Federal Reserve Economic Data

The FRED Blog has discussed the seasonality of food prices, labor markets, interest rates, and e-commerce. So, perhaps it’s no surprise to learn that there are also seasonal ups and downs for some import flows.

The FRED graph above shows two data series produced collaboratively by the Census Bureau and the Bureau of Economic Analysis: the monthly U.S. dollar value of goods imported from China (in green) and from Canada (in red). This price does not include import duties, freight, insurance, and other charges related to bringing the merchandise into the U.S.

The repeating up-and-down monthly pattern of U.S. imports from China contrasts with the comparatively steadier pattern of U.S. imports from Canada: Many Chinese goods arrive at U.S. ports and shipping centers in October, while far fewer do in February and March; Canadian goods, in comparison, arrive in fairly similar numbers throughout the year.

The data don’t offer a breakdown by type of imported good, so we can’t say if the Chinese goods are available for purchase only in the latter part of each year. But the timing of the imports is just ahead of the busiest retail season of the year, the Christmas holiday; that suggests these are consumer goods likely to be purchased as gifts. Perhaps Santa Claus prefers to shop in China rather than Canada. But we’ll need to do more research on that.

How this graph was created: Search for and select “U.S. Imports of Goods by Customs Basis from China.” From the “Edit Graph” panel, use the “Add Line” tab to search for and select “U.S. Imports of Goods by Customs Basis from Canada.” To change the graph type and style of the series use the “Format” panel.

Suggested by Diego Mendez-Carbajo.

The FRED Blog recently featured an ALFRED graph to discuss a revision to the methodology used by Realtor.com to report housing inventory data. Today, we return once more to ALFRED, the archive of historical versions (or vintages) of FRED data, to discuss revisions to employment data.

The ALFRED graph above shows 12 different vintages of total nonfarm employment data from the U.S. Bureau of Labor Statistics. The graph doesn’t display the legend, to leave more room for the data (graph with legends). The solid black line shows, as of January 7, 2022, the monthly changes in total nonfarm employment for each month in 2021. The dotted red lines and circles show the initially announced and subsequently revised monthly changes in total nonfarm employment.

Consider January 2021: While employment growth was initially estimated at 49,000 persons, during the next two months that figure was revised first to 166,000 and then to 233,000 persons. Revisions to employment data are a matter of common practice. As the BLS states: “Monthly revisions result from additional reports received from businesses and government agencies since the last published estimates and from the recalculation of seasonal factors.” In fact, during 2021, the BLS revised up eight monthly employment figures and it revised both up and down two monthly figures. (Note: At the time of this writing, data revisions for November and December had not yet been completed.)

The second ALFRED graph shows employment data revisions during 2020. In the year of the COVID-19-induced recession, the BLS revised up eight monthly employment figures, it revised down one monthly figure, and revised both up and down three others. Those revisions are harder to see in a graph because the reduction in total employment recorded during April 2020 was staggeringly large.

However, the takeaway from this post is that employment data are always revised. Economic policymakers are aware of economic data revisions and can see through “the fog of numbers” described by Jordà, Kouchekinia, Merrill, and Sekhposyan.

How this graph was created: Search ALFRED for “All Employees: Total Nonfarm Payrolls.” By default, ALFRED shows a graph with two sets of bars: the most recent vintage and the prior vintage. To change the data units, in the “EDIT BAR 1” tab, select “Units: Change.” To customize the graph type and style of the series use the “Format” panel. Add additional vintages by using the “Add Line” tab and select the date of the desired vintage from the “or select a vintage” dropdown menu.

Suggested by Diego Mendez-Carbajo.

The FRED Blog has discussed how central banks and finance ministries buy and sell foreign currencies to influence the value of their own currencies. Those purchases and sales are called interventions and FRED has data for Australia, Germany, Japan, Italy, Mexico, Switzerland, Turkey, and the United States. Today, we discuss the most recently recorded interventions from the Central Bank of Turkey and compare them with interventions from the Central Bank of Mexico.

The FRED graph above shows the amounts of U.S. dollars bought and sold by the Central Bank of Turkey in red and the Central Bank of Mexico in green. Purchases are recorded as positive values (larger than zero), sales are recorded as negative values (smaller than zero), and the sum totals for each month are the data points shown in the graph.

When a central bank sells U.S. dollars in foreign exchange markets, it increases their supply relative to the domestic currency, intending to prop up the value of that domestic currency. For example, in October 2008, the Central Bank of Mexico sold 3 billion U.S. dollars to address the ongoing depreciation of the peso. But that intervention, and several others that followed, did not prevent the depreciation of the peso over the following 12 months.

In the case of Turkey, the timing of the latest reported central bank intervention in relation to the relative value of the Turkish lira is less obvious: The December 2021 sale of 5 billion U.S. dollars took place while the domestic currency continued on its long path of steady depreciation.

These observations highlight how difficult it can be to interpret data. Obviously, the central banks are intervening to prevent something from happening. If it still happens, is it because the intervention was ineffective? Or would conditions have been even worse without the intervention? A simple graph cannot answer those questions.

How this graph was created: Search for and select “Turkish Intervention: Central Bank of Turkey Purchases of USD (Millions of USD).” From the “Edit Graph” panel, use the “Add Line” tab to search for and select “Mexican Intervention: Banco de Mexico Purchases of USD against MXN (Millions of USD).” To change the frequency of the data use the “Edit Line” panel and select “Modify Frequency: Monthly” and “Aggregation method: Sum.”

Suggested by Diego Mendez-Carbajo.