Estimating the Partisan Bias of Japanese Legislative Redistricting Plans Using a Simulation Algorithm

Although partisan gerrymandering has been found to be widespread for congressional redistricting in the United States, there exists little empirical research on legislative redistricting in other countries. We investigate the partisan bias of Japanese redistricting. Some scholars have argued that the prominent role played by the nonpartisan commission leaves little room for partisan gerrymandering. Others have pointed out, however, that the Japanese redistricting process may be subject to political influence because the members of the redistricting commission must be appointed by the Prime Minister and approved by the Diet. In addition, the commission invites the governor of each prefecture to provide their opinions on redistricting. We conduct a systematic empirical analysis to estimate the partisan bias of the 2022 Japanese Lower House redistricting plans. We apply a state-of-the-art redistricting simulation algorithm to generate a large number of alternative nonpartisan redistricting plans. The sampled plans are representative of the population of plans and are consistent with the redistricting rules with which the commission must comply. By comparing the enacted plan with this nonpartisan baseline, we quantify the extent to which the enacted plan favors a particular party. Unlike the traditional methods, our simulation approach accounts for political geography and redistricting rules specific to each prefecture. Our analysis shows that the Japanese redistricting process yields little partisan bias at both the prefecture and district levels.