Multiplicative interaction models are common in the quantitative political science literature. This is so for good reason. Institutional arguments frequently imply that the relationship between political inputs and outcomes varies depending on the institutional context. Models of strategic interaction typically produce conditional hypotheses as well. Although conditional hypotheses are ubiquitous in political science and multiplicative interaction models have been found to capture their intuition quite well, a survey of the top three political science journals from 1998 to 2002 suggests that the execution of these models is often flawed and inferential errors are common. We believe that considerable progress in our understanding of the political world can occur if scholars follow the simple checklist of dos and don'ts for using multiplicative interaction models presented in this article. Only 10% of the articles in our survey followed the checklist.

This article presents new evidence on the efforts of states to collect and process information about themselves, their territories, and their populations. We compile data on five institutions and policies: the regular implementation of a reliable census, the regular release of statistical yearbooks, the introduction of civil and population registers, and the establishment of a government agency tasked with processing statistical information. Using item response theory methods, we generate an index of “information capacity” for 85 states from 1789 to the present. We then ask how political regime changes have influenced the development of information capacity over time. In contrast with the literature on democracy and fiscal capacity, we find that suffrage expansions are associated with higher information capacity, but increases in the level of political competition are not. These findings demonstrate the value of our new measure, because they suggest that different elements of state capacity are shaped by different historical processes.

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