Little Compton’s population is so small that one must view its unemployment data fully aware that the actual survey sample for the town is likely extremely small, so estimates rely heavily on the model that the U.S. Bureau of Labor Statistics uses to understand New England.
Still, it was surprising to find in February that one of Rhode Island’s wealthiest towns has the relatively high unemployment rate of 12.7%, compared with the state’s overall 12.1% (numbers are not seasonally adjusted). Little Compton’s rate fell dramatically in March, to 10.6% (compared with the state’s 11.8%), but the reason was a big slip in total labor force, not increased employment.
The following chart illustrates that Little Compton has joined the rest of Rhode Island’s downswing. From 2000 to 2010, its population dropped by 2.8%, and the total number of employed residents fell 6.4%. Exacerbating Little Compton’s unemployment rate is the fact that the number of people actually looking for work increased, growing the town’s total labor force by 1.7%.
The following chart shows how the stagnant labor force and shrinking employment contributes to the town’s high unemployment rate, which is illustrated as 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.