Introducing UnemploymentPulse

UnemploymentPulse tracks state and local rates of unemployment through time.

Modeled after CovidPulse‘s use of sparkline map symbols, and using the regularly-updated Living Atlas layer of unemployment (sourced from the Bureau of Labor and Statistics monthly numbers), UnemploymentPulse visualizes a moving 14-month window of unemployment data at the state and county level, and shows them alongside national rates for comparison.

Unemployment is ever-changing, and it can be beneficial to see the meandering ups and downs as it shifts through time in addition to the latest rates. These rates are given much more meaning when viewed in light of the recent past, with trends of neighboring areas, and compared to a national baseline. All of this context provides a fuller terrain for understanding.

Click state or county to learn all kinds of other information. Compare this month’s rate to last month’s, this month’s rate last year, and the 14-month high and low. See how this area ranks compared to other states or counties.

Options

There are two options for visualizing these trends. The first shows local rates of unemployment alongside national rates, for context. Orange sparklines show the state and county unemployment trend, and the light blue trend reference line behind shows the national rate’s trend for reference:

Overlapping sparklines compare local to national unemployment rates.

The second option shows when local rates went above or below the national rate. Holding the national rate constant, see how much a particular area’s rate diverged from the national rate:

Local unemployment rates normalized by the national rate.

Charted details

Select any state or county to open a dashboard-like summary:

Select an area for a local unemployment report.

How is the unemployment rate measured here? This rate is not based on the weekly claims data, rather the monthly unemployment rate from Bureau of Labor Statistics (BLS), generally released with about a six-week lag. Some definitions:

Unemployed: Those who have actively looked for work during the past four weeks, and are available to start work (includes new graduates and other recent entrants into the labor force, those with informal jobs, those on temporary layoff/furlough).

Labor Force: All people age 16 and older who are either employed or unemployed (either working or actively looking for work).

Unemployment rate = (those unemployed / those in labor force) * 100.

These numbers are not seasonally adjusted. The figures for the latest month are preliminary when first released and are later revised.

You’ll notice next to each county’s rate, text is used to put that number into context, such as “recession-level” or “healthy.” The ranges are based on a report from the Federal Reserve Bank on the balance between unemployment and inflation:

Less than 4 percent: indicative of an economic boom, which is likely to cause inflation

4 to 6 percent: healthy levels of employment, which is unlikely to cause inflation

6 percent or higher: recession-level unemployment, which is likely to cause deflation

“An inflation rate of zero, or price stability, appears to require an unemployment rate of about 5.5 percent.” (page 6 of Inflation and Unemployment: A Layperson’s Guide to the Phillips Curve)

Rankings

Any data-drive map is really a visualization of the question, “compared to what?” For any selected area, click the “ranks” statement to show a high level comparative listing of the 10 top and bottom states and counties by unemployment:

The top and bottom ten states and counties are listed.

UnemploymentPulse is a collaboration of architect Jinnan Zhang, demographer Diana Lavery, and cartographer John Nelson, and other members of the Esri Living Atlas team. Data automation was created by Lisa Berry. ArcGIS Living Atlas is a repository of curated geographic data from all sectors of the mapping community.

Find more BLS-related resources in Living Atlas here.

If you are interested in creating your own app with data-dense sparkline symbology, check out this resource.

Note: this blog was updated on August 4, 2022.

About the authors

Diana Lavery

(she/her/hers) Diana loves working with data. She has 15 years experience as a practitioner of demography, sociology, economics, policy analysis, and GIS. Diana holds a BA in quantitative economics and an MA in applied demography. She is a senior GIS engineer on ArcGIS Living Atlas of the World's Policy Maps team. Diana enjoys strong coffee and clean datasets, usually simultaneously.

John Nelson

I have far too much fun looking for ways to understand and present data visually, hopefully driving product strategy and engaging users. I work in the ArcGIS Living Atlas team at Esri, pushing and pulling data in all sorts of absurd ways and then sharing the process. I also design user experiences for maps and apps. When I'm not doing those things, I'm chasing around toddlers and wrangling chickens, and generally getting into other ad-hoc adventures. Life is good. You might also like these Styles for ArcGIS Pro: esriurl.com/nelsonstyles

Connect:

Jinnan Zhang

Jinnan is a Senior Product Engineer at Esri's the Living Atlas team, He is interested in developing apps using TypeScript, React and Redux (if necessary), ArcGIS API for JavaScript, D3 and Vanilla JS.

Connect: