Credit

3.00   (L-T-P:   3-0-0)

Department / Center / School / Unit

Economics

Course Objectives

The primary objective of this course is to provide an advanced treatment of econometric methods for cross section and panel data including linear and non-linear models. Some selected topics are instrumental variable estimation, estimation of system of equations, estimation of panel data models, maximum likelihood estimation, generalised method of moments, discrete response models, censored regression models and estimation of average treatment effects.

Course Contents

Course contents (about 100 words) (Include laboratory/design activities):
1. Review of Classical Linear Regression Model:
Gauss-Markov assumptions, finite sample properties, large sample properties
2. Instrumental Variable Estimation:
Motivation for instrumentation, Simultaneity Bias, Endogeneity and Measurement Error; IV Estimation; 2SLS Estimation
3. Generalized Method of Moments:
Single equation linear GMM
4. Systems of Equations
Seemingly Unrelated Regressions (SUR) model; Simultaneous Equations Models: Identification
5. Panel Data models:
Pooled Estimation; Unobserved Heterogeneity: Fixed vs. Random Effects; ML vs. GMM estimation
6. Discrete Choice Models:
Binary response models, Multinomial Response Models, Ordered Response Models
7. Censored Regression Models:
Estimation and Inference with Censored Tobit
8. Estimating Average Treatment Effects:
Regression Methods, Methods Based on the Propensity Score, Estimating the ATE Using IV

Suggested References

1. Greene, W. H., Econometric Analysis, (7th edition), Pearson Prentice Hall, 2011
2. Wooldridge, J. M., Econometric Analysis of Cross Section and Panel Data, (2nd edition), The MIT Press, 2010
3. Angrist, J. D. and Pischke, J., Mostly Harmless Econometrics: An Empiricist's Companion, Princeton University Press, 2009
Apart from text books, readings from published journal articles will be suggested during the course.