Monday, May 30, 2011

Is California's Housing Problem that it has too Many Houses?


Below is a chart of residential vacancy rate by state from the 2010 US Census.

California has the second lowest vacancy rate among the 50 states and DC.  California builders may have built the wrong kind of housing in the wrong places, but overall, they did not build too many houses. 

Note that Florida and Arizona have very high rates, but their rates are always high, because so much of their housing stock is seasonal--I suspect vacation homes drive a lot of what is happening in Maine, Vermont and Alaska as well.  Nevada has had the largest increase in vacancy over the past 20 years, rising from about 10 percent to 14 percent. 

Are commercial property values rising or falling?

This might seem like a simple question.  But it is not.

The Moodys/REAL Commercial Property Price Index (CPPI), produced at MIT, says they are still falling:

Green Street's Commerical Property Price Index says they are rising:
Which one is correct matters.  If Green Street is right, and prices are only 12.6 percent off peak, then commercial properties by-and-large have equity (loan-to-value ratios rarely exceeded 80 percent on commericial properties).  If MIT is right, we are still in deep trouble.
Both sources do a good job explaining their methods.  For MIT:
The Moodys/REAL commercial property index (CPPI) is a periodic same-property round-trip investment price change index of the U.S. commercial investment property market based on data from MIT Center for Real Estate industry partner Real Capital Analytics, Inc (RCA). The methodology for index construction has been developed by the MIT/CRE through a project undertaken in cooperation with a consortium of firms including RCA and Real Estate Analytics, LLC (REAL). The index has been developed with the objective of supporting the trading of commercial property price derivatives. The index is designed to track same-property realized round-trip price changes based purely on the documented prices in completed, contemporary property transactions. The index uses no appraisal valuations. The methodology employed to construct the index is a repeat-sales regression (RSR), as described in detail in Geltner & Pollakowski (2007). The data source for the index is described in detail in a white paper available from RCA.

The set of indices developed so far includes a national all-property index at the monthly frequency, national quarterly indices for each of the four major property type sectors (office, apartment, industrial, retail), selected annual-frequency indices for specific property sectors in specific metropolitan areas, and primary markets quarterly indices for the top 10 metropolitan areas in the major property types. The annual indices are produced in four versions, beginning in January, April, July, and October of each year. These are respectively named the calendar year (CY) index, the fiscal year ending March (FYM) index, the fiscal year ending June (FYJ) index and the fiscal year ending September (FYS) index.

The RCA Database

The commercial property index is based on the RCA database which attempts to collect, on a timely basis, price information for every commercial property transaction in the U.S. over $2,500,000 in value. This represents one of the most extensive and intensively documented national databases of commercial property prices ever developed in the U.S.

The Moodys/REAL CPPI and the TBI

The Moodys/REAL CPPI index is a complementary information product to the transaction based index (TBI) also published on the MIT/CRE web site. Both the CPPI and the TBI are based purely on transaction price data. The TBI is based on NCREIF property sales prices data, while the CPPI is based on RCA sales prices data. Thus, the TBI is based on a smaller population of more purely institutionally held properties. The TBI is based on a hedonic regression methodology whereas the CPPI is constructed with a repeat-sales methodology. The TBI is published with history going back to 1984 but only at the quarterly frequency, and only at the national level (for the four major property types), whereas the CPPI includes monthly and annual frequencies and more geographic regional break outs. The CPPI is a variable-liquidity price-change (appreciation return) index, while the TBI includes total return and demand and supply-side indexes.
For Green Street:
Green Street’s Commercial Property Price Index is a time series of unleveraged U.S. commercial property values that captures the prices at which commercial real estate transactions are currently being negotiated and contracted.

Two features that differentiate this index are its timeliness and its ability to capture changes in the aggregate value of the commercial property sector.

• Timeliness: Other indices are based on closed transactions, and therefore convey info about market prices from several months earlier. Also, the Green Street index value for a given month is released within days of monthend, whereas other indices have a sizeable lag. As shown below, the Green Street index spots inflection points earlier than other indices.

• Weighting: This index is weighted by asset value within each property sector, and therefore it provides a gauge of changes in aggregate values. Most other indices are equally weighted.

So the big differences are: (1) MIT looks only at transactions, whereas Green Street looks at current negotiations; (2) MIT's valuation model gives equal weight to all properties, while Green Street's valuation gives greater weight to expensive properties than to cheaper properties; and (3) MIT has a much broader sample, because REITs would rarely buy properties as inexpensive as $2.5 million.

So which index is correct?  It all depends on context.  While I would be a little leary of using "negotiated price" as an indicator of value (as opposed to closed transactions), the timeliness of Green Street's data does give it an advantage.  For REIT's trying to determine strategy, the Green Street index is probably better.  For banks making loans to smaller properties--or for individual investors thinking of buying small office buildings--the MIT index is more relevant. 

Wednesday, May 25, 2011

Mortgage Defaulters can be good credit risks.

Transunion performed a study that shows that households whose only default is on their mortgage are pretty good credit risks. Reuters does a story about it, and I have seen the powerpoint deck on it, but I can't find a link to the powerpoint.

The long story short is that sometimes people stop making payments not because they are deadbeats, but because the economy kicked their legs out from under them. Such people are good prospective credit risks.

Sunday, May 22, 2011

The problem with rubber meeting road

In general, high gas prices are a good thing, in that they partially internalize the externalities of driving. But in the middle of a recess... (ahem, recovery), they create a real problem--the people who can least afford them are hit particularly hard by them. I am glad that at least the payroll tax was cut, but it would have been better for the cut to have been targeted.

Saturday, May 21, 2011

A Plot of Effective Marginal Tax Rates and Per Capita GDP by State

State Taxes and GDP 2

Jared Bernstein recently posted a scatter plot of Federal Marginal Tax Rates and GDP growth, and found no correlation between the two. The graph above depicts the top potential marginal effective tax rate by state as calculated by the Tax Foundation (I will explain their calculation below) against GDP per capita by state. The correlation is actually positive, at about .2. If one removes the "DC effect," the correlation drops to about .19.

The top rate number I use from the calculation is the number produced under the GOP tax plan from late 2010, since they essentially got everything they wanted from the president in their tax deal. State taxes also move fairly slowly, so there is some persistence in the data across time.

I would not use this plot to argue that taxes on the richest cause higher living standards; but it sure is hard to argue that they cause living standards to fall.

Friday, May 20, 2011

A testimonial to homeownership.

I am reading Howard Bryan's The Last Hero: A Life of Henry Aaron.  The first few chapters are especially interesting, as they are about life in Mobile, Alabama in the early 20th century.   

Henry's father, Herbert, did something that few African-Americans did in the American South after Reconstruction: he owned his own home:

For Herbert, ownership meant protecting his family from outside forces that could, at any time, take away what he had... 

Herbert purchased two adjascent lots for fifty-three dollars apiece on Edwards Street and began culling wood.  Herbert collected ship timber from Pinto Island.  Young Henry, all of six years old, collected wood from abandoned buildings.  Some of the wood came from houses that had partially burned down, and some of the original walls of the house still contained deeply discolored streaks, charred from fire.  Herbert construction a six-to-twelve-foot triangular gabled roof above the front door.  He used the smaller, miscellaneous pieces of wood for the inside walls.  The floor was made of yellow pine.  Like most of the houses of the South, the structure itself stood on concrete blocks...

"The only people who owned their houses," Henry would often day, "were rich people, and the Aarons...."

...Herbert fought for his space, but he used non-traditional weapons..."

Monday, May 16, 2011


The word is ugly (can't we come up with something better?), but intriguing.  One can go to a web site, and get a "walk score" for any address in the country.  Stephanie Yates Rauterkus and Norm Miller have a paper that shows that in Birmingham, Alabama, walk scores in the center of town have a mild impact on property values. 

The concept of a "walk score," a metric for how easy it is to not use a car to do things, is fun.  But so far as I can tell, the walk score presented on the web site is somewhat arbitrary; I have no idea how it was calibrated (although they do say "Street Smart Walk Score gives more weight to amenities that are highly correlated with walking. In addition, multiple amenities in each category count towards your score—for example, we count 10 restaurants to reflect the depth of choice that walkable neighborhoods offer.")

What I can say is this: my house in Bethesda received a much lower walk score than my house in Pasadena, and yet I almost never used my car during the week in Bethesda, because I could walk the .85 miles to the Red Line metro stop to get to work, and because for me driving in Washington was a much worse option than driving in LA (believe it or not!).  Both places are comparable in terms to walking to amenities in the evening.

So if we are going to do walk scores, we need to look at how often people in different neighborhoods, well, walk.  I am guessing my USC colleagues Gen Giuliano, Lisa Schweitzer and Peter Gordon, have done some work along these lines, and there seems to be a trove of data at Minnesota.

Sunday, May 15, 2011

Some stuff from Weimer School meetings worth thinking about.

1) Albert Saiz showed how rent is endogenous with respect to interest rates.  At the urban fringe, where land has no value, rent is equal to construction cost multiplied by the interest rate.  This pins down urban rents.  When interest rates fall, so do rents at the fringe.  Nevertheless, land values rise, because people want larger structures (because of falling rent), and so they demand more land.  Consequently, rent-to-value ratios fall as interest rates fall.

2) Ingrid Ellen showed that REO properties produce crime.  The interesting part--they induce violent crime, rather than property crime.  The data set she put together, which used block faces, instead of census blocks, was awesome.

3) Len Lin may have solved why real estate appears to have better Sharpe Ratios than stocks.  If they were really better, one could arbitrage between real estate and stocks.  But because real estate is illiquid--it takes a long time to sell it--one cannot arbitrage it.  When one adjusts formally for illiquidity, the Sharpe Ratio of real estate is the same as stocks.

4) Stephanie Yates Rauterkus presented some promising work that suggested that "walkability" near CBDs enhances value, but elsewhere might not.

It was a really good few days.  I learned a lot of other stuff too.

Friday, May 13, 2011


I was talking to a reporter the other day about policies to write down principal for some home buyers.  He told me that banks objected, saying that it would create moral hazard.  Which is sort of like Newt Gingrich defending the sanctity of marriage.

Thursday, May 05, 2011

Martin Feldstein says raise taxes, but not rates

While figuring out tax incidence-who actually bears the burden of the tax--is difficult, my guess is that his proposal, which would limit all deductions to two percent of adjusted gross income, would raise revenue, simplify the code, reduce deadweight losses (i.e., economic inefficiency), and produce a more progressive tax code.  It is the last of these that I am not sure about, but if we also raised the top rates to their Clinton-era levels, then one gets a more progressive code too.  I have seen no evidence that raising the top marginal rate from 35 to 39 percent would produce substantial deadweight loss.

I think such a proposal would need to be phased in--it would be a shock to lots of different markets, but I like the thinking behind it.  

Monday, May 02, 2011

My own beef with Trump

The Donald gives people the worst possible impression about the real estate business--the business that I study for a living. It is not principally about slapping your name on a gaudy building. It is about building 3 bedroom houses and apartment buildings; it is about building Targets and, yes, Walmarts; it is about managing class-B office buildings in suburbs; it is about distribution centers in Oconomowoc.  It is about providing environments where the bulk of people live, work, shop and build.