Error Correction Model

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Error Correction Model

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An error correction model ECM belongs to a category of multiple time series models most commonly used for data where the underlying variables have a long run common stochastic trend also known as cointegration ECMs are a theoretically driven approach useful for estimating both short term and long term effects of one time series on another # estimate error correction model ols ld_Ct const ld_Yt gap_1 # retrieve factor of proportionality genr prop = exp($coeff(const)/$coeff(gap_1)) print prop genr SSRr = $ess # now for the unrestricted model lags l_Ct l_Yt ols l_Ct const l_Yt l_Yt_1 l_Ct_1 genr SSRu = $ess genr dfu = $df genr Ftest = (SSRr-SSRu)*dfu/SSRu pvalue F 1 dfu Ftest

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Error Correction ModelThe Error-Correction Model for Co-integrated Time Series (and checking parameter stability) | by John Clements | Towards Data Science. L is the number of lags in the model, rho hat is our estimated long-run relationship coefficient, and eta hat is the deviation of from our long-run relationship in the previous period. Member-only story. This is where the Error Correction Model ECM finds its value in the econometrics world In simple words ECM describes how dependent variable y and the independent variable x behave

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