I'll get this thread started.

Friday music

Tonight's drink is a Manhattan.

The paper I'm reading today is the incredibly depressing Back to Square One: Identification Issues in DSGE Models, by Canova and Sala, 2009 JME. This paper went through a long revision process, and the working paper versions contain several instructive examples that were inevitably cut during the refereeing process.

The paper discusses identification, roughly, the extent to which we can learn about our DSGE models' parameters by estimating them with data. The results are somewhat distressing; many DSGE models are under-identified or not identified at all, and Canova is not particularly optimistic. It's a quite destructive paper. This paper kicked off the modern DSGE identification literature, with later papers trying to find conditions under which our models are identified, and if they aren't, what potential tricks we can use to make them identifiable (re-arranging some parameters, tweaking functional forms, using Bayesian priors, etc).