Smart Device Recreation Data
研究了智能手机移动数据在评估2019年休斯顿储罐火灾后娱乐需求变化中的效用，发现数据覆盖率的测量误差会影响反事实预测，经济学家应谨慎使用此类数据推导绝对娱乐价值。
<h3>Abstract</h3> Human mobility data (MD) from smartphones may offer a scalable alternative to fieldwork for Natural Resource Damage Assessments (NRDAs) and non-market valuation. We test MD9s utility for estimating recreational demand changes after a 2019 Houston tank fire. We apply count regressions and zonal travel cost models to calculate welfare losses. While this MD dataset reflects expected temporal patterns, comparisons with reference data reveal that "coverage rates" vary significantly across sites. This measurement error complicates counterfactual predictions. Economists should use caution when deriving absolute recreational value from MD.