Version 1
: Received: 5 September 2023 / Approved: 6 September 2023 / Online: 7 September 2023 (03:27:25 CEST)
How to cite:
Chasco, C.; Vallone, A. Introduction to Cross-Section Spatial Econometric Models with Applications in R. Preprints2023, 2023090413. https://doi.org/10.20944/preprints202309.0413.v1
Chasco, C.; Vallone, A. Introduction to Cross-Section Spatial Econometric Models with Applications in R. Preprints 2023, 2023090413. https://doi.org/10.20944/preprints202309.0413.v1
Chasco, C.; Vallone, A. Introduction to Cross-Section Spatial Econometric Models with Applications in R. Preprints2023, 2023090413. https://doi.org/10.20944/preprints202309.0413.v1
APA Style
Chasco, C., & Vallone, A. (2023). Introduction to Cross-Section Spatial Econometric Models with Applications in R. Preprints. https://doi.org/10.20944/preprints202309.0413.v1
Chicago/Turabian Style
Chasco, C. and Andrés Vallone. 2023 "Introduction to Cross-Section Spatial Econometric Models with Applications in R" Preprints. https://doi.org/10.20944/preprints202309.0413.v1
Abstract
This paper introduces the spatial component in cross-section econometric estimations and specifically, the spatial dependence effect inherent in some of the variables involved in the modelling process. First, the spatial structure of the data from thematic maps is observed and Moran's spatial autocorrelation indicators are presented. Subsequently, the spatial weights matrix is built under different specifications. Finally, several modelling specification strategies are shown and the interpretation of the estimated coefficients. The theoretical concepts are illustrated with examples and their corresponding R software codes. This code and databases are available in a freely accessible repository in the BE2SHARE-EUDAT platform so that they can be easily reproduced.
Business, Economics and Management, Econometrics and Statistics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
