Dataset accompanying the publication "Introduction to cross-section spatial econometric models with applications in R". 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 this repository.

Exploratory Spatial Data Analysis (ESDA) and spatial econometrics.

How to cite the database (APA style): Chasco, C., & Vallone, A. (2023). Introduction to cross-section spatial econometric models with applications in R [Data and Codes]. https://b2share.eudat.eu. https://doi.org/10.23728/B2SHARE.4066171FAA9B48329DAF3C03DE04305E. Source: 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