Federal Reserve Economic Data

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The federal budget balance as a fraction of GDP

Tracking data from two sources with two different calendars

The FRED Blog has discussed how many weekdays there are per month, quarter, and year. (It may seem trivial, but when you work with data, you need to be precise about federal and local holidays and how weekends shake out in a given month.)

Today, we consider two data sources, each with its own calendar year.

The FRED graph above shows the balance of the federal government budget as a percent of GDP. To calculate the budget balance, we subtract the value of federal net outlays from the value of federal receipts. Because those receipts and outlays change with the overall level of economic activity, we divide their difference by GDP and multiply by 100 to show it at as annual percentage.

And here’s the rub: Federal receipts and net outlays are reported by the Office of Management and Budget (OMB) for the fiscal year, which runs from October of the previous year to September of the current year. But GDP is reported by the Bureau of Economic Analysis (BEA) for the calendar year, which—just to make sure we’re on the same page—runs from January to December. So each organization counts 12 months for each year but starts counting on different dates.

If you want to learn more, keep on reading…

The second FRED graph shows the annual balance of the federal government budget as a percent of GDP using both calendars: Data from the fiscal year is in red, and data from the calendar year is in blue. The lines are very similar in value, meaning that the use of two different calendars has a small impact on the calculation overall. Small though it may be, the difference is largest for the calendar year at the end of a recession. At that time, the automatic stabilizers of fiscal policy have widened the gap between federal revenues and outlays while GDP is starting to rebound.

How these graphs were created: For the first graph, search for and select “Federal Receipts.” From the “Edit Graph” panel, use the “Edit Line 1” tab to customize the data by searching for and selecting “Federal Net Outlays” and “Gross Domestic Product (GDPA).” Next, create a custom formula to combine the series by typing in (((a-b)/1000)/c)*100 and clicking “Apply.”
For the second graph, from FRED’s main page, browse data by “Release.” Search for ”Debt to Gross Domestic Product Ratios” and check the two boxes under “Federal Surplus or Deficit [-] as Percent of Gross Domestic Product.” Last, click “Add to Graph.”

Suggested by Diego Mendez-Carbajo, Maria Arias, and Chris Russell.

View on FRED, series used in this post: FYFR, FYFSDFYGDP, FYFSGDA188S, FYONET, GDPA

Trade between the U.S. and China: Steady as she goes?

For years now, we’ve been talking about the tempest of tariffs and trade wars between the U.S. and China. The FRED graph above doesn’t reveal all the effects, but it gives us the big picture by tracking overall imports, exports, and the trade balance for goods. Clearly, U.S.-China trade has grown tremendously over the decades, along with a large trade surplus for China. But things haven’t changed in any substantial way for the past 10 years. The composition of traded goods today may be different from what it used to be, but there’s nothing remarkable happening in the aggregate.

A few more ideas:

  1. The units for imports and exports are in natural logarithms, which we’ve used before to evenly display changes over time.
  2. FRED has data only for traded goods, not services; but we did investigate this topic a while back.
  3. There’s nothing intrinsically bad about the U.S. having a trade deficit.

How this graph was created: Search for and select the “goods imports China” series and click “Add to Graph.” From the “Edit Graph” panel, use the “Add Line” option to search for and add the “good exports China” series. Set the units for both lines to “Natural Log.” For the third line, use “Add Line” again to search for and select the “good imports China” series. Then use the “Customize data” search field to search for and select the “good exports China” series. Apply formula b-a. Finally, use the “Format” tab to choose “Right” for the y-axis position of the last line.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: EXPCH, IMPCH

Negative nominal interest rates for real?

A true story in Switzerland

Real negative interest rates are easy to imagine when inflation is higher than the interest rate. But nominal negative interest rates have long been thought of as either inconceivable or unsustainable. Yet, in recent years, several European countries and Japan have made negative nominal interest rates a reality. The most extreme case seems to be Switzerland, which is featured in the top graph: The spot rate, the 3-month LIBOR, and even the 10-year government bond rate are all negative now and have been for several years. How is this possible?

This isn’t a case of an economy that needs major stimulus through low interest rates. Rather, it’s an export-focused economy whose currency has a strong tendency to appreciate; in fact, the Swiss franc is considered a refuge currency in times of crisis. The crisis at hand involves the euro’s various troubles in recent years, including the debt problems of some of its member countries. Switzerland has avoided these troubles and has even managed to achieve successive government surpluses. So it’s easy to understand why there’s so much demand for Swiss francs and bonds. But so much demand typically causes a local currency to appreciate, which would make exporting more difficult. The Swiss National Bank, therefore, has adopted a policy of negative interest rates to make the franc less attractive. Interestingly, the effect permeates the Eurodollar market as well, as shown in the bottom graph.

How these graphs were created: NOTE: Data series used in these graphs have been removed from the FRED database, so the instructions for creating the graphs are no longer valid. The graphs were also changed to static images.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: CHF3MTD156N, IR3TED01CHM156N, IRLTLT01CHM156N, IRSTCI01CHM156N


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