Inasmuch as South County is typically considered among the wealthiest, most economically resilient areas in Rhode Island, it’s somewhat surprising that the town’s unemployment rate is 13.9%. (That’s not seasonally adjusted, and it is well above the state’s 11.8%.) Growth during the last two decades, followed by consistent job losses since the housing bust, helps to explain the data.
From the 2000 U.S. Census to the 2010 iteration, Charlestown lost 0.4% of its population, but its labor force (those working or looking for work) grew 4.5%. Employment kept pace until about 2008, when it began dropping, falling below its 2000 level 4.4%.
In the years since the Census, Charlestown’s number of employment residents has continued to fall. What decrease in the unemployment rate there has been is attributable mainly to the erosion of the overall labor force, as unemployed residents either leave or give up.
In the following chart, unemployment is represented as the distance between the two lines. As illustrated, the town’s labor force is still near its all-time high (for the twenty-two years of data provided by the RI Dept. of Labor and Training, but its employment has returned to the average.
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.