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Advanced Econometrics I

Опубликовано на портале: 23-04-2003
Факультет: Economics
Дисциплина: Econometrics
Год: Fall 1999-2000
Язык: Английский
Тематические разделы: Экономика, Эконометрика

This course has two goals. The first is to provide students with a working knowledge of asymptotic statistical methods. The second is to apply these statistical concepts to study the large-sample properties of all commonly used econometric models.

The first half of the course focuses on deriving the large-sample properties of estimators defined as the solution to an optimization problem, under a variety of assumptions for the true data generation process. These large-sample results are applied to the maximum likelihood and nonlinear least squares estimators. Extensions to the case of nonlinear instrumental variables estimators, including the generalized method of moments estimator, are then presented. Various asymptotic testing procedures are derived for this general modeling framework.

The remainder of the course is devoted to several topics on the frontier of econometric theory research. The first is simulation estimation. Simulated maximum likelihood and simulated method of moments estimators will be presented and their large-sample properties discussed. The basics of non-parametric econometric techniques (specifically, kernel-based and spline-smoothing methods) and their large-sample properties will then be presented. The third topic to be studied is semiparametric estimation. The major issues to be discussed are identification and efficiency bounds in semiparametric models, in addition to the large sample properties of these estimators.

Required Textbooks:
A.W. Van Der Vaart, Asymptotic Statistics, Cambridge University Press, 1998 (AS).

Supplementary Textbooks:

Takeshi, Amemiya, Advanced Econometrics, Harvard University Press, 1985 (AE).

Christian Gourierioux and Alain Monfort, Simulation-Based Econometric Methods, 1996, (SBEM).

Gallant, A.R. Nonlinear Statistical Models, 1987, (NSM).

Halbert White, Asymptotic Theory for Econometricians, Academic Press, 1984 (ATE).

Charles F. Manski, Analog Estimation Methods in Econometrics, Chapman and Hall, 1988 (AEME).

Bernard W. Silverman, Density Estimation for Statistics and Data Analysis, Chapman and Hall, 1986 (DE).

Peter Bickel, Chris Klaasen, Ya'acov Ritov and Jon Wellner, Efficient and Adaptive Estimation for Semiparametric Models, Johns Hopkins, 1993, (BKRW).

Gallant, A.R. (1997) An Introduction to Econometric Theory, Princeton University Press, Princeton, New Jersey. [A very readable introduction to measure theory for economists.]