The Journal of Politics

ARTICLES

Distributive Politics and the Law of 1/n*

David M. Primoa1 and James M. Snyder Jr.a2

a1 University of Rochester

a2 Massachusetts Institute of Technology

Abstract

Distributive politics models often predict that legislators will demand inefficiently large projects, with inefficiency increasing in the number of districts, and that this will translate into larger projects and higher spending. The relationship between efficiency and legislature size is often referred to as the “law of 1/n”(Weingast, Shepsle, and Johnsen 1981). We demonstrate that the “law of 1/n” result with respect to project sizes and total spending is dependent on several factors, including the type of good being provided, the costs of raising revenue, and whether the local government has to share in the project's cost with the central government. In general, the “law of 1/n” need not hold for total government spending, and in fact a “reverse law of 1/n” often holds. In light of our theoretical findings, we reassess the empirical literature on this topic. The results have implications for a wide variety of applications in American and comparative politics.

(Received December 20 2006)

(Accepted May 25 2007)

Footnotes

* A previous version of this paper, “Public Goods and the Law of 1/n,” was presented at the 2005 annual meeting of the Midwest Political Science Association. Snyder thanks the W. Allen Wallis Institute of Political Economy for its generous support. Primo gratefully acknowledges the support of the National Science Foundation (Grant #SES-0314786). We would like to thank anonymous reviewers and the editor for helpful comments and Kris Ramsay and Muhammet Bas for excellent research assistance in the early stages of this project.

David M. Primo is assistant professor of political science, University of Rochester, Rochester, NY 14627. James M. Snyder, Jr. is Arthur and Ruth Sloan professor of political science and professor of economics. Massachusetts Institute of Technology, Cambridge, MA 02139.

Metrics