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Though several prominent econometricians have taken steps toward strengthening the intertheoretical links in statistical models, their isolated efforts will not ease the model selection problem.
Using robust control theory is a way to let our agents share the experiences of econometricians.
Transfer functions are applied widely in engineering and science, but they are not in favor among most time-series econometricians.
I argue there that econometricians have failed to confront the problems of inference that are central to macroeconomic policy modeling.
Of course, the typical rational expectations model reverses the situation: the agent knows more than the econometrician.
The agent inside the model knows the parameters of the true model while the econometrician does not and must estimate them.
When the strong abstract econometrician and the substantive researcher happen to be the same person, that's great, but it's rare.
You started out as a time series econometrician?
When an econometrician tries to deal with multicollinearity is that econometrician doing something connected to estimating cause and effect relations?
A colleague joked to me the other day that time-series econometricians have won finance but lost macro.
In the jargon of the econometrician, they are co-integrated.
And, as econometricians know very well, in misspecified models the outcome can be seriously distorted.
The numbers of econometricians was obviously much smaller then.
Because econometricians are very accustomed to thinking in terms of possible models, the semantic approach is likely very intuitive for econometricians.
Evidently, much of subsequent uncertainty (from the standpoint of the econometrician) is able to be forecasted by the agents at the time of their choices.
