Hostname: page-component-78c5997874-v9fdk Total loading time: 0 Render date: 2024-11-06T04:13:17.439Z Has data issue: false hasContentIssue false
  • English
  • Français

The Referendum Model: A 2010 Congressional Forecast

Published online by Cambridge University Press:  07 October 2010

Michael S. Lewis-Beck  and
Charles Tien
Michael S. Lewis-Beck
Affiliation:
University of Iowa
Charles Tien
Affiliation:
Hunter College and the Graduate Center, CUNY
Get access Rights & Permissions [Opens in a new window]

Extract

Congressional election forecasting has experienced steady growth. Currently fashionable models stress prediction over explanation. The independent variables do not offer a substantive account of the election outcome. Instead, these variables are tracking variables—that is, indicators that may trace the result but fail to explain it. The outstanding example is the generic ballot measure, which asks respondents for whom they plan to vote in the upcoming congressional race. While this variable correlates highly with presidential party House seat share, it is bereft of substance. The generic ballot measure is the archetypical tracking variable, and it holds pride of place in the Abramowitz (2010) model. Other examples of such tracking variables are exposed seats or lagged seats, features of the Campbell (2010) model. The difficulty with such tracking models is twofold. First, they are not based on a theory of the congressional vote. Second, because they are predictive models, they offer a suboptimal forecasting instrument when compared to models specified according to strong theory.

Type
Symposium
Information
PS: Political Science & Politics , Volume 43 , Issue 4 , October 2010 , pp. 637 - 638
Copyright
Copyright © American Political Science Association 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abramowitz, Alan. 2010. “How Large a Wave? Using the Generic Ballot to Forecast the 2010 Midterm Elections.” PS: Political Science and Politics 43 (4): 631–32.Google Scholar
Campbell, James E. 2004. “Introduction—The 2004 Presidential Election Forecasts.” PS: Political Science and Politics 37: 733–35.Google Scholar
Campbell, James E. 2010. “The Seats in Trouble Forecast of the 2010 Elections in the U.S. House.” PS: Political Science and Politics 43 (4): 627–30.Google Scholar
Lewis-Beck, Michael S., Jacoby, William, Norpoth, Helmut, and Weisberg, Herbert. 2008. The American Voter Revisited. Ann Arbor: University of Michigan Press.CrossRefGoogle Scholar
Lewis-Beck, Michael S., and Rice, Tom W.. 1984. “Forecasting Presidential Elections: A Comparison of Naive Models.” Political Behavior 6: 9–21.CrossRefGoogle Scholar
Lewis-Beck, Michael S., and Rice, Tom W.. 1992. Forecasting Elections. Washington, DC: Congressional Quarterly Press.Google Scholar
Lewis-Beck, Michael S., and Stegmaier, Mary. 2000. “Economic Determinants of Electoral Outcomes.” Annual Review of Political Science 3: 183–219.CrossRefGoogle Scholar
Lewis-Beck, Michael S., and Stegmaier, Mary. 2007. “Economic Models of Voting.” In The Oxford Handbook of Political Behavior, ed. Dalton, Russell J. and Klingeman, Hans-Dieter, 518–37. New York: Oxford University Press.Google Scholar
Lewis-Beck, Michael S., and Tien, Charles. 2000. “The Future in Forecasting: Prospective Presidential Models after the 1996 Election.” In Before the Vote: Forecasting American National Elections, ed. Campbell, Jim and Garand, James C., 83–102. Thousand Oaks, CA: Sage.Google Scholar
Lewis-Beck, Michael S., and Tien, Charles. 2008. “Forecasting Presidential Elections: When to Change the Model?” International Journal of Forecasting 24 (2): 227–36.CrossRefGoogle Scholar
Tufte, Edward R. 1978. Political Control of the Economy. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar