Demand Learning and Firm Dynamics: Evidence from Exporters
Author(s) -
Nicolas Berman,
Vincent Rebeyrol,
Vincent Vicard
Publication year - 2018
Publication title -
the review of economics and statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 8.999
H-Index - 165
eISSN - 1530-9142
pISSN - 0034-6535
DOI - 10.1162/rest_a_00731
Subject(s) - demand shock , shock (circulatory) , demand forecasting , dynamics (music) , on demand , economics , demand management , process (computing) , bayesian probability , microeconomics , supply and demand , demand patterns , econometrics , industrial organization , computer science , artificial intelligence , commerce , operations management , psychology , macroeconomics , medicine , pedagogy , operating system
This paper provides direct evidence that learning about demand is an important driver of firms’ dynamics. We present a model of Bayesian learning in which firms are uncertain about idiosyncratic demand in each market and update their beliefs as noisy information arrives. Firms update their beliefs to a given demand shock more, the younger they are. We test and empirically confirm this prediction, using the structure of the model, together with exporter-level data, to identify demand shocks and the firms’ beliefs about future demand. Consistent with theory, we also find the learning process to be weakened in more uncertain environments.
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