In urban and regional studies, spatial autoregressive models are widely employed to capture spatial patterns and a dependence structure in data. While numerous variable selection techniques based on the likelihood principle with favorable theoretical properties have been proposed, the practical...

We reconnect the economic and geographical dimensions of labour market dynamics by examining whether settlement models affect local labour markets' performances in Italy. Results of spatial Durbin regressions outline a quadratic relationship between unemployment and market area, with lower rates...

This paper presents a method to improve existing spatial dependence-robust inference procedures for spatial data. Our method involves augmenting a regression specification with functions of locations that reduce spatial correlation in regression scores and serves as a pre-whitener, followed by...

Brazilian agriculture is characterized by the prevalence of small farms and regions with a high degree of rurality and dominance of the agricultural sector in the economy. These two characteristics affect the diversity of agricultural production in the country. Specifically, the article aims to...

Spatial unit roots can lead to spurious regression results. We present a brief overview of the methods developed in Müller and Watson (2024) to test for and correct for spatial unit roots. We also introduce a suite of Stata commands (-spur-) implementing these techniques. Our commands exactly...