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Government revenue since the recent tax reform

The Tax Cuts and Jobs Act of 2017 applies to taxes starting in 2018, and the first quarterly data on tax revenue are in. This graph compares current tax revenue categories with categories for the previous year. Most noticeable are a major drop in corporate tax income and the increase in taxes from production and imports. (In the latter case, both excise tax income and import duty income increased.) These changes are actually quite impressive: -35% for corporate tax income, +16% for production and import tax income. Personal income taxes are slightly down while taxes on foreign entities follow trend. How does all this pan out in the aggregate? The thick black line reveals that overall tax receipts are down by close to 5%. Will this persist or is this a one-time event? Revisit this blog post in the coming months to see how this graph updates.

How this graph was created: From the Federal Government Current Receipts and Expenditures release table, check the relevant series and click on “Add to Graph.” From the “Edit Graph” menu, make the first series black and increase its width to 4.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: A074RC1Q027SBEA, B075RC1Q027SBEA, W006RC1Q027SBEA, W007RC1Q027SBEA, W008RC1Q027SBEA

A fertility map

Where in the world is the population replacing itself?

Populations can replace themselves by having children (fertility) and through immigration. Here, we focus on fertility. A general rule is that women must have an average of 2.1 children to maintain the population, with the extra 0.1 owing to the fact that some children will not reach the age of procreation.

This GeoFRED map of the world shows how each country stands with respect to replacing itself. The color white indicates the country is below its replacement rate, light blue indicates pretty much the minimum replacement rate, and the darkening greens move up the fertility scale from there.

It’s not news that many Western industrialized nations have low fertility, which they compensate for with immigration. Poorer countries, as expected, have higher fertility. But there are a few cases that aren’t so well known. For example, some South American countries have low fertility, as does Thailand. Iran is a low-fertility country in between two high-fertility countries, Iraq and Afghanistan. These latter two countries tend to have net emigration, which is not surprising given the waves of conflict there, and thus their populations don’t increase as fast as their fertility would otherwise indicate. And then there’s Eastern Europe: very low fertility and net emigration, leading to substantial population loss.

How this map was created: From GeoFRED, click on “Build New Map.” Under the “Tools” menu, enter “fertility” in the data search bar and select “fertility rate, total.” You can select your own color scheme (under “CHOOSE COLORS”) and your own range of values (under “EDIT LEGEND”).

Suggested by Christian Zimmermann.

Where is rail heading?

Tracking freight and passengers on U.S. railroads

What’s the story with trains? It turns out that U.S. railroad transportation has some nuances. The graph above shows that the amount of freight transported by train dropped during the Great Recession, as expected. But freight transport doesn’t appear to have gotten back on track since then. Passenger transport, however, rebounded in a big way after the Great Recession and has sustained levels well above those in the early-to-mid 2000s. What’s behind the disparity here? Passenger traffic in the U.S. is essentially driven by the Northeast corridor between Boston and Washington. This is where Amtrak introduced the Acela Express, a train that successfully competes with other modes of transportation. The gradual success of this train alone may explain the rise in passenger rail. Freight traffic appears to be less successful in matching its competition—mainly, trucking and waterway transportation. The graph below follows trucking and waterway, which seem to do better after the Great Recession than before.

How this graph was created: Search for “rail,” check the two series, and click on “Add to Graph.” From the “Edit Graph” menu, open the “Format” tab and place one of the series on the right axis. For the second graph, search for “tonnage,” check the two series, and click on “Add to Graph.”

Suggested by Christian Zimmermann.

View on FRED, series used in this post: RAILFRTCARLOADSD11, RAILPMD11, TRUCKD11, WATERBORNED11

Paying interest on excess reserves

An additional policy tool for the Fed

Commercial banks must adhere to regulations, including so-called reserve requirements. That is, banks must hold a certain fraction of their deposits as cash in a Federal Reserve account; these are known as “required reserves.” Banks can choose to hold even more cash in those accounts than what the Federal Reserve requires; these are known as “excess reserves.”

The graph above shows that required reserves are quite stable and grow as a constant fraction of total deposits in the banking system. But excess reserves increased considerably in 2008, as the Fed expanded the money supply to finance unconventional monetary policy measures such as quantitative easing. As of May 2018, excess reserves are nearly $1.9 trillion, ten times more than required reserves.

In normal times, excess reserves aren’t profitable, as they don’t earn a return. Instead of holding cash as excess reserves, banks could lend those funds and earn interest. However, after the 2008 recession, the Federal Reserve started paying interest on excess reserves (IOER). By altering the incentives for commercial banks to extend loans or hold excess reserves, the Fed is able to use the IOER as an additional monetary policy tool.

The second graph plots the IOER along with the (effective) federal funds rate, the Fed’s main tool for conventional monetary policy. The federal funds rate can be thought of as the interest rate at which financial institutions make short-term loans to each other. Here, we see that the federal funds rate tracks the IOER very closely. When banks have excess liquidity or reserves, they can choose whether to lend those reserves to other banks (at the federal funds rate) or deposit them at the Fed (and earn the IOER). Banks aren’t willing to lend to each other if the federal funds rate is substantially lower than the IOER, and so the two rates move closely together.

How these graphs were created: For the first graph, search for and select “required reserves of depository institutions” and click “Add to Graph.” From the “Edit Graph” panel, choose “Add Line,” search for and select the monthly “excess reserves of depository institutions” series, and click “Add data series.” The first series is in billions of dollars; to change it to match the second series (in millions of dollars), select “Edit Lines”/”Edit Line 1” and add the formula a*1000. For the second graph, search for and select the monthly “effective federal funds rate” series. From the “Edit Graph” panel, choose “Add Line” and search for and select “interest rate on excess reserves.” Use the date range tool to set the start date in August 2008.

Suggested by Asha Bharadwaj and Miguel Faria-e-Castro.

View on FRED, series used in this post: EXCSRESNW, FEDFUNDS, IOER, REQRESNS

Intermediate input dynamics

Buying goods to make more goods

When a firm manufactures a good, the production uses not only labor and physical capital, but also intermediate goods and materials produced “upstream” in the production network. For example, when an automaker produces a car, it needs to purchase steel, glass, electronic devices, and more from other companies. The graph above shows the ratio of the costs of intermediate goods to total revenue (or gross output) for all U.S. industries. We see that the whole economy relies heavily on the production network, as the revenue share of intermediate inputs is above 40% on average. Also, the material share isn’t constant and actually fluctuates over time. During the Great Recession (2007-09), for example, the share drops from 46% to 41%, which implies that firms slowed down their purchasing of goods from each other. And, by 2011, they were buying and selling at about the same level as before the recession.

The second graph shows the material share specifically for manufacturing, which is an industry that uses more intermediate goods for production: Its average material share is 65%—much higher than the 43% for the entire economy. Its material share dropped as well in the recession, but in 2011-14 it overshot its pre-recession level, probably because firms were compensating for the amount of shipments they would have ordered (but did not) during 2008-09.

The final graph shows the FIRE sector (finance, insurance, and real estate). The FIRE sector typically uses less material (focusing on office equipment and delivery of services), but the material share is still above 30%. Interestingly, the level of material usage for the FIRE industry fell in 2008, but it has not yet recovered to its pre-recession level.

We’ve seen a solid rebound, an overshoot, and a shortfall in the material share soon after the recession. Overall, the numbers in 2015-17 suggest that a full recovery hasn’t yet occurred for the U.S. production network.

How these graphs were created: From the FRED homepage, select the option to “Browse Data by Release” below the main search bar. Choose “Gross Domestic Product by Industry” as the release. This release contains both intermediate inputs and gross output for all industries. Select the intermediate inputs by industry table and view the first table, in billions of dollars, seasonally adjusted at annual rates. Click on “Private Industries” to view the intermediate input cost of all private industries. To express as a share of gross output, use the “Edit Graph” menu to customize the graph: Add “Gross Output of All Industries” in the search box on the “Edit Line 1” tab. Type a/b in the formula box and click “Apply.” Repeat this process for each subindustry as desired.

Suggested by Sungki Hong.

View on FRED, series used in this post: GOAI, GOFIRL, GOMA, IIAI, IIFIRL, IIMA

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