Generalized method of moments (GMM) estimation of nonlinear systems has two important advantages over conventional maximum likelihood (ML) estimation: GMM estimation usually requires less restrictive distributional assumptions and remains computationally attractive when ML estimation becomes burdensome or even impossible. This book presents an in-depth treatment of the conditional moment approach to GMM estimation of models frequently encountered in applied microeconometrics. It covers both large sample and small sample properties of conditional moment estimators and provides an application to empirical industrial organization. With its comprehensive and up-to-date coverage of the subject which includes topics like bootstrapping and empirical likelihood techniques, the book addresses scientists, graduate students and professionals in applied econometrics.
Populaire auteurs
Cram101 Textbook Reviews (948) J.S. Bach (447) Wolfgang Amadeus Mozart (305) Collectif (268) Schrijf als eerste een recensie over dit item (259) Doug Gelbert (238) Princess of Patterns (211) Charles Dickens (209) R.B. Grimm (197) Carolyn Keene (187) Jules Verne (183) Philipp Winterberg (180) William Shakespeare (174) Youscribe (172) Lucas Nicolato (169) Edgar Allan Poe (166) Herman Melville (166) Anonymous (165) Gilad Soffer (164) Robert Louis Stevenson (159)Populaire gewichtsboeken
418 KB 425 KB 435 KB 459 KB 445 KB 439 KB 386 KB 413 KB 493 KB 432 KB 455 KB 471 KB 421 KB 451 KB 485 KB 472 KB 416 KB 369 KB 419 KB 427 KB