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Optimal grants under asymmetric information: federalism versus devolution

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  • GRECO, Luciano

Abstract

Economic research has inquired the role of asymmetric information between central and local governments in shaping the structure of optimal regional grants. In the mainstream literature, the theoretical setting has been characterized by some basic informational asymmetry between central authority and local government (the informed party) about the state of regional social and economic fundamentals (i.e. adverse selection). This setting fits quite well in the stylized facts of consolidated federalism, while it is hardly satisfactory in the case of devolved-powers states: fiscal systems that were recently reformed in the sense of higher degree of decentralization of policy decision-making and implementation (e.g.: Belgium, Italy, etc.). This paper points out that the situation of newly decentralized public systems is better analyzed under pure moral hazard : the only source of asymmetric information is the imperfect verifiability of local policy (while the information about social and economic fundamentals is symmetric). Building on a simple model, it is shown that the sign of optimal distortion that grants induce on regional fiscal policy is likely to differ between federalism (adverse selection and moral hazard) and devolution (pure moral hazard).

Suggested Citation

  • GRECO, Luciano, 2003. "Optimal grants under asymmetric information: federalism versus devolution," LIDAM Discussion Papers CORE 2003024, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Handle: RePEc:cor:louvco:2003024
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    More about this item

    Keywords

    intergovernmental grants; adverse selection; moral hazard;
    All these keywords.

    JEL classification:

    • H77 - Public Economics - - State and Local Government; Intergovernmental Relations - - - Intergovernmental Relations; Federalism
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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