用反应时间数据更准地估计人的偏好，尤其适合研究拖延决策。
A General Framework for Estimating Preferences Using Response Time Data
- 结合选择与反应时间，构建通用偏好估计方法
- 在拖延实验中显著提升预测精度，影响关键经济参数估计
- 适用于扩散模型及多种决策模型，适合行为经济学研究
我们提出一种通用方法，从选择和反应时间数据中恢复偏好参数。当应用于流行的漂移扩散模型（DDM）时，该方法可实现 $1/n$ 的快速收敛率（$n$ 为数据点数），且广泛适用于 DDM 的推广形式及其他利用反应时间的决策模型。论文通过一个跨期选择实验的实证应用，表明引入反应时间能显著提高预测准确性，并对经济相关参数的估计产生实质性影响。
原文摘要 · Abstract (English)
We propose a general methodology for recovering preference parameters from data on choices and response times. Our methods yield estimates with fast ($1/n$ for $n$ data points) convergence rates when specialized to the popular Drift Diffusion Model (DDM), but are broadly applicable to generalizations of the DDM as well as to alternative models of decision making that make use of response time data. The paper develops an empirical application to an experiment on intertemporal choice, showing that the use of response times delivers predictive accuracy and matters for the estimation of economically relevant parameters.
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