Responding to a stated preference discrete choice experiment (DCE) is a complex task for respondents to undertake. Task complexity can induce response error, thereby decreasing the statistical precision of the econometric model. This study explores the link between task complexity and statistical precision as moderated by the level of thoughtful deliberation respondents exert when completing choice tasks. To do this, we make novel use of subjects’ certainty of response to DCE tasks as a measure of their deliberation. The distinction between intuitive and deliberate thought (System 1 and System 2, respectively) motivates how task complexity will differentially affect System 1 and System 2 respondents. The principle of utility balance in experimental design theory is used to understand how greater deliberation will increase task complexity, but will also improve statistical precision if respondents are engaging in System 2 processing. Our analyses find that increases in choice task utility balance decreases response certainty, and re-weighting the regression to favor respondents who are more uncertain of their choices increases the statistical precision of the econometric model.
