Topics in Microeconometrics
Professor William Greene
June 1-3, 2011
Professor William. Greene
Professor’s Home Page: http://www.stern.nyu.edu/~wgreene
This course will introduce the student to methods used to model cross section and panel data. We will depart from the linear regression model to specifications for binary and censored data, ordered choices, count data and multinomial choices. The discussion will present basic models for cross section data then introduce theory and methods for extensions to panel data and stated choice experiments..
This is a course in econometric analysis of cross section and panel data. There are a huge variety of models that are used in this context. We will focus on five which arguably comprise the foundation for the area: the linear regression model, the fundamental model of binary choice (and a number of variants); models for ordered choices; the Poisson regression model for count data; and the fundamental model for multinomial choice, the multinomial logit model. Discussions will cover the topics listed below.
Prior knowledge is assumed to include calculus at the level assumed in the first year of a Ph.D. program in economics and a course in econometrics at the beginning Ph.D. level using a textbook such as Greene, W., Econometric Analysis, 6th edition.
No specific textbook is assigned for the course. Useful references are
Greene, W., Econometric Analysis, 6th Ed., Prentice Hall, 2008
Cameron, A.C. and P. Trivedi, Microeconometrics: Methods and Applications,
Press, 2005. Cambridge University
A lower level textbook that discusses some of the topics we will visit is Wooldridge, J., Introduction to Econometrics: A Modern Approach, Southwestern, 2008
Some of the presentation will be based on Econometric Analysis, 7th ed., by Greene, W. (Prentice Hall, 2011). Six chapters are included with the course materials: Left click to activate. Right click to download
Chapter 11: Models for Panel Data Greene-Chapter-11.pdf (Panel data models)
Chapter 12: Estimation Methods Greene-Chapter-12.pdf (Estimation methods)
Chapter 14: Maximum Likelihood Greene-Chapter-14.pdf (Maximum likelihood estimation)
Chapter 15: Simulation Based Estimation and Inference Greene-Chapter-15.pdf (Simulation based estimation)
Chapter 17: Models for Discrete Data Greene-Chapter-17.pdf (Discrete choice models)
Chapter 18: Models for Unordered and Ordered Choices Greene-Chapter-18.pdf (Ordered and Unordered Choice Models)
Chapter 19: Limited Dependent Variable Models Greene-Chapter-19.pdf (LDV Models: Censoring, Truncation and Sample Selection)
Course Materials and Resources
II. Class Notes: These are Powerpoint slide presentations for use during the class sessions.
III. Software: The exercises in the labs will be done using NLOGIT. A copy for students to install on their own computers, that is useable for the duration of the course and a short while afterward, will be distributed by the organizers. Students may also download the installation kit for the software from the course home page. NOTE: This version of NLOGIT will work from May 1, 2011 to June 15, 2011.
IV. Lab Sessions:
LAB 1: Regression Models
LAB 2: Discrete Choice
LAB 3: Nonlinear Models, Heterogeneity, Multinomial Choice
V. Data Sets: