Economics 706
Time Series Econometrics
Professor F.X. Diebold
Spring 2018

 


Welcome!

This course provides a Ph.D.-level introduction to econometric time-series analysis.

Book, slides, code, etc. here. The slides are the center of everything.

Some materials that we will use here. Useful books here. Useful software here.

Format: Lectures that stress applied econometric theory.

Tentative Topics:

Time Domain: The Wold Representation and its Approximation
Frequency Domain: The Spectrum and its Approximation
Markovian Structure, State Space, and the Kalman Filter
Likelihood Evaluation and Optimization
Bayesian Posterior Analysis and Markov Chain Monte Carlo
Nonlinear/Non-Gaussian State Space
Conditional Variance Dynamics
More Simulation Methods and Applications
     (Monte Carlo Methods and Variance Reduction; Global Function Optimization;
      Simulated MM and Indirect Inference; Bootstrap)
Integration, Cointegration, and Long Memory

Office hours (held in McNeil 519) here. 

Teaching assistants will be heavily involved, including small-scale help by email and large-scale help in weekly review/supplementary sessions. (Office hours and review session times and locations, contact info, etc., to be announced.)

Grading: N problem sets (each 60/N %) and a final exam ("practice prelim") (40%). Good performance is crucially dependent on regular class preparation, attendance and participation.

Problem Set 1 (Due February 22.)
Use monthly U.S. housing starts and completions data (detrended and deseasonalized if necessary), reserving the last six observations for out-of-sample forecast comparisons. Discuss all results as appropriate. First graph the data. Then do the following. Model the two series jointly as a VAR(4); Calculate the autocorrelation and spectral density functions implied by your estimated VAR; Perform a Granger-causality analysis; Using Cholesky factor identification, calculate and graph the full set of impulse-response functions; Forecast the six hold-out observations and assess accuracy; using the full dataset forecast the sample path for the next twelve months.

Problem Set 2 (Due last day of class.)
Problem set is here. Also see the Federal Reserve Bank of Philadelphia web site.

Final exam date: Standard university date/time/location.

Note well that modifications and adjustments to this syllabus / web site are inevitable and may be implemented at any time. Check frequently for updates.