Econ 720
Advanced Econometrics
Spring 2003
Instructor: Professor Kao, Eggers 438, 443--3233,
email: cdkao@maxwell.syr.edu
Time and Location: Wednesday 3:30-6.00, ?
Office Hours: MW 4-5
Textbooks:
(L) Lee, M. J. (2002), Panel Data Econometrics, Academic Press.
(N) Nerlove, M. (2002), Essays in Panel Data Econometrics, Cambridge.
The purpose of this course is to provide students with a firm knowledge and understanding of the econometric methods used in microeconometrics and financial econometrics research. Modern microeconometrics and financial econometrics research are characterized by a heavy interplay between economic/finance theory and econometrics. The structure of the course will reflect that interplay by letting explicit theoretical microeconomic and financial models motivate each of the econometric methods taught.
Grading: There will be weekly assignments, and two exams.
They will count toward the grade as follows.
Introduction
Hansen, L. P. (2001), "Generalized Method of Moments Estimation: A Time Series Perspective," Working Paper, University of Chicago.
Hansen, B. E., and West, K. D. (2002), "Generalized Method of Moments and Macroeconomics," Journal of Business & Economic Statistics, 20, 460 - 469.
Jagannathan, R, Skoulakis, G., and Wang, Z. (2002), "Generalized Method of Moments: Applications in Finance," Journal of Business & Economic Statistics, 20, 470 - 481.
Tests for Model Specification
Hausman, J. A. (1978), "Specification Tests in Econometrics," Econometrica, 46, 1251-1271.
White, H. (1981), "Consequence and Detection of Misspecified Nonlinear Regression Models," Journal of the American Statistical Association, 76, 419-433.
Bierens, H. J. (1982), "Consistent Model Specification Tests," Journal of Econometrics, 20, 105-134.
Newey, W. K. (1985), "Maximum Likelihood Specification Testing and Conditional Moment Tests," Econometrica, 53, 1047-1070.
Asymptotic Distribution Theory
Lecture Notes on Asymptotic Theory:
web.mit.edu/14.381/www/matrix2.pdf.
www.ssc.wisc.edu/~bhansen/notes/chapter5.pdf.
www.econ.ohio-state.edu/lee/econ742/homework/ec742-ch2.PDF.
Newey, W. K. (1994), "Large Sample Estimation and Hypothesis Testing," Handbook of Econometrics Volume 4, Chapter 36, 2113 - 2148.
Wooldridge, J. M. (1994), "Estimation and Inference for Dependent Processes," Handbook of Econometrics Volume 4, Chapter 45, 2641 - 2695. www.elsevier.com/hes/books/02/04/045/c0204045.htm.
Generalized Method of Moments (GMM):
Lecture Notes on GMM Estimation:
web.mit.edu/14.384/www/384lecture10.pdf.
http://www.ssc.wisc.edu/~bhansen/notes/chapter11.pdf.
Hansen, L. P. (1982), "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, 50, 1029-1054.
Hansen, L. P., and Singleton, K. J. (1982), "Generalized Instrumental Variables Estimation of Nonlinear Rational Expectations Models," Econometrica, 50, 1269-1286.
Hansen, L. P., and Singleton, K. J. (1983), "Stochastic Consumption, Risk Aversion, and the Temporal Behavior of Asset Returns" Journal of Political Economy, 91, 249-265.
Hansen, L. P., and Singleton, K. J. (1984), "Errata," Econometrica, 52, 267-268.
Efficiency Bounds
Hansen, L., Heaton, J., and Ogaki, M. (1988), "Efficiency Bounds Implied by Multiperiod Conditional Moment Restrictions," Journal of the American Statistical Association, 83, 863-871.
Hansen, L. P. (1985), "A Method of Calculating Bounds on the Asymptotic Covariance Matrices of Generalized Method of Moments Estimators," Journal of Econometrics, 30, 203-238.
West, K. (2001), "On Optimal Instrumental Variables Estimation of Stationary Time Series Models," International Economic Review, 42, 1043 - 1050.
Feasible Estimation
Koenker, R., and Machado, J. A. F. (1999), "GMM Inference When the Number of Moment Conditions is Large," Journal of Econometrics, 93, 327 - 344.
West, K. D., Wong, K.-F., and Anatolyeve, S. (2001), "Instrumental variables estimation of heteroskedastic linear models using all lags of instruments,"
netec.mcc.ac.uk/WoPEc/data/Papers/attwimass200120.html.
Weight Matrix
Grenander, U., and Rosenblatt, M. (1953), "Statistical Spectral Analysis aArising from Stationary Stochastic Processes," Annals of Mathematical Statistics, 24, 537-558.
Parzen, E. (1957), "On Consistent Estimates of the Spectrum of a Stationary Time Series," Annals of Mathematical Statistics, 28, 329-348.
Andrews, D. W. K. (1991), "Heterokedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, 59, 817-858.
Newey, W. K., and West, K. D. (1987), "A Simple Positive Semi-Definite Heterokedasticity and Autocorrelation Consistent Covariance Matrix," Econometrica, 55, 703-708.
Newey, W. K., and West, K. D. (1994), "Automatic Lag Selection in Covariance Matrix Estimation," Review of Economic Studies, 61, 631-653.
Bootstrap
Lecture Notes on Boostrap: http://www.ssc.wisc.edu/~bhansen/notes/chapter7.pdf.
Hall, P., and Horowitz, J. L. (1996), "Boostrap Critical Values for Tests Based on Generalized-Method-of-Moments Estimators with Dependent Data," Econometrica, 64, 891-916.
Andrews, D. W. K. (2002), "Higher-Order Improvements of a Computationally Attractive k-step Boostrap for Extremum Estimators," Econometrica, 70, 119-162.
Brown, B. W., and Newey, W. K. (2002), "Generalized Method of Moments, Efficient Bootstrapping, and Improved Inference," Journal of Business & Economic Statistics, 20, 507-517.
Weak Instruments
Stock, J. H.,Wright, J. H., and Yogo, M. (2002), "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, 20, 518-529.
Bekker, P. A. (1994), "Alternative Approximations to the Distributions of Instrumental Variable Estimators," Econometrica, 62, 657-681.
Buse, A. (1992), "The Bias of Instrumental Variable Estimator," Econometrica, 60, 173-180.
Bound, J., Jaeger, D. A., and Baker, R. (1995), "Problems with Instrumental Variables Estimation When the Correlation Between Instruments and the Endogenous Explanatory Variable Is Weak," Journal of the American Statistical Association, 90, 443-450.
Staiger, D., and Stock, J. H. (1997), "Instrumental Variables Regressions with Weak Instruments," Econometrica, 65, 557-586.
Stock, J. H., and Wright, J. H. (2000), `GMM with Weak Identification," Econometrica, 68, 1055-1096.
Neely, C. J., Roy, A., and Whiteman, C. H. (2001), "Risk Aversion Versus Intertemporal Substitution: A Case Study of Identification Failure in the Intertemporal Consumption Capital Asset Pricing Model," Journal of Business & Economic Statistics, 19, 395-493.
Yogo, M., (2002), "Estimating the Elasticity of Intertemporal Substitution when Instruments are Weak," http://www.bus.qut.edu.au/esam02/program/papers/Yogo_Motohiro.pdf.
Stock, J. H., and Yogo, M., (2001), "Testing for Weak Instruments in Linear IV Regression,"
http://www.nber.org/papers/t0284.pdf.
Dynamic Panel Models
Nerlove, Chapters, 2, 3, 4, 6, 7, 8.
Lee, Chapter 3.
Dynan, K. E. (2000), "Habit Formation in Consumer Preferences: Evidence From Panel Data," American Economic Review, 90, 391-406.
Ahn, S. C. and Schmidt, P. (1995), "Efficient Estimation of Models for Dynamic Panel Data," Journal of Econometrics, 68, 5-27.
Ahn, S. C. and Schmidt, P. (1997), "Efficient Estimation of Models for Dynamic Panel Data: Alternative Assumptions and Simplified Estimation," Journal of Econometrics, 76, 309-321.
Anderson, T. W. and Hsiao, C. (1982), "Formulation and Estimation of Dynamic Models Using Panel Data," Journal of Econometrics, 18, 47-82.
Arellano, M. and Bond, S. (1991), "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, 58, 277-297.
Arellano, M. (1993), "On the Testing of Correlated Effects With Panel Data," Journal of Econometrics, 59, 87-97.
Arellano, M. and Bover, O. (1995), "Another Look at the Instrumental Variables Estimation of Error-Component Models," Journal of Econometrics, 68, 29-51.
Arellano, M., and Honore, B. (2001), "Panel Data Models: Some Recent Developments," Working Paper. ftp://ftp.cemfi.es/wp/00/0016.pdf.
Baltagi, B., and Kao, C. (2000), "Non-stationary Panels, Cointegration in Panel and Dynamic Panels: A Survey," Advances in Econometrics, 15, forthcoming.
Balestra, P., and Nerlove, M. (1966), "Pooling cross-section and Time-Series Data in the Estimation of a Dynamic for a Dynamic Model: The Demand for Natural Gas," Econometrica, 34, 585-612.
Blundell, R. W., and Bond, S. (1998), "Initial Conditions and Moment Restrictions in Dynamic Panel Data Models," Journal of Econometrics, 87, 115-143.
Hahn, J. (1997), "Efficient Estimation of Panel Data Models with Sequential Moment Restrictions," Journal of Econometrics, 79, 1-21.
Hahn, J. (1999), "How Informative is the Initial Condition in the Dynamic Panel Model with Fixed Effects?" Journal of Econometrics, 93, 309-326.
Im, K. S., Ahn, S. C., Schmidt, P., and Wooldridge, J. M. (1999), "Efficient Estimation of Panel Models with Strictly Exogenous Explanatory Variables," Journal of Econometrics, 93, 177-201.
Judson, R. A., and Owen, A. L. (1999), "Estimating Dynamic Panel Data Models: A Guide for Macroeconomists," Economics Letters, 65, 9-15.
Kiviet,, J. F. (1995), "On Bias, Inconsistency and Efficiency of Some Estimators in Dynamic Panel Data Models," Journal of Econometrics, 68, 53-78.
Nerlove, M. (1971), "Further Evidence on the Estimation of Dynamic Economic Relations from a Time-Series of Cross-Sections," Econometrica, 39, 359-382.
Nickell, S. (1981), "Biases in Dynamic Models with Fixed Effects," Econometrica, 49, 1417-1426.
Limited Dependent Variables in Panel Data
Lee, Chapters 4-6.
Honore, B. E. (1992), "Trimmed LAD and Least Squares Estimation of Truncated and Censored Regression Models with Fixed Effects," Econometrica, 60, 533-565.
Honore, B. E., and Kyriazidou, E. (2000), "Estimation of Tobit-Type Models with Individual Specific Effects," Econometric Review, 19, 341-366.
Kyriazidou, E. (1997), "Estimation of a Panel Data Sample Selection Model," Econometrica, 65, 1335-1364.