Recent development of covariance structure analysis in economics

被引:1
作者
Hayakawa, Kazuhiko [1 ]
机构
[1] Hiroshima Univ, Dept Econ, 1-2-1 Kagamiyama, Hiroshima 7398525, Japan
关键词
Covariance structure analysis; Structural equation modeling; Missing data; Panel data; Income process; Dynamic panel data models; Endogenous variable; Measurement error; PANEL-DATA MODELS; MAXIMUM-LIKELIHOOD-ESTIMATION; ERRORS-IN-VARIABLES; GMM ESTIMATION; MISSING DATA; TEST STATISTICS; 2-STAGE APPROACH; INCOME PROFILES; DYNAMIC-MODELS; HIGH DIMENSION;
D O I
10.1016/j.ecosta.2021.10.002
中图分类号
F [经济];
学科分类号
02 ;
摘要
A survey on the recent development of covariance structure analysis (CSA) in economics is provided. First, estimation, inference, specification tests, and the treatment of missing values are discussed for a general CSA model. Subsequently, to demonstrate the applications of CSA in economics, statistical analyses of income dynamics and panel regression models with endogeneity are examined. Finally, some future research directions are discussed.(c) 2021 The Author(s). Published by Elsevier B.V. on behalf of EcoSta Econometrics and Statistics. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ )
引用
收藏
页码:31 / 48
页数:18
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