Disaggregation and Nowcasting of Regional GDP Series with a Simple Smoothing Algorithm

We propose a simple smoothing method for the spatiotemporal disaggregation of economic time series. Contrary to the existing methods, our approach does not require exogenous regressors and can therefore be used for countries lacking long and reliable series of regional economic indicators. The proposed method can also be applied sequentially, implying that one needs to revise only the estimates for the last low-frequency period when new data are disaggregated. This is a convenient feature when historical estimates are of interest. We apply this method to disaggregate annual real GDP data for Polish regions into quarterly series and compare the results with the series obtained from a multivariate linear regression-based procedure, considering the differences between the estimates and the consequences for regional recession dating. We also examine the nowcasting performance of the smoothing algorithm and find that it is superior to the regression-based alternative for most of the studied sample lengths and horizons up to a year.