Can anyone provide me with a stimulus critic that actually tries to grapple with endogeneity issues when they look at the data?
I know it's just a blog post, but Casey Mulligan has a post up today that just looks at the raw data. His version of a counter-factual is to assume economic projections early in the downturn were right (hmmm...). He's not alone. John Taylor regulalry dumps some BEA numbers into excel and calls it a day. In a recent working paper by Cogan and Taylor, their counterfactual is that most of the stimulus spending to states went to reduce borrowing, and that purchases would not have changed at all in the absence of the stimulus (see page 13 and 14). Guess what - when you assume a "no effect" multiplier when designing your counter-factuals, you end up getting no effect in your results. Shocking! This is Stanford University and the University of Chicago being represented here.
I would be more open to these positions if any of these guys made any effort at all to even acknowledge the endogeneity problems and tried to objectively deal with them, rather than assuming their own conclusions and passing it off as economic science. I can think of one stimulus skeptic who has done this: Robert Barro. And he has a very interesting identification strategy. I like to highlight Barro's work whenever I criticize others' work because he actually makes a good effort. My critique of Barro is not that he does something wrong, but that his findings aren't generalizable. When you estimate multipliers outside of depressionary conditions you can't claim to have an estimate of what the multiplier would be in a depression. We expect it to change. But Barro provides good evidence that government spending crowds out private spending in normal times.
Anyway - just frustrating to see Mulligan this morning. These guys essentially assume their conclusions and a lot of people still take these to be reasonable claims.