dH(t)=aH(t)dt+bP(t)dt+cI(t)dt+dn(t)
where I(t) is the interest rate, and n(t) is a colection of random disturbance to pricing. They show the data as we show below.
They sate:
" During the most recent housing boom, the Census’ constantquality index of new home prices, adjusted for infl ation, rose approximately 33 percent. In the bust following the fi rst-quarter2007 peak, that same measure has fallen by nearly 15 percent.5 The sharp swings in house prices raise a question: Are these movements driven by economic fundamentals, or by irrational behavior that can trigger bubbles and busts? One indication of a bubble is that “the level of prices has been bid up beyond what is consistent with underlying fundamentals” (McCarthy and Peach 2005). This observation suggests that a logical way to explore the forces behind the recent housing price movements is to establish the magnitude and timing of the price shifts that would be warranted by changes in fundamentals alone."
They continue:
" Our model predicts a path for house prices over 1963-2008 that is based on the productivity data and on estimates of the relationship between income, house prices, and demand. Whenproductivity growth accelerates, the amount by which house prices will rise depends on certain basic supply and demand relationships.
The fact that land, a finite resource, is a relatively largecomponent of housing (compared with its “share” in other goods) makes the overall supply of housing relatively unresponsive to demand changes; the supply of houses cannot expand indefi nitely to meet increases in demand. In addition, because housing is viewed as a necessity that has no obvious substitute among other kinds of goods, consumers faced with a rise in housing prices will be relatively unwilling to curtail their demand for housing.
Thus, the demand for housing services is relatively inelastic—that is, insensitive to price changes. Indeed, our model incorporates a very low demand elasticity of 0.3, based on the calculations described in the box above. This combination of price-inelastic demand and supply means that productivity swings affecting the demand for housing can result in large changes in house prices."
They do state that there are other factors which they argue are de minimis. Specifically they call out:
"We have suggested that productivity growth infl uences housing prices through its effects on income. We recognize, however, that income growth can stem from sources other than longterm changes in productivity—most notably, increases in labor force participation or hours of work per household. While these alternative sources of income growth might be expected to affecthousehold demand and expenditure patterns, they may be less likely than productivity growth to infl uence housing prices.
First, the additional household income generated from increased labor force participation may be partially offset by additional expenses...
Second, the changes in workforce participation that result from shifting population demographics such as the aging of the baby-boomers or the increased presence of women in the labor force are relatively predictable...
Third, because labor force participation cannot grow without bound, its effects on income growth will necessarily be fi nite. There are only so many people who can join the workforce and only so many work hours in the day."
Their model is a bit different than out form above and it is:
" Housing rents represent the market price that consumers pay for housing services. From the property owner’s perspective, rental income net of expenses is analogous to the dividends earned from holding shares of common stock. Because the owner has the option to sell theproperty and put the proceeds in an interest-bearing security, he must expect a rate of return, adjusted for risk, comparable to the rate on other investments.
If Rt denotes rental income net of taxes and expenses in year t, it should obey the relationship
Rt + E {Pt +1}-Pt = rt Pt ,
where Pt is the price of the property at the beginning of year t, rt is the interest rate available on an alternative asset, and E{Pt +1} is the expected price as of year t+1.
The left side represents the total return (income plus capital gains) expected from owning the property, while the right side is the return on an alternative investment with similar risks. By itself, this relationship has no economic content other than “the law of one price,” or what financial economists refer to as “no arbitrage”—namely, that risk-adjusted returns should be equalized.
In particular, while the relationship implies that the rent-price ratio Rt /Pt should be reduced by expected capital gains—it implies that the rent-price ratio is negatively related to expected appreciation rate Et {(Pt +1-Pt )/Pt }—it does not explain which factors drive thoseexpectations. Identifying the factors is one goal of this article."
They then depict the analysis as follows:
There is indeed a good set of correlation between these two. The paper is of interest since it depicts a reasonable model for the housing bubble but it tends to lay the blame on productivity and consumer perceptions. However is fails to explain such effects as:
1. The expansive growth of money via the Government lowering of interest rates. The interest rate present a long term expectation on the part of the consumer as to the value of the property. The Austrian school and Mises in particular would tend to blame the Government and the soft money more than productivity changes. People see a good deal and thus are willing to defer savings and invest in property. This is an artificial investment because the rates are artificially low.
2. Scarcity of property, land, is also Government generated. Look at California where the Government, state and Federal, absorb massive amounts of land for Government use driving the remaining land prices to unreasonable levels. Thus land in California dominates the housing prices as compares to say the New York area. The same land control applies to the Washington DC area as well. This is a Government controlled effect. It is not included in the model.
3. Lowering of investment by the change in mortgage values means that savings is reduced in effect and the risk levels of investment are raised well above a "real interest" rate. The Government controls a low interest rate and induces "investment" into anticipated cash flows which are unachievable.
4. Cycles of boom and bust are not mitigated against by allowing zero down payments and it has been exacerbated by the elimination of the tax consequences of walking away from a mortgage. In the past if one defaulted on a mortgage and the bank sold the property at a price lower than the mortgage note the difference was impute taxable income to the one defaulting and the IRS would seek taxes on that amount. For the past two years that cost or risk was eliminated. Massive amounts of imputed taxes have been lost and in addition the moral peril associated with this event has been eliminated.
Notwithstanding the paper is of significant interest since the data shows excellent correlation. There is a great deal to understand here however and this is hardly the last word.
Posts
