摘要翻译：
我提出了一个框架，估计器，和推理程序，以分析因果影响的设置与空间处理。许多事件和政策（治疗），如开业、医院建设和污染源，发生在特定的空间位置，研究人员感兴趣的是它们对附近个人或企业的影响（结果单位）。然而，现有的治疗效果文献主要考虑可以直接在结果单元级别分配的治疗，潜在的溢出效应。我从一个类似的实验角度来研究空间治疗环境：我们会设计什么样的理想实验来估计空间治疗的因果效应？这一观点激发了在已实现治疗地点附近的个体和未实现候选地点附近的个体之间的比较，这与当前的经验实践不同。此外，我展示了如何找到这样的候选位置，并应用所提出的方法与观测数据。我应用所提出的方法来研究新冠肺炎封锁期间杂货店对附近企业步行交通的因果影响。
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英文标题：
《Causal Inference for Spatial Treatments》
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作者：
Michael Pollmann
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最新提交年份：
2020
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分类信息：

一级分类：Economics 经济学
二级分类：Econometrics 计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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一级分类：Statistics 统计学
二级分类：Methodology 方法论
分类描述：Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计，调查，模型选择，多重检验，多元方法，信号和图像处理，时间序列，平滑，空间统计，生存分析，非参数和半参数方法
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英文摘要：
I propose a framework, estimators, and inference procedures for the analysis of causal effects in a setting with spatial treatments. Many events and policies (treatments), such as opening of businesses, building of hospitals, and sources of pollution, occur at specific spatial locations, with researchers interested in their effects on nearby individuals or businesses (outcome units). However, the existing treatment effects literature primarily considers treatments that could be assigned directly at the level of the outcome units, potentially with spillover effects. I approach the spatial treatment setting from a similar experimental perspective: What ideal experiment would we design to estimate the causal effects of spatial treatments? This perspective motivates a comparison between individuals near realized treatment locations and individuals near unrealized candidate locations, which is distinct from current empirical practice. Furthermore, I show how to find such candidate locations and apply the proposed methods with observational data. I apply the proposed methods to study the causal effects of grocery stores on foot traffic to nearby businesses during COVID-19 lockdowns.
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