I came across this short paper by 4 economists on macroeconomic modelling. The focus of the paper is on the need for simpler macroeconomic models and go beyond DSGE models.
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.
I liked the paper more for its interesting account (brief though) of the history of macroeconomic modelling. It tells you how the thinking evolved and finally we had a DSGE model. Here is a sample:
The reason researchers clung to the rational expectations representative agent models for so long is not that they did not recognize their problems, but because of the analytical difficulties involved in moving beyond these models. Dropping the standard assumptions about agent rationality would complicate the already complicated models and abandoning the ad hoc representative agent assumption would leave them face to face with the difficulties raised by Sonnenschein, Mantel and Debreu.
Building more realistic models along these lines involves enormous work with little immediate payoff; one must either move beyond the extremely restrictive class of economic models to far more complicated analytic macro models, or one must replace the analytic modeling approach with virtual modeling. Happily, both changes are occurring; researchers are beginning to move on to models that attempt to deal with heterogeneous interacting agents, potential emergent macro properties, and behaviorally more varied and more realistic opportunistic agents.
Thankfully we are seeing some changes with more realistic model setting. However, the rep agent model is still too powerful.
Anyways a nice short discussion on history of macro modelling.