## ECM forecast

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PMaier
Posts: 36
Joined: Sat Sep 11, 2010 10:12 am

### ECM forecast

Hi,

I would appreciate some help forecasting an ECM model. The equation I'm trying to forecast is a traditional ECB equation:

f2 = beta(1)*f2(-1) - beta(2)*(f2_level(-1)-beta(3)*oil(-1) - beta(4)*comm_agriculture(-1)-beta(5)*comm_metals(-1)),

whereby f2 is the series in first differences and f2_level the series in levels. The attached workfile contains all series.
ecm model.wf1

Here's the code to set up the basic framework:

Code: Select all

`coef(5) betaseries f2_level = @cumsum(f2)' Test the cointegration relationship -- first the LR relationship, then the SR relationshipsmpl 1980q1 2007q4equation eq_lr.ls f2_level = c(1)*oil - c(2)*comm_agriculture-c(3)*comm_metalsequation eq_ecm.ls(n) f2=beta(1)*f2(-1) -beta(2)*(f2_level(-1) -beta(3)*oil(-1) - beta(4)*comm_agriculture(-1)-beta(5)*comm_metals(-1))fit f2_hatplot f2_level @cumsum(f2_hat)' Forecasting' Build a modelmodel model_testmodel_test.merge eq_lrmodel_test.merge eq_ecm`

In other words, I'm first generating f2_levels, then test the cointegration relationship, then estimate the ECM (don't look too hard on the econometrics; I'm just using this data as illustration).

Then, however, I run into difficulties as I'm trying to cast this in model form. I think I need to make explicit to the model that f2=d(f2_level), but if I try adding this equation, I get the error message that "f2 is specified as endogenous in another equation" (not surprising). So I'm a bit at a loss how to accomplish this.

Any advice would be greatly appreciated!

Many thanks, Philipp

PMaier
Posts: 36
Joined: Sat Sep 11, 2010 10:12 am

### Re: ECM forecast

I probably overlooked the simple solution. I think the following should be correct:

Code: Select all

`    coef(5) beta    series f2_level = @cumsum(f2)    ' Test the cointegration relationship -- first the LR relationship, then the SR relationship    smpl 1980q1 2007q4    equation eq_lr.ls f2_level = c(1)*oil - c(2)*comm_agriculture-c(3)*comm_metals    equation eq_ecm.ls(n) f2=beta(1)*f2(-1) -beta(2)*(f2_level(-1) -beta(3)*oil(-1) - beta(4)*comm_agriculture(-1)-beta(5)*comm_metals(-1))    ' Forecasting    model model_test    model_test.merge eq_ecm    model_test.append f2_level = f2_level(-1)+f2`

... and then solve the model dynamically.

I'm posting this in case anyone else struggles with the same issue -- or, if I'm wrong, to be corrected!

Thanks, Philipp