT

By using the probabilistic framework of production efficiency, the paper develops time-dependent conditional efficiency estimators performing a non-parametric frontier analysis. Specifically, by applying both full and quantile (robust) time-dependent conditional estimators, it models the dynamic effect of health expenditure on countries’ technological change and technological catch-up levels. The results from the application reveal that the effect of per capita health expenditure on countries’ technological change and technological catch-up is nonlinear and is subject to countries’ specific income levels.     

试论强化国家创新体系

我国现有的国家创新系统存在效率低下和创新活力不强的问题。强化我国的创新工作应该采取适应市场 ,及时调整创新系统中各因素的角色 ;实现创新组织网络化达到资源共享 ;政府推动创新文化建设 ,营造创新氛围这三项措施 ,从而提高我国整体创新能力和国家创新系统效率。     

互联网时代的信息传播悖论

互联网上存在这样一个悖论——一方面是海量信息 ,另一方面却是垃圾信息 ,有用信息难以查找 ,文章分析了这一现象产生的原因及其对网络生态环境的危害 ,并初步提出了解决方法。     

土地利用管制制度效率探讨

对于公共管理,管制是重要的管理手段。文章用经济学的观点阐述管制政策的效率原理,并在此基础上分析我国土地利用管制政策的效率,最后提出我国管制政策改进的建议和实施的条件。     

绍兴市贷款产出效率分析

通过对1991-2004年绍兴市实现的GDP与占用贷款变动关系的统计分析,指出贷款产出效率持续走低存在的问题,在分析了贷款产出效率下降的主要原因后,提出了相应的对策建议.     

当代西方关于全球性问题的哲理反思

当代人类面临种种全球性问题,科技社会效应的两重性空前突出。当代西方思想界出现了一场科技悲观论与科技乐观论的激烈论争。对这场极具哲理性的争论应给予全面分析并加以总结,这将有助于马克思主义的科技价值论和生态哲学观的深化和发展。     

高校德育低效的内因分析

高校德育低效除社会大环境的负面影响外,高校德育自身的问题也不可忽视。智德分离;不尊重学生的主体地位;忽视培育和发展学生的情感、忽视学生的差异和个性;德育与学生的生活和需要脱节;育德者的人格不适应德育的要求等德育自身的缺陷是德育低效的内在原因。     

阿兰·奈斯论深层生态学的哲学基础

在阿兰·奈斯看来 ,深层生态学既是一种社会思潮 ,又是以这种思潮为指导的一场旨在改变现行实践模式的社会运动。作为一种社会思潮 ,它是一个由一系列基本原理构成的演绎性的逻辑体系。奈斯认为 ,深层生态学的理论内核是八大原理 ,而在其背后 ,还有更为基本的前提与终极规范 ,即各种生态智慧。而奈斯本人的生态智慧的终极规范是 (大 )自我实现