Neighborhood Business Trends: Jobs, Wages, and Commuting Patterns

1. MCIC examples of use of LEHD data

2. Monitoring Area: a Neighborhood The LEHD block group data can be aggregated to a small, customized area(in gold)

3. Business in a Neighborhood Trend in # of businesses Businesses per 10 acres commercial / industrial

4. Jobs per Acre of Commercial, Industrial Property in a Neighborhood LOCAL JOBS: Concentration of jobs per acre of commercial/industrial property (per land use files)

5. 35,000 5,000 4,500 30,000 4,000 25,000 3,500 3,000 20,000 2,500 Park Blvd, Legends 15,000 2,000 Westhaven, W End 1,500 10,000 Roosevelt Sq 1,000 Oakwood, Lake Pk, Jazz 5,000 500 North Town Pk 0 0 2002 2003 2004 Trend in Number of Jobs in a Neighborhood LOCAL JOBS: Trend in # of jobs (the decrease in top line turns out to be due to key employers not reporting that year)

6. Wages of Workers Who Live in a Neighborhood RESIDENT WORKERS: Wages estimated from grouped data

7. Wages of Jobs Located in a Neighborhood LOCAL JOBS: Wages estimated from grouped data

8. Employment Profile of Residents of a Neighborhood RESIDENT WORKERS: Wages, Industry breakouts, wage/industry location indexes

9. Characteristics of Jobs Located in a Neighborhood LOCAL JOBS: Wages, Industry breakouts, wage/industry location indexes

10. Workers/Tract Where People Work Who Live in a Target Neighborhood Where RESIDENT WORKERS go to work . . . E.g. of use of origin/ destination commutershed data Commuting Area:where people who live in the neighborhood travel to work

11. Where People Live Who Work in a Target Neighborhood Where people come from who work in LOCAL JOBS. . . E.g. of other way to use origin/ destination commutershed data

12. Neighborhood Role: Bedroom Community vs. Work Zone Compares the two origin/destination tables: # LOCAL JOBSvs. # RESIDENT WORKERS