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The state of the minimum wage

Comparing U.S. state minimum wages in 2010 and 2021

The federal minimum wage has remained constant at $7.25 per hour since July 2009. The real value of this wage has declined over the past decade, and many people discuss if, when, and how this federal minimum should increase.

Not all U.S. workers earning minimum wage, however, have had a stagnant pay rate since 2009. Many U.S. states have increased their minimum wage rates to account for inflation and other changes in cost of living.

These GeoFRED maps display state minimum wage rates in 2010 and 2021. In 2010, 15 states (including Washington, D.C.) had minimum wage rates that exceeded the federal minimum. In 2021, 30 states do.

The 2010 map shows that a few states (AR, CO, GA, MN, WY) had minimum wage rates below the federal level. The 2021 map shows that all states now have minimum wage rates at or above the federal level. Technically, GA and WY still have state minimums of $5.15. But these sub-federal minimum wage rates apply only in select circumstances; in most cases, the higher federal minimum wage supersedes these state minimums. States shaded gray and labeled “No Data Available” don’t have their own state minimum wage laws and thus adhere to the federal minimum wage.

From 2010 to 2021, 32 states increased their minimum wages by varying degrees, with an average of +$3.42. Washington, D.C., increased its wage by the greatest amount (from $8.25 to $15.00, up $6.75), and Florida increased its wage by the lowest amount (from $7.25 to $8.65, up $1.40).

In 2010, Washington state had the highest minimum wage at $8.55; in 2021, Washington, D.C., with its $15 minimum wage, now tops the list. A few states, such as OR and CT, are slated to implement wage increases later in 2021.

How these maps were created: From GeoFRED, click the green “Build new map” button in the top right corner. From there, click the orange “Tools” button in the top left corner. Under the “Choose Data” menu, set “Region Type” as “State.” Click the dropdown arrow in the “Data” field and type into the search bar “State Minimum Wage Rate” and select the data series. Set the “Date” to the desired year. To make legend values comparable across years, click the “Edit Legend” tab and input desired legend values.

Suggested by YiLi Chien and Julie Bennett.

Service with a masked smile: How weaker demand reduced employment in 2020

The FRED Blog has discussed how the COVID-19 recession reduced the demand for services and boosted the demand for goods, whereas in previous recessions it was the inverse. Today we examine the same dynamic from a different angle: how these changes in consumption patterns have affected industry-specific employment.

The FRED graph above shows the large initial declines in employment for goods-producing industries (e.g., construction and manufacturing) and service-providing industries (e.g., leisure and hospitality). We changed the units of the data into an index, with a base period set at the start of the latest recession, to make it easier to measure and compare changes over time. (This post from October 2020 also uses an index to track unemployment by age during recessions.)

After the initial double-digit declines, employment in goods-producing and service-providing industries gradually bounced back. At the time of this writing they were 5.6% and 7% below pre-recession levels, respectively. For reference, we also plot employment data in the service-providing government sector. This includes federal, state, and local governments, which had similar but smaller declines.

For comparison, the second FRED graph shows changes in employment during the Great Recession, from December 2007 to June 2009. At that time, the largest losses in employment were registered in the goods-producing industry—specifically, in construction. Employment in service-providing industries declined more gradually and by a smaller amount. And employment in the government sector remained effectively unchanged.

In that recession, of course, there was no pandemic and no widespread use of masks and social-distancing measures. To learn more about how recent changes in work and consumption habits might impact future economic activity, read the Economic Synopses essay by Julian Kozlowski.

How these graphs were created: From FRED’s main page, browse data by “Release.” Search for ”Employment Situation” and select “Current Employment Statistics (Establishment Data) > Table B-1. Employees on nonfarm payrolls by industry sector and selected industry detail, Seasonally adjusted.” Select the series “Government,” “Goods-Producing,” and “Private Service-Providing.” From the “Edit Graph” panel, select the “Edit Lines” tab. In the “Units” drop-down menu, select “Index (Scale value to 100 for chosen date)” and choose “2020-02-01” for the first graph and “2007-12-01” for the second graph. Adjust the date range to mirror the dates shown in the blog post.

Suggested by Diego Mendez-Carbajo.

View on FRED, series used in this post: CES0800000001, USGOOD, USGOVT

A friendly warning: Data aren’t perfect

Graphing data can reveal issues that spreadsheets may not

“The greatest value of a picture is when it forces us to notice what we never expected to see.” – John Tukey

FRED gives you the option of downloading data into a spreadsheet. Of course, it’s also common to present the data in graph form, which is much easier on the eyes. But plotting your data is exceptionally important for other reasons.

A graph can give the numbers a clear and convincing voice. And it can also reveal the unexpected. Because your eyes can quickly catch something that simply looks wrong, you may observe the existence of data issues on a graph that would not be immediately apparent when looking only at the numbers.

The FRED graph above plots three vintages of the Economic Policy Uncertainty Index from January 5 (blue), 6 (red), and 7 (green) of 2021. The plots are indistinguishable until December 9, 2020, where the January 6 vintage jumps to a series maximum of over 1,000 before dropping to a constant value of 10.92. Notice that there are also some minor differences between values in the January 5 and January 7 vintages. While it’s normal for data vintages (even those that are a day apart) to differ slightly, the large discrepancies in the January 6 vintage clearly stem from data issues…

As it turns out, this vintage contains incorrect values. And that only became clear because we plotted the data. Had we not done that, the issue would have remained undetected and may have caused further errors during our application of the data.

Search the FRED Blog for more posts about the Economic Policy Uncertainty Index.

How this graph was created: Browse FRED data by category. Under the category “Academic Data,” select “Economic Policy Uncertainty” and then the not seasonally adjusted version of the series “Economic Policy Uncertainty Index for United States.” From the “Edit Graph” panel, select the vintage for 2021-01-05. From the “Edit Bars” tab, click “Edit Bar 2” and select the vintage for 2021-01-06. Using the “Add Line” tab, create another line with the same series and edit bar 3 to be the vintage 2021-01-07. Change the graph type and colors to taste using the “Format” tab. Last, change the range by using the scroller directly below the graph or choose specific dates by typing them into the white boxes just above the graph.

Suggested by Aaron Amburgey and Michael McCracken.

View on FRED, series used in this post: USEPUINDXD


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