Federal Reserve Economic Data

The fiscal conditions of US states vary quite a bit. Do they vary more by geography or over time? Let’s find out.

The first FRED graph above shows the total state tax revenue divided by the state population for five large states. (We don’t want 50 states on a single graph.) We divide by population because larger states obviously have more revenue and we must normalize that revenue per resident. In this view, taxes vary quite a bit across states. But what about over time?

To answer this question, we need to make sure we deal with inflation. Tax revenue may simply have increased because everything became more expensive. In our second graph, we take the first graph and divide it all by the consumer price index. In this view, we see tax revenue per capita tends to increase over time—with the exception of Florida, where it’s relatively stable.

But are these the right measurements? Indeed, incomes have increased as well, even after taking inflation into account. So our last graph divides tax revenue (per capita) by personal income (per capita). In this view, we see that revenue increases slightly in some states and decreases slightly in others. Nothing too dramatic.

A little more meaning behind the numbers: State taxes amount to 1-2% of personal income. Keep in mind that these are just state taxes. There’s also an array of taxes at local levels (county, town, school district, fire district, etc.) that may shift the “ranking” of states.

How these graphs were created: Search FRED for “state tax collections” and select any state. Below the resulting graph, look for the release table. In that table, select the states you want displayed and click on the “Add to graph” button. Now that you have a multi-series graph, use thew “Edit Graph” panel: Use “Edit Line 1” to add the series for the resident population of that state and apply formula a/b. Repeat for each line/state. You have the first graph. For the second graph, repeat by adding the CPI to each line and applying formula a/b/b. For the third graph, beyond the state tax collections, add state per capita personal income and apply formula a/b*1000.

Suggested by Christian Zimmermann.

New businesses play an important role in fostering job creation, innovation, and economic growth. A common measure of business dynamism relates to the number of new firms or establishments entering the market.

In this FRED blog post, we identify the states with the largest and smallest growth rates in the number of business applications across all industries relative to 2005: We adjust the data* by the state’s resident population, set an index value of 100 in the year 2005, and graph the top 5 and bottom 5 states as of 2022.

So, where is business booming in the US? The FRED graph above shows the five states with the largest growth rates in the number of business applications between 2005 and 2022. Wyoming, Delaware, Mississippi, Georgia, and Louisiana lead the nation for growth in new business applications adjusted by their populations. For instance, in 2022, the number of new businesses in Wyoming was seven times greater than it was in 2005. In Delaware, the number was three times greater.

The second graph shows the bottom five states: Nevada, New Hampshire, Maine, Minnesota, and Massachusetts had the lowest growth rates in the number of new businesses relative to 2005. In 2022, the number of new businesses in Nevada was almost the same as it was in 2005, while in New Hampshire it was only 21% greater than it was in 2005.

All states experienced some increase in the number of new businesses between 2005 and 2022. But why is business formation so strong in the first group of states? These states have low (or no) corporate and personal state income taxes as well as privacy laws regarding the ownership of businesses. Taxation and business laws play an important role when deciding where to incorporate a new firm.

But could this be the result of unusual data in 2005? To answer that question, we also assess whether 2005 was an outlier by computing the growth rate in new businesses relative to 2006 and 2007. Although the growth rates are smaller at the top, Wyoming, Delaware, and Mississippi are still the leading states in business formation. The number of new businesses grew fivefold in Wyoming and doubled in Delaware between 2006 or 2007 and 2022. In contrast, Nevada and New Hampshire remain the least dynamic states with similar growth rates in new businesses for 2005, 2006, and 2007.

*FRED has data on business applications for an employer identification number (EIN) from the Census Bureau’s business formation statistics, available at the state level starting in July 2004 for all industries as well as for specific industries. FRED also has population data at the state level.

How this graph was created: In FRED, search for and select “Business Applications: Total for All NAICS in Louisiana.” From the “Edit Graph” panel, click the “Edit Line” tab: Modify the frequency to annual, and in the “Customize data” field search for and add “Resident Population in Louisiana.” In the “Formula” tab, type in a/b. Change the units to “Index” with a custom scale of “2005-01-01.” Have the date range as “2021-07-04” to “2022-07-04.” Finally, go to the “Format” tab and change the graph type to “Bar.” Repeat these steps for Wyoming, Delaware, Mississippi, and Georgia to create the first graph. Repeat these steps for Nevada, New Hampshire, Maine, Minnesota, and Massachusetts to create the second graph.

Suggested by Ricardo Marto and Hoang Le.

The FRED Blog has discussed why residents of richer countries live longer lives, on average, than residents of poorer countries. In short, higher income levels allow access to higher-quality healthcare and overall better living conditions. Today, we highlight a positive trend on this topic: The average life expectancy in poor countries is rising and gradually catching up to the average life expectancy in rich countries.

The FRED graph above shows data from the World Bank about the average number of years a person born in each year is expected to live. Each line represents a set of countries grouped by level of income: high income in red, medium income in green, and low income in blue.

The graph shows that, in 1960, the resident of a poor country was expected to live an average of 41 years. By 2021, their life expectancy had increased to 62 years. That’s still short of the 80-year average a resident of a rich country born in 2021 is expected to live, but proportionally closer than the gap recorded more than half a century ago. And the reason for that is declining infant mortality in poor countries.

B. Ravikumar and Amy Smaldone at the St. Louis Fed argue that larger numbers of newborns surviving to at least age 1 raise the average count of years individuals are expected to live. In other words, lower infant mortality rates in poor countries are driving their higher life expectancy rates. These researchers prove their point by presenting a counterfactual argument: If their argument were wrong, the life expectancy data shown in the above FRED graph would look very different.

For more about this and other research, visit the website of the Research Division of the Federal Reserve Bank of St. Louis, which offers an array of economic analysis and expertise provided by our staff.

How this graph was created: Search FRED for “Life Expectancy at Birth, Total for Low Income Countries.” Next, click the “Edit Graph” button and select the “Add Line” tab to search for and add “Life Expectancy at Birth, Total for High Income Countries.” Repeat the last step to add “Life Expectancy at Birth, Total for Middle Income Countries.”

Suggested by Diego Mendez-Carbajo.