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


From   Christopher Baum <kit.baum@bc.edu>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   re: st: Out-of-sample forecasting using OLS regression
Date   Mon, 20 Aug 2012 23:36:56 +0000

<>
Edin said

I am currently working on my master thesis which is focused on the Dynamic
factor model forecasting.
Unfortunately, I got stuck at the out-of-sample forecasting. After running
OLS regression when I try to do out-of-sample forecast, Stata generates the
missing values for all the observations.


2011m12 is the last observation in my sample, afterward data set was
expanded.  I am using following command after running regression:

predict pcpi if t>tm(2011m12)

I would really appreciate if somebody could tell me what the potential
source of this problem is and how I could solve it.



I am confused by the mention of 'dynamic factor model', as there are such models (-dfactor-) in Stata. But I think what Edin
means is that he wants to do out-of-sample dynamic forecasting from a plain OLS regression. This can (currently only) be done with -arima-,
which despite its name can estimate OLS regressions, and can generate dynamic forecasts (help arima postestikmation) from a model
such as y_t = b0 + b_1 y_t-1 + x_t + epsilon_t. As Nick Cox points out, you must have values of x_t defined during the ex ante forecast 'period.
But in a dynamic forecast, you need not have values of y_t-1 beyond the estimation sample.

Kit

Kit Baum   |   Boston College Economics & DIW Berlin   |   http://ideas.repec.org/e/pba1.html
                             An Introduction to Stata Programming  |   http://www.stata-press.com/books/isp.html
  An Introduction to Modern Econometrics Using Stata  |   http://www.stata-press.com/books/imeus.html


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