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Measuring Geographic Distribution for Political Research

Published online by Cambridge University Press:  18 March 2019

Dong Wook Lee Open the ORCID record for Dong Wook Lee [Opens in a new window]  and
Melissa Rogers Open the ORCID record for Melissa Rogers [Opens in a new window]
Dong Wook Lee
Affiliation:
Department of Political Science, Adelphi University, Garden City, NY 11530, USA. Email: [email protected]
Melissa Rogers*
Affiliation:
Department of International Studies, Claremont Graduate University, Claremont, CA 91711, USA. Email: [email protected]
*
*Email: [email protected]
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Abstract

Political scientists are increasingly interested in the geographic distribution of political and economic phenomena. Unlike distribution measures at the individual level, geographic distributions depend on the “unit question” in which researchers choose the appropriate political subdivision to analyze, such as nations, subnational regions, urban and rural areas, or electoral districts. We identify concerns with measuring geographic distribution and comparing distributions within and across political units. In particular, we highlight the potential for threats to inference based on the modifiable areal unit problem (MAUP), whereby measuring concepts at different unit aggregations alters the observed value. We offer tangible options for researchers to improve their research design and data analysis to limit the MAUP. To help manage the measurement error when the unit of observation is unclear or appropriate data are not available, we introduce a new measure of geographic distribution that accounts for fluctuations in the scale and number of political units considered. We demonstrate using Monte Carlo simulations that our measure is more reliable and stable across political units than commonly used indicators because it reduces measurement fluctuations associated with the MAUP.

Keywords

measurement errorecological inferenceMonte Carlo methodsecological fallacy
Type
Articles
Information
Political Analysis , Volume 27 , Issue 3 , July 2019 , pp. 263 - 280
Copyright
Copyright © The Author(s) 2019. Published by Cambridge University Press on behalf of the Society for Political Methodology. 

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Footnotes

Authors’ note: The authors thank Daniel Bochsler for help with construction of the geographic distribution measure. The authors greatly benefited from the feedback from Editor Jeff Gill, three anonymous reviewers, Ryan Bakker, Scott Desposato, Indridi Indridiason, Stephanie Rickard, Guillermo Rosas, and participants at SCCPI at UC San Diego, Faculty Research Colloquium at CSU Long Beach, and MPSA 2017 and 2018. Replication data are available at the Harvard Dataverse: https://doi.org/10.7910/DVN/DKY4DY

Contributing Editor: Jeff Gill

References

Amrhein, C. G. 1995. “Searching For the Elusive Aggregation Effect.” Environment and Planning A 27(1):105–119.Google Scholar
Arbia, G., and Petrarca, F.. 2011. “Effects of MAUP on Spatial Econometric Models.” Letters in Spatial and Resource Sciences 4(3):173.Google Scholar
Barro, R. J., and Sala-i Martin, X.. 1992. “Convergence.” Journal of Political Economy 100(2):223–251.Google Scholar
Beramendi, P., Lee, D. W., Rogers, M., and Wikstrom, K.. 2018. Endogenous regional borders. Technical report.Google Scholar
Beramendi, P., and Rogers, M.. 2018. “Disparate Geography and the Origins of Tax Capacity.” The Review of International Organizations , https://doi.org/10.1007/s11558-018-9319-2.Google Scholar
Berry, W. D., Golder, M., and Milton, D.. 2012. “Improving Tests of Theories Positing Interaction.” The Journal of Politics 74(3):653–671.Google Scholar
Bochsler, D. 2010. “Measuring Party Nationalisation.” Electoral Studies 29(1):155–168.Google Scholar
Brülhart, M., and Traeger, R.. 2005. “An Account of Geographic Concentration Patterns in Europe.” Regional Science and Urban Economics 35(6):597–624.Google Scholar
Caramani, D. 2004. The Nationalization of Politics . New York: Cambridge University Press.Google Scholar
Chen, J., and Rodden, J.. 2013. “Unintentional Gerrymandering: Political Geography and Electoral Bias in Legislatures.” Quarterly Journal of Political Science 8(3):239–269.Google Scholar
Dark, S. J., and Bram, D.. 2007. “The Modifiable Areal Unit Problem in Physical Geography.” Progress in Physical Geography 31(5):471–479.Google Scholar
Fortunato, D., Swift, C. S., and Williams, L. K.. 2016. “All Economics is Local.” Political Science Research and Methods 6(3):1–21.Google Scholar
Fotheringham, A. S. 1989. “Scale-Independent Spatial Analysis.” In Accuracy of Spatial Databases , edited by Goodchild, M. and Gopal, S., 221–228. London: Taylor and Francis.Google Scholar
Giraudy, A., and Pribble, J.. 2018. “Rethinking Measures of Democracy and Welfare State Universalism: Lessons from Subnational Research.” Regional and Federal Studies , https://doi.org/10.1080/13597566.2018.1473250.Google Scholar
Guo, J. Y., and Bhat, C. R.. 2007. “Operationalizing the Concept of Neighborhood.” Journal of Transport Geography 15(1):31–45.Google Scholar
Hammersley, M. 1987. “Some Notes on the Terms Validity and Reliability.” British Educational Research Journal 13(1):73–82.Google Scholar
Hay, G., Marceau, D., Dube, P., and Bouchard, A.. 2001. “A Multiscale Framework for Landscape Analysis.” Landscape Ecology 16(6):471–490.Google Scholar
Hayward, P., and Parent, J.. 2009. “Modeling the Influence of the Modifiable Areal Unit Problem on Poverty in Pennsylvania.” The Pennsylvania Geographer 47(1):120–135.Google Scholar
Hoover, G. A., and Pecorino, P.. 2005. “The Political Determinants of Federal Expenditure at the State Level.” Public Choice 123(1-2):95–113.Google Scholar
Jelinski, D. E., and Wu, J.. 1996. “The Modifiable Areal Unit Problem and Implications for Landscape Ecology.” Landscape Ecology 11(3):129–140.Google Scholar
Jurado, I., and Leon, S.. 2017. “Geography Matters.” British Journal of Political Science 1–23.Google Scholar
King, G. 2013. A Solution to the Ecological Inference Problem: Reconstructing Individual Behavior from Aggregate Data . Princeton: Princeton University Press.Google Scholar
Kwan, M.-P. 2012a). “How GIS Can Help Address The Uncertain Geographic Context Problem in Social Science Research.” Annals of GIS 18(4):245–255.Google Scholar
Kwan, M.-P. 2012b. “The Uncertain Geographic Context Problem.” Annals of the Association of American Geographers 102(5):958–968.Google Scholar
Laakso, M., and Taagepera, R.. 1979. “Effective” Number of Parties.” Comparative Political Studies 12(1):3–27.Google Scholar
Lee, D. W., and Rogers, M.. 2019. “Inter-Regional Inequality and the Dynamics of Government Spending.” The Journal of Politics 81(2):.Google Scholar
Lessmann, C. 2009. “Fiscal Decentralization and Regional Disparity.” Environment and Planning A 41(10):2455–2473.Google Scholar
Levitt, S. D., and Snyder, J. M.. 1995. “Political Parties and the Distribution of Federal Outlays.” American Journal of Political Science 39(4):958–980.Google Scholar
Michalopoulos, S. 2012. “The Origins of Ethnolinguistic Diversity.” American Economic Review 102(4):1508–1539.Google Scholar
Monogan, J. E., and Gill, J.. 2016. “Measuring State and District Ideology with Spatial Realignment.” Political Science Research and Methods 4(1):97–121.Google Scholar
Murguía, M., and Villaseñor, J. L.. 2000. “Estimating the Quality of the Records Used in Quantitative Biogeography with Presence–Absence Matrices.” Annales Botanici Fennici 37:289–296.Google Scholar
Openshaw, S. 1984. The Modifiable Areal Unit Problem . Norwich, UK: Geo Books.Google Scholar
Rey, S. J., and Janikas, M. V.. 2005. “Regional Convergence, Inequality, and Space.” Journal of Economic Geography 5(2):155–176.Google Scholar
Rickard, S. J. 2012. “Electoral Systems, Voters Interests, and Geographic Dispersion.” British Journal of Political Science 42(4):855–877.Google Scholar
Rodden, J. 2010. “The Geographic Distribution of Political Preferences.” Annual Review of Political Science 13:321–340.Google Scholar
Rodríguez-Pose, A., and Ezcurra, R.. 2009. “Does Decentralization Matter for Regional Disparities? A Cross-Country Analysis.” Journal of Economic Geography 10(5):619–644.Google Scholar
Rogers, M., and Lee, D. W.. 2019. “Measuring Geographic Distribution for Political Research.” https://doi.org/10.7910/DVN/DKY4DY, Harvard Dataverse. V1.Google Scholar
Soifer, H. D., and Alvarez, A. M.. 2017. “Choosing Units of Analysis in Subnational Research.” Working Paper.Google Scholar
Spiezia, V. 2002. Geographic Concentration of Production and Unemployment in OECD Countries . Paris: OECD.Google Scholar
Tam Cho, W. K., and Gimpel, J. G.. 2007. “Prospecting for (Campaign) Gold.” American Journal of Political Science 51(2):255–268.Google Scholar
Wong, D. 2009. “The modifiable Areal Unit Problem.” In The SAGE Handbook of Spatial Analysis , edited by Fotheringham, A. S. and Rogerson, P., 105–123. London: SAGE Publications.Google Scholar
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