Rational Heuristics ? Expectations and behaviors in Evolving Economies with Heterogeneous interacting agents
Giovanni Dosi (),
Mauro Napoletano (),
Joseph Stiglitz and
Tania Treibich ()
No 32, Sciences Po publications from Sciences Po
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 naïve 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”.
Keywords: Complexity; Expectations; Heterogeneity; Heuristics; Learning; Agent based model; Computational economics (search for similar items in EconPapers)
JEL-codes: C63 E32 E6 G1 G21 O4 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cbe, nep-cmp, nep-hme, nep-mac, nep-ore and nep-upt
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Working Paper: Rational Heuristics ? Expectations and behaviours in evolving economies with heterogeneous interacting agents (2017)
Working Paper: Rational Heuristics? Expectations and Behaviors in Evolving Economies with Heterogeneous Interacting Agents (2017)
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