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Modeling Workers' Daily Nonwork Activity Participation and Duration

机译：模拟工人的日常非工作活动参与和持续时间

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摘要

This paper presents a mathematical model used to determine jointly a worker's decision to participate in a nonhome and nonwork activity and the decision on how long to participate. With the household interview survey data from the New York City area, the workers' participation and duration decisions were estimated for each of five periods in a worker's day: before morning commute, morning commute, midday, evening commute, and after evening commute. To account for the censored nature of the duration data (i.e., a large number of observations clustered at zero), Heckman's sample selection model was used together with the full information maximum likelihood estimation method. To enhance the behavioral basis for the models, extensive statistical tests were given to the model specifications and the assumptions underlying the model structure. The empirical results provide useful insights into the effects of socio-demographics, land use-transportation measures, and activity duration characteristics on workers' daily scheduling of nonwork activities and travel in a highly urbanized environment. This study also provides exploratory methodologic evidence that could lead to an approach for predicting the change in a worker's nonwork activity patterns (participation and duration) as a result of changes in future demographic conditions and land use-transportation scenarios.
机译：本文提出了一种数学模型，用于共同确定工人参加非家庭和非工作活动的决定以及参与时间的决定。利用纽约市地区的家庭访问调查数据，估计了工人一天中五个时段的每个时段的工人参与和持续时间决定：早上上下班前，早上上下班，中午，晚上上下班以及晚上上下班之后。为了说明持续时间数据的审查性质（即大量观测值聚集在零上），将Heckman的样本选择模型与完整信息最大似然估计方法一起使用。为了增强模型的行为基础，对模型规格和模型结构基础的假设进行了广泛的统计检验。实证结果为社会人口统计学，土地使用-运输措施以及活动持续时间特征对工人在高度城市化环境中的日常非工作活动和出行日程安排的影响提供了有用的见解。这项研究还提供了探索性的方法学证据，这些方法可能会导致一种预测工人的非工作活动模式（参与度和工期）变化的方法，该方法是由于未来人口统计学条件和土地使用-运输情景的变化而产生的。

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