Recommended readings¶
Anselin, L. (1988). Spatial Econometrics: Methods and Models. Studies in Operational Regional Science. Springer Netherlands, Dordrecht.
Anselin, L. & A. Getis (1992). Spatial statistical analysis and geographic information systems. Ann. Reg. Sci. 26, 19–33.
Anselin, L. & D. Arribas-Bel (2013). Spatial fixed effects and spatial dependence in a single cross-section. Pap. Reg. Sci. 92, 3–17.
Anselin, L. & S.J. Rey (2014). Modern Spatial Econometrics in Practice: A Guide to GeoDa, GeoDaSpace and PySAL. GeoDa Press LLC.
Brunsdon, C., A.S. Fotheringham & M. Charlton (1996). Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity. Geogr. Anal. 28, 281–298.
Comber, A., C. Brunsdon et al. (2020). The GWR route map: a guide to the informed application of Geographically Weighted Regression. ArXiv.
Fanning, A.L., D.W. O’Neill, J. Hickel, & N. Roux. (2022). The social shortfall and ecological overshoot of nations. Nat. Sustain. 5, 26–36.
Fotheringham, A.S., C. Brunsdon, M. Charlton (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley.
Fotheringham, A.S., W. Yang & W. Kang (2017). Multiscale Geographically Weighted Regression (MGWR). Ann. Am. Assoc. Geogr. 107, 1247–1265.
O’Neill, D.W., A.L. Fanning, W.F. Lamb, & J.K. Steinberger (2018). A good life for all within planetary boundaries. Nat. Sustain. 1, 88–95.
Raworth, K. (2017). Doughnut Economics: Seven Ways to Think Like a 21st-Century Economist. Chelsea Green Publishing, White River Junction, Vermont.
Rey, S.J. (2019). PySAL: the first 10 years. Spat. Econ. Anal. 14, 273–282.
Rey, S.J., W. Kang, L.J. Wolf (2019). Regional inequality dynamics, stochastic dominance, and spatial dependence. Pap. Reg. Sci. 98, 861–881.
Rey, S.J., D. Arribas-Bel & L.J. Wolf. (forthcoming). Geographical Data Science with Python. CRC Press.