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re: Re: st: Out-of-sample forecasting using OLS regression

From   Christopher Baum <>
To   "" <>
Subject   re: Re: st: Out-of-sample forecasting using OLS regression
Date   Tue, 21 Aug 2012 01:45:10 +0000

Edin said

I do dynamic factor model as it follows:

First of all I generate factors using factor analysis function which
is available in Stata.
Secondly, I save two factors in my data set as new variables.
Thirdly, I run following regression (ARIMA or OLS):

cpi = c + l.cpi + factor1 + factor2...

OK, so it is just OLS, with a desire to perform a dynamic forecast ex ante. The following will do that, and contrast it with the static (one-period-ahead) forecast. In the dynamic forecast, the past value of l.cpi generated by the model will be used after the end of the estimation sample, rather than the historical value. (OK, I know this equation is dynamically unstable, but it is merely illustrative).

arima cpi l.cpi d.oilprice d.wage if tin(, 2008q4)
predict double cpihat_s if tin(2006q1,), y
predict double cpihat_d if tin(2006q1,), dynamic(tq(2008q4)) y
tsline cpihat_s cpihat_d if !mi(cpihat_s)


Kit Baum   |   Boston College Economics & DIW Berlin   |
                             An Introduction to Stata Programming  |
  An Introduction to Modern Econometrics Using Stata  |

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