Darryl Mcleod

Fordham Department of Economics

ECON 5740 GIS Mapping in Stata and R

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General GIS Data Resources

  1. MIT geospatial library
  2. Harvard geospatial library
  3. Tufts GIS Tutorials
  4. GIS Training Manual for Historians and Historical Social Scientists
  5. Environmental Systems Research Institute (ESRI) ArcGIS tutorials
  6. Introduction to GIS Mapping and ESRI’s ArcGIS Software
  7. Finding GIS Data and Preparing it for Use Finding GIS Data and Preparing it for Use
  8. Raster: The ‘Other’ GIS Data Raster: The ‘Other’ GIS Data
  9. A Gentle Introduction to GIS
  10. GIS Programming and Automation (Open Access Online Class, PennState )
  11. Python Scripting for ArcGIS

GIS for Economists

  1. Melissa Dell, GIS Analysis for Applied Economists
  2. Kudamatsu’s Course: ArcGIS 10 for Economics Research
  3. Night Lights and ArcGIS: A Brief Guide
  4. CIESIN Thematic Guide to Night-time Light Remote Sensing and its Applications

Open Source GIS Software

There are many open source GIS applications. Here is a list of some of the best known opensource GIS packages.  For an extensive but somewhat dated list of 50+ see opensourcegis.org.

  1. ESRI ArcGIS:
  2. GeoDa:
  3. GRASS (Geographic Resources Analysis Support System)
  4. gvSIG (Generalitat Valenciana, Sistema d’Informació Geogràfica)
  5. Idrisi 16 QGIS – Formerly Quantum GIS
  6. Others: ERDAS Imagine; JUMP; KOSMO; MapWindow GIS; PCI Geomatica; ILWI; SAGA (System for Automated GeoScientific Analysis); uDig and Whitebox GAT.

Dealing with GIS Data in Stata

  1. Spatial Data Analysis in Stata
  2. Stata in space: Econometric analysis of spatially explicit raster data

Dealing with GIS Data in R

  1. For a list R spatial packages see the Analysis of Spatial Data library
  2. Common R packages for GIS are:
    1. sp (the basis of spatial functionality in R)
    2. rgdal (for loading spatial file formats such as shapefiles)
    3. rgeos (for spatial analysis)
  3. Basic GIS in R tutorials
  4. Advanced GIS in R tutorials
  5. Introduction to visualizing spatial data in R
  6. Analyzing spatial point patterns in R
  7. Spatial Regression Analysis in R: A Workbook
  8. GIS with R, or without ArcGIS! (NYU)

Books and Series

  1. Geospatial Analysis – A comprehensive guide (Free, online)
  2. Concepts and Techniques in Modern Geography (CATMOG)

DHS: Geospatial Demographic and Health Survey

  1. DHS Reports on Geospatial analysis data use:
    1. Creating Spatial Interpolation Surfaces with DHS Data
    2. Spatial Interpolation with Demographic and Health Survey Data: Key Considerations
    3. Linking DHS Household and SPA Facility Surveys: Data Considerations and Geospatial Methods
    4. Guidelines on the Use of DHS GPS Data (with displacement)
  2. Other DHS analytical reports using spatial data:
    1. Geographic Variation in Key Indicators of Maternal and Child Health Across 27 Countries in Sub-Saharan Africa
    2. The Relationship between the Health Service Environment and Service Utilization: Linking Population Data to Health Facilities Data in Haiti and Malawi
    3. Improving Estimates of Insecticide-Treated Mosquito Net Coverage from Household Surveys: Using Geographic Coordinates to Account for Endemicity and Seasonality
  3. Other Useful DHS Websites
    1. DHS Spatial Data Repository 
    2. The DHS Program Indicator Data API

Economics Papers in this Field

  1. Chen, X and W D Nordhaus (2011) “Using luminosity data as a proxy for economic statistics”, Proceedings of the National Academy of Sciences.
  2. Elvidge, C D, K E Baugh, E A Kihn, H W Kroehl and E R Davis (1997) “Mapping city lights with night-time data from the DMSP operational linescan system”, Photogrammetric Engineering & Remote Sensing, 63(6): 727-734.
  3. Feenstra, R C, R Inklaar and M P Timmer (2015) “The next generation of the Penn World Table”, American Economic Review, 105(10): 3150-3182.
  4. Henderson, J. V., A. Storeygard and D. Weil (2012) “Measuring Growth from Outer Space”,
    American Economic Review, 102(2), pp.994-1028.
  5. Pinkovskiy, M. (2013) “Economic Discontinuities at Borders: Evidence from Satellite Data on
    Lights at Night”, Working Paper.
  6. Pinkovskiy, M L and X Sala-i-Martin (2016a) “Lights, camera, … income! Illuminating the national accounts-household surveys debate”, Quarterly Journal of Economics, 131(2): 579-631.
  7. Pinkovskiy, M L and X Sala-i-Martin (2016b) “Newer need not be better: Evaluating the Penn World Tables and the World Development Indicators using night-time lights”, NBER, Working Paper no 22216.
  8. Pinkovskiy, M L and X Sala-i-Martin (2016) Shedding light on PPP-adjusted GDP measures
  9. Harttgen, K., Klasen, S., & Vollmer, S. (2013). An African growth miracle? Or: what do asset indices tell us about trends in economic performance?.Review of income and Wealth, 59(S1), S37-S61.
  10. Young, Alwyn. “The African Growth Miracle.” Journal of Political Economy 120.4 (2012): 696-739.
  11. Andy Schmitz, 2012, Geographic Information System Basics, v. 1.0 Creative Commons (homepage)
  12.  Gibson, J., & McKenzie, D. (2007). Using global positioning systems in household surveys for better economics and better policy. The World Bank Research Observer, 22(2), 217-241.
  13.  Travelling the Distance: A GPS-Based Study of the Access to Birth Registration Services in Latin America and the Caribbean

Blog Posts

  1. Satellite images can map poverty. John Bohannon, Aug. 18, 2016 , Science Magazine.
  2. Shedding light on PPP-adjusted GDP measures. Maxim Pinkovskiy, Xavier Sala-i-Martin, 26 June 2016. Voxeu.

 

Filed Under: GIS