Theil index


The Theil index is a statistic primarily used to measure economic inequality and other economic phenomena, though it has also been used to measure racial segregation.
The Theil index TT is the same as redundancy in information theory which is the maximum possible entropy of the data minus the observed entropy. It is a special case of the generalized entropy index. It can be viewed as a measure of redundancy, lack of diversity, isolation, segregation, inequality, non-randomness, and compressibility. It was proposed by econometrician Henri Theil at the Erasmus University Rotterdam.

Formula

For a population of N "agents" each with characteristic x, the situation may be represented by the list xi where xi is the characteristic of agent i. For example, if the characteristic is income, then xi is the income of agent i.
The Theil T index is defined as
and the Theil L index is defined as
where is the mean income:
Equivalently, if the situation is characterized by a discrete distribution function fk where fk is the fraction of the population with income k and W = is the total income, then and the Theil index is:
where is again the mean income:
Note that in this case income k is an integer and k=1 represents the smallest increment of income possible.
if the situation is characterized by a continuous distribution function f where f dk is the fraction of the population with income k to k + dk, then the Theil index is:
where the mean is:
Theil indices for some common continuous probability distributions are given in the table below:
If everyone has the same income, then TT equals 0. If one person has all the income, then TT gives the result, which is maximum inequality. Dividing TT by can normalize the equation to range from 0 to 1, but then the independence axiom is violated: and does not qualify as a measure of inequality.
The Theil index measures an entropic "distance" the population is away from the egalitarian state of everyone having the same income. The numerical result is in terms of negative entropy so that a higher number indicates more order that is further away from the complete equality. Formulating the index to represent negative entropy instead of entropy allows it to be a measure of inequality rather than equality.

Relation to Atkinson Index

The Theil index can be transformed into an Atkinson index, which has a range between 0 and 1, where 0 indicates perfect equality and 1 indicates maximum inequality.

Derivation from entropy

The Theil index is derived from Shannon's measure of information entropy, where entropy is a measure of randomness in a given set of information. In information theory, physics, and the Theil index, the general form of entropy is
When looking at the distribution of income in a population, is equal to the ratio of a particular individual's income to the total income of the entire population. This gives the observed entropy of a population to be:
The Theil index measures how far the observed entropy is from the highest possible entropy. Therefore, the Theil index is the difference between the theoretical maximum entropy minus the observed entropy:
When is in units of population/species, is a measure of biodiversity and is called the Shannon index. If the Theil index is used with x=population/species, it is a measure of inequality of population among a set of species, or "bio-isolation" as opposed to "wealth isolation".
The Theil index measures what is called redundancy in information theory. It is the left over "information space" that was not utilized to convey information, which reduces the effectiveness of the price signal. The Theil index is a measure of the redundancy of income in some individuals. Redundancy in some individuals implies scarcity in others. A high Theil index indicates the total income is not distributed evenly among individuals in the same way an uncompressed text file does not have a similar number of byte locations assigned to the available unique byte characters.

NotationInformation theoryTheil index TT
number of unique charactersnumber of individuals
a particular charactera particular individual
count of ith characterincome of ith individual
total characters in documenttotal income in population
unused information spaceunused potential in price mechanism
data compressionprogressive tax

Decomposability

According to the World Bank,
"The best-known entropy measures are Theil’s T and Theil’s L, both of which allow one to decompose inequality into the part that is due to inequality within areas and the part that is due to differences between areas. Typically at least three-quarters of inequality in a country is due to within-group inequality, and the remaining quarter to between-group differences."

If the population is divided into subgroups and
then Theil's T index is
For example, inequality within the United States is the average inequality within each state, weighted by state income, plus the inequality between states.
The decomposition of the Theil index which identifies the share attributable to the between-region component becomes a helpful tool for the positive analysis of regional inequality as it suggests the relative importance of spatial dimension of inequality.

Theil's ''T'' versus Theil's ''L''

Both Theil's T and Theil's L are decomposable. The difference between them is based on the part of the outcomes distribution that each is used for. Indexes of inequality in the generalized entropy family are more sensitive to differences in income shares among the poor or among the rich depending on a parameter that defines the GE index. The smaller the parameter value for GE, the more sensitive it is to differences at the bottom of the distribution.
The decomposability is a property of the Theil index which the more popular Gini coefficient does not offer. The Gini coefficient is more intuitive to many people since it is based on the Lorenz curve. However, it is not easily decomposable like the Theil.

Applications

In addition to multitude of economic applications, the Theil index has been applied to assess performance of irrigation systems and distribution of software metrics.