B55.9912: Econometric Analysis of Panel Data

Class Notes

Professor William Greene
Department of Economics
Office:MEC 7-78, Ph. 998-0876, Fax. 995-4218
e-mail:wgreene@stern.nyu.edu
URL: http://www.stern.nyu.edu/~wgreene

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Abstract: This is an intermediate level, Ph.D. course in the area of  Applied Econometrics dealing with Panel Data.  The range of topics covered in the course will span a large part of econometrics generally, though we are particularly interested in those techniques as they are adapted to the analysis of 'panel' or 'longitudinal' data sets.  Topics to be studied include specification, estimation, and inference in the context of models that include individual (firm, person, etc.) effects.  We will  begin with a development of the standard linear regression model, then extend it to panel data settings involving 'fixed' and 'random' effects.  The asymptotic distribution theory necessary for analysis of generalized linear and nonlinear models will be reviewed or developed as we proceed.. We will then turn to instrumental variables, maximum likelihood, generalized method of moments (GMM), and two step estimation methods.  The linear model will be extended to dynamic models and recently developed GMM and instrumental variables techniques.   The classical methods of maximum likelihood and GMM and Bayesian methods, expecially MCMC techniques, are applied to models with individual effects.  The last third of the course will focus on nonlinear models.  Theoretical developments will focus on heterogeneity in models including random parameter variation, latent class (finite mixture) and 'mixed' and hierarchical models.  We will also visit the theory for  techniques for optimization in the setting of nonlinear models.  We will consider numerous applications from the literature, including static and dynamic regression models, heterogeneous parameters models (e.g., Fama-Macbeth), random parameter variation, and specific nonlinear models such as binary and multinomial choice and models for count data. 

Notes: The following list points to the class discussion notes for Econometric Analysis of Panel Data. These are Powerpoint .ppt files.  Individual sets of notes may correspond to more or less than a full day of class.

*********** Notes 1 ************

Class 1. Introduction to Econometrics; Introduction to the course
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Class 2. Statistical Models: Estimation and Testing; The linear model
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Class 3. Models with Individual Effects
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Class 4. Fixed Effects and Hierarchical Models
*********** Notes 4-A ************
Class 4-A. Minimum Distance Estimation
*********** Notes 5 ************
Class 5. Random Effects Models

*********** Notes 6 ************

Class 6. Random Effects Model: Maximum Likelihood Estimation. Panel Data Structures
*********** Notes 7 ************
Class 7. Extensions of Effects Models; Heteroscedasticity, Measurement Error, Spatial Autocorrelation,...
*********** Notes 8 ************
Class 8. Instrumental Variables; The Hausman-Taylor Estimator, GMM Estimation

*********** Notes 9 ************

Class 9. GMM Estimation, Dynamic Models, Arellano/Bond/Bover, Schmidt and Ahn
*********** Notes 10 ************
Class 10. Dynamic Models, Time Series, Panels and Nonstationary Data
*********** Notes 11 ************
Class 11. Heterogeneous Parameter Models (Fixed and Random Effects), Two Step Analysis of Panel Data Models
*********** Notes 12 ************
Class 12. Random Parameters, Discrete Random Parameter Variation, Continuous Parameter Variation
*********** Notes 13 ************
Class 13. MIDTERM
*********** Notes 14 ************
Class 14. Nonlinear Models and Nonlinear Optimization; ML Estimation, M Estimation, GMM Estimation
*********** Notes 15 ************
Class 15. Classical Estimation of Nonlinear Effects Models; Random and Fixed Effects Binary Choice Models
*********** Notes 16 ************
Class 16. Random and Fixed Effects in Nonlinear Models, Quadrature and Simulation
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Class 17. Dynamic Discrete Choice Models and Incidental Parameters Problems
*********** Notes 18 ************
Class 18. Ordered Choices and Censored Dependent Variables - Microeconometrics
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Class 19. Limited Dependent Variable Models and Models for Count Data
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Class 20. Sample Sample Selection Models and Models of Attrition
*********** Notes 20A ************
Class 20-A. Hazard Function and Duration Models
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Class 21. Stochastic Frontiers and Efficiency Estimation, Applications from the Stochastic Frontiers Literature
*********** Notes 22 ************
Class 22. Random Parameters Models, Heterogeneity, Second Generation, Simulation Based Estimation
*********** Notes 23 ************
Class 23. Modeling Heterogeneity

*********** Notes 24 ************

Class 24. Bayesian Estimation Gibbs Sampling, Markov Chain Monte Carlo, Multinomial Choice, Economics and Marketing Application
*********** Notes 25 ************
Class 25. Semiparametric Approaches


*********** Final Exam ************ FINAL EXAM (NO CLASS MEETING) CLICK HERE TO DOWNLOAD THE FINAL EXAMINATION

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