An Access Advertising EconBrief:
Cause and Effect
Early man began trying to link cause and effect by simple observation of the world around him. Combining this with imagination produced the first scientific theories. Over time, man began to record his observations, hoping to weed out chance relationships from the truly systematic ones.
Gradually, science took on a formal character. Logic became a formal study. Early thinkers like Euclid and Pythagoras developed the basic structure of mathematics. Eventually, Newton and Leibniz paved the way for modern science by inventing the calculus. When the foundations of probability and statistics were laid in the late 19th and early 20th centuries, the way was clear for scientists to develop and test theories rigorously.
Although the progress made by the natural sciences has lifted man from the primordial ooze into a life of relative ease and comfort, the social sciences are still finding their proper place in the world. Economics, queen of the social sciences, has yielded the most benefit.
Unfortunately, it has also wreaked the most havoc. Formal economic theory is only a few centuries old – by historical standards, it is in its infancy. The problems of the social sciences tend to be much more complex than those of the natural sciences because human reason and motivation complicates the analytical process exponentially. It is hard enough to learn how plants fight disease, but at least scientists do not have to grapple with any plant motivations more complex than simple survival. Social scientists have tended to assume that the sophisticated mathematical and statistical methods will succeed just as well for them as they have for natural scientists, but it seems increasingly clear that this is not so.
To make matters worse, the general public has an upside-down view of this scientific dichotomy, believing that social-scientific problems are easier than natural-scientific ones. Because the facts of economics are the stuff of everyday experience, we tend to assume that casual observation and common sense are sufficient to allow deduction of cause and effect relationships in economics. As a result, Mark Twain’s Theorem applies with powerful force to public understanding of economics.
Twain’s Theorem is “It ain’t what you don’t know that hurts you, it’s the things you know that just ain’t true.” Popular economic theories of cause and effect, based on casual observation and superficial correlation, have embedded many myths and fallacies in the public consciousness. This leaves much work for economists to undo.
Urban Overcrowding and Poverty
Large populations of urban poor became commonplace during the Industrial Revolution. The sight of thousands of people crammed together in tight quarters, living cramped lives marred by comparatively poor nutrition and hygiene, inspired literary outrage from authors such as Dickens and reformist zeal from do-gooders like Jane Addams. Although average real incomes have zoomed upward in recent centuries, the phenomenon of urban overcrowding remains in cities like Mumbai and Calcutta, India. Today, the mantle of reformism has fallen upon filmmakers.
There has long been a presumption in the general public that the poverty experienced by the masses is due to their excessive numbers and close proximity – that is, to overcrowding. Indeed, this is generally viewed as so obvious that the causal connection is allowed to speak for itself. The tacit argument runs as follows: The more people there are living close to each other, the greater is the competition for the fixed amount of resources in that limited geographic area. As overcrowding increases, resource availability per capita falls. This implies that per-capita production of goods and services will also fall. The limited amount of resources will keep resource prices high, insuring that prices of consumer goods will also be high, causing real incomes of residents to be low.
The urban overcrowding hypothesis has great superficial appeal, particularly when it is given an environmentalist slant. The overcrowding also strains the natural resources of the geographic area by hurting the quality of air, water and land. An inexorable tendency for population to increase creates a doomsday scenario in which both economic growth and quality of life swoon into a downward spiral. Only drastic measures such as forced population control, draconian environmental regulations and socialist distribution programs can save human life or, indeed, the planet itself from destruction.
Urban Overcrowding Explained
Despite its visceral appeal, the urban overcrowding hypothesis is wrong. One of its obvious flaws is the lemming-like behavioral pattern it imputes to hundreds of millions of urban residents. Why should they be attracted and held by a way of life that operates so severely to their disadvantage? The answer is that they aren’t.
Contrary to the impression created by overcrowding theorists, only about 5% of the earth’s land area is occupied by human inhabitation. While some of it is clearly uninhabitable, most of the rest of up for grabs. This puts a crimp in the environmental doomsday hypothesis, since resource depletion can hardly be more than a local matter under these conditions. But the urban poor do not escape their poverty by fleeing the city because their advantage lies in remaining there. Urban overcrowding benefits poor residents in numerous ways.
The urban poor can live much more cheaply in their overcrowded cities than in suburbia or in rural areas. In the city, they have access to mass transportation – buses, subways, taxis – and forms of individual transportation like bicycling and walking that would be uneconomical, hence unavailable, on the outside. Their access to work, entertainment, recreation and medical care is also better. Bear in mind as well that close proximity has offsetting benefits – human companionship can and does serve as a substitute for material wealth.
A corollary to the choice made by the urban poor is the fact that middle-class, upper-class and rich families tend to spend real income on larger living quarters located outside the city. Their larger incomes offset the higher transport and transactions costs of suburban and rural living.
Cause and Effect Reversed
Although the correct reasoning is quite straightforward, stating it in cause-and-effect terms startles most people: Poverty causes overcrowding, not the other way around. Modern science and capitalist markets make it possible for many people to live who would otherwise never be born or would die early in life. These people make the best of their circumstances by living in conditions that those better situated find inexplicable and repellent. Moreover, the terms “poverty” and “overcrowding” are relative, not scientific absolutes. Poverty in the United States implies a level of real income many times greater than the same status does in India.
These facts have not prevented moralists and reformers from decrying the state of poverty and overcrowding in American cities throughout the 19th and 20th centuries, up to the present day.
The “Decline” of Wages and Income
Movements in income and their effects on American households have given rise to other popular theories of cause and effect. The financial crisis of 2008 and ensuing recession have produced persistent and lingering after-effects on income and employment. These have tilled the ground for hypotheses of decline for the U.S. economy and way of life. Two recent books have repeated longtime claims about the flatness of average U.S. wages over the past 30 years. A related claim is that average household income has also declined over the same time period.
These claims result not so much from casual observation as from casualness in the compilation and interpretation of data. Although economists are not normally themselves the guilty parties, they bear a measure of guilt for these popular errors.
In their anxiety to make use of sophisticated scientific tools, economists have fallen over themselves providing data to use the tools on. But the theorizing process only works as long as the man handling the data doesn’t manhandle the data. The combination of haste, carelessness, vested political and academic interest and personal prejudice adds up to a lot of ways for economic theory to go wrong. And when the lay public starts to monkey with the data, the result is chaos.
Take the case of wages. During World War II, the federal government chose to finance the war by borrowing and printing money. In the time-honored manner of governments throughout history, it slapped on controls intended to prevent the expenditure of printed and borrowed money from bidding up wages and prices to the stratosphere. But there were no controls on in-kind benefits like employer-paid health insurance. In addition, these benefits were not taxable by the IRS – unlike earned wage income.
The wartime trend in favor of substituting fringe benefits for wage increases survived the war and accelerated beginning in the 1970s. These benefits constitute real income because people could take wage income and use it to buy health insurance. If employers paid for (day) fruit and vegetable purchases of employees, this would constitute real income to employees for analogous reasons.
Clearly, people who study increases in the average or general level of wages usually do it in order to gauge the purchasing power of wage recipients. Equally clearly, it would be grossly misleading to omit consideration of fringe benefits from this consideration, since it enhances employee purchasing power as well. But all too often this is exactly the mistake made by (non-professional) students of wage trends.
The cause-and-effect theory of the non-professional students is straightforward enough. People work and earn wages in order to get real income with which to purchase goods and services. When their wages stagnate, their real income must do likewise. With rising prices, their purchasing power will fall.
This overlooks the fact that employment benefits also increase real income and purchasing power. And people can choose to work for employers to provide more and better fringe benefits. Thus, a marked trend favoring substitution of non-taxable benefits for taxable wages suggests that people are better served by the former than the latter.
Household Income in an Era of Changing Household Composition
Similar problems await the unwary student of trends in income. One popular data category is household income. At first glance, this choice seems eminently logical. The family is the predominant unit of American cultural and economic organization. Decisions about expenditure and saving are not made by mothers, fathers and children in isolation but rather in a household context.
So far, so good. The problems start when the neophyte starts making simple comparisons between household income at different points in time. Since population tends to increase over time, it seems logical to use average household income as the basis for comparison. But a hidden trap lies in store.
Throughout the Western industrialized world, birth rates have fallen in recent decades. The number of children in the average household has fallen. Divorce has increased, a factor tending to produce more and smaller households.
When the “average” household gets smaller, it will tend to have a lower income – even when business and personal productivity, Gross Domestic Product and other indicators of production and real income have not fallen. And this is exactly what has happened in the U.S. over the last 30 years. While observers have complained about “falling” household income, real personal consumption has increased some 74% over the last 30 years, according to economist Alan Reynolds. This strongly suggests that the decline in household income is artificial, a statistical artifact that does not reflect the true economic reality that the writers and commentators are trying to capture.
Cause and Effect Complicated
Theorists of wage/income decline told a story of cause-and-effect between wages and living standards. Hourly workers work for wages in order to be able to buy goods and services. If wages don’t rise, their consumption can’t rise. Wages increases cause rising consumption; wages decreases cause falling consumption; stagnant wages hold consumption constant.
But this story ran afoul of a confounding third factor – income. In any scientific endeavor, this plagues the linking of cause and effect. Not only is there the problem of deciding which of two correlated variables causes changes in the other, there is also the possibility that neither is the causal agent. A third variable may be causing changes in one or both of the first two.
Here the confounding variable is income. It is really income that facilitates consumption. Wages are one component of income, but benefits are another. A wage decline that is more than offset by an increase in benefits is compatible with an increase in consumption.
A parallel case involves theories of poverty. Studies claiming that the percentage of people living below the poverty line has been largely unaffected by increases in material wealth have generally failed to take into account all sources of income for poverty-level people. The steady rise in the number and size of government transfer programs designed to benefit poverty-level recipients has nurtured a trend in which these types of benefits have simply replaced work-related earnings as income sources. As with employer-paid benefits, this has been the choice of recipients rather than a factor beyond their control.
The Theory of Affordable Housing
A final popular theory of cause and effect is the theory of affordable housing. This theory is the implicit backing behind virtually every federal-government housing enactment since the 1930s. The theory says that, left to the whims and vagaries of a free market, the poorest people in society would die of exposure due to lack of housing or, at best, suffer unconscionably in intolerably poor housing. In order to insure an adequate supply of affordable housing, it is necessary to government to subsidize both the production of housing and its consumption. The government-produced housing is sold to the poor at artificially low prices. Government subsidy programs enable the poor to purchase homes or rent housing at affordable rates.
The Federal Housing Administration (FHA), Federal National Mortgage Association (Fannie Mae), Government National Mortgage Association (Ginnie Mae) and Federal Home Loan Mortgage Corporation (Freddie Mac) are all programs founded on the foregoing logic. The housing bubble preceding the recent financial crisis and Great Recession was fostered by men like James Johnson of Fannie Mae beginning in the mid-1990s, and was started, nurtured and stoked to fever pitch on the basis of this reasoning.
The truly amazing thing about this popular theory is its utter lack of corroboration. All of the available evidence suggests that government intervention in the housing market makes housing less rather than more affordable.
In 1901, housing costs comprised 23% of median income. In 2003, after a myriad of government programs intended to make housing more affordable, the figure was 33%. One of the most infamous of the World War II-era regulatory survivors is rent control, the program ostensibly designed to keep rental housing affordable by putting a legal ceiling on the height to which housing rents can rise. Swedish economist Assar Lindbeck delivered the consensus verdict of the economics profession on rent control by declaring that the best way to destroy a city was by bombing it and the second-best way was by imposing rent control within its boundaries. The artificial shortage of rental housing created by the controls not only reduces the quantity of rental housing available to consumers, it reduces housing quality by giving landlords an incentive to reduce the quality of their housing stock in compensation for not being able to raise rent. It kills the incentive to produce more rental housing but increases the incentive to convert rental housing stock to condominiums, whose prices are not controlled.
Affordable housing activists emphasize the fact that developers do not normally construct housing aimed directly at the poorest buyers. With no new construction of private affordable housing, they reason, it must be true that government production will be necessary to prevent the supply of housing available to poor people from drying up altogether as houses wear out but are not replaced.
Housing expert William Tucker has pointed out the fallacy inherent in this view. As the housing stock gradually ages, housing originally constructed for the rich or well-off eventually declines sufficiently in quality and value to be within the reach of the poor. This process is called “filtering.” Thus, it is not primarily new construction that provides housing stock for the poor, but rather secondary, used housing. As Tucker points out, this gives the lie to the necessity of government housing- construction programs.
A onetime counterargument to the filtering principle is that the poor deserve bright, shiny, new housing of their own. The experience of large-scale federal housing projects built in the 1950s and 60s has silenced proponents of this view. In cases like Pruitt-Igoe in St. Louis and Wayne Minor in Kansas City, tenants and vandals methodically destroyed the quality of the housing. In effect, government ownership is no ownership; the government lacks the private incentive to protect the value of the property.
In addition to direct government interference in housing, indirect interference via Federal Reserve pegging of artificially low interest rates must also be considered. Respected mainstream economists like John Taylor have now conceded that these actions constitute inefficient and counterproductive housing subsidies that were instrumental in inflating the housing bubble. Artificially subsidizing interest rates may make a housing purchase seem superficially more attractive, but it does not create the future real income necessary to amortize a mortgage nor does it make buying a house more economically efficient than renting in true economic terms.
Another form of indirect interference with housing markets is land-use restrictions. Starting in the 1970s, land-use restrictions were part of an anti-growth strategy that greatly reduced the volume of new housing construction in many U.S. markets. The result of a constriction in the supply of new housing is an increase in price. Moreover, the effect of the restrictions was to make the supply of housing more brittle, or less “elastic” in economic language. This means that the quantity response to any increase in demand is more restrained, resulting in a higher price for a given increase in demand. Economist Thomas Sowell showed that almost all of the regional markets that saw sharp upward spikes in housing prices during the housing bubble also featured these land-use restrictions.
Housing markets were among the most stable and reliable throughout U.S. and world history – until governments insisted on making housing affordable. Then we began to experience housing bubbles and ensuing recessions. The case for affordable housing policy is nonexistent.
Cause and Effect Turned Upside Down
The affordable-housing crowd asserts a direct causal relationship between government activity and housing affordability. Reality reveals a relationship that is not only inverse but perverse – the opposite of that intended. The more government intervenes, the less affordable housing becomes. Perversity is an uncommon result in a market economy characterized by voluntary action and rational choice, since people will usually act to bring about that which they intend. But it is typical of government, where people lack the information, the motivation and the incentives to bring about the ends that private individuals would consider optimal.
Cause and Effect in the Social Sciences
The foregoing examples demonstrate that cause and effect in the social sciences is not a simple matter of casual observation and common sense. Instead it is a complex matter that requires the application of training, logic and rigorous study. Economists do it better than non-specialists but are still prey to occupational and temperamental blind spots.