D1 Growth Story - Cluster Diversity by County

Overview

This analysis attempts to measure the economic diversity of clusters by county in the D1 region by applying the Herfindahl–Hirschman Index (HHI) approach to time-series data. This is just one of several method for measuring economic diversity. Others could be explored. In short, a higher score = lower diversity.

Data

This analysis is run with two separate data sets:

1. All jobs in the region, as obtained from the Quarterly Census of Employment and Wages public API, by 3 digit NAICS code.

   1. by County in D1
   2. Counties summarized to FDOT Districts

2. All cluster jobs by County in the D1 region by cluster, as obtained from the Clustermapping.us API.

Results

HHI Based on All Jobs (BLS QWI via Census API) by County by 3-digit NAICS Code

Smooth with LOWESS (Locally Weighted Scatterplot Smoothing) and Compare

HHI Based on All Jobs (BLS QWI via Census API) by FDOT District by 3-digit NAICS Code

Smooth with LOWESS (Locally Weighted Scatterplot Smoothing) and Compare

HHI Based on Cluster Jobs (via Clustermapping API)

Next steps

• All clusters (completed)
• Lock to 2018 clusters
• Share of traded clusters versus local clusters
• All jobs (traded plus local clusters OR BLS QWI annual) (completed)

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1. Renaissance Planning, jlehman@citiesthatwork.com↩︎