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Recursive Estimation of the Spatial Error Model |
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| Authors: | Chiara Ghiringhelli Gianfranco Piras Giuseppe Arbia Antonietta Mira |
| Institution: | 1. Department of Statistical Science, Università Cattolica del Sacro Cuore, Roma, Italy;2. Department of Economic Studies, Università G. d’Annunzio, viale Pindaro, Chieti-Pescara, Italy
Department of Economics, School of Arts and Sciences, The Catholic University of America, Washington, DC, USA;3. Department of Statistical Science, Università Cattolica del Sacro Cuore, Roma, Italy Università della Svizzera italiana, Lugano, Switzerland;4. Data Science Lab, Università della Svizzera italiana, Lugano, Switzerland Department of Science and High Technology, University of Insubria, Varese, Italy |
| Abstract: | 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. |
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