Robots and Property Values

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As robots begin to move goods and people from place to place, urban land might become more valuable.

Amazon.com has announced that it is testing package delivery by drones — small, unmanned helicopters that would bring a purchase from Amazon’s fulfillment center to the customer’s front porch. Driverless cars are being developed to help move goods and people from place to place.

“Location, location, location” is the saying in real estate: a property’s value is determined primarily by its location. An apartment in central Illinois might be worth 20 times as much in Manhattan, because a Manhattan apartment gives its resident access to many more goods, activities and high-paying jobs.

This is not to say that urban living is always the best, or that all urban properties are created equal. Locations involve trade-offs, and rural areas offer amenities that big cities cannot. But for centuries, real estate markets have shown that people and businesses are willing to pay more for urban properties.

As technology helps with moving goods and people more cheaply, it might seem that urban real estate would give up some of its price premium because distance becomes less of an obstacle to economic transactions. Wouldn’t a driverless car cause some workers to sell their Manhattan apartments and commute to their jobs from more spacious homes in the suburbs or even rural New York State?

But don’t forget that many people and businesses currently avoid urban areas because of the monthly expense of owning or renting urban property. New technologies might allow them to use urban properties on a part-time basis, or use less urban property to accomplish the same tasks, which would make urban property more valuable.

A restaurant may need less refrigeration and storage space because it takes multiple food deliveries per day. Grocery stores may save on shelf space by having a greater fraction of their items delivered directly to customers without being shelved in the store. Households may opt for less storage space or parking, for example — and more room for people — when they can get items and transportation cheaply and on time.

For every Manhattan resident who leaves his apartment for the suburbs, there could be many others for whom technology induces them to use a Manhattan property on a part-time basis.

New technologies are more likely to emerge in urban areas, because that’s where the innovators expect to find the most customers. Amazon said that it planned to start its drone service in urban areas, and I wouldn’t be surprised if the first commercial uses of driverless cars were in big cities like San Francisco or Los Angeles.

Thus, while cities already give their residents access to more goods and services, technology may further shift that advantage and thereby increase urban property values.

The Largest Marginal Tax Rate Ever?

Copyright, The New York Times Company In 2012, the Treasury Department began a new phase of its Home Affordable Modification Program, or HAMP. In doing so, it may have the distinction of putting into place the largest marginal income tax rate ever in a non-Communist country.

For home mortgage borrowers who appear to be headed for foreclosure, mortgage programs typically recommend a revised mortgage payment amount that is lower than the payment specified in the original mortgage contract. The new payment is set in proportion to the borrower’s income at the time of the modification.

The more the borrower is earning at the time of the modification, the more she will be required to pay her lender over several years. Typically, each additional $100 a borrower is earning (on an annual basis) at the time of the modification adds $31 to the annual amount of the mortgage payment recommended by the Treasury’s mortgage modification guidelines. (This modification is not revisited over time; the income is examined one time and payments set.)

The HAMP program, and its predecessor at the Federal Deposit Insurance Corporation, usually modified the mortgage payments by adjusting the loan interest rate over the subsequent five to seven years.

Thus, assuming a five-year modification time frame, each $100 earned at the time of the modification would add $155 to the borrower’s total mortgage payments, or about $130 in present value.

It is done this way with the intention of creating a monthly payment that is “affordable” (defined as 31 percent of income). But there’s a flip side to the argument: the disadvantage of higher earnings in calculating the resulting payment. To an economist looking at it that way, it’s the equivalent of a 130 percent marginal tax rate: a $130 payment differential solely as a consequence of earning an extra $100.

This year the Treasury decided to encourage changes in this procedure. In particular, it will now subsidize lenders for modifying mortgage principal balances rather than interest payments. Because the principal balance determines payments for the life of the loan, in effect Treasury is asking lenders to modify payments for the life of the loan and not just five to seven years.

Take a 30-year mortgage originated in 2006: it has 24 years left. Under the new rules, an extra $100 earned by the borrower at the time of modification costs her $31 a year for 24 years, which amounts to a total of about $390 in present value. That’s a 390 percent marginal tax rate that applies to borrowers who are having, or expect to have, their mortgage modified.

Economists agree that marginal income tax rates of 100 percent or more are destructive to the labor market and strongly encourage corruption. The best we can hope for is that people subject to such confiscatory marginal tax rates are and remain oblivious of the incentives that Treasury is presenting them.

Marginal tax rates in excess of 100 percent are also present in antipoverty programs, especially in what is known as the Medicaid notch, where an additional $1 of income can mean the complete loss of coverage. In a sense, the Medicaid notch is a marginal tax rate in the thousands of percent, because beneficiaries lose benefits valued in thousands of dollars as a consequence of earning an additional $1.

But while a few thousands of dollars are at stake with one family’s Medicaid coverage, tens of thousands, sometimes hundreds of thousands, are at stake in each mortgage modification transaction.

For this reason, I think Treasury officials have earned the award for largest marginal income tax rate ever. Let’s hope they are not in training to yet again break their record.

When Times Get Tough, the Elderly Work

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The elderly are one group whose work hours now exceed what they were before the recession began. This pattern is most evident in the most depressed regions of the United States.

The recession has varied in different regions of the United States. In some areas – including Arizona, California, Florida, Hawaii, and Nevada – housing prices surged more dramatically in the early part of the 2000s than they did in the rest of America, and their economies fell hard when housing prices collapsed.

One view is that such areas experienced a deeper recession because their banks became overwhelmed with defaults and were unable or unwilling to make new loans to consumers and businesses. Without those new loans, demand collapsed more than it did nationwide, and jobs were especially difficult to find, even while people living in the area were especially eager to work.

Absent demand, just about all workers will have a tough time retaining a job or finding a new one.

Another view is that old loans are the problem, not newer ones. A significant fraction of households and businesses are typically so burdened with the debts they accumulated during the housing surge that they have little incentive to produce and work, because their creditors would get most, if not all, of the fruits of their labor.

In contrast to the no-new-loans-and-no-demand theory, old loans do not affect all workers; some are less burdened by debt. The elderly may fall in this category, because they are more likely to have saved money over their lifetimes and to have paid off their mortgages. Although some elderly working for debt-burdened employers may have lost jobs, on average the elderly in these areas should be working more because they have better incentives to do so.

The chart below compares 2007-10 changes in work hours for two areas –- the regions where housing prices rose and fell the most, on the left side of the chart, and the rest of the United States on the right. For middle-aged and younger people (blue bars), hours worked fell 12 percent in the large cycle regions and about 9 percent in the rest of the United States.

Hours worked by elderly people increased in both regions.

As I noted a few weeks ago, the average American elderly person worked more in 2010 than did the average elderly person before the recession began, even while work hours were down sharply for middle-aged and young people. The chart above shows that this is true even in the states that generally experienced the largest collapse during this recession.

Demand is not the only factor driving employment patterns.

The Misunderstood Mortgage Interest Deduction

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The home-mortgage interest deduction does not by itself significantly distort housing markets. Too much owner-occupied housing has been built because housing is excluded from sales and other taxes owed by businesses.

The housing boom and bust of the last decade, and government revenue shortfalls, have brought back the topic of whether the government excessively encourages home building. Those discussions invariably mention the elimination of the home-mortgage interest deduction.

This deduction allows taxpayers who own a home, have a mortgage and itemize deductions to reduce their personal income tax by including home-mortgage interest payments in their tax deductions. Homeowners rightly consider this when considering whether and how much to invest in a home and how much they should borrow.

A homeowner who pays, say, one-third of his taxable income in federal and state personal income taxes will recognize that a $3,000 monthly mortgage-interest payment really only costs $2,000, because the mortgage interest reduces his taxable income by $3,000 and thus the personal income tax owed by $1,000 a month. It’s as if he paid $2,000 and the federal and state government treasuries paid the other $1,000.


At first glance, the home-mortgage interest deduction would seem to cause homeowners to borrow excessively for home ownership, and thereby deplete government treasuries. But that ignores the fact that one person’s mortgage interest payment produces interest income for another person or a business. The lender may well owe taxes on the interest income.

More home-mortgage borrowing means more home-mortgage lending, and the latter means more interest income that can be taxed. In theory, home-mortgage borrowing could even add revenue to the Treasury if the lender is in a higher tax bracket than the borrower (or if the borrower is not itemizing her tax deductions).

Interest deductions are present in the business sector, too, and have the same essential properties as the home-mortgage interest deduction. A corporation that borrows to finance an investment project can deduct its interest payments from its taxable income, and that borrowing will generate interest income for whoever made the loan.

Landlords can also take out mortgages on their properties and deduct the interest payments from their taxable income (that benefit may, in turn, affect the rent they set). In that sense, the possibility of deducting mortgage-interest payments from income taxes does not by itself discourage renting rather owning.

In contrast, consumer durable goods do not enjoy the interest deductions that housing and business capital do. Someone who takes out a car loan to purchase an personal automobile cannot deduct the interest payments from her taxable income, even while the Internal Revenue Service may be collecting taxes on the interest income of the lender. In this regard, tax policy discourages investment in consumer durable goods relative to investment in housing and businesses.

This is not to say that housing investment has been efficient. Earlier this year I explained how housing is much less profitable than business capital before taxes, largely because of the host of taxes — like sales taxes and income taxes on profits — that are owed by owners of businesses but not
by owners of homes.

Who Cares About the Fed?

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Short-term interest rates have an obvious effect on the housing market, but not the rest of the economy.

Federal Reserve policy affects short-term interest rates, bank regulation and eventually inflation. I will write about inflation next week, and my fellow Economix blogger Simon Johnson has written much about bank regulation, so today I focus on short-term interest rates.

The Federal Reserve, especially its New York branch, is actively engaged in buying and selling Treasury securities, and it lends money to banks on an overnight basis. As a result, it is widely thought that the Federal Reserve is an important determinant of the rate of interest paid on short-term Treasury securities.

By raising the supply of Treasury securities and reducing overnight lending, so-called “tight” monetary policy raises short-term interest rates. High short-term interest rates are said to discourage borrowing, and thereby curtail private sector investment projects. The idea is that private sector projects are undertaken only when their expected return exceeds the cost of borrowing.

In theory, high short-term interest rates result in relatively few capital projects, with high expected returns, and low short-term rates result in more capital projects, including those with lower expected returns.

But the effect of high short-term interest rates on Main Street’s economy has been exaggerated. Although it is commonly assumed that today’s rock-bottom rates should help strengthen a business recovery, it appears that business conditions actually have little to do with short-term money markets.

Many important private sector investment projects are relatively long term — it most likely takes a year or more for a project to be completed and deliver a positive cash flow to investors. As a result, many capital projects are financed through long-term borrowing, with equity financing, or out of corporate retained earnings, rather than borrowing in the short-term market where the Fed’s fingerprints are so obvious.

In theory, long-term interest rates could rise as the Fed tightens the short-term money market, because some savers would be on the margin of saving in either the short- or long-term markets. Equity capital markets and retained earnings could, in theory, also be subject to similar indirect effects.

Thus, the effects of Federal Reserve interest-rate policy on investment are indirect, and it is an empirical question as to whether the expected effects — tight money discourages investment projects — are significantly reflected in preventing capital projects with low expected returns.

Luke Threinen and I have measured national average profitability of capital projects from the national accounts by dividing total interest and profits in the economy during a year by the total capital stock in place at the beginning of the year. In doing so, we have distinguished residential capital (i.e., houses) from business capital.

Capital produces value over a number of years. In the case of housing capital, the value is in the form of shelter and the convenience of a home. For any piece of capital, profitability (capital’s marginal product, as economists call it) can be calculated as the dollar value it creates during a year — after subtracting depreciation, costs of labor, maintenance and intermediate goods — per dollar invested.

Owners of capital prefer their capital to be more profitable, rather than less. It’s the profitability of capital (after taxes and subsidies; more on those below) that makes an owner willing to purchase capital in the first place.

Chart 1 compares the profitability of housing capital to the inflation-adjusted return on one-year Treasury bills (for comparability with T-bills, housing profitability is adjusted for property taxes). Consistent with the view that tight monetary policy both raises Treasury bill rates and reduces housing investment, the two series are positively correlated. The home-mortgage market appears closely linked, so high Treasury bill rates cause banks to charge more for home mortgage loans, which discourages homeowners and landlords from building homes unless the demand for homes is sufficient (i.e., landlords can earn enough rent from their tenants to cover a high mortgage rate).

Among other factors, easy credit from the Federal Reserve in the early and mid-2000s made it easy to buy and build homes, and as the inventory of homes grew the amount of rent that each home could earn (many homes went vacant, for example) fell, which shows up in Chart 1 as especially low values for the red series. In this way, the housing cycle of the 2000s confirms the usual story about how monetary policy can affect housing investment.

The usual story about Federal Reserve policy and business investment says that a similar process works on the business sector: High Treasury bill rates cause banks to charge more for business loans, which discourages business from investing unless demand for their product is sufficient (i.e., businesses can earn enough profit from their operations to cover a high loan rate).

Our findings for the business sector are quite different from the usual story. Chart 2 compares the profitability of business capital to the inflation-adjusted return on Treasury bills, and the correlation is negative.

One way that easy monetary policy could hurt business investment is by encouraging home-construction activity, and home construction takes resources away from business construction.

The evidence in Charts 1 and 2 suggests that the housing market can be stimulated by easy monetary policy, at least in the short run. But the link between monetary policy and the business sector is much weaker, and our data are consistent with the view that, holding constant the rate of inflation and the amount of banking regulation, monetary policy does not have a discernible effect on the cost of business capital.

Real Estate Crisis? It Depends on Supply

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Real estate’s future can often be understood by closely watching the supply of residential and commercial buildings.

In early 2009, employment and gross domestic product were dropping sharply, and real estate values had plummeted from their highs in 2006. The housing market was already in crisis, so it felt right to expect the commercial real estate market to follow.

Nouriel Roubini predicted, “More than 700 banks could fail as a result of their exposure to commercial real estate.” Elizabeth Warren later reported, “There is a commercial real estate crisis on the horizon.”

And journalists frequently referred to a looming commercial real estate crisis.

But none of this commentary noted how the supply situation in commercial real estate was drastically different than it was in housing.

By 2008, it was clear that too many homes were built for the market to bear. But the four-to-five-year boom in housing construction had taken resources away from commercial building, holding down the inventory of structures that would be available for business use.

With commercial structures in relatively short supply, I concluded in early 2009 that there would probably not be a commercial real estate crisis creating waves of bank failures.

My conclusion was greeted with much skepticism (one example was Salon’s article on “The NYT’s Chicago Economist: Wrong Again,” insisting that warning of a commercial real estate meltdown was part of “reliable economy-watching”). Paul Krugman also weighed in.

More than two years have passed, and we no longer hear much about the once-imminent crisis.

Professor Roubini still thinks that a commercial real estate crisis is ahead. Others said the crisis was averted. Either way, it is now recognized that the relatively low supply of commercial real estate made a big difference.

In order to assess the likelihood that the housing sector double dips – that is, has another crisis something like the one in 2008 – it helps to look at the supply.

The black line in the chart below shows an index of housing inventory per person at the end of each year from 1990 to 2011 (with housing inventory measured as square footage, adjusted for quality; 2011 is a forecast). Housing supply almost always increases faster than population, but the housing boom of 2002-6 stood out compared with the other years in terms of the relative rate of housing construction.

By 2007, housing supply was well above the trend of the 1990s (before the housing boom). If you think that a rational market would have more or less followed that 1990s trend, then the excess supply in 2007 meant that housing prices had to come down.

Of course, housing prices did come down a lot in 2007 and 2008, and the housing supply stopped growing. By the end of 2010 – the second-to-last observation shown in the chart – housing supply had fully returned to the trend of the 1990s.

Because the pace of housing construction continues to be slow, it looks as if housing supply will be significantly below trend by the end of this year.

These supply results tell us something about the future of housing prices. Those prices depend on demand, too, but as long as housing demand is near or above the preboom trend, it looks as though housing prices are low enough already.

Part of the inventories of housing and commercial property sit vacant, but those vacancies are largely part of a slow economic recovery and the difficult task of dividing property losses from previous years among homeowners, landlords, banks and commercial tenants.

With the slow pace of new construction, neither the housing nor commercial real estate markets can any longer be characterized as having supply that significantly exceeds the fundamentals of demand.

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In Construction More Spending Can Also Mean Less

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The Census Bureau released its latest estimates of construction activity for the various sectors of the economy on Tuesday. Those data suggest that more spending in one sector tends to reduce spending in other sectors, contrary to the multiplier hypothesis put forward by Keynesian economists.

Last week I examined measures of the profitability of capital in the housing and business sectors and noted how, during the housing boom, profitability in the two sectors moved in opposite directions: housing profitability fell while business sector profitability rose.

The market appears to have built so many homes during those years because of an expectation that houses would be profitable in the future, and, in part, because home buyers were encouraged by easy credit. As a result, an ever-growing housing inventory was competing for the same demand for shelter, which kept rents low and vacancies high.

At the same time, it was more difficult for business to obtain capital, because so much of it was going into housing.

The battle for resources between the business and housing can easily be seen in the data for each sector’s structures investment (that is, construction activity), at least before 2009. The chart below shows quarterly data back to the beginning of the year 2000. A value of, say, 90 for either series means that structures investment, adjusted for inflation, was 90 percent of what it was in the first quarter of 2000 (for a related series, see this post).

The housing boom and bust are readily visible in the housing sector’s green line, which rose sharply through the end of 2005, and then fell even more sharply through 2009.

Nonresidential building normally increases over time with growth in the population and the economy, but it was low during the housing boom (see the red line in the chart), probably because so much capital was going into home building. Both residential and nonresidential investment turned at almost exactly the same time, in opposite directions. Nonresidential investment increased throughout 2006, 2007 and 2008, while residential investment was collapsing.

When President Obama was proposing his stimulus law in early 2009, he and his advisers contended that government spending would stimulate private spending.

Yet a number of economists warned that sectors compete with each other for resources, so government spending tends to displace – “crowd out,” in economics jargon – private spending. For example, some people employed by stimulus projects are people who quit their private-sector jobs to accept better positions funded by the new law.

Even the Obama administration, in its first Economic Report of the President (click here and scroll to page 124), pointed to the same data and noted how this seemed to be crowding out, at least before the recession. Admittedly, looking at the economy as residential versus nonresidential is not the same as looking at it as public versus private, but the former gives us some information about how economic activity spills from one sector to another.

Crowding out comes from scarcity of supply, and Keynesian economists assert that supply is not at all scarce during recessions. Perhaps they would point to the parallel movement of the residential and nonresidential building series after 2008 as evidence that crowding out stopped once the recession worsened.

However, even if the availability of former home builders was by itself encouraging nonresidential building, nonresidential building could fall during the recession because of declining demand. The large reduction in the workforce that became apparent by 2009, not to mention tight credit, is likely to have reduced the desired number of nonresidential buildings, and this, by itself, would cut nonresidential investment activity. So determining whether crowding out stopped after 2008 requires separating the effect of increased supply of resources for nonresidential investment from reduced demand.

In doing so I looked at the relationship before 2008 between building in the two sectors and the business cycle. Not surprisingly, nonresidential building follows a business cycle, going up and down with national employment.

As you might guess from Chart 1, more residential building is associated with less nonresidential building at a given point in the business cycle: each $3 billion of home building seems to crowd out nonresidential building by at least $1 billion. Now that’s crowding out: something that stimulated home building by $3 billion would raise total building activity, but only by $2 billion.

I used the pre-2008 relationships to predict nonresidential building during this recession and through the third quarter of last year, under two assumptions: that crowding out continued as before, and that crowding out ceased once the recession began.

Chart 2 shows the results, together with the same red actual investment data from Chart 1. The black line shows what would have happened to investment if it continued to move with employment, but crowding out disappeared. The blue line shows what would have happened to nonresidential investment if, in addition to moving with employment, crowding out continued at the same rate it did before the recession.

The predictions based on continued crowding out (the blue line) correctly anticipated this pattern, as well as the actual sharp drop to begin 2009. Nonresidential building did fall after 2008 but, thanks to the movement of resources away from housing, it fell less than it would have in a recession this deep.

The Keynesian model ignores the crowding-out effect, and thereby consistently underpredicts nonresidential building during the recession. Thus, all else the same, it appears that less spending in one sector is partly replaced by more spending in another.

Sometimes there are good reasons for the government to spend more, but Chart 2 shows how one of the costs of government spending is that it displaces spending in other sectors, even during a recession.

Housing-Sector Profitability Returns to Previous Levels

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The housing boom further increased our economy’s bias against business capital, but by 2010 housing profitability was back to normal.

Last week I examined a measure of the profitability of housing capital: the value added by houses in the form of shelter and convenience for their occupants during a year, expressed as a fraction of the total value of homes. Before the housing boom, housing added much less value per dollar than business capital did, largely because business taxes restrict the supply of business capital.

The less business capital there is, the higher the rate of return that remaining business capital earns, because each unit of capital serves more customers, as I noted last week. A low profit rate for housing is a symptom of its abundance.

The profitability gap between nonresidential and residential capital shows that our economy was overinvested in housing, long before the housing boom of the early 2000s. Business taxes cause an underinvestment in business capital, and business capital has been so profitable to the economy because it is more scarce.

Value added to the economy would have been greater if some housing investment had been invested in business instead; each $10 billion of housing investment redirected to business investment could have added almost a billion dollars to G.D.P.

The chart below displays the same marginal product measure of residential capital profitability (red line, from the first quarter of 2000 to the third quarter of last year (Luke Threinen, a University of Chicago student, helped with these calculations).

The chart also displays the marginal product of business capital (blue line). Because of the extraordinary “depreciation” from Hurricane Katrina, values for 2005 have been interpolated.

The marginal product of residential capital is measured on the right axis, while the marginal product of nonresidential capital is measured on the left axis. By looking at the 2000-1 values – 6.6 percent for residential and 15.2 percent for nonresidential – we see the result, noted last week, that nonresidential capital was twice as profitable before taxes than residential capital.

After the 2001 recession, and during the housing bubble, the marginal product of residential capital fell sharply. (This finding is related to previous findings that rent-to-price ratios were low during the mid-2000s, because housing profitability is essentially the rent-to-price ratio minus the expense-to-price ratio.) During this period, housing construction was booming.

Housing was not particularly profitable during the housing construction boom – the market appears to have built so many new homes during those years because of an expectation that houses would be profitable in the future, and in part because home buyers were encouraged by easy credit.

As a result, an ever-growing housing inventory was competing for much the same demand for shelter, which kept rents low and made vacancies high.

While housing sector profitability became so low, business sector profitability was quite high. At the peak of the housing boom, the marginal product of nonresidential capital was more than triple the marginal product of residential capital.

By widening the profitability discrepancy between the two sectors, the housing boom was more damaging than it would have been if the boom hadn’t begun with an abundance of housing.

When the housing bubble burst in 2006-7, and housing construction nearly came to a halt, the marginal product of housing began to rise toward previous levels as the population grew into the extra housing, and some existing housing deteriorated. By the fourth quarter of 2009, the marginal product of residential capital hit 6.2 percent and has remained about there since then.

The good news is that the 6.2 percent housing sector profitability of the past is actually a bit higher than the historical average from 1950 to 2000, which means that housing is adding value at a rate similar to the pre-bubble years.

The strongest economic pressures preventing further increases in our housing inventory have been gone for a year now, which is one reason I do not expect the housing market to get any worse.

Business capital profitability has also returned to previous levels, but the bad news is that housing capital remains much less profitable than business capital. In this sense, housing is still too abundant, an economic waste that shows no signs of repairing itself.

Housing Profitability -- Video Version

Housing Sector Profitability

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Long before the housing boom, overbuilding effects of government policy were evident.

A house is a piece of capital, meaning that it produces value over a number of years. In the case of housing capital, the value is in the form of shelter and the convenience of a home.

As with any piece of capital, a home’s profitability (its marginal product, as economists call it) can be calculated as the dollar value it creates during a year – after subtracting depreciation, costs of labor, maintenance, and intermediate goods – per dollar invested.

Owners of capital prefer their capital to be more profitable, rather than less. It’s the profitability of capital (after taxes and subsidies – more on those below) that makes an owner willing to purchase capital in the first place.

For a home that is rented or vacant, the home profitability calculation is straightforward: take the landlord’s rental income for the year, subtract depreciation, costs of maintenance and labor expenses (if any) for the same year and divide by the amount the home is worth.

A home occupied by its owner does not have rental income per se – the homeowner does not pay himself rent – but a hypothetical rental income can be imputed to owner-occupied homes by looking at the rental incomes earned by comparable homes that are on the rental market.

The Bureau of Economic Analysis makes rent imputations part of its preparation of gross domestic product and other items in the national economic accounts and reports a total value created during the year by all homes. It also estimates an aggregate home value (more precisely, it estimates what it would cost to replace each home with one just like it). The table below shows its results for the year 2000.

The first row of the table reports that the homes, condos and mobile homes in the United States in the year 2000 provided $1.01 trillion of housing services — that is, the value of the housing in rent or imputed rent — in the year 2000 (next week I’ll examine the years 2000 to 2010 more closely). A total of $160 billion of intermediate goods and services — mainly closing costs and brokers’ fees — were used, and the normal rate of depreciation of homes amounted to a cost of $162 billion.

The housing sector employed some people, such as apartment managers, with a payroll that amounted to $11 billion. But the Bureau of Economic Analysis does not try to measure the value of time of people who maintain their own homes, and for this reason the housing sector’s labor costs are significantly understated. With this caveat, the operating surplus of the housing sector was $677 billion.

The housing stock in the year 2000 was worth $10.63 trillion, so the housing sector’s operating surplus amounted to 6.4 percent of the value of its housing capital. (This surplus was divided among owners and mortgage lenders, but today I focus on the overall profitability of capital without regard to how it is shared).

Luke Threinen, a University of Chicago student, and I used these ingredients, and some minor adjustments for inflation during the year, to calculate housing profitability rates for 80 years. The chart below displays our results for the years 1950 to 2000.

The profitability of housing fluctuated between 4 and 7 percent, averaging 5.7 percent over the decades shown in the chart. The 5.7 percent may seem large, because few of us earn that much on our savings accounts.

Part of the explanation is that most homes owe property tax, and the chart shows pretax profitability (another part of the explanation is that savings accounts are generally low-return investments).

More notable is the comparison of housing’s 5.7 percent profitability to the profitability of business capital. Mr. Threinen and I made analogous calculations for the nonresidential sector – annual business revenue minus variable (nontax) costs expressed as a percentage of the amount of business capital – and found business capital to have a profit rate of 15.3 percent.

We concluded that the profitability gap between nonresidential and residential capital shows that our economy was overinvested in housing, long before the housing boom of the early 2000s.

Business capital has been so profitable to the economy because it is more scarce. It’s the law of demand: the less business capital there is, the higher the rate of return that remaining business capital earns because each unit of capital serves more customers. A low profit rate for housing is a symptom of its abundance.

With each dollar of business capital adding 15.3 cents of value per year and each dollar of housing capital adding only 5.7 cents, total value added in the economy would have been greater if some of the housing investment had been business investment instead, even before the housing boom. Each $10 billion of housing investment that could have been redirected to business investment have added almost a billion dollars to G.D.P.

Business capital has been more scarce largely because of business taxes and housing subsidies. Houses are not tax-free — I mentioned the property tax — but, in addition to property taxes, investors in businesses also owe sales taxes, corporate income taxes and personal income taxes.

The business-residential profitability gap is almost 10 percent, but our attempts to adjust both profit rates for applicable taxes show that the after-tax profitability gap is zero to five percentage points.

I mentioned last week how, in the short run, capital income taxes result in lower after-tax returns for the owners of the capital being taxed. In the long run, the opposite occurs: investors have choices about where and how to invest, so the after-tax profitability of housing has to be pretty close to the after-tax profitability of business.

Business taxes cause an underinvestment in business capital – scarcity is the only way business capital can earn an after-tax return that compares with the return on lesser-taxed housing – and overinvestment in housing.

Early Doubts About Whether Tax Credits Stimulate Investment

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By its very name, the 2009 American Recovery and Reinvestment Act was advertised to increase investment. Yet years before this stimulus act was proposed, Austan Goolsbee, now chairman of the President’s Council of Economic Advisers, explained in his doctoral dissertation how investment tax credits might do little to stimulate investment during the life of the credit.

In at least one respect, the results of the act appear to confirm his theory.

An investment tax credit permits someone who purchases one of the capital goods covered by the credit to pay less tax in proportion to the amount he spends on the investment. The 2009 stimulus act included tax credits for various capital items, the most publicized being homes: qualified first-time home buyers, for a limited time, received a 10 percent capped tax credit. The program was later expanded to include repeat home buyers.

With the government helping an investor pay for a capital good, each investor is more willing to pay for such goods than he or she would be without the credit. You might guess that eager investors would stimulate more investing – leading to the production of more capital goods. With more capital goods being produced, the credit would create jobs for people who make those goods.

This guess is correct in the long run when it comes to housing tax credits: a housing credit or subsidy does result in the building of more houses (I’ll explore this subject in more detail next week).

But in the short run, the situation may be very different, as Mr. Goolsbee’s dissertation explained. The production of capital goods may get more expensive. In the extreme case, investors may pay more for their capital goods, and more of those goods will not be available. (In technical terms, we economists say that the supply of capital goods is inelastic.)

With no additional capital goods being produced, the credit would not create any jobs – just create a windfall for people already making those goods.

Mr. Goolsbee’s statistical analysis found that “much of the benefit of investment tax incentives does not go to investing firms but rather to capital suppliers through higher prices. A 10 percent investment tax credit increases equipment prices 3.5-7.0 percent.”

Mr. Goolsbee’s study looked at equipment and not structures, and we cannot assume that the nature of housing supply is identical to the nature of equipment supply. Economic theory and experience suggest that housing is even less elastically supplied in the short run than is business equipment.

In other words, an increase in housing demand – which the tax credit helped create – would, in the short run, do more to make housing construction expensive, less to create houses and less to create jobs than Mr. Goolsbee found for equipment.

And, indeed, whatever the overall objectives of the stimulus bill, it appears to have made construction more expensive.

I do not know if President Obama’s advisers discussed this issue, or whether they expected job creation to come from other parts of the stimulus act.

White House economists are probably Keynesian, in the sense that they believe that the 2008-9 recession was a special time when supply did not matter, even though it normally matters in most economic circumstances.

Mr. Goolsbee’s dissertation examined a number of tax credits that were put in place during recessions and seems to refute the idea that supply doesn’t matter during recessions.

Yet we have to acknowledge that the home construction industry was unusually depressed in 2008-9 and might have been a rare example where a stimulus could create jobs without increasing prices.

Now that the Home Buyer Tax Credit has come and gone (it began in early 2009 and ended April 30, 2010, although some buyers had until September to finish transactions), we can look at home construction costs and home construction activity during that period.

The chart below displays the monthly producer price index for home building materials (the blue line, measured relative to the producer price index for all finished goods), along with employment in the residential building industry (the red line), for the period January 2008 through December 2010.

The blue line shows a curious spike in the prices of home building materials, peaking at the end of April 2010, almost exactly when the home buyer credit expired.

Perhaps Mr. Goolsbee’s dissertation applies here, and the rush to finish home transactions before the credit expired made home building 3 to 5 percent more expensive during that period than it would have been without the credit. In contrast, the red employment series shows no visible spike in people employed as home builders.

The Home Buyer Tax Credit is just one part of a complicated stimulus law, but it illustrates a general principle of economics.

Even when government spending, subsidy or credit is targeted at a highly depressed industry, with plenty of unemployed workers apparently available for hire, the government’s purchases may, in the short run, raise prices and costs without necessarily causing more of those items to be produced.

Bad News from the Housing Sector?

Copyright, The New York Times Company

A few economists are contending that our housing market is now in a “double dip,” based in part on last week’s report of housing price indexes for September and October that were lower than they were during the summer. In my opinion, the data on housing prices and construction do not show any significant housing market change during the second half of 2010.

When connecting the housing sector with the wider economy, three different measures of housing prices are helpful: inflation-adjusted housing prices, inflation-unadjusted housing prices and cost-adjusted housing prices.

Inflation-adjusted housing prices tell us how much the prices of homes have changed relative to the prices of other consumer goods. If, for example, we want to know whether demand for housing these days is any different than it was before the housing bubble, it helps to check whether, from the 1990s through 2010, housing prices failed to increase as much as other prices have.

In this case I look at a housing price index that has been normalized by a consumer price index.

Inflation adjustments are not appropriate for the purposes of analyzing foreclosures – a big drag on our economy – because the mortgage principal that pulls homeowners “under water” is not adjusted for inflation either. If unadjusted housing prices increase, even if more slowly than other consumer prices, that helps homeowners swim out of the water.

For this purpose, I look at an index of the dollar value of housing properties, without any adjustment for inflation.

For the purposes of understanding construction activity, it helps to know whether housing prices have increased more than the costs of building materials. The more that housing prices increase beyond the cost of materials, the more value that can be created by home construction activity.

For this purpose, I look at an index of housing prices that has been normalized by an index of building costs.

It turns out that practice is messier than theory, because there are so many different houses in America and many different price trends. In practice, it matters which housing price index is used, regardless of which inflation or cost adjustment is used.

The Case-Shiller repeat sales index is one such index of existing homes. The Federal Housing Finance Agency has another index of existing homes (and there are others, as well). The Census Bureau has a quality-adjusted index of new home prices.

Chart 1 displays the three aforementioned home price indexes, measured quarterly without any inflation adjustment. The Case-Shiller index for the third quarter of 2010 (the first quarter without the government’s home buyer tax credit) was essentially the same as in the previous quarter. The other two indexes show slight decreases over the same time period, although well within the range of ups and downs over the previous six quarters.

By themselves, these data suggest that homeowners did not go significantly deeper under water in the third quarter and that the housing market trends were not dramatically different in the third quarter than in previous quarters.

Chart 2 displays the same three indexes, adjusted by the implicit price deflator for consumer spending. Because inflation has been low recently, it shows a similar pattern to Chart 1. By themselves, these series show no dramatic change in housing demand over the most recent quarter.

Chart 3 displays the same three indexes, adjusted by the producer price index for home building materials. Deflated this way, the Case-Shiller index actually shows a housing price increase from the second to the third quarter. That’s because building costs peaked in May and have been lower since then.

Without home prices falling by this measure, we do not expect construction activity to be lower than it was during 2009 (but, unsurprisingly, lower than it was during the short rush to sell homes before the tax credit expired).

You may notice that various housing price indexes disagree, and our most recent data is still three months old. Yet another approach is to look at home construction activity. Chart 4 displays monthly home construction activity through November 2010, measured as the number of housing permits, housing starts, homes under construction and homes completing construction.

Permits and starts are particularly interesting, because homes take time to build and we presume that many builders are looking ahead to the prices homes will command in the future, when the construction project is complete. Those series were actually higher in November 2010 than they were for several months before.

Predicting the future is difficult, but the price and construction data so far do not seem to suggest that home values will be significantly different this year than they were in 2010.

Home Prices during and after the "Homebuyer Tax Credit"

The Case-Shiller Composite 20 index averaged 144 during the months that the "Home Buyer Tax Credit" was in effect. This credit was claimed by many (including Professor Shiller himself) to be essential to housing market performance.

As of September 2010 -- the most recent data available, and certainly after the credit was expired -- the index stood at 147.

So now the evidence is supporting what economic theory said all along: if the Home Buyer Tax Credit were to cause housing prices to be higher, that effect would be at most minuscule.

VAT: Another Reason for a Housing Boom?

The U.S. does not have a national sales tax, or a value-added tax (VAT). Many other countries do have VAT, and a number of economists and accountants (not me!) have recommended that the U.S. get a VAT.

Suppose that we knew that, say, a 10% VAT was coming to the U.S. in the year 2015. In principle, a consumption tax is levied on all forms of consumption, including housing consumption. However, in practice a VAT only taxes new housing -- that is, a sales tax is collected when a new home is sold, and no sales tax is collected on home resales or home rents (actual or imputed).

Thus, homes built before 2015 would be 10% more valuable that home built after 2015, because only the latter would pay tax. So anticipation of VAT would cause a temporary boom in housing construction and new housing prices.

Was something like this important during the housing boom of the 2000s?

Chicago More Under Water than the Nation

http://chicagobreakingbusiness.com/2010/11/a-third-of-chicago-area-homes-worth-less-than-mortgage.html

Case-Shiller Housing Value Index Rises

Case-Shiller reported today that housing values in July 2011 were higher than they were during the entire life of the "Home Buyer Tax Credit".

Yet the conventional wisdom, not to mention Professor Shiller's own analysis, says that the home buyer credit was the only thing propping up the housing market.

?

Life After the Home Buyer Tax Credit

Copyright, The New York Times Company

The Home Buyer Tax Credit contained in the American Recovery and Reinvestment Act of 2009 has been given much credit for buoying the housing market. But recent housing market data suggest that the credit’s effect was limited, even while it lasted.

The law passed in February 2009 included a temporary 10 percent capped tax credit for qualified first-time home buyers that expired April 30, 2010. The program was later expanded to include repeat home buyers, and recently home buyers were given until September 2010 to complete qualified transactions.

One view of the tax credit’s effect is that it changes the timing of housing transactions — market participants rush to complete transactions before the credit expires — but has little effect on the value and quantity of homes because homes are expected to last many times longer than the tax credit does. Another view is that the market cannot do without the credit, and the housing market collapse that preceded it may well continue when it’s gone.

Although we do not yet have housing data beyond the summer of 2010, homes take time to build and housing starts can be informative about what will happen in the housing market over the next few months. A housing start is likely to be a house that will be finished in a few months, and presumably builders expect to command a high enough sales price to cover the costs on building the house.

The chart below shows seasonally adjusted single-family housing starts and completions since October 2008. Housing completions rose sharply as the deadline neared and spiked immediately after it, and for July and August were about as low as they have been in years.

Housing starts began coming down this spring, which helped set up the situation of few completions in July and August. But yesterday’s release by the Census Bureau confirmed that housing starts are not much lower than they were in the second half of 2009, when the tax credit was supposedly propping them up.

For now, it appears that, aside from this spring’s rush to meet the tax-credit deadline, the housing market after the tax credit will proceed at much the same pace it did for the time that the credit was in place.

Quarterly Housing Prices through 2010 Q2

still waiting for the Case Shiller June 2010 value, but that would have to be way out of bounds to put Q2 below Q1.

Housing PPI Turns Down