EC 510/410 Econometric Analysis of Panel Data

Fall 2015, 6:40-8:30pm TTH (TBA)
Prof. K.-P. Lin (CH 241G, 725-3931)
Office Hours: 3:30-4:30 TTH & by appointment

This is a course on applied econometrics dealing with '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.) and/or time effects. We will begin with a review of the standard linear regression model, then apply it to panel data settings involving 'fixed', 'random', and 'mixed' effects. The basic model will be extended to spatial and dynamic models with recently developed GMM and instrumental variables methods. We will consider numerous applications from the literature, including static and dynamic panel data regression models.

Basic understanding of econometric analysis is required (EC 469, 569, 570 or equivalent). Knowledge of calculus, algebra, probability theory and statistics are essential for this course. Familiar with computer programming and econometric packages will be useful. The programming language and packages in R will be used throughout the course. Optionally, Stata may be used with limited support.

Texts and Software

• Required:
  • B. H. Baltagi, Econometric Analysis of Panel Data, 4th ed., John Wiley, New York, 2008.
  • W. H. Greene, Econometric Analysis, 7th ed., Chapter 11: Models for Panel Data (and selected sections in Chapters 13 and 17), Prentice Hall, 2011.
  • Download and install R from The Comprehensive R Archive Network, and RStudio.
• Recommended:
  1. M. Arellano, Panel Data Econometrics, Oxford University Press, 2003.
  2. A. Colin Cameron and Pravin K. Trivedi, Microecometrics: Methods and Applications, Part V, Models for Panel Data, Cambridge University Press, 2005.
  3. C. Hsiao, Analysis of Panel Data, 3rd ed., Cambridge University Press, 2014.
  4. J. M. Wooldridge, Econometric Analysis of Cross Section and Panel Data, 2nd ed., The MIP Press, 2010.

Topics

1. Reviews of Basic Econometrics
   1. Simple and Multiple Regression
   2. System of Regression Equations
   3. Model Estimation: OLS, IV, 2SLS, 3SLS
   4. Hypothesis Testing and Inference
2. Panel Data Analysis: Basic
   1. Pooled Model
   2. Fixed Effects Model
   3. Random Effects Model
   4. First-Difference Model
3. Panel Data Analysis: Extensions
   1. Heteroscedasticity and Autocorrelation
   2. Instrumental Variable and GMM Estimation
   3. Hypothesis Testing and Inference
4. Time Series Panel Data
   1. Time Series Correlation in Panel Data
   2. Dynamic Panel Data Analysis
5. Spatial Panel Data
   1. Spatial Correlation in Panel Data
   2. Panel Spatial Econometric Models
6. Advanced Topics (Time Permitting)
   1. Nonlinear Panel Data: Probit, Logit, Tobit Models
   2. Time-Space Autoregressive and Moving Average

Lecture Notes

Case Study and Homework

Expectation

1. There will be a mid-term (October ?, in class) and a final exam (December ?, 5:30pm). In addition, 3 or 4 homeworks will be assigned periodically (due every 2 weeks in average).
2. A course project is required for graduate students taking this course EC510. The project must be a panel data econometric model. A one-page project proposal is due on or before October ? for approval. Final report of the project is then due on or before December ?.
3. Grade distribution of this course looks like this:

   	EC410	EC510
   Mid-Term	40%	30%
   Final	40%	30%
   Project		20%
   Homeworks	20%	20%