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Spatial probit and the geographic patterns of state lotteries

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Author Info

  • Cletus C. Coughlin
  • Thomas A. Garrett
  • Rubén Hernández-Murillo

Abstract

We implement a spatial probit model to differentiate states with a lottery from those without a lottery. Our analysis extends the basic spatial probit model by allowing spatial dependence to vary across geographic regions. We also separate the spatial effects of neighbors versus non-neighbors. The methodology provides consistent and efficient coefficient estimation in light of the simultaneity in spatial dependence. We find evidence of spatial dependence and spatial heterogeneity in lottery usage, and we find that spatial patterns differ significantly by geographic region. The importance of spatial dependence in state lottery usage suggests the need to consider spatial effects in empirical models examining the use of any policy tool by subnational governmental units.

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Bibliographic Info

Paper provided by Federal Reserve Bank of St. Louis in its series Working Papers with number 2003-042.

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Date of creation: 2004
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Handle: RePEc:fip:fedlwp:2003-042

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Keywords: Regional economics;

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References

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  1. Garrett, Thomas A. & Marsh, Thomas L., 2002. "The revenue impacts of cross-border lottery shopping in the presence of spatial autocorrelation," Regional Science and Urban Economics, Elsevier, vol. 32(4), pages 501-519, July.
  2. Franklin Mixon & Steven Caudill & Jon Ford & Ter Peng, 1997. "The rise (or fall) of lottery adoption within the logic of collective action: Some empirical evidence," Journal of Economics and Finance, Springer, vol. 21(1), pages 43-49, March.
  3. Case, Anne C. & Rosen, Harvey S. & Hines, James Jr., 1993. "Budget spillovers and fiscal policy interdependence : Evidence from the states," Journal of Public Economics, Elsevier, vol. 52(3), pages 285-307, October.
  4. Murdoch, James C. & Sandler, Todd & Vijverberg, Wim P. M., 2003. "The participation decision versus the level of participation in an environmental treaty: a spatial probit analysis," Journal of Public Economics, Elsevier, vol. 87(2), pages 337-362, February.
  5. Rubén Hernández-Murillo, 2003. "Strategic interaction in tax policies among states," Review, Federal Reserve Bank of St. Louis, issue May, pages 47-56.
  6. Brueckner, Jan K. & Saavedra, Luz A., 2001. "Do Local Governments Engage in Strategic Property-Tax Competition?," National Tax Journal, National Tax Association, vol. 54(n. 2), pages 203-30, June.
  7. Dubin, Robin A, 1988. "Estimation of Regression Coefficients in the Presence of Spatially Autocorrelated Error Terms," The Review of Economics and Statistics, MIT Press, vol. 70(3), pages 466-74, August.
  8. Anselin, Luc, 2002. "Under the hood : Issues in the specification and interpretation of spatial regression models," Agricultural Economics, Blackwell, vol. 27(3), pages 247-267, November.
  9. P Bodson & D Peeters, 1975. "Estimation of the coefficients of a linear regression in the presence of spatial autocorrelation. An application to a Belgian labour-demand function," Environment and Planning A, Pion Ltd, London, vol. 7(4), pages 455-472, April.
  10. Cletus C. Coughlin & Eran Segev, 1999. "Foreign direct investment in China: a spatial econometric study," Working Papers 1999-001, Federal Reserve Bank of St. Louis.
  11. Case, Anne, 1992. "Neighborhood influence and technological change," Regional Science and Urban Economics, Elsevier, vol. 22(3), pages 491-508, September.
  12. Alm, James & McKee, Michael J. & Skidmore, Mark, 1993. "Fiscal Pressure, Tax Competition, and the Introduction of State Lotteries," National Tax Journal, National Tax Association, vol. 46(4), pages 463-76, December.
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Cited by:
  1. Kent Grote & Victor Matheson, 2011. "The Economics of Lotteries: An Annotated Bibliography," Working Papers 1110, College of the Holy Cross, Department of Economics.
  2. Luisa Alamá-Sabater & Andrés Artal-Tur & José Navarro-Azorín, 2011. "Industrial location, spatial discrete choice models and the need to account for neighbourhood effects," The Annals of Regional Science, Springer, vol. 47(2), pages 393-418, October.
  3. Sarker, M. Mizanur Rahman, 2012. "Spatial modeling of households’ knowledge about arsenic pollution in Bangladesh," Social Science & Medicine, Elsevier, vol. 74(8), pages 1232-1239.
  4. Jia Yan & Xiaowen Fu & Tae Oum, 2008. "Exploring Network Effects of Point-to-Point Networks: An Investigation of the Spatial Entry Patterns of Southwest Airlines," Working Papers 2008-21, School of Economic Sciences, Washington State University.

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