Wednesday, October 21, 2009
FHFA Prices: Will they be revised down?
Tomorrow morning at 10 am est, the FHFA will announce their monthly house price index for August. As I reported earlier, their headline growth rate has been biased up by 0.22% on average. Last month, the FHFA reported that house prices increased 0.3% from June to July. If the bias holds true, then we can expect that the August report will include a revision to the July growth, revising the growth down from 0.3% to something between 0.0% and and 0.1%. I'll report back tomorrow with their release.
Monday, October 12, 2009
Monthly FHFA House Prices are Irrationally Exuberent: Headline Growth Rate Overstates Year-to-date Growth by 2.4%
On September 22nd, the Federal Housing Finance Agency (FHFA) released the July 2009 monthly housing price index with the headline “U.S. Monthly House Price Index Estimates 0.3 percent price increase from June to July.” Such headlines are fueling optimism that the housing market and the economy are turning a corner. However, in the text of the announcement we learned that the previously reported increase of 0.5% from May to June was revised down to 0.1%. Combining the two effects, house prices actually fell 0.1% relative to what was previously reported. The downward revision is not new for the FHFA monthly price index. In fact, if you only read the headline monthly growth rates, you would be under the impression that house prices have risen 2.9% so far this year through July. In fact, in the latest report, house prices had only risen 0.5%. In other words, the headline monthly house price growth gives the impression that house prices have grown 2.4% more this year than they actually have.
The FHFA monthly house price index is new, only having been reported for 20 months. In the FHFA’s original analysis of the potential revisions to their monthly index (reported in the second quarter 2007 release) they stated the initial monthly estimate `would not be reliable’ and did not bother to even report the magnitude of the revisions in their analysis. This unreliable estimate is now the headline of their monthly release. We should not overly criticize the FHFA. The initial monthly index does provide information, explaining roughly 84% of the movements in house prices (in an R-squared sense).
To put the revisions in context, suppose instead that the FHFA was a stock broker handling your million dollar portfolio, and he called you up to tell you the news on your portfolio for July. The conversation could have played out like this:
BROKER: Great news, your portfolio is up 0.3% June to July.
YOU: Great, combined with the 0.5% from May to June, I’ve earned $8,000 the past two months. Maybe I’ll start thinking about getting the deck redone on my house.
BROKER: Yes, about that 0.5%, we re-estimated the increase from May to June to be only 0.1%, so that you actually have only earned $4,000 the last two months. Sorry.
I think most people with a million dollar portfolio would not like to frequently have such conversations with their stock broker. However, for the past twenty months that the FHFA (formerly OFHEO) has been reporting the monthly house price index, the FHFA has been regularly having just such conversations with Americans regarding their houses.
I do research using the quarterly house price index from FHFA. I know that this index states that house prices are down for the year, but it seemed to me that the monthly index had been reporting prices increases from month to month. I went back and checked the headline growth rates, here they are, stating the date reported along with the relevant period for the index:
If you add up all of the growth rates, you arrive at a year-to-date growth of 2.9%. In fact, prices have only rise 0.5%. Furthermore, the 0.5% is most likely overstated as the 0.3% reported from June to July is likely to be revised down. Figure one plots the perceived series for house prices relative to December 2008 if one accepts the headline growth rates as the truth, showing an increase of 2.9%. Figure one also reports the current path for house prices relative to December 2008. Clearly the headline growth rate overstates the actual growth. So far, the overstatement has been 2.4% for 2009.
To put the FHFA’s revisions back into the context of a stock broker managing a million dollar portfolio, if you just looked at the headline growth (maybe in the subject line of a monthly e-mail) you would think that you had earned $29,000 so far this year. You could be thinking about making a large transaction such as renovating a bathroom. However, when you actually looked at your most recent statement, you’d see that you were in fact only up $5,000 so far this year.
The FHFA only started reporting the monthly house price index on February 26, 2008 as part of the report for the 4th quarter of 2007, giving us an observation for December 2007. Since then, we have received 20 observations in total (including Dec 07). Figure two plots the initial estimated price growth along with the current estimate for price growth. There is a clear bias down in the revision. Figure three plots the error in the initial estimate, given by the difference between the initial and the current. Once again there is a clear bias in the revision. Not including the latest observation, the initial estimate overstates the growth rate of house prices by 0.22% on average. This amounts to an annual overstatement of 2.68%.
Before the FHFA started reporting the monthly price index, in their Second Quarter 2007 report, released on August 30 2008, they performed an analysis of revisions. In their analysis they state (see page 11 of the report):
“A primary concern with the construction of monthly price indexes is that revisions will tend to be large. …the most recent monthly price measures would seem to be particularly susceptible to later revision. A June index estimate and the corresponding May-June appreciation rate estimate would be prone to the greatest revision, and a review of the evidence suggests that the estimates would not be reliable.”
To analyze the revisions, they compare their estimate in the second quarter 2007 release with an estimate only using date through the first quarter of 2007. When they do this analysis they do not show the error for March 2007! They leave it out, stating “the line only extends through February 2007 because the data submission only included data through March, and—as indicated above—the index point for the latest month (March) is not deemed to be reliable.”
In other words, from their analysis they deemed the first estimate unreliable and not worth even making an analysis of the size of the revisions. This estimate that `would not be reliable’ is the estimate that they currently report in their monthly release. But not only do they report it, they make it their headline!
Before we overly criticize the FHFA, they have put out many warnings in the text of their announcements. When the monthly house price index was first released as part of the fourth quarter 2007 report (release on Feb. 26, 2008) they warned “index users should recognize that, while OFHEO’s initial review suggests that revisions may be reasonably small, this is no guarantee that future revisions cannot be significant.” They also made a warning for the January 2009 report—which ended up being the largest revision to date—stating that due to a low sample size that “the estimation imprecision associated with the January estimate is relatively large and subsequent revisions … could be significant.”
The initial monthly estimate does provide information. As the then OFHEO director James B. Lockhart stated in the release with the first monthly index “Given the recent turmoil in the housing markets we thought it would be helpful to provide a greater amount of information about price trends.” The FHFA has succeeded along this dimension. Inspection of figure 2 shows that, although there is a bias in the initial estimate, it does provide information about the final estimate. The R-squared of the fit of initial to the final (through June 2009) is 0.84. Therefore, the initial does provide more information about the price trends in the housing market.
Last, there have only been 20 observations of the initial monthly estimate. In addition, theses twenty observations have covered a period of unprecedented falling house prices and very low level of sales, especially considering that the FHFA’s data only starts in 1991. With such a small sample over observations that are so unprecedented, it is difficult to say definitively that the initial estimated is biased. Furthermore, large revisions consistently in one direction are not surprising.
The main problem with the overstatement in the initial monthly estimate is that the FHFA is using the initial estimate as their headline. Given that the FHFA stated in their own analysis that this estimate ‘would not be reliable’, they may want to think about not using this observation as their headline. Instead they could go with the change in the year-over-year or use a more descriptive headline like they use for the quarterly report.
The FHFA monthly house price index is new, only having been reported for 20 months. In the FHFA’s original analysis of the potential revisions to their monthly index (reported in the second quarter 2007 release) they stated the initial monthly estimate `would not be reliable’ and did not bother to even report the magnitude of the revisions in their analysis. This unreliable estimate is now the headline of their monthly release. We should not overly criticize the FHFA. The initial monthly index does provide information, explaining roughly 84% of the movements in house prices (in an R-squared sense).
To put the revisions in context, suppose instead that the FHFA was a stock broker handling your million dollar portfolio, and he called you up to tell you the news on your portfolio for July. The conversation could have played out like this:
BROKER: Great news, your portfolio is up 0.3% June to July.
YOU: Great, combined with the 0.5% from May to June, I’ve earned $8,000 the past two months. Maybe I’ll start thinking about getting the deck redone on my house.
BROKER: Yes, about that 0.5%, we re-estimated the increase from May to June to be only 0.1%, so that you actually have only earned $4,000 the last two months. Sorry.
I think most people with a million dollar portfolio would not like to frequently have such conversations with their stock broker. However, for the past twenty months that the FHFA (formerly OFHEO) has been reporting the monthly house price index, the FHFA has been regularly having just such conversations with Americans regarding their houses.
I do research using the quarterly house price index from FHFA. I know that this index states that house prices are down for the year, but it seemed to me that the monthly index had been reporting prices increases from month to month. I went back and checked the headline growth rates, here they are, stating the date reported along with the relevant period for the index:
- March 24: “1.7% increase from December to January”
- April 22: “0.7% increase from January to February”
- May 27: no headline, part of quarterly report. Reported change from February to March is 1.1% decrease
- June 23: “0.1% decline from March to April”
- July 22: “0.9% increase from April to May”
- August 25: no headline, part of quarterly report, in the text the FHFA states that the “monthly index for June rose 0.5%”
- September 22: “0.3% increase from June to July”
If you add up all of the growth rates, you arrive at a year-to-date growth of 2.9%. In fact, prices have only rise 0.5%. Furthermore, the 0.5% is most likely overstated as the 0.3% reported from June to July is likely to be revised down. Figure one plots the perceived series for house prices relative to December 2008 if one accepts the headline growth rates as the truth, showing an increase of 2.9%. Figure one also reports the current path for house prices relative to December 2008. Clearly the headline growth rate overstates the actual growth. So far, the overstatement has been 2.4% for 2009.
To put the FHFA’s revisions back into the context of a stock broker managing a million dollar portfolio, if you just looked at the headline growth (maybe in the subject line of a monthly e-mail) you would think that you had earned $29,000 so far this year. You could be thinking about making a large transaction such as renovating a bathroom. However, when you actually looked at your most recent statement, you’d see that you were in fact only up $5,000 so far this year.
The FHFA only started reporting the monthly house price index on February 26, 2008 as part of the report for the 4th quarter of 2007, giving us an observation for December 2007. Since then, we have received 20 observations in total (including Dec 07). Figure two plots the initial estimated price growth along with the current estimate for price growth. There is a clear bias down in the revision. Figure three plots the error in the initial estimate, given by the difference between the initial and the current. Once again there is a clear bias in the revision. Not including the latest observation, the initial estimate overstates the growth rate of house prices by 0.22% on average. This amounts to an annual overstatement of 2.68%.
Before the FHFA started reporting the monthly price index, in their Second Quarter 2007 report, released on August 30 2008, they performed an analysis of revisions. In their analysis they state (see page 11 of the report):
“A primary concern with the construction of monthly price indexes is that revisions will tend to be large. …the most recent monthly price measures would seem to be particularly susceptible to later revision. A June index estimate and the corresponding May-June appreciation rate estimate would be prone to the greatest revision, and a review of the evidence suggests that the estimates would not be reliable.”
To analyze the revisions, they compare their estimate in the second quarter 2007 release with an estimate only using date through the first quarter of 2007. When they do this analysis they do not show the error for March 2007! They leave it out, stating “the line only extends through February 2007 because the data submission only included data through March, and—as indicated above—the index point for the latest month (March) is not deemed to be reliable.”
In other words, from their analysis they deemed the first estimate unreliable and not worth even making an analysis of the size of the revisions. This estimate that `would not be reliable’ is the estimate that they currently report in their monthly release. But not only do they report it, they make it their headline!
Before we overly criticize the FHFA, they have put out many warnings in the text of their announcements. When the monthly house price index was first released as part of the fourth quarter 2007 report (release on Feb. 26, 2008) they warned “index users should recognize that, while OFHEO’s initial review suggests that revisions may be reasonably small, this is no guarantee that future revisions cannot be significant.” They also made a warning for the January 2009 report—which ended up being the largest revision to date—stating that due to a low sample size that “the estimation imprecision associated with the January estimate is relatively large and subsequent revisions … could be significant.”
The initial monthly estimate does provide information. As the then OFHEO director James B. Lockhart stated in the release with the first monthly index “Given the recent turmoil in the housing markets we thought it would be helpful to provide a greater amount of information about price trends.” The FHFA has succeeded along this dimension. Inspection of figure 2 shows that, although there is a bias in the initial estimate, it does provide information about the final estimate. The R-squared of the fit of initial to the final (through June 2009) is 0.84. Therefore, the initial does provide more information about the price trends in the housing market.
Last, there have only been 20 observations of the initial monthly estimate. In addition, theses twenty observations have covered a period of unprecedented falling house prices and very low level of sales, especially considering that the FHFA’s data only starts in 1991. With such a small sample over observations that are so unprecedented, it is difficult to say definitively that the initial estimated is biased. Furthermore, large revisions consistently in one direction are not surprising.
The main problem with the overstatement in the initial monthly estimate is that the FHFA is using the initial estimate as their headline. Given that the FHFA stated in their own analysis that this estimate ‘would not be reliable’, they may want to think about not using this observation as their headline. Instead they could go with the change in the year-over-year or use a more descriptive headline like they use for the quarterly report.
Tuesday, August 11, 2009
Another Article About Falling Rents
Marketwatch has an article providing anecdotal evidence that the high rental vacancy rates are putting downward pressure on rents:
Why you should ask for lower rent
As I have been saying, the downward pressure on rental rates will last for sometime, keeping downward pressure on all nominal prices.
Why you should ask for lower rent
As I have been saying, the downward pressure on rental rates will last for sometime, keeping downward pressure on all nominal prices.
Wednesday, August 5, 2009
Beveridge Curve and New Census Data: Owner-Occupied Market near Equilibrium, Rental Market Not
Recently, the census bureau released its latest figures on the housing stock, now updated to the second quarter of 2009. Interestingly, the vacancy rate for the owner-occupied market fell to 2.5% from 2.8%, but it rose to 10.7% in the rental market, a 40 year high. To shed some more light on the new census data, below, I redo the analysis in my "Beveridge Curve" paper which provides a quantitative measure of oversupply, or disequilibrium in the housing market. The main finding is that the owner-occupied market is almost back to equilibrium, in my opinion, a quite strong observation that the owner-occupied market has reached bottom. However, the overall housing market is still suffering from oversupply, with most of the oversupply residing in the rental market. This further supports what my research has been suggesting: a significant adjustment mechanism for the housing market is the shift of housing from the owner-occupied market to the rental market. I expect rents to continue to fall, putting downward pressure on the CPI. My hunch is that for the next several years multi-unit housing starts will remain depressed while the rental market corrects itself. Read on for the updated analysis.
Figure 1 plots the updated time series for the vacancy rates. In addition to the owner-occupied and rental vacancy rates, I provide a total vacancy rate, which provides the vacancy rate for the overall market, irrespective of ownership. We can see that the total vacancy rate has been flat of late, roughly at the all time high since the data started in 1965, while the owner-occupied rate has fallen and the rental vacancy rate has increased.
The census data also informs us about the rate of household formation, and how the rate of household formation is allocated across renters and owners. Figure 2 plots the rate of household formation for owners, renters, and total households irrespective of tenure status. Due to the noisiness of the data, I use the % increase in households over the past 8 quarters and report the rate of change at an annual frequency. In my opinion figure 2 is one of the most striking pictures of the housing bubble. We see quite clearly the shift in owning starting around 1995, and then the dramatic shift to renting starting around 2005. In fact, the first quarter of 2006 was the first observation where the previous two years had more growth in renters than owners since the last quarter of 1994! Even more striking, for the first time since Census began this series in 1965, the growth rate of owners has been roughly zero for the past two years.
My research suggests that there is a negative relationship between the rate of household formation and the vacancy rate. This is true in the owner-occupied market, the rental market, and the total market irrespective of ownership. I call this relationship the Beveridge Curve in the Housing Market, and it can be thought of as a long-run supply relationship. For a deeper analysis of the Beveridge curve see my earlier posts here and here or read the academic paper.
The most interesting aspect of the research is that the deviations from the Beveridge curve give us an estimate of the magnitude of the disequilibrium in the housing market. I can do this for the owner-occupied market, the rental market, or the total market irrespective of ownership. The result for the owner-occupied market is shown in figure 3, the units are in a % of the total housing stock. We can see quite clearly the oversupply that resulted from the bubble, peaking at 0.49% of the total housing stock in the fourth quarter of 2006. However, the market has been quickly correcting itself, now standing at 0.10% of the total housing stock. The correction in the owner-occupied market stems from two adjustments: (1) the growth rate of owners has fallen, now being consistent with the high vacancy rate; and (2) the number of units in the owner-occupied market has been falling, due to less construction and a shift of units to the rental market. I expect that these trends are still continuing, so that sometime in the next year the owner-occupied market will actually shift to a state of undersupply.
However, the picture is much different in the total housing market. Figure 4 shows the oversupply in all three markets: owner-occupied, rental, and total market irrespective of ownership status (the rental market reported here is simply the residual between the total market and the owner-occupied market—the independent estimate of the rental market implies an even larger oversupply in the rental market). Here, we can see that the total market still is far from equilibrium, with an oversupply of 0.89% of the total housing stock. However, this is down from the peak of 1.18% in the second quarter of 2006. Therefore, while the owner-occupied market is almost back to equilibrium, the overall market still has a large oversupply. Almost all of the oversupply is showing up in the rental market. Clearly, we are seeing the market respond by shifting resources from the owner-occupied market to the rental market. This will undoubtedly put pressure on rents to fall as has been recently reported. I expect rents to continue to fall for quite some time, putting downward pressure on the CPI.
Punchline: the market is adjusting, which means the owner-occupied market clears while the rental market holds the oversupply. The owner-occupied market has probably already moved back into a state of equilibrium, while the total market will slowly reach equilibrium as the production of primarily multi-unit rentals remains sluggish for several years.
Figure 1 plots the updated time series for the vacancy rates. In addition to the owner-occupied and rental vacancy rates, I provide a total vacancy rate, which provides the vacancy rate for the overall market, irrespective of ownership. We can see that the total vacancy rate has been flat of late, roughly at the all time high since the data started in 1965, while the owner-occupied rate has fallen and the rental vacancy rate has increased.
The census data also informs us about the rate of household formation, and how the rate of household formation is allocated across renters and owners. Figure 2 plots the rate of household formation for owners, renters, and total households irrespective of tenure status. Due to the noisiness of the data, I use the % increase in households over the past 8 quarters and report the rate of change at an annual frequency. In my opinion figure 2 is one of the most striking pictures of the housing bubble. We see quite clearly the shift in owning starting around 1995, and then the dramatic shift to renting starting around 2005. In fact, the first quarter of 2006 was the first observation where the previous two years had more growth in renters than owners since the last quarter of 1994! Even more striking, for the first time since Census began this series in 1965, the growth rate of owners has been roughly zero for the past two years.
My research suggests that there is a negative relationship between the rate of household formation and the vacancy rate. This is true in the owner-occupied market, the rental market, and the total market irrespective of ownership. I call this relationship the Beveridge Curve in the Housing Market, and it can be thought of as a long-run supply relationship. For a deeper analysis of the Beveridge curve see my earlier posts here and here or read the academic paper.
The most interesting aspect of the research is that the deviations from the Beveridge curve give us an estimate of the magnitude of the disequilibrium in the housing market. I can do this for the owner-occupied market, the rental market, or the total market irrespective of ownership. The result for the owner-occupied market is shown in figure 3, the units are in a % of the total housing stock. We can see quite clearly the oversupply that resulted from the bubble, peaking at 0.49% of the total housing stock in the fourth quarter of 2006. However, the market has been quickly correcting itself, now standing at 0.10% of the total housing stock. The correction in the owner-occupied market stems from two adjustments: (1) the growth rate of owners has fallen, now being consistent with the high vacancy rate; and (2) the number of units in the owner-occupied market has been falling, due to less construction and a shift of units to the rental market. I expect that these trends are still continuing, so that sometime in the next year the owner-occupied market will actually shift to a state of undersupply.
However, the picture is much different in the total housing market. Figure 4 shows the oversupply in all three markets: owner-occupied, rental, and total market irrespective of ownership status (the rental market reported here is simply the residual between the total market and the owner-occupied market—the independent estimate of the rental market implies an even larger oversupply in the rental market). Here, we can see that the total market still is far from equilibrium, with an oversupply of 0.89% of the total housing stock. However, this is down from the peak of 1.18% in the second quarter of 2006. Therefore, while the owner-occupied market is almost back to equilibrium, the overall market still has a large oversupply. Almost all of the oversupply is showing up in the rental market. Clearly, we are seeing the market respond by shifting resources from the owner-occupied market to the rental market. This will undoubtedly put pressure on rents to fall as has been recently reported. I expect rents to continue to fall for quite some time, putting downward pressure on the CPI.
Punchline: the market is adjusting, which means the owner-occupied market clears while the rental market holds the oversupply. The owner-occupied market has probably already moved back into a state of equilibrium, while the total market will slowly reach equilibrium as the production of primarily multi-unit rentals remains sluggish for several years.
Monday, June 29, 2009
More on Beveridge Curve: Disequilibrium and Oversupply in the Housing Market
Earlier I posted on some research that I was working on about a Beveridge curve in the housing market (the work that motivates the name of this blog). The working paper version of the paper is now finished and available for downloading.
The main results of the paper:
The primary change from the earlier results is that instead of doing the fairly ad-hoc HP filter, I have gone ahead and estimated the model using biannual data. In my opinion this gives a better estimation. In addition to the new estimation I have also found some interesting results relating oversupply of houses to house prices. I will go over those results in my next entry, for now I give an overview of my previous results under the new estimation.
The main idea of the Beveridge curve is that it represents the long-run equilibrium in the housing market. The Beveridge curve has its origins in labour economics, where Lord Beveridge found a negative relationship between the unemployment rate and the amount of job vacancies. For an example, see Rob Shimer's website. In the housing market I have found a negative relationship between the rate of household formation and the residential vacancy rate. I deem this negative relationship the Beveridge curve in the housing market. The Beveridge curve relationship exists in the owner-occupied market, the rental market, and the overall market irrsepective of ownership. Figure 4 from the paper, shown here below, shows the relationship for the overall house market. There is a clear and statistically significant negative relationship and the R-squared from a linear regression is 0.626.
As I stated, the curve represents a long-run relationship, so that short-run deviations (two to four years) represent periods of disequilibrium in the housing market, these are periods of under or over supply, see figure 7 below.
The next figure shows the estimated time-series of oversupply for the total housing market irrespective of home-ownership. The metric of oversupply is in a % of the total housing stock. Here we clearly see three periods of oversupply since the start of the data in 1968: (1) the 1974 crisis; (2) the mid to late 1980s housing boom; and (3) the current crisis. The oversupply in the current crisis is similar in magnitude to the 1974 crisis, with both having an oversupply of just under 1% of the total housing stock.
However, the rate of household formation is much lower now, so that it may take much longer to work off the oversupply. The next figure plots the estimate of oversupply in years of oversupply. This is the oversupply in years of household formation. For instance, if the rate of household formation was 1% and the oversupply of the housing stock was 1%, then it would take one year of no housing production for the oversupply to disappear. Using this metric, the amount of oversupply is staggering, being about one year of supply in 2007-2008 compared to under 0.3 years in the 1974 crisis.
One point that I cannot stress enough is that what we are currently facing is a huge oversupply of housing, irrespective of whether it is rental or owner-occupied housing. As I stated in the earlier post there is actually more oversupply in the rental market. To see this, below is figure 12 from the paper. The metric is years of oversupply in terms of the total rate of household formation, so that we are comparing apples to apples. There are several striking features in this figure:
The main results of the paper:
- The Beveridge Curve represents a long-run supply condition
- Short run deviations represent periods of disequilibrium, either over or under supply
- Using a years of oversupply metric, the observation of 2007-2008 was an all-time high of 0.995 years of oversupply, more than three times the previous peak of 0.285 in 1973-1974.
- Generally, oversupply is a phenomena in the rental market
- Oversupply in the rental market is twice as volatile as in the owner-occupied market
- Oversupply first shows up in the rental market
- Oversupply in the owner-occupied market is related to house prices, reinforcing the idea that short run deviations in house prices from fundamentals (such as bubbles) can lead to periods of oversupply
The primary change from the earlier results is that instead of doing the fairly ad-hoc HP filter, I have gone ahead and estimated the model using biannual data. In my opinion this gives a better estimation. In addition to the new estimation I have also found some interesting results relating oversupply of houses to house prices. I will go over those results in my next entry, for now I give an overview of my previous results under the new estimation.
The main idea of the Beveridge curve is that it represents the long-run equilibrium in the housing market. The Beveridge curve has its origins in labour economics, where Lord Beveridge found a negative relationship between the unemployment rate and the amount of job vacancies. For an example, see Rob Shimer's website. In the housing market I have found a negative relationship between the rate of household formation and the residential vacancy rate. I deem this negative relationship the Beveridge curve in the housing market. The Beveridge curve relationship exists in the owner-occupied market, the rental market, and the overall market irrsepective of ownership. Figure 4 from the paper, shown here below, shows the relationship for the overall house market. There is a clear and statistically significant negative relationship and the R-squared from a linear regression is 0.626.
As I stated, the curve represents a long-run relationship, so that short-run deviations (two to four years) represent periods of disequilibrium in the housing market, these are periods of under or over supply, see figure 7 below.
The next figure shows the estimated time-series of oversupply for the total housing market irrespective of home-ownership. The metric of oversupply is in a % of the total housing stock. Here we clearly see three periods of oversupply since the start of the data in 1968: (1) the 1974 crisis; (2) the mid to late 1980s housing boom; and (3) the current crisis. The oversupply in the current crisis is similar in magnitude to the 1974 crisis, with both having an oversupply of just under 1% of the total housing stock.
However, the rate of household formation is much lower now, so that it may take much longer to work off the oversupply. The next figure plots the estimate of oversupply in years of oversupply. This is the oversupply in years of household formation. For instance, if the rate of household formation was 1% and the oversupply of the housing stock was 1%, then it would take one year of no housing production for the oversupply to disappear. Using this metric, the amount of oversupply is staggering, being about one year of supply in 2007-2008 compared to under 0.3 years in the 1974 crisis.
One point that I cannot stress enough is that what we are currently facing is a huge oversupply of housing, irrespective of whether it is rental or owner-occupied housing. As I stated in the earlier post there is actually more oversupply in the rental market. To see this, below is figure 12 from the paper. The metric is years of oversupply in terms of the total rate of household formation, so that we are comparing apples to apples. There are several striking features in this figure:
- Generally, oversupply is a phenomena in the rental market
- Oversupply in the rental market is twice as volatile as in the owner-occupied market
- Oversupply first shows up in the rental market
Friday, June 26, 2009
Distressed Sales and House Prices
In my last entry I argued that a shock was causing existing home sales to rise relative to new home sales, and that this same shock was causing house prices to fall more than would be suggested by the level of existing home sales. This `shock' is more than likely a supply side shock: quantity up, prices down, Econ 101 at work. A question is how much of this is being driven by distressed sales where the house is being sold because the current owner has stopped paying the mortgage.
Andrew Leventis, a researcher at the Federal Housing Finance Agency has attemped to answer this question is a recent working paper: "The Impact of Distressed Sales on Repeat-Transactions House Price Indexes".
In the paper, Leventis uses transactions data from California and breaks down transactions into distressed and non-distressed. A transaction is distressed if a Notice of Default was filed on the property up to a year before the transaction occurred and no other transactions occurred for the same property between the transaction and the Notice of Default. He performs the analysis for two different groupings of data. The first grouping he calls `Enterprise' data, and this consists of the transactions that would be included for calculating the FHFA House Price Index (HPI). The second grouping is `Recorder' data, which consists of the data that would be used to calculate the Case-Shiller index. His figure one shows that the share of distressed sales has increased from less than 5% before the fourth quarter of 2006, and has been rising steadily ever since, now over 45% for the first quarter of 2009. The rise in distressed sales is very similar to the gap that has appeared between new and existing home sales.
The main question of the paper is "How much are these distressed sales driving down house prices?" To paraphrase Leventis, we can breakdown the effect of distressed sales on house prices into two categories:
Therefore, by the end of 2008, distressed sales were selling at a 20% discount and made up roughly 45% of sales. Relative to the peak in the housing bubble in 2006 (when the discount was essentially zero), if this sales pattern would maintain itself for a year, it would imply that the house price index is being pushed down an extra 9% due to the direct effect from distressed sales. However, the total effect so far has been smaller. His figure 2 shows the effect of the distressed sales on year-over-year price growth for the `Enterprise' data. The figure contains two plots: one showing price growth for the entire sample, another with the distressed sales removed. The effects are fairly small. The cumulative effect of the distressed sales is estimated to drive down prices an extra 5.3% from the peak, for a fall of 41.3% relative to only 36.0% when the distressed sales are excluded. The effect on the `Recorder' data is smaller, implying an extra house price fall of 1.9% from 44.8% to 46.7% (see his figure 3, not shown here).
To summarize, the divergence between new and existing homes seems related to the surge in distressed sales. The work by Leventis suggests that the direct effect of the distressed sales on the reported house price indexes is most likely small relative to the total decline we've seen in house prices. What we do not know is whether the distressed sales are directly responsible for the fall in house prices and the increase in existing sales relative to new sales, or if the distressed sales are simply the result of the large supply of housing, which is then responsible for distressed sales, housing price falls, and an increase in existing relative to new sales. My viewpoint is that we are just seeing the effects of supply at work.
Andrew Leventis, a researcher at the Federal Housing Finance Agency has attemped to answer this question is a recent working paper: "The Impact of Distressed Sales on Repeat-Transactions House Price Indexes".
In the paper, Leventis uses transactions data from California and breaks down transactions into distressed and non-distressed. A transaction is distressed if a Notice of Default was filed on the property up to a year before the transaction occurred and no other transactions occurred for the same property between the transaction and the Notice of Default. He performs the analysis for two different groupings of data. The first grouping he calls `Enterprise' data, and this consists of the transactions that would be included for calculating the FHFA House Price Index (HPI). The second grouping is `Recorder' data, which consists of the data that would be used to calculate the Case-Shiller index. His figure one shows that the share of distressed sales has increased from less than 5% before the fourth quarter of 2006, and has been rising steadily ever since, now over 45% for the first quarter of 2009. The rise in distressed sales is very similar to the gap that has appeared between new and existing home sales.
The main question of the paper is "How much are these distressed sales driving down house prices?" To paraphrase Leventis, we can breakdown the effect of distressed sales on house prices into two categories:- Direct Effect: distressed houses sell at a discount, therefore, as the share of distressed sales in the sample increases, then the reported house price index will fall.
- Indirect Effects: the more distressed sales there are, the harder it is for a non-distressed seller to sell a house, lowering the prices for all houses.
Therefore, by the end of 2008, distressed sales were selling at a 20% discount and made up roughly 45% of sales. Relative to the peak in the housing bubble in 2006 (when the discount was essentially zero), if this sales pattern would maintain itself for a year, it would imply that the house price index is being pushed down an extra 9% due to the direct effect from distressed sales. However, the total effect so far has been smaller. His figure 2 shows the effect of the distressed sales on year-over-year price growth for the `Enterprise' data. The figure contains two plots: one showing price growth for the entire sample, another with the distressed sales removed. The effects are fairly small. The cumulative effect of the distressed sales is estimated to drive down prices an extra 5.3% from the peak, for a fall of 41.3% relative to only 36.0% when the distressed sales are excluded. The effect on the `Recorder' data is smaller, implying an extra house price fall of 1.9% from 44.8% to 46.7% (see his figure 3, not shown here).
To summarize, the divergence between new and existing homes seems related to the surge in distressed sales. The work by Leventis suggests that the direct effect of the distressed sales on the reported house price indexes is most likely small relative to the total decline we've seen in house prices. What we do not know is whether the distressed sales are directly responsible for the fall in house prices and the increase in existing sales relative to new sales, or if the distressed sales are simply the result of the large supply of housing, which is then responsible for distressed sales, housing price falls, and an increase in existing relative to new sales. My viewpoint is that we are just seeing the effects of supply at work.
Wednesday, June 24, 2009
House Prices and New versus Existing Homes Sales
This week we have received the May data on existing home sales (from the National Association of Realtors) and new home sales (from Census). Existing home sales have been flat or rising a bit for 2009. Such stabilization in the market for existing homes has been a sign to many observers that we may be reaching the bottom in house prices. However, at the same time new home sales have continued to fall relative to their 2008 levels. As people have noted (see CalculatedRisk), there is now a gap between new home sales and existing home sales that did not exist before 2006. As I show here, whatever is driving a gap between new and existing homes sales is also driving a gap between the relationship of existing home sales and real house price growth. The evidence suggests that a supply side shock is driving up existing homes sales relative to new home sales and at the same time driving down prices, just as standard econ 101 predicts. Furthermore, price growth is related to new home sales, not existing home sales. The punchline: if we are seeking stability in house prices we should look at new home sales, not existing sales.
Figure 1 plots annual single family existing homes sales and single family new homes sales as a percentage of the total housing stock (the total housing stock is taken from Census). We see that new home sales average about 1% of the total housing stock, while existing home sales average roughly 4%. To get a feel for how the two series move together, figure 2 plots the percentage deviation for each series from its mean from 1975-2008. We see clearly that from 1975 to 2006 (the solid lines) that new home sales and existing homes sales move around together, with a correlation of 0.944 over the the time period up to 2006. However, as shown by the dashed lines, a gap has developed post 2006, resulting in the correlation for the sample from 1975-2008 falling to 0.876. There seems to be some type of a shock that is driving existing homes sale up relative to new homes sales.
Turning to prices, figure 3 graphs expected annual real house price growth next to existing homes sales. Expected real house price growth is the FHFA (formerly OFHEO) house price index, made real by the rate of expected inflation from the Philly Fed survey of forecasters. The existing sales series is the same as in figure 2. Once again, we can see clearly that from 1975 to 2006 both series move around together, with a correlation of 0.921. However, post 2006, a gap develops just like the gap between new home sales and existing home sales. Using the whole sample up to 2008 the correlation falls to 0.812.
Both of the gaps suggest a shock hitting the housing market. To put it more clearly, figure 4 plots both a `price shock' and and `existing sales shock'. The price shock is the shock to price growth that is not explained by existing sales in figure 3. (This is actually the error term from a linear regression of price growth on existing homes sales relative to the housing stock). The existing sales shock is the shock to existing homes relative to new home sales, the difference in figure 2. (the existing sales shock has been normalized to be on the same graph as the price shock). From 1975 to 2006 these two shocks are essentially unrelated. However, in 2007 and 2008 both shocks are sizeable, moving in opposite directions. What we have is a classic supply side shock: quantities rising and prices falling. The glut of vacant houses on the market are doing what they do: drive down prices, and drive up sales.
The implication is that the supply shock is breaking down the standard relationship between sales and price growth. Existing home sales is not the place to be looking for stability in house prices. Instead, figure 5 plots new home sales relative to house price growth. Here we can see that new home sales are related to house price growth, and this relationship has maintained itself through the crisis. The correlation from 1975-2006 is 0.881, while for the whole sample from 1975 to 2008 it is 0.899. Therefore, if we are looking for price stability, we should look to new home sales, not existing home sales. The supply side shock that is hurting prices and raising existing home sales causes new home sales to fall. To stress the point a bit more, the stability in the housing market that we want for economic recovery is stable prices and new home construction. Stable prices are associated with new home sales not existing home sales. The current stability in existing home sales is most likely just the effects of a supply side shock that is driving down both prices and new home sales. In my next entry I will use search theory to guide us in understanding this behavior in the housing market.
Figure 1 plots annual single family existing homes sales and single family new homes sales as a percentage of the total housing stock (the total housing stock is taken from Census). We see that new home sales average about 1% of the total housing stock, while existing home sales average roughly 4%. To get a feel for how the two series move together, figure 2 plots the percentage deviation for each series from its mean from 1975-2008. We see clearly that from 1975 to 2006 (the solid lines) that new home sales and existing homes sales move around together, with a correlation of 0.944 over the the time period up to 2006. However, as shown by the dashed lines, a gap has developed post 2006, resulting in the correlation for the sample from 1975-2008 falling to 0.876. There seems to be some type of a shock that is driving existing homes sale up relative to new homes sales.
Turning to prices, figure 3 graphs expected annual real house price growth next to existing homes sales. Expected real house price growth is the FHFA (formerly OFHEO) house price index, made real by the rate of expected inflation from the Philly Fed survey of forecasters. The existing sales series is the same as in figure 2. Once again, we can see clearly that from 1975 to 2006 both series move around together, with a correlation of 0.921. However, post 2006, a gap develops just like the gap between new home sales and existing home sales. Using the whole sample up to 2008 the correlation falls to 0.812.
Both of the gaps suggest a shock hitting the housing market. To put it more clearly, figure 4 plots both a `price shock' and and `existing sales shock'. The price shock is the shock to price growth that is not explained by existing sales in figure 3. (This is actually the error term from a linear regression of price growth on existing homes sales relative to the housing stock). The existing sales shock is the shock to existing homes relative to new home sales, the difference in figure 2. (the existing sales shock has been normalized to be on the same graph as the price shock). From 1975 to 2006 these two shocks are essentially unrelated. However, in 2007 and 2008 both shocks are sizeable, moving in opposite directions. What we have is a classic supply side shock: quantities rising and prices falling. The glut of vacant houses on the market are doing what they do: drive down prices, and drive up sales.
The implication is that the supply shock is breaking down the standard relationship between sales and price growth. Existing home sales is not the place to be looking for stability in house prices. Instead, figure 5 plots new home sales relative to house price growth. Here we can see that new home sales are related to house price growth, and this relationship has maintained itself through the crisis. The correlation from 1975-2006 is 0.881, while for the whole sample from 1975 to 2008 it is 0.899. Therefore, if we are looking for price stability, we should look to new home sales, not existing home sales. The supply side shock that is hurting prices and raising existing home sales causes new home sales to fall. To stress the point a bit more, the stability in the housing market that we want for economic recovery is stable prices and new home construction. Stable prices are associated with new home sales not existing home sales. The current stability in existing home sales is most likely just the effects of a supply side shock that is driving down both prices and new home sales. In my next entry I will use search theory to guide us in understanding this behavior in the housing market.
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