Recursive Estimation of the Spatial Error Model

In this paper, we propose a recursive approach to estimate the spatial error model. We compare the suggested methodology with standard estimation procedures and we report a set of Monte Carlo experiments which show that the recursive approach substantially reduces the computational effort affecting the precision of the estimators within reasonable limits. The proposed technique can prove helpful when applied to real-time streams of geographical data that are becoming increasingly available in the big data era. Finally, we illustrate this methodology using a set of earthquake data.

Automated summary

In this paper, a recursive approach is proposed for estimating the spatial error model. The suggested methodology is compared with standard estimation procedures, and a series of Monte Carlo experiments demonstrate that the recursive approach significantly reduces computational effort while maintaining reasonable precision of the estimators. This technique proves valuable for analyzing real-time geographical data streams, especially in the era of big data. Finally, the methodology is illustrated using earthquake data.