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Posts tagged with: "GDP"

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Switzerland’s mountainous monetary base

More Swiss uniqueness on their national holiday

Today is the Swiss national holiday. In the past, we’ve taken this opportunity to discuss some unique (i.e., weird) feature of the Swiss economy. This time we use FRED to compare the Swiss monetary base with the U.S. monetary base. To make them comparable, we divide each by its country’s nominal GDP. We see that the general patterns are similar, with a sudden increase in 2008. While the U.S. monetary base has started to go back down (it’s lost a quarter since its high point), there’s nothing that shows any tendency to return to the long-run trend. Indeed, Switzerland is still working with extremely low (even negative) interest rates.

But let’s talk about the stark difference shown in the graph. This statistic for Switzerland is dramatically higher than it is for the U.S.: The Swiss monetary base is now worth over three years of its GDP, while the U.S. monetary base is worth only about two months of its GDP. There has always been a large difference, but it’s larger than ever now. This situation is likely fueled by the oversized banking sector in Switzerland as well as the refuge currency role of the Swiss franc. The latter is particularly true in times of uncertainty, including the uncertainty of its neighbors’ currency, the euro.

How this graph was created: Search for and select “Swiss monetary base” and click “Add to Graph.” From the “Edit Graph” panel, add a series by searching for “Switzerland GDP,” taking the quarterly series with nominal data, and applying formula a/b. Then, from the “Add Line” tab, search for and select “monetary base,” add a series by searching for “GDP” again taking the nominal series and applying formula a/b/1000. Finally, adjust the sample period to start in 1980.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: BOGMBASE, CPMNACSAB1GQCH, GDP, SNBMONTBASE

A mirror image of mortgages and equity

The story of the Great Recession told with two intersecting lines

Take a look at mortgage or real estate data on FRED. The main story (for a number of years, now) is all about the Great Recession, which is clear in the graph above. Let’s unpack that story.

In blue, we have the share of equity in the real estate that households own. In the 1950s, 70-80% of the value of the average house was owner equity, and 20-30% was owned by a financial institution. The share of owner equity essentially stayed within a 60-70% band until the end of the millennium. Then it quickly dropped to below 40%, before rebounding today to its previous level (from 2001 or so). What happened during the Great Recession is clearly a deviation from normal.

This being a ratio, the deviation could have come from changes on either side of that ratio: 1. Mortgages could have sharply increased without a change in owner equity. 2. Owner equity could have dramatically shrunk. To help figure this out, we can look at the red line, which tracks household mortgages normalized by GDP. It shows the opposite pattern of the blue line: Mortgages clearly become more popular in the initial years, as the financial sector develops. Then they stabilize, with a push in the 1980s before really taking off, earlier than the blue line, and then they crash; soon after, the blue line shoots up.

What does this teach us? First, there was clearly a sharp increase in mortgages before the crisis. But it was accompanied by an equivalent increase in the value of the homes, so there was no visible change in the share of owner equity until the value of homes stopped keeping up with the mortgages and even dropped. At the bottom of the crisis, owner equity is at its lowest, and it is only then that mortgages start decreasing: Virtually no new mortgages are issued, current mortgages are gradually paid off and some existing ones are foreclosed, returning to their historical levels.

How this graph was created: Search for and select “Household equity in real estate” and click “Add to Graph.” From the “Edit Graph” panel, use the “Add Line” tab to search for “home mortgages.” Select a series in levels and add it to the graph. From the “Customize data” search bar, search for and add the nominal (not real) GDP series. Finally, apply formula a/b*100.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: GDP, HMLBSHNO, HOEREPHRE

Assets U.S. households hold

Changes in the value of financial assets, real estate, and durable goods

FRED just expanded its coverage of the Z.1 release from the Board of Governors. Hidden behind this obscure name is a massive dataset that describes the financial situation of the nation, divided into sectors— households, businesses, government, and “the rest of the world.” Here, we look at the assets of households, which we’ve divided into three broad categories: real estate, consumer durables (cars, household appliances, furniture, etc.), and financial assets. The value of these assets has generally increased (no surprise; inflation is a factor), so we decided to divide each series by nominal GDP. This gives us a better idea of the quantities.

We can see that financial assets are the largest type of household asset, and their value relative to the other categories has continually increased; their value has also increased relative to total income (GDP). Currently, households’ financial assets are about 4 times annual GDP, rising from 2.5 times in 1987 when the data start. There hasn’t been a substantial increase in the relative value of real estate, however, which has usually been a little over one year’s worth of GDP (an exception being the run-up before the Financial Crisis). Consumer durable goods has actually decreased, from a third to a quarter of annual GDP. And financial assets comprised about 60% of all household assets in 1987, but now stand at almost 75%.

How this graph was created: From the release table for the balance sheet of households, select the series you want displayed and click “Add to Graph.” From the “Edit Graph” panel, add to each line nominal (not real) GDP. Apply formula a/b/1000 to each line, except for real estate where we don’t need to add /1000 to a/b to get the units right.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: BOGZ1FL194090005Q, BOGZ1LM155111005Q, GDP, HOOREVLMHMV


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