Estimation of Unobservable Household Time-Use Decision-Making Parameters

Effective policy analysis is predicated upon quantitative models, and forward-looking simulation is often limited to extensions of past events. However, the method of simulated moments (MSM) allows for estimates of unobservable parameters, making possible truly forward-looking quantitative models. In labor economics, existing estimates of household time-use decision parameters, performed by del Boca and Flinn using 2005 PSID data, are outdated by two decades and contain few robustness checks. Using the MSM, we estimate preference and efficiency parameters under a collaborative behavioral model. Data are a subset of the 2005, 2017, 2019, 2021, and 2023 PSID data, filtered by similar requirements to del Boca and Flinn. We successfully replicate prior results and show mixed robustness to sample and initial search conditions. Moreover, updated decision-making parameters suggest significant differences from 2005. This research begets further questions of the evolving nature of household time use decision dynamics and improves on existing parameter estimates for policy simulation.