Happy Times: Measuring Happiness Using Response Times
针对幸福感调查中排序数据模型的识别问题，提出利用受访者反应时间中的计时效应来推断潜在变量分布，并通过在线实验验证了该方法，为检验传统分布假设提供了理论条件。
Surveys measuring happiness or preferences generate discrete ordinal data. Ordered response models, which are used to analyze such data, suffer from an identification problem. Their conclusions depend on distributional assumptions about a latent variable. We propose using response times to solve that problem. Response times contain information about the distribution of the latent variable through a chronometric effect. Using an online survey experiment, we verify the chronometric effect. We then provide theoretical conditions for testing conventional distributional assumptions. These assumptions are rejected in some cases, but overall our evidence is consistent with the qualitative validity of the conventional models.