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Aggregate Dynamics in Models with Heterogeneous Agents
Bounded Learning from Incumbent Firms
Erzo Luttmer, University of Minnesota, Twin Cities
Wednesday, October 27, 2021
Abstract: Social learning plays an important role in models of productivity dispersion and long-run growth. In economies with a continuum of producers and unbounded productivity distributions, social learning can sometimes leave long-run growth rates completely indeterminate. This paper modifies a model in which potential entrants attempt to imitate randomly selected incumbent firms by introducing an upper bound on how much entrants can learn from incumbents. When this upper bound is taken to infinity, a unique long-run growth rate emerges, even though the economy without upper bound has an unbounded continuum of balanced growth rates.