Housing, A Series: Part 87 - Erosion of Conventional Mortgages Comes From Supply Constraints

I want to think through this issue of rent vs. home prices some more.  Because the US housing market was divided between a few cities with sharp supply constraints and the rest of the country, we have this deceptive statistical issue where, nationally, average rents from 1995 to 2005 were relatively flat while home prices rose sharply, but if we disaggregate by city, we find that in the places where home prices increased the most, rents also were high and increasing.

Many researchers have found a connection between subprime mortgage expansion and the scale of the housing boom and bust.  They have interpreted this to mean that excess or predatory lending was the causal factor.  I have been looking at evidence that housing supply constraints may have been the causal factor in these markets, and I think this issue of how subprime mortgages were related to rising home prices and subsequent defaults is yet another case where subtle and complex factors have caused us to misinterpret the relationship.

During the 1995-2005 period, national rent was relatively stable, but rent in the closed access cities (cities where public policy prevents housing expansion) was rising.  Even in the largest metropolitan areas (MSAs) that have open access policies, rents were rising somewhat during that period.  During the last years of the housing boom, rent was claiming 5% more of the median income in LA and San Francisco than the typical historical levels.  Since then it has risen to claim another 10%.  Rents aren't just rising in these cities; they are rising faster than incomes.

In addition, in a city with persistent rent inflation, home prices will be pushed even higher, much like a growth stock will have a higher Price/Earnings ratio than a mature stock, because owning the home is a hedge against future rent increases.  So, in cities with high rent inflation, and especially cities where long-running supply constraints would cause us to expect rent inflation to remain high, home prices will be very high.

And, we see from 1995 that rent affordability (rent/income) was rising in the closed access cities, and mortgage affordability was rising even more.

(By the way, notice that rent continued to climb after 2007 while mortgage affordability dropped to the lowest levels since at least the 1970s.  That is when a crisis of disequilibrium struck our housing markets, not when both rents and mortgage costs were rising.)

Thinking about the revealed preferences long term household behavior implies, it looks like in the absence of income shocks and housing constrictions, the median household will tend to find a comfort zone where they calibrate their housing consumption to around 20% of income.  If they live in an area with strong housing supply constraints, they will eventually reach a point where they will be reluctant to reduce their real housing expenditures any more, and they will allow their housing expenditures to rise as a portion of their incomes.

Thinking of the higher cost of homes in the constricted areas as a problem of excess demand misses this detail about rents, I think.  I submit that it is more accurate to think of the rising cost of housing in these cities as a measure of the amount of distress households are willing to accept before they decide they have to migrate.  In the worst cities, gross incomes have risen sharply compared to the rest of the country, but income after rent expenses has actually declined, relative to the rest of the country.  Given localized housing constraints, if households held no preferences for location, then prices would not have risen at all, and households would have simply moved to the places where building was allowed without the intervening behavior of bidding up local rents.  The rise of home prices in the closed access cities comes entirely from that preference.  The prices of homes in the open access parts of the country is a reflection of demand, lending, etc.  The prices of homes in the closed access cities is a measure of "location stickiness", if you will.

Our conventions about home buying reflect the expectations of a household with a comfortable cost of housing in an open access area.  So, conventional mortgages usually call for mortgage expenses of less than 30% of income.  Conventional mortgage guidelines are not calibrated for the typical housing costs of a closed access city.  The rise of subprime loans coincided with the rise of rent affordability in the high cost cities because of the supply problem.  Marginal households were buying homes on terms that were sometimes creative, but the trigger for this wasn't that they were enticed by mortgage originators into increasing their housing expenditures.  They had already increased their housing expenditures, passively, by living in cities with rent inflation.  In a city where the median house rents for 35% or 40% of median income, how does a potential homebuyer purchase a home with a conventional mortgage?

These households were faced with the decision to either (1) use creative financing to remain in their home city, (2) move down market into a neighborhood they weren't willing to rent in, so they could buy a home in their city, or (3) move away.  Of course, many chose number 1.  So, we call the lenders predatory and we call the homebuyers speculators.  They didn't ask to be speculators.  They were forced to be speculators by the housing policies of their cities.  Unless they chose option 3 and moved away, they were forced to be speculators.  If they continued to rent, they had to spend (at the median) more than 30% of their income on housing.  And this would keep rising each year, eating up all of their future income gains.  If they bought, they had to pre-commit to paying that rent, based on today's expectations about those future rent increases, which was baked into the price of homes.  Buying was the more expensive option in those cities, but households who were buying in those markets were taking the less speculative position.  They were in a position where their housing budgets were at the frontier of what was personally sustainable.  Thousands of families were being hit with rent increases and forced to move away.  Buying a home would create a stable path of expenses.

Thinking about the conditions brought about by the supply constraints, the creative financing products don't seem so outrageous.  If a family has been living in the same home for a decade, and they have seen their income rise by 3% per year while their rent has risen by 5% per year, with uncertainty each year about the year to come, then is it really that speculative for them to save up a little money for a down payment and take out a mortgage with 95% LTV and a negative amortization schedule so that their monthly payments increase by a set 2% per year?  That looks like the hedge position to me, not the speculative position.  And if rent already claims 40% of their income, is it really unreasonable for them to apply for a subprime loan that doesn't verify income?  What would you have them do?

Furthermore, in the closed access cities, we can infer that housing demand was inelastic because rents were high as a percentage of income.  Households in those cities didn't have higher rents because households in San Francisco and LA were living in mansions compared to households in Houston.  They had high rent budgets because home prices were so high that their demand had become inelastic.  They had made significant cuts in their real housing consumption, and were unwilling to cut more - their housing demand was inelastic.  So, it seems unlikely that households who decided to be buyers would use generous mortgage terms to increase their housing expenses (in terms of rent).

There were some marginally closed access and open access cities that saw significant subprime activity and did see a price spike later in the boom, coincident with the largest increases in private subprime lending - inland California, Florida, Nevada, and Arizona.  It is possible that some of that late price spike was related to demand side excess.  But, on the national level, that probably amounted to 10% or less of the total increase in real estate prices over the 1995-2005 time frame.

There were some open access areas, like Houston, that saw significant subprime activity.  But there was not a price spike there.  In Houston, housing expenses were low.  In Houston, housing demand for the median household would have been elastic.  Houston is the place that we would expect to see overconsumption in housing because of lenient mortgage terms.  In Houston, a reckless family offered a questionable mortgage might say, "Hey, now we can move into that mansion down the street, and still only spend 25% of our income on it."  In San Francisco, they would say, "Hey, we can use these questionable terms to get 5% of our budget back."  In other words, if we are just thinking about the effect of generous credit on individual homebuyers, in Houston easy credit might lead to a price bubble.  It would not in San Francisco.

I'm surprised that this hadn't occurred to me until now.  And, I'm surprised it apparently hasn't occurred to anyone else that I know of.  When we recognize the clear separation between these high rent/high price cities and the rest of the country, this is almost definitional.  Households in the cities where home prices shot up had inelastic housing demand.  The price boom had to be dominated by supply factors.



Based on 30 year fixed rate, 20% down, Median House & Income

Here is a chart of mortgage affordability in Houston, Dallas, and Atlanta (all the data I am using here is from Zillow).  A decent number of subprime loans were originated in these cities in the 2000s.  With a cumulative population of 14 million, they built over 1.6 million homes over the decade.  New York, San Francisco, LA, San Diego, and Boston, with a total population of 42 million, managed to build just under 1.2 million homes.  Of the top 20 MSAs, these 3 cities accounted for 13% of the population and 27% of the housing permits over that decade. So, where was there a housing boom?  Where were marginal new households becoming homeowners?  I think we can consider these cities the baseline cities for how demand and excess lending affected the housing market.

I conclude that there were relatively stable demand forces in these cities until mid-2006, when an unprecedented negative demand shock started an unprecedented decline in real estate prices, where, by the end of the decline,  the median homebuyer in low cost cities could buy the median home for 10% of their annual income - half the cost of renting.  That negative demand shock remains operative today.

But, I think, in the end what we have here is a peculiar interplay between supply and demand, which is due to the migration and income patterns that come from the extreme level of supply deprivation in the closed access cities.  I will save that for the next post.

Housing, A Series: Part 86 - Regional Inequality: The regime shift in American progress.

The subtitle of this article from the Washington Monthly (HT: EV) was so enticing: "Regional inequality is out of control. Here’s how to reverse it."  I first went to see if they would have any data on housing's role.  Soon, I realized I would have to read the whole thing only to confirm that they never mentioned housing.  They didn't.

They have properly identified the problem.  The author even recognizes the reversal of migration flows that now has households moving away from high income cities.  But, I will just say that the repeal of the Civil Aeronautics Board, the ICC's deregulation of interstate trucking routes, and the toleration of branch banking loom large in his list of causes.  I'm not kidding.  Click the link if you want more.

But, I mention the article because of this graph.  They truncated this graph to before 1980, when the convergence stopped.  This is out of BEA table SA1.  The regional inequality doesn't diverge again after the 1970's, so in all of the author's comparisons about recent rising regional income inequality, he compares cities like Houston and Atlanta to Washington, New York City, and San Francisco.

So, I downloaded the data to see how it looks after 1980.  On the regional level, I think we can see how the technological and commercial innovations that made the world a figuratively smaller place created a more equitable world.  (Or maybe it was the ICC, or 70% tax brackets.)  We are basically seeing the same phenomenon now, globally.

The regional inequality we have seen since then has been specific to cities.  But, on the scale of the metropolitan area, the added gross income for the highest income cities frequently goes to housing expenses.  I think much of the topic of the regime shift in income inequality before and after the 1970's relates to these factors.  Free economies naturally tend to produce convergence, and this was the case regionally until that convergence had generally played out.  Possibly, some divergence on the individual or household scale also tends to grow with economic expansion, and this was mitigated by those regional convergences until the 1970's.  A new phenomenon that seems to selectively infect cities across the Anglosphere is sharp limits on housing in high income cities.  So a regional phenomenon that reduced aggregate income inequality is largely played out, but a new localized phenomenon has caused aggregate income inequality to rise.

Convergence comes from free flow of capital and labor.  Everyone understands this, at least implicitly - this realization is a basis for nativism and protectionism.  When deregulation (unfettered immigration and trade) pulls the top 1% (the average American) down toward the mean, everyone understands how deregulated markets create income convergence.  (edit: This reflects the protectionist argument.  In most cases, I would argue that most or all of the convergence that comes from the flow of capital and labor is due to the mean rising.)

If we want to reduce measured inequality, we need to let labor flow to where it is valuable.  Here is a long term chart of population growth in selected urban counties.  There may have been a time when households were leaving for the suburbs.  But, nobody can argue today that these counties are not growing because nobody cares to move there.  In a way, this graph is a graph of American progress, or the lack of it.  An irony that makes this topic difficult to understand is that the cities that are impeding equitable progress are the cities with the highest gross incomes.

Maybe Bryan Caplan should be applying his open borders project to America's cosmopolitan cities.

Housing, A Series: Part 85 - Housing Prices were sustainable because of migration

I think the migration patterns of the closed access cities are an important and underestimated factor in the characteristics of the housing market.



Here is one of many strange patterns that we see in housing markets.  There is a positive correlation between incomes and Price/Income of local real estate.  As incomes rise in these cities, households don't just increase their housing budget proportionately; they spend more of their budget on housing.  I believe that this explosion of incomes in just a few cities is due to the constraint on housing.  The constraint on housing explains the higher incomes and the peculiar pattern of spending more of those incomes on housing.

Here we see that these outlier closed access cities have unusually high rents.  The high prices are based on rents and expected future rents.  (Washington, D.C. is a special case where high incomes are not caused by a housing constraint.)

Next we see that home prices are even higher in these cities than we might expect from the higher rents.  This implies that the cities with high rents also have high expected rent inflation.

The result of these relationships between price, rent, and incomes means that in these cities home prices are very high as a proportion of incomes.

It seems like there might be a sort of disconnect here.  If rents are already high in these cities, how can we expect rent inflation to continue?  I have even walked through a model of housing expenditures myself that says households reach an upper limit when rent affordability reaches a level 10% or 15% higher than other cities.  But, this is where migration creates a distortion in our analysis.

If rent as a proportion of income tends to run about 50% higher in the closed access cities than it does in the open access parts of the country, then we might expect home prices to be 5x or 6x income there instead of the 3x or 4x levels we see in the rest of the country.  So, housing selling for 9x or 10x incomes seems like it must be speculative and unsustainable.

But, the tricky part here is that the value of that home is based on the present value of its future rental income.  Under current policies, out-migration of financially stressed households and in-migration of high income households is inevitable.  It should be a part of home buyer expectations, and thus home prices.  This means that the income of the household who currently owns that house is not the binding constraint on its price.  The price of the house, and its future rents, should reflect the income of the household that will live in it 5, 10, or 20 years from now.  In the open access market that we tend to assume is operable, there is no persistent migration, so we can almost always assume that the income of the tenant household is stable.  But, because the tight constraint on housing in these cities will create a transition of higher incomes into the city, the Price/Income of the city's current inhabitants will be high, because they are living in a home that is likely to be sold to a higher income household when they are finally forced to migrate out of the city.  The housing market is so efficient that it has already priced in that household's future economic stress.

Median rent is now about 45% of an $80,000 median income in San Francisco.  What will happen is that migration will support an increase of 30% in rents.  Median rent will remain 45% of the median income, but the median income will now be $104,000, partly as a result of migration of low income households out of the city.  And, today's price is much closer to 6x that new household's income than it is to the current tenant's income.

It is common to point to these cities and claim that these high home prices are clear signs of credit-fueled speculation.  But, given the supply constraints in these cities and the ongoing population flows that result, what do these observers expect home markets to do?  Given the severe supply constraint, home prices that are unsustainable for their existing owners are a sign of efficiency.  The city itself is unsustainable for its current residents.  They have been and will be leaving.

Of course, in these cities homebuyers have to use much higher levels of credit and creative financing.  They have to buy a home at the price that reflects the future value it will have to in-migrating buyers.  They don't have a choice.  Given the severe supply constraint, high mortgage levels are a sign of efficiency.

And, of course, the real estate in these cities will be more volatile and more susceptible to a downturn.  They have the characteristics of a growth stock.  Their value is highly dependent on that future rent inflation.  Given the severe supply constraint, collapsing prices in response to a negative liquidity shock and income shock are a sign of efficiency.

A new economic letter from Glick, Lansing, and Molitor at the San Francisco Federal Reserve Bank (HT: CR) is almost a paragraph-by-paragraph example of how the assumption that these things are the product of lending and excess demand seems so irrefutable, yet is so wrong.  We were so convinced that the demand explanation was right that nobody bothered to realize that all of these facts are just as emblematic of a supply constraint.  We have been so sure of ourselves, that nobody has noticed how weird it is that the excess lending only applied to a few peculiar geographic areas.  We just thought that there must have been something in those areas that was especially enticing to those frothing speculators.

The letter references a Gelain, Lansing, and Natvik (2015) article that claims to reverse engineer the housing boom in a way that suggests loose lending standards were to blame for unsustainable home prices.  They claim that rational expectations models fail because they would require a rise in rental expense along with a rise in home values, and aggregate rent expenditures did not rise during the housing boom.  They find that a model dominated by persistent and backward looking buyer expectations and related changes in lending standards explains this behavior better.  They point out that several studies have found that home prices rose more sharply in areas where subprime loans were more prevalent.  But, it seems to me that they are assuming away the supply factor, and this causes them to reverse the causation on these factors.  Persistent buyer expectations of price appreciation, more lenient lending standards, and higher consumption of households in appreciating areas are all unsurprising outcomes from a housing supply constraint in a city with high demand for labor.

And, what the studies that saw these connections between rising mortgages and home prices should have also noticed was that those were areas with high rents and rent inflation.  What the authors failed to notice was that the stable rent/income ratio was achieved through geographically selective growth and migration - high income households bidding up rents in the closed access cities and middle income households building new homes in open access cities.  More than 80% of new homes built during the boom were built in areas with little or no home price appreciation.  (I touched on this in the last post. I hope to follow up on it some more in an upcoming post.)  Why didn't it strike anyone as strange that in all of those cities with sharply rising mortgages and home prices, where the demand excesses were supposedly centered, there were relatively few new homes being built?

Disaggregating by city, we can see quite clearly that home prices and rents were highly correlated.  Rational expectations certainly describes the pattern of prices and rents between cities.  Here is a comparison of the top 20 MSAs by home price and rent in 2005, at the top of the market.

Looking at rent 10 years later, in 2015, compared to 2005 prices, we see that even after subsequent rent appreciation, there is a systematic relationship between price and rents.  Rents have risen proportionately to the peak prices, even though (1) the patterns of rent inflation and population migrations were interrupted by the recession, reducing increases in rents in the closed access cities, and (2) continued repression of the mortgage markets has caused rents to rise unnaturally even in the open access cities.

But, even with those factors at play, obviously there were strong connections between price and rent appreciation during the boom.  The model that the article develops specifically favors the lending standards explanation for the boom because it results in a disconnection between home prices and rents and rejects a rational expectations explanation because that results in a connection between prices and rents.  That does appear to be what happened in the aggregate data, but when we disaggregate by city, their model doesn't describe price and rent behavior anywhere.

Back to the FRBSF letter:

An accommodative interest rate environment combined with lax lending standards, ineffective mortgage regulation, and unchecked growth of loan securitization all helped fuel an overexpansion of consumer borrowing. An influx of new homebuyers with access to easy mortgage credit helped bid up house prices to unprecedented levels relative to rents or disposable income. The run-up, in turn, encouraged lenders to ease credit further on the assumption that house prices would continue to rise. Similarly optimistic homebuilders responded to the price signals and embarked on a record-setting building spree...

Disaggregating by city, we can see that this is incorrect. The influx of new homes was almost completely within the parts of the country that saw moderate price increases.  The price run up and the construction boom happened in different places.  Homebuilders did not respond to price signals.  They built in the lowest cost cities.  There was no record-breaking building spree where prices were high.

But when the various rosy projections failed to materialize, the housing bubble burst, setting off a chain of defaults and financial institution failures that led to a full-blown economic crisis.

Here is a chart comparing the prices of the median home in each MSA in 2005 near the peak of the boom with the subsequent change in price.  Not only have rents continued to climb, but as we have escaped the liquidity crash, home prices have recovered at least as strongly for high priced cities as they have for low priced cities.  Except for the projections of a stable money supply, what projections have failed to materialize for home buyers in the boom?  Vacancy rates have tended to remain low in the closed access cities, and rent inflation rose sharply in 2006 and early 2007 after housing starts collapsed.

In contrast, the recovery in new housing starts has been more sluggish; the series remains roughly 50% below its prior peak—suggesting that homebuilders are exercising caution in light of the substantial overbuilding that occurred during the mid-2000s. The pattern in Figure 1 also suggests that there may be further upside growth potential for the housing market; continued high house prices should contribute to more building activity and more construction jobs.

In the decade from 1995 to 2005, in New York City and coastal California, where Home Price/Income reached an average of 9x at the peak, there were 2.8 housing permits issued for every 100 residents.  In the rest of the country, where the average Price/Income never reached 3x, 7.2 permits were issued per resident.  Homebuilders aren't exercising caution.  Lenders are.  There was no overbuilding related to high prices.

I really want to try to be polite here, because really we have all missed the boat on this issue, but I just have to point out that this is the San Francisco Federal Reserve Bank.  Everyone involved in preparing this analysis about "substantial overbuilding" triggered by high prices that were unmoored from rents, at the end of the day, turned off their computers, walked outside, and went home to the most expensive, constrained, undersupplied housing market with the highest rents that we have ever managed to conjure.

Depending on whether their analysis is correct, their closing sentence: "Nevertheless, given that housing booms and busts can have significant and long-lasting effects on employment and other parts of the economy, policymakers and regulators must remain vigilant to prevent a replay of the mid-2000s experience." is either the most comforting or the most frightening economic statement you will read today.

Housing, A Series: Part 84 - The Two Housing Markets and the Crisis Timeline

I have been looking at the housing "bubble" among the different metropolitan areas (MSAs).  The data points to a housing "bubble" that comes from an error of aggregation.  We had two housing markets - a closed market where there was massive price appreciation, and an open market where there was healthy expansion of the real housing stock.  When we statistically mushed these two markets together, we thought we had one housing market where housing expansion and price appreciation seemed to be related.  As with so many issues on this topic, we were fooled into a conclusion that was precisely the opposite of reality.

Here is a scatterplot of the largest 20 MSAs, comparing the relative amount of building permits allowed from 1995 to 2005 to the change in the Home Price/Income for that metro area.

There was a fundamental shift in home values between 1995 and 2005.  There are several things going on here.

1) In 1995, Price/Income was 2x to 4x in most cities, and there was little difference between cities, whether it was Detroit or Boston.  This is the picture of a housing market that we took for granted, and the unhinging of the national housing market from this anchor over the following decade is the central piece of information at the center of subsequent interpretations of the economy and public policy.

2) The explosion of housing expenses in the closed access cities is of a wholly different magnitude than the rest of the country.  Price/Income reached 10x in the California closed access cities.  These are the cities of the housing price bubble.

3) The other 16 of the largest MSAs also saw a rise in Price/Income.  Some of this is due to closed access policies, zoning regulation, and inertia in housing expansion.  The three cities of these sixteen that rose above 6x are Boston, which has the signature of a closed access housing market, but to a lesser extent than the worst cities, Riverside, which has allowed some population growth but tends to share the sorts of housing affordability problems that occur throughout California, and Miami, which is a city I haven't quite put my finger on.  The other MSAs rose fairly uniformly from a typical level of just under 3x to about 4x.  During this period, rent also increased as a proportion of incomes by about 10% across cities.  So about 0.3x of the increase in Price/Income is a reflection of higher housing expenses in general (in terms of rent).  The remaining increase in Price/Income, which still amounts to an increase of more than 1x (or about a 30% increase in home prices) in these cities is a combination of the effect of low long term interest rates on the intrinsic value of homes and the closed access policies that were in place in cities like Boston.  I have looked into the math in other posts.  Here, I just want to repeat the point more generally.  The total amount of the housing "bubble" in these cities that can be attributed specifically to demand-side excess among homebuyers, would be the increase in Price/Income that remains after factoring in these other issues.  The precise number would depend on the specifications of your model, such as the effect of long term real interest rates on the intrinsic value of homes.  But, even among these cities, that probably amounts to less than 10% of home prices, even in 2005 - a rounding error in the broad scheme of things.  Certainly not the central factor of the story.  And certainly not a reason to point to lending excesses as the cause of the episode.

Change in P/I 1995-2005

4) The lowest dark circle in the P/I graphs is the US aggregate value.  The two purple diamonds are the values for (1) the US outside the 4 closed access cities I have highlighted and for (2) the US outside the 20 largest MSAs.  The four main closed access cities amounted to about 14% of US population in 2000 and the twenty largest MSAs amounted to about 38% of US population.  In 1995, these three groups all had similar values from 2.4x to 2.8x.  By 2005, US Price/Income had risen sharply from 2.8x to 3.9x.  If we only remove the 4 largest closed access cities, P/I rose from 2.5x to 2.9x, a rise of only 0.4x.  In other words, nearly 2/3 of the aggregate national increase in home prices/incomes came from those four cities.  If we remove all 20 of the largest MSAs, P/I in the rest of the US (which includes more than 60% of the population), actually fell from 2.4x to 2.2x.  And remember that this was during a period of falling long term real interest rates when we would expect P/I to rise in a normal, efficient market.  Some of this decline is due to a small decline in rent/income over that period.

This is our two part housing boom.  In the closed access part, most prevalent in New York City and coastal California, there was little supply.  The boom was entirely a pricing boom due to supply deprivation which was not related at all to expanding housing starts.  In fact, it was due to a dearth of housing starts.

In the open access part, most prevalent outside the 20 largest MSAs, markets operated just as we would expect them to.  Lower long term real interest rates led to healthy expansion of the real housing stock and rents declined slightly during the boom.  Home prices didn't rise in these areas, relative to incomes, because the increase in housing consumption came through new building.  Households had better shelter for lower cost.

In between these two markets, the other 16 of the largest MSAs reflected some combination of these markets, but generally they were much more like the open access part of the country than they were like the closed access part. Some of the price appreciation in places like Phoenix and Riverside, CA seems to have been related to the level of out-migration from coastal California reaching high enough levels that local bureaucracies couldn't meet demand for permits.  In 2005, when Phoenix briefly saw a spurt of unusual home price appreciation, builders simply couldn't get new lots permitted quickly enough to accommodate the inflow.

Source

This relates to one of those pieces of information that should have had all of us perplexed, if we hadn't been so convinced of the demand-side story.  The Case-Shiller 10 cities, which includes the main closed access cities, saw the sharpest price increases during the boom.  The national Case-Shiller measure of home prices was more subdued.  But, the strange thing that nobody seems to have noticed was that new home prices were increasing at an even slower pace than measures of national aggregate existing home prices.  If banks were pressing households into inappropriately overvalued homes, the increase in the housing stock would have been reflected in strong new home prices.  But, looking at this through the lens of the two separate housing markets, the strength of the new home market was an entirely separate event from the rising prices in the Case-Shiller 10 cities.  Housing starts were strong because houses in the open access cities were cheap!

Source

It's worth pondering, here, the timing of events in the financial crisis.  Mortgage debt service began to rise in late 2004, as the Fed began to raise the Fed Funds Rate.  Looking at this as if it was a national market where demand-side pressures and demand from low mortgage rates were pushing houses to unsustainable levels, this seemed like the inevitable result of households continuing to speculate and to draw from their housing "ATMs" in a desperate attempt to prolong the bubble.

But, we need to separate the country into closed access and open access markets.  Zillow has a "mortgage affordability" measure.  This is basically what the Mortgage Debt Service measure would be if every household had a mortgage at 80% LTV.  The blue lines here are the open access cities.  These are the cities where houses were being built.  The median household in the median home in those cities with a 20% down payment would have had a debt service ratio of 20% or less.  (An aside: note that when we separate the market into closed access and open access, the size of down payments as a factor becomes irrelevant.  Even with 95% LTV, mortgage service levels in the open access cities would have been moderate.  I haven't seen city-by-city data on the prevalence of subprime loans, but I suspect that the sharp rise in subprime loans from 2004 to 2006 was very focused on the closed access cities.  Entire metro areas had homes selling at 10x income.  A 20% down payment in that context would be 2 years' income!  It could be that FHA and Ginnie Mae underwriting guidelines simply made most homes in these cities unattainable through their programs, so that private markets developed to meet demand.  Some research has suggested that timing had much to do with the higher rates of defaults among the subprime securitizations, but if my intuition is correct, this would mean that when the bust hit, geography was working against the subprime MBS's also.)

In the open access cities, households easily adjusted their marginal real housing investment.  Fixed mortgage rates didn't actually rise very much, so not much adjustment was necessary.

In the closed access cities, this made a bad situation worse.  Low and middle income households were at their upper limit of housing expenditures, but the housing market in these cities was buoyed by high income migrants who could move into the city when locals were priced away.  The economy was expanding and incomes were still rising.  Until the end of 2005, the migration pattern remained.  I think this is why we see the strange late-boom behavior that cycled through the Inland Empire, Las Vegas, and Phoenix.  Californian households were fleeing the ratcheting costs.

By early 2006, the Fed Funds Rate had been pushed up so high that the yield curve was inverted, and as that happened, housing starts began to collapse, home prices leveled off, and rent inflation shot up.  Nominal income growth had remained strong, but real income growth was disappointing.  But, over this time, what was happening was that more and more income growth was going to rent.  Non-shelter inflation peaked in 2005.  New income was being captured by closed access city real estate owners, and a country that was blaming all the wrong causes for the problem was demanding that the Fed push on the brakes.

Fed Funds Rate, Forward 5 year and Forward 10 year rates

It is easy to blame the Fed for the costly errors of late 2008, and it is even possible to see those mistakes as early as late 2007, but I think when we remove the false narrative of a housing bubble as a cause of the recession, we can see these errors going all the way back to early 2006.  The universal error in seeing a housing demand bubble where we had a housing supply bust meant that we didn't see obvious signals of a breakdown.  That sharp drop in housing starts beginning in 2006 was a bright red flag of monetary instability.  Home prices remained fairly level until later in 2007, but rent inflation was surging.  So, Price/Rent and Price/Income levels were falling sharply.  Since the collapse in liquidity was due to national policy, these price ratios were falling even in open access places like Dallas, Houston, and Atlanta.  Forward interest rates were not rising along with the Fed Funds Rate, so the intrinsic value of homes was not falling.

If we can't build homes in California and New York City, then our second-best solution is to build them everywhere else.  This means that economic growth will not be shared with low income households in Silicon Valley and New York City.  Economic growth will create economic stress for them, until the stress is relieved when they move away to make room for new households that can leverage the value of the local skills networks in those cities.

Since we can't build homes there, and since we misdiagnosed the problem, we decided, tragically, to shut down homebuilding across the country.  This has now been the case for nearly a decade.  During the housing boom, rising home prices were a sort of measure of how much stress families would take before they would finally migrate.  Households were migrating from cities where rent took 30-40% of income to cities where rent only took 20-25% of income.  Now, rent in our formerly open access cities takes 25-30% of income, and rent in our closed access cities is up to 40-50%.  The tension was high enough in those cities when you could at least build a suburban house in Dallas and start fresh.  Now, we have taken that option away from many families.

The reason the recession was so deep was because the only way to stop the aggregate increase in home prices was to hobble the economy so badly that our best industries were too weak to entice highly skilled workers to our closed access cities.  Many people believe that the housing bubble caused an inevitable recession.  People like Scott Sumner argue that there was a housing correction which might have only led to a slight recession, but that Fed errors in 2007 and 2008 led to a deep recession that was unrelated to the housing bust.

I think we must consider taking this a step further.  The Fed created an economic downturn which led to the housing bust.  In fact, short of a revolutionary and unlikely change in the local politics of our closed access cities, this was the only way to create a housing bust.  The nation demanded a housing bust, really.  And, so the Fed kept pulling back on the money supply and saying, Yeah, we figure housing prices are probably due to fall quite a bit - all the while mistaking the rent inflation that was the result of their error as a reason to double down on their error.

They had little choice.  Any economic recovery would have led rising rents and prices for houses in the closed access cities, and those stressed out households would have argued, with deep anger, that the Fed was fueling a bubble to keep their Wall Street buddies happy while working families struggled.  In the end, they received the same criticism anyway, even though they pulled back so hard that they wounded the banks, along with everyone else, including many open access families who were simply moving along in a pretty functional economy until the dominoes started to fall.

Source

I think the CPI inflation indicators point to a just-so story of the course of events.  The Fed pulled currency out of the economy as recovery was developing coming out of the previous recession, out of fear that credit creation in the housing market was fueling inflation.  Until the end of 2005, households were able to counter this with creative financing that allowed the housing market to continue to expand functionally.  Financing had become more expensive, though, which pushed closed access homebuyers more strongly into lower cost tertiary markets like the Inland Empire and Phoenix.  By 2006, the liquidity pullback had become sharp enough that there was no new funding for homebuilding.  Home prices leveled off and housing starts collapsed, but incomes were still strong enough from an otherwise strong economy that households continued to bid up rents, even though hobbled credit markets meant they couldn't bid up home prices.  Core inflation outside of rent (the purple line) dropped.  By 2007, incomes had been damaged enough that households could no longer bid up rents.  By mid 2007, some households were beginning to have trouble making payments.  The combination of the lack of credit and falling incomes, along with the first increases in defaults, meant that there was no longer enough demand to even support the market for existing homes, so home prices and rents began to fall sharply.  However, the drop in owner-occupier imputed rent levels was due to dislocations from the liquidity crisis, not housing oversupply, so tenant rents ("Rent of Primary Residence") remained elevated until 2009 when the last major Fed errors finally caused even the nominal demand for rental housing to collapse.  (This period provided another bright red flag when home prices and long term real interest rates were both collapsing.  Yields on homes were shooting up while real yields on long term bonds were falling down.)  In late 2007 and early 2008, the Fed provided enough accommodation to allow non-shelter inflation to stabilize, but the lack of support for housing credit meant that home prices continued to fall.  Then, in late 2008, one last liquidity shock sent the economy over a cliff.  Since the crisis, we have continued to enforce deep cutbacks in housing credit, creating a national housing shortage, so that rent inflation has resumed its upward march, especially for tenants.  Incomes have been hurt by the lack of a strong construction market.  Much of the  income growth that we have managed to create accrues to landlords - now across the country, not just in the cities with local housing constrictions.

Source

Here is a graph of real and nominal GDP growth, Year-over-Year.  NGDP growth moved below 5% by the end of 2006 and hasn't recovered above that threshold even now.  Real GDP growth had been falling since 2004.  The exact timing of recessions is somewhat semantical, but my point here is that it is quite easy to point to broad economic weakening in 2006.

Much of the growth in incomes in New York City and California are really value added that should accrue to consumer surplus, but limited access to those labor markets means that some portion of our marginal economic growth registers as inflation, captured by laborers and real estate owners in those markets as economic rents from closed access.

Housing, A Series: Part 83 - Mortgage Affordability vs. Rent Affordability

One measure we might look at as a sign of a housing bubble is the ratio of mortgage payments to rent payments.  If households were bidding up the prices of homes as owner-occupiers in an unsustainable speculative bubble, we might expect to see mortgage expenses rise relative to rent payments.

Zillow tracks a measure of mortgage affordability, which is the monthly cost of a 30 year fixed mortgage on the median home, with 20% down, as a proportion of median income.  They have a similar measure of rent affordability, which is the monthly cost of rent on the median home as a proportion of median income.

Here is a graph of the ratio of mortgage affordability to rent affordability, for the US, the US with NY, LA, and SF removed, and for NY, LA, SF, and Washington DC.

Note: scales aren't calibrated.  M/R ratios of cities on the left scale
do not correspond to expected inflation on the right scale.

The main difference between rent and mortgage payments is that rents rise with inflation and mortgage payments are fixed, so in an efficient market this ratio is a rough measure of expected rent inflation.

Nationwide mortgage/rent ratios were about the same in 2005 as they had been since 1990, and rent inflation was about the same in 2005 as it had been since 1990.  Some might want to make the argument that Fed policy was pulling down interest rates, which created the bubble by pushing mortgage rates lower.  I would argue that the Fed has little control over 30 year mortgage rates, and that if Fed policy really was loose, 30 year fixed rates would rise due to inflation expectations.  But, even taking that criticism on its own terms, the Mortgage/Rent ratio reached a low point in 2003.  Even if mortgage rates had been at levels similar to the 1990s, the national Mortgage/Rent ratio would have been within the normal range.  And, by the time the ratio reached the top of the range in early 2006, short term interest rates had reached their high point and monetary policy could not be described as loose.

Mortgage/Rent ratios in the closed access cities are much higher than they are in the rest of the country, and they rose more steeply during the housing boom.  As with so many of the indicators I have looked at, there are two stories here.  There is the supply story in the closed access cities.  Then, there is the rest of the country, where there is little indication of any unusual activity.

I have included Washington, D.C. in this graph.  It is slightly different than the other closed access cities.  In the closed access cities, the cost of housing is capturing economic rents from geographically captured industries.  Incomes are being pushed up by housing costs.  In Washington, the causality is the other direction.  High incomes are pushing up housing costs as households use their rising incomes to bid up preferred housing units.  That means that rent inflation has been high in Washington, but rent expense has remained low as a proportion of income.  In this measure, Washington looks like the other closed access cities, because the high Mortgage/Rent ratio is a reflection of expected future local rent inflation.

In upcoming posts, I plan on comparing permits for new homes to housing affordability.  One way in which the aggregation of these two housing stories led to a mistaken interpretation is that in the closed access cities, prices were being bid up, but this was dominated by existing sales.  New sales were overwhelmingly in the open access parts of the country.  When these data were aggregated, it was easy to believe that the rise in new housing starts was related to households over-borrowing and overspending on housing.  But, when we keep these stories separate, what is clear is that new homes did not have the characteristics of the aggregate data.  New homes were being built in the inexpensive parts of the country at reasonable prices.

Here, as with all the other scatterplots of city housing data, we can see the two stories - the open access story, where population flows between cities with relatively equalized costs, and the closed access story where constricted cities create wild upswings in valuations.  These graphs plot cities based on housing permits issued from 1995 to 2005 (x-axis) and the increase in the mortgage affordability index from 1995 to 2005 (y-axis).  The first graph is based on permits as a proportion of 2000 population.  The second graph plots the cities based on the raw number of housing permits issued.

Just over a million permits were issued in the largest closed access cities.  In those cities, the median mortgage in 2005 claimed from 14% to 30% more of the median income than it had in 1995.  Over 18 million permits were issued in the US during the same period, around 17 million outside those cities.  And mortgage payments for those 17 million new homes only claimed about 2% more of the median income in 2005 than they had in 1995.  On this scatterplot, we can see places like Phoenix, Atlanta, Dallas, and Houston, where these millions of new homeowners were buying homes at relative valuations much lower than the closed access cities.

Just to be thorough, here is a similar graph, using the mortgage/rent ratio that I used in the first graph above.  Where housing can expand, mortgage/rent affordability was stable.  Where costs rose sharply, housing permits were low.  (The three cities that appear to have rising costs in these graphs along with the main closed access cities I have highlighted are, from left to right, Boston, Miami, and Riverside, CA.)

The housing boom in prices was part of a different story than the housing boom in new construction.  I hope to dig a little deeper into this over the next week.

Housing, A Series: Part 82 - The Components of Home Yields

Today, I'm going to step back a bit and think about the components of the implied yield on home ownership.  Here is a diagram of the basic outline of home yields.

At the core of an efficient home market is the double trend toward no-arbitrage home prices.  In a market with unconstrained supply, the Real Net Yield / Price of homes in the aggregate should move with other similar discount rates.  Over time, this rate of return on homes appears to move roughly in parallel with risk free real long term interest rates, with a small added spread.

We tend to think of the price as the dependent variable in home valuations, but home prices also have a natural arbitrage tendency with the cost of new supply.  This is especially the case for homes where most of the value of the homes are based on the structures, as opposed to the lot or the location.  In that context, home prices are also roughly tethered to the cost of similar new homes.

Falling interest rates correspond to rising Price/Rent levels.  But, in an unconstrained market, with these dual arbitrage forces, prices should not be able to rise.  The rise in Price/Rent would have to come from falling rents.

This is one of the tragedies of the housing boom.  The main effect of lower long term real interest rates on housing should have been a broad decline in rental expenses, which would be especially helpful for lower income households.  This should have been a period where low inflation reduced de facto income inequality and pushed material quality of life higher across the income scale.  But, instead supply constraints in a few cities undermined the arbitrage factor that normally would moderate home prices, so that in those cities, rents remained level and home prices rose.

One way we might think about the problem of housing supply constraints is that as the value of the property moves above replacement value and as location value becomes a larger portion of the total value, the price of that property will become more sensitive to interest rate fluctuations and less sensitive to the moderating influence of new building.  Here is a scatterplot of the largest 20 metro areas, where rent affordability in 1995 is a proxy for supply constraints, and I compare this to the change in home prices from 1996 to 2005.

There is a strong relationship here.  This is just one more way to view the housing boom through the lens of supply constrictions.

We can think through the effects of different changes in an unconstrained environment vs. a constrained environment.

In an unconstrained environment, the median household tends to keep housing expenses at about 20% of income.  So, if we think about the diagram above, falling long term real interest rates would cause both net and gross rents to drop, relative to prices.  But, since the median household in these cities tends to prefer more housing consumption when the budget allows for it, this will have the effect of increasing demand.  So, households will push total rent expenses back up - but not by pushing home prices up.  This will happen through an increase in the quantity of homes "consumed" or lived in.  So, if nominal rent expenses remain a constant proportion of incomes, lower interest rates will cause rents of existing homes to fall, prices in existing homes to remain level, and new homes to be built to accommodate the growing demand.  In fact, housing demand might be a little inelastic.  If households can rent much nicer homes for the same amount of money, relative to other expenditures they have, they may even increase their total housing consumption, in rent terms, as a reaction to lower long term interest rates, even if the first order effect is for rent to decline.  (By the way, this would be capital intensive, and should push up real long term interest rates.  The fact that we have undercut this potential adjustment from the economy since the crisis could be a significant factor in the unusual decline in long term interest rates since 2007.)

Here is a graph comparing Home Price / Median Income in the main closed access cities to the main open access cities.  Very late in the boom, Phoenix did see a bit of a bump.  Even this was related to at least a temporary supply constraint.  But, I think this generally is a pretty stark picture of two housing booms that had little to do with each other.

And, next is a graph of rent affordability in these cities.  Rent inflation was moderate during the boom in Dallas and Atlanta (and Phoenix until late 2005 and 2006), so the stability in rent affordability reflects real increases in housing growth.  Price/Rent levels tended to rise, at least moderately, everywhere, real rents increased, rents on existing homes were falling relative to other prices, and housing starts were strong.

Source

This is the picture of a normal, functioning, open economy that happens to have low real long term interest rates.  If the national statistics were more a reflection of these cities, would anybody be calling this a bubble?  If out of control banks, if a bubble in AAA rated securities, if a decade-long run-up in private-issue securitizations and subprime loans were the source of the housing "bubble" wouldn't we expect to see broadly similar behavior throughout the country?  Yet, what we see are quite normal behaviors in the majority of the country and very extreme behaviors in a few cities that have notorious housing problems.  How did this ever look like anything but a supply problem to anyone?

Notice that rental affordability and rent inflation are both high across the board now.  Nobody lives in an open access housing market now.

Going back to the beginning diagram, let's think about what happens in a closed access city when long term real interest rates decline.  Nominal rents will still remain stable.  But, since there is little new homebuilding, in those cities the Price/Rent ratio increases through rising home prices.  And that is basically what we saw.  The most significant trend was the rising prices and Price/Rent ratios in the problem cities.

Here is a graph of rent inflation relative to core inflation, for the US, the 8 cities from the Case-Shiller 10 index that have CPI rent inflation data for the period (which includes the largest closed access cities), and an estimate of inflation for the US outside those cities.  Rent inflation was high in the closed access cities, but it was declining.  This is partly because of the aftermath of the internet bubble in Silicon Valley.  But, I think partly what we are seeing is the reaction of households to falling rents in open access cities, which was drawing households away from the closed access cities.

Source

The housing boom coincided with net migration out of the closed access cities because low long term real interest rates provide a relative cost of living savings in housing - but that can only happen in open access areas where there is not a constraint on housing supply.  The relative value of housing was improving in the open access areas, so this naturally created a draw from the closed access areas.  This relieved pressure on rents even in the closed access cities.  The fact everyone notices is the liquidity provided by the housing "ATM", but this seems to be rarely noticed.  The housing boom was disinflationary.

Look at rent inflation since 2008.  That is what a demand shock related to the national banking sector looks like, with rents rising in lockstep - except we have created a negative demand shock where there never was a positive demand shock.

Taking one last look back at the first diagram, I want to think about taxes.  When I first started this project, I expected them to be at the center of the story.  They may push owner-occupier prices up by 10% or more.  I still think they are worth thinking about, but their effect pales compared to the supply problem and our misdiagnosis of it.

Tax breaks - the largest of which is the non-taxability of imputed rent - have the same effect as falling interest rates.  In housing, these breaks tend to accrue only to owner-occupiers.  As with lower interest rates, the long run effect of tax breaks is probably mostly to increase housing demand from owner-occupiers, which is accompanied by rising Price/Rent ratios.  I think this might further bifurcate housing into multi-unit rental housing and single-unit owner-occupier housing, because in efficient markets landlords can't compete with owner-occupiers on an after-tax basis.

Property taxes, on the other hand, don't affect Real Net Yields or Price/Net Rent, but increasing property taxes increases gross rents and decreases Price/Gross Rent.  Property taxes will generally increase rent expense for both owners and renters.  This is regressive for two reasons.  First, low income households spend more on housing than high income households.  Second, because low income households tend to be closer to their minimum comfort level of housing expenditures, which is why they spend more of their incomes on rent, they also have more inelastic demand for housing, so they will tend to adjust their housing consumption less in the face of higher taxes.

I think the only realistic way to remove the tax benefit of imputed rent for owner-occupiers is to stop taxing capital income, or at least stop taxing real estate income.  This could be paired with increased property taxes.  Even though property taxes are quite regressive, I think this arrangement would be much less regressive than the arrangement we have today.

With home prices so far below intrinsic value, a switch of this kind now would not be as much of a shock as it normally would be.  And, if we aren't going to allow middle class households to take out mortgages any more, this would level the playing field to encourage continued expansion of the single-unit rental market.

Ps. It may seem like higher property taxes would help solve the closed access city problem by lowering home values.  But, since it would only lower values by reducing housing demand through higher gross rent expense, it would mainly be making the cost problem worse, leading to more stress for low income urban households and more migration between closed access and open access cities.  On the other hand, if higher public revenues through property taxes or development fees could incentivize cities to allow more building, then maybe higher housing taxes could be part of a grand solution.

Housing, A Series: Part 81 - The Cost of Access

Following up on yesterday's post, I want to look at the shape of incomes over time in various metro areas some more.  I am using data from the top 97 metro areas that have data for this time frame in the Zillow database.

One of the interesting aspects of recent increases in income inequality is that the source of changing distribution of household incomes seems to be a similar change in the distribution of firm incomes.  Also, as I have found, and as Matt Rognlie found with much more detail and sophistication, the coincidental shift downward in labor incomes was largely a shift to real estate income, not corporate income.  Recently, researchers who have been focused on income inequality have also been coming to the conclusion that it is mostly a shift within labor income, not so much an increase in the share of income going to employers.

I find that income by city shares this same trend of increased variance.  A few cities at the top of the distribution have been exhibiting income growth unrelated to the rest of the country.  I believe that all of these findings tie together to point to one source of the problem - housing constraints in our most productive cities.  This leads to a high level of income for firms and workers in these cities and a transfer of income from laborers to real estate owners.  The localized housing constraint is a cause that can explain all of these patterns.

Here is a graph comparing 97 metro areas, ordered by median household income as a proportion of the national average, in 1979 and 1995.  The next graph shows the same cities, in the same order, but in that graph, the y-axis is the median household income after rent expenses.  There was not a housing constraint problem during this period.  There was a slight rise in the variance of median household incomes between cities.  So, the highest income cities saw incomes rise slightly more than other cities.  And, as the next graph shows, incomes after rent followed the same pattern.  Since these cities are ordered by gross income, the second graph is a little messy.  I have fitted 3rd degree polynomial lines to the distributions to get a cleaner picture of the general trend, and we can see from those lines that the shift in incomes after rent mimics the shift in incomes before rent.  Households in more productive cities were retaining those income gains, but the income gains were slight.

Next, we move to the same two graphs, except this is for the period 1995-2015.  Here we see a sharper divergence of the top cities.  Income inequality between cities increased more during this period than it had before, but that increase is concentrated in the few highest income cities.  However, this is reversed when we look at incomes after rent expenses.  The top two cities fared well (San Jose and especially Washington, DC), but for the other 95 metro areas, the change in income distribution after rent is the reverse of the change before rent.  The poorest cities actually gained on the average, and high income cities lost.  In other words, workers in the high income cities were paying all of their income gains, and more, to their landlords (which in many cases are themselves).

Households in San Jose retained some of their additional income because there was still some positive relative population growth there in the 1990s, allowing some relief in the real estate bidding war.  The new housing stock would have tended to supply very high income households who were moving into the area.  I expect San Jose to revert to the pattern of the other productive cities as the city matures and succumbs to political obstacles to growth in its housing stock.  The economic rents captured by the median household in the Washington, D.C. area are retained by the household because the economic rents there are not caused by the housing constraint; they are created by other factors, presumably largesse related to the federal bureaucracy.  I'm sure, according to the theory of efficiency wages, this will lead employees of Washington's main industries to work even more diligently to keep supplying the rest of us with the blessed fruits of their labors.

Here is a graph that combines the graphs above for 1995 to 2015.  I have labeled the 2015 Income after Rent points of the problem cities.  Except for Washington and San Jose, what we see is that during this period, household median income among most cities didn't change much, either before or after rent.  The strange behavior in Income after Rent comes from these few problem cities.  In New York City and the California cities, housing costs were high in 1995, and they increased so sharply from 1995 to 2015 that Income after Rent in these cities dropped by 7% to 14% of the national average over those twenty years. (We can see several cities that had unusually low incomes after rent in 1995 which recovered by 2015 - the dips in the light blue line.  These cities were characterized by high housing costs that declined over this time.  They tend to be secondary cities in California and New England.  I am not sure how that peculiar signature relates to the rest of the story.)

Residents of those cities really are experiencing a different economy than the rest of us.  They really do live in cities where middle class households have experienced two decades of decline.  This decline now dominates our national political conversation, but it has little to do with national policy.

Here are a few more graphs that may help to highlight the pattern.  The first is a graph (in current dollars) of the annualized growth in median income, rental expense, and income after rent for the US and the closed access cities.  We can see here again how high gross income growth did not translate into high income growth after rental expense.  The US median annualized income growth during the period was about 3% before and 2% after rent.  New York and San Francisco saw about 5% growth before and about 1 1/2% growth after rent.  These are nominal dollars, so the median families in those cities have seen falling real incomes, after rent, for 20 years!  And, it is worse than that.  Since this problem creates a steady migration flow of low income households out of these cities and high income households into these cities, a household over time that remains in the city will be moving down the distribution over time.  The household with income higher than 60% of the other households in New York or San Francisco in 1995 was probably below the median by 2015.  In other words, the income growth of the median household may overstate the experiences of the typical households.  (This may be mitigated by other factors like lifecycle income patterns.)

Here are some other graphs.  I was hoping that I could include real-vs-inflationary effects in these graphs, but there is just too much of a difference between aggregate national expenditures and median expenditures to do that easily.  I think it would be a useful exercise, but it would require a lot of work to estimate inflation specific to the median household.  (Here is an interesting recent paper <HT: John Wake> on this topic that deals with the compositional effects of rent inflation, since new housing tends to be higher value housing.  I think the composition of households within cities also has an effect on measured rent inflation.  But, to be honest, I haven't been able to wrap my head around this issue.)

The first graph is in nominal terms, for the US from 1995 to 2005 and 2005 to 2015.  The x-axis is the growth in the nominal median income.  The y-axis is the growth in nominal median income after rent expense.  The idea here is that, the square indicator represents the potential growth in income after expense if households do not increase rent expense at all.  In a static context where households maintain a constant proportion of housing expenditures as incomes grow, we would expect rent expense to grow along with incomes so that income after rent falls near the 45 degree line.

We can see that this pattern held for the aggregate national data from 1995-2005.  Rent inflation was high during this period, so contrary to conventional wisdom, households were not increasing their real consumption of housing.  They were not moving into more valuable houses (by rent).  They were living in homes that, on average, were less valuable (by rent) in real terms, but rents were rising faster than the pace of inflation.  But, in nominal terms, housing expenditures were rising in step with incomes.

From 2005-2015, first, we can see that income growth has been very low because of the Great Recession.  But, in addition to that problem, the collapse of the US housing market has led to rising rents nationwide, so that income growth after rent is not even keeping pace with the low level of gross income growth.

The next graph looks at the closed access cities in terms of growth relative to the US median household for the entire 1995-2015 period.  In other words, this is how the median household is faring in these cities compared to the median US household that already has income after rent that is lagging gross income.  The measures in this graph are the change in median income relative to the US.  For instance, San Francisco's median income grew from 137% of the US median to 153% from 1995 to 2015 - excess growth of 11.2% (153/137).

As with the previous graph, the top square is the rate of growth in income after rent these median households would have received if they did not increase their rent expenditures, relative to the US average, over this time.  As above, in a world with stable proportional spending, we would expect households to increase their housing expenses, on average, at a rate similar to income growth.  So, in an unconstrained world, the circles would fall near the 45 degree line.  In other words, we would expect incomes after rent expenses to grow at a pace similar to gross incomes.

Looking at Washington, DC, as I did in the previous post, we have an exogenous influence on incomes that has created tremendous income growth there relative to the rest of the country.  And, here, Washington looks like an open access city, with income before and after rent growing at similar rates.  But, in Washington, this is practically all inflationary.  Households are bidding up housing stock in prime locations with their new higher incomes.  Washington is a special case where, because the income growth is unrelated to housing, the higher incomes are leading to higher rents in the closed access parts of the metropolitan area.



Boston and San Jose are closed access cities that haven't quite reached the tipping point where all income gains go to real estate owners.  The median households in those cities retained a small amount of their income gains.  In San Jose, incomes rose 23% faster than in the rest of the US, but the median household only retained 6% extra income growth after rent expense.  The migration patterns are especially strong in San Francisco and San Jose, so much of the income growth there is probably compositional - high income households moving in and low income households moving out.  So, San Jose is realistically probably in the category with San Francisco, LA, and New York City as experienced by households living there.

Those cities are in a category where housing is so constrained that real estate owners are capturing all of the relative income gains plus additional income, leaving households poorer after housing expenses, even if they have higher gross incomes.  In these cities, I think this evidence points to a reversal of causation compared to Washington, DC.  The lack of housing is pushing up costs.  As long as local industries are capable of retaining some economic rents as a result of the local closed access policies and firms in other locations are unable to compete away those rents, then much of those excess profits must flow to labor to entice workers to the closed access city, and those extra wages then flow on to the landlord.

This is why income inequality among workers appears to be highly correlated with income inequality at the firms they work for.  They are both capturing excess profits from the same phenomenon.  The source of monopoly profits are the workers themselves, who are protected from competition because there is no housing for additional workers.  Firms who can get exposure to these closed access cities share these excess profits along with the workers.  However, since there aren't nearly as many political constraints to commercial real estate as there are to residential real estate, and since shelter expenses are a smaller portion of firm expenses, the firms are able to retain much of their excess profits.

Among the workers, it looks to me like there is actually more income inequality than aggregate measures tend to show, because low income households at the threshold of sustainable budgets will send all of their marginal income to the landlord.  Higher income workers may be able to retain some of their new income if their income is high enough that they can stand to reduce their real housing expenditures to a more comfortable portion of their budget.

This is one way to view the migration patterns - when a poor household moves out of a closed access city and a high income household moves in, the rent of the unit becomes a smaller proportion of the new household's budget.  The closed access policies won't allow rents to decline relative to incomes, but something has to give, and the migration pattern accomplishes this by pushing up local incomes.  This is why it looks to locals like high income in-migration is the cause of the crisis.  And, the migration pattern is the reason that relative incomes after rent are falling, because the inflow of high-productivity workers to the profitable local industries allows those firms to increase their productive activity and capture more economic profits from the rest of the world, which then funnel through the new workers to the local real estate owners.

I think this migration pattern has much to do with the extreme income growth at the top of the income distribution, too.  These closed access cities are much more valuable to high income workers, and the migration pattern we see is a reflection of that value.  Highly productive workers who can benefit from these valuable professional networks in tech. and finance can especially increase their incomes as a result of the closed access, and they spend a much smaller portion of those incomes on housing.

The irony is that the best policy we could institute for reducing all these forms of economic inequality between workers and capital is to build hundreds of thousands of high end housing units in the core areas of San Francisco, San Jose, and New York City.  In fact, this is the only policy that can accomplish that task.