Statistical foundations for econometric techniques
著者
書誌事項
Statistical foundations for econometric techniques
(Economic theory, econometrics, and mathematical economics)
Academic Press, c1996
- : pbk
大学図書館所蔵 全52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
Bibliography: p. 541-562
Includes index
内容説明・目次
内容説明
"Statistical Foundations for Econometric Techniques" features previously unavailable material in a textbook format for econometrics students, researchers, and practitioners. Taking strong positions for and against standard econometric techniques, the book endorses a single best technique whenever possible. In many cases, the recommended optimal technique differs substantially from current practice. Detailed discussions present many new estimation strategies superior to conventional OLS and ways to use them. It evaluates econometric techniques and the procedures commonly used to analyze those techniques. It challenges established concepts. It introduces many techniques that are not available in other texts. It recommends against using the Durbin-Watson and Lagrange Multiplier tests in favor of tests with superior power. It provides many new types of estimation strategies superior to conventional OLS. It forms a judicious mixture of various methodological approaches. It illustrates Empirical Bayes estimators and robust regression techniques possessing a 50 per cent breakdown value.
目次
Lists of Symbols and Notation. Introduction. Estimators for Regression Models: Least Squares and Projections. Maximum Likelihood. Bayesian Estimators for Regression. Minimax Estimators. Robust Regression. Hypothesis Tests for Regression Models: Stringent Tests. UMP Invariant Hypothesis Tests. Some Tests for Regression Models. Applications: F and Related Tests. Similar Regression Models. Asymptotic Theory: Consistency of Tests and Estimators: Direct Methods. Consistency of Estimators: Indirect Methods. Asymptotic Distributions. More Accurate Asymptotic Approximations. Asymptotic Optimality of ML and LR. Empirical Bayes: Applications: Simple Examples. Utilizing Information of Uncertain Validity. Hierarchical Bayes and the Gibbs Sampler. Appendices: The Multivariate Normal Distribution. Uniformly Most Powerful Tests. A Review of Decision Theory. Bibliography. Index.
「Nielsen BookData」 より