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Improving Ecological Inference by Predicting Individual Ethnicity from Voter Registration Records

  • Kosuke Imai (a1) and Kabir Khanna (a2)

Abstract

In both political behavior research and voting rights litigation, turnout and vote choice for different racial groups are often inferred using aggregate election results and racial composition. Over the past several decades, many statistical methods have been proposed to address this ecological inference problem. We propose an alternative method to reduce aggregation bias by predicting individual-level ethnicity from voter registration records. Building on the existing methodological literature, we use Bayes's rule to combine the Census Bureau's Surname List with various information from geocoded voter registration records. We evaluate the performance of the proposed methodology using approximately nine million voter registration records from Florida, where self-reported ethnicity is available. We find that it is possible to reduce the false positive rate among Black and Latino voters to 6% and 3%, respectively, while maintaining the true positive rate above 80%. Moreover, we use our predictions to estimate turnout by race and find that our estimates yields substantially less amounts of bias and root mean squared error than standard ecological inference estimates. We provide open-source software to implement the proposed methodology.

Copyright

COPYRIGHT: © The Author 2016. Published by Oxford University Press on behalf of the Society for Political Methodology 

Corresponding author

e-mail: kimai@princeton.edu; URL: http://imai.princeton.edu (corresponding author)

Footnotes

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Authors' note: We thank Bruce Willsie, the CEO of L2, for the data and answering numerous questions, and the participants of “Building the Evidence to Win Voting Rights Cases” conference at the American Constitutional Society for Law and Policy for their helpful comments. Two anonymous reviewers provided helpful suggestions. The R package, wru: Who Are You? Bayesian Prediction of Racial Category Using Surname and Geolocation, is freely available for download at https://cran.r-project.org/package=wru. Replication files for this study are available on the Political Analysis Dataverse at http://dx.doi.org/10.7910/DVN/SVY5VF. Supplementary materials for this article are available on the Political Analysis Web site.

Footnotes

References

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Ansolabehere, S., and Hersh, E. 2003. Gender, age, race, and voting: A research note. Politics and Governance 1(2): 132–37.
Barber, M., and Imai, K. 2013. Estimating neighborhood effects on turnout from geocoded voter registration records. Working Paper available at http://imai.princeton.edu/research/neighbor.html (accessed February 24, 2016).
Barreto, M. A. 2007. Si Se Puede! Latino candidates and the mobilization of Latino voters. American Political Science Review 101(3): 425–41.
Barreto, M. A., Segura, G. M., and Woods, N. D. 2004. Mobilizing effect of majority-minority districts. American Political Science Review 98(1): 65–75.
Dempster, A. P., Laird, N. M., and Rubin, D. B. 1977. Maximum likelihood from incomplete data via the EM algorithm (with discussion). Journal of the Royal Statistical Society, Series B, Methodological 39(1): 1–37.
Elliott, M. N., Fremont, A., Morrison, P. A., Pantoja, P., and Lurie, N. 2008. A new method for estimating race/ethnicity and associated disparities where administrative records lack self-reported race/ethnicity. Health Services Research 43(5p1): 1772–36.
Elliott, M. N., Morrison, P. A., Fremont, A., McCaffrey, D. F., Pantoja, P., and Lurie, N. 2009. Using the Census Bureau's surname list to improve estimates of race/ethnicity and associated disparities. Health Services and Outcomes Research Methodology 9(2): 69–83.
Enos, R. D. 2015. Testing the elusive: A field experiment on intergroup competition and voting. Working Paper, Department of Government, Harvard University.
Fieldhouse, E., and Cutts, D. 2008. Diversity, density and turnout: The effect of neighbourhood ethno-religious composition on voter turnout in Britain. Political Geography 27(5): 530–48.
Fiscella, K., and Fremont, A. M. 2006. Use of geocoding and surname analysis to estimate race and ethnicity. Health Services Research 41(4p1): 1482–500.
Fraga, B. 2013. Winning the race, losing the base? Demobilization, competitiveness, and electoral influence. Working Paper, Department of Political Science, Indiana University.
Fraga, B. 2016. Candidates or districts? Reevaluating the role of race in voter turnout. American Journal of Political Science 60(1): 97–122.
Gay, C. 2001. The effect of black congressional representation on political participation. American Political Science Review 95(3): 589–602.
Goodman, L. 1953. Ecological regressions and behavior of individuals. American Sociological Review 18:663–66.
Greiner, J. D. 2007. Ecological inference in voting rights act disputes: Where are we now, and where do we want to be? Jurimetrics 47(2): 115–67.
Greiner, D. J., and Quinn, K. M. 2008. R × c ecological inference: bounds, correlations, flexibility and transparency of assumptions. Journal of the Royal Statistical Society, Series A 172(1): 67–81.
Greiner, D. J., and Quinn, K. M. 2010. Exit polling and racial bloc voting: Combining individual level and ecological data. Annals of Applied Statistics 4(4): 1774–96.
Hajnal, Z. L., and Trounstine, J. 2005. Where turnout matters: The consequences of uneven turnout in city politics. Journal of Politics 67(2): 515–35.
Harris, J. A. 2015. What's in a name? A method for extracting information about ethnicity from names. Political Analysis 23(2): 212–24.
Henderson, J. A., Sekhon, J. S., and Titiunik, R. 2014. Cause or effect? Turnout in Hispanic majority-minority districts. Department of Political Science, University of California, Berkeley.
Herron, M. C., and Sekhon, J. S. 2005. Black candidates and black voters: Assessing the impact of candidate race on uncounted vote rates. Journal of Politics 67(1): 154–77.
Imai, K., Lu, Y., and Strauss, A. 2008. Bayesian and likelihood inference for 2 × 2 ecological tables: An incomplete data approach. Political Analysis 16(1): 41–69.
Khanna, K., and Imai, K. 2016. Replication data for: Improving ecological inference by predicting individual ethnicity from voter registration records. http://dx.doi.org/10.7910/DVN/SVY5VF, Harvard Dataverse, V1 (accessed February 24, 2016).
King, G., 2004. A solution to the ecological inference problem: Reconstructing individual behavior from aggregate data. Princeton, NJ: Princeton University Press.
King, G., and Roberts, M. 2012. Ei: A(n r) program for ecological inference.
King, G., Rosen, O., and Tanner, M., eds. 2004. Ecological inference: New methodological strategies. Cambridge: Cambridge University Press.
Michelson, M. R. 2003. Getting out the Latino vote: How door-to-door canvassing influences voter turnout in rural central California. Political Behavior 25(3): 247–63.
Newport, F. 2013. Democrats racially diverse; Republicans mostly white—Gallup. http://www.gallup.com/poll/160373/democrats-racially-diverse-republicans-mostly-white.aspx (accessed January 24, 2015).
Tam Cho, W. K., Gimpel, J. G., and Dyck, J. J. 2006. Residential concentration, political socialization, and voter turnout. Journal of Politics 68(1): 156–67.
Wakefield, J. 2004. Ecological inference for 2 × 2 tables (with discussion). Journal of the Royal Statistical Society, Series A 167:385–445.
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Improving Ecological Inference by Predicting Individual Ethnicity from Voter Registration Records

  • Kosuke Imai (a1) and Kabir Khanna (a2)

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