Course Introduction: Overview, Format, and Objectives
Laying a Foundation for Economic Modeling
Methods for Researching the Competitive Strengths of a Region
Workforce and Growth: Using Data to Tell Your Region's Labor Market Story
Mapping Industry Clusters, Analyzing Interdependencies, and Identifying Targets
Tools for Evaluating and Communicating Economic and Fiscal Impacts

Exercise: Use Location Quotient to Understand Regional Specialization

The Tableau data visualization below is shared courtesy of the Miami Valley (Ohio) Regional Planning Commission. It displays 2016 LQs for the entire Metropolitan Statistical Area (MSA) and for the six individual counties that comprise the MSA. It also allows you to use the U.S. or the state of Ohio as the comparative reference.

The data viz is structured to occupy four quadrants. The quadrants represent areas of relative strength or weakness as shown below:

Have fun exploring the map and drilling down into the data it displays. Then, use the data visualization selectors to locate answers to the questions below. (You’ll see these questions again in the multiple-choice knowledge check that follows this interactive module!)

  1. According to the data shown here, which industry in the six-county MSA has the highest Location Quotient, as compared to the entire U.S.?
  2. Which industry in Preble County has the highest Location Quotient, as compared to the U.S.?
  3. Which industry in the six-county MSA has the lowest LQ, as compared to the rest of the state of Ohio?