基于ECM模型的城镇居民收入与消费问题的实证研究——以杭州为例

本文根据协整理论与误差修正模型,利用1978-2007年度数据以杭州市为例对城镇居民收入与消费的协整关系进行了实证分析。结果表明:杭州市城镇居民家庭的人均消费与收入之间存在单向长期稳定的因果关系,即人均可支配收入变动是影响人均消费变动的原因,而人均消费变动不是影响人均可支配收入变动的原因。因此,从长期来看,要刺激城镇居民消费来拉动经济增长,必须增加城镇居民的可支配收入。     

Mean-Minimum Exact Confidence Intervals

This article introduces mean-minimum (MM) exact confidence intervals for a binomial probability. These intervals guarantee that both the mean and the minimum frequentist coverage never drop below specified values. For example, an MM 95[93]% interval has mean coverage at least 95% and minimum coverage at least 93%. In the conventional sense, such an interval can be viewed as an exact 93% interval that has mean coverage at least 95% or it can be viewed as an approximate 95% interval that has minimum coverage at least 93%. Graphical and numerical summaries of coverage and expected length suggest that the Blaker-based MM exact interval is an attractive alternative to, even an improvement over, commonly recommended approximate and exact intervals, including the Agresti–Coull approximate interval, the Clopper–Pearson (CP) exact interval, and the more recently recommended CP-, Blaker-, and Sterne-based mean-coverage-adjusted approximate intervals.     

A Modified Knox Test of Space-Time Clustering

Tests of space-time clustering such as the Knox test are used by epidemiologists in the preliminary analysis of datasets where an infectious aetiology is suspected. The Knox test statistic is the number of cases close in both space and time to another case. The test statistic proposed here is the excess number of such cases over that expected under H₀ of no infection. It is argued that this modified test is more powerful than the Knox test, because the test statistic is not heavily tied as is the Knox test statistic. The use of the test is illustrated with examples.     

协整理论和ECM模型在我国经济增长因素分析中的应用

文章运用协整理论,建立了排除伪回归的长期均衡方程以及ECM模型,对影响经济增长的资本因素、劳动因素、制度因素和产业结构因素进行分析,从定量角度探寻长期和短期影响我国经济增长的主要因素。     

高新技术产业发展与科技投入的关系分析

探索R&D科技投入与高新技术产业产出的关系,对于增加科技投入以促进该产业的发展具有重要作用。在VAR模型估计的基础上,运用协整理论、因果检验和误差修正模型,分析了1995-2010年科技投入与高技术产业产出之间的动态关系。结论表明:科技投入是高技术产业发展的格兰杰原因,在长期内能明显促进该产业的增长,但短期效果有限。因此,要求我们应当增加对高新技术产业的长期科技投入,为其长远发展奠定基础。     

A Parametric Test of Perfect Ranking in Balanced Ranked Set Sampling

Many techniques based on data which are drawn by Ranked Set Sampling (RSS) scheme assume that the ranking of observations is perfect. Therefore it is essential to develop some methods for testing this assumption. In this article, we propose a parametric location-scale free test for assessing the assumption of perfect ranking. The results of a simulation study in two special cases of normal and exponential distributions indicate that the proposed test performs well in comparison with its leading competitors.     

Tests of hypotheses on concomitant variables in linear models

The likelihood ratio test for the equality of k univariate normal populations is extended to include the case in which the means are expressed as simple linear regression functions involving two parameters, The moments of the likelihood ratio statistic are derived, and an approximation to the null distribution is obtained.     

Testing for the maximum mean in a mixture of normals

We consider the test of the null hypothesis that the largest mean in a mixture of an unknown number of normal components is less than or equal to a given threshold. This test is motivated by the problem of assessing whether the Soviet Union has been operating in compliance with the Nuclear Test Ban Treaty. In our analysis, the number of normal components is determined using Akaike's Information Criterion while the hypothesis test itself is based on asymptotic results given by Behboodian for a mixture of two normal components. A bootstrap approach is also considered for estimating the standard error of the largest estimated mean. The performance of the testa are examined through the use of simulation.     

Vector autoregression and causality: a theoretical overview and simulation study

This paper provides a theoretical overview of Wald tests for Granger causality in levels vector autoregressions (VAR's) and Johansen-type error correction models (ECM's). The theory is based on results in Toda and Phillips (1991a) and allows for stochastic and deterministic trends as well as arbitrary degrees of cointegration. We recommend some operational procedures for conducting Granger causality tests that are based on the Gaussian maximum likelihood estimation of ECM's. These procedures are applicable in the important practical case of testing the causal effects of one variable on another group of variables and vice versa. This paper also investigates the sampling properties of these testing procedures through simulation exercises. Three sequential causality tests in ECM's are compared with conventional causality tests in levels and differences VAR's.