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Introduction to econometrics /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Introduction to econometrics /James H. Stock, Mark W. Watson.
作者:	Stock, James H.
其他作者:	Watson, Mark W.
出版者:	Harlow, United Kindom :Pearson,c2020.
面頁冊數:	797 p. :col. ill. ;26 cm.
附註:	Previous edition: 2015.
附註:	"Authorized adaptation from the United States edition, entitled Introduction to Econometrics , 4th Edition, ISBN 978-0-13-446199-1 by James H. Stock, Mark W. Watson, published by Pearson Education c2020"--T.p. verso.
標題:	Econometrics.
ISBN:	9781292264455

Introduction to econometrics /
Stock, James H.

Introduction to econometrics /James H. Stock, Mark W. Watson. - 4th ed., global ed. - Harlow, United Kindom :Pearson,c2020. - 797 p. :col. ill. ;26 cm. - The Pearson series in economics. - Pearson series in economics..

Previous edition: 2015.

Includes bibliographical references (p. 771-774) and index.

Part I. Introduction and review : 1. Economic questions and data ; 2. Review of probability ; 3. Review of statistics -- Part II. Fundamentals of regression analysis : 4. Linear regression with one regressor ; 5. Regression with a single regressor: hypothesis tests and confidence intervals ; 6. Linear regression with multiple regressors ; 7. Hypothesis tests and confidence intervals in multiple regression ; 8. nonlinear regression functions ; 9. Assessing studies based on multiple regression -- Part III. Further topics in regression analysis : 10. Regression with panel data ; 11. Regression with a binary dependent variable ; 12. Instrumental variables regression ; 13. Experiments and quasi-experiments ; 14. Prediction with many regressors and big data -- Part IV. Regression analysis of economic time series data ; 15. Introduction to time series regression and forecasting ; 16. Estimation of dynamic causal effects ; 17. Additional topics in time series regression -- Part V. The economic theory of regression analysis ; 18. The theory of linear regression with one regressor ; 19. The theory of multiple regression.

"Designed for a first course in undergraduate and introductory econometrics, this text reflects modern theory and practice. With riveting empirical applications as well as real-world examples and data integrated into the development of the theory, the authors ensure that students grasp the relevance of econometrics by providing an effective treatment of the substantive findings of the resulting empirical analysis. New to this edition : Chapter on "Big Data" and machine learning methods ; Parallel treatment of prediction and causal inference using regression ; Brand new general interest boxes, like "The distribution of adulthood earnings in the United Kingdom by Childhood Socioeconomic Circumstances" and "Conditional cash transfers in Rural Mexico to increase school enrollment," that focus on contemporary and global choice of topics ; Coverage of realized volatility as well as autoregressive conditional heteroskedasticity ; Concept exercises in MyLab that focus on core concepts and economic interpretations." -- Back cover.

ISBN: 9781292264455

Nat. Bib. No.: GBB976524bnbSubjects--Topical Terms:

182271
Econometrics.

LC Class. No.: HB139 / S76 2020

Dewey Class. No.: 330.015195

Introduction to econometrics /
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260 $a Harlow, United Kindom : $b Pearson, $c c2020.
300 $a 797 p. : $b col. ill. ; $c 26 cm.
490 1 $a The Pearson series in economics
500 $a Previous edition: 2015.
500 $a "Authorized adaptation from the United States edition, entitled Introduction to Econometrics , 4th Edition, ISBN 978-0-13-446199-1 by James H. Stock, Mark W. Watson, published by Pearson Education c2020"--T.p. verso.
504 $a Includes bibliographical references (p. 771-774) and index.
505 0 $a Part I. Introduction and review : 1. Economic questions and data ; 2. Review of probability ; 3. Review of statistics -- Part II. Fundamentals of regression analysis : 4. Linear regression with one regressor ; 5. Regression with a single regressor: hypothesis tests and confidence intervals ; 6. Linear regression with multiple regressors ; 7. Hypothesis tests and confidence intervals in multiple regression ; 8. nonlinear regression functions ; 9. Assessing studies based on multiple regression -- Part III. Further topics in regression analysis : 10. Regression with panel data ; 11. Regression with a binary dependent variable ; 12. Instrumental variables regression ; 13. Experiments and quasi-experiments ; 14. Prediction with many regressors and big data -- Part IV. Regression analysis of economic time series data ; 15. Introduction to time series regression and forecasting ; 16. Estimation of dynamic causal effects ; 17. Additional topics in time series regression -- Part V. The economic theory of regression analysis ; 18. The theory of linear regression with one regressor ; 19. The theory of multiple regression.
520 $a "Designed for a first course in undergraduate and introductory econometrics, this text reflects modern theory and practice. With riveting empirical applications as well as real-world examples and data integrated into the development of the theory, the authors ensure that students grasp the relevance of econometrics by providing an effective treatment of the substantive findings of the resulting empirical analysis. New to this edition : Chapter on "Big Data" and machine learning methods ; Parallel treatment of prediction and causal inference using regression ; Brand new general interest boxes, like "The distribution of adulthood earnings in the United Kingdom by Childhood Socioeconomic Circumstances" and "Conditional cash transfers in Rural Mexico to increase school enrollment," that focus on contemporary and global choice of topics ; Coverage of realized volatility as well as autoregressive conditional heteroskedasticity ; Concept exercises in MyLab that focus on core concepts and economic interpretations." -- Back cover.
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700 1 $a Watson, Mark W. $3 323803
830 0 $a Pearson series in economics. $3 490868