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DEW - The Detailed Economic Window

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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.

Published in: Technology
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DEW - The Detailed Economic Window

  1. 1. It ain’t about the rain It’s the economy.
  2. 2.   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 assistance programs.  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 (CMS).  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. Team
  3. 3.   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 CENSUS Reporter. Background
  4. 4.  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 exporter. Economics 101
  5. 5.  Work-In-Progress http://dew.herokuapp.com
  6. 6. The Future Leveraging CitySDK to build exciting new apps like DEW.

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