Welcome to the Broadly Shared Growth Initiative Web Map
About this data tool
Introducing our new online data tool: a powerful resource for assessing economic inclusivity. Beyond averages, it provides insights into how different demographic groups fare in local economies. Explore comparisons for your community across the first two decades of the 21st century, analyzing trends by age, gender, race, ethnicity, and education level.
Geography
This interactive tool uses Core-based Statistical Areas (CBSAs) as its unit of measure. CBSAs include a core urban area with a population of at least 10,000, along with nearby counties that have strong social and economic connections to the core, typically through commuting. Each CBSA in the dataset is identified by its largest city or county. Our tool focuses on CBSAs with a total population of at least 100,000 to ensure data reliability.
Time Period
The interactive tool's time frame spans from 2000 to a five-year average of data spanning from 2015 to 2019. This duration captures economic changes both preceding the Great Recession and during the recovery period leading up to the Covid-19 recession.
Measures
We measure a CBSA’s “success” by the change over time in its employment rate, real (inflation-adjusted) hourly wage, and real annual earnings, measured both for all residents and for specific demographic groups. Each measure (besides employment rate) has been adjusted for local price levels. We further adjust each measure by taking into account what an area's performance would be given its local demographics and the national performance of those demographic groups. These adjustments allow us to make comparisons on a more equitable basis. If local amenities stay roughly constant, these adjusted changes are likely to represent real gains (or losses) in well-being.
The percentage change indicates the performance of a CBSA compared to its baseline in 2000. Higher values signify that an area's performance, relative to its expected performance based on local demographics and national trends, has improved. Conversely, negative values indicate that the CBSA experienced a decline in relative performance.
Change in real annual earnings per person: Real annual earnings depend on both the employment rate and the real hourly wage, as well as hours worked per week and the number of weeks worked during the year. Change in real annual earnings is a summary indicator providing the best “average” bottom line for communities. The values have been adjusted for inflation and local prices.
Change in employment rates: The employment rate is measured as the number of people employed divided by the total population. For a person who might be on the margin between employment and nonemployment, the ability to readily find and keep a job is reflected in the employment rate.
Change in real hourly wage rates: Hourly wage rates are measured as usual weekly earnings divided by usual weekly hours worked. For someone employed full time throughout the year, the real hourly wage might best represent the strength of local labor market opportunities. Real hourly wage rates are adjusted for inflation and local prices.
Rankings
The rankings are based on each Core-based Statistical Area (CBSA) compared to all other CBSAs in our sample (383 CBSAs with total populations of at least 100,000 in the year 2000) across different performance measures and demographic groups. A rank of 1 signifies that the CBSA achieved the highest performance nationwide in that particular measure. It should be noted that the underlying statistics used to rank each CBSA subgroup's performance changes are subject to a margin of error. Thus, the rankings should be viewed as approximate.
Demographic Sub-Groups
Measures are available for all CBSA residents (aged 25-64) collectively as well as for select sub-groups. Sub-group data is available based on race/ethnicity, age, sex, and educational attainment.
Peer Geographies
For every CBSA in the dataset, we've identified five “peer geographies”: the most similar areas, based on their characteristics in the year 2000. Users can use these peer geographies to compare how their community performed in various measures against the most similar places in the United States.