Econ Papers Daily / 期刊论文
估计努力和金钱上的现时偏向与成熟度
Estimating present bias and sophistication over effort and money
摘要
We design and conduct a real-effort experiment to jointly estimate present bias and sophistication across effort and monetary domains. Unlike prior work (e.g., Augenblick and Rabin, 2019; Fedyk, 2024), we do not assume that these parameters are identical across domains. We explain and empirically demonstrate how assuming identical sophistication across money and effort domains can bias the estimates of key parameters. In our online experiment, participants chose to (predicted to) complete 14% (10%) fewer tasks on the same day than on a future day, leading to an estimated present bias ( beta e $\beta_e$ β e ) over effort of 0.70–0.79, and an estimated sophistication ( beta caret e $\widehat{\beta}_e$ β ^ e ) of 0.80–0.88. For money, aggregate present bias ( beta m $\beta_m$ β m ) is near zero, but there is substantial heterogeneity, with roughly equal numbers of participants exhibiting present bias and future bias. At the individual level, roughly three quarters of all participants correctly anticipate the direction of their bias in both domains, even if not its full magnitude.
中文摘要
我们设计并实施了一项真实努力实验，以联合估计努力领域和货币领域中的现时偏向与老练程度。与先前研究（如Augenblick and Rabin, 2019; Fedyk, 2024）不同，我们并未假设这些参数在不同领域间具有一致性。我们解释并实证证明了：假设货币与努力领域的老练程度相同，会导致关键参数估计产生偏误。在我们的在线实验中，参与者当天完成的任务量比未来某天少14%（预测值为10%），由此估算的现时偏向系数接近于零，但存在显著的异质性——表现出现时偏向与未来偏向的参与者数量大致相当。在个体层面，约四分之三的参与者能正确预判自身在两个领域中的偏向方向，尽管未能完全预判其程度。