How is Housing Affecting Inflation? An Update

A few months ago, I argued that housing was messing up inflation measures, in particular the core CPI. With last week’s release of fresh CPI data, I decided to check in to see if that’s still true.

Answer: Yes, but less so. The cost of housing is still rising slower than for other core goods and services, but the gap has narrowed.

In my earlier post, I found that year-over-year core inflation through October was a remarkably low 0.6% and that housing costs (as measured by the CPI for shelter) had fallen 0.4%. As a result, core inflation less shelter was 1.3% — low, but not remarkably so.

We now have data through January: core inflation has picked up a bit to 0.9% over the past 12 months. Shelter costs rose 0.6% over the same period, and core inflation less shelter is 1.2%.

As you can see, the big change is that shelter costs over the past year are now rising, not falling:

Bottom line: Housing costs have dragged the core CPI down over the past year, but not as much as was true a few months ago.

P.S. My earlier post provides details about the BLS measure of shelter prices.

Is Housing Messing Up Inflation Measures? Yes, But …

Here’s the simplest argument in favor of the Fed’s decision to restart quantitative easing:

  1. The economy remains very weak. Unemployment, for example, is still almost 10%, and the underemployment rate is close to 17%.
  2. Key inflation measures are exceptionally low. The core consumer price index (CPI), for example, is up only 0.6% over the past year.
  3. It’s unlikely that Congress and the White House will do anything to stimulate the economy.

In short, the economy is struggling, inflation appears tame, and the Fed is the only game in (Washington) town.

Items (1) and (3) are, I suspect, not controversial. Moderate economic growth is moving us in the right direction, but has done little to create jobs or reduce the yawning output gap. And given the Republican’s election gains, it’s hard to imagine a new round of fiscal stimulus (except an extension of the expiring tax cuts — a form of anti-anti-stimulus).

Item (2), however, is highly controversial. Some commentators argue, for example, that it’s not appropriate to focus on core measures of inflation, which exclude volatile food and energy prices. Others argue that the government systematically (and, perhaps, intentionally) understates inflation.

I will leave those old debates to the side today and focus on a third, more contemporary question: Is housing messing up inflation measures?

Although the housing bubble popped several years ago, America is still adjusting to its aftermath. Falling house prices don’t directly show up in the CPI, but over time they do result in lower rents and lower estimates of the rental equivalent for owning a home. My question is how big an effect those falling housing prices are having on measured inflation.

To start, note that the core CPI really is running at exceptionally low levels:

Indeed, core inflation is well below the levels that inspired the previous round of deflation worries back in 2003.

Now let’s look at what’s happening with the shelter component of the CPI, which tracks the cost of owning or renting a home:

The CPI for shelter has fallen off a cliff. Shelter price inflation averaged about 3% from 1995 through 2007. Over the past year, however, it’s negative.

Shelter makes up almost a third of overall consumer spending, so you might expect that weak shelter prices are having a big effect on measured inflation. They do:

If you strip out shelter from the core CPI, you find that the remaining consumer prices have risen at a moderate pace over the past year (1.3%) – low, but not exceptionally low. Indeed, the economy came much closer to deflation back in 2003, by this measure, than it has so far today.

In short, the ongoing weakness in housing is a key reason why measured inflation is so low. But — and this is an important but — inflation still appears quite moderate even when you adjust for this effect. At 1.3% over the past year, the core CPI less shelter certainly doesn’t inspire concern about inflationary pressures. And if you look more recently, you find that this measure of inflation has been falling (e.g., the pace of inflation was about 1% annually over the past six months).

Bottom line: Housing weakness has indeed pushed measured inflation down a great deal, but it’s not the only factor at work.

Note 1: BLS tracks four costs of shelter: rent of primary residence (for renters), owners’ equivalent rent of residences (for homeowners), lodging away from home, and tenants and household insurance. Lodging and insurance account for only 3.5% of shelter, so it didn’t seem worth the trouble to strip them out to get a housing-only measure. You will sometimes see analysts do this comparison using the BLS measure of housing costs. Housing is about one-third larger than shelter because it includes household energy and utilities purchases, furnishings, and other household operations. For that reason, I think shelter is a better measure for exploring the relationship between the housing market and measured inflation.

Note 2: According to BLS, food comprises about 14% of consumer expenditures, energy about 9%, and shelter about 32%. So the core CPI less shelter covers about 45% of consumer expenditures. So use it with care.

October Rail Traffic – Still Upbeat

October was another solid month for America’s railroads, according to the Association for American Railroads. October traffic was 11% higher than the depressed levels of a year ago:

Intermodal traffic (think trailers and containers) is up 14% over 2009, thus returning to 2008 levels:

Carloads (think bulk materials like coal, grains, minerals, and chemicals plus autos) are up almost 9%:

Another Tepid Quarter for GDP

BEA released its first estimates for third-quarter GDP yesterday. Headline growth was a disappointing, if not surprising, 2.0%.

Here’s my usual graph of how various components of the economy contributed to overall growth:

Housing fell back into the red, while non-residential structures eked out a small gain. Consumers continued to spend at a moderate pace (consumer spending grew at a 2.6% rate, thus adding 1.8 percentage points to growth). But the big stories were the continued boost from inventories, and the continued drag (in GDP-accounting terms) from imports.

The pessimistic take on inventories (see, for example, this tweet from Nouriel Roubini) is that the third quarter build up was unintentional, and thus is bearish for fourth quarter growth. The optimistic take, I suppose, is that maybe businesses see stronger demand ahead. But that feels rather, er, speculative.

For my usual set of caveats about the import figures (and, therefore, all of these figures), see my last post on the GDP numbers.

August Rail Traffic, An Upbeat Economic Indicator

August was a busy month for America’s railroads, according to the Association for American Railroads. Traffic spiked up, as often happens during the month. More importantly, August traffic was 11% higher than a year ago (the same gain as reported in July):

Carloads (think bulk materials like coal, grains, minerals, and chemicals plus autos) are up about 6% over 2009:

Intermodal traffic (think trailers and containers) is up almost 20%, thus returning to 2008 levels:

Further Signs of a Slowdown

As expected, BEA’s second stab at GDP growth for the second quarter was even less inspiring than the first. Headline growth was a tepid 1.6%, down from the 2.4% previously reported. Consumer spending and business spending on equipment and software were actually stronger than earlier estimates, but business structures, inventories, and exports all weakened, while imports (which deduct from GDP the way BEA calculates it) grew faster than previously expected.

Last month I pointed out one, small silver lining in the original GDP report: every major category of demand had increased. That is still true in the revised data, although structures just squeaked by with a miniscule 0.01 percentage point contribution to overall growth:

Investment showed particular strength. Business investment in equipment and software (E&S) grew at a 25% pace, thus adding about 1.5 percentage points to overall GDP growth. Boosted by the end (hopefully permanent) of the new homebuyer tax credit, housing investment grew at a bubble-like 27% pace (adding about 0.6 percentage points to GDP).

Despite solid growth in disposable incomes–up 4.4% adjusted for inflation–consumer spending grew at only a 2.0% pace.  As a result, the saving rate increased to 6.1%, compared with 5.5% in the first quarter.

And then there are imports. As I’ve discussed before, BEA calculates GDP by adding up all the components of demand for U.S. products–consumers, businesses, governments, and export markets–and then subtracting the portion of that demand that is supplied by imports. That means that any growth in imports appears as though it subtracts from overall economic growth.

That happened in a big way in the second quarter. Imports grew at a brisk 32% pace, thus subtracting (using BEA’s accounting approach) 4.5 percentage points from overall growth. Which is why all those blue bars in the graph net out to only 1.6% GDP growth.

I should also note that BEA’s calculation of contributions to GDP growth, which I graphed above, is subject to the same criticism that I’ve leveled at the claim that consumer spending is 70% of the economy. In a perfect world, an appropriate share of the imports (the red bar) would be netted against each of the components of demand (the blue bars). The result would be a graph of contributions that would truly illustrate how much each category of demand actually contributed to U.S. GDP growth. I hope to take a crack at that in the future (but I said that last month, too).

Fiscal Policy in Interesting Times

Back on August 5, I gave a speech at the Retirement Research Consortium’s annual conference “Retirement, Planning, and Social Security in Interesting Times.” I’ve been saving up the link to the C-Span video to share during my vacation.

Here it is. (I hope the link still works; if not, I will fix it once I get back on the grid.)

Keeping with the spirit of the event, I spoke about “Fiscal Policy in Interesting Times.” And with that title, I simply had to mention the famous curse, “May you live in interesting times.”

As the helpful folks at Wikipedia point out, chances are good that this curse originated in England or the United States not, as often alleged, China. Regardless of its origin, it’s still an excellent curse, which I remember my mom invoking often in my childhood (rhetorically, I should note, not at me). For an audience of policy researchers, however, it’s a curse with a silver lining. We may not want interesting things to happen (financial crises, trillion-dollar deficits, 9.5% unemployment, etc.), but they do increase the odds that policymakers, journalists, and the public will pay attention to what we are saying (whether they should is a separate question …).

What makes today particularly interesting is that we face lots of uncertainty and major challenges. That a potent mix. We know less about what’s going on than usual, but we are playing for bigger stakes. Case in point: Fed Chairman Ben Bernanke’s recent statement about the outlook being “unusually uncertain” while the economy still struggles to heal from the financial crisis. Is it a rebound or a relapse? I fear it may be the latter, but we just don’t know.

The meat of the speech considers the economic and fiscal uncertainties and challenges we face. For example, I lament the ridiculous uncertainty in our tax system. Not only do we not know what will happen in 2011, after the scheduled expiration of the 2001 and 2003 tax cuts, we don’t even know what the tax code is in 2010. Will there be an AMT patch? A retroactive change to the temporarily extinct estate tax? What about the (in)famous tax extenders?

I wrap up by sharing one other thing I learned from Wikipedia. The “interesting times” curse is apparently the mildest of a trio of curses.

If you are feeling really mad, the appropriate curse is “May you come to the attention of people in authority.” Which again is rather a mixed curse for policy researchers who want policymkaers to pay attention.

And if you are really, really mad, then you should bring out the worst of the curses: “May you find what you are looking for.”

P.S. At the moment, I am looking for puffins, humpback whales, glaciers, and grizzly bears.

“Tracking” the Economy

The fine folks at the Association of American Railroads are out with their latest edition of Rail Time Indicators. Total traffic (carloads plus intermodal) in July was about 11% higher than the dismal levels of a year ago, but remains about 10% below earlier years:

The rebound has been weaker in carloads (think bulk materials like coal, grains, minerals, and chemicals plus autos); they are up about 4% over 2009:

And stronger in intermodal (think trailers and containers), which are up about 17%:

A Silver Lining in Second Quarter GDP?

Last Friday the Bureau of Economic Analysis released its first look at GDP growth in the second quarter. BEA estimates that the economy grew at a moderate 2.4% annual pace in the quarter, notably slower than the 3.7% pace in the first quarter and the 5.0% pace in the fourth quarter of 2009 (both those figures were revised in this release).

As usual, I think it’s helpful to break down economic growth into its key components. The following chart illustrates how much various types of economic activity contributed to (or subtracted from) second quarter growth:

The chart illustrates the silver lining in an otherwise tepid GDP report: every major category of domestic demand expanded in the second quarter. Consumers, businesses, export markets, and governments all increased their purchases. That’s a good sign. Indeed, you have to go back more than five years, to the first quarter of 2005, for the last time that happened.

Investment showed particular strength. Business investment in equipment and software (E&S) grew at a 22% pace, thus adding about 1.4 percentage points to overall GDP growth. Boosted by the end (hopefully permanent) of the new homebuyer tax credit, housing investment grew at a bubble-like 28% pace (adding about 0.6 percentage points to GDP). And business investment in new structures recorded its first gain in two years

Despite solid growth in disposable incomes–up 4.4% adjusted for inflation–consumer spending grew at only a 1.6% pace.  As a result, the saving rate increased to 6.2%, compared with 5.5% in the first quarter.

And then there are imports. As I’ve discussed before, BEA calculates GDP by adding up all the components of demand for U.S. products–consumers, businesses, governments, and export markets–and then subtracting the portion of that demand that is supplied by imports. That means that any growth in imports appears as though it subtracts from overall economic growth.

That’s what happened in the second quarter. Imports grew at a brisk 29% pace, thus subtracting (using BEA’s accounting approach) 4.0 percentage points from overall growth. Which is why all those blue bars in the graph net out to only 2.4% growth in GDP.

I should hasten to add that this does not actually mean that imports are bad for growth. The big red bar is an accounting convention, not a measure of economic impact. Indeed, many imports are essential to our economy, at least in the foreseeable future (think oil for transportation and coffee for Starbucks).

I should also note that BEA’s calculation of contributions to GDP growth, which I graphed above, is subject to the same criticism that I’ve leveled at the claim that consumer spending is 70% of the economy. In a perfect world, an appropriate share of the imports (the red bar) would be netted against each of the components of demand (the blue bars). The result would be a graph of contributions that would truly illustrate how much each category of demand actually contributed to U.S. GDP growth. I will take a crack at that in the future.

Consumer Spending is 60% of the Economy, not 70%

Early Friday, the Bureau of Economic Analysis released its third look at economic growth in the first quarter. The results were disappointing: BEA now estimates that Q1 growth was only 2.7%, down from the prior estimate of 3.0%. A key reason: consumer spending was weaker than previously thought.

As I noted in May, the monthly release of GDP data is inevitably followed by commentators claiming that “consumer spending makes up 70% of the U.S. economy” (see, for example, here). Unfortunately, that isn’t right. Consumer spending appears to be about 70% of the economy based on a seemingly obvious calculation (consumer spending divided by GDP), but that ignores the way that macroeconomic accounting handles imports. For reasons detailed in my earlier post, careful analysis suggests that the actual ratio is about 60%.

One reason the 70% error is so common is that doing the correct calculation requires a great deal of work; for example, you need to estimate the fraction of consumer purchases that come from imports. If we want commentators to start using the right figure, we need an easier way to get the idea across using the information reported in the headline GDP release.

Here’s one idea: Compare consumer spending to a measure of overall demand. To do so, we start with the usual macroeconomic identity:

GDP = C + I + G + X – M,

which says that GDP equals Consumer spending, Investment, Government spending, and eXports minus iMports (which are subtracted to avoid double-counting). Looking at this identity, you see that C, I, G, and X can be viewed as measures of demand from consumers, businesses, governments, and overseas markets, while M is a measure of supply from overseas producers.

To get a more reasonable measure of the importance of consumer spending, we can calculate what share of “overall demand” (C + I + G + X) comes from consumers. As shown in the chart, that measure (in red) has been roughly 60% for decades. The usual, misleading measure of consumer spending’s importance (in blue), however, has been up around 70% over the past decade, but used to be lower back when imports were smaller.

The C / (C + I + G + X) measure of consumer spending’s importance is hardly exact. For example, it doesn’t consider how much consumer spending actually comes from imports. However, it’s the simplest measure I could think of that comes close to the right answer. But maybe readers have an even better idea?

P.S. Thanks to Cornelia Strawser for helpful discussion of this measurement challenge.