The document discusses various econometric modeling techniques including regression equations, cointegration, error correction models, vector autoregressive (VAR) modeling, and vector error correction models (VECM). It explains that regression equations can produce spurious results if the data is non-stationary, and that cointegration exists if the residuals from a regression equation are stationary. Error correction models specify the short-run relationship that maintains the long-run equilibrium between cointegrated variables. VAR models express current values of variables as functions of past values, while VECMs are VARs in first differences that incorporate the long-run cointegrating relationships between variables.

1. Econometric Modelling using Eviews Edward Bahaw March19 th 2008 Natural Gas Institute of the Americas

4. A Regression Equation X 2t X 1t u i

6. Non stationary data Time Non - Stationary Time Series Mean does not represent the value which the time series approaches Time Mean represents the value which the series approaches over time Stationary Time Series

8. Spurious Regression Residuals Time u t is non-stationary u t corresponding to a spurious regression u t Mean

9. Spurious Regression Using X 1t = μ + β 2 X 2t + u t , Then u t = X 1t – β 2 X 2t – μ If X 1t and X 2t are non-stationary a spurious regression may be obtained

10. Cointegration and Non-Stationary Variables In the model: X 1t = μ + β 2 X 2t + u t , Or u t = X 1t – β 2 X 2t – μ If u t is stationary about a mean of zero then cointegration exists.

14. Long run and Short Run Models … (Long Run or Equilibrium Equation) … (Short run equation or ECM)