中国经济周期实证分析

 改革开放以来,中国经济取得了举世瞩目的伟大成就。我国的国内生产总值由1978年的3624亿元迅速提高到1998年的79553亿元,按可比价计算,年均增长9.7%。但是,不可否认,我国经济增长在年度间的波动仍然比较频繁和剧烈。例如,经济增长率最高的1984年仅为15.2%,而经济增长率最低的1900年仅为3.8%,两者相差11.4个百分点。由此引出的一个问题是,中国的经济波动究竟是一种杂乱无章的随机波动,还是一种有章可循的周期波动？我国经济理论界对此问题,众说纷纭,莫衷一是。有人不同意社会主义经济存在周期性波动这一说法,认为不能把资本主义经济周期理论硬套在社会主义经济发展的规律上,我国发生的历次经济波动也不具有历史必然性。但也有人认为,经济周期不是资本主义制度所特有的,社会主义经济同样存在周期性波动。本文围绕这一问题,用定性和定量两种方法对我国经济周期的存在性进行实证分析,并对各周期的特点和成因等作一初步探讨,最后运用经济周期模型对未来12年经济增长率进行了预测。     

我国产业结构的实证分析

China’s structure of industries has experienced three periods of evolution. The major factors determining China’s structure of industries are industrial policy, the structure of demand, the structure of labour forces and the structure of foreign trade. Disequilibrium exists both in China’s structure of second industry and in different regions in China. Faced with problems existing in the structure of industries, China should take active actions to rationalize its structure of industries.     

我国国债风险的实证分析

 近年来,我国国民经济出现明显的通货紧缩迹象,有效需求不足,物价指数下跌,经济增长率也从1992年的14.2%下降到1999年的7.1%。在货币政策实施效果不明显的情况下,1998年下半年,政策决定采取积极的财政政策,刺激消费和投资,拉动经济增长。在财政收入的“两个比重”下降的情况下,政府不得不采取积极的国债政策,扩大国债发行规模,筹集更多资金,以加大公共投资支出。因此,国债政策已成为当前积极财政政策的重要组成部分。但从动态趋势来看,中国国债发行规模自1994年以来以30%的速度急剧扩张,正面临着巨大的压力及与日俱增的财政信用风险。因此,在实施积极财政政策时,既要充分发挥国债对国民经济增长的拉动作用及对经济运行的反周期调节作用,又要防止国债规模过大对财政收支造成难以承受的压力,避免像某些发展中国家那样因债务问题而陷入财政信用危机。     

中国财政赤字问题的实证分析

中国财政赤字问题的实证分析史永东朱东明ＡＢＳＴＲＡＣＴＢｙｃａｓｅａｎａｌｙｓｉｓ,ｔｈｅｐａｐｅｒｓｔｕｄｉｅｓｔｈｅｇｒｏｗｔｈｒｅｇｕｌａｒｉｔｙｏｆＣｈｉｎａ＇ｓｆｉｎａｎｃｉａｌｄｅｆｉｃｉｔ,ａｎｄｔｈｅｉｎｔｅｒ－ｒｅｌａｔｉｏｎｓｂｅ...     

国有银行效率决定因素实证分析

 在中国银行业改革过程中,市场化的发展会使银行的技术效率、资源配置效率有所提高,而同时也会对其产生竞争压力,促使银行提高效率。Andrew c.Worthington（1998）运用随机成本前研法研究了澳大利亚非银行金融机构效率的决定因素,结果表明,银行效率的增长来源于资产质量、人力素质和教育程度的改善。本文试图对效率来源做一解释,以全面地理解改革促进哪些要素推动了银行效率的提高,进而为国有银行的进一步改革提供决策依据。     

我国经济增长质量的实证分析

建国40多年来,我国的经济发展取得了长足的发展,尤其是改革开放以来的近20年,中国经济发展的成就更是举世瞩目,中国经济现已步入快速稳定发展的上升通道。但是,我国经济在高速增长的同时,经济增长中的一些问题也逐渐暴露出来,其中尤其突出的问题就是经济增长质量问题。在此,笔者就经济增长稳定性、协调性、持续性和增长潜能四个方面作一实证研究。     

对上海期货交易所金属铜量价关系的实证分析

一、引言对商品价格变动与交易量之间相互关系的分析一直是金融市场讨论的热门话题。Ｋａｒｐｏｆｆ(1987)指出 ,研究商品价格波动与交易量之间关系有助于了解市场的结构、市场信息传播的方式和速度 ,以及市场价格如何对信息作出反映。通常价格的变化可以理解为市场对新的信息的反映 ,而交易量则可解释为投资者新信息认识的差异程度 ,如果商品价格的变动与交易量之间存在关联 ,则可利用价格变动与交易量之间的联合分布信息进行有益的分析和推断。Ｇｒａｎｇｅｒ(196 3)等最早利用周数据资料 ,采用谱分析方法对美国证券交易综合价格指数 (Ｓ…     

对我国银行业集中度决定因素的实证分析

产业集中度是用来说明产业结构的一个重要指标 ,但更多用于衡量大规模企业在行业中垄断程度的大小 ,通常以该产业最大 4家企业的相关数值占整个行业的比重来表示 ,简称ＣＲ4。一般认为 ,高的产业集中度对经济有不良影响 ,因为这会导致垄断价格和垄断利润 ,形成资源配置的无效率和收入分配不均。因此 ,各种改革的思路之一 ,就是设法降低集中度 ,打破垄断 ,促进竞争 ,以消除产业高度集中的不良后果。众所周知 ,在 1978年以前 ,我国银行业由中国人民银行绝对垄断 ,各专业银行只是人民银行或财政部的一个部门 ,严格意义上的金融市场是不存在的 ,…     

中国工业经济增长因素的实证分析

所谓经济增长是指一国或一地区在一定时期(如一季度、一年等)包括产品和劳务在内的产出的增长。经济增长问题是一个非常复杂的经济问题,如何实现持续、稳定、协调的增长,寻求最快的经济增长途径,以达到最显著的经济发展,是世界普遍关心的问题。经济增长与经济发展是有区别的,一般来讲,经济发展不仅包括产品和劳务的增加,还意味着产出的增长而出现的经济、社     

改革开放以来中国物价动态的实证分析

The article systematically analyses China’s price reform process from 1978 to the year 1995, and thoroughly presents the basic trends and stage characteristics of price change of China, and further analyses the factors of sustained price hike since China carried out the economic reform and open door policy.     

高科技公司投资价值信息识别的实证研究

一、研究背景高科技公司具有高风险、高回报、高成长的特性 ,因此投资风险较大。面临快速的环境变迁和风险变化 ,投资者如何分析和判断高科技公司未来的增长潜力和投资价值 ,己经成为投资决策的重要问题。投资风险是指投资者对高科技公司各个不同发展时期内在真实价值的估算偏差。目前西方学者的理论研究及企业的实践经验表明 ,由于投资者与高科技公司存在严重的信息不对称 ,投资者事实上承担了企业很大一部分的投资风险。因此 ,投资者需要对高科技企业投资价值信息进行全面的识别、筛选和监控 ,通过建立一种信息识别模式 ,正确地反映并评价…     

对证券投资基金的比较分析

 证券投资基金的出现是我国证券市场发展的结果。自1998年以来,已经有6家基金上市交易。成立基金的初衷是增加市场中机构投资者。向市场导入稳健的投资理念,同时通过专家理财提高投资收益率,推动市场的健康成长。那么,如何评价基金的积极作用,基金的操作到底怎样,新基金应当从旧基金学习什么如何改进？我们试作一些具体分析,同时避免先入为主的某些成见。     

Statistical analysis of rock-burst events in underground mines and excavations to present reasonable data-driven predictors

Rock bursts are sudden and violent failures of surrounding rockmasses in underground mines and excavations. In this paper, a database consisting of 188 case histories was collected. Each case history contains some of the predictor variables ‘overburden thickness, maximum tangential stress, uniaxial compressive strength of rock, tensile strength of rock, stress ratio, brittleness ratio and elastic energy index’ and one of the four defined classes for the dependent variable ‘rock burst intensity’. A strategy, including ‘outlier detection and substitution, normality evaluation, deduction of distribution functions, estimation of mean and mean variation ranges, evaluation of mean-equality and distribution function-equality hypotheses, correlation analysis and factor analysis for in-review variables’, was implemented. The strategy led to conclude that some predictor variables with available case histories have no contributions for rock burst prediction. These inferences were in accordance with the results of regression techniques for qualitative dependent variables. Besides, many predictor variable arrangements were incompatible with factor analysis. In the case of compatible arrangements, the variation of the predictor variables cannot be considerably reflected. Application of nonlinear principal component analysis using auto-associative neural networks did not also lead to representative components. Therefore, the significant predictor variables can only be used to design new classifiers.     

基于2007年投入产出表的我国投资乘数测算和变动分析

 本文对固定资产投资乘数、凯恩斯投资乘数和投入产出投资乘数等三种投资乘数进行了测算分析,结果表明近年来我国投资乘数并没有发生大幅度下降,对经济增长的拉动贡献较大。通过对4万亿投资计划的具体测算,表明投资对拉动内需和抵御外部冲击发挥了巨大作用。作为发展中国家,保持较高的投资增速是经济可持续发展的必要条件,未来投资仍将是拉动我国经济增长的主要动力。但应当积极调整投资结构,避免产能过剩、抑制房地产价格上涨,提高投资效率。     

Empirical comparison of error rate-estimators in logistic discriminant analysis

A simulation study related to the comparison of 15 estimators of the actual-error rate in two-group logistic discriminant analysis is achieved in 528 cases taking into account some characteristics of the groups such as the common distribution of the variables, the overlap of the populations, the number of variables, etc. For each combination of these parameters, the relative errors of the estimators with regard to the theoretical actual-error rate (empirically determined) are computed and help to compare the performance of the estimators. The results show an overall best performance of the estimators e632 and eOS. On the contrary, the estimators eA, epp and eppcv record the lowest performance in terms of the mean relative error and the mean relative bias. Moreover, the performance of most of the parametric estimators depends on the normality and heteroscedasticity degrees of the populations.     

Growth rate models: emphasizing growth rate analysis through growth curve modeling

To emphasize growth rate analysis, we develop a general method to reparametrize growth curve models to analyze rates of growth for a variety of growth trajectories, such as quadratic and exponential growth. The resulting growth rate models are shown to be related to rotations of growth curves. Estimated conveniently through growth curve modeling techniques, growth rate models have advantages above and beyond traditional growth curve models. The proposed growth rate models are used to analyze longitudinal data from the National Longitudinal Study of Youth (NLSY) on children's mathematics performance scores including covariates of gender and behavioral problems (BPI). Individual differences are found in rates of growth from ages 6 to 11. Associations with BPI, gender, and their interaction to rates of growth are found to vary with age. Implications of the models and the findings are discussed.     

Empirical likelihood confidence intervals for nonparametric functional data analysis

We consider the problem of constructing confidence intervals for nonparametric functional data analysis using empirical likelihood. In this doubly infinite-dimensional context, we demonstrate the Wilk's phenomenon and propose a bias-corrected construction that requires neither undersmoothing nor direct bias estimation. We also extend our results to partially linear regression models involving functional data. Our numerical results demonstrate improved performance of the empirical likelihood methods over normal approximation-based methods.     

Empirical influence functions for misclassification rates in discriminant analysis

The empirical influence function for Mahalanobis distance and for misclassification rates are presented for discriminant analysis with two multivariate normal populations, following Campbell (1978). Conclusions about the effects of outliers from the empirical influence function are contrasted with exact calculations for four simple cases. These cases demonstrate that the higher-order terms discarded in deriving the empirical influence function can be important in practical problems.     

Empirical Bayes regression analysis with many regressors but fewer observations

In this paper, we consider the prediction problem in multiple linear regression model in which the number of predictor variables, p, is extremely large compared to the number of available observations, n  . The least-squares predictor based on a generalized inverse is not efficient. We propose six empirical Bayes estimators of the regression parameters. Three of them are shown to have uniformly lower prediction error than the least-squares predictors when the vector of regressor variables are assumed to be random with mean vector zero and the covariance matrix (1/n)X^tX$(1/n){\mathit{X}}^{\mathrm{t}}\mathit{X}$ where X^t=(_x1,…,_xn)${\mathit{X}}^{\mathrm{t}}=({\mathit{x}}_1,\dots ,{\mathit{x}}_n)$ is the p×n$p\times n$ matrix of observations on the regressor vector centered from their sample means. For other estimators, we use simulation to show its superiority over the least-squares predictor.