Prior studies search for evidence that distributive spending influences Congress members’ vote shares but find limited evidence. The authors argue that Democratic and Republican members each benefit from different types of distributive projects. Democrats benefit from delivering spending projects (what most people think of as “pork”) to their constituents, while many Republican members benefit from delivering contingent liabilities (in which the federal treasury underwrites a private entity’s financial risk). Empirical tests using data from U.S. House elections between 1984 and 2002 generally confirm these hypotheses, with one exception: only Republicans in relatively conservative districts gain from contingent liabilities. This result is further explored in the text.
Ballot questions often feature obscure and legalistic language that is difficult to comprehend. Because the language of ballot questions is often unclear, the authors hypothesize that questions with lower readability will have higher roll-off because voters will not answer questions they do not understand. The authors use an objective measure of readability to code readability scores for 1,211 state-level ballot questions from 1997 to 2007. Using hierarchical linear regression models of state-level data, the authors find that increased complexity leads to more roll-off. The authors further analyze some possible influences on readability by examining whether it is affected by the question topic. Keywords direct democracy, elections, ballot language, participationDoes the complex language of ballot questions lead to roll-off? Direct democracy propositions are far more complex than traditional candidate vote decisions. These propositions ask the public about a variety of policies with few heuristics such as party identification or incumbency. In addition to these cognitive difficulties, they often feature obscure and legalistic language that is difficult to comprehend. The complex wording may explain why voting on ballot measures is often less than voting for higher offices on the same ballot, because people skip the measures they do not understand. We examine this potential impact on roll-off by using a quantifiable objective measure of language readability to determine the complexity of ballot question wording. To evaluate if readability influences roll-off, we coded readability scores for all state-level ballot questions from 1997 to 2007 (1,211 ballot measures). Using hierarchical linear regression models of state-level data while controlling for other known determinants, we find that less readability leads to more roll-off. We further analyze what influences ballot questions to be written in a less readable way, and whether readability is affected by question topic.Prior research has repeatedly shown that complex wording for survey questions increases nonresponse bias (e.g., Mondak 1994). Using this evidence, we expect poor readability to also increase nonresponse to ballot questions, known as roll-off. We find that the average readability of these questions is far above the reading levels of average citizens. By gathering the wording for each ballot measure and putting them through a Flesch-Kincaid Grade Level readability test, it is possible to ascertain at what grade level the question is written. For example, the median resident of the state of Georgia reads at an eighthgrade level. We find that the average Georgia ballot question is written so that understanding it requires someone to read at the equivalent of a twenty-second-grade level. This language complexity far surpasses a plausible level of understanding by the public.This research informs our understanding of direct democracy, as it examines in a new way the classic question of whether voters are prepared to directly make laws. If a major portion o...
Google Insights for Search provides a new and rich data source for political scientists, which may be particularly useful for state politics scholars. We outline the prior uses of Google Insights for Search in social and health sciences, explain the data-generating process, and test for the first time the validity of this data for state politics research. Our empirical test of validity shows that Google searches for ballot measures' names and topics in state one week before the 2008 Presidential election correlate with actual participation on those ballot measures. This demonstrates that the more Internet searches there were for a ballot measure, the less likely voters were to rolloff (not answering the question), and establishes the construct validity for this data for one important topic in state politics research. We also outline the limitations to this data source.
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