Building on the availability of geospatial data, improvements in mapping software, and innovations in spatial statistics, political scientists are increasingly taking geography seriously. As we adopt the tools of geographers, we must also consider the methodological challenges they have identified. We focus on the modifiable areal unit problem (MAUP)—the idea that the size of aggregate spatial units and the location of their borders affect the empirical results we obtain. We first describe the logic of the MAUP, and then demonstrate the MAUP through simulations, showing MAUP-related inconsistency in regression results in randomly generated and real-world data. We identify MAUP concerns, and best practices, in top journals in political science. We conclude by suggesting how scholars may respond in theoretical and empirical terms to concerns about validity and reliability that arise from the MAUP.

The link between objective facts and politically relevant beliefs is an essential mechanism for democratic accountability. Yet the bulk of empirical work on this topic measures objective facts at whatever geographic units are readily available. We investigate the implications of these largely arbitrary choices for predicting individual-level opinions. We show that varying the geographic resolution—namely aggregating economic data to different geographic units—influences the strength of the relationship between economic evaluations and local economic conditions. Finding that unemployment claims are the best predictor of economic evaluations, especially when aggregated at the commuting zone or media market level, we underscore the importance of the modifiable areal unit problem. Our methods provide an example of how applied scholars might investigate the importance of geography in their own research going forward.

Recent accounts of American politics focus heavily on urban–rural gaps in political behavior. Rural politics research is growing but may be stymied by difficulties defining and measuring which Americans qualify as “rural.” We discuss theoretical and empirical challenges to studying rurality. Much existing research has been inattentive to conceptualization and measurement of rural geography. We focus on improving estimation of different notions of rurality and provide a new dataset on urban–rural measurement of U.S. state legislative districts. We scrutinize construct validity and measurement in two studies of rural politics. First, we replicate Flavin and Franko (2020, Political Behavior, 845–864) to demonstrate empirical results may be sensitive to measurement of rural residents. Second, we use Mummolo and Nall’s (2017, The Journal of Politics, 45–59) survey data to show rural self-identification is not well-captured with objective, place-based classifications, suggesting a rethinking of theoretical and empirical accounts of rural identity. We conclude with strategies for operationalizing rurality using readily available tools.