Introduction to Econometrics

Chapter 11 : Time series models

By Lund University

Time series models

Univariate time series models

Univariate time series models

Time series data

Stationarity

The AR(1) process

The AR(p) process

Test for unit root

Multivariate time series models

Multivariate time series models

LRM with time series data – the static model

The properties of the OLS estimator in the static model

ADL(p,q) model

Estimating ADL(p,q) models

Long run and short run effects in ADL models

Autocorrelation

By autocorrelation in a regression model, we mean that the error term in this period depends on its value in previous periods. We will begin by looking at the Breusch-Godfrey test for autocorrelation. If we find that autocorrelation is present then the standard errors from OLS are no longer useful and we will look at robust standard errors. If it can be assumed that the error terms follow an AR(1) process, then it is possible to replace OLS with an efficient estimator.

Autocorrelation

Test for autocorrelation, Breusch-Godfrey test

Robust standard errors with autocorrelation

Efficient estimation with AR(1) errors