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Abstract

Interest groups are introduced in a spatial model of electoral competition between two political parties. We show that the presence of these interest groups increases the winning set, which is the set of policy platforms for the challenger that will defeat the incumbent. Therefore interest groups enhance the probability of the challenger winning the election.

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File URL: http://www.cesifo-group.de/portal/page/portal/DocBase_Content/WP/WP-CESifo_Working_Papers/wp-cesifo-2006/wp-cesifo-2006-04/cesifo1_wp1698.pdf
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Bibliographic Info

Paper provided by CESifo Group Munich in its series CESifo Working Paper Series with number 1698.

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Date of creation: 2006
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Handle: RePEc:ces:ceswps:_1698

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Related research

Keywords: spatial voting models; electoral competition; winning set; interest groups;

Other versions of this item:

Find related papers by JEL classification:

• D71 - Microeconomics - - Analysis of Collective Decision-Making - - - Social Choice; Clubs; Committees; Associations
• D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior

This paper has been announced in the following NEP Reports:

• NEP-ALL-2006-04-08 (All new papers)
• NEP-POL-2006-04-08 (Positive Political Economics)

References

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1. Vjollca Sadiraj & Jan Tuinstra & Frans Winden, 2005. "Interest group size dynamics and policymaking," Public Choice, Springer, vol. 125(3), pages 271-303, December.
2. Sadiraj, V. & Tuinstra, J. & Winden, F. van, 2004. "A Computational Electoral Competition Model with Social Clustering and Endogenous Interest Groups as Information Brokers," CeNDEF Working Papers 04-08, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
   
   • Vjollca Sadiraj & Jan Tuinstra & Frans Winden, 2006. "A computational electoral competition model with social clustering and endogenous interest groups as information brokers," Public Choice, Springer, vol. 129(1), pages 169-187, October.
   • Vjollca Sadiraj & Jan Tuinstra & Frans van Winden, 2004. "A computational electoral competition model with social clustering and endogenous interest groups as information brokers," Experimental Economics Center Working Paper Series 2006-19, Experimental Economics Center, Andrew Young School of Policy Studies, Georgia State University.
3. Potters, J.J.M. & Sloof, R., 1996. "Interest groups: A survey of empirical models that try to assess their influence," Open Access publications from Tilburg University urn:nbn:nl:ui:12-73373, Tilburg University.
   
   • Potters, Jan & Sloof, Randolph, 1996. "Interest groups: A survey of empirical models that try to assess their influence," European Journal of Political Economy, Elsevier, vol. 12(3), pages 403-442, November.
4. Kramer, Gerald H., 1977. "A dynamical model of political equilibrium," Journal of Economic Theory, Elsevier, vol. 16(2), pages 310-334, December.
5. George A. Akerlof & Rachel E. Kranton, 2000. "Economics And Identity," The Quarterly Journal of Economics, MIT Press, vol. 115(3), pages 715-753, August.

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Cited by:

1. Sadiraj, V. & Tuinstra, J. & Winden, F. van, 2004. "A Computational Electoral Competition Model with Social Clustering and Endogenous Interest Groups as Information Brokers," CeNDEF Working Papers 04-08, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
   
   • Vjollca Sadiraj & Jan Tuinstra & Frans Winden, 2006. "A computational electoral competition model with social clustering and endogenous interest groups as information brokers," Public Choice, Springer, vol. 129(1), pages 169-187, October.
   • Vjollca Sadiraj & Jan Tuinstra & Frans van Winden, 2004. "A computational electoral competition model with social clustering and endogenous interest groups as information brokers," Experimental Economics Center Working Paper Series 2006-19, Experimental Economics Center, Andrew Young School of Policy Studies, Georgia State University.
2. Altavilla, C & De Grauwe, Paul, 2006. "Forecasting and combining competing models of exchange rate determination," Open Access publications from Katholieke Universiteit Leuven urn:hdl:123456789/120865, Katholieke Universiteit Leuven.
   
   • Carlo Altavilla & Paul De Grauwe, 2010. "Forecasting and combining competing models of exchange rate determination," Applied Economics, Taylor and Francis Journals, vol. 42(27), pages 3455-3480.
   • Altavilla, Carlo & De Grauwe, Paul, 2010. "Forecasting and combining competing models of exchange rate determination," Open Access publications from Katholieke Universiteit Leuven urn:hdl:123456789/234426, Katholieke Universiteit Leuven.
   • Altavilla, Carlo & De Grauwe, Paul, 2010. "Forecasting and combining competing models of exchange rate determination," Open Access publications from Katholieke Universiteit Leuven urn:hdl:123456789/288330, Katholieke Universiteit Leuven.
   • Carlo Altavilla & Paul De Grauwe, 2006. "Forecasting and Combining Competing Models of Exchange Rate Determination," CESifo Working Paper Series 1747, CESifo Group Munich.
   • Carlo Altavilla & Paul De Grauwe, 2006. "Forecasting and Combining Competing Models of Exchange rate Determination," Discussion Papers 5_2006, D.E.S. (Department of Economic Studies), University of Naples "Parthenope", Italy.

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