Introduction to Econometrics. A Practical Guide for First, Second and Third Year Undergraduate, Postgraduate and Research Students.

Michel Guirguis
{"title":"Introduction to Econometrics. A Practical Guide for First, Second and Third Year Undergraduate, Postgraduate and Research Students.","authors":"Michel Guirguis","doi":"10.2139/ssrn.3274224","DOIUrl":null,"url":null,"abstract":"Econometrics is a mixed discipline that requires different degrees of introductory knowledge related to probability, probability distributions, statistics, mathematical economics, calculus, and matrix algebra. For example, random variables are described by probability distributions such as the normal distribution, the t- distribution, the Chi-squared distribution, the F – distribution. Econometrics is basically related to economic measurement. It is the application of statistics and mathematics to economic or financial data to obtain and interpret numerical results. Econometricians are economic and financial analysts that are interested in numerical estimation of the relationship between economic or financial variables. It is a discipline that goes beyond expressing only economic or financial theory through mathematical equations. It is focused on the empirical estimation of these mathematical equations. Econometrics is divided into theoretical and applied econometrics. Theoretical refers to the methods for measurement of economic or financial relationships. Applied econometrics examines the structure of the problem and findings in particular fields of economics or finance. As an example, we can mention demand theory or asset allocation and investment. The findings of a financial or economic theory should be combined with empirical and additional evidence by checking the coefficient estimates and their significance. Significant autocorrelation and heteroskedasticity indicate to us that we need to change the estimation method.","PeriodicalId":373500,"journal":{"name":"EduRN: Financial Economics Education (FEN) (Topic)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"EduRN: Financial Economics Education (FEN) (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3274224","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Econometrics is a mixed discipline that requires different degrees of introductory knowledge related to probability, probability distributions, statistics, mathematical economics, calculus, and matrix algebra. For example, random variables are described by probability distributions such as the normal distribution, the t- distribution, the Chi-squared distribution, the F – distribution. Econometrics is basically related to economic measurement. It is the application of statistics and mathematics to economic or financial data to obtain and interpret numerical results. Econometricians are economic and financial analysts that are interested in numerical estimation of the relationship between economic or financial variables. It is a discipline that goes beyond expressing only economic or financial theory through mathematical equations. It is focused on the empirical estimation of these mathematical equations. Econometrics is divided into theoretical and applied econometrics. Theoretical refers to the methods for measurement of economic or financial relationships. Applied econometrics examines the structure of the problem and findings in particular fields of economics or finance. As an example, we can mention demand theory or asset allocation and investment. The findings of a financial or economic theory should be combined with empirical and additional evidence by checking the coefficient estimates and their significance. Significant autocorrelation and heteroskedasticity indicate to us that we need to change the estimation method.
计量经济学导论。一年级、二年级和三年级本科生、研究生和研究生实用指南。
计量经济学是一门混合学科,需要不同程度的概率论、概率分布、统计学、数学经济学、微积分和矩阵代数相关的入门知识。例如,随机变量由概率分布描述,如正态分布、t分布、卡方分布、F分布。计量经济学基本上与经济计量有关。它是统计学和数学对经济或金融数据的应用,以获得和解释数值结果。计量经济学家是对经济或金融变量之间关系的数值估计感兴趣的经济和金融分析师。这是一门超越了仅仅通过数学方程来表达经济或金融理论的学科。它的重点是这些数学方程的经验估计。计量经济学分为理论计量经济学和应用计量经济学。理论是指衡量经济或金融关系的方法。应用计量经济学检查问题的结构和在经济或金融的特定领域的发现。例如,我们可以提到需求理论或资产配置与投资。金融或经济理论的发现应该通过检查系数估计及其重要性与经验和额外证据相结合。显著的自相关和异方差表明我们需要改变估计方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信