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Time-Series
EconometricsIan Helfrich PhD ↗

Fifteen lectures

Lecture summaries

Each summary restates a lecture's economic question and central relation, poses one individual problem with a worked answer, and names a consequential failure with its repair. The chapter supplies the full argument, derivations, and laboratory.

Read the chapter first, attempt its assignment on the practice page, and run its laboratory in one language. Then use the summary to check that you can state the central relation, the failure, and the repair without the chapter open. Dates follow the course's 2027 teaching sequence.

  1. The decision and its information set · January 15
    Complete chapter · R, Julia, and Python
  2. Persistence, recursion, and aggregation · January 22
    Complete chapter · R, Julia, and Python
  3. ARMA models and recoverable innovations · January 29
    Complete chapter · R, Julia, and Python
  4. Forecasts that survive a chronological comparison · February 5
    Complete chapter · R, Julia, and Python
  5. Signals, noisy measures, and information-preserving filters · February 12
    Complete chapter · R, Julia, and Python
  6. Trends, unit roots, and misleading level regressions · February 19
    Complete chapter · R, Julia, and Python
  7. Weather, seasonality, and dynamic regression · February 26
    Complete chapter · R, Julia, and Python
  8. Estimating a latent state as observations arrive · March 5
    Complete chapter · R, Julia, and Python
  9. Multivariate dynamics and regional networks · March 12
    Complete chapter · R, Julia, and Python
  10. What an impulse response can claim · March 26
    Complete chapter · R, Julia, and Python
  11. A stable relation between moving levels · April 2
    Complete chapter · R, Julia, and Python
  12. Predictable risk with an unpredictable return · April 9
    Complete chapter · R, Julia, and Python
  13. When the model or the measurement changes · April 16
    Complete chapter · R, Julia, and Python
  14. Freeze a revision before its next test · April 23
    Complete chapter · R, Julia, and Python
  15. Defend a forecast in an unfamiliar setting · April 30
    Complete chapter · R, Julia, and Python

Assignments and worked practice · Project specifications