1. Bayesian Basics

   1. The Likelihood Principle, Post-Sample and Pre-Sample Probability

      [BW88]

      [GCSR95], Chapters 1-4

      [Rob94] is another good reference, with more emphasis on proofs of optimality

      [Sch95] treats Bayesian and non-Bayesian approaches symmetrically, with an emphasis on careful proofs

   2. Limited information Bayesian Inference

      [Kwa98]

      1. Bayesian Interpretation of GMM and 2SLS

         Chamberlain and/or Imbens.

   3. Markov Chain Monte Carlo, Importance Sampling

      [GCSR95], Chapter 11

2. Linear Stochastic Difference Equations

   1. Roots, Lag Operators, Impulse Responses

      [Ham94], Chapters 1-3

   2. Inference for Impulse Responses

      [SZ98a]

      [SZ98b]

      (These two readings treat some more advanced material that we will return to in section 8a below.)

3. The Kalman Filter

   [Ham94], Chapter 13

4. Information in Initial Conditions

   [Sim89]

   [Sim98]

5. VAR's for Panel Data

   references from convergence literature

   [Sim98]

6. Stochastic Volatility, ARCH

   [Ham94], Chapter 21

   reference on stochastic volatility via MCMC

7. Mixture Models, Regime Switching

   [Ham94], Chapter 22

   {reference for MCMC approach}

8. Inference and Policy Analysis with Structural Models

   1. Identified VAR's
   2. DSGE Models

      [Sch98]

References

[BW88]

James O. Berger and Robert L. Wolpert. The Likelihood Principle. Institute of Mathematical Statistics, Hayward, California, 2nd edition, 1988.

[GCSR95]

Andrew Gelman, John B. Carlin, Hal S. Stern, and Donald B. Rubin. Bayesian Data Analysis. Chapman and Hall, London, 1995.

[Ham94]

James D. Hamilton. Time Series Analysis. Princeton University Press, Princeton, NJ, 1994.

[Kwa98]

Yum K. Kwan. Asymptotic bayesian analysis based on a limited information estimator. Journal of Econometrics, 88:99-121, 1998.

[Rob94]

Christian Robert. The Bayesian Choice. Springer Texts in Statistics. Springer-Verlag, New York, 1994.

[Sch95]

Mark J. Schervish. Theory of Statistics. Springer Series in Statistics. Springer, New York, 1995.

[Sch98]

Frank Schorfheide. A unified econometric framework for the evaluation of dsge models. Discussion paper, Department of Economics, University of Pennsylvania, 1998.

[Sim89]

Christopher A. Sims. Modeling trends. In Proceedings, American Statistical Association Annual Meetings, August 1989.

[Sim98]

Christopher A. Sims. Using a likelihood perspective to sharpen econometric discourse: Three examples. forthcoming, Journal of Econometrics, Department of Economics, Yale University, www.econ.yale.edu\~sims, 1998.

[SZ98a]

Christopher A. Sims and Tao Zha. Bayesian methods for dynamic multivariate models. International Economic Review, 1998.

[SZ98b]

Christopher A. Sims and Tao Zha. Error bands for impulse responses. (forthcoming, Econometrica), Yale University, Department of Economics, www.econ.yale.edu/~sims, 1998.