I have become aware that a group at a large corporation is developing an econometrics model to forecast sales of their product. They are using this model solely to estimate sales in specified stress test economic scenarios where they are given what the economic environment will be like, including real GDP contraction, rising unemployment rate, etc… out to 2016. Because of the nature of those scenarios, they think the most proper way to construct this model is to focus solely on the 2008-2009 period capturing the main period of the recent financial crisis. They have monthly data, so that gives them 24 monthly data points. Given that GDP's frequency is really quarterly, on this one variable it gives them only 8 true datapoints. But, they extrapolate it into 24 month observations.
For the record, if they chose to, they have good internal data going back to 2001 and up to the current period. But, as mentioned they decided to focus instead solely on the 2008-2009 period.
I will also answer this question as I have built many such econometrics models. And, I invite others to debate and rebutt my answer… and to post your own better answer.
Best Answer
The points you are making are valid, but there are also arguments that if not counter to yours, they create a dilemma:
When trying to estimate and forecast extreme cases, incorporating information from "normal times" may "average" your predictor, which would then be more reliable to estimate long-term trends rather than short-term (and severe) fluctuations. Models that describe well both these aspects are still not available, because we do not yet understand well how "normal times" breed their own crises (in "normal times" I include the concept of a business cycle - a crisis is something much more severe).
One could build three models: one based just on "crisis data", one based on only "normal times" data, and one based on both data. Comparing the three in terms of their forecasts would be very valuable. Also one could implement "model-averaging" on the two "pure" models and compare its forecasts with the "both kind of data" model forecasts.
Since they are a large corporation and only in it for the money, this multiplication of resources allocation to estimate their sales can be justified -and financed.