Federal Reserve Economic Data

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A friendly warning: Data aren’t perfect

Graphing data can reveal issues that spreadsheets may not

“The greatest value of a picture is when it forces us to notice what we never expected to see.” – John Tukey

FRED gives you the option of downloading data into a spreadsheet. Of course, it’s also common to present the data in graph form, which is much easier on the eyes. But plotting your data is exceptionally important for other reasons.

A graph can give the numbers a clear and convincing voice. And it can also reveal the unexpected. Because your eyes can quickly catch something that simply looks wrong, you may observe the existence of data issues on a graph that would not be immediately apparent when looking only at the numbers.

The FRED graph above plots three vintages of the Economic Policy Uncertainty Index from January 5 (blue), 6 (red), and 7 (green) of 2021. The plots are indistinguishable until December 9, 2020, where the January 6 vintage jumps to a series maximum of over 1,000 before dropping to a constant value of 10.92. Notice that there are also some minor differences between values in the January 5 and January 7 vintages. While it’s normal for data vintages (even those that are a day apart) to differ slightly, the large discrepancies in the January 6 vintage clearly stem from data issues…

As it turns out, this vintage contains incorrect values. And that only became clear because we plotted the data. Had we not done that, the issue would have remained undetected and may have caused further errors during our application of the data.

Search the FRED Blog for more posts about the Economic Policy Uncertainty Index.

How this graph was created: Browse FRED data by category. Under the category “Academic Data,” select “Economic Policy Uncertainty” and then the not seasonally adjusted version of the series “Economic Policy Uncertainty Index for United States.” From the “Edit Graph” panel, select the vintage for 2021-01-05. From the “Edit Bars” tab, click “Edit Bar 2” and select the vintage for 2021-01-06. Using the “Add Line” tab, create another line with the same series and edit bar 3 to be the vintage 2021-01-07. Change the graph type and colors to taste using the “Format” tab. Last, change the range by using the scroller directly below the graph or choose specific dates by typing them into the white boxes just above the graph.

Suggested by Aaron Amburgey and Michael McCracken.

View on FRED, series used in this post: USEPUINDXD

Changes in the U.S.-China trade deficit

Exports and imports before and after tariffs and the pandemic

Many of the trade policies that began in 2018 were driven by the high and persistent U.S. trade deficit with China. For example, the U.S. announced tariffs on solar panels and washing machines from China in January 2018, which is marked by the first vertical line in the FRED graph above. Several rounds of U.S. tariffs followed, and China enacted retaliatory tariffs.

We start our graph in January 2016 to include data before and during the period when these trade policies were initiated.*

The basic story told by the graph is that U.S. exports to China (in blue) seem to be relatively stable over time, but U.S. imports from China (in red) are more variable and also much larger. So, the bilateral trade deficit (in green), which is the excess of imports over exports, seems to follow the variable path of imports. Despite the trade war, the trade deficit peaked in October 2018. It fell after that for a few months, only to rise again above its January 2016 level by the middle of 2019.

These facts seem to suggest that the trade war didn’t achieve any significant, durable difference in the U.S.-China trade deficit. How the deficit will evolve in the future, of course, will depend on a whole host of factors, including consumption behavior and the evolution of comparative advantage in each nation.

The second vertical line on the graph marks the first COVID-19 case reported in Wuhan in December 2019. In the months that followed, there was a sharp decline in imports from China to the U.S. and also in the bilateral trade deficit.

Interestingly, since March 2020, there has been a sharp turnaround in imports and the U.S.-China trade deficit. Among other factors, this turnaround in imports may be related to imports of essential medical equipment, described in an Economic Synopses essay by Leibovici and Santacreu.

With the easing of lockdowns in the U.S. and growth in China, there also seems to be a recent spurt in U.S. exports to China, which rose to its highest level in October 2020. Indeed, because of this increase in exports, the U.S.-China trade deficit in October of 2020 is a bit lower than its level in July 2020.

Overall, COVID-19’s effect on U.S.-China trade seems somewhat surprising, with a strong rebound of trade in the relatively early months of the COVID-19 crisis in the U.S., followed by a further strengthening of trade in more recent months when the U.S. economy has seemed to be on a path to recovery.

*By the way, the numbers shown here are nominal (i.e., not adjusted for inflation). It’s a good idea to pay attention to this distinction when interpreting data, but we found that “real” numbers based on the U.S. CPI deflator here don’t lead to any qualitative differences.

How this graph was created: Search for and select “U.S. Exports of Goods by F.A.S. Basis to Mainland China.” From the “Edit Graph” menu, use the “Add Line” tab to search for “U.S. Imports of Goods by Customs Basis from China.” For the dotted line, use “Add Line” again to search for and select “U.S. Imports of Goods by Customs Basis from China.” Then in the “Customize data” section, search for “U.S. Exports of Goods by F.A.S. Basis to Mainland China.” Next, create a custom formula to combine the series by typing “a-b” and clicking on “Apply.” To add the vertical lines, refer to these instructions. Finally, use the “Format” tab to adjust the format of the graph.

Suggested by Subhayu Bandyopadhyay and Praew Grittayaphong.

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

What’s behind the recent surge in the M1 money supply?

While the terms “money” and “wealth” often mean the same thing in everyday parlance, economists define money more narrowly as the component of wealth consisting of “transaction balances.” That is, if you can use it to buy goods and services and to settle debts, then it’s considered to be money.

Money is distinct from other forms of wealth that first need to be liquidated—that is, converted into money—before their value can be spent. According to this definition, physical currency and checkable bank deposits constitute money. And, indeed, these objects make up the definition of what economists label as the M1 money supply.

Because money is valued as a payment instrument, people are willing to hold a fraction of their wealth in money form for the sake of convenience, even though money earns relatively little interest and cash usually earns no interest at all.

If M1 carries the opportunity cost of not earning much interest, then why has the M1 money supply been increasing?

This increase is shown in the FRED graph above (purple line), where we measure M1’s opportunity cost as the one-year U.S. Treasury yield (green line). In late February and early March of 2020, the Fed cut its policy interest rate dramatically to help ease credit conditions during the COVID-19 crisis. The resulting acceleration in the supply of M1 can be understood largely as banks accommodating an increase in people’s demand for money. However, the opportunity cost of money has remained more or less constant throughout 2020, over which time M1 growth has accelerated. What might account for this behavior?

To help answer this question, we’ll need to talk a bit about banking regulations…

One factor responsible for this behavior may be related to a change earlier this year to Regulation D: The Federal Reserve requires banks to hold reserves against checkable deposits. But the regulation does not require banks to hold reserves against savings and money market accounts, which restrict depositors to no more than six transfers or withdrawals per month. These latter accounts are highly liquid (and in the case of some money market funds, even checkable). But because they’re not as convenient as checkable deposits, they typically compensate depositors with a more attractive interest rate.

Another measure of the money supply adds these savings deposits and checkable money funds to M1: It’s known as, you guessed it, M2. From the graph, we see that the growth rate of M2 has remained relatively stable since May 2020. This suggests that the rapid acceleration in M1 since May 2020 is mainly from money moving out of the non-M1 components of M2 into M1, rather than reflecting any acceleration in the demand for transaction balances.

For even more about the role of banking regulations, read on…

On April 24, 2020, the Federal Reserve Board announced that Regulation D would no longer impose limits on the number of transactions or withdrawals permitted on savings deposit accounts. According to this ruling, if a bank suspends enforcement of the six-transfer limit on a savings deposit, the bank may report that account as a “transaction account” on its FR 2900 reports. However, the bank may instead, if it chooses, continue to report the account as a “savings deposit” (See Board of Governors FAQ #6). Since banks have been flush with excess reserves since 2008, reporting savings deposits as transaction balances incurs no cost. On the other hand, it’s not immediately clear what advantage there is from the bank’s perspective in relabeling savings accounts as transactions balances. In any case, it seems that the modification of Regulation D in late April has effectively rendered savings accounts almost indistinguishable from checking accounts from the perspective of depositors and banks. Accordingly, the composition of M2 between M1 and non-M1 components conveys little economic information.

How this graph was created: From FRED, search for “M2 Money Stock” and select the first search result. To add the other series, select “Edit Graph,” “Add Line,” and search for “M1 Money Stock” and “1-Year Treasury Constant Maturity Rate.” For the latter, change the frequency to weekly (ending Monday, last value), to match the other series. To change the M1 and M2 money stock units select “Edit Graph” and “Edit Lines.” Then select the lines corresponding to the M1 and M2 series and change the value under “Units:” to “Percent Change from Year Ago.” To move the y-axis for the M1 and M2 series on the right, select “Edit Graph” and “Format.” Then scroll down and select “Right” under “Y-Axis position” for the lines corresponding to the M1 and M2 series. Finally, to change the time span, click on “5Y” above the graph.

Suggested by David Andolfatto and Joel Steinberg.

View on FRED, series used in this post: DGS1, M1, M2


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