arXiv 15 Feb 2024 · Econometrics · 1 citations (OpenAlex)
arXiv:2402.09895 · PDF · DOI · OpenAlex · Extracted main text
This handbook chapter provides an essential introduction to the field of spatial econometrics, offering a comprehensive overview of techniques and methodologies for analysing spatial data in the social sciences. Spatial econometrics addresses the unique challenges posed by spatially dependent observations, where spatial relationships among data points can be of substantive interest or can significantly impact statistical analyses. The chapter begins by exploring the fundamental concepts of spatial dependence and spatial autocorrelation, and highlighting their implications for traditional econometric models. It then introduces a range of spatial econometric models, particularly spatial lag, spatial error, spatial lag of X, and spatial Durbin models, illustrating how these models accommodate spatial relationships and yield accurate and insightful results about the underlying spatial processes. The chapter provides an intuitive guide on how to interpret those different models. A practical example on London house prices demonstrates the application of spatial econometrics, emphasising its relevance in uncovering hidden spatial patterns, addressing endogeneity, and providing robust estimates in the presence of spatial dependence.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Rüttenauer (2022) `Spatial Regression Models: A Systematic Comparison of Different Model Specifications Using Monte Carlo Experiments', Sociologic… | 1.000 | 9 | 4 | 100% |
| 2 | LeSage \ Pace (2009) Introduction to Spatial Econometrics, Statistics, Textbooks and Monographs, CRC Press, Boca Raton | 1.000 | 8 | 4 | 100% |
| 3 | Cook, Hays \ Franzese (2020) Model Specification and Spatial Interdependence, in L. Curini \ R. Franzese, eds, `The Sage Handbook of Research Methods in Poli… | 1.000 | 8 | 3 | 100% |
| 4 | LeSage (2014) `What Regional Scientists Need to Know about Spatial Econometrics', The Review of Regional Studies 44(1), 13–32 | 1.000 | 7 | 4 | 100% |
| 5 | Pebesma \ Bivand (2023) Spatial Data Science: With Applications in R, first edn, Chapman and Hall/CRC, Boca Raton | 1.000 | 5 | 4 | 100% |
| 6 | Halleck Vega \ Elhorst (2015) `The SLX Model', Journal of Regional Science 55(3), 339–363 | 0.928 | 4 | 4 | 100% |
| 7 | Kelejian \ Piras (2017) Spatial Econometrics, Elsevier | 0.843 | 3 | 3 | 100% |
| 8 | Bivand \ Piras (2015) `Comparing Implementations of Estimation Methods for Spatial Econometrics', Journal of Statistical Software 63(18), 1–36 | 0.737 | 3 | 2 | 100% |
| 9 | Anselin (2003) `Spatial Externalities, Spatial Multipliers, and Spatial Econometrics', International Regional Science Review 26(2), 153–166 | 0.644 | 4 | 1 | 100% |
| 10 | Bivand, Millo \ Piras (2021) `A Review of Software for Spatial Econometrics in R', Mathematics 9(11), 1276 | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 61 scored citations.