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You can build a house on paper, but you don’t always make it brick

In other words, housing permits don’t always equal housing starts.

So, say you want to build a house… You’ll need to plan for financing and contractor schedules, among other things. But first and foremost, you must apply for and be granted a building permit before you can start to build. FRED has time series for both building permits granted and housing starts. Given that permits and actual construction go hand in hand, you might expect the two series to follow each other closely if not exactly, with possibly a small delay between the two.

As the graph shows, the two series are well connected during booms, when there’s an upswing in construction. But the two series aren’t nearly as well connected when building activity contracts. The lesson here is that a building permit doesn’t guarantee a house will be built. If economic conditions worsen, for example, between the time you apply for a permit and the time you plan to build, you might decide to postpone or even scrap an approved project. It’s during those times when the housing starts series falls faster than the permits series.

How this graph was created: Search for and add the “housing permits” series to the graph. Then open the “Edit Graph” panel to add a line: Search for and add the “housing starts” series. Finally, shorten the sample period to allow for more detail—in this case, starting 2000-01-01.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: HOUST, PERMIT

Engel’s law is still good food for thought

If your income rose by 15%, would your spending also rise by 15%? Maybe. But would all your spending rise by that amount? Ernst Engel surveyed households and published his results in 1857: He found that spending on food did not rise in proportion to a rise in income. Food is clearly a necessity; we all need some. And households that become wealthier will likely increase spending on food to some degree. But the increase in food consumption will be proportionately less than the increase in income.

Engel’s law is remarkably consistent. For the U.S., we can simply take food expenditures in the national account and divide it by GDP. This ratio is pretty much in continuous decline, with the exception of recessionary periods when incomes drop more than usual from unemployment or reduced work time. Engel’s law has held steady for 160 years.

A primer on income elasticity of demand: Food in general is a “normal good,” which means its consumption rises as income rises. It’s a specific type of normal good, though—a “necessity good”—which rises as income rises, but less than one for one. A more formal description is that food has an income elasticity of demand between 0 and 1. Another type of normal good is a “luxury good”—for example, a yacht. Its consumption rises more than one for one as income rises, so its income elasticity of demand is above 1. Consumption of an “inferior good”—for example, bus tickets—actually declines as income rises. Its income elasticity of demand is below 0.

How this graph was created: Search for “food expenditure,” and you’ll see many price indices. To speed up your search, click on the “consumption” tag in the side bar. Once you add the series shown here, open the “Edit Graph” panel and another series to Line 1: GDP. Then apply formula a/b.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: DFXARC1Q027SBEA, GDP

A marginal look at bank margins

How have banks performed over recent years in this environment of very low interest rates? Banking can be complex, so it’s difficult to pinpoint exactly how low interest rates affect banks’ bottom lines. But there’s a simple measure in FRED that we can examine: the net interest margin. It calculates the ratio of a bank’s net income from assets to the level of those assets. (Put another way, it’s the interest banks earn on investments minus the interest they pay to their lenders and depositors divided by the total level of their interest-earning assets.) Of course, the devil is in the details, and the note on the FRED series page captures some of those details.

Did the lending rate decline less than the cost of funds? Or are margins being squeezed by the low interest rates? The graph seems to imply the latter, but it also shows a general tendency toward lower margins over the span of two decades, which hints that more may be at play here. Maybe widespread use of computers in the management of deposits and credits allowed banks to reduce costs and thus margins. Maybe there’s been increased competition. Maybe something else entirely…

How this graph was created: Search for “net interest margin” and add it to the graph.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: USNIM

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