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Optimal Design of Social Security Reforms

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  • Juan Carlos Conesa
  • Carlos Garriga

Abstract

We argue that a privatization of the social security system, going from a Pay-As-You- Go to a Fully Funded system, can be interpreted as the explicit recognition of an implicit debt and there is no efficiency gain in doing so. As a consequence, potential efficiency gains upon reforming the system come from the elimination of distortions and the optimal management of that implicit debt. Based on that argument, this paper studies the optimal design of a social security privatization in a Pareto improving way. The government decides endogenously how to finance the transition and the welfare of the initial generations alive becomes policy constraint. We find that the government can design a Pareto improving reform that exhibits sizeable welfare gains, arising because of a reduction in labor supply distortions. In contrast, the welfare gain from reducing savings distortions is relatively small. Our approach explicitly provides quantitative policy prescriptions towards the policy design of future and maybe unavoidable social security reforms.

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  • Juan Carlos Conesa & Carlos Garriga, 2004. "Optimal Design of Social Security Reforms," Working Papers 140, Barcelona School of Economics.
  • Handle: RePEc:bge:wpaper:140
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    15. Carlos Garriga, 2019. "Optimal Fiscal Policy in Overlapping Generations Models," Public Finance Review, , vol. 47(1), pages 3-31, January.
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    Cited by:

    1. Mr. Alfredo Cuevas & Ms. Maria Gonzalez & Arnoldo López-Marmolejo & Davide Lombardo, 2008. "Pension Privatization and Country Risk," IMF Working Papers 2008/195, International Monetary Fund.
    2. Dirk Krueger, 2006. "Public Insurance against Idiosyncratic and Aggregate Risk: The Case of Social Security and Progressive Income Taxation," CESifo Economic Studies, CESifo Group, vol. 52(4), pages 587-620, December.
    3. Juan Carlos Conesa & Carlos Garriga, 2004. "Optimal Response to a Demographic Shock," Working Papers 157, Barcelona School of Economics.

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