12  D1. Time Series — Overview

12.1 About

This section introduces time series econometrics — the analysis of data indexed over time. Unlike cross-sectional data, time series observations are ordered and exhibit serial correlation. Standard OLS assumptions must be modified accordingly.

Topics: stationarity, ARMA models, unit roots, Dickey-Fuller tests, cointegration, ECM, VAR, HAC standard errors.

12.2 Lecture Notes

 

12.3 Slides

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Note: Slides and notes are pending translation to English.

12.4 Overview

This block introduces time series econometrics — the analysis of data indexed over time. Unlike cross-sectional data, time series observations are ordered and typically exhibit serial correlation. Standard OLS assumptions must be modified to account for dependence over time.

Key topics

  • Stationarity and ergodicity
  • Autoregressive (AR) and moving average (MA) processes; ARMA models
  • Unit roots and integration; Dickey-Fuller tests
  • Cointegration and error-correction models (ECM)
  • Vector autoregressions (VAR)
  • Heteroskedasticity and autocorrelation consistent (HAC) standard errors

Reference

Hamilton (1994) provides the classic treatment. Davidson y MacKinnon (2004), chapters 13–15, covers asymptotics for time series regressions.