Asterisked references are more important to the course. The following is a tentative list of topics that will be covered in this course.

## Required Text

[Hamilton] = Hamilton, James D. *Time Series Analysis*. Princeton University Press, 1994. ISBN: 9780691042893.

## Recommended Texts

[Brockwell and Davis] = Brockwell, Peter, and Richard Davis. *Time Series: Theory and Methods*. Springer-Verlag, 1991. ISBN: 9780387974293. [Preview with Google Books]

[Canova] = Canova, Fabio. *Methods for Applied Macroeconomic Research*. Princeton University Press, 2007. ISBN: 9780691115047. [Preview with Google Books]

[DeJong and Dave] = DeJong, David, and Chetan Dave. *Structural Macroeconometrics*. Princeton University Press, 2011. ISBN: 9780691126487. [Preview with Google Books]

[Hall and Heyde] = Hall, Peter, and C. C. Heyde*. Martingale Limit Theory and Its Application (Probability and Mathematical Statistics)*. Academic Press, 1980. ISBN: 9780123193506.

[Griliches and Intriligator] = Griliches, Zvi, and Michael Intriligator, eds. *Handbook of Econometrics*. Vol. 3. North Holland, 1986. ISBN: 9780444861870.

[Lütkepohl] = Lütkepohl, Helmut. *Introduction to Multiple Time Series Analysis*. Springer-Verlag, 1993. ISBN: 9780387569406.

SES # | TOPICS | READINGS |
---|---|---|

I. Introduction: Stationary Time Series | ||

1–3 | Introduction to stationary time series | [Hamilton] Chapters 1–5, 7, and 8. *[Hall and Heyde] Chapter 3. [Brockwell and Davis] Chapters 1, 3, and Section 5.7. *Newey, W. K., and K. D. West. "A Simple Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix." *Andrews, D. W. K. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation." Beveridge, S., and C. R. Nelson. "A New Approach to Decomposition of Economic Time Series into Permanent and Transitory Components with Particular Attention to Measurement of the 'Business Cycle'." Andrews, D. W. K., and J. C. Monahan. "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator." den Haan, W. J., and A. Levin. "A Practitioner's Guide to Robust Covariance Matrix Estimation." Chapter 12 in Kiefer, N., and T. Vogelsang. "Heteroskedasticity-Autocorrelation Robust Testing Using Bandwidth Equal to Sample Size." |

3–5 | Frequency domain analysis | *[Hamilton] Chapter 6. [Brockwell and Davis] Chapters 4, and 10. *Baxter, M., and R. King. "Measuring Business Cycles: Approximate Band-Pass Filters for Economic Time Series." Berk, K. N. "Consistent Autoregressive Spectral Estimates." Hodrick, R., and E. Prescott. "Post-War U.S. Business Cycles: An Empirical Investigation." Christiano, L. J., and T. J. Fitzgerald. "The Band Pass Filter." NBER Working Paper no. 7257, 1999. |

5 | Model selection and information | *Geweke, J., and R. Meese. "Estimating Regression Models of Finite but Unknown Order." Ng, S., and P. Perron. "A Note on the Selection of Time Series Models." Leeb, H., and B. M. Potscher. "Model Selection and Inference: Facts and Fiction." ———. "The Finite-Sample Distribution of Post-Model-Selection Estimators and Uniform versus Nonuniform Approximations." Hansen, B. "Challenges for Econometric Model Selection." Kuersteiner, G. M. "Automatic Inference for Infinite Order Vector Autoregressions." |

II. Mutivariate Stationary Analysis | ||

6–7 | VAR | *[Hamilton] Chapters 10, and 11. *[Lütkepohl] Chapters 2, and 3 (2005). Watson, M. "Vector Autoregressions and Cointegration." Chapter 47 in Stock, J. H., and M. W. Watson. "Vector Autoregressions." Wright, J. H. "Confidence Intervals for Univariate Impulse Responses with a Near Unit Root." Killian, L. "Small Sample Confidence Intervals for Impulse Response Functions." Mikusheva, A. "One-Dimensional Inferences in Autoregressive Models in a Potential Presence of a Unit Root." |

8 | Structural VARs | *Sims, C. A. "Macroeconomics and Reality." *Blanchard, O. J., and D. Quah. "Dynamic Effects of Aggregate Demand and Supply Disturbances." Blanchard, O. J. "A Traditional Interpretation of Macroeconomic Fluctuations." King, R. G., C. I. Plosser, et al. "Stochastic Trends and Economic Fluctuations." Cooley, T., and S. LeRoy. "A Theoretical Macroeconomics: A Critique." Braun, P., and S. Mittnik. "Misspecification in VAR and their Effects on Impulse Responses and Variance Decompositions." Cooley, T., and M. Dwyer. "Business Cycle Analysis Without Much Theory: A Look at Structural VARs." Wright, J. H. "What does Monetary Policy do to Long-Term Interest Rates at the Zero Lower Bound?" Moon, H. R., F. Schorfheide, et al. "Inference for VARs Identified with Sign Restrictions." Manuscript, University of Pennsylvania (2009). |

9 | VAR and DSGE models | Chari, V., P. Kehoe, et al. "A Critique of Structural VARs Using Business Cycle Theory." Federal Reserve Bank of Minneapolis, Research Department Staff Report 364 (2005). *Christiano, L., M. Eichenbaum, et al. "Assessing Structural VARs." Northwestern University, manuscript (2005). *Fernandez Villaverde, J., J. Rubio Ramirez, et al. "The ABC and (D's) to Understand VARs." NYU manuscript (2005). Erceg, C, L. Guerrieri, et al. "Can Long Run Restrictions Identify Technology Shocks?" Board of Governors of the Federal Reserve, International Finance discussion paper 792 (2005). Lippi, M., and L. Reichlin. "VAR Analysis, Non-Fundamental Representation, Blaschke Matrices." Faust, J., and E. Leeper. "Do Long Run Restrictions Really Identify Anything?" |

10–11 | Factor model and FAVAR | *Stock, J. H., and M. W. Watson. "Implications of Dynamic Factor Models for VAR Analysis." NBER Working Paper no. 11467, 2005. Bernanke, B. S., and J. Boivin. "Monetary Policy in a Data-rich Environment." *Bernanke, B. S., J. Bovian, et al. "Measuring the Effects of Monetary Policy: A Factoraugmented Vector Autoregressive (FAVAR) Approach." *Forni, M., D. Giannoni, et al. "Opening the Black Box: Structural Factor Models with Large Cross-Sections." European Central Bank, working paper 712. Chamberlain, G., and M. Rothschild. "Arbitrage, Factor Structure and Mean-Variance Analysis of Large Asset Markets." Favero, C. A., M. Marcellino, et al. "Principal Components at Work: The Empirical Analysis of Monetary Policy with Large Datasets." Forni, M., M. Hallin, et al. "The Generalized Dynamic Factor Model: Identification and Estimation." Bai, J., and S. Ng. "Determining the Number of Factors in Approximate Factor Models." ———. "Determining the Number of Primitive Shocks in Factor Models." *———. "Instrumental Variable Estimation in a Data Rich Environment." Forni, M., M. Hallin, et al. "One-Sided Representations of Generalized Dynamic Factor Models." Manuscript (2011). |

III. Univariate Non-Stationary Processes | ||

12 | Asymptotic theory of empirical processes | *[Hamilton] Sections 17.1–17.3. [Hall and Heyde] Chapters 3, 4, and 5, and the Appendix. |

13–14 | Univariate unit roots and near unit root problem | *[Hamilton] Chapter 17. *Stock, J. H. "Unit Roots and Trend Breaks in Econometrics." Sections 1–4 in Dickey, D. A., and W. A. Fuller. "Distribution of the Estimators for Autoregressive Time Series with a Unit Root." Campbell, J. Y., and P. Perron. "Pitfalls and Opportunities: What Macroeconomists Should Know About Unit Roots." Andrews, D. W. K. "Exactly Median-Unbiased Estimation of First Order Autoregressive/Unit Root Models." Hansen, B. E. "The Grid Bootstrap and the Autoregressive Model." *Phillips, P. C. B. "Toward a Unified Asymptotic Theory for Autoregression." Stock, J. "Confidence Intervals for the Largest Autoregressive Root in U.S. Macroeconomic Time Series." Mikusheva, A. "Uniform Inference in Autoregressive Models." |

15 | Structural breaks and non-linearity | *[Hamilton] Chapter 22. *Andrews, D. W. K. "Tests for Parameter Instability and Structural Change with Unknown Change-Point." *Hansen, B. E. "The New Econometrics of Structural Change: Dating Breaks in U.S. Labor Productivity." *Perron, P. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis." Andrews, D. W. K., and W. Ploberger. "Optimal Tests When a Nuisance Parameter is Present Only Under the Alternative." Bai, J. S. "Estimating Multiple Breaks One at a Time." Bai, J., and P. Perron. "Estimating and Testing Linear Models with Multiple Structural Changes." Bai, J., R. L. Lumsdaine, et al. "Testing For and Dating Common Breaks in Multivariate Time Series." Zivot, E., and D. W. K. Andrews. "Further Evidence on the Great Crash, the Oil Price Shock, and the Unit Root Hypothesis." |

IV. Multivariate Non-Stationary | ||

16–17 | Multivariate unit roots and co-integration | Stock, J. H. "Asymptotic Properties of Least Squares Estimators of Cointegrating Vectors." Stock, J. H., and M. W. Watson. "A Simple Estimator of Cointegrating Vectors in Higher Order Integrated Systems." *Watson, M. W. "Vector Autoregressions and Cointegration." Sections 1, and 2 in *———. "Cointegration." In |

17 | Persistent regressors (prediction regression) | Bekaert, G., and R. J. Hodrick. "Expectations Hypotheses Test." Campbell, J. Y., and M. Yogo. "Efficient Tests of Stock Return Predictability." *Cavanagh, C. L., G. Elliott, et al. "Inference in Models with Nearly Integrated Regressors." *Stambaugh, R. F. "Predictive Regressions." Jansson M., and M. J. Moreira. "Optimal Inference in Regression Models with Nearly Integrated Regressors." |

V. GMM and Related Issues | ||

18 | GMM and simulated GMM | *[Hamilton] Chapter 14. *[DeJong and Dave] Chapter 7. [Canova] Chapter 5. *Hansen, L. P. "Large Sample Properties of GMM Estimators." *Hansen, L. P., and K. Singleton. "Generalized Instrumental Variables Estimation of Nonlinear Rational Expectations Models." Mc Fadden, D. "A Method of Simulated Moments of Estimation for Discrete Response Models without Numerical Integration." Pakes, A., and D. Pollard. "Simulation and the Asymptotics of Optimization Estimators." *Lee, B., and B. Ingram. "Simulation Estimation of Time Series Models." Duffie, D., and K. Singleton. "Simulated Moments Estimation of Markov Models of Asset Prices." *Smith, A. "Estimation of Nonlinear Time Series Models Using Simulated VARs." (PDF) |

19 | Weak IV | Andrews, D. W. K., M. Moreira, et al. "Optimal Two-Sided Invariant Similar Tests for Instrumental Variables Regression." Andrews, D. W. K., and J. H. Stock. "Inference with Weak Instruments." In Kleibergen, F. R., and S. Mavroeidis. "Weak Instrument Robust Tests in GMM and the New Keynesian Phillips Curve." (PDF) Manuscript, Brown University (2008). Staiger, D., and J. H. Stock "Instrumental Variables Regression with Weak Instruments." *Stock, J. H., and M. Yogo. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments." *Stock, J. H., and J. Wright. "GMM With Weak Identification." Yogo, M. "Estimating the Elasticity of Intertemporal Substitution when the Instruments are Weak." |

VI. Likelihood Methods | ||

20–21 | Kalman filter and its applications | *[Hamilton] Chapter 13. [Canova] Chapter 6. *Hamilton, J. D. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle." |

22 | ML estimation of DSGE | [DeJong and Dave] Chapter 8. [Canova] Chapter 6. Sargent, T. "Two Models of Measurements and the Investment Accelerator." Ingram, Kocherlakota, and Savin. "Explaining Business Cycles: A Multi-Shock Approach." Hansen, and Sargent. Ireland, P. "A Method for Taking Models to Data." White, H. "Maximum Likelihood Estimation of Misspecified Models." |

23 | Identification and weak identification of DSGE | Canova, F., and L. Sala. "Back to Square One: Identification Issues in DSGE Models." Iskrev, N. "Evaluating the Strength of Identification in DSGE Models. An a Priori Approach." Komunjer, I., and S. Ng. "Dynamic Identification of DSGE Models." Andrews, I., and A. Mikusheva. "Maximum Likelihood Inference in Weakly Identified DSGE Models." Manuscript (2011). Müller, U. "Measuring Prior Sensitivity and Prior Informativeness in Large Bayesian Models." Manuscript (2011). |

VII. Bayesian Methods | ||

24 | Bayesian concepts | *[Hamilton] Section 12.3. |

25 | Markov Chain Monte Carlo (MCMC) | *Chib, S., and E. Greenberg. "Understanding the Metropolist-Hastings Algorithm." *———. "Markov Chain Monte Carlo Simulation Methods in Econometrics." *Chib, S. "Markov Chain Monte Carlo Methods: Computation and Inference." Chapter 5 in Chib, S., F. Nardari, et al. "Markov Chain Monte Carlo methods for Stochastic Volatility Models." |

26 | Estimation of DSGE models using Bayesian methods | Del Negro, M., and F. Schorfheide. "Priors from General Equilibrium Models for VARs." Del Negro, M. Schorfheide, et al. "On the Fit and Forecasting Performance of New Keynesian Models." Rabanal, P., and J. Rubio-Ramirez. "Comparing New Keynesian Models of the Business Cycle: A Bayesian Approach." Fernandez-Villaverde, J., and J. Rubio-Ramirez. "Estimating Dynamic Equilibrium Economies: Linear versus Nonlinear Likelihood." |