浅析运用计量经济模型的缺陷

１９８１年当美国的L．Klein主要因构造计量经济模型而获得诺贝尔经济学奖时，人们充分意识到计量经济学在经济研究工作中的重要性和必要性。我国也从这时起真正开始学习和借鉴传来的新方法。经过二十多年的长足发展，计量经济模型已广泛应用于经济分析研究中。当前，在经济研究领域一个十分引人注目的现象是广泛采用计量经济模型，而且是相当艰深的数量模型。不少当代经济学前沿书籍和杂志，满篇满纸都是数学公式。运用计量经济模型进行经济研究可谓蔚然成风，难道研究经济问题非得用大量大部分人都看不懂的数学模型，数学公式不可吗？诚…     

论数理经济模型有别于计量经济模型——从关于柯布-道格拉斯生产函数的一个争论谈起

一些研究人员在进行计量经济分析的时候,直接把数理经济学里面的数学模型当作计量经济模型使用,并且把这类数学模型所设置的各种假定当作计量经济分析理所当然的前提.本文指出,数理经济模型和计量经济模型分别属于两门不同的学科,担负着不同的任务,不能把二者混为一谈.计量经济分析担负测算因果效应和预测两种不同的任务,在两种不同的任务下对计量经济模型的要求不同.因此强调指出,不论是测算因果效应还是预测,直接简单地把数理经济模型当作计量经济模型使用都是不妥当的.     

劳动力流动对中国地区经济差距影响的空间计量经济模型分析

学术界对劳动力流动对地区经济发展产生的影响有两种不同观点：一种观点认为劳动力流动能够缩小地区差距;另一种观点则认为劳动力流动会扩大地区发展差距。考虑各地区经济发展的空间依赖性,通过构建空间计量经济模型,并利用中国各省区经济的面板数据进行研究与实证分析。结果表明：劳动力流动对中国不同地区经济发展的作用方向和强度表现不同,对地区差距的影响是劳动力流入与劳动力流出综合作用产生的结果。     

中国居民消费行为计量经济分析

消费是拉动经济增长的重要因素,九十年代以来,我国居民消费行为发生了很大变化,文章利用计量经济分析选择适合我国居民消费行为的假设消费函数模型,以期揭示影响现阶段我国居民消费储蓄行为的基本要素及其影响机制,并提出相应的政策性建议。     

农户融资困境及其福利经济模型

贷款融资是农户生产经营中最关键的要素之一.它帮助农户缓解流动性约束,从而促进其对现代农业技术和生产方式的采用,增强农户的风险承担能力,借贷融资对于农民收入的提高和福利的改善具有十分重要的意义.文章对农户借贷融资进行了研究,考察了农户借贷融资的经济影响,以及当发生融资困境时,借贷融资如何影响农户的福利水平.     

关于我国人均消费水平的计量分析

本文从一般消费理论出发研究我国人均消费水平,根据1981—2003年我国消费样本数据建立了我国消费模型,通过EVIEWS3.1软件利用OLS方法进行参数估计,并对模型进行了检验。经过计量分析得知我国人均消费水平主要由当年人均GDP决定,且人均消费水平与人均GDP呈明显的线性关系,若我国人均GDP增长1%,则人均居民消费约增加0.46%。滞后的人均消费水平对我国当年人均消费水平的影响是不显著的。文章最后提出了主要通过提高我国人均GDP的途径来提高我国人均消费水平的建议,并指出我国人均消费水平随着我国人均GDP的增加而提高,但其增速逐年递减。应正确处理我国消费与生产、消费与积累的关系。     

经济模型结构稳定性的统计诊断

1模型结构稳定性的统计描述为分析问题方便起见,我们设在所研究的模型中,内生变量为y,外生变量为x1熏x2熏…,xk,其N个序列观测值yt熏x1t熏x2t熏…熏xkt熏t=1熏2熏…,N来自两个经济环境不同的时期,其中前N0(N0相似文献   

基于空间计量经济的中国FDI区位分布决定因素研究

现有FDI区位问题的研究多强调各类传统区位因素的作用,却忽略了地理空间效应的影响.文章采用空间计量经济模型与普通计量经济模型对比分析的方法,对中国大陆省域FDI区域分布决定因素进行了研究.结果表明,中国FDI区域分布决定除受传统因素影响外,空间效应因素的作用也不可忽视,并对我国(尤其中西部地区)引进FDI具有重要政策启示.     

计量经济模型的数据基础

计量经济模型,是关于某一个别经济过程或宏观经济整体内在运行机制的数量结构,揭示或刻画的是经济变化的统计规律性。虽然,构造一个实际的计量经济模型,需要很多富于技术性甚至艺术性的努力,但统计数据在其中的重要地位是不容忽视的。1 .向模型编制者粗略显示经济过程的运转规则或机制,这表现在构造理论计量模型阶段。     

贷款组合信用风险VaR仿真计算的一种优化方法

This paper presents the principle of Monte Carlo optimize calculation of credit risk VaR for loanportfolio using Importance Sampling technique. Based on Matlab language, simulation experiments arecarried out and the result shows this approach can effectively reduce the numher of simulation runs andimprove the precision of parameter estimation.     

Cross-entropy method for estimation of posterior expectation in Bayesian VAR models

In this article, an importance sampling (IS) method for the posterior expectation of a non linear function in a Bayesian vector autoregressive (VAR) model is developed. Most Bayesian inference problems involve the evaluation of the expectation of a function of interest, usually a non linear function of the model parameters, under the posterior distribution. Non linear functions in Bayesian VAR setting are difficult to estimate and usually require numerical methods for their evaluation. A weighted IS estimator is used for the evaluation of the posterior expectation. With the cross-entropy (CE) approach, the IS density is chosen from a specified family of densities such that the CE distance or the Kullback–Leibler divergence between the optimal IS density and the importance density is minimal. The performance of the proposed algorithm is assessed in an iterated multistep forecasting of US macroeconomic time series.     

风险值法在金融机构信用风险管理中的运用

一、现代信用风险的主要特点长期以来 ,金融机构承担的信用风险主要被视方信贷风险 ,而信用暴露则等于债权的账面价值加上累积利息。但是 ,随着衍生产品交易的不断发展 ,信用风险变得日益复杂、量大 ,不仅透明度大大降低 ,而且也比传统的信贷风险更加难以测定。主要原因有三个方面 :第一 ,由于衍生工具交易中经常涉及到名义本金。而在银行贷款中 ,贷款的账面价值至少会让银行知道其将承担的最大损失。然后银行可以利用其对名义金额的违约概率和返回率的估计来计算出可能发生的损失额。但在衍生产品交易中 ,合约的价值与其信用暴露之间往往没…     

On unification of the asymptotic theory of nonlinear econometric models

After reading a few articles in the nonlinear econonetric literature one begins to notice that each discussion follows roughly the same lines as the classical treatment of maximum likelihood estimation. There are some technical problems having to do with simultaneously conditioning on the exogenous variables and subjecting the true parameter to a Pittman drift which prevent the use of the classical methods of proof but the basic impression of similarity is correct . An estimator – be it nonlinear least squares, three – stage nonlinear least squares, or whatever – is the solution of an optimization problem. And the objective function of the optimization problem can be treated as if it were the likelihood to derive the Wald test statistic, the likelihood ratio test statistic , and Rao's efficient score statistic. Their asymptotic null and non – null distributions can be found using arguments fairly similar to the classical maximum likelihood arguments. In this article we exploit these observations and unify much of the nonlinear econometric literature. That which escapes this unificationis that which has an objective function which is not twice continuously differentiable with respect to the parameters – minimum absolute deviations regression for example.

The model which generates the data need not bethe same as the model which was presumed to define the optimization problem. Thus, these results can be used to obtain the asymptotic behavior of inference procedures under specification error We think that this will prove to be the nost useful feature of the paper. For example, it i s not necessary toresortto Monte Carlo simulat ionto determine i f a Translog estimate of an elasticity of sub stitution obtained by nonlinear three-stage least squares is robust against a CES truestate of nature. The asymptotic approximations we give here w ill provide an analytic answer to the question, sufficiently accurate for most purposes.     

A practical method to calculate probabilities: illustrative example from the electronic industry business

The real-life environment is made of probabilistic data by nature and the ability to make decisions based on probabilities is crucial in the business world. It is common to have a set of data and the need of calculating the probability of taking a value greater or less than a specific value. It is also common in many companies the unavailability of a statistical software or a specialized professional in statistics. The purpose of this paper is to present a practical and simple method to calculate probabilities from normal or non-normal distributed data set and illustrate it with an application from the electronic industry. The method does not demand statistical knowledge from the user; there is no need of normality assumptions, goodness test or transformations. The proposed method is easy to implement, robust and the experiments have evidenced its quality. The technique is validated with a large variety of instances and compared with the well-known Johnson system of distributions.     

Basic structure of the asymptotic theory in dynamic nonlinear econometric models

This is the second of two papers that provide an expository discussion of the basic structure of the asymptotic theory of M-estimators in dynamic nonlinear models and a review of the literature. The first paper, Pötscher and Prucha(1991), deals with consistency. In the present paper we discuss asymptotic normality. As an important ingredient to the asymptotic normality proof in dynamic nonlinear models we consider central limit theorems for dependent random variables. We also discuss the estimation of the variance covariance matrix of m-estimators under heteroscedasticity and autocorrelation.     

A method for checking regression models in survival analysis based on the risk score

We propose to perform model check for the Cox and Aalen regression models using martingale residual processes grouped after the risk score. Asymptotic distributions of the grouped martingale residual processes are deduced, so both formal and graphical model check can be performed. The method is validated by stochastic simulation. A data example with patients with primary biliary cirrhosis of the liver is discussed.     

A new test for residual randomness in a class of dynamic autocorrelated econometric models

This paper presents a new test statistic for dynamic or stochastic mis-specification for the dynamic demand or dynamic adjustment class of economic models. The test statistic is based on residual autocorrelations, asymptotically X² and is suspected to be of low power. The test is illustrated with an example from recent econometric literature.     

Checks of model adequacy for univariate time series models and their application to econometric relationships

Tests derived from time series analysis play an important role in many empirical studies. These tests are frequently applied to the residuals obtained by fitting an econometric model using some standard estimator. We focus attention here on tests developed for univariate time series models. Various approaches to testing the adequacy of such models are discussed and compared. The validity and sefulness of applying these tests to econometric residuals are then examined and some Monte Carlo evidence is reported.