摘要
本文基于现代计量经济学的发展历程,介绍了现代计量经济学的思想、理论、主要内容体系、模型、方法与工具.文中首先回顾经典计量经济学中经典线性回归模型的基本假设,并考察通过扬弃这些假设,发展而来的现代计量经济学的历史背景,进而阐述现代计量经济学的理论体系与主要内容;同时讨论了在大数据时代,大数据为计量经济学带来的挑战与机遇,以及计量经济学今后发展的若干重要方向与趋势.
This paper aims to introduce the philosophy,theories,fundamental content systems,models,methods and tools of modern econometrics based on its development history.We first review the classical assumptions of the linear regression model and discuss the historical development of modern econometrics by various relaxations of the classical assumptions to further illustrate the modern theoretical system and fundamental contents.We also discuss the challenges and opportunities for econometrics in the Big Data era and point out some important directions for the future development of econometrics.
作者
洪永淼
HONG Yongmiao(Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 100190,China;School of Economics and Management,University of Chinese Academy of Sciences,Beijing 100190,China)
出处
《计量经济学报》
2021年第2期266-284,共19页
China Journal of Econometrics
基金
国家自然科学基金“计量建模与经济政策研究”基础科学中心项目(71988101)
关键词
非实验性
线性回归模型
非线性模型
模型设定
正态分布
条件异方差
内生性
工具变量
广义矩估计
平稳性
结构变化
模型不确定性
大数据
高维数据
机器学习
预测
因果关系
政策评估
non-experimental
linear regression model
non-linear model
model specification
normal distribution
conditional heteroskedasticity
endogeneity
instrumental variable
generalized method of moments
stationarity
structure changes
model uncertainty
Big Data
high-dimensional data
machine learning
forecast
causal inference
program evaluation
