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Spatial Decentralization and Program Evaluation: Theory and an Example from Indonesia

  • Nidhiya Menon

    ()

    (Department of Economics, Brandeis University)

  • Mark M. Pitt

    (Brown University)

This paper proposes a novel instrumental variable method for program evaluation that only requires a single cross-section of data on the spatial intensity of programs and outcomes. The instruments are derived from a simple theoretical model of government decision-making in which governments are responsive to the attributes of places and their populations, rather than to the attributes of individuals, in making allocation decisions across space, and have a social welfare function that is spatially weakly separable, that is, that the budgeting process is multi-stage with respect to administrative districts and sub-districts. The spatial instrumental variables model is then estimated and tested by GMM with a single cross-section of Indonesian census data. The results offer support to the identification strategy proposed.

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File URL: http://www.brandeis.edu/departments/economics/RePEc/brd/doc/Brandeis_WP16.pdf
File Function: First version, 2010
Download Restriction: no

Paper provided by Brandeis University, Department of Economics and International Businesss School in its series Working Papers with number 16.

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Length: 31 pages
Date of creation: Sep 2010
Date of revision:
Handle: RePEc:brd:wpaper:16
Contact details of provider: Postal: MS032, P.O. Box 9110, Waltham, MA 02454-9110
Web page: http://www.brandeis.edu/departments/economics/

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  1. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2007. "Enhanced routines for instrumental variables/GMM estimation and testing," Boston College Working Papers in Economics 667, Boston College Department of Economics, revised 05 Sep 2007.
  2. Conley, Timothy G & Ligon, Ethan, 2002. " Economic Distance and Cross-Country Spillovers," Journal of Economic Growth, Springer, vol. 7(2), pages 157-87, June.
  3. Frank Kleibergen & Mark E Schaffer, 2007. "RANKTEST: Stata module to test the rank of a matrix using the Kleibergen-Paap rk statistic," Statistical Software Components S456865, Boston College Department of Economics, revised 24 Jan 2015.
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