Least squares estimation of a panel data model with multifactor error structure and endogenous covariates

Matthew Harding; Carlos Lamarche

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Least squares estimation of a panel data model with multifactor error structure and endogenous covariates

机译：具有多因素误差结构和内生协变量的面板数据模型的最小二乘估计

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摘要

We propose a method for estimating the slope parameter in an interactive effects panel data model with endogenous loadings and factors, and endogenous regressors.

机译：我们提出了一种在具有内源性载荷和因子以及内源性回归因子的交互式效应面板数据模型中估算坡度参数的方法。

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来源
《Economics letters》 |2011年第3期|p.197-199|共3页
作者
Matthew Harding; Carlos Lamarche;
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作者单位

Department of Economics, Stanford University, 579 Sena Mail, Stanford, CA 94305, United States;

Department of Economics, University of Oklahoma, 729 Elm Avenue, Norman, OK 73019, United States;

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原文格式 PDF
正文语种 eng
中图分类
关键词
panel data instrumental variables interactive fixed effects;

机译：面板数据工具变量互动固定效应;
入库时间 2022-08-17 23:10:56

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机译：具有多因素误差结构的大型异构面板的估计和推断

Least squares estimation of a panel data model with multifactor error structure and endogenous covariates

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