At 8.5%, not seasonally adjusted, Narragansett’s March unemployment number was third best in the state, but from 2000 to 2010, Narragansett’s number of employed residents fell eighth fastest in the state and has continued falling. These two seemingly contrary rankings are possible because the town also lost a high percentage of population and labor force.
Between the two most recent U.S. Census counts, Narragansett’s population fell 3.0%. Its labor force fell 1.3% (while most cities’ and towns’ grew). And its number of employed residents fell 6.7%.
The following chart shows that the town’s labor force and employment have continued to evaporate. It also shows that the number of employed residents as receded to the point at which it stood in the early ’90s.
Making Narragansett unique, in Rhode Island, is the fact that its labor force has historically tracked closely with actual employment. That has resulted in regularly low unemployment (the gap between the two lines).
Two possible explanations are that Narragansett’s population is especially mobile and able to pack up and leave when jobs disappear, or that multiple-income families find it easy to remove members from the labor force when jobs are scarce.
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.