Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/147230
Authors: 
Sato, Kimitoshi
Year of Publication: 
2016
Citation: 
[Journal:] Journal of Economic Structures [ISSN:] 2193-2409 [Volume:] 5 [Year:] 2016 [Issue:] 12 [Pages:] 1-31
Abstract: 
This paper revisits the family of MDP Procedures and analyzes their properties. It also reviews the procedure developed by Sato (Econ Stud Q 34:97-109, 1983) which achieves aggregate correct revelation in the sense that the sum of the Nash equilibrium strategies always coincides with the aggregate value of the correct marginal rates of substitution. The procedure named the Generalized MDP Procedure can possess other desirable properties shared by continuous-time locally strategy proof planning procedures, i.e., feasibility, monotonicity and Pareto efficiency. Under myopia assumption, each player's dominant strategy in the local incentive game associated at any iteration of the procedure is proved to reveal his/her marginal rate of substitution for a public good. In connection with the Generalized MDP Procedure, this paper analyzes the structure of the locally strategy proof procedures as algorithms and game forms. An alternative characterization theorem of locally strategy proof procedures is given by making use of the new condition, transfer independence. A measure of incentives is proposed to show that the exponent attached to the decision function of public good is characterized. A Piecewise Nonlinearized MDP Procedure is presented, which is coalitionally locally strategy proof. Equivalence between price-guided and quantity-guided procedures is also discussed.
Subjects: 
Aggregate correct revelation
Coalitional local strategy proof
Fujigaki-Sato Procedure
Generalized MDP Procedure
Local strategy proof
Measure of incentives
Piecewise Nonlinearized MDP Procedure
Price-quantity equivalence
Transfer independence
JEL: 
H41
Persistent Identifier of the first edition: 
Creative Commons License: 
http://creativecommons.org/licenses/by/4.0/
Document Type: 
Article

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