Econometrics by example
著者
書誌事項
Econometrics by example
Palgrave, 2015
2nd ed
- : pbk
大学図書館所蔵 全16件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Previous ed.: 2011
Includes index
内容説明・目次
内容説明
The second edition of this bestselling textbook retains its unique learning-by-doing approach to econometrics. Rather than relying on complex theoretical discussions and complicated mathematics, this book explains econometrics from a practical point of view by walking the student through real-life examples, step by step. Damodar Gujarati's clear, concise, writing style guides students from model formulation, to estimation and hypothesis-testing, through to post-estimation diagnostics. The basic statistics needed to follow the book are covered in an appendix, making the book a flexible and self-contained learning resource.
The textbook is ideal for undergraduate students in economics, business, marketing, finance, operations research and related disciplines. It is also intended for students in MBA programs across the social sciences, and for researchers in business, government and research organizations who require econometrics.
New to this Edition:
- Two brand new chapters on Quantile Regression Modeling and Multivariate Regression Models.
- Two further additional chapters on hierarchical linear regression models and bootstrapping are available on the book's website
- New extended examples accompanied by real-life data
- New student exercises at the end of each chapter
Accompanying online resources for this title can be found at bloomsburyonlineresources.com/econometrics-by-example-2. These resources are designed to support teaching and learning when using this textbook and are available at no extra cost.
目次
PART I: BASICS OF LINEAR REGRESSION
1. The Linear Regression Model
2. Functional Forms of Regression Models
3. Qualitative Explanatory Variables Regression Models
PART II: REGRESSION DIAGNOSTICS
4. Regression Diagnostic I: Multicollinearity
5. Regression Diagnostic II: Heteroscedasticity
6. Regression Diagnostic III: Autocorrelation
7. Regression Diagnostic IV: Model Specification Errors
PART III: REGRESSION MODELS WITH CROSS
SECTIONAL DATA
8. Stochastic Regressors and the Method of Instrumental Variables
9. The Logit and Probit Models
10. Multinomial Regression Models
11. Ordinal Regression Models
12. Limited Dependent Variable Regression Models
PART IV: TIME SERIES ECONOMETRICS
13. Modeling Count Data
14. Stationary and Nonstationary Time Series
15. Conintegration and Error Correction Models
16. Asset Price Volatility: the ARCH and GARCH Models
PART V: SELECTED TOPICS IN ECONOMETRICS
17. Economic Forecasting
18. Panel Data Regression Models
19. Stochastic Regressors and the Method of Instrumental Variables
20. Quantile Regression Modeling
21. Multivariate Regression Models.
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