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Gini coefficient

In economics, the Gini coefficient, also known as the Gini index or Gini ratio, is a measure of statistical dispersion intended to represent the income inequality, the wealth inequality, or the consumption inequality within a nation or a social group. It was developed by Italian statistician and sociologist Corrado Gini.

The Gini coefficient measures the inequality among the values of a frequency distribution, such as levels of income. A Gini coefficient of 0 reflects perfect equality, where all income or wealth values are the same, while a Gini coefficient of 1 (or 100%) reflects maximal inequality among values, a situation where a single individual has all the income while all others have none.

The Gini coefficient was proposed by Corrado Gini as a measure of inequality of income or wealth. For OECD countries in the late 20th century, considering the effect of taxes and transfer payments, the income Gini coefficient ranged between 0.24 and 0.49, with Slovakia being the lowest and Mexico the highest. African countries had the highest pre-tax Gini coefficients in 2008–2009, with South Africa having the world's highest, estimated to be 0.63 to 0.7. However, this figure drops to 0.52 after social assistance is taken into account, and drops again to 0.47 after taxation. The country with the lowest Gini coefficient is Slovakia, with a Gini coefficient of 0.232. The Gini coefficient of the global income in 2005 has been estimated to be between 0.61 and 0.68 by various sources.

There are some issues in interpreting a Gini coefficient, as the same value may result from many different distribution curves. To mitigate this, the demographic structure should be taken into account. Countries with an aging population, or those with an increased birth rate, experience an increasing pre-tax Gini coefficient even if real income distribution for working adults remains constant. Many scholars have devised over a dozen variants of the Gini coefficient.

History
The Gini coefficient was developed by the Italian statistician Corrado Gini and published in his 1912 paper Variabilità e mutabilità (variability and mutability). Building on the work of American economist Max Lorenz, Gini proposed that the difference between the hypothetical straight line depicting perfect equality, and the actual line depicting people's incomes, be used as a measure of inequality. In this paper, he introduced the concept of simple mean difference as a measure of variability.

He then applied the simple mean difference of observed variables to income and wealth inequality in his work On the measurement of concentration and variability of characters in 1914. Here, he presented the concentration ratio, which further developed in the Gini coefficient used today. Secondly, Gini observed that his proposed ratio can be also achieved by improving methods already introduced by Lorenz, Chatelain, or Séailles.

In 1915, Gaetano Pietra introduced a geometrical interpretation between Gini’s proposed ratio and the ratio between the area of observed concentration and maximum concentration. This altered version of Gini coefficient became the most commonly used inequality index in upcoming years.

According to data from OECD, Gini coefficient was first officially used country-wide in Canada in the 1970s. Canadian index of income inequality ranged from 0.303 to 0.284 from 1976 to the end of 1980s. OECD started to publish more countries’ data since the start of the 21st century. Central European countries Slovenia, Czechia, and Slovakia have had the lowest inequality index out of all OECD countries ever since the 2000s. Scandinavian countries also frequently appeared at the top of the list of equality in the last decades.

Definition

The Gini coefficient is an index for the degree of inequality in the distribution of income/wealth, used to estimate how far a country's wealth or income distribution deviates from an equal distribution.

The Gini coefficient is usually defined mathematically based on the Lorenz curve, which plots the proportion of the total income of the population (y-axis) that is cumulatively earned by the bottom x of the population (see diagram). The line at 45 degrees thus represents perfect equality of incomes. The Gini coefficient can then be thought of as the ratio of the area that lies between the line of equality and the Lorenz curve (marked A in the diagram) over the total area under the line of equality (marked A and B in the diagram); i.e.,. If there are no negative incomes, it is also equal to 2A and due to the fact that.

Assuming non-negative income or wealth for all, the Gini coefficient's theoretical range is from 0 (total equality) to 1 (absolute inequality). This measure is often rendered as a percentage, spanning 0 to 100. However, if negative values are factored in, as in cases of debt, the Gini index could exceed 1. Typically, we presuppose a positive mean or total, precluding a Gini coefficient below zero.

An alternative approach is to define the Gini coefficient as half of the relative mean absolute difference, which is equivalent to the definition based on the Lorenz curve. The mean absolute difference is the average absolute difference of all pairs of items of the population, and the relative mean absolute difference is the mean absolute difference divided by the average, $$\bar{x}$$, to normalize for scale. If xi is the wealth or income of person i, and there are n persons, then the Gini coefficient G is given by:

 * $$G = \frac{\displaystyle{\sum_{i=1}^n \sum_{j=1}^n \left| x_i - x_j \right|}}{\displaystyle{2 n^2 \bar{x}}} = \frac{\displaystyle{\sum_{i=1}^n \sum_{j=1}^n \left| x_i - x_j \right|}}{\displaystyle{2 n \sum_{i=1}^n x_i}} $$

When the income (or wealth) distribution is given as a continuous probability density function p(x), the Gini coefficient is again half of the relative mean absolute difference:

 * $$G = \frac{1}{2\mu}\int_{-\infty}^\infty\int_{-\infty}^\infty p(x)p(y)\,|x-y|\,dx\,dy$$

where $$\textstyle\mu=\int_{-\infty}^\infty x p(x) \,dx$$ is the mean of the distribution, and the lower limits of integration may be replaced by zero when all incomes are positive.

Calculation

While the income distribution of any particular country will not correspond perfectly to the theoretical models, these models can provide a qualitative explanation of the income distribution in a nation given the Gini coefficient.

Example: Two levels of income
The extreme cases are represented by the most equal possible society in which every person receives the same income, and the most unequal society (with N individuals) where a single person receives 100% of the total income and the remaining people receive none.

A simple case assumes just two levels of income, low and high. If the high income group is a proportion u of the population and earns a proportion f of all income, then the Gini coefficient is f − u. A more graded distribution with these same values u and f will always have a higher Gini coefficient than f − u.

For example, if the wealthiest u = 20% of the population has f = 80% of all income (see Pareto principle), the income Gini coefficient is at least 60%. In another example, if u = 1% of the world's population owns f = 50% of all wealth, the wealth Gini coefficient is at least 49%.

Alternative expressions
In some cases, this equation can be applied to calculate the Gini coefficient without direct reference to the Lorenz curve. For example, (taking y to indicate the income or wealth of a person or household):
 * For a population of n individuals with values $$y_1 \leq y_2\leq \cdots \leq y_n $$,
 * $$G = \frac{1}{n}\left ( n+1 - 2 \left ( \frac{\sum_{i=1}^n (n+1-i)y_i}{\sum_{i=1}^n y_i} \right ) \right ). $$
 * This may be simplified to:
 * $$G = \frac{2 \sum_{i=1}^n i y_i}{n \sum_{i=1}^n y_i} -\frac{n+1}{n}.$$

The Gini coefficient can also be considered as half the relative mean absolute difference. For a random sample S with values $$y_1 \leq y_2\leq \cdots \leq y_n $$, the sample Gini coefficient
 * $$G(S) = \frac{1}{n-1}\left (n+1 - 2 \left ( \frac{\sum_{i=1}^n (n+1-i)y_i}{\sum_{i=1}^n y_i}\right ) \right )$$

is a consistent estimator of the population Gini coefficient, but is not in general unbiased. In simplified form:

 * $$G(S) = 1 - \frac{2}{n-1}\left ( n - \frac{\sum_{i=1}^n iy_i}{\sum_{i=1}^n y_i}\right ). $$

There does not exist a sample statistic that is always an unbiased estimator of the population Gini coefficient.

Discrete probability distribution
For a discrete probability distribution with probability mass function $$f ( y_i ),$$, where $$f ( y_i )$$ is the fraction of the population with income or wealth $$y_i >0 $$, the Gini coefficient is:
 * $$G = \frac{1}{2\mu} \sum\limits_{i=1}^n  \sum\limits_{j=1}^n \, f(y_i) f(y_j)|y_i-y_j|$$

where
 * $$\mu=\sum\limits_{i=1}^n y_i f(y_i).$$

If the points with non-zero probabilities are indexed in increasing order $$(y_i < y_{i+1})$$, then:
 * $$G = 1 - \frac{\sum_{i=1}^n f(y_i)(S_{i-1}+S_i)}{S_n}$$

where
 * $$S_i = \sum_{j=1}^i f(y_j)\,y_j\,$$ and $$S_0 = 0.$$ These formulas are also applicable in the limit, as $$n\rightarrow\infty.$$

Continuous probability distribution
When the population is large, the income distribution may be represented by a continuous probability density function f(x) where f(x) dx is the fraction of the population with wealth or income in the interval dx about x. If F(x) is the cumulative distribution function for f(x):

 * $$F(x)=\int_0^x f(x)\,dx$$

and L(x) is the Lorenz function:

 * $$L(x)=\frac{\int_0^x x\,f(x)\,dx}{\int_0^\infty x\,f(x)\,dx}$$

then the Lorenz curve L(F) may then be represented as a function parametric in L(x) and F(x) and the value of B can be found by integration:

 * $$B = \int_0^1 L(F) \,dF. $$

The Gini coefficient can also be calculated directly from the cumulative distribution function of the distribution F(y). Defining μ as the mean of the distribution, and specifying that F(y) is zero for all negative values, the Gini coefficient is given by:
 * $$G = 1 - \frac{1}{\mu}\int_0^\infty (1-F(y))^2 \,dy = \frac{1}{\mu}\int_0^\infty F(y)(1-F(y)) \,dy$$

The latter result comes from integration by parts. (Note that this formula can be applied when there are negative values if the integration is taken from minus infinity to plus infinity.)

The Gini coefficient may be expressed in terms of the quantile function Q(F) (inverse of the cumulative distribution function: Q(F(x)) = x)
 * $$G=\frac{1}{2 \mu}\int_0^1 \int_0^1 |Q(F_1)-Q(F_2)|\,dF_1\,dF_2 .$$

Since the Gini coefficient is independent of scale, if the distribution function can be expressed in the form f(x,φ,a,b,c...) where φ is a scale factor and a, b, c... are dimensionless parameters, then the Gini coefficient will be a function only of a, b, c.... For example, for the exponential distribution, which is a function of only x and a scale parameter, the Gini coefficient is a constant, equal to 1/2.

For some functional forms, the Gini index can be calculated explicitly. For example, if y follows a log-normal distribution with the standard deviation of logs equal to $$\sigma$$, then $$G = \operatorname{erf}\left(\frac{\sigma }{2 }\right)$$ where $$\operatorname{erf}$$ is the error function ( since $$ G=2 \Phi \left(\frac{\sigma }{\sqrt{2}}\right)-1$$, where $$\Phi$$ is the cumulative distribution function of a standard normal distribution). In the table below, some examples for probability density functions with support on $$[0,\infty)$$ are shown. The Dirac delta distribution represents the case where everyone has the same wealth (or income); it implies no variations between incomes.

 * {| class="wikitable" style="float: left; margin-left: 1em;"

! Income Distribution function !! PDF(x) !! Gini Coefficient \frac{1}{b-a} & a\le x\le b \\ 0 & \mathrm{otherwise} \end{cases}$$ \frac{\alpha k^\alpha}{x^{\alpha+1}} & x\ge k\\0 & x < k \end{cases}$$ 1 & 0<\alpha < 1\\ \frac{1}{2\alpha -1} & \alpha \ge 1 \end{cases}$$ \dfrac{x^{k-1}e^{-x^2/2}}{2^{k/2-1}\Gamma\left(\frac{k}{2}\right)}, & x\geq 0 \\ 0, & x<0 \end{cases} $$                      { \left (1+(x/\alpha)^{\beta} \right)^2  }$$
 * Dirac delta function || $$\delta(x-x_0),\, x_0>0$$ || 0
 * Uniform distribution
 * $$\begin{cases}
 * Uniform distribution
 * $$\begin{cases}
 * $$\frac{(b-a)}{3(b+a)}$$
 * Exponential distribution
 * $$\lambda e^{-x\lambda},\,\,x>0$$
 * $$1/2$$
 * Log-normal distribution
 * $$\frac{1}{x\sigma\sqrt{2\pi}} e^{-\frac 12 \left(\frac{\ln\,(x)-\mu}{\sigma}\right)^2}$$
 * $$\textrm{erf}(\sigma/2)=2 \Phi \left(\frac{\sigma }{\sqrt{2}}\right)-1$$
 * Pareto distribution
 * $$\begin{cases}
 * Pareto distribution
 * $$\begin{cases}
 * $$\begin{cases}
 * $$\begin{cases}
 * Chi distribution
 * $$f(x;k) = \begin{cases}
 * $$f(x;k) = \begin{cases}
 * $$(-1)^k \left| I_{-1}(k,\tfrac{1}{2})\right|$$
 * Chi-squared distribution
 * $$\frac{2^{-k/2} e^{-x/2} x^{k/2 - 1}}{\Gamma(k/2)}$$
 * $$\frac{2\,\Gamma\left(\frac{1+k}{2}\right)}{k\,\Gamma(k/2)\sqrt{\pi}}$$
 * Gamma distribution
 * $$\frac{e^{-x/\theta}x^{k-1}\theta^{-k}}{\Gamma(k)}$$
 * $$\frac{\Gamma\left(\frac{2k+1}{2}\right)}{k\,\Gamma(k)\sqrt{\pi}}$$
 * Weibull distribution
 * $$\frac {k} {\lambda}\, \left(\frac {x}{\lambda} \right)^{k-1} e^{-(x/\lambda)^k}$$
 * $$1-2^{-1/k}$$
 * Beta distribution
 * $$\frac {x^{\alpha-1}(1-x)^{\beta-1}} {B(\alpha,\beta)}$$
 * $$\left(\frac{2}{\alpha}\right)\frac{B(\alpha+\beta,\alpha+\beta)}{B(\alpha,\alpha)B(\beta,\beta)}$$
 * Log-logistic distribution
 * $$\frac{ (\beta/\alpha)(x/\alpha)^{\beta-1} }
 * $$\frac {x^{\alpha-1}(1-x)^{\beta-1}} {B(\alpha,\beta)}$$
 * $$\left(\frac{2}{\alpha}\right)\frac{B(\alpha+\beta,\alpha+\beta)}{B(\alpha,\alpha)B(\beta,\beta)}$$
 * Log-logistic distribution
 * $$\frac{ (\beta/\alpha)(x/\alpha)^{\beta-1} }
 * $$\frac{ (\beta/\alpha)(x/\alpha)^{\beta-1} }
 * $$1/\beta$$
 * }

 * $$\Gamma(\,)$$ is the Gamma function
 * $$B(\,)$$ is the Beta function
 * $$I_k(\,)$$ is the Regularized incomplete beta function

Other approaches
Sometimes the entire Lorenz curve is not known, and only values at certain intervals are given. In that case, the Gini coefficient can be approximated using various techniques for interpolating the missing values of the Lorenz curve. If (Xk, Yk) are the known points on the Lorenz curve, with the Xk indexed in increasing order (Xk – 1 < Xk), so that: If the Lorenz curve is approximated on each interval as a line between consecutive points, then the area B can be approximated with trapezoids and:
 * Xk is the cumulated proportion of the population variable, for k = 0,...,n, with X0 = 0, Xn = 1.
 * Yk is the cumulated proportion of the income variable, for k = 0,...,n, with Y0 = 0, Yn = 1.
 * Yk should be indexed in non-decreasing order (Yk > Yk – 1)
 * $$G_1 = 1 - \sum_{k=1}^{n} (X_{k} - X_{k-1}) (Y_{k} + Y_{k-1})$$

is the resulting approximation for G. More accurate results can be obtained using other methods to approximate the area B, such as approximating the Lorenz curve with a quadratic function across pairs of intervals or building an appropriately smooth approximation to the underlying distribution function that matches the known data. If the population mean and boundary values for each interval are also known, these can also often be used to improve the accuracy of the approximation.

The Gini coefficient calculated from a sample is a statistic, and its standard error, or confidence intervals for the population Gini coefficient, should be reported. These can be calculated using bootstrap techniques, mathematically complicated and computationally demanding even in an era of fast computers. Economist Tomson Ogwang made the process more efficient by setting up a "trick regression model" in which respective income variables in the sample are ranked, with the lowest income being allocated rank 1. The model then expresses the rank (dependent variable) as the sum of a constant A and a normal error term whose variance is inversely proportional to yk:

 * $$k = A + \ N(0, s^{2}/y_k) $$

Thus, G can be expressed as a function of the weighted least squares estimate of the constant A and that this can be used to speed up the calculation of the jackknife estimate for the standard error. Economist David Giles argued that the standard error of the estimate of A can be used to derive the estimate of G directly without using a jackknife. This method only requires using ordinary least squares regression after ordering the sample data. The results compare favorably with the estimates from the jackknife with agreement improving with increasing sample size.

However, it has been argued that this depends on the model's assumptions about the error distributions and the independence of error terms. These assumptions are often not valid for real data sets. There is still ongoing debate surrounding this topic.

Guillermina Jasso and Angus Deaton independently proposed the following formula for the Gini coefficient:

 * $$G = \frac{N+1}{N-1}-\frac{2}{N(N-1)\mu}(\sum_{i=1}^n P_iX_i)$$

where $$\mu$$ is mean income of the population, Pi is the income rank P of person i, with income X, such that the richest person receives a rank of 1 and the poorest a rank of N. This effectively gives higher weight to poorer people in the income distribution, which allows the Gini to meet the Transfer Principle. Note that the Jasso-Deaton formula rescales the coefficient so that its value is one if all the $$X_i$$ are zero except one. Note however Allison's reply on the need to divide by N² instead.

FAO explains another version of the formula.

Generalized inequality indices
The Gini coefficient and other standard inequality indices reduce to a common form. Perfect equality—the absence of inequality—exists when and only when the inequality ratio, $$r_j = x_j / \overline{x}$$, equals 1 for all j units in some population (for example, there is perfect income equality when everyone's income $$x_j$$ equals the mean income $$\overline{x}$$, so that $$r_j=1$$ for everyone). Measures of inequality, then, are measures of the average deviations of the $$r_j=1$$ from 1; the greater the average deviation, the greater the inequality. Based on these observations the inequality indices have this common form:

 * $$\text{Inequality} = \sum_j p_j \, f(r_j), $$

where pj weights the units by their population share, and f(rj) is a function of the deviation of each unit's rj from 1, the point of equality. The insight of this generalized inequality index is that inequality indices differ because they employ different functions of the distance of the inequality ratios (the rj) from 1.

Of income distributions
Gini coefficients of income are calculated on a market income and a disposable income basis. The Gini coefficient on market income—sometimes referred to as a pre-tax Gini coefficient—is calculated on income before taxes and transfers. It measures inequality in income without considering the effect of taxes and social spending already in place in a country. The Gini coefficient on disposable income—sometimes referred to as the after-tax Gini coefficient—is calculated on income after taxes and transfers. It measures inequality in income after considering the effect of taxes and social spending already in place in a country.

For OECD countries over the 2008–2009 period, the Gini coefficient (pre-taxes and transfers) for a total population ranged between 0.34 and 0.53, with South Korea the lowest and Italy the highest. The Gini coefficient (after-taxes and transfers) for a total population ranged between 0.25 and 0.48, with Denmark the lowest and Mexico the highest. For the United States, the country with the largest population among OECD countries, the pre-tax Gini index was 0.49, and the after-tax Gini index was 0.38 in 2008–2009. The OECD average for total populations in OECD countries was 0.46 for the pre-tax income Gini index and 0.31 for the after-tax income Gini index. Taxes and social spending that were in place in 2008–2009 period in OECD countries significantly lowered effective income inequality, and in general, "European countries—especially Nordic and Continental welfare states—achieve lower levels of income inequality than other countries."

Using the Gini can help quantify differences in welfare and compensation policies and philosophies. However, it should be borne in mind that the Gini coefficient can be misleading when used to make political comparisons between large and small countries or those with different immigration policies (see limitations section).

The Gini coefficient for the entire world has been estimated by various parties to be between 0.61 and 0.68. The graph shows the values expressed as a percentage in their historical development for a number of countries.

Regional income Gini indices
According to UNICEF, Latin America and the Caribbean region had the highest net income Gini index in the world at 48.3, on an unweighted average basis in 2008. The remaining regional averages were: sub-Saharan Africa (44.2), Asia (40.4), Middle East and North Africa (39.2), Eastern Europe and Central Asia (35.4), and High-income Countries (30.9). Using the same method, the United States is claimed to have a Gini index of 36, while South Africa had the highest income Gini index score of 67.8.

World income Gini index since 1800s
Taking income distribution of all human beings, worldwide income inequality has been constantly increasing since the early 19th century (and will keep on increasing over the years). There was a steady increase in the global income inequality Gini score from 1820 to 2002, with a significant increase between 1980 and 2002. This trend appears to have peaked and begun a reversal with rapid economic growth in emerging economies, particularly in the large populations of BRIC countries.

The table below presents the estimated world income Gini coefficients over the last 200 years, as calculated by Milanovic.

More detailed data from similar sources plots a continuous decline since 1988. This is attributed to globalization increasing incomes for billions of poor people, mostly in countries like China and India. Developing countries like Brazil have also improved basic services like health care, education, and sanitation; others like Chile and Mexico have enacted more progressive tax policies.

Of social development
The Gini coefficient is widely used in fields as diverse as sociology, economics, health science, ecology, engineering, and agriculture. For example, in social sciences and economics, in addition to income Gini coefficients, scholars have published education Gini coefficients and opportunity Gini coefficients.

Education
Education Gini index estimates the inequality in education for a given population. It is used to discern trends in social development through educational attainment over time. A study across 85 countries by three World Bank economists, Vinod Thomas, Yan Wang, and Xibo Fan, estimated Mali had the highest education Gini index of 0.92 in 1990 (implying very high inequality in educational attainment across the population), while the United States had the lowest education inequality Gini index of 0.14. Between 1960 and 1990, China, India and South Korea had the fastest drop in education inequality Gini Index. They also claim education Gini index for the United States slightly increased over the 1980–1990 period.

Though India's education Gini Index has been falling from 1960 through 1990, most of the population still has not received any education, while 10 percent of the population received more than 40% of the total educational hours in the nation. This means that a large portion of capable children in the country are not receiving the support necessary to allow them to become positive contributors to society. This will lead to a deadweight loss to the national society because there are many people who are underdeveloped and underutilized.

Opportunity
Similar in concept to the Gini income coefficient, the Gini opportunity coefficient measures inequality in opportunities. The concept builds on Amartya Sen's suggestion that inequality coefficients of social development should be premised on the process of enlarging people's choices and enhancing their capabilities, rather than on the process of reducing income inequality. Kovacevic, in a review of the Gini opportunity coefficient, explained that the coefficient estimates how well a society enables its citizens to achieve success in life where the success is based on a person's choices, efforts and talents, not their background defined by a set of predetermined circumstances at birth, such as gender, race, place of birth, parent's income and circumstances beyond the control of that individual.

In 2003, Roemer reported Italy and Spain exhibited the largest opportunity inequality Gini index amongst advanced economies.

Income mobility
In 1978, Anthony Shorrocks introduced a measure based on income Gini coefficients to estimate income mobility. This measure, generalized by Maasoumi and Zandvakili, is now generally referred to as Shorrocks index, sometimes as Shorrocks mobility index or Shorrocks rigidity index. It attempts to estimate whether the income inequality Gini coefficient is permanent or temporary and to what extent a country or region enables economic mobility to its people so that they can move from one (e.g., bottom 20%) income quantile to another (e.g., middle 20%) over time. In other words, the Shorrocks index compares inequality of short-term earnings, such as the annual income of households, to inequality of long-term earnings, such as 5-year or 10-year total income for the same households.

Shorrocks index is calculated in several different ways, a common approach being from the ratio of income Gini coefficients between short-term and long-term for the same region or country.

A 2010 study using social security income data for the United States since 1937 and Gini-based Shorrock's indices concludes that income mobility in the United States has had a complicated history, primarily due to the mass influx of women into the American labor force after World War II. Income inequality and income mobility trends have been different for men and women workers between 1937 and the 2000s. When men and women are considered together, the Gini coefficient-based Shorrocks index trends imply long-term income inequality has been substantially reduced among all workers, in recent decades for the United States. Other scholars, using just 1990s data or other short periods have come to different conclusions. For example, Sastre and Ayala conclude from their study of income Gini coefficient data between 1993 and 1998 for six developed economies that France had the least income mobility, Italy the highest, and the United States and Germany intermediate levels of income mobility over those five years.

Features
The Gini coefficient has features that make it useful as a measure of dispersion in a population, and inequalities in particular. The coefficient ranges from 0, for perfect equality, to 1, indicating perfect inequality. The Gini is based on the comparison of cumulative proportions of the population against cumulative proportions of income they receive.

Relative, not absolute
The Gini coefficient is a relative measure. The Gini coefficient of a developing country can rise (due to increasing inequality of income) even when the number of people in absolute poverty decreases. This is because the Gini coefficient measures relative, not absolute, wealth.

Gini coefficients are simple, and this simplicity can lead to oversights and can confuse the comparison of different populations; for example, while both Bangladesh (per capita income of $1,693) and the Netherlands (per capita income of $42,183) had an income Gini coefficient of 0.31 in 2010, the quality of life, economic opportunity and absolute income in these countries are very different, i.e. countries may have identical Gini coefficients, but differ greatly in wealth. Basic necessities may be available to all in a developed economy, while in an undeveloped economy with the same Gini coefficient, basic necessities may be unavailable to most or unequally available due to lower absolute wealth.

Mathematical limitations
Gini has some mathematical limitations as well. It is not additive and different sets of people cannot be averaged to obtain the Gini coefficient of all the people in the sets.

Even when the total income of a population is the same, in certain situations two countries with different income distributions can have the same Gini index (e.g. cases when income Lorenz Curves cross). Table A illustrates one such situation. Both countries have a Gini coefficient of 0.2, but the average income distributions for household groups are different. As another example, in a population where the lowest 50% of individuals have no income, and the other 50% have equal income, the Gini coefficient is 0.5; whereas for another population where the lowest 75% of people have 25% of income and the top 25% have 75% of the income, the Gini index is also 0.5. Economies with similar incomes and Gini coefficients can have very different income distributions. Bellù and Liberati claim that ranking income inequality between two populations is not always possible based on their Gini indices. Similarly, computational social scientist Fabian Stephany illustrates that income inequality within the population, e.g., in specific socioeconomic groups of same age and education, also remains undetected by conventional Gini indices.

Income Gini can conceal wealth inequality
A Gini index does not contain information about absolute national or personal incomes. Populations can simultaneously have very low income Gini indices and very high wealth Gini indexes. By measuring inequality in income, the Gini ignores the differential efficiency of the use of household income. By ignoring wealth (except as it contributes to income), the Gini can create the appearance of inequality when the people compared are at different stages in their life. Wealthy countries such as Sweden can show a low Gini coefficient for the disposable income of 0.31, thereby appearing equal, yet have a very high Gini coefficient for wealth of 0.79 to 0.86, suggesting an extremely unequal wealth distribution in its society. These factors are not assessed in income-based Gini.

Country size and granularity bias
Gini index has a downward-bias for small populations. Counties or states or countries with small populations and less diverse economies will tend to report small Gini coefficients. For economically diverse large population groups, a much higher coefficient is expected than for each of its regions. For example, taking the world economy as a whole and income distribution for all human beings, different scholars estimate the global Gini index to range between 0.61 and 0.68. As with other inequality coefficients, the Gini coefficient is influenced by the granularity of the measurements. For example, five 20% quantiles (low granularity) will usually yield a lower Gini coefficient than twenty 5% quantiles (high granularity) for the same distribution. Philippe Monfort has shown that using inconsistent or unspecified granularity limits the usefulness of Gini coefficient measurements.

Changes in population
Changing income inequality, measured by Gini coefficients, can be due to structural changes in a society such as growing population (increased birth rates, aging populations, emigration, immigration) and income mobility.

Another limitation of the Gini coefficient is that it is not a proper measure of egalitarianism, as it only measures income dispersion. For example, suppose two equally egalitarian countries pursue different immigration policies. In that case, the country accepting a higher proportion of low-income or impoverished migrants will report a higher Gini coefficient and, therefore, may exhibit more income inequality.

Household vs individual
The Gini coefficient measure gives different results when applied to individuals instead of households, for the same economy and same income distributions. If household data is used, the measured value of income Gini depends on how the household is defined. The comparison is not meaningful when different populations are not measured with consistent definitions. Furthermore, changes to the household income Gini can be driven by changes in household formation, such as increased divorce rates or extended family households splitting into nuclear families.

Deininger and Squire (1996) show that the income Gini coefficient based on individual income rather than household income is different. For example, for the United States, they found that the individual income-based Gini index was 0.35, while for France, 0.43. According to their individual-focused method, in the 108 countries they studied, South Africa had the world's highest Gini coefficient at 0.62, Malaysia had Asia's highest Gini coefficient at 0.5, Brazil the highest at 0.57 in Latin America and the Caribbean region, and Turkey the highest at 0.5 in OECD countries.

Billionaire Thomas Kwok claimed the income Gini coefficient for Hong Kong has been high (0.434 in 2010 ), in part because of structural changes in its population. Over recent decades, Hong Kong has witnessed increasing numbers of small households, elderly households, and elderly living alone. The combined income is now split into more households. Many older people live separately from their children in Hong Kong. These social changes have caused substantial changes in household income distribution. The income Gini coefficient, claims Kwok, does not discern these structural changes in its society. Household money income distribution for the United States, summarized in Table C of this section, confirms that this issue is not limited to just Hong Kong. According to the US Census Bureau, between 1979 and 2010, the population of the United States experienced structural changes in overall households; the income for all income brackets increased in inflation-adjusted terms, household income distributions shifted into higher income brackets over time, while the income Gini coefficient increased.

Instantaneous inequality vs lifetime inequality
The Gini coefficient is unable to discern the effects of structural changes in populations. Expanding on the importance of life-span measures, the Gini coefficient as a point-estimate of equality at a certain time ignores life-span changes in income. Typically, increases in the proportion of young or old members of a society will drive apparent changes in equality simply because people generally have lower incomes and wealth when they are young than when they are old. Because of this, factors such as age distribution within a population and mobility within income classes can create the appearance of inequality when none exist, taking into account demographic effects. Thus a given economy may have a higher Gini coefficient at any timepoint compared to another, while the Gini coefficient calculated over individuals' lifetime income is lower than the apparently more equal (at a given point in time) economy's. Essentially, what matters is not just inequality in any particular year but the distribution composition over time.

Benefits and income in kind
Inaccuracies in assign monetary value to income in kind reduce the accuracy of Gini as a measurement of true inequality.

While taxes and cash transfers are relatively straightforward to account for, other government benefits can be difficult to value. Benefits such as subsidized housing, medical care, and education are difficult to value objectively, as it depends on the quality and extent of the benefit. In absence of a free market, valuing these income transfers as household income is subjective. The theoretical model of the Gini coefficient is limited to accepting correct or incorrect subjective assumptions.

In subsistence-driven and informal economies, people may have significant income in other forms than money, for example, through subsistence farming or bartering. These forms of income tend to accrue to poor segments of populations in emerging and transitional economy countries such as those in sub-Saharan Africa, Latin America, Asia, and Eastern Europe. Informal economy accounts for over half of global employment and as much as 90 percent of employment in some of the poorer sub-Saharan countries with high official Gini inequality coefficients. Schneider et al., in their 2010 study of 162 countries, report about 31.2%, or about $20 trillion, of world's GDP is informal. In developing countries, the informal economy predominates for all income brackets except the richer, urban upper-income bracket populations. Even in developed economies, 8% (United States) to 27% (Italy) of each nation's GDP is informal. The resulting informal income predominates as a livelihood activity for those in the lowest income brackets. The value and distribution of the incomes from informal or underground economy is difficult to quantify, making true income Gini coefficients estimates difficult. Different assumptions and quantifications of these incomes will yield different Gini coefficients.

Alternatives
Given the limitations of the Gini coefficient, other statistical methods are used in combination or as an alternative measure of population dispersity. For example, entropy measures are frequently used (e.g. the Atkinson index or the Theil Index and Mean log deviation as special cases of the generalized entropy index). These measures attempt to compare the distribution of resources by intelligent agents in the market with a maximum entropy random distribution, which would occur if these agents acted like non-interacting particles in a closed system following the laws of statistical physics.

Relation to other statistical measures
There is a summary measure of the diagnostic ability of a binary classifier system that is also called the Gini coefficient, which is defined as twice the area between the receiver operating characteristic (ROC) curve and its diagonal. It is related to the AUC (Area Under the ROC Curve) measure of performance given by $$AUC = (G+1)/2$$  and to Mann–Whitney U. Although both Gini coefficients are defined as areas between certain curves and share certain properties, there is no simple direct relationship between the Gini coefficient of statistical dispersion and the Gini coefficient of a classifier. The Gini index is also related to the Pietra index — both of which measure statistical heterogeneity and are derived from the Lorenz curve and the diagonal line.

In certain fields such as ecology, inverse Simpson's index $$1/\lambda$$ is used to quantify diversity, and this should not be confused with the Simpson index $$\lambda$$. These indicators are related to Gini. The inverse Simpson index increases with diversity, unlike the Simpson index and Gini coefficient, which decrease with diversity. The Simpson index is in the range [0, 1], where 0 means maximum and 1 means minimum diversity (or heterogeneity). Since diversity indices typically increase with increasing heterogeneity, the Simpson index is often transformed into inverse Simpson, or using the complement $$1 - \lambda$$, known as the Gini-Simpson Index.

The Lorenz curve is another method of graphical representation of wealth distribution. It was developed 9 years before the Gini coefficient, which quantifies the extent to which the Lorenz curve deviates from the perfect equality line (with slope of 1). The Hoover index (also known as Robin Hood index) presents the percentage of total population's income that would have to be redistributed to make the Gini coefficient equal to 0 (perfect equality).

Gini coefficients for pre-modern societies
In recent decades, researchers have attempted to estimate Gini coefficients for pre-20th century societies. In the absence of household income surveys and income taxes, scholars have relied on proxy variables. These include wealth taxes in medieval European city states, patterns of landownership in Roman Egypt, variation of the size of houses in societies from ancient Greece to Aztec Mexico, and inheritance and dowries in Babylonian society. Other data does not directly document variations in wealth or income but are known to reflect inequality, such as the ratio of rents to wages or of labor to capital.

Other uses
Although the Gini coefficient is most popular in economics, it can, in theory, be applied in any field of science that studies a distribution. For example, in ecology, the Gini coefficient has been used as a measure of biodiversity, where the cumulative proportion of species is plotted against the cumulative proportion of individuals. In health, it has been used as a measure of the inequality of health-related quality of life in a population. In education, it has been used as a measure of the inequality of universities. In chemistry it has been used to express the selectivity of protein kinase inhibitors against a panel of kinases. In engineering, it has been used to evaluate the fairness achieved by Internet routers in scheduling packet transmissions from different flows of traffic.

The Gini coefficient is sometimes used for the measurement of the discriminatory power of rating systems in credit risk management.

A 2005 study accessed US census data to measure home computer ownership and used the Gini coefficient to measure inequalities amongst whites and African Americans. Results indicated that although decreasing overall, home computer ownership inequality was substantially smaller among white households.

A 2016 peer-reviewed study titled Employing the Gini coefficient to measure participation inequality in treatment-focused Digital Health Social Networks illustrated that the Gini coefficient was helpful and accurate in measuring shifts in inequality, however as a standalone metric it failed to incorporate overall network size.

Discriminatory power refers to a credit risk model's ability to differentiate between defaulting and non-defaulting clients. The formula $$G_1$$, in the calculation section above, may be used for the final model and at the individual model factor level to quantify the discriminatory power of individual factors. It is related to the accuracy ratio in population assessment models.

The Gini coefficient has also been applied to analyze inequality in dating apps.

Kaminskiy and Krivtsov extended the concept of the Gini coefficient from economics to reliability theory and proposed a Gini-type coefficient that helps to assess the degree of aging of non-repairable systems or aging and rejuvenation of repairable systems. The coefficient is defined between −1 and 1 and can be used in both empirical and parametric life distributions. It takes negative values for the class of decreasing failure rate distributions and point processes with decreasing failure intensity rate and is positive for the increasing failure rate distributions and point processes with increasing failure intensity rate. The value of zero corresponds to the exponential life distribution or the Homogeneous Poisson Process.

title: Gini coefficient


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GCHQ

Government Communications Headquarters (GCHQ) is an intelligence and security organisation responsible for providing signals intelligence (SIGINT) and information assurance (IA) to the government and armed forces of the United Kingdom. Primarily based at "The Doughnut" in the suburbs of Cheltenham, GCHQ is the responsibility of the country's Secretary of State for Foreign and Commonwealth Affairs (Foreign Secretary), but it is not a part of the Foreign Office and its Director ranks as a Permanent Secretary.

GCHQ was originally established after the First World War as the Government Code and Cypher School (GC&CS) and was known under that name until 1946. During the Second World War it was located at Bletchley Park, where it was responsible for breaking the German Enigma codes. There are two main components of GCHQ, the Composite Signals Organisation (CSO), which is responsible for gathering information, and the National Cyber Security Centre (NCSC), which is responsible for securing the UK's own communications. The Joint Technical Language Service (JTLS) is a small department and cross-government resource responsible for mainly technical language support and translation and interpreting services across government departments. It is co-located with GCHQ for administrative purposes.

In 2013, GCHQ received considerable media attention when the former National Security Agency contractor Edward Snowden revealed that the agency was in the process of collecting all online and telephone data in the UK via the Tempora programme. Snowden's revelations began a spate of ongoing disclosures of global surveillance. The Guardian newspaper was forced to destroy computer hard drives with the files Snowden had given them because of the threats of a lawsuit under the Official Secrets Act. In June 2014, The Register reported that the information the government sought to suppress by destroying the hard drives related to the location of a "beyond top secret" GCHQ internet monitoring base in Seeb, Oman, and the close involvement of BT and Cable & Wireless in intercepting internet communications.

Structure
GCHQ is led by the Director of GCHQ, Anne Keast-Butler, and a Corporate Board, made up of executive and non-executive directors. Reporting to the Corporate Board are:
 * Sigint missions: comprising maths and cryptanalysis, IT and computer systems, linguistics and translation, and the intelligence analysis unit
 * Enterprise: comprising applied research and emerging technologies, corporate knowledge and information systems, commercial supplier relationships, and biometrics
 * Corporate management: enterprise resource planning, human resources, internal audit, and architecture
 * National Cyber Security Centre (NCSC).

World War I
During the First World War, the British Army and Royal Navy had separate signals intelligence agencies, MI1b and NID25 (initially known as Room 40) respectively. In 1919, the Cabinet's Secret Service Committee, chaired by Lord Curzon, recommended that a peacetime codebreaking agency should be created, a task which was given to the Director of Naval Intelligence, Hugh Sinclair. Sinclair merged staff from NID25 and MI1b into the new organisation, which initially consisted of around 25–30 officers and a similar number of clerical staff. It was titled the "Government Code and Cypher School" (GC&CS), a cover-name which was chosen by Victor Forbes of the Foreign Office. Alastair Denniston, who had been a member of NID25, was appointed as its operational head. It was initially under the control of the Admiralty and located in Watergate House, Adelphi, London. Its public function was "to advise as to the security of codes and cyphers used by all Government departments and to assist in their provision", but also had a secret directive to "study the methods of cypher communications used by foreign powers". GC&CS officially formed on 1 November 1919, and produced its first decrypt prior to that date, on 19 October.

Before the Second World War, GC&CS was a relatively small department. By 1922, the main focus of GC&CS was on diplomatic traffic, with "no service traffic ever worth circulating" and so, at the initiative of Lord Curzon, it was transferred from the Admiralty to the Foreign Office. GC&CS came under the supervision of Hugh Sinclair, who by 1923 was both the Chief of SIS and Director of GC&CS. In 1925, both organisations were co-located on different floors of Broadway Buildings, opposite St. James's Park. Messages decrypted by GC&CS were distributed in blue-jacketed files that became known as "BJs". In the 1920s, GC&CS was successfully reading Soviet Union diplomatic cyphers. However, in May 1927, during a row over clandestine Soviet support for the General Strike and the distribution of subversive propaganda, Prime Minister Stanley Baldwin made details from the decrypts public.

World War II
During the Second World War, GC&CS was based largely at Bletchley Park, in present-day Milton Keynes, working on understanding the German Enigma machine and Lorenz ciphers. In 1940, GC&CS was working on the diplomatic codes and ciphers of 26 countries, tackling over 150 diplomatic cryptosystems. Senior staff included Alastair Denniston, Oliver Strachey, Dilly Knox, John Tiltman, Edward Travis, Ernst Fetterlein, Josh Cooper, Donald Michie, Alan Turing, Gordon Welchman, Joan Clarke, Max Newman, William Tutte, I. J. (Jack) Good, Peter Calvocoressi and Hugh Foss. The 1943 British–US Communication Intelligence Agreement, BRUSA, connected the signal intercept networks of the GC&CS and the US National Security Agency (NSA). Equipment used to break enemy codes included the Colossus computer. Colossus consisted of ten networked computers.

An outstation in the Far East, the Far East Combined Bureau, was set up in Hong Kong in 1935 and moved to Singapore in 1939. Subsequently, with the Japanese advance down the Malay Peninsula, the Army and RAF codebreakers went to the Wireless Experimental Centre in Delhi, India. The Navy codebreakers in FECB went to Colombo, Ceylon, then to Kilindini, near Mombasa, Kenya.

Post Second World War
GC&CS was renamed the Government Communications Headquarters (GCHQ) in June 1946.

The organisation was at first based in Eastcote in northwest London, then in 1951 moved to the outskirts of Cheltenham, setting up two sites at Oakley and Benhall. One of the major reasons for selecting Cheltenham was that the town had been the location of the headquarters of the United States Army Services of Supply for the European Theater during the War, which built up a telecommunications infrastructure in the region to carry out its logistics tasks.

Following the Second World War, US and British intelligence have shared information as part of the UKUSA Agreement. The principal aspect of this is that GCHQ and its US equivalent, the National Security Agency (NSA), share technologies, infrastructure and information.

GCHQ ran many signals intelligence (SIGINT) monitoring stations abroad. During the early Cold War, the remnants of the British Empire provided a global network of ground stations which were a major contribution to the UKUSA Agreement; the US regarded RAF Little Sai Wan in Hong Kong as the most valuable of these. The monitoring stations were largely run by inexpensive National Service recruits, but when this ended in the early 1960s, the increased cost of civilian employees caused budgetary problems. In 1965 a Foreign Office review found that 11,500 staff were involved in SIGINT collection (8,000 GCHQ staff and 3,500 military personnel), exceeding the size of the Diplomatic Service. Reaction to the Suez War led to the eviction of GCHQ from several of its best foreign SIGINT collection sites, including the new Perkar, Ceylon site and RAF Habbaniya, Iraq. The staff largely moved to tented encampments on military bases in Cyprus, which later became the Sovereign Base Area.

During the Cuban Missile Crisis, GCHQ Scarborough intercepted radio communications from Soviet ships reporting their positions and used that to establish where they were heading. A copy of the report was sent directly to the White House Situation Room, providing initial indications of Soviet intentions with regards the US naval blockade of Cuba.

Duncan Campbell and Mark Hosenball revealed the existence of GCHQ in 1976 in an article for Time Out; as a result, Hosenball was deported from the UK. GCHQ had a very low profile in the media until 1983 when the trial of Geoffrey Prime, a KGB mole within it, created considerable media interest.

Trade union disputes
In 1984, GCHQ was the centre of a political row when, in the wake of strikes which affected Sigint collection, the Conservative government of Margaret Thatcher prohibited its employees from belonging to a trade union. Following the breakdown of talks and the failure to negotiate a no-strike agreement, it was believed by the Thatcher Government that membership of a union would be in conflict with national security. A number of mass national one-day strikes were held to protest this decision, claimed by some as the first step to wider bans on trade unions. Appeals to British courts and European Commission of Human Rights were unsuccessful. The government offered a sum of money to each employee who agreed to give up their union membership. An appeal to the International Labour Organization resulted in a decision that the government's actions were in violation of Freedom of Association and Protection of the Right to Organise Convention.

A no-strike agreement was eventually negotiated and the ban lifted by the incoming Labour government in 1997, with the Government Communications Group of the Public and Commercial Services Union (PCS) being formed to represent interested employees at all grades. In 2000, a group of 14 former GCHQ employees, who had been dismissed after refusing to give up their union membership, were offered re-employment, which three of them accepted.

The legal case Council of Civil Service Unions v Minister for the Civil Service is significant beyond the dispute, and even beyond trade union law, in that it held for the first time that the royal prerogative is generally subject to judicial review, although the House of Lords ruled in favour of the Crown in this instance.

1990s: Post-Cold War restructuring
The Intelligence Services Act 1994 formalised the activities of the intelligence agencies for the first time, defining their purpose, and the British Parliament's Intelligence and Security Committee was given a remit to examine the expenditure, administration and policy of the three intelligence agencies. The objectives of GCHQ were defined as working as "in the interests of national security, with particular reference to the defence and foreign policies of His Majesty's government; in the interests of the economic wellbeing of the United Kingdom; and in support of the prevention and the detection of serious crime". During the introduction of the Intelligence Agency Act in late 1993, the former Prime Minister Jim Callaghan had described GCHQ as a "full-blown bureaucracy", adding that future bodies created to provide oversight of the intelligence agencies should "investigate whether all the functions that GCHQ carries out today are still necessary."

In late 1993 civil servant Michael Quinlan advised a deep review of the work of GCHQ following the conclusion of his "Review of Intelligence Requirements and Resources", which had imposed a 3% cut on the agency. The Chief Secretary to the Treasury, Jonathan Aitken, subsequently held face to face discussions with the intelligence agency directors to assess further savings in the wake of Quinlan's review. Aldrich (2010) suggests that Sir John Adye, the then Director of GCHQ performed badly in meetings with Aitken, leading Aitken to conclude that GCHQ was "suffering from out-of-date methods of management and out-of-date methods for assessing priorities". GCHQ's budget was £850 million in 1993, (£ as of ) compared to £125 million for the Security Service and SIS (MI5 and MI6). In December 1994 the businessman Roger Hurn was commissioned to begin a review of GCHQ, which was concluded in March 1995. Hurn's report recommended a cut of £100 million in GCHQ's budget; such a large reduction had not been suffered by any British intelligence agency since the end of World War II. The J Division of GCHQ, which had collected SIGINT on Russia, disappeared as a result of the cuts. The cuts had been mostly reversed by 2000 in the wake of threats from violent non-state actors, and risks from increased terrorism, organised crime and illegal access to nuclear, chemical and biological weapons.

David Omand became the Director of GCHQ in 1996, and greatly restructured the agency in the face of new and changing targets and rapid technological change. Omand introduced the concept of "Sinews" (or "SIGINT New Systems") which allowed more flexible working methods, avoiding overlaps in work by creating fourteen domains, each with a well-defined working scope. The tenure of Omand also saw the construction of a modern new headquarters, intended to consolidate the two old sites at Oakley and Benhall into a single, more open-plan work environment. Located on a 176-acre site in Benhall, it would be the largest building constructed for secret intelligence operations outside the United States.

Operations at GCHQ's Chung Hom Kok listening station in Hong Kong ended in 1994. GCHQ's Hong Kong operations were extremely important to their relationship with the NSA, who contributed investment and equipment to the station. In anticipation of the transfer of Hong Kong to the Chinese government in 1997, the Hong Kong stations operations were moved to Australian Defence Satellite Communications Station in Geraldton in Western Australia.

Operations that used GCHQ's intelligence-gathering capabilities in the 1990s included the monitoring of communications of Iraqi soldiers in the Gulf War, of dissident republican terrorists and the Real IRA, of the various factions involved in the Yugoslav Wars, and of the criminal Kenneth Noye. In the mid 1990s GCHQ began to assist in the investigation of cybercrime.

2000s: Coping with the Internet
At the end of 2003, GCHQ moved in to its new building. Built on a circular plan around a large central courtyard, it quickly became known as the Doughnut. At the time, it was one of the largest public-sector building projects in Europe, with an estimated cost of £337 million. The new building, which was designed by Gensler and constructed by Carillion, became the base for all of GCHQ's Cheltenham operations.

The public spotlight fell on GCHQ in late 2003 and early 2004 following the sacking of Katharine Gun after she leaked to The Observer a confidential email from agents at the United States' National Security Agency addressed to GCHQ agents about the wiretapping of UN delegates in the run-up to the 2003 Iraq war.

GCHQ gains its intelligence by monitoring a wide variety of communications and other electronic signals. For this, a number of stations have been established in the UK and overseas. The listening stations are at Cheltenham itself, Bude, Scarborough, Ascension Island, and with the United States at Menwith Hill. Ayios Nikolaos Station in Cyprus is run by the British Army for GCHQ.

In March 2010, GCHQ was criticised by the Intelligence and Security Committee for problems with its IT security practices and failing to meet its targets for work targeted against cyber attacks.

As revealed by Edward Snowden in The Guardian, GCHQ spied on foreign politicians visiting the 2009 G-20 London Summit by eavesdropping phonecalls and emails and monitoring their computers, and in some cases even ongoing after the summit via keyloggers that had been installed during the summit.

According to Edward Snowden, at that time GCHQ had two principal umbrella programs for collecting communications:
 * "Mastering the Internet" (MTI) for Internet traffic, which is extracted from fibre-optic cables and can be searched by using the Tempora computer system.
 * "Global Telecoms Exploitation" (GTE) for telephone traffic.

GCHQ has also had access to the US internet monitoring programme PRISM from at least as far back as June 2010. PRISM is said to give the National Security Agency and FBI easy access to the systems of nine of the world's top internet companies, including Google, Facebook, Microsoft, Apple, Yahoo, and Skype.

From 2013, GCHQ realised that public attitudes to Sigint had changed and its former unquestioned secrecy was no longer appropriate or acceptable. The growing use of the Internet, together with its inherent insecurities, meant that the communications traffic of private citizens were becoming inextricably mixed with those of their targets and openness in the handling of this issue was becoming essential to their credibility as an organisation. The Internet had become a "cyber commons", with its dominance creating a "second age of Sigint". GCHQ transformed itself accordingly, including greatly expanded Public Relations and Legal departments, and adopting public education in cyber security as an important part of its remit.

2010s: Disinformation, discord and division
In February 2014, The Guardian, based on documents provided by Snowden, revealed that GCHQ had indiscriminately collected 1.8 million private Yahoo webcam images from users across the world. In the same month NBC and The Intercept, based on documents released by Snowden, revealed the Joint Threat Research Intelligence Group and the Computer Network Exploitation units within GCHQ. Their mission was cyber operations based on "dirty tricks" to shut down enemy communications, discredit, and plant misinformation on enemies. These operations were 5% of all GCHQ operations according to a conference slideshow presented by the GCHQ.

Soon after becoming Director of GCHQ in 2014, Robert Hannigan wrote an article in the Financial Times on the topic of internet surveillance, stating that "however much [large US technology companies] may dislike it, they have become the command and control networks of choice for terrorists and criminals" and that GCHQ and its sister agencies "cannot tackle these challenges at scale without greater support from the private sector", arguing that most internet users "would be comfortable with a better and more sustainable relationship between the [intelligence] agencies and the tech companies". Since the 2013 global surveillance disclosures, large US technology companies have improved security and become less co-operative with foreign intelligence agencies, including those of the UK, generally requiring a US court order before disclosing data. However the head of the UK technology industry group techUK rejected these claims, stating that they understood the issues but that disclosure obligations "must be based upon a clear and transparent legal framework and effective oversight rather than, as suggested, a deal between the industry and government".

In 2015, documents obtained by The Intercept from US National Security Agency whistleblower Edward Snowden revealed that GCHQ had carried out a mass-surveillance operation, codenamed KARMA POLICE, since about 2008. The operation swept up the IP address of Internet users visiting websites, and was established with no public scrutiny or oversight. KARMA POLICE is a powerful spying tool in conjunction with other GCHQ programs because IP addresses could be cross-referenced with other data. The goal of the program, according to the documents, was "either (a) a web browsing profile for every visible user on the internet, or (b) a user profile for every visible website on the internet."

In 2015, GCHQ admitted for the first time in court that it conducts computer hacking.

In 2017, US Press Secretary Sean Spicer made allegations that GCHQ had conducted surveillance on US President Donald Trump. These unfounded claims were based on statements made during an opinion piece in a FOX media segment. The US government formally apologised for the unfounded allegations and promised they would not be repeated.

British intelligence did gather information relating to Russian contacts made by Trump's campaign team in the run-up to his election, which were passed on to US intelligence agencies.

On 31 October 2018, GCHQ joined Instagram.

Personnel awards
GCHQ personnel are recognised annually by King Charles III (formerly the Prince of Wales) at the Prince of Wales's Intelligence Community Awards at St James's Palace or Clarence House alongside members of the Security Service (MI5), and Secret Intelligence Service (MI6). Awards and citations are given to teams within the agencies as well as individuals.

Security mission
As well as a mission to gather intelligence, GCHQ has for a long time had a corresponding mission to assist in the protection of the British government's own communications. When the Government Code and Cypher School (GC&CS) was created in 1919, its overt task was providing security advice. GC&CS's Security section was located in Mansfield College, Oxford during the Second World War.

In April 1946, GC&CS became GCHQ, and the now GCHQ Security section moved from Oxford to join the rest of the organisation at Eastcote later that year.

LCSA
From 1952 to 1954, the intelligence mission of GCHQ relocated to Cheltenham; the Security section remained at Eastcote, and in March 1954 became a separate, independent organisation: the London Communications Security Agency (LCSA), which in 1958 was renamed to the London Communications-Electronic Security Agency (LCESA).

In April 1965, GPO and MOD units merged with LCESA to become the Communications-Electronic Security Department (CESD).

CESG
In October 1969, CESD was merged into GCHQ and becoming Communications-Electronic Security Group (CESG).

In 1977 CESG relocated from Eastcote to Cheltenham.

CESG continued as the UK National Technical Authority for information assurance, including cryptography. CESG did not manufacture security equipment, but worked with industry to ensure the availability of suitable products and services, while GCHQ itself funded research into such areas, for example to the Centre for Quantum Computation at Oxford University and the Heilbronn Institute for Mathematical Research at the University of Bristol.

In the 21st century, CESG ran a number of assurance schemes such as CHECK, CLAS, Commercial Product Assurance (CPA) and CESG Assisted Products Service (CAPS).

Public key encryption
In 1970 the concept for public-key encryption (public key infrastructure) was developed and proven by GCHQ's James H. Ellis. Ellis lacked the number theory skills required to build a workable system. In 1974 GCHQ mathematician Clifford Cocks had developed a workable public key cryptography algorithm and a workable PKI system. Cock's system was not available in the public domain until it was declassified in 1997.

By 1997 broader public key cryptography commercial technologies had been independently developed and had become well established, in areas such as email security, digital signatures, and TLS (a fundamental TCP/IP security component) etc. Most notably in 1977 the RSA algorithm had been developed (equivalent to Cocks' system) and by 1997 was extremely well established.

NCSC
In 2016, the National Cyber Security Centre was established under GCHQ but located in London, as the UK's authority on cybersecurity. It absorbed and replaced CESG as well as activities that had previously existed outside GCHQ: the Centre for Cyber Assessment (CCA), Computer Emergency Response Team UK (CERT UK) and the cyber-related responsibilities of the Centre for the Protection of National Infrastructure (CPNI).

Joint Technical Language Service
The Joint Technical Language Service (JTLS) was established in 1955, drawing on members of the small Ministry of Defence technical language team and others, initially to provide standard English translations for organisational expressions in any foreign language, discover the correct English equivalents of technical terms in foreign languages and discover the correct expansions of abbreviations in any language. The remit of the JTLS has expanded in the ensuing years to cover technical language support and interpreting and translation services across the UK Government and to local public sector services in Gloucestershire and surrounding counties. The JTLS also produces and publishes foreign language working aids under crown copyright and conducts research into machine translation and on-line dictionaries and glossaries. The JTLS is co-located with GCHQ for administrative purposes.

International relationships
GCHQ operates in partnership with equivalent agencies worldwide in a number of bi-lateral and multi-lateral relationships. The principal of these is with the United States (National Security Agency), Canada (Communications Security Establishment), Australia (Australian Signals Directorate) and New Zealand (Government Communications Security Bureau), through the mechanism of the UK-US Security Agreement, a broad intelligence-sharing agreement encompassing a range of intelligence collection methods. Relationships are alleged to include shared collection methods, such as the system described in the popular media as ECHELON, as well as analysed product.

Legal basis
GCHQ's legal basis is established by the Intelligence Services Act 1994 Section 3 as follows:

"(1) There shall continue to be a Government Communications Headquarters under the authority of the Secretary of State; and, subject to subsection (2) below, its functions shall be—(a) to monitor or interfere with electromagnetic, acoustic and other emissions and any equipment producing such emissions and to obtain and provide information derived from or related to such emissions or equipment and from encrypted material; and

(b) to provide advice and assistance about—(i) languages, including terminology used for technical matters, and

(ii) cryptography and other matters relating to the protection of information and other material, to the armed forces of the Crown, to Her Majesty's Government in the United Kingdom or to a Northern Ireland Department or to any other organisation which is determined for the purposes of this section in such manner as may be specified by the Prime Minister.

(2) The functions referred to in subsection (1)(a) above shall be exercisable only—(a) in the interests of national security, with particular reference to the defence and foreign policies of His Majesty's Government in the United Kingdom; or

(b) in the interests of the economic well-being of the United Kingdom in relation to the actions or intentions of persons outside the British Islands; or

(c) in support of the prevention or detection of serious crime.

(3) In this Act, the expression 'GCHQ' refers to the Government Communications Headquarters and to any unit or part of a unit of the armed forces of the Crown which is for the time being required by the Secretary of State to assist the Government Communications Headquarters in carrying out its functions."

Activities that involve interception of communications are permitted under the Regulation of Investigatory Powers Act 2000; this kind of interception can only be carried out after a warrant has been issued by a Secretary of State. The Human Rights Act 1998 requires the intelligence agencies, including GCHQ, to respect citizens' rights as described in the European Convention on Human Rights.

Oversight
The Prime Minister nominates cross-party Members of Parliament to an Intelligence and Security Committee. The remit of the Committee includes oversight of intelligence and security activities and reports are made directly to Parliament. Its functions were increased under the Justice and Security Act 2013 to provide for further access and investigatory powers.

Judicial oversight of GCHQ's conduct is exercised by the Investigatory Powers Tribunal. The UK also has an independent Intelligence Services Commissioner and Interception of Communications Commissioner, both of whom are former senior judges.

The Investigatory Powers Tribunal ruled in December 2014 that GCHQ does not breach the European Convention of Human Rights, and that its activities are compliant with Articles 8 (right to privacy) and 10 (freedom of expression) of the European Convention of Human Rights. However, the Tribunal stated in February 2015 that one particular aspect, the data-sharing arrangement that allowed UK Intelligence services to request data from the US surveillance programmes Prism and Upstream, had been in contravention of human rights law prior to this until two paragraphs of additional information, providing details about the procedures and safeguards, were disclosed to the public in December 2014.

Furthermore, the IPT ruled that the legislative framework in the United Kingdom does not permit mass surveillance and that while GCHQ collects and analyses data in bulk, it does not practice mass surveillance. This complements independent reports by the Interception of Communications Commissioner, and a special report made by the Intelligence and Security Committee of Parliament; although several shortcomings and potential improvements to both oversight and the legislative framework were highlighted.

Abuses
Despite the inherent secrecy around much of GCHQ's work, investigations carried out by the UK government after the Snowden disclosures have admitted various abuses by the security services. A report by the Intelligence and Security Committee (ISC) in 2015 revealed that a small number of staff at UK intelligence agencies had been found to misuse their surveillance powers, in one case leading to the dismissal of a member of staff at GCHQ, although there were no laws in place at the time to make these abuses a criminal offence.

Later that year, a ruling by the Investigatory Powers Tribunal found that GCHQ acted unlawfully in conducting surveillance on two human rights organisations. The closed hearing found the government in breach of its internal surveillance policies in accessing and retaining the communications of the Egyptian Initiative for Personal Rights and the Legal Resources Centre in South Africa. This was only the second time in the IPT's history that it had made a positive determination in favour of applicants after a closed session.

At another IPT case in 2015, GCHQ conceded that "from January 2010, the regime for the interception/obtaining, analysis, use, disclosure and destruction of legally privileged material has not been in accordance with the law for the purposes of Article 8(2) of the European convention on human rights and was accordingly unlawful". This admission was made in connection with a case brought against them by Abdelhakim Belhaj, a Libyan opponent of the former Gaddafi regime, and his wife Fatima Bouchard. The couple accused British ministers and officials of participating in their unlawful abduction, kidnapping and removal to Libya in March 2004, while Gaddafi was still in power.

On 25 May 2021, the European Court of Human Rights (ECHR) ruled that the GCHQ is guilty of violating data privacy rules through their bulk interception of communications, and does not provide sufficient protections for confidential journalistic material because it gathers communications in bulk.

Surveillance of parliamentarians
In 2015 there was a complaint by Green Party MP Caroline Lucas that British intelligence services, including GCHQ, had been spying on MPs allegedly "in defiance of laws prohibiting it."

Then-Home Secretary, Theresa May, had told Parliament in 2014 that: "Obviously, the Wilson Doctrine applies to parliamentarians. It does not absolutely exclude the use of these powers against parliamentarians, but it sets certain requirements for those powers to be used in relation to a parliamentarian. It is not the case that parliamentarians are excluded and nobody else in the country is, but there is a certain set of rules and protocols that have to be met if there is a requirement to use any of these powers against a parliamentarian."

The Investigatory Powers Tribunal investigated the complaint, and ruled that contrary to the allegation, there was no law that gave the communications of Parliament any special protection. The Wilson Doctrine merely acts as a political convention.

Constitutional legal case
A controversial GCHQ case determined the scope of judicial review of prerogative powers (the Crown's residual powers under common law). This was Council of Civil Service Unions v Minister for the Civil Service [1985] AC 374 (often known simply as the "GCHQ case"). In this case, a prerogative Order in Council had been used by the prime minister (who is the Minister for the Civil Service) to ban trade union activities by civil servants working at GCHQ. This order was issued without consultation. The House of Lords had to decide whether this was reviewable by judicial review. It was held that executive action is not immune from judicial review simply because it uses powers derived from common law rather than statute (thus the prerogative is reviewable).

Leadership
The following is a list of the heads and operational heads of GCHQ and GC&CS:

 * Sir Hugh Sinclair (1919–1939) (founder)
 * Cmdr Alastair Denniston (1921–February 1942) (operational head)
 * Sir Edward Travis (February 1942 – 1952)
 * Sir Eric Jones (April 1952 – 1960)
 * Sir Clive Loehnis (1960–1964)
 * Sir Leonard Hooper (1965–1973)
 * Sir Arthur Bonsall (1973–1978)
 * Sir Brian John Maynard Tovey (1978–1983)
 * Sir Peter Marychurch (1983–1989)
 * Sir John Anthony Adye (1989–1996)
 * Sir David Omand (1996 –1997)
 * Sir Kevin Tebbit (1998)
 * Sir Francis Richards (1998–2003)
 * Sir David Pepper (2003–2008)
 * Sir Iain Lobban (2008–2014)
 * Robert Hannigan (2014–2017)
 * Sir Jeremy Fleming (2017–2023)
 * Anne Keast-Butler (2023–Present)

Stations and former stations
The following are stations and former stations that have operated since the Cold War.

United Kingdom

 * GCHQ Bude, Cornwall
 * GCHQ Cheltenham, Gloucestershire (headquarters)
 * GCHQ London
 * GCHQ Manchester
 * GCHQ Scarborough, North Yorkshire
 * RAF Digby, Lincolnshire
 * RAF Menwith Hill, North Yorkshire

Overseas

 * GCHQ Ascension Island
 * GCHQ Cyprus
 * GCHQ Oman

United Kingdom

 * GCHQ Brora, Sutherland
 * GCHQ Cheadle, Staffordshire
 * GCHQ Culmhead, Somerset
 * GCHQ Hawklaw, Fife

Overseas

 * GCHQ Hong Kong

In popular culture
In the historical drama film The Imitation Game (2014) Benedict Cumberbatch portrays Alan Turing in his efforts to break the Enigma code while employed by the Government Code and Cypher School.

GCHQ have set a number of cryptic online challenges to the public, used to attract interest and for recruitment, starting in late 1999. The response to the 2004 challenge was described as "excellent", and the challenge set in 2015 had over 600,000 attempts. It also published the GCHQ Puzzle Book in 2016 which sold more than 300,000 copies, with the proceeds going to charity. A second book was published in October 2018.

GCHQ appeared in the Doctor Who 2019 special "Resolution" where the Reconnaissance Scout Dalek storms the facility and exterminates the staff in order to use the organisation's resources to summon a Dalek fleet.

GCHQ is the setting of the 2020 Sky One sitcom Intelligence, featuring David Schwimmer as an incompetent American NSA officer liaising with GCHQ's Cyber Crimes unit.

In October 2020, intelligence and security expert John Ferris published Behind the Enigma: The Authorised History of GCHQ, Britain's Secret Cyber-Intelligence Agency.

GCHQ is the setting of the 2022 Channel 4 drama The Undeclared War. Set in the near future, it depicts a work experience student at the government agency during a cyberattack on the UK and the implications.

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/

title: GCHQ


text:
Wikipedia:Naming conventions (Polish rulers)

There has been an attempt to create a naming system specifically for Polish monarchs (but it is just a proposal and never received consensus), against the system used for other European monarchs. There is also the fact that most Polish monarchs now are located in places which contravene to general naming convention. There is no consensus for permission to use an exception for Polish monarchs, and such permission should be sought from consensus at Wikipedia talk:Naming conventions (names and titles) where there is the thread Wikipedia talk:Naming conventions (names and titles). At that spot there are editors who are more or less experienced in overall picture of monarch naming and not only one country. It is deception to advertise any system for naming before a consensus there is convinced of the need for such exception. I hope all of you continue the naming scheme discussion for Polish monarchs there, before continuing or creating policy forks. Shilkanni 13:06, 6 June 2006 (UTC)
 * agree with this analysis of current state of affairs, which means: relay this to Wikipedia talk:Naming conventions (names and titles). And which also means that until further notice current separate NC proposals for Polish rulers are rejected. --Francis Schonken 13:42, 6 June 2006 (UTC)
 * agree with Shilkanni, and the rejection of this proposal. There have been too many forked discussions about this matter, especially in nooks and crannies of Wikipedia that do not have the attention they need to garner a genuine cross-cultural community consensus.  Moving all of the discussions to one centralized location at Wikipedia talk:Naming conventions (names and titles) is an excellent idea. --Elonka 18:19, 6 June 2006 (UTC)
 * agree also. It is sad that this little coup was allowed to take place without anyone but its two perpetrators being informed. Despite all his attempts to convince, Piotrus has given no reason other than his own patriotism as to why these monarchs should be different from those of other European monarchies. - Calgacus (ΚΑΛΓΑΚΟΣ) 19:12, 6 June 2006 (UTC)


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Francis Gary Powers

Francis Gary Powers (August 17, 1929 – August 1, 1977) was an American pilot whose Central Intelligence Agency (CIA) Lockheed U-2 spy plane was shot down while flying a reconnaissance mission in Soviet Union airspace, causing the 1960 U-2 incident.

He later worked as a helicopter pilot for KNBC in Los Angeles and died in a 1977 helicopter crash.

Early life and education
Powers was born August 17, 1929, in Jenkins, Kentucky, the son of Oliver Winfield Powers (1904–1970), a coal miner, and his wife Ida Melinda Powers (Ford; 1905–1991). His family eventually moved to Pound, Virginia, just across the state border. He was the second-born and only male of six children.

His family lived in a mining town, and because of the hardships associated with living in such a town, his father wanted Powers to become a physician. He hoped his son would achieve the higher earnings of such a profession and felt that this would involve less hardship than any job in his hometown.

Education and service
After graduating with a bachelor's degree from Milligan College in Tennessee in June 1950, Powers enlisted in the United States Air Force in October. He was commissioned as a second lieutenant in December 1952 after completing his advanced training with USAF Pilot Training Class 52-H at Williams Air Force Base, Arizona. Powers was then assigned to the 468th Strategic Fighter Squadron at Turner Air Force Base, Georgia, as a Republic F-84 Thunderjet pilot.

Powers married Barbara Gay Moore in Newnan, Georgia, on April 2, 1955. In January 1956 he was recruited by the CIA. In May 1956 he began U-2 training at Watertown Strip, Nevada. His training was complete by August 1956 and his unit, the Second Weather Observational Squadron (Provisional) or Detachment 10-10, was deployed to Incirlik Air Base, Turkey. By 1960, Powers was already a veteran of many covert aerial reconnaissance missions. Family members believed that he was a NASA weather reconnaissance pilot.

U-2 incident
Powers was discharged from the Air Force in 1956 with the rank of captain. He then joined the CIA's U-2 program at the civilian grade of GS-12. U-2 pilots flew espionage missions at altitudes of 70,000 ft, supposedly above the reach of Soviet air defenses. The U-2 was equipped with a state-of-the-art camera designed to take high-resolution photos from the stratosphere over hostile countries, including the Soviet Union. U-2 missions systematically photographed military installations and other important sites.

Reconnaissance mission
The primary mission of the U-2s was to overfly the Soviet Union. Soviet intelligence had been aware of encroaching U-2 flights at least since 1958 if not earlier but lacked effective countermeasures until 1960. On May 1, 1960, Powers' U-2A, 56-6693, departed from a military airbase in Peshawar, Pakistan, with support from the U.S. Air Station at Badaber (Peshawar Air Station). This was to be the first attempt "to fly all the way across the Soviet Union ... but it was considered worth the gamble. The planned route would take us deeper into Russia than we had ever gone, while traversing important targets never before photographed."

Shot down
Powers was shot down by an S-75 Dvina (SA-2 "Guideline") surface-to-air missile over Sverdlovsk. A total of 14 Dvinas were launched, one of which hit a MiG-19 jet fighter which was sent to intercept the U-2 but could not reach a high enough altitude. Its pilot, Sergei Safronov, ejected but died of his injuries. Another Soviet aircraft, a newly manufactured Su-9 on a transit flight, also attempted to intercept Powers' U-2. The unarmed Su-9 was directed to ram the U-2 but missed because of the large differences in speed.

As Powers flew near Kosulino in the Ural Region, three S-75 Dvinas were launched at his U-2, with the first one hitting the aircraft. "What was left of the plane began spinning, only upside down, the nose pointing upward toward the sky, the tail down toward the ground." According to his book Operation Overflight, Powers delayed activating the camera's self-destruct mechanism until he made sure he could exit the cockpit before the charges detonated. When g-forces unexpectedly threw him from the spinning aircraft, he could no longer reach the destruct switches. While descending under his parachute, Powers had time to scatter his escape map, and rid himself of part of his suicide device, a silver dollar coin suspended around his neck containing a poison-laced injection pin, though he kept the poison pin. "Yet I was still hopeful of escape." He hit the ground hard, was immediately captured, and taken to Lubyanka Prison in Moscow. Powers did note a second chute after landing on the ground, "some distance away and very high, a lone red and white parachute".

Attempted deception by the U.S. government
When the U.S. government learned of Powers' disappearance over the Soviet Union, they lied that a "weather plane" had strayed off course after its pilot had "difficulties with his oxygen equipment". What CIA officials did not realize was that the plane crashed almost fully intact and that the Soviets had recovered its pilot and much of the plane's equipment, including its new top-secret high-altitude camera. Powers was interrogated extensively by the KGB for months before he made a confession and a public apology for his part in espionage.

Portrayal in U.S. media
Following admission by the White House that Powers had been captured alive, American media depicted Powers as an all-American pilot hero, who never smoked or touched alcohol. In fact, Powers smoked and drank socially. The CIA urged that his wife Barbara be given sedatives before speaking to the press and gave her talking points that she repeated to the press to portray her as a devoted wife. Her broken leg, according to the CIA disinformation, was the result of a water-skiing accident, when in fact it happened after she had had too much to drink and was dancing with another man.

In the course of his trial for espionage in the Soviet Union, Powers confessed to the charges against him and apologized for violating Soviet airspace to spy on the Soviets. In the wake of his apology, American media often depicted Powers as a coward and even as a symptom of the decay of America's "moral character."

Pilot testimony compromised by newspaper reports
Powers tried to limit the information he shared with the KGB to that which could be determined from the remains of his plane's wreckage. He was hampered by information appearing in the western press. A KGB major stated "there's no reason for you to withhold information. We'll find it out anyway. Your Press will give it to us." However, he limited his divulging of CIA contacts to one individual, with a pseudonym of "Collins". At the same time, he repeatedly stated the maximum altitude for the U-2 was 68,000 ft, lower than its actual flight ceiling.

Political consequence
The incident set back talks between Khrushchev and Eisenhower. Powers' interrogations ended on June 30, and his solitary confinement ended on July 9. On August 17, 1960, his trial began for espionage before the military division of the Supreme Court of the Soviet Union. Lieutenant General Borisoglebsky, Major General Vorobyev, and Major General Zakharov presided. Roman Rudenko acted as prosecutor in his capacity of Procurator General of the Soviet Union. Mikhail I. Grinev served as Powers' defense counsel. In attendance were his parents and sister, and his wife Barbara and her mother. His father brought along his attorney Carl McAfee, while the CIA provided two additional attorneys.

Conviction
On August 19, 1960, Powers was convicted of espionage, "a grave crime covered by Article 2 of the Soviet Union's law 'On Criminality Responsibility for State Crimes'". His sentence consisted of 10 years' confinement, three of which were to be in a prison, with the remainder in a labor camp. The US Embassy "News Bulletin" stated, according to Powers, "as far as the government was concerned, I had acted in accordance with the instructions given me and would receive my full salary while imprisoned".

He was held in Vladimir Central Prison, about 150 mi east of Moscow, in building number 2 from September 9, 1960, until February 8, 1962. His cellmate was Zigurds Krūmiņš, a Latvian political prisoner. Powers kept a diary and a journal while confined. Additionally, he learned carpet weaving from his cellmate to pass the time. He could send and receive a limited number of letters to and from his family. The prison now contains a small museum with an exhibit on Powers, who allegedly developed a good rapport with Soviet prisoners there. Some pieces of the plane and Powers' uniform are on display at the Monino Airbase museum near Moscow.

CIA opposition to exchange
The CIA, in particular chief of CIA Counterintelligence James Jesus Angleton, opposed exchanging Powers for Soviet KGB Colonel William Fisher, known as "Rudolf Abel", who had been caught by the FBI and tried and jailed for espionage. First, Angleton believed that Powers might have deliberately defected to the Soviet side. CIA documents released in 2010 indicate that U.S. officials did not believe Powers' account of the incident at the time, because it was contradicted by a classified National Security Agency (NSA) report which alleged that the U-2 had descended from 65,000 to 34,000 ft before changing course and disappearing from radar. The NSA report remains classified as of 2022.

In any event, Angleton suspected that Powers had already revealed all he knew to the Soviets and therefore reasoned that Powers was worthless to the U.S. On the other hand, according to Angleton, William Fisher had revealed little to the CIA, refusing to disclose even his real name, and for this reason, William Fisher was still of potential value.

However, Barbara Powers, Gary Powers' wife, was allegedly often drinking and having affairs. On June 22, 1961, she was pulled over by the police after driving erratically and was caught driving under the influence. To avoid bad publicity for the wife of the well-known CIA operative, doctors tasked by the CIA to keep Barbara out of the limelight arranged to have her committed to a psychiatric ward in Augusta, Georgia, under strict supervision. She was eventually released to the care of her mother. However, the CIA feared that Gary Powers languishing in Soviet prison might learn of Barbara's plight and as a result reach a state of desperation causing him to reveal to the Soviets whatever secrets he had not already revealed. Thus, Barbara unwittingly may have aided the cause of the approval of the prisoner exchange involving her husband and William Fisher. Angleton and others at the CIA still opposed the exchange but President John F. Kennedy approved it.

The exchange
On February 10, 1962, Powers was exchanged, along with U.S. student Frederic Pryor, for Soviet KGB Colonel Rudolf Abel. Due to political differences between the Soviet Union and the German Democratic Republic at the time, Pryor was turned over to American authorities at Checkpoint Charlie, before the exchange of Powers for Abel was allowed to proceed on the Glienicke Bridge.

Powers credited his father with the swap idea. When released, Powers' total time in captivity was 1 year, 9 months, and 10 days.

Aftermath

Powers initially received a cold reception on his return home. He was criticized for not activating his aircraft's self-destruct charge to destroy the camera, photographic film, and related classified parts. He was also criticized for not using a CIA-issued "suicide pill" to kill himself (a coin with shellfish toxin embedded in its grooves, revealed during CIA testimony to the Church Committee in 1975).

He was debriefed extensively by the CIA, Lockheed Corporation, and the Air Force, after which a statement was issued by CIA director John McCone that "Mr. Powers lived up to the terms of his employment and instructions in connection with his mission and in his obligations as an American." On March 6, 1962, he appeared before a Senate Armed Services Select Committee hearing chaired by Senator Richard Russell Jr. which included Senators Prescott Bush, Leverett Saltonstall, Robert Byrd, Margaret Chase Smith, John Stennis, Strom Thurmond, and Barry Goldwater. During the hearing, Senator Saltonstall stated, "I commend you as a courageous, fine young American citizen who lived up to your instructions and who did the best you could under very difficult circumstances." Senator Bush declared, "I am satisfied he has conducted himself in exemplary fashion and in accordance with the highest traditions of service to one's country, and I congratulate him upon his conduct in captivity." Senator Goldwater sent him a handwritten note: "You did a good job for your country."

Divorce and remarriage
Powers sued his wife for divorce on August 14, 1962, claiming she cursed and abused him for no reason. Powers stated that the reasons for the divorce included her infidelity and alcoholism, adding that she constantly threw tantrums and overdosed on pills shortly after his return. He started a relationship with Claudia Edwards "Sue" Downey, whom he had met while working briefly at CIA Headquarters. Downey had a child, Dee, from her previous marriage. They were married on October 26, 1963. Their son Francis Gary Powers Jr. was born on June 5, 1965. The marriage proved to be a very happy one, and Sue worked hard to preserve her husband's legacy after his death.

Praise
During a speech in March 1964, former CIA Director Allen Dulles said of Powers, "He performed his duty in a very dangerous mission and he performed it well, and I think I know more about that than some of his detractors and critics know, and I am glad to say that to him tonight."

Later career
Powers worked for Lockheed as a test pilot from 1962 to 1970, though the CIA paid his salary. In 1970, he wrote the book Operation Overflight with co-author Curt Gentry. Lockheed fired him, because "the book's publication had ruffled some feathers at Langley." Powers then became a traffic reporting airplane pilot for Los Angeles radio station KGIL. After that he became a helicopter news reporter for KNBC television.

Death
Powers was piloting a helicopter for Los Angeles TV station KNBC Channel 4 over the San Fernando Valley on August 1, 1977, when the aircraft crashed, killing him and his cameraman George Spears. They had been recording video following brush fires in Santa Barbara County in the KNBC helicopter and were heading back when the crash occurred.

His Bell 206 JetRanger helicopter ran out of fuel and crashed at the Sepulveda Dam recreational area in Encino, California, several miles short of its intended landing site at Burbank Airport. The National Transportation Safety Board report attributed the probable cause of the crash to pilot error. According to Powers' son, an aviation mechanic had repaired a faulty fuel gauge without informing Powers, who subsequently misread it.

It is surmised that, at the last moment, he noticed children playing in the area and directed the helicopter elsewhere to avoid landing on them. He might have landed safely if not for the last-second deviation, which compromised his autorotative descent. Powers was survived by his wife, children (Claudia Dee and Francis Gary Powers Jr.), and five sisters. He is buried in Arlington National Cemetery as an Air Force veteran.

Honors
Powers received the CIA's Intelligence Star in 1972 after his return from the Soviet Union. Powers was originally scheduled to receive it in 1963 along with other pilots involved in the CIA's U-2 program, but the award was postponed for political reasons. In 1970, Powers published his first—and only—book review, on a work about aerial reconnaissance, Unarmed and Unafraid by Glenn Infield, in the monthly magazine Business & Commercial Aviation. "The subject has great interest to me," he said, in submitting his review.

In 1998, newly declassified information revealed that Powers' mission had been a joint USAF/CIA operation. In 2000, on the 40th anniversary of the U-2 Incident, his family was presented with his posthumously awarded Prisoner of War Medal, Distinguished Flying Cross, and National Defense Service Medal. In addition, CIA Director George Tenet authorized Powers to posthumously receive the CIA's coveted Director's Medal for extreme fidelity and extraordinary courage in the line of duty.

On June 15, 2012, Powers was posthumously awarded the Silver Star medal for "demonstrating 'exceptional loyalty' while enduring harsh interrogation in the Lubyanka Prison in Moscow for almost two years." Air Force Chief of Staff General Norton Schwartz presented the decoration to Powers' grandchildren, Trey Powers, 9, and Lindsey Berry, 29, in a Pentagon ceremony.

Legacy
Powers' son, Francis Gary Powers Jr., founded the Cold War Museum in 1996. Affiliated with the Smithsonian Institution, it was essentially a traveling exhibit until it found a permanent home in 2011 on a former Army communications base outside Washington, D.C in Warrenton, Virginia.

In popular culture

 * In the 1976 telemovie Francis Gary Powers: The True Story of the U-2 Spy Incident, Lee Majors portrayed Powers.
 * In the 1989 song We Didn't Start the Fire by Billy Joel, one of the lines references the U2 based on this event.
 * In 1999, the History Channel aired Mystery of the U2, hosted by Arthur Kent as part of their History Undercover series. The program was produced by Indigo Films.
 * In the 2015 movie Bridge of Spies, dramatizing the negotiations to repatriate Powers, he is portrayed by Austin Stowell, with Tom Hanks starring as negotiator James Donovan.
 * In April 2018, The Aviationist featured an article about the song "Powers Down", a tribute to Powers.

title: Francis Gary Powers