David Colander

This paper argues that macro models should be as simple as possible, but not more so. Existing models are “more so ” by far. It is time for the science of macro to step beyond representative agent, DSGE models and focus more on alternative heterogeneous agent macro models that take agent interaction, complexity, coordination problems and endogenous learning seriously. It further argues that as analytic work on these scientific models continues, policy-relevant models should be more empirically based; policy researchers should not approach the data with theoretical blinders on; instead, they should follow an engineering approach to policy analysis and let the data guide their choice of the relevant theory to apply. Beyond DSGE Models: Towards an Empirically-Based Macroeconomics Maybe there is in human nature a deep-seated perverse pleasure in adopting and defending a wholly counterintuitive doctrine that leaves the uninitiated peasant wondering what planet he or she is on.— Robert Solow1 There has, for some time, been a strong undercurrent of opposition to modern macroeconomic models which, in their latest incarnation, have coalesced around dynamic stochastic genera