论文检索

协方差约束下联立方程模型的有效估计与识别AI 解读

The authors consider estimation of simultaneous equations models with covariance restrictions. They consider FIML estimation and extend J. A. Hausman's instrumental variables interpretation of the FIML estim ator to the covariance restrictions case. A slight variation on the i nstrumental variables theme yields a simple, efficient alternative to FIML. The authors augment the original equation system by equations implied by the covariance restrictions, linearized around an…

带协方差约束的线性联立方程模型识别：工具变量解释AI 解读

This picture is greatly complicated when restrictions on the structural disturbance variances and covariances, (henceforth "covariance restrictions") are allowed.Koopmans Rubin, and Leipnik (1950) recognized the usefulness of such restrictions for identification and demonstrated their equivalence to bilinear restrictions on the coefficients.This work was pursued by Wegge (1965) j Rothenberg (1971), and especially Fisher (1963, 1965), surveyed in Fisher (19-66, Chapters 3 and…

面板数据与不可观测个体效应AI 解读

Abstract An important purpose in pooling time-series and cross-section data is to control for individual-specific unobservable effects which may be correlated with other explanatory variables, e.g. latent ability in measuring returns to schooling in earnings equations or managerial ability in measuring returns to scale in firm cost functions. Using instrumental variables and the time-invariant characteristics of the latent variable, we derive: 1. (1) a test for the presence…

摘要暂缺

摘要暂缺

摘要暂缺

扰动协方差矩阵未知时的系数先验信息AI 解读

usefulness of prior information. Viewed broadly, this theme has encompassed such diverse topics as the estimation of a system of simultaneous structural equations, the specification and estimation of distributed lags, and the formal integration of stochastic prior and sample information through Bayes' theorem. Without exception, the results have encouraged the incorporation of further prior information into our statistical procedures, in the sense that the judicious use of…