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The pandemic made calculating national income even more difficult

Archival FRED tracks the data revision process

There are three ways to measure GDP:

  • The expenditure approach adds private and public consumption, investment, and the trade balance. It’s the famous Y=C+I+G+X-M.
  • The income approach principally counts labor income and profits.
  • The product approach adds up each step of production.

All three measurements should add up to the same number. But, for various reasons detailed in this blog post, there’s always a small difference, called a “statistical discrepancy.” The ALFRED graph above shows this discrepancy as the proportional difference between GDP and national income. For the period just before and during the recent pandemic, that discrepancy went as high as 3%, for the first quarter of 2022.

Compare that graph with our second graph, which covers a more “normal” period. Here, the largest discrepancy is only 1.3%.

ALFRED’s job is to track “vintages” of data: In these graphs, the vintages are the values assigned to quarterly GDP. Those values for each given quarter were revised over time as more (and/or more-precise) information was collected.

During the “normal” period shown in the second graph, these revisions are minor compared with the revisions during the pandemic, shown in the first graph. This comparison highlights how difficult it was to compute the initial estimates of GDP and national income during the pandemic. Later vintages of the quarterly data had more typical discrepancies. This observation tells us that the BEA was able to adapt to the challenges of the pandemic quite rapidly and maintain the high level of accuracy in their data collection process.

How these graphs were created: Go to ALFRED, search for (nominal) GDP, click “Edit Graph,” search for (nominal) “national income,” and apply formula a/b-1. Finally, play with vintage dates and sample periods to obtain the two graphs.

Suggested by Christian Zimmermann.

International and US consumer prices for sugar

The FRED Blog has discussed how changes in global commodity prices for coffee, tea, and cocoa have impacted the price of comfort drinks in the European Union. Today, we compare global and US consumer prices for sugar and discuss why they’re disconnected.

The FRED graph above shows three data series on sugar prices:

  • The blue line is the domestic consumer price index for sugar and sweets. This is an index number, reported by the US Bureau of Labor Statistics, that measures the trend in the prices paid by US consumers.
  • The red line is the world benchmark price for raw cane sugar ready to be shipped for export. The International Monetary Fund (IMF) uses data on sugar No. 11 futures contracts from Intercontinental Exchange (ICE) to report this price in US cents per pound. At the time of this writing, Brazil is the world’s largest exporter of raw cane sugar.
  • The green line is the price of raw cane sugar for delivery at one of five designated US ports with refinery facilities. The IMF uses data on sugar No. 16 futures contracts from ICE to report this price in US cents per pound.

We customized the data to an index with a value of 100 in the first quarter of 1990, when the first IMF commodity price data are available, to better compare the changes in global commodity prices to the change in the US consumer price index. We can’t sugarcoat it: These indexes don’t tend to move in sync.

Between 1990 and 2009, the price of raw cane sugar delivered to US refineries was remarkably stable. During that period, consumer prices rose steadily while international prices bounced up and down. During the next several years, the US and the global prices for raw sugar moved in sync; but their spike in 2011 was not fully reflected in the domestic CPI in the US. Between 2020 and the time of this writing, the co-movement between rising raw sugar prices and rising consumer prices for sugar and sweets is more noticeable.

So, what’s the story behind the numbers?

This brochure about the ICE’s sugar futures contracts provides an overview of the international sugar market and the factors that hinder the free trade in this commodity. In short, the disconnect between international and domestic prices stems from subsidies to growers, import restrictions, and other regulations by producers and consumers organized in trade blocs.

Most recently, the US Department of Agriculture’s October 2023 “Sugar and Sweeteners Outlook” by Vidalina Abadam and David Marquardt describes how the exceptional drought conditions in the southern US are reducing the projected domestic sugar supply in 2023-2024. Trade partners are also experiencing droughts, and thus international commodity prices and domestic consumer prices are rising faster than in previous years.

How the graph was created: Search FRED for and select “Consumer Price Index for All Urban Consumers: Sugar and Sweets in U.S. City Average.” Next, click on the “Edit Graph” button and use the “Add Line” tab to search for and add “Global price of Sugar, No. 11, World.” Repeat the previous step to add “Global price of Sugar, No. 16, US.”

Suggested by Diego Mendez-Carbajo.

Federal Reserve remittances to the US Treasury

The Federal Reserve is subject to a dual mandate of price stability and maximum sustainable employment. In the course of achieving these goals, the Fed generates income and incurs costs:

  • Income is earned from interest earned on securities acquired through its open market operations and from regulatory and supervisory fees.
  • Costs are incurred from paying interest on reserve balances, interest on securities sold under agreements to repurchase (reverse repos), and operational costs such as payroll.

The Fed’s income typically exceeds the cost of its operations. By law, the Fed’s excess earnings must be turned over to the US Treasury as remittances. The FRED graph above shows the weekly excess earnings that are turned over to the US Treasury. From 2012 until 2021, the Federal Reserve remitted over $800 billion to the US Treasury. However, what happens when the Fed’s costs are greater than its income?

When the Fed’s costs exceed its income, the Fed creates a “deferred asset,” which is a negative liability whose value equals the cumulative shortfall in earnings. Once the Fed returns to earning a positive net income, it will pay down the value of the deferred asset until it reaches zero, at which point the Fed will resume sending remittances to the Treasury. This graph shows that the Fed’s costs started exceeding its income in September 2022, after the rapid increase in policy rates and the corresponding increase in the Fed’s interest costs.

Note that this data series from the Board of Governors provides a flow when positive, but a stock when negative. That is, when the Fed’s net income is positive, this series reports the weekly amount that is remitted to the US Treasury. When the Fed’s net income is negative, this series records the value of the deferred asset, which corresponds to the cumulative value of the negative net income incurred by the Fed. To compute weekly net income when this income is negative, one must then take the difference of the weekly series. This is why the series appears extremely negative over the past year: It reports the total value of the deferred asset, not the weekly flow.

In FRED, when a deferred asset exists, one can still compute the weekly flow of net income by editing the graph and switching the units to “Change, Millions of U.S. Dollars,” as below. Note that this will only represent the flow for weeks when the Fed’s deferred asset is positive and was also positive for the prior week. Note also that the amplitude of this change in deferred assets is similar to when the Fed is making remittances, as in the first graph.

How these graphs were created: Search FRED for and select “Liabilities and Capital: Liabilities: Earnings Remittances Due to the U.S. Treasury: Wednesday Level.” You have the second graph. End the sample period on 2022-08-31 and you have the first graph. For the third graph, start the sample on 2022-09-21, click on “Edit graph,” and change units to “Change, Millions of U.S. Dollars.”

Suggested by Miguel Faria-e-Castro and Samuel Jordan-Wood.

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