North Smithfield is in the small group of Rhode Island cities and towns that experienced upward trends in population (12.7% growth), labor force (17.2%), and employment (8.5%), from 2000 to 2010. However, because its labor force grew so much more quickly than its number of employed residents (and because the latter has dipped more rapidly over the past two years), the town still has a not-seasonally-adjusted unemployment rate of 10.1%. Of course, that compares favorably with the state’s 11.8%.
The following chart illustrates that North Smithfield’s unemployment (represented as the space between the lines) results largely from its labor force’s continued upward drift. The number of employed residents has generally been stagnant since before the housing bust and financial crisis, although increasing numbers of people continued to look for work.
All three metrics are near their all-time highs for the twenty two years of data provided by the RI Dept. of Labor and Training.
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.