Of course, the town’s small size means that the sample on which the data is based is very small (see data note below), but it’s surprising to discover that East Greenwich’s unemployment rate is actually pretty high. In March, it stood at 11.1%, which is only a little below the statewide number of 11.8% (numbers not seasonally adjusted).
Part of the reason, if the model is to be believed, is that 5.5% more East Greenwich residents are looking for work (measuring 2010 against 2000), but 2.4% fewer of them are actually finding it. That 7.9% change nearly tripled the town’s unemployment rate from 2000, when it stood at 3.9%.
As the following chart shows, population accounts for some of the labor force increase, but not all of it.
Unlike some of the other towns that the Current has examined, none of East Greenwich’s data points are record-breaking, across the twenty-two-year span of the Department of Labor and Training’s data. Both labor force and employment are near their historic averages. However, with the small population, the 756 people currently counted as unemployed is around 6% of all residents and is nearly double the 398 average.
In the following chart, unemployed residents equal the distance between the two lines.
Note on the Data
The population data above comes from the U.S. Census conducted every ten years and is therefore generally considered reliable, to the extent that is used as reference for various government programs and voter districting.
The labor force and unemployment data, however, derives from the New England City and Town Areas (NECTAS) segment of the Local Area Unemployment Statistics (LAUS) of the federal Bureau of Labor Statistics (BLS). A detailed summary of the methodology is not readily available, but in basic terms, it is a model based on and benchmarked to several public surveys. It can be assumed that the sample rate (i.e., the number of people actually surveyed) in each Rhode Island town is very small (averaging roughly 30 people per municipality).
The trends shown, it must be emphasized, are most appropriately seen as trends in the model that generally relate to what’s actually happening among the population but are not an immediate reflection of it. Taking action on the assumption that the exact number of employed or unemployed residents shown corresponds directly to real people in a town would vest much too much confidence in the model’s accuracy.
Be that as it may, the data has been collected and published, and taken a town at a time, it is relatively easy to digest. So, curiosity leads the Current to see it as the best available data to deepen our understanding of trends within Rhode Island. If the findings comport with readers’ sense of how the towns relate to each other, perhaps lessons regarding local and statewide policies may be drawn. If not, then the lesson will be on the limitations of data in our era of information overload.