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Optimal Stabilization Policy in the Presence of Learning by Doing
Author(s) -
Martin Philippe,
Rogers Carol Ann
Publication year - 2000
Publication title -
journal of public economic theory
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.809
H-Index - 32
eISSN - 1467-9779
pISSN - 1097-3923
DOI - 10.1111/1097-3923.00037
Subject(s) - subsidy , economics , recession , stabilization policy , term (time) , production (economics) , state (computer science) , microeconomics , macroeconomics , monetary policy , computer science , market economy , physics , algorithm , quantum mechanics
This paper analyses the optimal stabilization policy when growth is driven by learning by doing. If benefits of learning by doing are not fully internalized, the optimal policy is to tax labor during expansions and to subsidize it during recessions. The long‐term impact of this policy depends critically on initial conditions: If stabilization starts during an expansion, it has a positive effect on long‐term production. When stabilization starts during a recession, its long‐term effect is negative. The paper makes a methodological contribution in its analytical derivation of the optimal policy along the transition path as well as in the steady state.