# When estimating a basic macroeconomics model, why is goodness of fit with labor data not often dealt with?

So when dealing with not-too-complex RBC models or New Keynesian models, we often arrive with a few final reduced-form equations, and as far as I know, we use these equations to estimate the model. For Gali's simple New Keynesian model we have consumption Euler equation, New Keynesian Phillips Curve and some form of Taylor rule.

But it seems that when estimating them, labor data (for example, labor $N_t$ in production function $Y_t = A_tN_t^{1-\alpha}$) seems to be dropped and not compared with model's prediction that can be inferred from coefficients and how reduced-form equations got derived.

Why is this comparison not often done? This seems to be an important indicator for a model..

It's somewhat public knowledge that Macroeconomic models don't fit labor data without

• High Frisch Elasticity (but Rogerson, Prescott try to argue for that)
• Preference shocks (but, as Chari, Kehoe, McGrattan (AER 2006?) show, we cannot really understand these properly
• Search&Matching with weird parametrization or assumed wage rigidity
• Some other spooky thing going on that helps fitting the data

So since we know it doesn't work out, why feel bad about posting the correlations and make everyone feel bad? :)

If it were to work out, surely post it though.

• So the answer is because none of the other emperors are wearing anything either? (Not criticizing your answer or sources, as I believe it to be accurate, just intellectually unsatisfying) – Jason Nichols Dec 18 '14 at 17:35
• @JasonNichols Every emperor is naked, and that fact is common knowledge. So there's no point in pointing it out. – FooBar Dec 18 '14 at 17:43
• thersa.org/events/rsaanimate/animate/… (Very relevant though NSFW-ish depending on your work's view of marker drawn naked emperors, but deals with the difference between common knowledge and collective knowledge and the importance of pointing things out even if everyone knows and everyone thinks everyone else knows them) – Jason Nichols Dec 18 '14 at 17:49