Abstract

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.

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