Estimating the Probability Distribution of Party Representation as a Result of Political Redistricting Using a Random Walk Monte Carlo Technique
With each decennial census states create the boundaries that are to be used for their legislative districts for the next ten years. In this paper we present a Random Walk Monte Carlo technique that can be used to determine the probability that a set of districts has been drawn without partisan bias – gerrymandered. This is done through the creation of random spanning trees to form the representative districts. Historical election results will then be used to estimate the party representation of that random redistricting map. Through bootstrapping a probability distribution can estimated. This distribution will be used to test the hypothesis that a particular redistricting plan does not disenfranchise voters of that state.
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Work Title Estimating the Probability Distribution of Party Representation as a Result of Political Redistricting Using a Random Walk Monte Carlo Technique Access Creators - Joseph Brian Adams
- Nathaniel H Netznik
Keyword - Gerrymandering
- Redistricting
- Monte Carlo simulation
- Bootstrapping
- Probability distribution
License In Copyright (Rights Reserved) Work Type Article Publisher - Journal of Management Policy and Practice
Publication Date August 23, 2021 Publisher Identifier (DOI) - https://doi.org/10.33423/jmpp.v22i2
Deposited August 30, 2022 Versions
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Updated Keyword Show ChangesKeyword
- Gerrymandering, Redistricting, Monte Carlo simulation, Bootstrapping, Probability distribution
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