Research
Research
The Stability of Location Quotients
Mariya Pominova,Todd Gabe, and Andrew Crawley
Although location quotients are widely used to analyze local industry specialization and identify industry clusters in regions of all size, past studies have noted issues related to the accuracy of location quotients in small places. This paper examines the stability of location quotients in response to a marginal (i.e., one-unit) increase in the number of business establishments, with a focus on small regions. The analysis considers location quotients calculated for cities and towns in Maine, as well as all U.S. counties, and uses a range of industry classifications (e.g., 1-digit and 3-digit NAICS categories). Results show that the stability of location quotients increases with the population size of regions, but they do not uncover a single, universal population size cutoff for the reliable use of location quotients. Rather, the analysis shows that population size, the level of industry aggregation (e.g., 1-digit versus 3-digit NAICS) and even how the data are collected matter in determining the stability of location quotients.
Population size and the job matching of college graduates
Mariya Pominova and Todd Gabe
This paper examines the relationship between a region’s population size and the match of college-educated workers to jobs that require a degree. Results show a positive relationship between degree match and county population size in the United States, with a 100,000-person increase in population associated with a 1.3-percentage point increase in the likelihood of a match. The analysis uses a person’s grade point average in college to account for the potential sorting of higher-skilled workers into larger urban areas and the dataset has individuals across a wide range of regions from small rural areas to big cities.