The Detailed Economic Window (DEW) was born from the District Data Labs Incubator Program. The goal of this project is to help those in the public and private sectors make efficient investment decisions. For this project, the team estimated economic activity and demand by analyzing historic data from the Bureau of Labor Statistics (BLS) and CENSUS data. At the same time, we created predictive algorithms identifying regions of the country with overwhelming demand for specific industries, skills or resources. The outcome of these efforts is an interactive national map showing these results.
The team is made up of Elaine Ayo, Danielle Llanos, Will Sankey and Jing You.
The BLS/DOLadvisors are Emily Liddel and Tyrone Grandison.
Elaine Ayo Elaine Ayo is finishing up her master’s in mathematics
and statistics at Georgetown, and works as a data analyst for a
policy research firm, primarily focusing on evaluation of nutrition
Danielle Llanos Danielle Llanos is an enterprise architect at the
World Bank who recently completed her master’s in mathematics
and statistics at Georgetown.
Will Sankey Will Sankey is a researcher at L&M Policy Research,
LLC with three years experience working on large project
evaluations for the Centers for Medicare and Medicaid Services
Jing You Jing You is a recent graduate of George Washington
University’s master’s in business analytics program. She has one-
year experience on data analysis and business intelligence, and she
is also a data analytics intern at Golfswell.
The Detailed Economic Window (DEW) was born
from the District Data Labs Incubator Program.
Goal: To help those in the public and private sector
leaders make efficient investment decisions.
How: By estimating economic activity and demand -
analyzing historic data from the Bureau of Labor
Statistics (BLS) and integrating it with data from
It is based on the Location Quotient (LQ)
A way of quantifying the concentration of a particular industry,
occupation, or demographic group in a region as compared to a
larger area (in this case, the nation) as a whole.
Location Quotient = (% of local employment in sector X) / (%
of regional employment in sector X)
A LQ greater than 1 signifies that an industry’s concentration in a
local region is larger than the national concentration.
A LQ less than or equal to 1 signifies than an industry’s
concentration in a local region is less than the national
concentration and may not have a great effect on the economic
landscape as a whole.
Meanwhile an LQ significantly greater than 1 is expected to
indicate an industry that has the potential to be classified as an