2017/31 | LEM Working Paper Series | ||||||||||||||||
Rational Heuristics? Expectations and Behaviors in Evolving Economies with Heterogeneous Interacting Agents |
|||||||||||||||||
Giovanni Dosi, Mauro Napoletano, Andrea Roventini, Joseph E. Stiglitz and Tania Treibich |
|||||||||||||||||
Keywords | |||||||||||||||||
complexity, expectations, heterogeneity, heuristics, learning, agent-based model, computational economics
|
|||||||||||||||||
JEL Classifications | |||||||||||||||||
C63, E32, E6, G01, G21, O4
|
|||||||||||||||||
Abstract | |||||||||||||||||
We analyze the individual and macroeconomic impacts of heterogeneous
expectations and action rules within an agent-based model populated by
heterogeneous, interacting firms. Agents have to cope with a complex
evolving economy characterized by deep uncertainty resulting from
technical change, imperfect information and coordination hurdles. In
these circumstances, we find that neither individual nor macroeconomic
dynamics improve when agents replace myopic expectations with less
naı̈ve learning rules. In fact, more sophisticated, e.g. recursive
least squares (RLS) expectations produce less accurate individual
forecasts and also considerably worsen the performance of the
economy. Finally, we experiment with agents that adjust simply to
technological shocks, and we show that individual and aggregate
performances dramatically degrade. Our results suggest that fast and
frugal robust heuristics are not a second-best option: rather they are
“rational” in macroeconomic environments with heterogeneous,
interacting agents and changing “fundamentals”.
|
Downloads
|
|
| |
|
Back
|
|