Policymakers and stakeholders face important data gaps due to the inherent lag between economic activity and the publication of official statistics. To assess economic activity closer to real-time, the Western Development Commission (WDC) has compiled a set of timely economic indicators in an attempt to bridge this gap. The WDC acknowledges that this indicator set is limited given the lack of detailed and frequently published official economic data at the county level. To address this limitation the WDC aims to supplement the regular indicators report with a series of ad-hoc reports based on less conventional data sources. The WDC has now compiled the first such supplement to the initial Timely Economic Indicators report and examines Google Mobility data for the Western Region and Atlantic Economic Corridor (AEC).
Google Mobility is a publicly available dataset compiled by Google to provide insight into how peoples’ movements have changed throughout the pandemic. The dataset provides Google related data on visitor numbers (or duration for the residential category) to various categories of location each day. Within Google Maps if you find a restaurant you will normally see a chart that shows you how busy that establishment is for a typical day and time, this is the type of data that Google mobility is based on. The mobility categories cover retail and recreation (places such as restaurants, cafés, shopping centres, theme parks, museums, libraries and cinemas), grocery and pharmacy (places such as supermarkets, food warehouses, farmer’s markets, specialty foodshops & pharmacies), parks (places like national parks, public beaches, marinas, dog parks, plazas & public gardens), public transport (places that are public transport hubs, such as underground, bus and train stations), workplaces (places of work) and residential (places of residence).
Google measures visitor numbers (or duration in the case of the residential category) and compares this change relative to a baseline before the pandemic outbreak. It is important to note that a return to the pre-pandemic baseline does mean a return to “normal.” For example, suppose retail and recreation mobility was equal to the baseline in December, this would likely be a lower level than normal for December as we might expect December to be a much busier month than the baseline (January/February). As we do not know what “normal” mobility is during any period for any region/county, comparing across regions/counties or comparing the Western Region/AEC to Ireland may be misleading. For example, historical summer retail and recreation mobility in Clifden is likely to have been much higher due to seasonal tourism than the winter months and this disparity between winter and summer is likely to be much larger than say in Dublin City. Looking only at baseline deviations will not accurately capture the comparative changes in normal mobility levels.