## Second Order Differencing

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bspoon
Posts: 3
Joined: Fri Apr 14, 2017 9:05 am

### Second Order Differencing

Hello,

In order to make my data stationary, I had to take the second difference of the natural log of my data. Ex: logy=dlog(y,2).

I used this transformed data to produce a forecast and get values in those terms. I wish to compare my forecasted values to the original values for y in my dataset, so my question is how do I reverse the second order differencing in order to get my forecasted values back into the same terms as my actual values?

Any help would be appreciated.

Thank you!

EViews Gareth
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### Re: Second Order Differencing

Use dlog(y,2) as your dependent variable.
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bspoon
Posts: 3
Joined: Fri Apr 14, 2017 9:05 am

### Re: Second Order Differencing

Yes so the regression that I used for forecasting was with dlog(y,2) as my dependent variable so my forecasted values were in those terms. My original "y" dataset was an index in the 100s so is it possible to transform the forecasted values back in terms of the index in the 100s? I want to compare my forecasted index value with the actual index value if possible.

EViews Gareth
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### Re: Second Order Differencing

When you use dlog(y,2) as the dependent variable, EViews will forecast y not dlog(y,2)
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bspoon
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Joined: Fri Apr 14, 2017 9:05 am

### Re: Second Order Differencing

Oh okay I see now. That helps, thank you!

One more thing, when you select the "static" option for a forecast, is that recursive or rolling window? I couldn't find the specification in the Eviews guide.

EViews Gareth
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### Re: Second Order Differencing

Simple 1-step ahead forecast.
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Saakshi
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### Re: Second Order Differencing

Hi Gareth,

As you mentioned static forecast means 1 step ahead. What about 4 step ahead forecast?

thanks,
Saakshi

EViews Glenn
EViews Developer
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Joined: Wed Oct 15, 2008 9:17 am

### Re: Second Order Differencing

Forecast of data at t+4 given information at t.

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