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The distribution of patents across U.S. states

Tracking innovation for Californians, Massachusettsans, Idahoans, Mainers, etc. etc.

FRED Blog posts have discussed patent royalties, R&D, and the balance of payments and the changing geography of U.S. innovation. Today, we tap into a recently added data set from the U.S. Patent and Trademark Office to discuss the distribution of patented new ideas across U.S. states.

The GeoFRED map above shows the number of patents registered in each state during 2019, which is the latest available data point as of this writing. The total number of new patents for the whole country was 186,022, and the map illustrates their uneven geographical distribution. While California recorded 50,667 patents, Maine recorded 249. That might be expected simply because the population isn’t evenly distributed across the country: For each Mainer, there are 29 Californians. But it’s not all about population.

The second graph shows the number of patents divided by the number of persons (in thousands) residing in each state in 2019. At the top of the graph is Massachusetts, with 1.31 patents per 1,000 residents. California is a close second, despite the fact that there are almost 8 Californians for each Massachusettsan.

Let’s take another example: West Virginia and Idaho are the two most similar states in terms of population size, yet Idahoans record 6.4 times more patents than West Virginians.

Factors like the presence of large cities, institutions of higher education, particular industries, and research centers help explain the disparities in the numbers of patents per person.

How this map was created: From GeoFRED, click on “Build new map” (green button, northeast corner of the screen) and then click on “Tools” (orange cogwheel button, northwest corner). Under “Region” select “State,” under “Data” select “U.S. Granted Patents: Total Patents Originating,” and under “Date” select 2019. Note that you can also edit the colors, legend, and labels. To create a map for the population figures by state repeat the process, searching for “Resident Population.”

Suggested by Diego Mendez-Carbajo.

The jump in used car prices

Economic restrictions related to the COVID-19 pandemic are being loosened, and economic activity is beginning to pick up. That’s expected to generate temporary increases in consumer price inflation. Over the past few months, prices for energy commodities and services have increased. But the largest monthly change in the April 2021 CPI belonged to another sector: used cars and trucks.

The FRED graph above shows that year-over-year growth in used vehicle prices reached 21% in April 2021, up from an already elevated 9.4% in March 2021. This is especially remarkable given that the general increase in the price level as of April was 4.2%. Used vehicle prices haven’t increased this much since December 1981, when they measured 21% and general inflation was 8.9%. Prior to 2020, the last time used vehicle prices had a monthly increase of more than 10% was between September 2009 and 2010. So how did this come about?

Comparing Beige Books in 2020 and 2021

A look back at economic conditions a year ago can help shed some light. In the April 2020 Beige Book, compiled around the time the country initiated restrictions on economic activity, auto dealers reported “significantly lower used car prices and a greater tendency to sell new cars for less than their sticker price.” Rental car agencies, the largest seller of used vehicles, responded to the lack of demand for their services by offloading excess inventory of used vehicles, increasing the supply of used vehicles and putting downward pressure on their prices.

The April 2021 Beige Book, however, tells a very different story. With demand recovering, rental companies are building up their fleets again, leaving fewer options for other used vehicle buyers. Not only has consumer spending activity increased moderately, lack of new vehicle inventory has been a “major issue,” in part due to semiconductor shortages that have created supply chain issues for vehicle manufacturers. All this has pushed more consumers to consider purchasing used vehicles. In the past, a glut in the supply of new vehicles would be absorbed into the used vehicle market over time, keeping prices low with a steady supply of off-lease and trade-in vehicles.

Trends over time

This blog has discussed trends for vehicle sales in general, but let’s stick with used vehicle prices and add some historical context. Before the current recession, annual growth in used vehicle prices hadn’t hit 3% since May 2012 and remained largely flat during the period from 2013 to 2020. Indeed, this trend goes back well over two decades: As measured by the CPI, used vehicle prices were largely flat or falling going back to 1997.

So the current spike in prices feels more like a correction after a lengthy stretch of falling prices. A 21% annual rise in prices is extraordinary, but it came about due to a unique and unprecedented set of economic conditions now impacting the supply of vehicles. Looking at how and why it happened gives us a better understanding of where things stand.

How this graph was created: Search FRED for “CPI new cars” and click on the right series. From the “Edit Graph” panel, use the “Add Line” tab to search for and select “CPI used cars.” Select units “Percent change from year ago” and click on “Select for all.” Finally, restrict the sample to start in May 1996.

Suggested by Nathan Jefferson.

View on FRED, series used in this post: CUSR0000SETA01, CUSR0000SETA02

Savings are now more liquid and part of “M1 money”

Regulation D has made savings deposits as convenient as currency

Money is marvelously nuanced. Because different assets can be used as money, we need several categories and definitions to keep track of it. M1 describes the most liquid and widely accepted assets used to easily settle transactions: currency, demand deposits, and highly liquid accounts.

A previous FRED blog post discussed how recent changes in the opportunity cost of money and the regulation of savings accounts have affected measures of the money stock (a.k.a. monetary aggregates). In this post, we tighten our focus on how these regulations have affected M1.

Before April 24, 2020, savings accounts were not part of M1. Limitations in the number of transfers from savings deposits made savings accounts less liquid than M1. M1 consisted of currency, demand deposits, and other highly liquid accounts called “other checkable deposits” (OCDs). An example of OCDs are the demand deposits at thrifts.

But the limitation on the number of these transfers was lifted on April 24 as an amendment to Regulation D, which specifies how banks must classify deposit accounts. Savings deposits are now just as liquid and convenient as currency, demand deposits, and OCDs. To reflect this fact, savings deposits are now included in M1.

The FRED graph compares the new M1 with what would have been M1 under previous regulations, when it included only currency, demand deposits, and OCDs. From May 2020 on, M1 comprises currency, demand deposits, and a new item called “other liquid deposits.” These are the OCDs plus savings deposits. Previously, the OCDs consisted about 17% of M1. Now, the other liquid deposits consist about 70% of M1.

As of May 2020, the old M1 would have had a value of around $5 trillion. The new M1 has a value of $16 trillion, a substantial increase and a clear break in the time series.

For all you data scientists and researchers: It’s no longer possible to reconstruct the old measure of M1 because OCDs and savings deposits are not reported separately anymore. They’re now reported as a sum under “other liquid deposits.” But the graph here shows the separate series for OCDs and savings deposits that were still available from May 2020 to January 2021.

The graph also shows that M1 is now close to M2. Before May 2020, the difference between M2 and M1 was large because a great portion of M2 consisted of savings deposits. These savings deposits are now part of M1, so M1 is much larger and closer to M2. M2 is still larger than M1 because it includes less-liquid assets such as time deposits.

How this graph was created: To graph the previous measure of M1, search for and select the seasonally adjusted series for “Currency component of M1.” Add the two other components to this line from the “Edit Graph” panel’s “Edit Line 1” tab: In the “Customize data” field, search for seasonally adjusted series for demand deposits and other checkable deposits. In the formula field, type a+b+c and select “Apply.” To add the current series of M1 and M2, use the “Add Line” tab to search for and select each aggregate: “M1 Money Stock” and “M2 Money Stock.”

Suggested by Andre C. Silva and Christian Zimmermann.

View on FRED, series used in this post: CURRSL, DEMDEPSL, M1SL, M2SL, OCDSL


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