Winning the Electoral College: How Presidential Candidates Optimally Allocate Resources across States
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Title:
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Winning the Electoral College: How Presidential Candidates Optimally Allocate Resources across States |
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Author:
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Marsden, Benjamin
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Advisor:
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Ball, Richard J.
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Department:
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Haverford College. Dept. of Economics |
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Type:
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Thesis (B.A.) |
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Running Time:
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291748 bytes |
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Issue Date:
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2008 |
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Abstract:
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This paper addresses the question of how candidates in a two-player, n-state election can optimally allocate their resources across states to maximize their probability of winning. It begins with an overview of the Electoral College system and an analysis of past theoretical papers. The model in this paper diverges from this literature in two respects. First, candidates are assumed to maximize their probability of winning rather than their expected number of electoral votes. Many authors have assumed the latter to simplify the problem, but the two objectives are not necessarily equivalent. Second, the functional form analyzed, which maps spending within a state to the probability that a candidate wins the state, has yet to be investigated in detail. In a simplified set-up no pure-strategy equilibrium emerges in this model, but a mixed strategy equilibrium does exist. This breaks with previous authors such as Snyder (1989), who have shown the existence of a pure-strategy equilibrium under certain conditions. The crucial difference between Snyder’s model and the one examined in this paper is the concavity of each candidate’s objective function. Concavity arises in Snyder’s model and fails to emerge in this paper because of differences in the second derivatives of the functions for the probability of winning a state. |
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Subject:
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Electoral college -- United States
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Subject:
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Presidents -- United States -- Election
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Terms of Use:
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http://creativecommons.org/licenses/by-nc/3.0/us/
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Permanent URL:
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http://hdl.handle.net/10066/1452
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Files in this item
Citation
Marsden, Benjamin.
"Winning the Electoral College: How Presidential Candidates Optimally Allocate Resources across States".
2008. Available electronically from
http://hdl.handle.net/10066/1452.
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