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Period
5, 2000/01
prof.
Stanislav
Anatolyev
The course
features several very interesting and important issues of the
modern econometric theory. First, we will study nonparametric
estimation, which combines a strong applied context with a delicate
asymptotic theory. Second, we will see the beauty and elegance
of GMM ideas when dealing with construction of optimal instruments.
Last, but not least, we will focus on the models where distributional
assumptions happen to be incorrect, and a related issue of model
selection problem, the Big Brother of the R2.
TENTATIVE
SYLLABUS
I. Nonparametric
estimation (1.5 weeks)
- Discrete
regressors: estimation of mean regression
- Continuous
regressors: kernel estimation of density and mean regression
- Non-kernel
nonparametric methods: nearest neighbors, local polynomial
regression, spline regression, sieve estimation
- Nonparametric
estimation in time series
- Some
applications
Härdle,
W., Linton, O. Applied Nonparametric Methods, in
Handbook of Econometrics, Vol. 4, Elsevier Science,
North Holland
Heiler,
S. A Survey on Nonparametric Time Series Analysis.
Working paper.
II. Conditional
moment restrictions and optimal instruments (2.5 weeks)
- Conditional
vs. unconditional moment restrictions and allowable instruments
- Conditional
restriction in cross-sectional analysis: Chamberlain’s optimal
instrument
- Conditional
restriction in time series analysis: Hansen’s, West–Wong–Anatolyev’s
and Anatolyev’s optimal instruments
- Some
applications
Newey,
W. Efficient Estimation of Models with Conditional Moment
Restrictions, in Handbook of Statistics, Vol.
11, Ch. 16, Elsevier Science, North Holland
Chamberlain,
G. (1987). Asymptotic Efficiency in Estimation with Conditional
Moment Restrictions. Journal of Econometrics 34, 305-334.
Robinson,
P. (1987). Asymptotically Efficient Estimation in the
Presence of Heteroskedasticity of Unknown Form. Econometrica
55, 875-891.
Hayashi,
F., Sims, C. (1983). Nearly Efficient Estimation of Time
Series Models with Predetermined, but Not Exogenous, Instruments.
Econometrica 51, 783-798.
Hansen,
L., Singleton K. (1996). Efficient Estimation of Linear
Asset Pricing Models with Moving-Average Errors. Journal
of Business and Economic Statistics 14, 53-68.
West,
K. (1997). On Optimal Instrumental Variables Estimation
of Stationary Time Series Models. University of Wisconsin-Madison.
West,
K., Wilcox, D. (1996). A Comparison of Alternative Instrumental
Variables Estimators of a Dynamic Linear Model. Journal
of Business and Economic Statistics 14, 281-293.
West,
K., Wong K., Anatolyev S. (1998). Feasible Optimal Instrumental
Variables Estimation of Linear Models with Moving Average
Disturbances. University of Wisconsin-Madison.
Anatolyev,
S. (1999). Approximately Optimal Nonlinear Instrumental
Variables Estimation in Time Series Models. University of
Wisconsin-Madison.
- Misspecification
and model selection (3 weeks)
- Consistency
any asymptotic normality under misspecification
- Nested
and non-nested models
- Kullback–Leibler
discrepancy measure and Likelihood Ratio test
- Discrimination
between misspecified models
- Some
applications
Gourieroux,
C., Monfort, A. (1993) Pseudo-Likelihood Methods,
in Handbook of Statistics, Vol. 11, Ch. 16, Elsevier
Science, North Holland
Sawa,
T. (1978) Information Criteria for Discriminating Among
Alternative Regression Models. Econometrica 46, 677-694.
Pesaran,
M., Deaton, A. (1978) Testing Non-nested Nonlinear Regression
Models. Econometrica 46, 677-694.
White,
H. (1982) Maximum Likelihood Estimation of Misspecified
Models. Econometrica 50, 1-25.
Vuong,
Q. (1989) Likelihood Ratio Tests for Model Selection
and Non-nested Hypotheses. Econometrica 57, 307-333.
Smith,
R. (1992) Non-nested Tests for Competing Models Estimated
by Generalized Method of Moments. Econometrica 60, 973-980.
Monfort,
A. (1996) A Reappraisal of Misspecified Econometric Models.
Econometric Theory 12, 597-619.
Gourieroux,
C., Monfort, A. Non-nested Hypotheses, in Handbook
of Econometrics, Vol. 4, Elsevier Science, North Holland
Kitamura,
Y. (1997) Comparing Misspecified Dynamic Econometric
Models Using Nonparametric Likelihood. University of
Minnesota.
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