Kuznets: Reified. Reinterpreted. Smashed.

A Lorenz curve is one of the most sensible ways an economist would measure inequality in a society. The yellow line in the graph represents a situation of perfect equality, where each quintile (or one fifth) of the population earns exactly one quintile of the income. That situation is certainly not argued by most economists to be a desirable state of affairs, since perfect income equality is not the policy prerogative of economists or governments. But it is a good measure of how well a society is developing, since development should give rise to, among other things, rising income and equity. By development I simply mean the transition of economy from an agrarian society to a modern, industrialized or consumer society. Any society that is in transition from an agrarian society to some modern form of production is developing.

The Lorenz curve above shows the income equality in both China and Brazil. We notice that the equality in Brazil is in fact much lower than China even. And China is known to exacerbate their system of inequality, since its rural working classes are not given any of the societal benefits and opportunities that its urban classes are. Rural workers are given fewer legal rights, while the urban class has more rights and fewer restrictions anywhere else in the country. The income inequality in China, overall, is rising. In 1985 the GINI coefficient, the representational number that comes from this model, was 0.31. With "0" being the line of perfect income equality and "1" being the line of perfect income inequality. In 2004, however, that number had moved closer to the line of inequality at 4.6.

In the previous entry, Middle Classistics, I mentioned the state of rising inequality in Brazil. Other things being equal, that is, if we assume no disasters (whether natural, financial, or political), economic growth theory stipulates that economies ought to see rising income equality after an initial period of inequality. It is not clear how long the rising inequality period is supposed to take, however, this stages-model was developed by Simon Kuznets who won the Nobel Prize in economics in 1971 "for his empirically founded interpretation of economic growth which has led to new and deepened insight into the economic and social structure and process of development". It has been argued in recent years, however, that the Kuznets Curve -- the U-Curve -- is wrong in its assumptions since it was based on static data. The data Kuznets used was based on static data from the current situations in developed and developing countries. At the time, developing countries were showing great differences in income equality. Kuznets argued that since developed countries were showing higher income equalities, this meant that developing countries, once they develop, will also show higher income equalities.

Economists, if they are going to reason this way, are now pressured to build time-series data models, which will argue more persuasively that what was experienced in one country will also happen in another. Inductive validity and causality should be more persuasively argued for. But the Kuznets model, it turns out, is largely falsified. The U-Curve might happen in some cases, but it is not a necessary stage in development, and therefore income inequalities cannot be justified on the basis that incomes will simply equal out in the future.

It is my view that states rarely develop in ways that do not significantly limit or violate the rights of their population. For example, all sorts of landgrab reforms in Brazil have taken place over the years. The development strategies are often aimed at enriching a certain class, the upper class, with a trickle-down theory about how that income will reach the rest of society.

We can demonstrate the lack of persuasion the Kuznets model should have with a time-series model of Brazil and China. Despite China's effort to develop in recent years, income inequality has risen at a dramatic pace. As I mentioned earlier, the GINI coefficient in 1985 was 0.31. In 2004 it is 0.46. If we look closer at the rural and urban distinction, we see this transformation had even greater effects on the rural population, who have been systematically denied participation in China's development scheme. In 1985, the rural GINI was 0.27, which reflects inequality among rural workers themselves. In 2001 that number was 0.343. The average coefficient over the years 0.31, the same level of inequality that existed in the entirety of China in 1985. The average coefficient among the urban population has been 0.21, which means urban equality has been higher than rural equality over the years.

The international GINI warning level is 0.4, and this has provoked a discussion about whether we are really considering two distinct countries--the rich and the poor. However, the situation in Brazil, whose GINI in 2004 was 0.59, is much more unequal than China. In Brazil the poorest quintile of the population earn 3% of the income, while the richest quintile earn 61% of the income. In China the inequalities are increasing, yet the lowest quintile earns 4% of the income and the highest quintile earns 52%.

We can see also from the 2004 World Bank data that China would appear to have a much more prosperous middle class than Brazil. China's middle quintile earns 14% of the income, while in Brazil they earn 11% of the income. This is reflected in the Lorenz curve shown above. The entire population in both countries is unimodally skewed toward the richest quintile. But Brazil is far worse.

The GINI time-series model for Brazil, however, seems to fit the overall Kuznets picture of an inverted-U dynamic. In fact, it appears to be a perfect example of the U-curve hypothesis. This, I argue later, is not always the case, although Brazil for now appears to be a good example of it. It is important to say, however, that the U-curve model itself would be insignificant if the inequalities did not give rise to anything else, that is, if they were not justified by anything else. Kuznets' intention was to show that the increase in inequality was justified due to an increase in overall economic activity as measured by GDP. And the real GDP growth estimates show that Brazil has increased from $15b in 1960 to $1068b in 2006, using current US currency value as the base-year value.

But -- and this is a big but -- it's important to mention, just before we start thinking the Kuznets model has circumnavigated Brazil, and we reify this information as socioeconomic laws of nature, it needs to be said that the GINI Coefficients in my graph are misleading. If you look at the Y-axis, you'll see I had to squish the numbers so that the only variation we see is between 0.57 and 0.61. This is a very small margin, but I needed to do that so it would appear to be a noticeable difference. If we look at overall GINI coefficients for the time period, in full scale, the picture we get is much different:

Brazil's GINI coefficients have hardly moved from around the 0.6 area. We can rightly ask whether this is a good example of the inverted-U hypothesis, although many think that it is. To use Brazil as an example of the empirical justification of the model seems absurd. China, on the other hand, has grown faster than Brazil since 1960, and we see that its GINI index over time has evidently not become an inverted-U shape. In 1960, GDP in China was $61b in current US dollars. By 2006 that value had risen to $2,668b, or $2.6 trillion. By measuring gross domestic product, China has grown faster than Brazil by more than 70%. Yet take a look at the GINI values over time:

The GINI coefficients on a time-series scale do not match the Kuznets prediction that they will eventually drop to levels equal to or below the GINI coefficients at the time inequalities began rising. One may say that the isolated urban population would be expected to display lower levels of inequality, since they are the most rapidly developing areas of China. Yet even in the urban areas inequality measurements are increasing at the same pace each year. The rural population suffers the most, due to all sorts of social and legal issues, but also due to the rising inequality amongst themselves. The GINI index of rural populations in China is increasing at an increasing rate, which is not desirable.

In fact, overall, the World Bank measurements are more optimistic than other measurements. The 2004 World Bank GINI puts the number at 0.41, whereas other data have found this number to be closer to 0.46. We might expect this to be the case since the World Bank analysis is tightly connected to the Washington Consensus, which argues that rising inequalities are justified if shock therapeutic developmental policies are in place.

One could say that what I have said about the Kuznets model is not yet proven correct, since China still has the opportunity to decrease inequality rates and increase GDP rates, thus proving the model correct. However, there is no reason to accept this idea if there is a persuasive case to be made that the methodological approach of the model is not cogent.

The argument that inequality must increase before it decreases, the conclusion of Kuznets' work, is based on cross-sectional data. The other way to gather and present data in economics is through time-series analyses. The U-shape in the curve comes not from progression in the development of individual countries, but rather from historical differences between countries. In his data set, many of the middle income countries were Latin American countries. The individual countries Kuznets used as the basis for argument were developed countries, such as the United States, where income inequalities had historically been lower. In Latin America, with its history of colonialism and presence of neo-colonial and white minority who own the majority of the means of production, inequalities were historically very high. When we factor in this time-series variable, the shape of the U-curve tends to disappear. And in some instances, such as the time-series GINI index of Canada 1970-1999, we see what would appear to be an inverted U-curve. That is, a situation in which rising equality eventually gave way to inequality conditions that existed before the increase in equality.

The status of the Kuznets curve was once reified as a socioeconomic law. Economists and social scientists have recently demonstrated how Kuznets’s arguments, originally advanced under more limited conditions, became transformed into overarching theoretical, empirical, and political constructions. The time-series analyses suggests that even empirically grounded and testable social science models are contingent on the broader social and political contexts in which they are produced and negotiated.

Middle Classistics

While poverty is measurable, the word “middle-class” is subjective. The kind of people who call themselves middle-class in Brazil, for example, tend to be at the top of the scale: prosperous professionals with several servants, children at private schools and holidays in Europe or Miami. From the 1940s to the 1970s, state-led industrialization and the growth of public employment saw the rise in some Latin American countries of a middle class of managers, bureaucrats and a labor aristocracy of skilled workers. But the policies that pushed them up proved unsustainable; they were abandoned after the 1982 debt crisis, which triggered a decade of mediocre growth and high inflation. Since then, partly because protected industries were subjected to privatization and import competition, this group has struggled. The middle class that is emerging now in Brazil is very different. It is more accurately described as a lower-middle class which consumes more like an American middle-class.

Simultaneously, there has been a drop in the income-defined "middle class" category in Brazil, and there have been increases in the sale of new cars, computers, Coca Cola, wine, American clothing, i Pods, and other consumer electronics. This should be counter-intuitive to anyone familiar with rational choice theory. There are other ways of explaining the situation, however. Pictures on Flickr and elsewhere attest that uppity Brazilians see themselves as members of a rising global middle class, even if their incomes don't agree. The picture on the right depicts a young couple in which the man is wearing an Abercrombie and Fitch shirt, and the woman is wearing busty white and red clothing. If we weren't paying attention, we might have assumed these consumers were American. However, they are Brazilians. The deception lies in the fact that the image is an imitation of an American high school jock and his girlfriend. The reality is that the image is a symbol of class oppression, an image which represents the American-style bondage to consumerist fashion sensibilities.

The Microeconomics of Fertility

The carrying capacity of the earth is continually increasing, due to technology enhancements and advances in gene selection, such as the Green Revolution of the 1970s. The earth can carry much more people than was thought by Thomas Malthus, who assumed that populations grow at a rapid rate unless checked by limited supplies of food and other subsistence goods. The notion that subsistence goods increase arithmetically and population increases exponentially needs to say something about the increase in the carrying capacity which in turn increases the human populations which are able to scavenge the earth.

Jan van der Veen's work (drawing on other work) shows that population is now increasing at a decreasing rate since the 1985—1990 period. Moreover, there is a 15% probability that in a hundred years population will be less than that of today.

Population growth has some obvious positive impacts on the economy. First of which is the contingent growth in the labor supply, and the even more contingent growth in gross domestic product. Labor supply growth is merely a means to economic growth, which is merely a means to rising standards of living. At each point there are contingencies involved, and we should be doubtful about any “necessary” connections implied in the pro-natalist argument. There is also the argument that each person added to the population has the potential for genius, and that increases in population increases the number of baby-geniuses in the world.

On the other hand there are profound negative macroeconomic consequences of the microeconomic decisions made in the sphere of the family. The economics of the family can for example give rise to environmental degradation problems, strains on public services such as health and education, decreasing savings rates, and various other externalities on, say, negative externalities on other members of the totem or joint family, negative externalities on members of the community, and wage depression due to an overabundance of labor. And to state the obvious, children necessarily consume resources, drawing on the family’s income and societies’ natural capital. These points make clear that the family’s private cost and benefits do not match up with social and natural costs and benefits.

Diagrammatically, this is captured by the fact that the social cost is graphed steeper than the private costs. It may also be possible that there is no difference in costs, yet social and private benefits diverge greatly. The negative impacts of population growth are much more sufficient for negative outcomes than the positive impacts are sufficient for positive outcomes.

The microeconomic theory of fertility is useful here because it asks the question why a family would decide to rear children in the first place. The economics of the family asks what kinds of incentives are involved. After all, the decisions being made are often not based on society’s natural capital, or local wage levels. Family decisions are often made at the microeconomic rather than the macroecnomic level.

These are salient microeconomic behaviors based on things like private prices, tastes and preferences, incomes, and especially the expected marginal benefit from having children and so on. To frame this discussion, children in regions of high-income (correlated with low fertility) often are considered “consumption goods”, whereas in regions with low-income (correlated with high fertility) they are often considered “investment goods”. The difference will be clear in a moment.

We can also ask lots of other interesting economic questions about fertility. Such as whether children are substitute goods or complimentary goods for any other good or activity. Or, dare we ask the striking question of whether children are normal or inferior goods. That question is actually quite relevant, since if a child were an inferior good, it would imply that the family that there are clear substitutes to having children that are available—such as owning a boat or a helicopter if children are consumption goods, or such as viable savings or insurance markets if children are investment goods.

We can use the micro theory to explain the behavior of families in developing countries, where children are seen as an investment good, in the absence of markets for insurance and institutions like social security schemes. The first calculation is, of course, the direct costs of rearing children, i.e. the private costs in this activity, first of which are the costs of food and other subsistence goods. The other sort of costs is, more obviously, the opportunity costs. The family must reach a verdict on the trade-off between, say, raising children or enrolling in community college.

The opportunity costs, however, pervade the decision-making process at every level, even down to the trade-off between sleep and sleeplessness. We can also identify methods of decision-making in relation to certainties about life expectancy. If children are expected to die in infancy, and 15% of infants die within a year in developing countries, the parents may be expected to target children, choosing to wait until the child lives to have another child. If the uncertainty resides in the overall probability that a child will look after the parents in old age, they may be expected to hoard children as an appropriate insurance policy.

It is often assumed that the reason why families in developing countries have so many children is due to the lack of education. This seems to be a blatant myth, and the microeconomic theory spells this out in terms of the rational decision-making that a family goes through. In non-welfare states, families often prefer to invest in children as a form of old-age security and insurance rather than rely on money savings or social security programs that provide these benefits in other societies.

Families will often engage in mutual insurance networks, such as marrying off their children in distant villages, to minimize the risk of flood or disaster and thus of not having anyone provide for them in their old age. This is the problem of missing markets in developing countries, which need to develop in order for strong negatively external micro fertility issues to be mitigated. These can easily be provided in the market -- and developing countries have clear examples in developed countries and access to capital to achieve these ends.

However, there are some problems with the microeconomic theory of utility that I wish to briefly explain. It is arguably too simplistic, although it dispels the simplicity of earlier scholarship. If women do not have reproductive rights in these societies, then arguably there is no basis for the calculation. If decisions are made unequally in the households, then there is going to be some obvious bias that will tend toward having more children than the micro calculations would deem rational. These can also be explained by gender biases and social norms that are not accounted for in the model.

However, this problem is much more a case for a welfare state approach rather than a problem of the market itself. Markets do in fact provide these programs, yet developing countries often lack the infrastructure involved. For example, a functioning legal system is integral to the development of an insurance scheme, in order to validate claims made by injured parties.