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Splitting the Difference? Causal Inference and Theories of Split-party Delegations

Published online by Cambridge University Press:  04 January 2017

Daniel M. Butler  and
Matthew J. Butler
Daniel M. Butler*
Affiliation:
Department of Political Science, Encina Hall West, Room 100, Stanford University, Stanford, CA 94305
Matthew J. Butler
Affiliation:
Department of Economics, 549 Evans Hall, University of California, Berkeley, CA 94720. e-mail: butler@econ.berkeley.edu
*
e-mail: daniel_butler@stanford.edu (corresponding author)
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Abstract

We provide an introduction to the regression discontinuity design (RDD) and use the technique to evaluate models of sequential Senate elections predicting that the winning party for one Senate seat will receive fewer votes in the next election for the other seat. Using data on U.S. Senate elections from 1946 to 2004, we find strong evidence that the outcomes of the elections for the two Senate seats are independent.

Type
Research Article
Information
Political Analysis , Volume 14 , Issue 4 , Autumn 2006 , pp. 439 - 455
Copyright
Copyright © The Author 2006. Published by Oxford University Press on behalf of the Society for Political Methodology 

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Footnotes

Authors' note: An earlier version of this article was presented at the 2005 meeting of the Midwest Political Science Association. The authors wish to thank participants of that panel, seminar participants at Stanford and the University of California, Berkeley, and especially Richard Butler, Mo Fiorina, and Jonathan Wand for their feedback and suggestions on earlier versions of this article. Any remaining errors are our own.

References

Alesina, Alberto, Fiorina, Morris, and Rosenthal, Howard. 1991. Why Are There So Many Divided Senate Delegations? National Bureau of Economic Research Working Paper No. 3663.Google Scholar
Angrist, Joshua D., and Lavy, Victor. 1999. Using Maimonides Rule to Estimate the Effect of Class Size on Scholastic Achievement. Quarterly Journal of Economics 114(2): 533–75.Google Scholar
Ansolabehere, Stephen, Snyder, James M. Jr., and Charles Stewart, III. 2001. Candidate Positioning in U.S. House Elections. American Journal of Political Science 45(1): 136–59.Google Scholar
Brunell, Thomas L., and Grofman, Bernard. 1998. Explaining Divided U.S. Senate Delegations, 1788-1996: A Realignment Approach. American Political Science Review 92(2): 391–99.CrossRefGoogle Scholar
Burden, Barry C., and Kimball, David C. 2002. Why Americans Split Their Tickets: Campaigns, Competition, and Divided Government. Ann Arbor: University of Michigan Press.Google Scholar
DiNardo, John, and Lee, David S. 2004. Economic Impacts of New Unionization on Private Sector Employers: 1984-2001. Quarterly Journal of Economics 119(4): 1383–441.Google Scholar
Downs, Anthony. 1957. An Economic Theory of Democracy. New York: Harper and Row.Google Scholar
Fowler, James. 2005. Dynamic Responsiveness in the U.S. Senate. American Journal of Political Science 49(2): 299–312.Google Scholar
Gelman, Andrew, and King, Gary. 1990. Estimating Incumbency Advantage without Bias. American Journal of Political Science 34(4): 1142–64.Google Scholar
Groseclose, Tim, Levitt, Steven D., and Snyder, James M. Jr. 1999. Comparing Interest Group Scores across Time and Chambers: Adjusted ADA Scores for the U.S. Congress. American Political Science Review 93(1): 33–50.Google Scholar
Hahn, Jinyong, Todd, Petra, and van der Klaauw, Wilbert. 1999. Evaluating the Effect of an Antidiscrimination Law Using a Regression-Discontinuity Design. National Bureau of Economic Research Working Paper No. 7131.Google Scholar
Hahn, Jinyong, Todd, Petra, and van der Klaauw, Wilbert. 2001. Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design. Econometrica 69(1): 201–9.Google Scholar
Heckelman, Jac C. 2000. Sequential Elections and Overlapping Terms: Voting for US Senate. Journal of Economic Behavior and Organization 42(1): 97–108.Google Scholar
Heckelman, Jac C. 2004. A Spatial Model of U.S. Senate Elections. Public Choice 118(1): 87–103.Google Scholar
Judd, Charles M., and Kenny, David A. 1981. Estimating the Effects of Social Interventions. England: Cambridge University Press.Google Scholar
Jung, Gi-Ryong, Kenny, Lawrence W., and Lott, John R. Jr. 1994. An Explanation for Why Senators from the Same State Vote Differently So Frequently. Journal of Public Economics 54(1): 65–96.Google Scholar
Lee, David S. Forthcoming. Randomized Experiments from Non-Random Selection in U.S. House Elections. Journal of Econometrics.Google Scholar
Lee, David S., Moretti, Enrico, and Butler, Matthew J. 2004. Do Voters Affect or Elect Policies? Evidence from the U.S. House. Quarterly Journal of Economics 119(3): 807–59.Google Scholar
Leuven, Edwin, and Oosterbeek, Hessel. 2004. Evaluating the Effect of Tax Deductions on Training. Journal of Labor Economics 22(2): 461–88.Google Scholar
Mebane, Walter. 2000. Coordination, Moderation, and Institutional Balancing in American Presidential and House Elections. American Political Science Review 94(1): 37–57.Google Scholar
Mebane, Walter, and Sekhon, Jasjeet. 2002. Coordination and Policy Moderation at Midterm. American Political Science Review 96(1): 141–57.Google Scholar
Peltzman, Sam. 1976. Towards a More General Theory of Regulation. Journal of Law and Economics 19(2): 211–40.Google Scholar
Schiller, Wendy J. 2000. Partners and Rivals: Representation in US Senate Delegations. Princeton, NJ: Princeton University Press.Google Scholar
Schmidt, Amy B., Kenny, Lawrence W., and Morton, Rebecca B. 1996. Evidence on Electoral Accountability in the U.S. Senate: Are Unfaithful Agents Really Punished? Economic Inquiry 34(3): 545–67.Google Scholar
Segura, Gary M., and Nicholson, Stephen P. 1995. Sequential Choices and Partisan Transitions in U.S. Senate Delegations: 1972-1988. Journal of Politics 57(1): 86–100.Google Scholar
Shadish, William R., Cook, Thomas D., and Campbell, Donald T. 2002. Experimental and Quasi-experimental Designs for Generalized Causal Inference. Boston: Houghton Mifflin.Google Scholar
Stigler, George J. 1971. Theory of Regulation. Bell Journal of Economics and Management Science 2(1): 3–21.Google Scholar
Thistlethwaite, Donald, and Campbell, Donald. 1960. Regression-Discontinuity Analysis: An Alternative to Ex Post Facto Experiment. Journal of Educational Psychology 51: 301–17.Google Scholar
Trochim, William. 1984. Research Design for Program Evaluation: The Regression-Discontinuity Approach. Beverly Hills, CA: Sage.Google Scholar
van der Klaauw, Wilbert. 2002. Estimating the Effect of Financial Aid Offers on College Enrollment: A Regression-Discontinuity Approach. International Economic Review 43 (4): 1249–87.CrossRefGoogle Scholar
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