Kling on the Stimulus Package and Macro

Arnold Kling, my go-to-guy anything macro-related, offers some thoughts on the stimulus package:

It would appear that the great claim to fame of the stimulus is that it kept state and local governments from having to reduce spending. If you combine that with wage stickiness at the state and local level (that is, if you believe that they would cut jobs rather than cut pay for government workers), then the stimulus saved jobs. From a Recalculation perspective, one might ask whether those are the jobs that you would want to save.

Here's an essay by Kling on why he lost faith in traditional macro. Some key snippets:

There are no controlled experiments in macroeconomics. We would like to observe what would happen to employment and output in the United States in 2010 under different stimulus proposals. Ideally, we could construct alternative universes with the exact same initial conditions and try different policies. In practice, this is not possible.

When researchers attempt macroeconometrics, they are attempting to turn different time periods into controlled experiments. In effect, we take the situation in 1980 and 2005 and identify the factors that cause them to be different. We are interested in the effects of particular factors, notably fiscal and monetary policy. This method is valid only if we have properly controlled for other factors. The way I see it, controlling for other factors is impossible, because structural change is too important, too multi-faceted, and too pervasive for any statistical methodology to overcome.

***

Because of the need to impose strong priors, the structural approach is nothing but a roundabout way of communicating the way you believe the economy works. The estimated equations are not being used to discover relationships. Instead, the equations are being used by the econometrician to communicate to others the econometrician's beliefs about how the economy ought to work. To a first approximation, using structural estimates is no different from creating a simulation model out of thin air by making up the parameters.

His concluding paragraph:

We badly want macroeconometrics to work. If it did, we could resolve bitter theoretical disputes with evidence. We could achieve better forecasting and control of the economy. Unfortunately, the world is not set up to enable macroeconometrics to work. Instead, all macroeconometric models are basically simulation models that use data for calibration purposes. People judge these models based on their priors for how the economy works. Imposing priors related to rational expectations does not change the fact that macroeconometrics provides no empirical information to anyone except those who happen to share all of the priors of the model-builder.