Econ/ARE 240D

Department of Economics
University of California - Davis
Winter 2012

Professor Colin Cameron
SSH Building 1124   (530) 564-0630

Tues Thurs 10.00 – 11.50 a.m. Wickson 1038

Office Hours:
Tuesday afternoon     3.00 - 5.00 p.m.
Thursday morning       9.00 a.m. – 9.50 a.m.

Teaching Assistant:
Lucas Herrenbrueck  
Office Hours: Wednesday 9.30 - 11.30 a.m.

Course Goals: (1) To be able to perform estimation and testing in non-linear cross-section regression models, (2) to be sufficiently comfortable with asymptotic theory for nonlinear models to be able to read econometrics articles in journals such as Econometrica and Journal of Econometrics, (3) to be able to implement cross-section methods as needed for Ph.D. thesis.

Pre-requisites: The listed pre-requisite is Econ / Ag Econ 240B.
The essential pre-requisite is a good understanding of the linear regression model with matrix algebra.

Course Outline:
Class 1 0.5 class Introduction: Linear Models
    CT: 4.4-4.5.  Gr: 3.2, 5.2.  W: 4.2. 
Class 2 1.5 classes Introduction: Review of Asymptotic Theory
    CT: Appx.A.  Am: 3.   Gr: AppxD.  W: 3.1-3.4
Classes 3-4
2 classes Estimation: Extremum and M-estimators
    CT: 5.2-5.5  Am: 4.1.   Gr: 16.5.  W: 12.1-12.3
 Class 5 1 class Estimation: Iterative Methods for Computation
    CT: 10.2-10.3.  Am: 4.4.   Gr: AppxE  W: 12.7.
Class 6-7
1 class Estimation: ML and NLS
    CT: 5.6-5.8  Am: 4.3  Gr: 9.2, 21.1-4  W: 12.4, 13.1-5
Class 8-9, 11-12 4 classes Models: Logit and probit (binary and multinomial outcomes)

  CT: 14.1-14.4, 15.1-15.5, 15.9.  Am: 9.1-9.3.
Gr: 21.1-21.8.  Mad: 2-3.  W: 15.1-15.6, 15.9-15.10.
Class 10 1 class Midterm Exam.
Class 13-14  2 classes Models: Tobit

CT: 16.1-16.6.  Am: 10.1-10.7.   
Gr: 22.1-22.4.  Mad: 6.1-6.6, 8.1-8.5.  W: 16.1-16.6
Class 15 1 class Estimation: GMM
    CT: 6.1-6.5.  Gr 18.1-18.3.  W: 14.1-14.2
Class 16 1 class Testing, bootstrap methods
    CT: 7.1-7.4, 8.2-8.3. Gr: 17.5, AppxE.4. 
W: 12.6, 13.6.
Class 17-20 4 classes Panel data
    CT: 21.1-21.8.  Am: 6.4, 6.6-6.8.
Gr: 13.1-13.4.  Wooldridge 10.1-10.7.

CT=Cameron&Trivedi, Am=Amemiya, DM=Davidson&MacKinnon, Gr=Greene, Mad=Maddala,
W = Wooldridge.

Required Material:

Cameron, A.C. and P.K. Trivedi (2005), Microeconometrics: Methods and Applications, Cambridge University Press.

Much of the class will follow this book. The book is at times more detailed than what will be covered in this class.

Recommended Material:

These are more than you can buy but are good to have in a microeconometrics library.  I have not ordered these for the bookstore, but still recommend their purchase - in the sequence close to what I would consider buying them in. You should already have Greene. These books can be ordered on-line.

Greene, W.G. (2007), Econometric Analysis, 6th edition, Prentice-Hall.

Wooldridge, J.M. (2010), Econometric Analysis of Cross Section an Panel Data, 2nd edition, MIT Press.

Maddala, G.S. (1983), Limited-Dependent and Qualitative Variables in Economics, Cambridge University Press.

Amemiya, T. (1985), Advanced Econometrics, Harvard University Press.

Davidson, R. and J.G. MacKinnon (2004), Econometric Theory and Methods, Oxford University Press.

Cameron, A.C. and P.K. Trivedi (1998), Regression Analysis of Count Data.

Cameron, A.C. and P.K. Trivedi (2009, revised ed. 2010), Microeconometrics using Stata, Stata Press.

Greene (which you should have from 240A,B) is useful for more elementary treatment of topics.
Wooldridge is at similar level to Cameron and Trivedi with more on linear models and not as much on nonlinear models and related topics. It is also more formal econometrically.
The second edition is a significant expansion on the first edition, especially Nonlinear Models and Related Topics.
Maddala is the standard reference for introductory treatment of probit, logit and probit models and is cheap in paperback.
Amemiya was the standard book before D&M (1993) and even now has an excellent advanced treatment of limited dependent and discrete choice models.
D&M is an updated and somewhat less advanced version of Davidson, R. and J.G. MacKinnon (1993), Estimation and Inference in Econometrics, Oxford University Press. It emphasises econometric theory.
Cameron and Trivedi (1998) focuses on count data models, but includes many general results and approaches for nonlinear regression, especially in chapters 3 and 5, and is cheap in paperback.
Cameron and Trivedi (2009, 2010) focuses on use of Stata and covers most microeconoemtrics models.

These recommended books emphasize cross-section data. For panel data, which we have little time for in this course, Cameron & Trivedi and Wooldridge provide considerable coverage.
In addition econometrics panel data books are:
Baltagi, B.H (2001), Econometrics Analysis of Panel Data, 2nd edition, Wiley.
Hsiao, C. (2003), Analysis of Panel Data, 2nd edition, Cambridge University Press.
Lee, M.J. (2010), Microeconometrics: Methods of Moments and Limited Dependent Variables, 2nd edition, Springer.
Arellano M. (2003), Panel Data Econometrics, Oxford University Press.

Additional Materials:

Selected papers can generally be downloaded from the web, mostly using JStor.

Computer Materials:

Stata: Assignments will use STATA. STATA is available on both Econ and ARE computers.  
More complicated models require use of a matrix programming language. We will use the new MATA inrtroduced in Stata 9, rather than GAUSS or MATLAB. 

Most course material is at  (some is at )
Some further computer information will be available at my personal home page:

Course Grading:

Assignments 15%
Best 5 out of 6. Last assignment is compulsory. Each worth 3%.
Due Thursdays Jan 19, 26; Feb 2, 23; March 8, 15.

Midterm 35%
Thursday Feb 9  in class

Final 50%
Saturday March 24   3.30 – 5.30 p.m. Comprehensive.

Assignments must be handed in on time, so solutions can be discussed in class and distributed in a timely manner.
No credit for late assignments. Lowest assignment score is dropped.
Academic integrity is required. What is academic integrity? See the UCD Student Judicial Affairs website
As an exception to their rules, I permit some collaboration with other students in doing assignments, but the work handed in must be your own. Each person must create their own Stata output and write up their own answers. And you are to write on your assignment the name of the person(s) you worked with.
Exams will be closed book. The final exam is comprehensive.