A Spatio-Temporal Panel Data Model for Coronavirus Deaths: Evidence from Europe

Asep Rusyana, Anwar Fitrianto, Marzuki Marzuki

Abstract


The spatial panel data model is a model in which the independent variables are estimated to be influenced by place, time, and explanatory variables. Almost all countries have been attacked by the coronavirus, starting in China in February 2020. Some of the affected residents died, some recovered, and some are still under surveillance. This study aims to identify the most accurate model with the response variable of population deaths due to coronavirus and the independent variables of the number of cases with coronavirus and the number of tests. This study uniquely compares multiple spatial models for pandemic analysis. The four models are SAR, SEM, GSM, and Temporal Spatial Panel Data. The fourth model enables more accurate analysis of COVID-19 mortality by capturing both spatial and temporal dependencies. As a result, the spatial temporal panel data model is the best model with a coefficient of determination of 63.9%.

Keywords


Coronavirus; General Spatial Model; Lagrange Multiplier; Spatial Autoregressive; Spatial Error Model; Spatial Weight Matrix; Temporal Spatial Panel Data.

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DOI: http://dx.doi.org/10.30829/zero.v9i2.25933

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