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Private Information and Optimal Infant Industry Protection

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Abstract

We study infant industry protection using a dynamic model in which the industry's cost is initially higher than that of foreign competitors. The industry can stochastically lower its cost via learning by doing. Whether the industry has transitioned to low cost is private information. Using a mechanism-design approach, we solve for the optimal protection policy that induces the industry to reveal its true cost. We show that (i) the optimal protection, measured by infant industry output, declines over time and is less than that under public information, (ii) the optimal protection policy is time consistent under public information but not under private information, (iii) eventual viability of the infant industry is neither necessary nor sufficient for the optimal protection under private information, and (iv) the optimal protection policy can be implemented with minimal information requirements. We also deliver a one-dimensional metric to rank industries to help a government with a limited budget to choose which industries to protect.

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  • B. Ravikumar & Raymond Riezman & Yuzhe Zhang, 2022. "Private Information and Optimal Infant Industry Protection," Working Papers 2022-013, Federal Reserve Bank of St. Louis, revised 18 Apr 2024.
    • Handle: RePEc:fip:fedlwp:94263
    DOI: 10.20955/wp.2022.013
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    More about this item

    Keywords

    protection; infant industry; private information; mechanism design; time consistency;
    All these keywords.

    JEL classification:

    • F10 - International Economics - - Trade - - - General
    • F13 - International Economics - - Trade - - - Trade Policy; International Trade Organizations
    • O25 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - Industrial Policy
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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