Political Science 787: Multivariate Analysis

Fall 2008
Monday 12-2 (5664 HH)
Professor: Walter R. Mebane, Jr.
Office: 7735 Haven Hall (734/763-2220); email wmebane@umich.edu
Office hours: Tue 2-4 or other times by appointment.
Course web page: http://www.umich.edu/~wmebane/fall07/ps787.html

Assignment Due Dates
due date	description	weight
TBA	several data analysis problems	75%
TBA	final take-home exam	25%

Reading Availability

Much of the course will refer to journal articles. I plan to follow or refer to a few chapters in the following.

Cameron, A. Colin, and Pravin K. Trivedi. 2005. Microeconometrics: Methods and Applications. Cambridge UP.

Class meeting and reading schedule

1. nonlinear models, MLE and asymptotics (Sep 15)
   • Cameron and Trivedi. Chapter 5 and Appendix A.

   • D. A. Freedman. 2006. On the so-called ``Huber Sandwich Estimator'' and ``robust'' standard errors. The American Statistician 60: 299-302.

2. selectivity (Sep 22)
   • Heckman, J. J. 1978. Dummy endogenous variables in a simultaneous equation system. Econometrica 46: 931-959.

   • Heckman, J. J. 1979. Sample selection bias as a specification error. Econometrica 47: 153-161.

   • David A. Freedman and Jasjeet S. Sekhon. 2008. Endogeneity in Probit Response Models. Working paper.

   • Pratt, John W. 1981. Concavity of the Log Likelihood. Journal of the American Statistical Association 76(373): 103-106.

3. generalized linear models and QMLE (Sep 29)
   • White, Halbert. 1982. ``Maximum Likelihood Estimation of Misspecified Models,'' Econometrica 50 (1): 1-25.

   • McCullagh, Peter. 1983. ``Quasi-likelihood Functions.'' Annals of Statistics 11 (Mar.): 59-67.

4. bounded influence estimation (Oct 6)
   • Stefanski, Leonard A., Raymond J. Carroll, David Ruppert. 1986. Optimally Bounded Score Functions for Generalized Linear Models with Applications to Logistic Regression. Biometrika 73 (Aug): 413-424.

   • Hampel, Frank R. and Peter J. Rousseeuw and Elvezio Ronchetti. 1981. The Change-of-Variance Curve and Optimal Redescending M-Estimators. Journal of the American Statistical Association 76 (Sep): 643-648.

   • Croux, Christophe and Peter J. Rousseeuw and Ola Hossjer. 1994. Generalized S-Estimators. Journal of the American Statistical Association 89 (Dec): 1271-1281.

   • Mebane, Walter. R., Jr., and Jasjeet S. Sekhon. 2004. Robust Estimation and Outlier Detection for Overdispersed Multinomial Models of Count Data. American Journal of Political Science 48 (April): 392-411.

5. BUGS and MCMC (Oct 13, 27)
   • Brooks, S. P. 1998. Markov chain Monte Carlo method and its application. The Statistician 47: 69-100.

   • Brooks, S. P. and A. Gelman. 1998. Alternative methods for monitoring convergence of iterative simulations. Journal of Computational and Graphical Statistics 7: 434-455.

   • Spiegelhalter, D. J., N. G. Best, B. P. Carlin and A. van der Linde. 2002. Bayesian measures of model complexity and fit (with discussion). J. Roy. Statist. Soc. B 64: 583-640.

   • OpenBUGS. http://mathstat.helsinki.fi/openbugs/

   • The BUGS Project. http://www.mrc-bsu.cam.ac.uk/bugs/

6. bootstrap and refinements (Nov 3)
   • Cameron and Trivedi. Chapter 11.

   • Barndorff-Nielsen, O. E., and D. R. Cox. 1984. ``Bartlett Adjustments to the Likelihood Ratio Statistic and the Distribution of the Maximum Likelihood Estimator,'' Journal of the Royal Statistical Society. Series B (Methodological) 46 (3): 483-495.

7. hypothesis tests (Nov 10)
   • Cameron and Trivedi. Chapter 7.

   • Vuong, Quang H. 1989. ``Likelihood-ratio Tests for Model Selection and Non-nested Hypotheses.'' Econometrica 57 (2): 307-333.

8. random assignment (Nov 17)
   • Freedman, D. A. 2007. On regression adjustments to experimental data. In press, Advances in Applied Mathematics.
     http://www.stat.berkeley.edu/users/census/neyregr.pdf

   • D. A. Freedman. 2008. Randomization does not justify logistic regression. Statistical Science 23: 237-249.

   • D. A. Freedman. 2008. On regression adjustments in experiments with several treatments. Annals of Applied Statistics 2: 176-196.

9. choice models (Nov 24)
   • McFadden, Daniel. 1974. ``Conditional logit analysis of qualitative choice behavior.'' In P Zarembka, ed., Frontiers of Econometrics, New York: Acadmic Press. pages 105-142.
     http://emlab.berkeley.edu/reprints/mcfadden/zarembka.pdf

   • McFadden, Danel. 1981. ``Structural Discrete Probability Models Derived from Theories of Choice.'' In Charles F. Manski and Daniel L. McFadden, eds, Structural Analysis of Discrete Data and Econometric Applications, Cambidge, MA: MIT Press, chapter 5, pp. 198-272.
     http://emlab.berkeley.edu/discrete/ch5.pdf

10. stategic choice models (Dec 1, 8)
    • McKelvey, Richard D., and Thomas R. Palfrey. 1995. Quantal Response Equilibria for Normal Form Games. Games and Economic Behavior 10: 6-38.

    • Goeree, Jacob K., and Charles A. Holt. 2005. An Explanation of Anomalous Behavior in Models of Political Participation. American Political Science Review 99 (May): 201-213.

    • Haile, Philip A., Ali Hortaçsu and Grigory Kosenok. 2007. On the Empirical Content of Quantal Response Equilibrium. Working paper.
      http://www.econ.yale.edu/ pah29/qre.pdf

Additional Reading

Here are some potentially useful books on R.

Crawley, Michael R. 2007. The R Book. Wiley.

Spector, Phil. 2008. Data manipulation with R. Springer.

Albert, Jim. 2007. Bayesian Computation with R. Springer.

Chambers, John M. 2008. Software for Data Analysis. Springer.

Braun, W. John, and Duncan J. Murdoch. 2007. A First Course in Statistical Programming with R. Cambridge.