Mason Gaffney Predicts China Crash

Dear friend,

An acid test of a hypothesis is its success in forecasting. The “Real Assets Model of Economic Crises”, published in March, 2015, seems so far (up to August 21, 2015) to have passed the test, w.r.t. China. It is likely that “standard brand” economists and other forecasters, their visions narrowed by the same blinders that have kept them from foreseeing so many major downturns since at least (and probably before) 1720, will ignore this forecast and its rationale.  Anticipating that response, I take the liberty of circulating this material.

 

FORECAST

 

“For a number of years, it seemed that the Chinese miracle of rapid economic growth based on massive public investment would somehow steer clear of the economic distress caused by land speculation and marginal investment in capital projects.  Because of the backlog of latent demand in that economy for better housing, it was possible to construct thousands of projects in mid-size cities without exhausting the ability of China to make efficient use of those investments. By 2014, however, it became clear that China’s economy had reached a limit of productive investment in housing and other fixed investment and would be subject to the same constraints as other economies.  There were voices in China that began warning of this fate as early as 2006, but they were ignored.  It now seems likely that China will face several years of sluggish growth as land prices fall, defaults rise on marginal projects, and the loss of liquidity of the state-owned banks forces the central government to cut back on its investments.  At the same time, as house prices fall in the major cities, the urban middle class will respond to its reduced nominal wealth by cutting back on consumption.  The combination of these effects will reduce growth further and increase the rate of unemployment.

 

The one ray of hope in this otherwise gloomy picture is that some of the top leadership of China is at least aware that rising land prices need to be controlled by means of taxation.  This is the first sign that any national government has recognized the use of land value taxation as an instrument of macroeconomic policy.  Although that recognition came too late to prevent the present crisis in China, it could be used to prevent future repetitions of the present situation.  If China can learn that lesson in its first experience with a boom-bust cycle in land values, it will be far ahead of Western governments that have ignored the signs for centuries.”

 

  • Mason Gaffney, AJES, March 2015. 355

 

FULFILLMENT

 

“Stocks tumbled worldwide Thursday (August 20 2015) … as investors fretted about China’s slowing growth … . … reasons to avoid stocks start… with ongoing concerns about the cooling of China’s huge economy.  China devalued its currency, the yuan, last week, and its stock market has suffered a massive sell-off in the last two months despite government attempts to stem the drop. … The overarching concern for the (world) markets is just how much China’s economy is going to slow down.”  – James Peltz,, “Stocks sink globally on China fears”, L.A. Times 8-21-2015 p.C1.

 

READERS, NOTA BENE!!:  The full article below is presented mainly for those who might demand full evidence of the forecast and its bases. The sender understands that many recipients will not choose to take the time and effort to read it.  If you want a cleaner copy, write and ask, or use JSTOR or other standard alternative.

 

A Real-Assets Model of Economic Crises:

Will China Crash in 2015?

By MASON GAFFNEY*

 

American Journal of Economics and Sociology, Vol. 74, No. 2 (March, 2015).

DOI: 10.1111/ajes.12093

VC 2015 American Journal of Economics and Sociology, Inc.

 

ABSTRACT. Loosely derived from Henry George’s theory that land

speculation creates boom-bust cycles, a real-assets model of economic

crises is developed. In this model, land prices play a central role, and

three hypothesized mechanisms are proposed by which swings of land

prices affect the entire economy: construction on marginal sites, partial

displacement of circulating capital by fixed capital investment, and the

over-leveraging of bank assets. The crisis of 2008 is analyzed in these

terms along with other examples of sudden economic contractions in

U.S. history, recent European experience, and global examples over the

past 20 years. Conditions in China in 2014 are examined and shown to

indicate a likely recession in that country in 2015 because its banks are

over-leveraged with large-scale, under-performing real estate loans.

Finally, alternative methods of preventing similar crises in the future are

explored.

Introduction

Concern about economic instability is understandably limited in the

minds of most people to their own country. Thus, the economic and

financial contraction in the United States that began in 2008 has been

the object of most interest to American economists. When they make

comparisons, the experience of the United States in the 1930s tends to

be the primary event that is viewed as parallel to the current crisis.

A general theory of the business cycle or economic instability should

not be derived from or tested solely by two events. If a theory is valid, it

*Professor of economics emeritus at University of California, Riverside. Email: m.

gaffney@dslextreme.com. Author of After the Crash: Designing a Depression-Free

Economy (2009) and The Corruption of Economics. The latter examines how economics

was historically distracted from its potential to create models of an economy based

on both efficiency and equity.

American Journal of Economics and Sociology, Vol. 74, No. 2 (March, 2015).

DOI: 10.1111/ajes.12093

VC 2015 American Journal of Economics and Sociology, Inc.

should apply to numerous cases in the past and, ideally, it would serve

as the basis for predicting future cycles of boom and bust, growth and

decline. We cannot, like scientists in a laboratory, create the conditions

we wish to study, but economists can attempt to be more scientific than

we have been until now by examining as many cases as possible from

many countries and time periods.

This article will begin with a conceptual model that first offers an

explanation of numerous panics, crashes, or crises in the history of the

United States. It will then discuss its relevance to recent expansion and

contractions in several European economies. Finally, it will analyze the

prospective problems facing the Chinese economy in 2015, with the

hope of demonstrating the value of this model for prediction, not

merely description. By applying the model to a number of different circumstances,

I hope to show that it is a universal model, capable of

explaining cycles of economic expansion and contraction throughout

the world.

The theory presented here derives from a simple model developed

by Henry George ([1879] 1979: BK V, Ch. 1). George blamed the periodic

“paroxysms” in modern economies on the effects of land speculation.

In his view, if enough people held land off the market in the hope

of a price increase, the resulting artificial scarcity of land would raise

rents and land prices, driving down wages and returns to productive

investment. Eventually, this process would reach a limit, land prices

would fall, workers would be laid off, and factories would close. We

should give George credit for seeing the general outlines of this process,

but we must elaborate on his ideas to incorporate elements other

than land prices. I have elsewhere presented a thorough explanation of

the model developed below (Gaffney 2009), so I shall merely summarize

it here.

General Theory

To make sense of what happened to China in 2014 and the United

States in 2008 and 1927, we must shift our attention away from the

details of each crisis and attempt to detect, amid the noise and varying

particulars, a general pattern of economic crisis. I will develop here a

326 The American Journal of Economics and Sociology

“real-assets” model or theory that will be useful in understanding that

pattern. The hypothesis here has four elements:

  1. A rise and fall of land prices, resulting mostly from autonomous

real economic changes. These are less visible and less measurable

than purely monetary and fiscal changes, which may reflect

and even reinforce the real changes but not initiate them,

  1. Investment in projects at the margins, both in terms of geographic

location and value,

  1. Concomitant changes in the structure of capital investment to

favor structures with long payout periods, and

  1. An increase in bank leverage ratios as a result of lower capital

turnover, leaving many banks technically in default by the time

the land price bubble bursts.

Land Price Changes

The present hypothesis begins a posteriori from observing land prices

increasing over a period of five to eight years after a trough. This contrasts

to common scenarios that cast the banking system as the autonomous

factor initiating economic crises. Once price increments begin to

seem the normal, “rational” expectation, staid banks and other financial

institutions turn to lending on land collateral, and expand their balance

sheets to accommodate the increased investment in real estate. But

banks are responding to an external stimulus (an apparent improvement

in the value of real estate) rather than creating the conditions for a

boom on their own. It is only in the late stages of the land price boom

that banks, when they are lending money on increasingly marginal

sites, must develop creative accounting methods to circumvent the

financial regulations that were put in place during a previous period of

contraction to prevent reckless lending.

The first sign of a new cycle of boom and bust is a self-generated rise

in land prices, which shows up in the form of higher priced houses.

When we speak of an increase in housing prices, what we really mean

is the change in the price of urban land on which the houses are built.

Since the actual housing stock depreciates over time, it makes no sense

to conflate the two. If the price of housing rises 8 percent, the price of

Real-Assets Model of Crisis 327

land must have increased by, say, 15 or even 20 percent to account for

the stability or decline of the portion of value invested in physical

capital.

A land price occurs naturally as a result of increased economic productivity

or, often enough, a period of “peace dividends” following a

major war. For the first few years after a crash, the land market remains

unnoticeable. Buyers are wary of investing in real estate immediately,

and banks are even warier of lending for that purpose. In addition,

banks are unable to lend much because they have to retrench in order

to lower their leverage ratios. Nevertheless, four or five years after a

crash, land prices will start creeping back upward as a result of general

economic growth. Initially, that will cause an increase in the price of

existing houses. (Actually, the price change will represent an increase

in the value of sites, not the buildings, which are depreciating, becoming

obsolescent, and often being replaced at lower cost.) Increases in

real estate prices will signal to home builders and commercial real

estate developers that the time has come to build new homes and offices.

At that point, perhaps 10 to 12 years after the last crash, a new

speculative boom begins. At this point, the rise in land prices accelerates

because a rise stimulates more investment, which stimulates a

faster price increase, and so on. This occurs first in residential markets,

followed closely by commercial and industrial (C&I) real estate. Land

price appreciation becomes noticeably higher than alternative investments,

and a frenzy takes hold in which more and more people imagine

they can make money without effort by investing in real estate.

Many of those caught up in a frenzy fancy they are the rational ones, as

revealed by the phrases they publish, like Fisher’s “permanently high

plateau” of prices, and Sargent’s “rational expectations,” and Will

Rogers’s “Buy land, they ain’t makin’ any more of it!”

The rise in land prices must eventually reach a limit. The ratio of loan

repayments to cash flow (and service flow) eventually becomes high

enough, even to the point of exceeding unity, to reverse the speculative

frenzy and cause a sell-off. There is a plateau at the peak, as owners

who bought for short-term gain are now reluctant to take a loss, so as

the market softens, bid prices fall faster than asking prices, and sales

slow down for a few years. According to the S&P/Case-Shiller Home

Price Index (2014), the index of home prices hovered at 206 from June

328 The American Journal of Economics and Sociology

to August 2006 (January 2000 5 100), before beginning a decline to 139

in April 2009. (The price of land is more volatile than home prices, since

the relative price stability of the housing stock moderates the combined

price of land and housing.1) Once prices start to fall, some speculators

begin selling quickly, accepting declining bids in order to avoid holding

property in a falling market. Others, with greater holdout power and

more sanguine expectations, settle in for the long wait, hoping prices

will recover. The price of land—those few parcels that do sell—then

starts to fall faster than it rose. Land prices may crash in two or more

waves, the housing market leading the commercial market by about

two years, as happened 1927–1929 and 2006–2008.

If there were a national land price index, it would be possible to

demonstrate this pattern. In the absence of such an index, we can use

data on construction from the U.S. Census Bureau (2012, 2014a).2 The

value of residential construction rose 95 percent from 2000 (annual

average) to March 2006, then declined by 66 percent by February 2011.

A similar phenomenon occurred in nonresidential construction, which

includes not only commercial, industrial, and service-sector construction,

but also infrastructure such as roads and sewer lines, harbors, and

airports. From June 2002 to November 2008, it rose 232 percent, then

fell 29 percent by May 2011. There was a lag of 32 months between the

peak of housing construction (March 2006) and the peak of

nonresidential construction (November 2008).

National data on government gross investment in fixed assets

(around 20 percent of private investment) shows much less volatility

than private investment, which is surprising, given the importance of

local infrastructure investment in fueling a boom and the immediate

depreciation of abandoned public infrastructure after a crash. However,

the absence of volatility in aggregate data may simply reveal the relatively

small number of cities affected by “irrational exuberance” that

can create a national economic crisis. National data may obscure what

is going on in key local economies. There are also temporal idiosyncracies,

varying with the ideologies of politicians. Thus the canal boom of

1820–1840 was a nationwide mania in spite of President Jackson’s

refusal to use federal funds directly. This is an area for future research.

Note that in the case of housing, the peak of construction in 2000–

2008 occurred three to five months before the peak of the S&P house

Real-Assets Model of Crisis 329

price index. This would suggest that housing starts might represent a

leading indicator of an impending contraction in the economy.

The same pattern of successive waves of housing and nonresidential

construction cycles can be found in the 1920s, indicating that this model

is useful in explaining the Great Depression as well as the most recent

crisis. The value of housing construction rose 167 percent from 1921 to

1926, then declined 93 percent by 1933 (U.S. Census Bureau 1975a:

Column N32). Nonresidential construction rose 93 percent from 1921 to

$2.7 billion in 1929, then fell 85 percent by 1933 (U.S. Census Bureau

1975a: Column N36). The peaks of residential and nonresidential construction

were thus around three years apart. Add to that, housing prices

peaked in 1927, two or three years before stock prices did in late

1929.

Of course, a rise and decline in housing construction is not a perfect

proxy for changes in land prices, but it is a good approximation. A large

increase in housing construction occurs during the boom phase of the

land price cycle because (a) building and selling houses is one way to

generate immediate revenue from rising land prices, and (b) rising land

prices generally encourage investment in capital with low turnover (as

will be explained below). Since there are no land price indices in the

United States and most other countries, construction data must serve as a

proxy in following the economic events that lead up to a financial crisis.

Use of Marginal Sites During Booms

During an economic boom, as land prices are rising, an immediate

effect is hoarding of good locations. If land prices are expected to rise

at 20 percent per year, and other investments yield only 10 percent,

owners have an incentive to hold land off the market until the growth

of land prices falls below the return on alternatives. Although some

properties are “flipped” multiple times during a period of rising land

prices, other sites remain idle or underdeveloped while the owner

waits. Since that process occurs on many of the most desirable locations,

land on the margins of a city will benefit from the artificial scarcity

of better locations and the rise in land prices.

As a result of bottlenecks in the use of sites, boom periods lead to

speculative investment in housing and office buildings in marginal

330 The American Journal of Economics and Sociology

areas of a city: sites on the urban periphery, sites with hazards like

flood, fire, windstorms, quakes, and unstable ground subject to liquefaction.

The market signals that these sites are suddenly valuable, and

developers respond with new projects. There is a reason these areas

are marginal.

A higher than average proportion of the households or businesses

that purchase or lease the new construction lack the cash flow required

to make their payments to the developers. When the land price bubble

bursts, foreclosures become commonplace. Highly-leveraged builders

are then also forced into foreclosure, leaving office buildings or housing

tracts uncompleted or unoccupied: “Hayeks” in the 1920s; “The

Empty State” building in 1930s Manhattan, and “orphan subdivisions”

around Chicago and Detroit; “see-through” buildings in 1988 in Dallas

and Denver. In addition, the dispersal of development when the economy

is experiencing “irrational exuberance” creates a drag on the economy

to the extent that economic activity becomes less geographically

concentrated. Extensive development beyond the limits of ordinary

(non-speculative) economic activity is inefficient and raises transportation

and linkage costs of many kinds. Thus, land price rises cause

geographically inefficient investment.

Changing Characteristics of Capital

Although speculative growth of land prices and investment in marginal

locations are the initial factors that lead to major episodes of economic

instability, a proximate cause of crisis is a shift that occurs in the nature

of capital investment. The net effect is to increase the average payback

period of capital investments, which creates instability in the banking

system. Raising the average length of loan retirement has effects on

other economic variables, such as reducing employment opportunities,

a question we shall return to later.

In the following section, we will explain the effects of capital lengthening

on the financial sector of the economy. In this section, we will

consider only the process by which rising land prices lead to this

phenomenon.

Circular (positive feedback) effect. The first relationship of land and

capital is a circular process whereby the development of marginal

Real-Assets Model of Crisis 331

locations lowers the rate of return on productive investments. That reinforces

the advantage of further investment in land, which fuels this

cycle. Potential developers buy more land than is necessary for current

development plans because they are reacting defensively to the anticipation

of higher prices. This biases investment still further. What looks

like a virtuous cycle to the individual who invests in land looks like a

vicious circle to businesses that produce things of value and that lose

their financing to those caught up in a land-buying frenzy. Net effect:

More investment in land, less in physical capital.

Price effect. The second consequence of rising land prices on capital

investment is a price effect. As the price of land rises relative to construction

materials, builders will substitute capital goods (mostly buildings

and equipment) for land. (Alfred Marshall ([1890] 1920: Appendix G)

foresaw this clearly.). This is a price effect that occurs whenever the relative

price of inputs changes. As we have already seen from the statistics

cited above, as the relative price of constructionmaterials falls compared

to land prices, developerswill engage in a flurry of construction. Nothing

is ever quite that simple, to be sure, since building materials like metals

and lumber and cement are land-intensive in their own production, but

the net effect is: Less investment in land,more in physical capital.

Wealth effect. The third effect of rising land prices is a wealth effect,

according to which landowners feel richer than before and spend at

least part of the rise in value of their paper assets. The wealth effect is

either inflationary, if no value is produced in conjunction with higher

spending, or simply destructive of capital, if consumption displaces

saving. Net effect: Saving declines, as illusory income is spent on consumption

goods.

Sprawl Effect. A fourth effect is the capital cost of sprawl (scattered

settlement). Scattering a given population over more space calls for longer

roads, pipes, wires, canals, and all kinds of connective capital, plus

more vehicles, more fuels with wells and mines and refineries. It is a

long list that the reader can supplement. The land idled in hollowedout

cities may be replaced by suburbs and exurbs and whole counties

filled with dachas and their connective infrastructure.

What is the net effect of all of these complex interactions? To find an

answer, we must first distinguish between two types of capital, which

are actually differences along a continuum, not distinct categories.

332 The American Journal of Economics and Sociology

However, for the sake of simplicity, we will refer to them as “circulating

capital” and “fixed capital.” We draw the distinction sharply here to

emphasize that not all capital investment is alike and that the behavior

of land markets strongly influences which kind of capital will dominate

investment.

Circulating capital here stands for a one-time investment that quickly

generates revenue that can be reinvested again and again. In other

words, it is capital (K) with high turnover. We can think of turnover (T)

as the number of times capital is recouped in a year or some other time

period. It is the reciprocal of the payout period (P), or the time required

to produce enough value to fully recoup the original investment.

For example, a children’s lemonade stand with a $2 investment (K) in

lemons and sugar at the start of the day might yield $10 in revenue. In

that case, T is 5 because the capital turns over five times in one day, and

P is 1/5 of a day. In a small convenience store, if K is $100,000 ($50,000

for initial payroll and $50,000 for inventory), T might be 12, so the flow

of capital (F) would be 12 3 $100,000 5 $1,200,000. We assume here

that the revenue in each payout period (one month) is sufficient to pay

forwages, inventory replacement, and other operating costs.

In general, capital investment (K) times turnover (T) equals the flow

of capital (F) or KT 5 F. For a given level of investment, the higher the

turnover and flow, the more will be available to hire labor. If the inventory

in this hypothetical convenience store turned over only twice a

year, the flow would be only $100,000, which is also the amount that

would be available to pay wages and other costs. Thus, the ability of

capital to sustain labor is as much a question of turnover as it is the size

of the capital stock.

If that sounds novel to modern ears it is a sign of retrogression in economic

thinking: Adam Smith, David Ricardo, Knut Wicksell, and before

them, Turgot spelled it out clearly in their classic works.

Fixed capital here refers to capital that yields value slowly and thus

turns over slowly. It is typified by a house, office building, or factory,

where capital turns over only once every 40 years (or more). (Thus T 5

1/40 or 0.025.) Since interest is the primary cost of a long-term investment,

a given level of capital yields a dramatically reduced flow, so that

KT > F. For a 40-year loan at 8 percent interest, 70 percent of payments

are for interest, and only 30 percent are available to yield net value of

Real-Assets Model of Crisis 333

production.3 Even with an interest rate of only 4 percent or a building

life of 20 years, interest would still claim 50 percent of total payments.

Thus, in the case of fixed capital, interest drives a wedge between initial

investment and the production of value. The lower the turnover (or,

equivalently, the longer the payout period) the more capital is diverted

into simply maintaining itself rather than combining with labor to add

value. If fixed capital becomes too large a portion of total capital in use,

this imposes a drag on the entire economy.

This brings us back to the question of land prices. When land prices

start to rise during a boom, investments in circulating capital are shifted

to fixed capital. The latter now suddenly seems more profitable

than mundane investments in the circulating capital of productive

enterprises. This illusion of highly profitable construction is created by

conflating the increase in land values with returns on construction, an

easy mistake to make since revenues do not announce themselves as

payments for location as opposed to structures. In fact, the return on

construction will be negative for many buildings produced in a boom

period, since construction on marginal land is often abandoned or

delayed for many years. As in a Ponzi scheme, some early construction

investments may turn out to be profitable, but much of the capital

invested in construction is simply wasted, gone forever.

The dissipation of private investment on fixed capital is matched by

the equally foolish investment of public funds in similar projects. Even

where private developers pay for infrastructure within the area of their

project, local governments pay for later maintenance and often pay for

utility pipes, arterial roads, and other amenities years in advance of

actual development. If the development never takes place and the

developer goes bankrupt, cities and counties may be faced with

massive debt that yields no return, so they must reduce spending on

other services to repay it.

From a macroeconomic standpoint, there is no difference between

public and private borrowing and the resulting debt overhang. In both

cases, the investment in fixed capital, particularly in cases where repayment

stops or is delayed, creates a severe drag on the economy because

productive enterprises are starved for financing for several years. That

is why so many small businesses face bankruptcy in the early stages of

economic contraction.

334 The American Journal of Economics and Sociology

Overextended Banks

The final element in the real assets theory of economic crisis is the process

by which banks become overextended and highly leveraged.

Banks are the public face of economic crises because their lending

behavior during a boom adds fuel to the fire and their foreclosure on

borrowers during the contraction phase adds to the drama that makes

them seem like the villains.

Banks are always heavily leveraged, meaning their reserves are a

small percent of their loans. Leverage enables banks to profit during

boom periods because the value of their assets seems to be rising in the

form of the real estate they hold as collateral. But eventually, the price

of real estate reaches a peak and begins to fall. At that point, the value

of bank assets is put in danger. Everyone tries to sell their real estate at

the same time, but that just drives the price down further. When borrowers

cannot repay their loans or choose to abandon property that is

“under water” (worth less than the loan on it), the bank takes the property

that was held as collateral. Now banks have a lot of low valued

property that they cannot sell. Their reserves become tied to these illiquid

(unsellable) assets, so they can no longer lend money to small

businesses for their operational expenses. As a result, bankruptcies rise

dramatically.

The price of land could not rise during a speculative binge unless

banks and other financial intermediaries were willing to lend money

against inflated collateral values. Bankers thus contribute to the speculative

process by expanding their balance sheets and knowingly leveraging

their assets beyond the bounds of good business practice,

sometimes to the point of criminality. Creating subprime mortgages

and lending money to families that banks knew would not be able to

repay their loans was not an innovation in the 2000s. The same policy

was put into practice during the 1920s, but it was called “shoestring

financing” then. In addition, lobbyists for the banking industry persuaded

the U.S. Congress to overturn the Glass-Steagal Act, which was

adopted during the Great Depression to separate commercial and

investment banking. Enabling the same banks to perform both operations

permitted them to turn normal mortgages into collateralized

mortgage obligations, through which they cut up mortgages of various

Real-Assets Model of Crisis 335

levels of risk and repackaged them for sale as investment instruments.

When land prices dropped, and those assets fell far below their face

value (thereby becoming “toxic”), it was nearly impossible to hold

mortgage lenders accountable for their irresponsible lending.

Although a few investment bankers profited handsomely by putting

the global economy at risk, other banks such as Lehman Brothers

gambled and lost. Many commercial banks that participated in the

euphoria of making money from rising land values also created the

conditions of their own illiquidity. For the year ending June 1, 2010,

Goldman Sachs showed a 24.5 percent return on equity, but during the

same period, the return for all banks was only 3.5 percent, far below

the S&P average of 14.5 percent (Reuters 2010). By 2014, when the

return for all banks had risen to 10.2 percent, the five-year average for

banks was 4.7 percent, suggesting a very slow recovery in the banking

sector (Reuters 2014). Even those figures exaggerate the health of banks

in the wake of the crisis. If banks were required to “mark to market”

(assign current market value to their real estate assets), large numbers

of seemingly healthy banks would have been bankrupt in 2010, meaning

their liabilities would have exceeded their assets and their equity

would have been negative.

In summary, the real-assets theory of crisis views the disorganized

activities of land speculators and the organized activities of ambitious

bankers as equal partners in fomenting the cycle of boom and bust.

They work in tandem to freeze capital in forms that take years to thaw,

thereby undermining the flexibility of the economy and the banking

system at the same time.

Comparative History

We now have the outline of a real-assets theory of economic crisis

that can explain major periods of expansion and contraction in any

economy in which land is exchanged through impersonal, monetized

markets. Feudal and modern socialist command economies lack that

characteristic. Thus, the model predicts that, whereas they may have

suffered low productivity and short-term business cycle problems due

to production bottlenecks, they should not have experienced the sorts

of dramatic swings to which modern market economies are subject.

336 The American Journal of Economics and Sociology

Market economies have, however, experienced cycles of boom and

bust for centuries. In the United States, peaks occurred in 1797, 1817,

1836, 1857, 1872, 1893, 1909, 1928, 1957, 1973, 1989, and 2006. There

are individual studies of a number of these panics, although few economists

have noted that they have common characteristics and occur with

regularity every generation. As Carmen M. Reinhart (2010) has noted:

“The economics profession has an unfortunate tendency to view recent

experience in the narrow window provided by standard datasets. With

a few notable exceptions, cross-country empirical studies of financial

crises typically begin in 1980 and are limited in other important

respects. Yet an event that is rare in a three-decade span may not be all

that rare when placed in a broader context.” The “South Sea Bubble” of

1720 is well known. Before that was the Dutch “Tulip Bubble.” One

French historian has documented cycles as far back as the 12th century

(Levasseur 1893).

One piece of evidence of a common pattern has already been presented:

the similarity of the successive rise and fall of home building

and nonresidential construction, approximately two to three years

apart. For the United States, there is some statistical evidence that that

pattern can be traced further into the past, although the data become

murkier the further back we go. In the decades before the Great

Depression, the peaks in the value of housing construction occurred in

1892 and 1909, in each case followed by a drop of more than 20 percent

in the following year. In 1892, the peak in residential and nonresidential

construction coincided, whereas in 1909, the nonresidential

peak followed by one year, in 1910 (U.S. Census Bureau 1975b: Columns

73, 75). This confirms the real-assets theory, but it raises doubts

about the generality of the pattern by which nonresidential peak construction

occurs two or three years after the peak in residential construction.

A theoretical explanation for this variation is called for, but

we offer none here. This is another area for further study.

Hoyt (1933) offers further empirical evidence that land values peak

immediately prior to major depressions, and he extends this analysis

back to 1835. He does this by focusing on a single city: Chicago. In this

case study, he was able to gather data on actual land values rather than

having to rely on proxies such as the value of construction. Hoyt (1933:

348) shows land value peaks in 1836, 1856, 1872, 1891, and 1928,

Real-Assets Model of Crisis 337

followed by a decline in land prices of at least 50 percent in all but one

case (1872), when prices fell “only” 33 percent.

In addition to confirming the general hypothesis that land value peaks

precede depressions, Hoyt (1933: 347) also reveals the differential pattern

within a city. Table 1 shows the value of land in Chicago in 1910, 1928,

and 1933 according to usage categories: the Loop (central business district),

outlying business districts, residential, industrial, and total (citywide

average). The data clearly show that land values shift to more peripheral

locations during boom periods and contract more severely in those same

areas after a crash. Thus, land values in the central business district did

not even double from 1910 to 1928, but land for housing and outlying

business districts grew by a factor of 4.5 and 6.7, respectively. The subsequent

crash was also much greater in outlying areas. This shows that the

volatility of land prices is in newly-developedmarginal lands.

The central business district contained only 0.1 percent of the land in

Chicago’s borders in 1933, and yet it held at least 20 percent of the city’s

land value during most of its first century of expansion. The percentage

fell during boom periods, when the bubble in land values in outlying

areas took place, but it rose during periods of recovery when peripheral

land values fell faster and further than inner-ring land values did.

(Simpson and Burton (1931) elaborated on this phenomenon and provided

one inspiration for Hoyt’s work.)

In England, for example, between 1892 and 1926, the average price

per acre

 

 

has come from state-owned banks. In addition, all land is owned by the

state in China, in contrast to most other countries, where individuals

and businesses own land in fee simple. Nevertheless, de facto private

ownership of land occurs in China through 70-year leases for residences

and 50-year leases for most commercial purposes. As a result, the

economic fundamentals are the same, and those characteristics are

likely to supersede the differences.

The most notable resemblance between China and crisis-afflicted

Western nations in relation to macroeconomic instability is the rapid

increase in land prices over a period of five or more years. Gyourko

et al. (2010: Figure 5) have estimated that land prices in Beijing rose

more than 750 percent from 2003 to 2010, but they are hesitant to

regard that as a price bubble, absent more complete knowledge about

China’s property markets over a longer period. (By contrast, average

housing prices in 35 cities rose only 100 percent during the same period

(Gyourko et al. 2010: Figure 1). This reveals the much higher volatility

of land prices than housing prices, as one would expect.)

Gyourko et al. (2010) and other analysts present other evidence that

a land-price bubble had begun to form in China by 2007. For example,

Gyourko et al. (2010: Figure 3) shows a price-to-rent ratio in eight major

cities, in which the mid-point of the eight cities was around 30 from

2007 to 2010. (Previous years are not available and thus historic trends

cannot be observed because data were not collected before 2007.) By

comparison, Davis et al. (2008) show the price-to-rent ratio in the

United States rose to 30 only from 2005 to 2007, just before the bubble

burst. However, this information is not decisive, since the price-rent

and price-income ratios have only limited predictive ability in forecasting

price peaks and declines. Until there is evidence that they predict

over-investment in fixed capital, they function only as secondary indicators

of a price bubble.

Another sign of a reversal in the housing market that will lead to a

general economic contraction in China is the buildup of housing inventories.

Nie and Cao (2014: 3) report this accumulation in the past two

years in China: “The average inventory-to-sales ratio—a measure of

how many months it would take to sell all existing inventory at the current

rate of sales—rose 50 percent in the past 12 months, from 12

months in June 2013 to 18 months in June 2014, a rate well above the

Real-Assets Model of Crisis 343

United States’ 5.8 months.” Nie and Cao (2014: 1) also point out that

investment in private housing in China has grown an average of 20.2

percent per year since 1998, double the rate of GDP growth, and it now

comprises 15 percent of GDP. Thus, a decline in housing construction,

almost certain, given the excessive inventory buildup, will have a large

and immediate effect on the overall growth of the Chinese economy.

We should have learned from earlier boom-bust cycles that the seeds

of bank failure may be sown in a small number of jurisdictions. Those

jurisdictions are often not the largest cities. Thus, national averages of

land prices, house prices, and inventories, and statistics about prices in

the largest cities may not accurately warn of an impending crash, which

may come from the hinterlands. China is now famous for its “ghost cities,”

massive investments in land and infrastructure that stand virtually

idle, but since there are only a handful of them, they are statistically

unimportant by themselves. Far more relevant are the thousands of

small, underutilized development projects, scattered in hundreds of

small cities and towns. Davis and Fung (2014) summarize the situation

in the large number of small- and medium-sized cities, which is precisely

where trouble has been brewing.

Evidence is mounting that in dozens of third- and fourth-tier Chinese

cities rarely visited by foreigners, overbuilding is out of control and a

major property-market slowdown is now under way. The 200 or so Chinese

cities with populations ranging from 500,000 to several million

account for 70% of the country’s residential-property sales. In many of

these cities, developers are slashing prices and offering freebies such as

kitchen furnishings and parking spaces as they try to work through vast

gluts of unsold property. Protests are breaking out among buyers angry

that their investments are losing value.

Overbuilding in small cities throughout China is a much better indicator

of a coming decline in land prices and loss of bank liquidity than

indices that measure only the big cities. Of course, if the building boom

in Beijing, Shanghai, and Hangzhou occurs on the margins of those

cities, then their condition could contribute to a major economic reversal.

However, since no existing construction or price index reveals the

location of construction, that aspect of the process will remain hidden

until after the crash occurs, and the location of abandoned projects in

344 The American Journal of Economics and Sociology

major cities becomes apparent. While bad investments in the center of

a city may eventually be recovered, investments on the periphery will

normally be lost forever.

It would also be desirable to know much more about the commercial

real estate building boom and its impending collapse. As early as 2010,

office towers were facing vacancy rates of 15–17 percent in Beijing and

13 percent in Shanghai (Colliers International 2010). That was viewed

as mildly alarming at the time. It has now become clear that the problem

of excessive expansion in real estate is a national problem, particularly

in the mid-size cities. Frank Chen, executive director for China of

CBRE, explains that the vacancy rate in second-tier cities is 21 percent,

double the rate considered healthy (China Economic Review 2014).

FlorCruz (2014) cites an example of this phenomenon: “Chengdu, in

the southwestern province of Sichuan, embodies the problem faced by

many Chinese cities—a huge oversupply of buildings spurred by abundant

finance. Nearly half the offices in the city are now vacant, and the

problem is expected to worsen: More than 1.5 million square meters of

space are scheduled to be completed this year.”

As if the rise of land values and excessive construction of housing

and commercial units were not enough, local governments in China

have also been borrowing heavily and guaranteeing loans, all to engage

in real estate developments of various kinds: to buy land or make infrastructure

improvements. According to Davis and McMahon (2013),

local government debt grew from 10.7 trillion yuan in 2010 to 17.9 trillion

yuan ($3 trillion) in 2013, and only a small portion of the increase

has come from conventional banks. More than 10 percent of financing

now comes from “shadow banks” and about 17 percent comes from

“other” sources. The transition from conventional sources of capital

represents a decline in the quality of the investments. Davis and

McMahon (2013) continue:

China’s world-beating record of about 10% annual growth for the past

three decades is based in large part on local governments spending

heavily on such building projects. But since the global financial crisis of

2008, that construction has depended more and more on heavy borrowing

and often resulted in dead-end projects that have a tough time paying

their bills, economists say. Nearly half of the debt comes due by the

end of 2014.

Real-Assets Model of Crisis 345

The reference to “dead-end projects” is a good indicator of the falling

quality of local government investments. It points toward the problems

that arise when marginal sites are being developed during a boom,

locations that cannot generate enough revenue to repay loans.

As Das (2014) explains, 90 percent of bank loans since 2008 were

invested in fixed assets, particularly by state-owned enterprises. The

result has been a total debt held by government, corporations, and

households of around 200–250 percent of GDP. Local government debt

is around 25 percent of the total, and its share of the total has increased

substantially since 2008. But, Das continues, official debt statistics do

not include various off-budget forms of debt, such as “nonperforming

loans purchased from state-owned commercial banks, which all trade

on the basis of an explicit or implicit government support.” Thus, it is

difficult to know the true debt situation in China today. This somewhat

parallels the condition of today’s Euro-zone, where major banks

depend on presumed government support, while the supporting

governments depend on the banks.

Many commentators in the past few years have discussed the ballooning

investment by the Chinese government and rising debt levels.

For example, gross capital formation in China was 49 percent of GDP

in 2013, more than double the world average (World Bank 2014). But

the quality of debt is at least as important as the quantity. According to

Das (2014):

Chinese data measures two different types of investment—gross fixed

capital formation measures investment in new physical assets which

contribute to GDP and fixed-asset investment measures spending on

already existing assets including land. In 2008, gross fixed capital formation

and fixed interest investment were roughly equal. Today, gross fixed

capital formation has fallen to about 70% of fixed-asset investment, consistent

with increasing turnover of already existing assets at frequently

rising prices. Investment in new assets is heavily focused on frequently

large scale infrastructure and property. The major concern is that many

of the projects will not generate sufficient income to service or repay the

borrowing used to finance the investment. (Italics added.)

Since land is the primary existing fixed asset in which investment occurs

without adding value, this evidence confirms that the Chinese economy is

nowbeing weakened by excessive investment in a land boom.

346 The American Journal of Economics and Sociology

Riddell (2014) makes the same point, although more obliquely. He

notes that China’s nominal growth rate has slowed from an average of

10 percent per year to 7.7 percent in 2013. At the same time, the rate of

investment has increased from 48 percent of GDP to 54 percent. Logically,

he suggests, this is a sign of danger. If investment is increasing

and being used productively, GDP should be rising in step with the

new capital. However, if the growth rate of GDP falls as investment

increases, that indicates investments are either sterile or not adding as

much value as before. Riddell (2014) continues:

It should be a concern if a country experiences a surge in its investment

rate over a number of years, but has little or no accompanying improvement

in its GDP growth rate. . .. This suggests that the investment surge

is not productive, and if accompanied by a credit bubble (as is often the

case), then the banking sector is at risk (e.g. Ireland and Croatia followed

this pattern pre 2008, Indonesia pre 1997). . . . The most likely explanation

for China’s surging investment being coupled with a weaker growth

rate is that China is experiencing a major decline in capital efficiency.

Whatmight cause a “credit bubble” or a “decline in capital efficiency”?

In the absence of any reference to real estate or other real assets, presumably

Riddell, like most other analysts, would assign responsibility to the

banking system.

A more plausible explanation, and one that fits the real-assets model

presented in this article, is that the bubble and decline in capital efficiency

are the result of speculative investment in land, particularly marginal

land, and in complementary fixed capital, which will lose much or

all of its value after a crash. Before the economy becomes frozen, these

investments are counted as contributions to growth, but eventually they

will turn out to be sterile because they actually drain value from the

economy rather than adding to it. At that point, the previous growth will

be revealed as a mirage. The problem is thus not the total quantity of

debt per se, which is positive as long as it is productive and selfliquidating.

The threat posed by debt to the national economy arises

only when it fails to turn over with enough frequency and engage with

labor in producing needed goods and services. The total quantity of debt

is relevant only because high levels and high growth rates of debt generally

indicate investment inmarginal land and capital projects.

Real-Assets Model of Crisis 347

Despite all of the signs that the days of China’s miraculous growth

are coming to an end, opinion remains divided about whether it is facing

a crisis similar to the one experienced by the United States and

Europe in 2008. Leeb (2013), still bullish on China in July 2013, wrote:

“Whatever overbuilding China may have done, it was simply insufficient

to create an economic crisis. The IMF authored the most comprehensive

report to date on Chinese overinvestment. China’s debts,

unlike those of the U.S. and most other countries, the IMF notes, are

owed to China itself. Therefore, the risks of a full-blown Chinese economic

crisis remain small. . .. [F]ears of a Chinese real estate bubble in

particular are way overblown.”

Nevertheless, the “overblown” bubble seems to be starting to burst.

CNTV (2014) reports a 7.6 percent decline (annualized basis) in house

prices from January to July 2014 in 70 Chinese cities. Anderlini (2014),

writing in the Financial Times, announced that the March 2014 default

of Zhejiang Xingrun Real Estate Company, a Chinese developer,

prompted an emergency discussion with China Construction Bank, its

largest lender, and the central bank of China about a potential bailout.

Zhiwei Zhang, an economist at Nomura Securities, added that most

financial analysts had not yet taken account of the growing risk of such

defaults because they were misled by rising land prices in big cities,

even as property values had dropped by as much as one-third in some

provincial areas, which accounted for two-thirds of the housing under

construction in 2013.

The Chinese government sought in January 2014 to slow the boom in

property prices by limiting credit (Kerkhoff 2014). By September, it had

reversed course and was trying to prop up the sagging housing market

with incentives for first-time home buyers (Qing and Shao 2014). But

the government is learning the limits of its power to control markets

with short-term financial instruments. Even though the government

owns all of the banks in China, it will not be able to stem the tide of

defaults in a falling land market because it can do nothing to transform

fixed capital, tied up in real estate, into productive circulating capital.

The real-assets model thus predicts that China will face a significant

decline in growth rates over the next three to five years, possibly dropping

into the realm of negative growth. Unemployment will rise, and

conventional stimulus techniques will fail to revive the economy. Land

348 The American Journal of Economics and Sociology

and other asset prices will fall, and if the Chinese banks mark them to

market, they will face liquidity problems in the short run. If they fail to

revalue assets and keep them on their books according to their historic

highs, as Western banks have generally done, it will take even longer to

recover because banks will only be able to resume normal lending

when land prices rise enough to reach the levels of 2013.

Policy Responses

We have now seen evidence from a number of countries that a real

assets theory can account for a number of past and present economic

crises that have otherwise been attributed solely to financial mismanagement.

By integrating real variables into the model (investments in

land and fixed capital compared to circulating capital, and the geographic

location of investment), policymakers have more options to

use in formulating instruments to prevent asset bubbles and financial

crises.

Post-Crash Response

The current orthodoxy about economic crises is that each one is peculiar

and that it is therefore impossible to model them or create policies

to prevent them. Each is caused by a sudden change brought about by

external forces, an “exogenous shock,” such as a sudden increase in oil

prices, the default of a major bank, or the rapid withdrawal of capital

from a nation’s banking system. In such a world of random cataclysm,

all one can do is to make an effort to stabilize the economy after a

shock with fiscal and monetary policies. The debate is then mostly limited

to a conflict between the call for austerity and the call for stimulus.

Even within the framework of this orthodox account of randomly

generated crises, there is one policy that could be implemented. After a

crash has occurred, one simple response that would restore an economy

to normalcy in short order would be to require all banks to value

their assets at current market value. Banks that lent wisely instead of

joining the mob mentality at the height of the boom would have nothing

to fear. By contrast, banks that supplied land speculators with credit

would face bankruptcy, and equity holders would lose their investment

in the bank. This policy need not weaken the banking system as long

Real-Assets Model of Crisis 349

as the central bank provided enough equity on an emergency basis to

keep the bank operating until private investors could be sure the toxic

assets had been removed and were again willing to buy the government’s

shares. This policy of requiring honesty in accounting could

have the effect of deterring banks in the future from financing asset values

not merited by normal lending practices. However, since many of

the largest banks are now “too big to fail,” meaning too big to be held

accountable, it is not clear whether this remedy could actually be

applied.

Crash Prevention: Using the Real-Assets Model

The real assets model proposes two possible methods of preventing

panics before they ever have a chance to get started. The first method

involves credit controls. The second method involves real-asset price

limits.

Credit controls

The original impetus behind periodic booms and busts in modern

economies is the desire to gain a profit by investing in an activity that

generates economic rent—money for nothing. As a collective frenzy

builds, banks become involved and accommodate the boom with lending

against properties with inflated value. As a result, it seems to many

analysts that the best way to prevent or control the boom is to limit

credit.

On its face, increasing interest rates, capital requirements, down payment

requirements, or any number of other rules ought to be capable

of regulating aggregate financial transactions and preventing speculative

booms from occurring. In practice, however, most such efforts ultimately

fail. When land prices start rising, lenders in booming cities or

regions become more resourceful in finding ways to circumvent regulations,

sometimes legally, sometimes not. This does not mean that financial

regulations can be ignored. It means that other instruments must

also be pursued.

One conclusion that has been derived from the series of economic

crises in developing nations is that they should protect themselves from

boom and panics by instituting capital controls—rules that limit the

amount of money that can be invested from outside the country.

350 The American Journal of Economics and Sociology

Logically, this makes a great deal of sense. Palma’s (2000) analysis of

crises in Chile, Mexico, and Malaysia in the late 1990s indicates that

their economies were destabilized by a rapid influx of capital, followed

by a sudden decline a few years later. In a relatively small economy,

only a small amount of mobile capital can cause instability. The model

Palma uses, however, presupposes that the boom in asset prices in

those countries was caused by the influx of capital.

Kim and Yang (2008) investigated the validity of that assumption and

discovered that although capital inflows in emerging Asian economies

contribute to booms in asset prices, they only explain a small part of

asset price fluctuations. Kim and Yang (2008: 18) conclude: “Capital

inflows indeed contributed to asset price appreciation in the region,

although capital inflow shocks explain a relatively small part of asset

price fluctuations. Positive capital flow shocks increase stock prices

immediately and land prices with some delay.” One might assume,

nevertheless, that capital controls can help regulate boom-bust cycles

in small, open economies. Olaberr_?a (2012:18) finds just the opposite:

“A perhaps surprising result is that higher capital controls (less financial

openness) do not appear to reduce the probability of large capital

inflows being associated with booms in real asset prices.”

Consider also the anomaly that exchange controls in central Europe,

early in the 1930s, were focused on blocking capital exports, not

imports (Ellis 1941).

Again, the conclusion from recent evidence seems to be that regulatory

controls can only be partially successful in preventing the sorts of

asset price fluctuations (booms and busts) that destabilize market

economies. If the instability of developing economies comes primarily

from factors internal to those economies, attention should be focused

on getting the fundamentals right.

Since the major economic disruptions of Mexico and Malaysia are surprisingly

similar to the periodic crises that have affected Japan, the United

States, China, and Spain, it would seem that “the fundamentals” are universal,

not limited to economies that require financial “deepening.”

Taxing land values to limit asset prices

Although adopting financial regulations that limit the credit that banks

can issue during a boom may help prevent future economic crises, it is

Real-Assets Model of Crisis 351

not a sufficient solution. The problem lies mainly in implementing the

restrictive rules adopted after a previous crash and enforcing them

when rising incomes precipitate the next round of growing asset values.

Bank regulators who try to enforce such rules during a boom are trying

to fight psychological forces that deem the rise of asset values as

“progress.”

A second approach is also needed to contain the problem at an early

stage, before asset prices rise fast enough to create the collective frenzy

that becomes difficult to control. The required instrument would reduce

the incentive of borrowers to invest in fixed assets. A substantial tax on

the value of those assets, particularly on land values, would lower the

price at which those assets trade and simultaneously raise holding costs.

At present, a borrower who can borrow $1 million with a $100,000

down payment must pay carrying costs (interest) on $900,000, a fixed

amount for the life of the loan. By contrast, if the price of land is subject

to a heavy tax, the carrying costs are divided between interest and tax

payments. If tax assessments are updated frequently in a rising market,

the part of the holding cost associated with the tax will rise with the

price and send a signal to buyers discouraging them from purchasing

land for speculative purposes. With that simple device, it should be

possible to prevent the growth of asset values (particularly land values)

beyond their productive capacity. What gives rise to a boom is the idea

that a purchase can be quickly sold to another person who also expects

the rapid escalation of prices. A tax, backed by frequent reassessments,

automatically tempers and dampens that process. When fee-appraisers

base their valuations on “comparable sales,” overpricing of each parcel

generates a cumulative reflective process wherein overpricing may

reflect or reverberate back and forth (Gaffney 1986). When a taxassessor

follows an upswing in comparable sales it has the opposite

effect. I am not aware that this important tempering function of land

value taxes as been recognized either in the literature or in the consciousness

and practice of market actors.

The effectiveness of the use of property taxation as a method of limiting

speculation has implicitly been demonstrated to some extent in the

United States. A number of states have adopted legislation that limits

the rate of increase in the assessed value on residences. California

began the process in 1978 by limiting additions to assessed value for

352 The American Journal of Economics and Sociology

property tax purposes to no more than 2 percent per year. Similar laws

were subsequently adopted in Alabama, Arizona, Arkansas, Florida,

Georgia, Illinois, Iowa, Maryland, Michigan, Nevada, New Jersey, New

York, Oklahoma, Oregon, South Carolina, Texas, and Washington

(Mikhailov and Kolman 2002). In the subsequent economic crisis, the

eight states that led the nation in foreclosures (Nevada, California,

Arizona, Florida, Oregon, Illinois, Georgia, and Michigan) all had

assessment limitations. Legislation that was intended to protect homeowners

had the unintended effect of permitting higher land prices and

greater land speculation because assessments could not keep up with

rising prices and thus temper the “irrational exuberance.”

In nations where provinces or states control the assessment and taxation

of land, the disruptive character of land speculation is beyond

the reach of the central government. In China, that is not the case. In

principle, at least, the central government can implement a land value

tax or property tax that would limit investment in land for speculative

purposes. Thus, it is significant that the leadership of China, alone

among nations, has explicitly stated the intention of adopting a

property tax as a method of controlling speculation in housing prices.

Xinhua News Service (2006) reported that a prominent economist, Lin

Yifu, director of the China Economy Research Center of the Beijing

University, favored a property tax “to rein in speculative investment

and ward off a possible financial crisis.” Four years later, “a report submitted

to Deputy Premier Li Keqiang said surging prices for housing

price posed a threat to social stability” (Tao 2010). Presumably, the

news was not that a report was written, but that Deputy Premier Li

had accepted it. Li Keqiang, a trained economist, became Premier of

China in March 2013 (the number two position in the government).

That same month, the government announced a plan “to introduce a

unified national property registration system by the end of 2014,

which could eventually make it possible to impose an annual property

tax on households—yet another way the authorities expect to fight

housing speculation and fend off bubbles” (Barboza 2013). In the second

half of 2014, as the crisis began to unfold, and house prices began

to fall in most of China, top officials remained quiet (Lelyveld 2014). It

seems likely that top government officials are aware that China’s

banks will soon face a liquidity problem, but a property tax and other

Real-Assets Model of Crisis 353

preventive measures that might have prevented a rise in housing

prices can no longer avoid a crisis.

Conclusion

One of the most basic principles of economic theory is that it deals with

real costs: the time, energy, and materials we give up in one pursuit to

follow another. In that sense, money is not real. It is just a symbol.

There is no real cost when we spend money. In the same way, money,

by itself, does not represent the creation of value. It merely serves as a

claim on value that is created by real economic activity.

A great deal of economic analysis in recent decades has created confusion

on this basic point. It treats money as an object of analysis as if

the manipulation of symbols is the same as the management of real

relationships. For example, the standard Keynesian identity that equates

GDP with consumption plus investment plus government spending

plus net exports creates the illusion that we can remain indifferent

about the qualitative features of each variable. Macroeconomics, in this

view, is simply a matter of balance sheets and has nothing to do with

the real productivity of private or public investments. In this world of

magical thinking, a dollar spent on education is the same whether students

gain any proficiency or not.

The two most important features of a real-assets model are 1) that the

real economy matters, and 2) that the health of an economy depends

on the quality, as well as the quantity, of investments. Those who claim

that banks can expand their balance sheets arbitrarily and without adding

deposits are correct. But in doing so, banks destabilize the financial

system by increasing their leverage—lowering the ratio of equity to

assets. If they are simultaneously reducing their liquidity by investing

heavily in fixed capital (long-repayment projects) rather than circulating

capital (short-repayment projects), they are pushing the entire economy

into a hazardous position.

The real-assets model explains why economic crises have been a

recurrent feature of capitalist economies for the past two centuries and

more. The French historian Pierre _Emile Levasseur (1893) traced cycles

back to 1200 A.D. The problem is not inherent in the private ownership

of capital, the characteristic feature of capitalism. The systemic flaw lies

354 The American Journal of Economics and Sociology

in the failure to ensure that investment is balanced between circulating

capital and fixed capital. The greatest crises arise when land is not taxed

adequately to prevent the speculative growth of its value. Land speculation

then leads periodically to overinvestment in complementary fixed

capital, often in peripheral areas of low inherent value. Credit becomes

tied up in long-term investments, many of which eventually default.

The resulting foreclosures leave banks with overvalued assets that they

refuse to mark to market, leaving banks unable to generate new credit

during the lengthy recovery.

For a number of years, it seemed that the Chinesemiracle of rapid economic

growth based on massive public investment would somehow

steer clear of the economic distress caused by land speculation and marginal

investment in capital projects. Because of the backlog of latent

demand in that economy for better housing, it was possible to construct

thousands of projects in mid-size cities without exhausting the ability of

China to make efficient use of those investments. By 2014, however, it

became clear that China’s economy had reached a limit of productive

investment in housing and other fixed investment and would be subject

to the same constraints as other economies. There were voices in China

that began warning of this fate as early as 2006, but they were ignored. It

now seems likely that China will face several years of sluggish growth as

land prices fall, defaults rise onmarginal projects, and the loss of liquidity

of the state-owned banks forces the central government to cut back on

its investments. At the same time, as house prices fall in the major cities,

the urban middle class will respond to its reduced nominal wealth by

cutting back on consumption. The combination of these effects will

reduce growth further and increase the rate of unemployment.

The one ray of hope in this otherwise gloomy picture is that some of

the top leadership of China is at least aware that rising land prices need

to be controlled by means of taxation. This is the first sign that any

national government has recognized the use of land value taxation as

an instrument of macroeconomic policy. Although that recognition

came too late to prevent the present crisis in China, it could be used to

prevent future repetitions of the present situation. If China can learn

that lesson in its first experience with a boom-bust cycle in land values,

it will be far ahead of Western governments that have ignored the signs

for centuries.

Real-Assets Model of Crisis 355

Notes

  1. There is no index of land prices in the United States to show this. There

are, however, many studies of particular times and places and industries that

show the point clearly enough to be sure of it. We discuss one of them below:

Homer Hoyt’s classic 100 Years of Land Values in Chicago, 1833–1933. Many

others are in the bibliography.

  1. All construction figures from 2002 to 2012 come from U.S. Census

Bureau (2014a). The 2000 estimate of housing construction comes from U.S.

Census Bureau (2012). All monthly figures represent seasonally adjusted

annual rate.

  1. If capital is $5 million, the annual payments at 8 percent will be $419,300.

Total payments will be $16.77 million (40 x $419,300). Of that amount, $5 million

repays the principal, and $11.77 million is interest, which is 70 percent of

the total payment.

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PRICES_BY_GEOGRAPHICAL_AREA.PDF

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