Hostname: page-component-6bf8c574d5-8gtf8 Total loading time: 0 Render date: 2025-02-20T22:14:46.370Z Has data issue: false hasContentIssue false
  • English
  • Français

Improving Ecological Inference by Predicting Individual Ethnicity from Voter Registration Records

Published online by Cambridge University Press:  04 January 2017

Kosuke Imai  and
Kabir Khanna
Kosuke Imai*
Affiliation:
Department of Politics and Center for Statistics and Machine Learning, Princeton University, Princeton, NJ 08544
Kabir Khanna
Affiliation:
Department of Politics, Princeton University, Princeton, NJ 08544
*
e-mail: kimai@princeton.edu; URL: http://imai.princeton.edu (corresponding author)
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

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.

Type
Letters
Information
Political Analysis , Volume 24 , Issue 2 , Spring 2016 , pp. 263 - 272
Copyright
Copyright © The Author 2016. Published by Oxford University Press on behalf of the Society for Political Methodology 

Footnotes

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.

References

Ansolabehere, S., and Hersh, E. 2003. Gender, age, race, and voting: A research note. Politics and Governance 1(2): 132–37.Google Scholar
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).Google Scholar
Barreto, M. A. 2007. Si Se Puede! Latino candidates and the mobilization of Latino voters. American Political Science Review 101(3): 425–41.Google Scholar
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.Google Scholar
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.Google Scholar
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.Google Scholar
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.Google Scholar
Enos, R. D. 2015. Testing the elusive: A field experiment on intergroup competition and voting. Working Paper, Department of Government, Harvard University.Google Scholar
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.Google Scholar
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.Google Scholar
Fraga, B. 2013. Winning the race, losing the base? Demobilization, competitiveness, and electoral influence. Working Paper, Department of Political Science, Indiana University.Google Scholar
Fraga, B. 2016. Candidates or districts? Reevaluating the role of race in voter turnout. American Journal of Political Science 60(1): 97–122.Google Scholar
Gay, C. 2001. The effect of black congressional representation on political participation. American Political Science Review 95(3): 589–602.Google Scholar
Goodman, L. 1953. Ecological regressions and behavior of individuals. American Sociological Review 18:663–66.Google Scholar
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.Google Scholar
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.CrossRefGoogle Scholar
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.Google Scholar
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.CrossRefGoogle Scholar
Harris, J. A. 2015. What's in a name? A method for extracting information about ethnicity from names. Political Analysis 23(2): 212–24.Google Scholar
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.Google Scholar
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.CrossRefGoogle Scholar
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.Google Scholar
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).Google Scholar
King, G., 2004. A solution to the ecological inference problem: Reconstructing individual behavior from aggregate data. Princeton, NJ: Princeton University Press.Google Scholar
King, G., and Roberts, M. 2012. Ei: A(n r) program for ecological inference.Google Scholar
King, G., Rosen, O., and Tanner, M., eds. 2004. Ecological inference: New methodological strategies. Cambridge: Cambridge University Press.Google Scholar
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.Google Scholar
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).Google Scholar
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.Google Scholar
Wakefield, J. 2004. Ecological inference for 2 × 2 tables (with discussion). Journal of the Royal Statistical Society, Series A 167:385–445.Google Scholar
Supplementary material: PDF

Imai and Khanna supplementary material

Appendix

Download Imai and Khanna supplementary material(PDF)
PDF 415.8 KB
Supplementary material: Image

Imai and Khanna supplementary material

Figure

Download Imai and Khanna supplementary material(Image)
Image 209.3 KB