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变量测量误差与恩格尔曲线分析AI 解读

The traditional method of estimating Engel curve parameters uses either (recorded) income or total expenditure as an independent variable in least squares analysis. Neither of these is, however, a satisfactory index of the economic position of the family. This results in biased estimates of the income elasticities of the various consumption categories. The bias can, however, be eliminated in large samples by using both income and total expenditures in the estimation…

广义经典线性可识别性检验统计量的有限样本分布AI 解读

In the estimation of econometric simultaneous equations models, hypothesized necessary conditions for the identifiability of a single equation usually specify the exclusion of a number of variables from the structural equation in question. If the pre-determined variables are completely exogenous, if the disturbances in the equations are jointly normally distributed, and if a moderately high degree of precision can be obtained in reduced-form estimation, then the exact finite…

不同联立方程估计量的蒙特卡洛研究AI 解读

We study the small sample properties of the simultaneous equation estimators by a Monte Carlo approach. The four methods of estimation considered are: least squares, two-stage least squares, unbiased and minimumsecond-moment. The last of these four methods possesses the smallest secondorder sampling moments about the true parameter value in a majority of cases, while two-stage least squares shows the smallest bias in all cases. It is also founld that the usual asymptotic…

最大似然估计程序及其配套显著性检验AI 解读

Summary The essence of many statistical problems, including most standard techniques, is to test whether or not the unknown parameters of an appropriate statistical model satisfy certain restrictions; and the outcome of such a test dictates whether it is necessary to provide estimates of these parameters which also satisfy the restrictions. In this paper we discuss and illustrate the relative merits, as practical tools for the consulting statistician, of two large-sample…

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用工具变量估计残差自相关的关系AI 解读

SUMMARY The instrumental variables method of estimating the coefficients of a linear relationship between time series which have measurement errors is applied to the case where the coefficients are functions of a set of parameters. The asymptotic error variance matrix of the estimates is obtained, asymptotic tests for the existence and identification of the suggested form of relationship are suggested, and asymptotic confidence regions are given. The general theory is then…

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随机微分方程系统中的参数估计AI 解读

In many fields of study there occur systems of lagged dependences which can be described approximately by systems of linear stationary stochastic differential equations. In this paper we consider the estimation of parameters in such systems, using an approach similar to that of Bartlett (1946, 1955) and Quenouille (1957), and discuss conditions for identification of the separate behaviour relationships of a system. Little is known about the small-sample properties of…

使用工具变量估计经济关系AI 解读

which the relationships are not exact, so that a set of ideal economic variables is assumed to be generated by a set of dynamic stochastic relationships, as in Koopmans [12], and the actual economic time series are assumed to differ from the ideal economic variables because of random disturbances or measurement errors. The asymptotic error variance matrix for the coefficients of one of the relationships is obtained in the case in which these relationships are estimated using…

一种随机结构的识别AI 解读

THE TASK OF estimating the components, i.e., parameters and distributions, of a stochastic structure and the companion problem of identification have been treated in a series of papers in the last few years. Impetus to research in this sphere was given by the work of Reiersol [2] which appeared in a 1950 issue of Econometrica. Recently, Wolfowitz [3] has shown that strongly consistent estimators may be obtained by the method of minimum distance for various structures when…

正态变量二次型的迹与累积量AI 解读

Summary The cumulants of a quadratic form in n independent standardized variables are identified with the traces of the powers of the matrix of the form. This identification leads to some very simple proofs of well-known theorems. It is proved that only in a normal system is it possible to have non-trivial linear transformations from one set of independent variables to another set of independent variables. Matrix proofs are given for the Cochran theorems paying special…

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观测误差方差未知时变量系统部分间线性关系的确定AI 解读

Given a sufficient number of instrumental variables significantly correlated with the\ninvestigational variables, consistent estimates of the coefficients of the linear relations can be determined (if they exist), without knowledge of the disturbance variances. The estimates are discussed from the viewpoint of probability convergence. In the case of two investigational and one instrumental variable, all three variables distributed on the normal surface, the distribution of…

关于从时间序列统计估计供需关系的札记AI 解读

IN A discussion in this Journal of the estimation from time series of economic relations such as demand and supply equations, G. Tintner developed a technique based on multivariate methods of statistical analysis, the economic relations being identified with the linear relations existing (within the limits of observational error) among the economic variables considered. In the present note a more precise analysis of the same type is adopted in which some of the limitations…

以句长作为文学风格标准的统计分析札记AI 解读

SOME years ago I made a number of calculations of the frequency distribution of words of different length in different books to see to what extent authors kept to a definite distribution and so perhaps might be identified by such a method.The results obtained, however, were not striking and the work was put at one side.Mr Udny Yule (1939), however, has attacked the problem of authorship from the angle of the variation in sentence length, and this appears to be a much more…

小样本相关系数分布的密度值与概率积分表AI 解读

Editor's preface Introduction 1. Introductory 2. Construction of the tables 3. Interpolation, methods and illustration 4. Use of the tables and illustrations 5. Efficacy of the z'-transformation 6. Conclusion Appendix References Diagrams I-X Tables Charts I-IV.

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