Income inequality measurement is one of the major instruments of macroeconomic policy makers all over the world. It has been used for more than two centuries now for the purpose of economic planning and forecasting. It has been defined as the difference between the income of a rich person and that of an average one. Income inequality can be measured in many ways, depending on the country, the type of analysis being done and the preferences of the different parties involved in the analysis. There are two general methods of income inequality measurement: the microlevel and the macrolevel.

Microlevel measurement of income inequality is done at the level of individuals and families. In this method, there is no special reference to a given group or category, as such. Rather, each individual is treated as a distinct and unique case. There is no room here for macroeconomic indicators of overall economic growth. This sort of measurement is often called the microlevel approach.

The United Nations has been using this microlevel approach since 1990, when it created the Worldometers for the purpose of understanding global poverty and inequality. This system was later refined by Bracken and Wells (1990). Bracken and Wells found that high inequality can significantly reduce the rate of economic growth, due to the fact that there are limited sources of growth for the poor members of a society. High inequality also makes political stability more difficult, because governing bodies do not trust the honesty and integrity of the low-income groups that make up part of the society.

Macrolevel metrics on the other hand are based on a wide variety of economic metrics that can be measured on a wide array of categories and countries. These include Gross Domestic Product (GDP), Purchasing Managers Index (PMI), Purchasing Managers Compensation (PMC), Purchasing Manager Data, Balance of Payments, Interest Income, Debt to GDP, and Interest Rate. These are just a few of the different types of metrics. There are many more, and they tend to vary widely in their level of importance.

One type of economic growth indicator is the Gini index. The Gini index measures the extreme difference between the rich and the poor. In general, as the size of the poor grows, the Gini index tends to decrease, reflecting the fact that the poor can afford to purchase products that are higher in value. For example, if one group’s income is thirty times that of another’s, then the Gini can indicate a high inequality. Economic textbooks and programs use the Gini index as a measure of economic equality.

Another way to calculate inequality is the standard deviation of the mean income of a population. The standard deviation is defined as the deviation of the mean income from the average, or mean income, for a discrete sample. The function that estimates the value of the deviation of the mean is called the logit, or the log-likelihood. One can also use the robust range approach, which is to calculate the mean income of the population as the log-likelihood minus the standard deviation. Using the robust range approach, differences in distributions can be examined, for example, between state or national rates.

One of the most commonly used measurement techniques for economic inequality is the logistic regression, which calculates a normal curve, called the log-linear function. This function describes the probability distribution of the logit, or some other integral value, over some discrete parameters. One can also calculate the theoretical maximum and minimum values of the theoretical maximum income and theoretical minimum income.

One popular methodology for measuring economic inequality is the national income distribution. This approach, based on the United Nations (UN) World Distribution Model, estimates inequality measures for countries within the framework of the UN. This model is able to explain national differences in consumption and income because of macroeconomic factors such as the level of taxation and public infrastructure as well as characteristics of the country’s economy. The underlying assumption of this methodology is that households draw their income from similar sources, and that there is no significant difference between them. Another popular measurement method used within the framework of the UN WFDM is the equal weights theory, which postulates that the unequal distribution of resources among households will lead to severe economic problems.