Income inequality metrics

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Income inequality metrics or income distribution metrics are techniques used by economists to measure the distribution of income and economic inequality among the participants in a particular economy, such as that of a specific country or of the world in general. These techniques are typically categorized as either absolute measures or relative measures. Inequality is determined by the demand for and supply of skill. Education, immigration, and new technologies all play a role.

Income distribution has always been a central concern of economic theory and economic policy. Classical economists such as Adam Smith, Thomas Malthus and David Ricardo were mainly concerned with factor income distribution, that is, the distribution of income between the main factors of production, land, labour and capital.

Modern economists have also addressed this issue, but have been more concerned with the distribution of income across individuals and households. Important theoretical and policy concerns include the relationship between income inequality and economic growth. The article economic inequality discusses the social and policy aspects of income distribution questions.

Contents

[edit] Absolute income criteria

Absolute measures define a minimum standard, then calculate the number (or percent) of individuals below this threshold. These methods are most useful when determining the amount of poverty in a society. Examples include:

  • Poverty line - This is a measure of the level of income necessary to subsist in a society. It varies from place to place and from time to time, depending on the cost of living and people's expectations. It is usually defined by governments and calculated as that level of income at which a household will devote two thirds (to three quarters) of its income to basic necessities such as food, water, shelter, and clothing.
  • Poverty index - This index was developed by Amartya Sen, who won the 1998 Nobel Prize for Economics, "for his contributions to welfare economics." It takes into account both the number of poor and the extent of their poverty. Sen defined the index as:
I = (P/N)(B − A)/A

where:

P = number of people below the poverty line
N = total number of people in society
B = poverty line income
A = average income of those people below the poverty line

[edit] Defining income

All of the above measures use income as the basis for evaluating poverty. However, 'income' is here understood different from a common understanding: It means the total amount of goods and services that a person receives, and thus there is not necessarily money or cash involved. If a poor subsistence farmer in Uganda grows her own grain it will count as income. Services like public health and education are also counted in. Often expenditure or consumption (which is the same in an economic sense) is used to measure income. The World Bank uses the so-called living standard measurement surveys (LSMS) to measure income. These consist of questionnaires with 200+ questions. Surveys have been completed in most developing countries.

[edit] Proper use of income inequality metrics

  1. When using income metrics, it has to be made clear how income should be defined. Should it include capital gains, imputed house rents from home ownership, and gifts? If these income sources or alleged income sources (in the case of "imputed rent") are ignored (as they often are), how might this bias the analysis? How should non-paid work (such as parental childcare or doing ones own cooking instead of hiring a chef for every meal) be handled? Wealth or consumption may be more appropriate measures in some situations. Broader metrics of human well-being might be useful.
  2. The comparison of inequality measures requires, that the segmentation of compared groups (societies etc.) into quintiles should be similar.
  3. Distinguish properly, whether the basic unit of measurement is households or individuals. The Gini value for households is always lower than for individuals because of income pooling and intra-family transfers. And housholds have a varying amount of members. The metrics will be influenced either upward or downward depending on which unit of measurement is used.
  4. Consider life cycle effects. In most Western societies, an individual tends to start life with little or no income, gradually increase income till about age 50, after which incomes will decline, eventually becoming negative. This affects the conclusions which can be drawn from a measured inequality. It has been estimated (by A.S. Blinder in The Decomposition of Inequality, MIT press) that 30% of measured income inequality is due to the inequality an individual experiences as they go through the various stages of life.
  5. Clarify, whether real or nominal income distributions should be used. What effect will inflation have on absolute measures? Do some groups (eg., pensioners) feel the effect of inflation more than others?
  6. When drawing conclusion from inequality measurements, consider how we should allocate the benefits of government spending? How does the existence of a social security safety net influence the definition of absolute measures of poverty? Do government programs support some income groups more than others?
  7. Inequality metrics measure inequality. They do not measure possible causes of income inequality. Some alleged causes include: life cycle effects (age), inherited characteristics (IQ, talent), willingness to take chances (risk aversion), the leisure/industriousness choice, inherited wealth, economic circumstances, education and training, discrimination, and market imperfections.

Keeping these points in mind helps to understand the problems caused by the improper use of inequality measures. However, they do not render inequality coefficients invalid. If inequality measures are computed in a well explained and consistent way, they can provide a good tool for quantitative comparisons of inequalities at least within a research project.

[edit] Inequality, growth, and progress

The question whether equality is beneficial for economic growth and progress has occupied the minds of the greatest scientific thinkers as well as policy makers. Evidence from a broad panel of recent academic studies shows the relation between income inequality and the rate of growth and investment is indeed robust however not linear.

Robert J. Barro, Harvard University found in his study "Inequality and Growth in a Panel of Countries" that higher inequality tends to retard growth in poor countries and encourage growth in well developed regions.[1] In their study for the World Institute for Development Economics Research, Giovanni Andrea Cornia and Julius Court (2001) reach analogous conclusions.[2] The authors therefore recommend to pursue moderation also as to the distribution of wealth and particularly to avoid the extremes. Both very high egalitarianism and very high inequality cause slow growth.

Income inequality diminishes growth potential through the erosion of social cohesion, increasing social unrest and social conflict causing uncertainty of property rights. Extreme inequality can effectively reduce access to productivity enhancement measures, or cause such measures to be allocated inefficiently toward those who already have, or can no longer absorb such measures.

On the other hand, The World Bank World Development Report 2000/2001[3] shows, that inequality and growth are not related. Inequality neither drives growth nor does it impair growth. Other Research (W.Kitterer[4]) also shows, that in perfect markets inequality does not influence growth. In real markets redistribution contributes to growth.

Considering the inequalities in economically well developed countries, public policy should target an ‘efficient inequality range’. The authors claim that such efficiency range roughly lies between the values of the Gini coefficients of 25 (the inequality value of a typical Northern European country) and 40 (that of countries such as China[5] and the USA[6]).

The precise shape of the inequality-growth relationship depicted in the Chart obviously varies across countries depending upon their resource endowment, history, remaining levels of absolute poverty and available stock of social programs, as well as on the distribution of physical and human capital.

[edit] See also

[edit] Notes

  1. ^ economics.harvard.edu - Inequality and Growth in a Panel of Countries
  2. ^ wider.unu.edu - Inequality, Growth and Poverty in the Era of Liberalization and Globalization
  3. ^ World Bank World Development Report 2000/2001, chapter 3, box 3.5
  4. ^ Wolfgang Kitterer: Mehr Wachstum durch Umverteilung? (More Growth through Redistribution?), 2006
  5. ^ Due to the economic dynamics and the increasing income gap between the Chinese east cost and the rest of the country, the Gini index for China may have reached 50. Sources from China report 47 for the year 2005. With regard to the huge population in China and the challenges to data collection, a good understanding of the data is required, based on which the Gini indices are computed.
  6. ^ USA: Also countries like France, Germany and UK have a Gini index slightly above 40.

[edit] Literature

  • Yoram Amiel (Author), Frank A. Cowell: Thinking about Inequality: Personal Judgment and Income Distributions, 2000
  • Philip B. Coulter: Measuring Inequality, 1989

[edit] External links

Retrieved from "http://en.wikipedia.org/wiki/Income_inequality_metrics"
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