Dynamic taxes and quotas with learning
Dynamic taxes and quotas with learning
We compare dynamic taxes and quotas when a regulator and non-strategic firm have asymmetric information. The regulator learns by using either a tax or a quota that can be slack. With a tax, the information asymmetry is resolved in one period. Optimal learning using a quota is less transparent, but we show that learning never takes place gradually. In the first period, the regulator either acts myopically, or he tries to improve his information, but he never experiments in subsequent periods. We use this result to assess the informational advantage of taxes compared to quotas under asymmetric information.
prices, quantities, asymmetric information, searching
1661-1680
Costello, Christopher
49a957b1-21b2-470f-864e-a85e6e9abdd5
Karp, Larry
8d426eef-d88c-4e60-be58-ee1e23bd83a9
2004
Costello, Christopher
49a957b1-21b2-470f-864e-a85e6e9abdd5
Karp, Larry
8d426eef-d88c-4e60-be58-ee1e23bd83a9
Costello, Christopher and Karp, Larry
(2004)
Dynamic taxes and quotas with learning.
Journal of Economic Dynamics and Control, 28 (8), .
(doi:10.1016/S0165-1889(03)00082-4).
Abstract
We compare dynamic taxes and quotas when a regulator and non-strategic firm have asymmetric information. The regulator learns by using either a tax or a quota that can be slack. With a tax, the information asymmetry is resolved in one period. Optimal learning using a quota is less transparent, but we show that learning never takes place gradually. In the first period, the regulator either acts myopically, or he tries to improve his information, but he never experiments in subsequent periods. We use this result to assess the informational advantage of taxes compared to quotas under asymmetric information.
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Published date: 2004
Keywords:
prices, quantities, asymmetric information, searching
Identifiers
Local EPrints ID: 39694
URI: http://eprints.soton.ac.uk/id/eprint/39694
ISSN: 0165-1889
PURE UUID: 28dd49e5-a85d-4a0d-a0e2-09d678dabc7d
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Date deposited: 29 Jun 2006
Last modified: 15 Mar 2024 08:16
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Author:
Christopher Costello
Author:
Larry Karp
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