天气的误测:在经济背景下使用遥感地球观测数据

Anna Josephson, Jeffrey D. Michler, Talip Kilic, Siobhan Murray
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引用次数: 0

摘要

从遥感地球观测(EO)数据中获取天气数据降低了将天气变量纳入计量经济学模型的成本。天气变量是用于预测经济结果的常见工具变量,也是雨水灌溉农业作物产量建模的输入变量。在计量经济学应用中使用环 境观测数据时,最近才对这些数据在经济学中的适用性和质量进行了严格评估。我们以小农农业生产率为背景,量化了 EO 数据测量误差影响的意义和程度。我们发现,来自不同环 境观测数据源的不同测量方法:研究结果并不因选择的环境观测数据集而稳健,结果也不是简单的仿射变换。这就要求研究人员在使用这些数据时要谨慎,并建议稳健性检查应包括测试替代的环 境观测数据源。
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The Mismeasure of Weather: Using Remotely Sensed Earth Observation Data in Economic Context
The availability of weather data from remotely sensed Earth observation (EO) data has reduced the cost of including weather variables in econometric models. Weather variables are common instrumental variables used to predict economic outcomes and serve as an input into modelling crop yields for rainfed agriculture. The use of EO data in econometric applications has only recently been met with a critical assessment of the suitability and quality of this data in economics. We quantify the significance and magnitude of the effect of measurement error in EO data in the context of smallholder agricultural productivity. We find that different measurement methods from different EO sources: findings are not robust to the choice of EO dataset and outcomes are not simply affine transformations of one another. This begs caution on the part of researchers using these data and suggests that robustness checks should include testing alternative sources of EO data.
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