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Consultants present data findings for St. Mary's County SEDS; commissioners press for inclusion of federal employment and workforce training

St. Mary's County Economic Development Commission · October 15, 2014
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Summary

University of Maryland consultants summarized employment, income, cluster and real‑estate data for St. Mary's County, highlighting the county's high share of federal employment, concentration in defense-related clusters, wage distribution extremes, and next steps to reconcile datasets and schedule small-group commissioner briefings.

University of Maryland consultants presented highlights of a data-driven strategy process that will inform St. Mary's County—s Strategic Economic Development Strategy (SEDS) at the Oct. 15, 2014 meeting of the St. Mary—s County Economic Development Commission.

Dr. Scott Dempelt framed the work as an effort to help commissioners understand data sources and limitations. He reviewed multiple datasets (BEA, EMSI, LAUS, QCEW), explained differences between place-of-work and place-of-residence measures, and warned analysts and policy-makers not to overread single indicators. Using QCW/QCEW place-of-work data, the consultant showed the county has one of the highest percentages of federal employment in Maryland and emphasized that federal and contractor payrolls materially affect average wage and employment patterns.

Key findings and discussion points included:

- Federal dependence and cluster structure: St. Mary's County shows high concentration in defense and security, energy, business services and information/telecommunications clusters. The consultant said the county sits at the periphery of larger Maryland–D.C. clusters but can still exploit regional linkages.

- Employment and wages: Different data sources produced different totals; LAUS-based resident employment rose at roughly 1% annually from 2009–2014. QCEW-based figures showed an employment composition near 67% private, 21% federal and 11.7% state/local; Dempelt noted federal employees average near $100,000 annually while other workers average near $50,000, producing a polarized income distribution.

- Occupation and industry detail requests: Commissioners asked for a private-sector breakdown that isolates defense-related private employment and for verification of the top-employer list (questions were raised about inclusion of the county school system and local government). The consultant agreed to verify and update figures.

- Data coverage and reconciliation: Commissioners raised concerns that some hotspot and cluster analyses omit federal employees and base contractors when using standard private-sector datasets. Dempelt committed to re-running hotspot and cluster analyses to include military and federal employment where possible, to reconcile commuting datasets, and to follow up with updated slides.

- Engagement and next steps: Dempelt proposed individual or small-group meetings with commissioners to walk through the data between mid-November and the second week of December and said he would provide slide decks and a Dropbox link in advance. He also said next months— materials will include innovation-network analysis, patents and regional supply-chain mapping.

The meeting closed with administrative items, a reminder about an Open Meetings Act summary included in packets, and a motion to adjourn.