January | 2020 | FRED Blog

Working 9 to 5: Women make up more of the workforce

A look at women in the workforce by sector

Posted on January 16, 2020

“Tumble out of bed and I stumble to the kitchen. Pour myself a cup of ambition…” —Dolly Parton

The song and the movie 9 to 5 were released in 1980, back when women made up only 41% of employed workers in the U.S.

The Bureau of Labor Statistics has continued to collect the data and recently announced that women have broken through the 50/50 threshold in the U.S. workforce: That is, more women are employed than men. As the FRED graph above shows, this is the second time in U.S. history this threshold has been crossed. (Note that the December 2019 number is 50.0% in this graph, but a more exact value is 50.04%.)

FRED has more-specific data to help illuminate this event. To begin with, there have been more employed women than employed men in the private service-providing industry since 1985; and this share has grown over time. In the goods-producing industry, the percentage of women peaked at the end of 1991, at 27.8%.

The trends within the service-providing industry show a shifting landscape:

The ratio of women employees to all employees has recently increased in professional & business services and in leisure & hospitality.
It has remained effectively constant in education & health services and in trade, transportation & utilities.
And it has decreased in financial activities and information over the past 20 years or so.

Thus, it looks like the employment share of women has increased or at least persisted in sectors where women have achieved a strong presence. But it doesn’t seem like women are increasing their share in every given sector. Economists call this the composition effect. In this case, one single figure—or ratio—doesn’t tell the whole story: For example, Dolly Parton’s movie character, when heading to her job in professional & business services, is still entering a workplace where less than half of her coworkers are women.

How these graphs were created: All the data series are part of Table B-5. Employment of women on nonfarm payrolls by industry sector, Seasonally adjusted. For the first graph: Select “Total nonfarm,” click “Add to Graph,” open the “Format” tab, select “Add Line” and “Create user-defined line,” then enter 50 as the “value start/end.” The two other graphs are similar, but select “Goods producing” and “Private service-producing” and then the six different industries within the private service-providing sector. Adjust line colors and shapes in the “Format” tab so that the trends across individual industries are easier to see.

Suggested by Diego Mendez-Carbajo.

View on FRED, series used in this post: CES0000000039, CES0600000039, CES0800000039, CES4000000039, CES5000000039, CES5500000039, CES6000000039, CES6500000039, CES7000000039

What fuels air pollution?

A look at CO2 emissions by fuel type

Posted on January 13, 2020

The U.S. Energy Information Administration collects data on CO₂ emissions, and FRED has recently added these data to its catalog. The graph above stacks the amount of CO₂ emitted from the three main energy sources: coal, natural gas, and petroleum. Given the recent shift in energy sources, it shouldn’t be surprising the coal-related share of emissions has declined as the natural gas-related share of emissions has grown. Now let’s look at the picture across different economic sectors.

Our second graph shows the sources of CO₂ emissions from coal. Clearly, electric power generation creates the bulk of emissions. Industrial uses—the creation of steel, for example—contribute some emissions as well. The other sectors are negligible, with transportation registering a zero for all periods. (Coal-powered steam locomotives had been decommissioned by the start of the sample period.) Our next graph shows the same distribution for natural gas, with all sectors contributing to emissions. The shares seem pretty steady, except for the recent increases in the electric power sector.

The last graph shows emissions from petroleum use. Here, transportation creates the lion’s share and any changes in overall emissions can be traced back to that sector. So, if you give a hoot about reducing emissions from coal or natural gas, the power-generating sector seems key; for petroleum, transportation is key.

How these graphs were created: First graph: Search for “total carbon dioxide emissions,” restrict results in the side bar to “nation,” select the three series, and click “Add to Graph.” From the “Edit Graph” panel, open the “Format” tab and select graph type “Area” and stacking “Normal.” The three other graphs are built similarly by searching for “carbon dioxide emissions” and the respective fuel type. Adjust line colors in the “Format” tab so that each sector has the same color across graphs.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: EMISSCO2TOTVCCCOA, EMISSCO2TOTVCCNGA, EMISSCO2TOTVCCPEA, EMISSCO2TOTVECCOA, EMISSCO2TOTVECNGA, EMISSCO2TOTVECPEA, EMISSCO2TOTVICCOA, EMISSCO2TOTVICNGA, EMISSCO2TOTVICPEA, EMISSCO2TOTVRCCOA, EMISSCO2TOTVRCNGA, EMISSCO2TOTVRCPEA, EMISSCO2TOTVTCCOA, EMISSCO2TOTVTCNGA, EMISSCO2TOTVTCPEA, EMISSCO2TOTVTTCOUSA, EMISSCO2TOTVTTNGUSA, EMISSCO2TOTVTTPEUSA

Native Americans in the U.S.

A look at county-level Native American population data

Posted on January 9, 2020

FRED has added a great deal of county-level data recently, including population estimates, which include various race and ethnicity categories. These new data are especially well-suited for viewing on a map. So, of course, we look to GeoFRED: The map above shows non-Hispanic Native Americans. Note that the color scheme relates to the total number of Native Americans in each county, not in proportion to the county’s overall population.

Clearly, large numbers of Native Americans live in the West, especially the Southwest, and in Oklahoma—for obvious historical reasons that involve displacement of Native peoples. There are also quite a few counties where hardly any Native Americans live: For example, there are none in the Kansas counties of Comanche and Cheyenne. On the other side of the range, the Arizona counties of Navajo and Apache are in the top five most-populated. Unfortunately, we have no data for Oglala Lakota County in South Dakota.

How this map was created: The original post referenced an interactive map from our now discontinued GeoFRED site. The revised post provides a replacement map from FRED’s new mapping tool. To create FRED maps, go to the data series page in question and look for the green “VIEW MAP” button at the top right of the graph. See this post for instructions to edit a FRED map. Only series with a green map button can be mapped.