Evaluating forecasting accuracy of the temporally aggregated space-time autoregressive model

This article aims at analysing the effect of temporal aggregation in space-time autoregressive models. By means of a simulation experiment, it is shown that, the greater the spatial dependence in time series, the lower the bias due to temporal aggregation. However, the ratio between the average mean squared forecasting errors for daily data and that for yearly data seems to decrease for high parameter values.