Bounded Learning from Incumbent Firms
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.
File(s): File format is application/pdf https://www.minneapolisfed.org/research/wp/wp771.pdf
Provider: Federal Reserve Bank of Minneapolis
Part of Series: Working Papers
Publication Date: 2020-08-07