Causal Inference with Spatial Data: ArcGIS 10 for Economics Research This course introduces economists to ArcGIS 10 and Python programming to handle spatial datasets for causal inference in economics research. The course content is updated on 27 July 2018. NOTE: Press SPACE key to go through slides. Lecture 1: Introduction Lecture 2: Spatial Join Lecture 3: Buffer Lecture 4: Distance as instruments Lecture 5: Zonal Statistics Lecture 6: Elevation Lecture 7: Spatial Regression Discontinuity Design Lecture 8: Map Algebra For students in Osaka University, Oct-Dec 2018 Syllabus (Schedule, Reading List, and Grading Policy) For students in Oslo University, Aug 2018 Syllabus (Schedule, Reading List, and Grading Policy) Overview: A summary of the above 8 lectures These lecture notes were created with reveal.js, a neat HTML5-based presentation slide tool. Useful web links for using ArcGIS General
Dealing with ArcGIS python scripting quirks
Calculation on raster datasets
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