Equity Returns and GDP Growth

Part of the secular stagnation story is about demographics.  Real GDP growth has been lower than at any previous time since at least WW II.  But, if we adjust this for labor force growth, we see that real GDP growth is low, but it is within the range of previous periods.

Even so, notice that real GDP growth per worker is currently very low, even though we are in a recovery phase, and it has been near zero twice since the recession.  In the post-WW II era, this has generally been associated with a recession.  Maybe this is related to the Great Moderation.  When real GDP growth per worker was low in the 1970s, quarterly growth whipsawed through recessions and recoveries.  Now, both the top and bottom have been moderated, so we get a slow, grinding recovery with the same level of real GDP growth per worker.

S&P Data from Robert Shiller

It looks to me like, over the long term, returns on equities are related more to real GDP growth per worker than they are to unadjusted real GDP growth.  They certainly are more related to real GDP growth, over the long term, than to nominal GDP growth, even though the zeitgeist currently seems to accept some sort of Austrian business cycle idea that monetary accommodation leads to real stock market gains.  I think this is an error.  The stock market rises when the Fed accommodates because monetary policy has been too tight throughout the current period, so accommodation leads to real growth, and a rising stock market is a secondary effect of real economic growth.

As we see in the second chart, the returns to equities are much more variable than changes in GDP (a 200% ten year return corresponds to average annual GDP growth of around 2%).  This makes it look like there is a reaction of equities to nominal growth, because if nominal accommodation leads to real growth, equity returns will have gains in excess of the real GDP gains.

But, the point here is that, even adjusting for the demographic problem, there is a stagnation problem.  It's not particularly worse than the problem we had in the 1970s, but it is a problem.  GDP growth, adjusted for labor force size, needs to recover if we are going to see better returns to equities over the next decade.  (Total returns to equities have been much worse than they look in the past couple of decades because returning capital through buybacks instead of through dividends creates a side effect of inflating the stock indexes, but it doesn't really change total returns.  So, whenever someone uses an unadjusted stock index, like the S&P 500, without adding in dividends, it will be skewed.  I am probably making a separate error here, because I am comparing S&P returns to GDP, even though corporate revenues have become increasingly global.  That's something to keep in mind.  Maybe adjusting for foreign profit would add a downward trend to the equity returns, and make them look more like the unadjusted GDP growth.)

I'm still not sure if the secular stagnation problem is a demographic problem.  There seems to be a general sin wave pattern of 35 years or so that goes back at least to the early 20th century.  Maybe, this is a shadow of the demographics issue.  Maybe, when baby boomers were crowding into the labor force in the 1970s, they were bringing down productivity because there was an inflow of young, inexperienced workers.  And, today, they are bringing down productivity because low labor force growth today is the result of retiring baby boomers who are leaving the labor force at their peak levels of productivity, taking a lifetime of experience with them.  Maybe, we have another decade or so of this, and when the baby boomer retreat has peaked, growth per worker will naturally begin to rise again.  Buying in after the next recession might be like buying in after WW II or after the 1982 recession.  It's probably more like the post-WW II period, because inflation and nominal bond yields are low, so that there will probably be a period of significant excess returns to equity, like there were in the 1945-1970 time period.

Housing Part 114 - More on Homeownership Rates

In the recent post on homeownership rates by age, Ironman helpfully pointed me to some archived Census information before 1994.  I haven't been able to find age-specific homeownership rates in the old pdf files, but I did realize that there is digital data going back to 1982.

This confirms that there was a similar rise in homeownership among the younger age groups in the late 1970s and early 1980s.  I did find one other source with some decadal age data, and it suggests that homeownership rates in 1970 were slightly lower than 1980 for both young and old households.

It looks like homeownership has been pushed up slightly because of a permanent increase in ownership rates for households over 65 years old from 1982 to around 2000, where it leveled off at a rate similar to 55 to 64 year olds.

From 1982 to 2005, homeownership rates for 45 to 64 year olds were fairly stable at high levels.  Note that there was very little change in ownership among these groups during the boom, but ownership has fallen by about 5% for both of those groups since then.  This is a story of a bust, not a bubble, folks.

In 1982, homeownership for 35-44 year olds was higher than it was at its peak in 2005.  The rate for households younger than 35 was also near the 2004 peak in 1982, and the decadal source suggests that it also peaked at a level at least as high as 2004.  Of course, 1982 was a time of crazy speculation, when households took on unsustainable mortgages because they were convinced that home prices would never stop rising because of loose monetary policy.

But seriously, as I have mentioned before, this seems like strong evidence that credit fueled demand and easy credit terms aren't as strong a factor as people seem to think.  Before 1982, real long term interest rates were very low and nominal rates were very high.  That made mortgage term onerous.  But, the low real rates meant that homes had high intrinsic values because future rents were worth more in present value.  Also, the high inflation meant that imputed rental income and accumulating capital gains on homes provided a significant tax advantage.  Whichever of these factors dominated, they clearly overpowered the negative influence of those payments on 12% mortgage rates.

If intrinsic value is what dominates, then these changing homeownership rates simply reflect marginal reactions to real long term interest rates.  If the tax benefits of inflationary gains are what dominate, then that same effect would not have been as important in the 2000s, because inflation was lower.  So, the rising homeownership rates in the 2000s could reflect some ease of ownership resulting from low interest rates and aggressive lending.  And, there might have been a secondary effect of the tax benefits on the high home price appreciation that was happening at the time, even though that wasn't a reflection of broader inflation.

The 1970s and the 1995-2005 periods also were periods with rent inflation, so rising homeownership rates in both periods could have been a sort of hedging reaction, where younger households felt more incentive to avoid the uncertainty of future rising rents.  (By the way, put another knot in the rope for the theory that urban housing supply constrictions are actually a cause of the declining real interest rates, because they remove some uses of capital while producing capital gains for existing capital.  It so happens that we have two periods where rent inflation was high, real long term interest rates were low, and home prices were high.  I don't have detailed data on metropolitan specific housing measures for the 1970s, but there seems to be evidence that urban housing constraints were ratcheted up during that period.)

In any case, what is clear is that for households over 45 years old, homeownership was never elevated, and has dropped precipitously since the bust.  And for households under 45 years old, there do seem to be systematic fluctuations in homeownership over time, and homeownership rates in 2005 were within the range of ownership levels we had seen before.  In fact, they were at a level we had seen when mortgage rates were over 10%, so there simply is no reason to think that marginal homeowners in the 2000s needed to be any different or less suited than households who might have owned homes at other times in the HUD era.


PS: I also found this graph on page 131 of this report, which gives us some age-specific information going back to 1960.  This also shows 1980 homeownership rates for working-age households at the same level as in 2000.  And households skewed younger in 1980 than in 2000, so within each age group, ownership would have been higher in 1980 to make up for the demographic shift.

Housing Part 111 - More data on mortgages to low income households

Previously, I have looked at homeownership rates through the Survey of Consumer Finances.  And, there I find no evidence of a rise in homeownership among low income households.  This is incredible, given the vats of ink that have been spilled discussing that very topic.  It happens that the Census Bureau has some detailed data on homeownership, going back to 1994, which covers just enough time for us to analyze the boom.  This data also shows absolutely no rise in the relative share of low income homeownership.

Here is the graph of Census data.  Homeownership rates rose for both households above and below the median income.  The black line is the proportion of owner-occupied homes owned by the top half of the income distribution.  This line is straight as an arrow, just above 60%.  As I pointed out in the earlier post on the subject, in a period with rising homeownership rates, we should expect to see this decline.  For instance, if the homeownership rate was 100%, then 50% of homes would be owned by the top half of the income distribution.  So, in order for this measure to remain flat, new homeowners among the pool of potential buyers had to be slightly biased to higher incomes.

The Census Bureau also tracks ownership rates by age group.  Somewhere back in a previous post, I have taken a stab at demographically adjusted homeownership rates before.  But, this data is more complete than what I used before.

Here are several graphs to help think through the effects.

First is simply a graph of homeownership rates, by age.  Then, below that, I have included a graph of these age-specific homeownership rates, relative to the levels as of 1Q 2004, when homeownership had generally peaked.

Notice that homeownership among older households was fairly flat.  Households over 65 years old generally have very high equity positions in their homes.  (They also tend to have lower incomes than they did when they were younger and working.  This tends to create confusion regarding statistics in the lower income quintile.)  Their large equity positions tended to protect them from the collapse.

As we move down the age scale, homeownership tends to have risen more steeply and then fallen more steeply.  I think this may not be very widely appreciated.  But, when we look at homeownership by age, homeownership rates for all age groups under 65 are well below the rates that applied back in 1994.

But, the aggregate homeownership rate is at about the same level as in 1994.  How can this be?  As with so many things, homeownership rates are being skewed upward as baby boomers move into age ranges that tend to have high ownership.  So, homeownership rates have collapsed much more sharply than it first appears.

The next graph shows the actual homeownership rate, and an estimate of what the homeownership rate would be if age demographics were still what they were in 1994.  I had thought that the peak homeownership rates might have overstated the rise in homeownership because of these demographic issues.  And, it did, somewhat.  But, much more than that, the demographic effects have masked the devastating fall that has come with the collapse.

If we adjust for demographics, the current homeownership rate has fallen to below any level we have seen since the Census Bureau began tracking it on an annual basis, back in the mid 1960s.  And, to think that many observers are warning about a new phase in irresponsible lending.

I would also like to point out how this relates to a topic I have been reviewing in a couple of recent posts.  Low real interest rates appear to have a much stronger affect on homeownership than credit terms.  Price/Rent ratios were high in the 1970s, even when mortgage payments were extremely high.  This should be somewhat shocking.  Even in that environment, where, surely, outrageously high mortgage payments would have served as a high obstacle to both ownership and to buyer willingness to pay, home prices appear to have approximated the higher intrinsic value created by low long term real interest rates.  But, it is even more shocking than that.  Not only were prices efficient, but, homeownership rates were high then.  And, adjusted for demographics, they were nearly as high as they were at the top of the boom in 2004.

Given low long term real interest rates, it appears that the facts that nominal rates were under 6% instead of being over 12%, and many new financial instruments were being used to help households take on mortgage debt, had very little effect on homeownership.


Taking all of this in, a broad theme starts to coalesce, I think.  There is a significant age story here.  There are many attempted explanations about why young families are less likely to buy homes than they used to.  But, since the story of what happened is so misunderstood, nobody is fingering the cause.  The unnecessary housing bust decimated the balance sheets of young households.  Look back at those age-group graphs.  The boom was mostly about increasing homeownership for households under 45 years of age.

The marginal new mortgage originations weren't facilitating new homeownership of poor households.  They were facilitating ownership for high income young households.

One of the themes that runs through Mian and Sufi's book, "House of Debt", is that the boom and bust especially hurt low-wealth households, who tend to hold a lot of debt, while it may have actually benefited high-wealth households, who have claims on that debt because they are savers.  This is all true enough, as far as it goes.  And, it must seem to fit into the standard narrative of the unsustainable bubble, built on the backs of low income households.

But, we have to be careful about who we imagine these households to be.  We tend to think of a category of households that are "poor" - both low wealth and low income.  But, this creates confusion.  In truth,  families we tend to think of as poor tend to have very little debt.  Low income households who own homes tend to have high equity levels, because the lowest income households don't tend to take out mortgages, regardless of the frightening anecdotes that have been traded around since the boom.  Debt is held, mostly, by high net worth, high income, and young households.  And, when it comes to debt and net worth, age is the most important factor.

So, really, what Mian and Sufi are describing is a loss of wealth for young households and an advantage to old households.  The households that really took a hit were young households who had tried to become new homeowners, who, it appears, tended to have high incomes.  In fact, since incomes also tend to rise with age, the relative tendency of new homeowners during the boom to have higher incomes is especially strong given that they also tended to skew younger.  But, since they were young, they had high debt levels and low net worth.  The younger the age group, the worse the collapse in homeownership rates has been.  This is because young families tend to be new homeowners with little equity.

While households over 65 have generally recovered - especially those with high net worths - as of 2011, the median household in the 45-54 age range had net worth 35% below the 2005 level, and the median household in the 35-44 age range had net worth less than half the 2005 level.

------------------------------

In the reading I have done so far, I have not yet seen a single reference to this piece of evidence.  It's sort of fascinating for me, because I now have some support for publishing my findings in book form, and the task is daunting, because I have to go, piece by piece, through all the evidence that I can find and explain why my thesis stands.  If something like this census data was out there that contradicted my story, and I didn't have a good explanation for it, it would be a significant black mark against my argument.  Something this broad and clear would probably lead many readers to write off the story and go no further.  But, among all the writers who have filled library shelves with stories of a credit bubble, I haven't seen a single one, yet, that even noticed this data.  This isn't a state secret.  Numerous people are involved in creating this data and making it available.  I assume some number of people look at it on a regular basis.  I think it has just been edited out of notice.  I mean, if everyone believes a story very strongly, and they are all sharing what seems to be insurmountable evidence for it, if you see something that blatantly doesn't fit, it seems reasonable to simply ignore it.  Something must be wrong with it.  We all do this everyday.  Making these decisions is a necessary part of understanding our world.

So, on the one hand, the task before me is daunting, because I don't have that benefit.  I can't just ignore the data that doesn't fit my story.  On the other hand, while normally there aren't any $100 bills on the ground, because "someone would have picked them up already", on this topic, I am swimming in them.  Telling the story is as easy as reproducing basic charts from the Census Bureau.  The hardest part will be before readers even open the book.  The most important part of the publishing process, I think, will be getting a broad range of authorities to say, clearly, "This is a book you need to read to the end.  I was surprised by it, and it changed me."  Otherwise, at the slightest hint of a weak argument, readers will be tempted to put it down as a lark before they see all the intertwining facets.

Changes in Male Labor Force

These charts from the New York Times are just the kind of thing I've been looking for.

Here is the static version of the chart from the article.  It would be great to see a moving version of this over a longer period of time.

I'm not sure there is much to worry about on the age groups under 50 years.  Some blame the increase in young workers not working while in school on the minimum wage.  There might have been some of that after the 2007-2009 hikes, but the minimum wage is nearly back to insignificant levels, so I can't believe it would have had that much of an effect.  And, we saw this same trend between the MW hikes of 1996 and 2007.  So, I think this is largely a cultural shift.

Between 25 and 50 years, there has been a shift to unemployment, which is cyclical and should be generally temporary.  Otherwise, there have been small shifts to disability and caring for family.

I would also attribute much of the drop in rates of retirement to cultural changes, generally from people being more productive and active at older ages.  Some attribute this to older workers lacking retirement support, but as with the young, this represents a long term shift in behaviors that has persisted through business cycles.  There is a tendency to negativity in some of these interpretations, so that lower labor force participation in 50 year olds is blamed on stagnation and higher labor force participation in 60 year olds is also blamed on stagnation.

The largest problem is the disability issue, which affects the over 50 age groups the most.  This is clearly the product of bloat in a program that has devastating moral hazard issues, and it appears to be a significant input into the decline in US labor force participation compared to other nations over the past couple of decades.  Other public programs have the problem of creating a high de facto marginal tax rate for the poorest households.  But, this policy provides a meager support level and then explicitly directs recipients to self-identify as unproductive.  Local news teams expose frauds on disability who are filmed playing in softball leagues, etc.  This is trees and forests, people.  We're the monsters that put them in that situation.  (Of course, you could say the same for banks overleveraged on AAA securities.)  I predict that this problem will not be a topic in the political theater associated with upcoming elections.

Homeownership and the wisdom of markets

Here is an article from Meta Brown, Sydnee Caldwell, and Sarah Sutherland at the New York Fed (HT: Mark Thoma).  Here's the take-away:

(T)he failure of young consumers, and particularly the comparatively skilled young consumers of our student loan group, to re-enter the housing market remains a puzzle. Many factors could be contributing to this phenomenon, including growing student debt balances, limited access to credit, lowered expectations for future earnings, and perhaps even a cultural shift by which young people—whether they went to college or not—are deferring home purchases. Whatever the cause of student borrowers’ reticence, the housing market rebound of 2013 appears to have proceeded without the help of this skilled set of young buyers.

This is good news, and it's a good example of the wisdom of markets.  With real long term interest rates at 1%, home prices should be high and volatile.  Homes are very bond-like in this environment, and, speaking strictly from a portfolio construction point of view, they have no place in a young person's portfolio.  Young families should size-down, rent, and put their money in the stock market.  In 20 years, when the baby boomers are selling their homes and long term real rates are at 4%, then these young families should buy.

It might be a good rule of thumb for portfolio management for non-boomers to just ask, "What do the boomers need to hold", and then take the opposite position.

Homes have always been a good investment for just about everyone who could arrange the financing.  They are still a great investment for people who need bond-like exposure (baby boomers) but they are not currently a good investment for everyone.  The market represented by young families has figured this out, even if individual families, social convention, regulators, the GSE's, and the New York Fed haven't.

New Home Sales and Prices

The conventional view seems to be that housing is "bubbly".  Here is the monthly annualized change in the Case-Shiller 10 city home price index.

Home prices have been increasing by around a 10% annualized rate for two years.  (Case-Shiller is already smoothed enough that I don't see the need for a YOY treatment.  This is annualized monthly percent change.)Interestingly, while the Case-Shiller Index reflected much higher increases in the 2000s than the Census Bureau's new home price series, both series are moving up at a similar rate now.

Here is a recent post by Political Calculations on the topic.  Ironman is taking the bubble position.  Bill McBride at Calculated Risk is more optimistic.  He thinks that a recent downswing in new home sales is temporary, and that new single unit home sales will eventually recover back to about 800,000 - less than before the crisis, but about double the current level.  I think he expects home prices to settle down, but he doesn't think we have a bubble.

Ironman sees prices as a function of median income.  McBride sees a pullback because of the increase in mortgage rates.  I think both of these perspectives are subtly wrong, in that they both miss the importance of real long term rates on the intrinsic value of the home.

The Crazy, but true, Counterintuitive Effect of Real Interest Rates

Rent may be a function of median income, but home values should be a product of the discounted future value of those rents, which is highly responsive to the discount rate, especially when rates are as low as they are now.  One sign of this is the current low level of mortgage debt service - at 5, compared to a long-term level of 6.  This actually understates the depressed level of real estate credit, because given a stable expected inflation, lower real rates should raise the mortgage payment on a home with a given implied rent.  This is counterintuitive, but it's true.  The subtle mis-reading of thinking home values are a product of the mortgage payment is wrong.  When you divide interest rates into real rates and an inflation premium, and treat a home's value as the present value of future net rent payments that rise at the rate of inflation, the justifiable mortgage payment will decrease if expected inflation decreases, as we would expect, but it will increase if real interest rates decrease.  If you are skeptical, it's a simple model you can put in a spreadsheet in 2 minutes.

That's been a theme here lately.  Look how this subtle interpretive error completely reverses the interpretation of the housing market.  If you think that home prices increase because falling nominal rates lead people to bid up houses until they have the original mortgage payment, then that graph above of mortgage debt service looks like a rational market until 2005, when speculative froth caused people to be so irrational that they bid the price of houses up beyond that point to where they were making larger mortgage payments.  Your model of home prices would assume that there was no reason for this, and it would seem to obviously be a bubble.

But, if you see this counterintuitive effect of real interest rates, you would expect the low real interest rate environment of the 2000's to lead to higher mortgage debt service levels.  You would wonder what frictions in the home market kept the mortgage debt services levels from rising earlier than 2005.  Remember how homebuilders would hold lotteries to see who could buy homes at the listed prices that week?  Remember how homes would receive multiple offers above the list price?  That seems like an obvious bubble, doesn't it?  But, understanding this subtle change in interpretation, those activities now look more like a sticky price issue.  I find sticky prices to be a much more plausible explanation of those incidents.  There is a tremendous amount of  mental benchmarking in home markets - consider the use of comparables, etc.  When home prices need to move by more than 15% or 20%, it takes a while to get there.  These price inertias are so strong that home sellers were still underpricing their homes, even when they were surrounded by homes that had been bid above their list prices.  The housing market wasn't out of a rational equilibrium in 2005 and 2006 with prices that were too high; it was out of equilibrium in 2003 when prices were too low, because of sticky prices.

So, now, because everyone knows that the increase in mortgage debt service was a sign of bubble behavior, when mortgage debt service starts moving above 6% again, there will be a groundswell of demands for the Fed to pop the supposed bubble.  It's a shame.  This is a perfectly understandable misinterpretation, but it is a misinterpretation, and if we continue to take that interpretation seriously, we will continue to create undue economic hardship.

Regarding Current Prices

I don't see any relationship in the data between mortgage rates and home sales or prices.  At the time frame of the business cycle, the correlation can be positive or negative - rates tend to go up as the economy strengthens, and so do prices and quantities.  So, I don't see any reason to attribute monthly or yearly price fluctuations to mortgage rates, and I don't see any strong basis for this in the data.  However, what makes sense to me, and what I believe we can see in the data, is a long term relationship between home values and real long term interest rates.

Rising rates can create a drag on demand by locking some households out of the mortgage market.  But, this effect should be minimal at any level we will be seeing in the next several years.  Rates like we saw in the late 1970's - over 10% - can start to have noticeable effects, but even when those rates were in effect, home prices were rising because home values were bolstered by the low real rates of the time.  Home prices began to fall after 1980 when real rates jumped, even though nominal mortgage rates declined.

The funding mechanism is fairly arbitrary.  All of the public policy measures that we have to encourage mortgage funding have some marginal effect on the cost of funding.  The mortgage interest tax deduction is probably the most distortionary.  But, generally, the value of an asset is not a function of the method used to finance it.  I believe this general principal has been lost due to the high correlation between mortgage rates and the discount rate that should apply to the discounted cash flow value of homes, and the misinterpretation that comes from that confusion.

In any case, the current value of homes is not constrained by mortgage rates or by the intrinsic value of future implied rents.  The current value of homes has been constrained by the lack of liquidity imposed by tight Fed policy and the lack of capital from banks that has resulted from that liquidity crisis.

Here is a graph of price to rents (using both Case-Shiller (blue) and Median new home prices (red), 1987=1).  These were rising as real interest rates fell (shown here with an approximation using mortgage rates minus U. of Michigan inflation expectations and with 10 year TIPS).  I believe that Case-Shiller reflected the justifiable price of homes even near the top of the market.  (As a simple example, an asset discounted from 20 years in the future will increase by about 50% when the discount rate declines by 2% and by 75% when the discount rate declines by 3%.  This is the range of the change in long-term low risk real interest rates and the corresponding change in home
price-to-rent, as reflected in the Case-Shiller Index, over this period.)  Notice that home prices were declining slightly in 2006 and 2007 as rates rose.  This relationship broke down in late 2007 as the liquidity crisis intensified.  Price to Rent at 1.7 in 2007 was mainly a product of the interest rate environment.  The drop from 1.7 to 1 was a product of the liquidity crisis.  It is at 1.3 now.  Even if rates rise an additional 2%, so that 10 year treasury rates are at 5%, a Price to Rent ratio of 1.7 is justifiable.  At worst, it's somewhere between the Case-Shiller and the Medium New Home levels from the 2000s.  And, it could be a decade before 10 year treasury rates are sustainably above 5%, unless the Fed begins to allow inflation to rise above 2%.  So the market, when credit markets are functioning, will be reaching for Price to Rent levels 30% higher than current levels, and in the meantime, rent inflation is accelerating.  And, looking back at the first graph, there is no sign of home price growth subsiding when we look at the month-to-month Case-Shiller index.  Calls for a market top are getting ahead of the data because so many people are convinced that we have a bubble.

Political Calculations sees a market top in the March decline in new home sales.  It will be interesting to see how the data proceeds.  I suspect that we are seeing a temporary dip because much of the all-cash investor demand for real estate was essentially funded by QE3.  (Perfectly reasonably, IMO.)  Now that QE3 is being tapered, that demand is falling away, but the banks are just now garnering the ability to extend their own credit to replace the liquidity that QE3 was creating.  I think we will see bank credit continue to recover, but if it doesn't, my thesis could be busted by more liquidity problems.  Here is the weekly level of real estate loans at all commercial banks.  It appears to be rebounding over the past few months.  This may reflect the winding down of foreclosure activity as much as an increase in purchasing activity, but at least it is a move in the right direction, and it signals a willingness or ability for banks to add to their real estate exposure.  If this process takes a few more months to gather full momentum, home prices may look like they are beginning to moderate before they reassert their movement toward previous highs.

This could also reflect a lack of demand.  The relationship between price and demand is complicated on a durable asset.  I don't want to go down that rabbit hole right now, but suffice it to say, I'm not entirely confident with my understanding of exactly what is keeping real estate loans depressed at the banks.  Please let me know in the comments if you have insight.

A Caveat

I am considering being more bearish than Bill McBride on one factor, and that is the projected quantity of new home sales.  He expects a doubling from around 400,000 units to around 800,000 units.  That seemed reasonable to me.  But, looking at demographics, I'm not sure if that is sustainable.  To approximate the demand for single family housing units, I have compared the annual change in the number of males in the labor force to the SAAR quantity of new home sales.  (For male labor force I used the YOY change in the 12 month moving average, in an attempt to reduce noise.)  The labor force series carries an array of information regarding business cycle and demographic trends and plots remarkably well against new home sales.  (I used males because their age-specific labor force behavior has generally been stable for decades.)

Going forward, annual increases in male labor force participation are expected to remain around 500,000 per year for several decades.  There might be a cyclical rebound of an additional 500,000 or more over the next couple of years.  Also, baby boomers' movement out of the labor force may predate their movement out of single family units. Also, the excess capital associated with this demographic shift may move some homebuilding back in time.  So, we might get to that level of 800,000 units or more, temporarily.  But, I think it may be prudent, when modeling future cash flows of homebuilder, to base it on long term annual new home sales more in the range of 600,000.  I continue to see unexpected profits for homebuilders resulting from rising property values, but I think unit sales may remain significantly below where they were before the crisis.

Hooray for International Capital Flows

Antonio Fatas presents these charts (HT: Mark Thoma) comparing global growth rates  and investment rates among advanced and emerging economies.

It seems to me that this relates to a topic I have touched on here:
http://idiosyncraticwhisk.blogspot.com/2013/08/stop-hatin-on-trade-deficit-aka-america.html

And here (with probably a little too much sarcasm):
http://idiosyncraticwhisk.blogspot.com/2013/08/compensation-as-portion-of-gdp.html

It looks to me like we have a set of growing emerging markets, who are accumulating their own capital.  But, their own economies are still characterized by high risk premiums.  So, emerging market capital is hungry for a source of low risk income.  Western sovereign debt, low-yield bonds, and real estate fill that need.  So, emerging market capital is moving to the developed world.

And, in return, developed world capital is filling the gap.  American capital, especially, is lured by profitable risk, so our corporations are investing very profitably in emerging markets.  As the Western baby boomer bulge enters their twilight years, we are confronted with a time mismatch between boomer production abilities today and boomer consumption needs in 20 or 30 years.  Part of that mismatch is being bridged through investment in durable property like homes.  Part of that mismatch is being bridged through the investment of boomer savings into emerging economies, where growth of labor output is not as constrained by demographics.  Here is a graph of labor force growth in the US.  This looks like it tracks pretty closely with Antonio Fatas' graph of GDP growth.  Maybe in the US, investment is constrained by the availability of labor.

So, there is this huge, mutually beneficial transfer happening between emerging market capital and developed market capital.  This causes all sorts of problems for politically charged statistics, because, for starters, it makes it look like developed nation capital is capturing a larger portion of production, God forbid.  And, it creates a sustained trade deficit in the US.

But the actual result here is basically what we should have hoped for from global finance.  Risks are being traded off to where they are more appropriate.  And the end result is that huge populations of the world's laborers are being exposed to more opportunities for prosperity.

The increasing wages in these economies, the high growth rates, and the high returns to capital, are all products of improving market-securing institutions.  This is why I hate the subtly incorrect notion that production moves to places with low wages.  Production moves to places with rising wages, not low wages.  From a previous post:

This is basically the problem with developing economies, where institutional improvements make capital investments safer, and foreign investment is lured into the growing economy.  But, since reversals are possible, and trust requires the passage of time, firms require a higher rate of return.  Nations that reverse to poorer institutions will lead to losses for those firms.  In nations that continue to improve, the realized returns of the investing firms will appear to be high.  Over time, as trust is gained, realized returns will settle to a long term reasonable equilibrium.

This is why it appears that production moves to places with low wages, when production really only moves to places with rising wages.  The necessary development of trust creates a lag effect where the higher required returns cause wages to rise more slowly than they would without this long tail risk.  So, there is a period of time where firms earn seemingly oversized profits at the expense of lower wages for the laborers in the developing economy.  Of course, the profits aren't oversized, they are just the payment received for taking on long tail risk with a binary and unpredictable payoff.  This generally calls for a high return, and also tends to produce survivorship bias in hindsight.
......
 In a way, the ability of US corporations to earn excess profits by moving production to developing economies is very similar to the well-documented momentum effect on individual US stocks.  Markets have a trust-but-verify mentality.  Efficiency means that prices fairly quickly react to new information, but not all the way, because the veracity of new information has its own risk distribution, with its own long tail of failure risk.

CEO's don't necessarily even need to model their investment decisions this way.  These factors will be built into their assumptions about wage growth and other costs, and their heuristics for how risky each location is.  So, they could account for all this and still misunderstand their investment decisions as being the result of moving to places with low wages.

But, it's not the low wages that attract capital.  Improving institutions lead to capital investment and increasing wages.  That's why most capital flows to high wage countries and why Korea and Taiwan are now among them.  That's why low wages aren't drawing capital to Congo, Zimbabwe, and Niger.  And, it's why American inner cities lack retail.

We are living in much better times, globally, than is sometimes acknowledged.

Follow up post.

Quick Follow-Up on the Beveridge Curve (updated)

I always realize that I left out some useful item after I make a post.

For point of reference, here is the Beveridge Curve for 35-44 Year Olds.

Compare that to the two age groups I posted yesterday:

I also wondered, after I posted the original material, what effects population changes or labor force participation changes might have on this output.  The Boston Fed paper, by Rand Ghayad, used the unemployment of each group, expressed as a percentage of the entire labor force.  This was useful in their analysis, but it does allow for changes in labor force levels to affect the appearance of these Beveridge Curve outputs.

Population and labor force changes don't affect the 20-34 year old group.  But, they do have a small effect on the 35-44 and 45+ groups.  The 35-44 group Beveridge Curve would shift right by about 0.1% and the 45+ curve would shift left by about 0.15%.  So, the scale of the unusual shift among 45+ year olds is reduced by about a quarter. (See update below.) The general pattern remains, however, and this adjustment would seem to strengthen the bifurcation between job losers and job leavers, since it reduces the small Beveridge Curve shift that the Boston Fed did find among older job leavers.

The labor force shifts among 16-19 year olds has been large enough to change the character of the shift for them, however.  Adjusting for labor force changes makes the 16-19 year old pattern look more like the 20-34 year olds.

I know I'm a broken record on these issues, but I think this strengthens the argument that the effect among the 20-34 year olds (now among 16-34 year olds) is minimum wage related.

Employment loss and recovery showing up in 16-19 year olds earlier than in the other populations, and for much of the 16-19 year old employment losses to be reflected in changing labor force participation is typical pattern for the few federal minimum wage episodes that we can analyze.

The good news is that these groups are recovering as the minimum wage level is reduced in real terms over time.



PS. (Added)  Here are the Beveridge Curves for the 3 main separate groups:  The young group where the extra unemployment is from job leavers or entries, the middle aged group that didn't see much of a shift in the Beveridge Curve using the Boston Fed's measure, and the older group where the extra unemployment was from job losers (which have had especially long unemployment durations in this cycle, coincidentally with the very long Unemployment Insurance benefits).  In these graphs, I have used age-specific labor force levels in the denominators so that changes in unemployment would not reflect relative changes in age-group population levels.

y=Openings Rate, x=unemployment rate

The young group saw a shift right in the Beveridge Curve, which has been partially reversed, with a little more recovery to come.



y=Openings Rate, x=unemployment rate

The middle group had a shift in the Beveridge Curve, which was not apparent with the Boston Fed's methodology.  It has partially been reversed.  The effect still appears to be smaller here than in the other age groups.  Because the effect doesn't show up when the Fed separates the unemployed according to reasons for unemployment (job losers, job leavers, etc.), it is difficult to know the weight of the shift that can be attributed to each type.  The shift in this ratio from this age group accounts for less than a quarter of the total excess unemployment, so the difficulty of addressing this age group in the Fed paper would only make a small difference to the aggregate picture.

y=Openings Rate, x=unemployment rate

The older group saw a large shift right in the Beveridge Curve, which has recovered slightly.




I predict that the young group will continue to slowly merge toward the pre-2008 trend.  The older group will merge more quickly toward the pre-2008 trend, and will account for much of the lower unemployment rate to come over the next 6 months.

By around summer 2014, we'll see unemployment at 6.0% or less and the leading edge of the Openings/Unemployed ratio for the older age group in the same range as the pre-2008 ratio.

There, I've put the gauntlet down.  Either, come summer, I'll be proven right, or there will be some previously unknown development that will have invalidated the test of the forecast.  ;-)


Review of Tricky Issues in Labor Force Participation

This post from the Mercatus Center offers a good overview of the complications that arise from adjustments that need to be made with analysis of Labor Force Participation.  They have adjusted for age, which is an important first step.  Here's a graph they use, with my notations added:

1:  This is the one group with a truly unusual drop in LFP.  Some of this is a part of a long term cultural shift toward longer time spent in education.  But, the shock specific to the current time period was the 3 hikes in the minimum wage from 2007 to 2009.  In 2006, about 4% of the 16-24 year old labor force worked at or below the federal minimum wage.  By 2010, that was up to 10%.

Here is the 16-24 year old LFP rate, from the BLS:

Note how LFP in this age group dropped precipitously from 2007-2009, and has been flat since then.  This is a distinctly different character from the other age groups.  Minimum wages affect a larger proportion of this age group compared to the other age groups.

The unusual decline in this age group can be attributed to the minimum wage, but that shock to labor demand ended 4 years ago.

2:  The movements in the 45+ age groups have, on net, been positive, and mostly reflect the undulations of boomer populations through these groups and the tendency of baby boomers to work later than earlier generations.  So, this group has seen an anomalous net increase in labor force participation during a cyclical downturn.

3:  This group represents the heart of the labor force, and the age group LFP declines appear to still be damning, even when looking at the age groups.  The average LFP drop here has been about 1.9% since 2007.  But, there are additional adjustments that need to be made.

A) There has been a long-standing secular decline in the LFP of each age group of more than 1% per decade, which was temporarily countered by the increase in female participation which lasted until the early 1990's.  It has now been 6 years since 2007, so even within age groups, we should expect trend LFP to have decreased by about 0.7% during this time for reasons unrelated to short term cyclical or structural issues.

B) The 2007 labor market was very strong and LFP at the time was significantly above trend.  This was not commonly recognized because the trend was declining due to the aging workforce.  But, since the 2005-2007 period is widely recognized as a boom-time, it should not be difficult to believe that LFP was at least 0.5% above trend.  We could have experienced a shallow recession with unemployment topping out around 6%, and an age-group specific decline of 0.5% back to trend would have been reasonable.  This is roughly what happened during 2001-2002.

These two adjustments leave us with about a 0.7% decline in LFP, below trend, which can be attributed to short term issues.

Long term secular declines as well as demographic issues will continue to weigh down on LFP at a rate of up to 0.3% or so, annually, for the time being.  So, if LFP simply stops declining, much as it did from 2003 to 2007, we will be back above trend by 2016.

Obamacare, or some other structural issue, could prevent that kind of recovery in LFP.  But, in assessing those effects, we need to be careful in adjusting LFP for all of these other issues.  The fully adjusted LFP rate is, at most, a few tenths of a percent lower than normal cyclical fluctuations would portend (plus including the effects on the prime age groups of the minimum wage hikes that ended in 2009 - which might account for those few tenths of a percent).  The status quo should lead to an annual decline of something near 0.3%, together with a cyclical recovery of at least 0.7% over the remaining recovery period of the cycle, plus any additional fluctuations above trend if the recovery remains healthy.  Deviations from that trajectory could be attributed to labor market problems.  But, we should be careful to measure appropriately.

Some Great Graphs on Labor Force Participation

I wish I'd thought of these.

From the Federal Reserve of Atlanta. (via Pinetree Economics, with great added commentary)

Here, just to wet your whistle:



Excellent work.

PS.  OK.  I'm done.  With this incredible interactive chart, there is nothing left to be said about LFP.

Minimum Wage, Demographics, Emergency Unemployment Insurance, and Labor Force Participation from 2007-2011

In the previous post, I estimated the effects of these issues on unemployment.  Now, I'm going to look at Labor Force Participation (LFP).

Edit:  After looking some more at the relationship between the MW and the proportion of workers at or below MW, I noticed a non-linearity at the low end of the range, where MW levels were in 2007.  The first hike in 2007 hardly budged the proportion of workers at MW.  This was likely because the legislated MW had fallen below the typical voluntary MW.  I have updated the graphs and numbers below to reflect that deviation from the trend.


Minimum Wage

I discussed this in the previous post, and went into more details in the posts before that.  Even though there have been relatively few separate minimum wage episodes over the past 60 years, I was able to establish a strong relationship between the 6 month change in employment over the course of the typical episode and the scale of the MW increase in relation to the average wage.  The forecast specified by that relationship is what I use here to estimate the effect on labor force participation (LFP).  Much of the lost employment coming from MW hikes appears to lead to lower labor force participation instead of unemployment.

Demographics

I have discussed this quite a bit.  Most recently here.  This shouldn't be complicated.  There are stable long-term trends among different age groups.  As the population bulge enters the older age groups, this causes the reported labor force participation rate to shrink.

Emergency Unemployment Insurance

EUI plays a small role here.  I referenced a GAO report here that found about 1/5 of EUI recipients who had aged out of EUI exited the labor force.  An analysis of these factors should include the effect that EUI should have on inflating LFP.  I presume that, on the margin, this is not controversial.  On this particular effect, I don't have any clever methods to get at a number, so I have simply estimated this effect to be equal to 10% of the cyclical long term unemployed.  This estimate leads to a fairly small number, in any event.  I don't believe I am double counting with the EUI unemployment effect, because that measure specifically did not attribute any additional unemployed workers to the effect.  It only accounted for longer durations of unemployment among the given number of unemployed.

Here is the estimated effect of these factors on LFP.

graph before update



The minimum wage effect is estimated to outweigh the demographic effect since 2009.  Adding these effects up and comparing them to the actual change in LFP over this period, we see this comparison:

Considering that these three forecasts come from three separate contexts, it's kind of surprising that they would add up to explain the entire recent this much of the character and the decline in the LFP.  But, maybe they do.

Here is the chart, extended to 2013.  As with the unemployment chart, I am less confident in the Minimum Wage effect once we get past 2011.  But, we can see here that as the EUI and MW factors dissipate, the actual LFP is now sloping below the estimate derived from these factors.


graph before update

Unemployment, Labor Force Participation, Market Frictions, and the Definition of Cyclical

Here is a long term chart of the cyclical deviation of LFP, compared to the inverted Unemployment Rate:

Here is that chart, with the adjustments from 2007-2013 that I have just estimated, removed.  If my estimates are correct, this would represent the truly cyclical behavior of the current labor market.



graph before update

With the adjustments, unemployment looks similar to previous downturns.  But, adjusted LFP seems just a little too high.

It could be that I have overestimated something.  It could be that my model doesn't capture enough unemployment among the MW job losers, so that adjusted unemployment and adjusted LFP are both too high.  The adjustment to reduce the estimated effect of the 2007 mimimum wage hike, as discussed above, does create a more realistic looking cyclical LFP path in the early part of the crisis.  In the 2nd version of the new graph, I changed the assumption about EUI and the labor force.  If we assume that, instead of 10% of the excess long term unemployed, that a full 25% of excess long term unemployment will transfer out of the labor force, then the cyclical trend looks very normal.

Obviously, tweaking other estimates here and there would move the demographically detrended LFP up or down, slightly.  The point here isn't to claim exact numbers, but simply to suggest that reasonable estimates of the effects of these policies and long term trends can explain all of the supposedly unusual labor market behavior.  At least, I think I've given some plausibility to the idea that there is no big mystery in recent LFP behavior.

One other comparison I will make with the adjusted data is to compare the standard Beveridge Curve (the relationship between unemployment and the number of job openings) and an adjusted Beveridge Curve that utilizes my policy-and-demographic-adjusted unemployment rate.  My adjusted unemployment rate pulls the Beveridge curve back into the recent conventional range.

graph before update

So, if my adjustments are accurate, does this shift in the Beveridge curve point to labor market frictions and rigidities.  Historically, the Beveridge curve has shifted slowly through decades:

Is this just a reflection of shifting levels of labor market frictions?  How much have policies such as the Minimum Wage been reflected in these changes?

The other question that comes to mind is, "What is the difference between structural and cyclical or demand-driven shocks?"

Disemployment from the minimum wage is clearly a structural shock, but it plays out like a cycle.  EUI also looks pro-cyclical to me.  It's countercyclical for the unemployed person who is provided with a safety net.  But, it's pro-cyclical to the analyst looking at the unemployment rate.

So, the discussion seems a little confusing to me if someone says, "Bad news.  It looks like the LFP drop is cyclical.  Unemployment should be even higher than it looks."  Once you correct for the demographic issue, do you answer, "No, it's not.  Much of this might be a minimum wage or EUI effect."?  Or, do you answer, "Yes.  You're right.  Much of it might be a minimum wage or EUI effect."?

I believe I have two more posts coming on the topic, if anyone is still reading at this point...

Minimum Wage, Demographics, Emergency Unemployment Insurance, and Unemployment from 2007-2011

So, after reviewing the historical evidence on increases in the national minimum wage, I have some method for estimating each of these factors on employment in the latest downturn.

Edit:  After looking some more at the relationship between the MW and the proportion of workers at or below MW, I noticed a non-linearity at the low end of the range, where MW levels were in 2007.  The first hike in 2007 hardly budged the proportion of workers at MW.  This was likely because the legislated MW had fallen below the typical voluntary MW.  I have updated the graphs and numbers below to reflect that deviation from the trend.

Minimum Wage:
This is based on the forecast described in the previous few posts, based on the relationship between the change in the minimum wage as a proportion of average wages, and the change in employment, during episodes of minimum wage increases from 1956 to 2004.  For total employment, during two-year periods following an initial MW hike, the null is rejected at the 10% level.  For follow-up MW hikes in episodes with more than one increase, the null is rejected at the .001% level if we include all periods of time, and is rejected at the 10% level for the 1956-2004 period.
The null hypothesis could not be rejected when tested in terms of unemployment instead of employment for the period ending in 2004.  But, the employment forecast gives us the more important number, in terms of expected jobs lost.  The unemployment forecast simply helps parse that out between workers who leave the labor force and workers who are categorized as unemployed.  With that caveat, I have used the forecast from those tests for the estimated unemployment due to MW hikes.

Demographics:
This estimate is based on a pattern I touched on here.  Unemployment duration tends to grow with age, and education.  I think this tendency can basically be thought of as labor market friction.  Older workers may have greater skill specialization, which creates searching costs.  They may also have more back-up resources, and a greater ability for consumption smoothing.  All of these factors may lead to greater cyclicality in the unemployment rate during times when there are more older workers.  This estimate is based on simple relative average unemployment durations for each age group, with unemployment increasing in proportion to average duration.
This is one of the earliest effects of the baby boomer aging process.  This effect is already diminishing because as older workers enter the oldest age categories, their labor force participation and general level of unemployment decline enough to counteract this effect on unemployment.

Emergency Unemployment Insurance:
I touched on this issue in this post.  Here is a graph of the relationship between unemployment durations of less than 26 weeks and durations of 26 weeks or more, going back to 1960.  Short term unemployment durations and long term unemployment durations moved with some uniformity through many different business cycles over that time, until the implementation of 99 week EUI.  David Grubb from the OECD explains how the level of EUI support was vastly longer than in any previous period.

My estimate for how much this policy affected the unemployment level treats this, much as in the demographic effect, as a labor market friction.  I compared the proportional level of durations over 26 weeks to the typical level we have seen in business cycles over the past 3 decades, and attributed that difference to the EUI policy.  One might be able to argue that there are some other factors involved here, but decades-long pattern of this relationship suggests that those other factors have been dwarfed.  Further, my measure ignores any influence EUI might have had in increasing the average unemployment duration of workers unemployed for less than 26 weeks.  This is clearly a conservative assumption.  On net, until I figure out how to sensibly estimate EUI influence on durations under 26 weeks, this estimate will probably be somewhat conservative.

Here are the unemployment estimates:



graph before update

This chart covers the time period until July 2011.  This is the period where I have a monthly model for minimum wage related employment changes.  These estimates suggest that if we did not have these demographic and policy issues, this would have been a typical unemployment cycle.  (The pale blue line is where I estimate we would be without these policies.)

Here is the graph extended to June 2013.  We are getting far enough away from the MW hikes that the recovery in low-wage employment is mostly dependent on broader economic recovery, Fed policy, etc..  As the earlier posts on MW showed, MW episodes that were small enough would eventually see catch-up employment growth as the economy naturally outgrew the wage-price floor.



graph before update

We may be near a normal labor market, if not for these issues.  These issues might continue to inflate the unemployment rate for a few years, but they shouldn't be permanent.  The Fed hasn't been too loose up to this point, but if they start to err on the side of being stimulative in the face of an unemployment rate that stays stubbornly above 6%, the hidden core of the labor market which may already be back to recovery levels, might create unexpected inflation.  The scale of the recent MW hikes was large enough that there may be low wage workers who continue to be priced out of the market if we don't experience some inflationary adjustments.  There may also be some frictions for long-term unemployed who want to go back to work.  So, unemployment declines might slow down at a higher range than has been the recent experience.  But, it is possible that if federal policies allow these issues to decrease in importance, that could help to reaccelerate the decline in unemployment.

Next up, Labor Force Participation.