Abstract:
Central Park is an iconic feature of New York City, which was the first and one of the hardest hit cities in the United States by the Coronavirus. State-level stay-at-home order, raising COVID-19 cases, as well as the public\'s personal concerns regarding exposure to the virus, led to a significant reduction of Central Park visitation. We utilized extensive cellphone tracking data to conduct one of the pioneering empirical studies assessing the economic impact of COVID-19 on urban parks. We integrated the difference-in-difference (DID) design with the recreation-demand model. The DID design aids in identifying the causal impacts, controlling for unobservable factors that might confound the treatment effects of interest. Concurrently, the recreational demand model examines the driving factors of visitation changes and enables us to estimate the welfare changes experienced by New York City\'s residents. Our findings shine a light on the substantial, yet often overlooked, welfare loss triggered by the pandemic. The analysis indicates that the pandemic resulted in a 94% reduction in visitation, corresponding to an annual consumer surplus loss of $450 million. We noted a rebound in visitation following the initial outbreak, influenced by shifts in government policy, weather conditions, holiday periods, and personal characteristics.
摘要:
中央公园是纽约市的标志性建筑,这是美国第一个也是受冠状病毒影响最严重的城市之一。国家一级的居家秩序,提高COVID-19病例,以及公众对接触病毒的个人担忧,导致中央公园的游客大大减少。我们利用广泛的手机跟踪数据进行了一项开创性的实证研究,评估了COVID-19对城市公园的经济影响。我们将差异(DID)设计与娱乐需求模型集成在一起。DID设计有助于识别因果影响,控制可能混淆感兴趣的治疗效果的不可观察因素。同时,娱乐需求模型考察了造访变化的驱动因素,使我们能够估计纽约市居民经历的福利变化。我们的发现照亮了实质性的,但经常被忽视,大流行引发的福利损失。分析表明,大流行导致访问减少了94%,相当于每年4.5亿美元的消费者剩余损失。我们注意到,在最初的疫情爆发后,访问量出现了反弹,受政府政策变化的影响,天气条件,假日期间,和个人特征。