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Title: Endogenous learning in input-output economies Authors:  Stefano Nasini - IESEG School of Management (France) [presenting]
Nessah Rabia - IESEG School of Management (France)
Abstract: Consider a multisector general equilibrium model where firms have incomplete information about the return to scale of their production and that information is sequentially updated once real production is observed. What is the impact of these learning dynamics on the market-wise equilibrium objects? Under which conditions firms are able to efficiently learn their actual return to scale? At which rate does this learning happen? We analyze endogenous learning mechanisms and their implications for the market-wise equilibrium objects in the multisector model. The results shed light on how idiosyncratic shocks translate into learning dynamics of the input-output elasticity structure. In particular, we observe that (i) all the relevant information in the learning dynamics are encoded in the input decisions; (ii) firms are able to learn the actual return to scale independently from the way in which input decisions are taken; (iii) the mismatch between the true (unknown) returns to scale and the ones predicted by firms has a critical effect on the aggregate production, which is amplified when the economy is intensive in capital.