Posts filed under “Data Analysis”

OER, CPI and the Fed: A Strange Love Story

What do apartment rents in NYC have to do with Federal Reserve policy, interest rates, and rising bond yields?

According to a recent analysis out of Barclay’s Capital by Dean Maki and Julia Coronado, a whole lot more than you might imagine.

When April CPI was released on May 15th, the surprise was to the softside. U.S. markets rallied, as traders believed rate cuts were coming sooner rather than later. We disagreed with this assessment, noting various Inflation Errors, including the very telling Core/Headline CPI Spread.

Barclay’s looked at the key reason for this CPI surprise — they found it was buried in the way the core CPI gets constructed. The BLS measure of home price inflation is the Owner’s Equivalent Rent (OER); it’s what a homeowner could theoretically rent their house out for. That is the key to the housing portion of the BLS CPI calculation — OER is about 43% of the core CPI measure.

My pal David Kotok (whom I owe 2 bottles of Wine to, having lost a market bet — but thats an entirely sperate post), who is Chairman and Chief Investment Officer of Cumberland Advisors, points to a terrific piece of research from Barclays Capital that "disaggregated the OER and found that the bulk of the OER surprise came
from the New York City metropolitan area. The CPI is broken down into
four regions. Only the Northeast showed a pronounced deceleration in
OER. Within the region, NY jumps out so dramatically that Barclays
argues it accounts for roughly 75% of the total national deceleration
in OER."

Why is this? Given the strength in the Investment Banking, Hedge Fund and Private Equity industries in and around NYC, the local housing market here is doing much better than the national averages. "Barclays surmises that this is tied to the rise in existing home
sales in NY. The region has seen stronger housing sales recovery than
elsewhere in the Northeast or in the national statistics.  Rising home sales suggest a substitution of ownership for
renting. That may be more important than vacancy rates in determining
OER."

Thus, Barclays suggests that we not get too excited about a potential Fed easing because of
this surprise in OER.

Kotok makes the following astute observation as to what this may mean: 

"The Fed sees this OER data, too. They incorporate it into their policy decision making.   OER is a very large piece (24%) of the total CPI. It is the key to the housing component which is 43% of the total CPI.  When you remove the food and energy parts and derive the core CPI, the OER component looms even larger at 30% of core CPI. Note that it is a large 14% of the Feds preferred core PCE according to Jim Bianco.

At Cumberland we have been proceeding under the assumption that the national housing slump has not bottomed. We saw the upturn in NY housing sales as an exception to the national trend and due to the bull market in the financial sector. We believe that the weakness in housing keeps the Fed from raising rates even though the inflation numbers are still above the Feds comfort zone.   

This recent analysis by Barclays Capital gives us some pause. Its not enough for us to change strategy now. But we might alter our strategy if we conclude that the nations housing sector deterioration is ending sooner rather than later.

The next CPI release is June 15th and will cover the month of May."

 

Good stuff, David.  Its more proof that inflation is much higher than reported by BLS.

If I can access the full research document, I will update this later with the link.

Category: Data Analysis, Economy, Federal Reserve, Fixed Income/Interest Rates, Inflation, Psychology

The Value of the Dollar

Category: Currency, Data Analysis, Economy, Inflation

Housing is Falling Much Faster than Reported

Category: Data Analysis, Economy, Real Estate

Inflation Errors (Part II)

Category: Data Analysis, Economy, Federal Reserve, Inflation, Psychology

Category: Data Analysis, Economy, Federal Reserve, Inflation

CPI & Retail Sales

Category: Data Analysis, Economy, Energy, Federal Reserve, Inflation, Markets

Commerce Retail Sales Data: Beware Gas Inflation

Category: Consumer Spending, Data Analysis, Economy, Energy, Retail

More on NFP: More Recognition of Disbelief

Category: Data Analysis, Economy, Employment, Psychology

NFP: 88k (and I don’t believe even that)

The Payroll numbers are out, and they are not particularly pretty:

88,000 new jobs were created in April, according to BLS. This is the weakest job gain since November ’04. Cumulative revisions for prior months were to the downside by 26,000.

As expected, losses were in Manufacturing (19k), Retail (26k) and Construction (11k). The  weakness in Construction has been very uted, implying that the full impact of the housing slow down has yet to be fully realized.

Biggest gains were had in Services (116k), Education and Health (53k), Gov’t (25k) Professional (24k) and Leisure/Hospitality (22k).    

Temporary help jobs fell for a 3rd month (January was flat) making 4 consecutive months of no gains. Temp help tends to lead employment gains, and this weakness can be read as a future forecastor of employment.

We don’t pay close attention to the Household survey, (the self reported number is very volatile) but the drop of -468k was an eyebrow raiser.

~~~

Birth Death Adjustment:  A whopping 317k B/D adjustment — that is the single largest "adjustment" on record for any single given month. And despite that giant add, the number was a very soft 88k.

To put this into some context, of those 317k new jobs hypothesized by BLS, 49k of those supposed jobs are in construction. Now what are the odds of that?

While Wall Street celebrates the upcoming recession, let me remind you that this economy requires about 150k new monthly jobs to merely keeep up with population growth.


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Category: Data Analysis, Economy, Employment

NFP: The Return of the Over?

Category: Data Analysis, Economy, Employment