Employment Centers 2.0

What is an Employment Center?

Employment Centers are areas in the region with high densities of employment. SANDAG identified the industries located in these areas, where employees commute from and what their commute looks like along with other attributes.

Background

The San Diego region is a growing and dynamic place to live and work. As the community, policymakers, and other stakeholders collaborate regarding how we create transportation options for our residents that are competitive and environmentally responsible, it is essential we utilize the data we have regarding where people live and work to invest in strategies that will best serve our communities. As we continue to work together to create a region that maintains and improves our quality of life now and in the future, SANDAG is committed to bringing the most up-to-date information to the public by applying data science and analytics capabilities to facilitate a better understanding of where employment centers are in the region, where the employees in these areas commute from, and what their commute patterns look like.

Results

Ninety-one separate employment centers were identified and divided into 4 different tiers based on the number of jobs within their boundaries. 
Note: The exact job count within each employment center will vary depending upon the source and vintage of data, if the values are counts of employees or jobs, as well as the types of employees (full-time/part-time) or jobs (wage and salary only on non-wage and salary included).
Explore each employment center in the map and table below. Hover in the map for details.

Explore Further

Take a more detailed look at economic, demographic, and transportation data of different geographies in the pages below.

Interactive Employment Centers

Take a closer look at individual Employment Centers with this interactive dashboard.

Interactive Jurisdictions

Take a look at individual municipal jurisdictions with this interactive dashboard.

Interactive Tiers

Take a closer look at the tiers as a whole with this interactive dashboard.

Work Destinations by Residence

Take a closer look at work destination for the residents of each jurisdiction.   

SANDAG InfoBits

Highlights of Employment Centers 2.0 with key takeaways.  
First page of the linked document



Methodology

SANDAG used a collaborative empirical approach to identifying employment centers across the San Diego region. The 2019 vintage of point-level business locations with counts of employees from the California Economic Development Department (CA-EDD) were summarized by ¼ mile radius hexagons (hexbins). Local-maxima were identified as starting points, and regions were grown to include neighboring hexagons meeting a minimum employment density threshold within an approximate 2-mile radius. The resulting boundaries were normalized based on the existence and location of major barrier features such as topography and the road network. These normalized boundaries were then used to select the SANDAG Master Geographic Reference Areas (MGRAs) that would come to define each employment center. These MGRAs were selected based on their activity-weighted (population and employment) centroids being within each boundary.
Through this process, over 70 initial areas were identified, all of which are areas of relatively high levels of employee and job densities compared to their neighboring areas. However, the result of this approach did not adequately address military bases and tribal gaming centers, both of which are significant sources of economic activity in the region. Therefore, the above process was modified slightly to better recognize the clusters of job counts typically found in these types of areas, placing more emphasis on counts within a single hexbin rather than thresholds within the neighboring hexbins. This approach resulted in the inclusion of several military bases and gaming centers not originally included. These centers provide the geographies used to evaluate travel patterns, employment information, and resident information. Additional technical information regarding this methodology is available by contacting the Data Science Department at SANDAG at data@sandag.org

Data Sources

Longitudinal Employer-Household Dynamics (LEHD) Origin-Destination Employment Statistics (LODES) (2002-2020)  
The Longitudinal Employer-Household Dynamics (LEHD) Origin-Destination Employment Statics (LODES) data are a publicly available product of the U.S. Census Bureau. The LODES data are an extract of the LEHD infrastructure which is composed of administrative records, census, and survey data. The LODES data provide counts of wage and salary jobs covered by unemployment insurance, including private sector and state, local and federal government jobs. Workplace location and residential location of an employee are measured at the census block-level (2020). The 2019 data used are from version 8.0 of the LEHD-LODES Data are specifically pulled from two primary tables: Original-Destinations (OD) (used to determine where people live who have jobs in the various employment centers), and Workplace Area Characteristics (WAC) (used to determine the demographic characteristics of the people with jobs in the employment centers). It should be noted that these data (1) contain only wage and salary jobs (and exclude self-employed individuals); (2) do not include military and other security-related federal agencies, postal workers, some employees at nonprofits and religious institutions, and informal workers; and (3) only include an individual’s primary job if an individual has more than one. These analyses reflect preliminary results and are pending final verification.  Additional information is available at https://lehd.ces.census.gov/data/
SANDAG Job Estimates (2022)
On a regular basis, SANDAG produces estimates of employment in the San Diego region. The employment estimates are the count of jobs in civilian private and public sectors and include uniformed military. Both wage and salary and non-wage and salary (often referenced as the gig or contract work and self-employed) positions are counted. These estimates utilize California Employment Development Department (EDD) data, the Quarterly Census of Employment and Wages (QCEW) data, the Bureau of Economic Analysis (BEA), and the LEHD LODES data from the U.S. Census Bureau. Additional information regarding these estimates is available by contacting the Data Science Department at SANDAG at data@sandag.org
SANDAG Population and Housing Estimates (2022)
Each year SANDAG produces estimates of population and housing for the San Diego region. These estimates utilize several data sources including the California Department of Finance, the U.S. Census Bureau, and a variety of other publicly available datasets. These small-area estimates contain information on the characteristics of the population (ethnicity, age, sex) and housing units (occupied, vacant, unoccupiable) in the region. The population living in military barracks, college dorms and other institutional facilities are included in the population and are counted in housing referred to as Group Quarters. The active military population and their dependents who live in households are included in the household population counts. The population and housing estimates are created in a process similar to the Regional Growth Forecast and contain similar information; however, the Population and Housing estimates reflect current conditions. Additional information regarding these estimates is available by contacting the Data Science Department at SANDAG at data@sandag.org
SANDAG Activity Based Transportation Model (2023)
In order to plan and complete regional transportation projects, SANDAG creates and maintains a transportation model which uses a variety of regional transportation survey data, socioeconomic data, and demographic data (e.g., count of trips from home to work, how people carpool, what bus routes are most frequented, and which highways are used and when). These data are then utilized in the Activity Based Model (ABM) to simulate individual and household transportation choices. These choices include how individuals travel around the region (the mode), why people travel around the region (the trip purpose), and when they travel (time of day). The ABM model is refined based on transportation data and expert feedback on methodology and data sources. For this analysis, SANDAG utilized release version 14.3.0 of the ABM to estimate travel for the year 2023 (reference scenario #289). Data are restricted only to transportation trips in the model in which (1) the trip begins at home and ends at work and does not have any intermediary stops (e.g., dropping a child at school); and (2) the trip’s purpose is work. Transit travel time includes initial wait time, walk time to transit stop, transfer time between stops, in vehicle time, and walk time to the destination. Data based on peak period is defined as occurring on weekdays between 6:00 am to 8:59 am and 3:30 pm to 6:59 pm. It should be noted that estimated auto trip path and VMT data from the model used to create vehicle usage maps include vehicle travel across all trip purposes that either start or end in the study area. Additional information about the ABM is available here: https://github.com/SANDAG/ABM/wiki

Footnote and Limitations

Please note that components of the underlying data are collected by other agencies. As such, SANDAG does not perform data validation procedures on these components.  Although SANDAG makes efforts to identify and address potential issues, users, and analysts should exercise their professional judgment when relying on the data product. This data product is an updated version of the previous SANDAG Employment Centers 1.0, which was released in May 2019. Justifiable inconsistencies may be observed when comparing Employment Centers 1.0 with Employment Centers 2.0 due to the expected changes in data sources, geographical boundaries, demographics and economic attributes, and newly introduced Employment Centers. For any questions, please reach out to data@sandag.org.