Introductory Econometrics(ISBN=9780521843195) 下载 网盘 kindle mobi 115盘 pdf pdb rtf

　　This highly accessible and innovative text and accompanying

CD．ROM useExcel workbooks powered by Visual Basic macros to teach

the core con—cepts of econometrics without advanced

mathematics．These materials enableMonte Carlo simulations to be run

by students with a click of a button．Thefundamental teaching

strategy is to use clear language and take advantage ofrecent

developments in computer technology to create concrete．visual

expla—nations of difficult．abstract jdeas．Intelligent repetition of

concrete exampleseffectively conveys the properties of the ordinary

least squares rOLs)esti．mator and the nature of heteroskedasticitv

and autocorrelation．Coverageincludes omitted variables，binary

response models，basic time series methods．and an introduction to

simultaneous equations．The authors teach studentshow to construct

their own real—world data sets drawn from the Internet．which they

can analyze with Excel or with other econometric software．TheExcel

add—ins included with this book allow students to draw

histograms．findP—values of various test statistics(including

Durbin—Watson)、obtain robuststandard errors，and construct their own

Monte Carlo and bootstrap simula—tions．For more．visit

wwwabash．edu／econometrics．

Preface

User Guide

0.1 Conventions and Organization of Files  

0.2.Preparing and Working with Microsoft Excel

1.Introduction

1.1.Definition of Econometrics

1.2.Regression Analysis C／g.x／s

1.3.Conclusion

1.4.Exercises

References

PART l.DESCRIPTION

2.Correlation

2.1.Introduction

2.2.Correlation Basics Correlartion.xls

2.3.Correlation DangersCorrelation.xlsIMRGDPX

2.4.Ecological CorrelationEcolCorr.xls EcolCorrCPSx

2.5.Conclusion

2.6.Exercises

References

……

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书籍介绍

This highly accessible and innovative text (and accompanying website: www.wabash.edu/econometrics) uses Excel (R) workbooks powered by Visual Basic macros to teach the core concepts of econometrics without advanced mathematics. It enables students to run monte Carlo simulations in which they repeatedly sample from artificial data sets in order to understand the data generating process and sampling distribution. Coverage includes omitted variables, binary response models, basic time series, and simultaneous equations. The authors teach students how to construct their own real-world data sets drawn from the internet, which they can analyze with Excel (R) or with other econometric software.