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Quantifying spatial misallocaton in centrally provided public goods

Author

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  • Siva Athreya

    (Indian Statistical Institute, New Delhi)

  • Rohini Somanathan

    (Indian Statistical Institute, New Delhi)

Abstract

We show how an optimization algorithm can be used to approximately quantify the costs to users of spatial misallocation in centrally provided goods.These methods can be employed to evaluate the large programs of public good construction that have been central features of economic plans in many developing countries. We apply these methods to the allocation of post-offices in an administrative block of South India between 1981-1991 and find that more appropriate choices for post office locations could have reduced aggregate costs of travel to citizens in this area by at least 20.

Suggested Citation

  • Siva Athreya & Rohini Somanathan, 2004. "Quantifying spatial misallocaton in centrally provided public goods," Discussion Papers 04-07, Indian Statistical Institute, Delhi.
    • Handle: RePEc:alo:isipdp:04-07
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    File URL: http://www.isid.ac.in/~pu/dispapers/dp04-07.pdf
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    1. Banerjee, Abhijit & Somanathan, Rohini, 2007. "The political economy of public goods: Some evidence from India," Journal of Development Economics, Elsevier, vol. 82(2), pages 287-314, March.
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    3. Guilhem Cassan, 2015. "Identity-Based Policies and Identity Manipulation: Evidence from Colonial Punjab," American Economic Journal: Economic Policy, American Economic Association, vol. 7(4), pages 103-131, November.
    4. Fredriksson, Anders, 2017. "Location-allocation of public services – Citizen access, transparency and measurement. A method and evidence from Brazil and Sweden," Socio-Economic Planning Sciences, Elsevier, vol. 59(C), pages 1-12.

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    More about this item

    JEL classification:

    • H41 - Public Economics - - Publicly Provided Goods - - - Public Goods
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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