The forecasts may be coming from some external agency, not from me… My goal is to use that number and come up with a better forecast from it.
In this case calling your inputs “forecasts” is just confusing. For you they are nothing but data on the basis of which you will build your own model to produce your forecasts.
In this framework you’re just doing normal forecasting and should use all the normal tools. There’s no reason to limit yourself to OLS regression, for example.
OLS regression isn’t the only tool, but it is the most standard one to fit a functional form. One can use other kinds of regressions. My focus was on techniques that can use existing forecast estimates in a black-box fashion rather than those that require one to create new models of one’s own on the evolution of the relevant processes.
but it is the most standard one to fit a functional form
It is the most simple one and probably the most widely used, though often inappropriately.
My focus was on techniques that can use existing forecast estimates in a black-box fashion rather than those that require one to create new models of one’s own on the evolution of the relevant processes.
As soon as you do something with “existing forecast estimates” other than just accepting them, you are creating a new model of your own. You want to correct them for bias? That’s a model you’ve created.
If you use external forecasts as data, as inputs, you are using them in “black-box fashion”.
In this case calling your inputs “forecasts” is just confusing. For you they are nothing but data on the basis of which you will build your own model to produce your forecasts.
In this framework you’re just doing normal forecasting and should use all the normal tools. There’s no reason to limit yourself to OLS regression, for example.
OLS regression isn’t the only tool, but it is the most standard one to fit a functional form. One can use other kinds of regressions. My focus was on techniques that can use existing forecast estimates in a black-box fashion rather than those that require one to create new models of one’s own on the evolution of the relevant processes.
It is the most simple one and probably the most widely used, though often inappropriately.
As soon as you do something with “existing forecast estimates” other than just accepting them, you are creating a new model of your own. You want to correct them for bias? That’s a model you’ve created.
If you use external forecasts as data, as inputs, you are using them in “black-box fashion”.