Which of the following best explains a limitation of the map in answering questions about the worlds changing economic landscape?

How the Footprint Works

Ecological Footprint accounting measures the demand on and supply of nature.

On the demand side, the Ecological Footprint adds up all the productive areas for which a population, a person or a product competes. It measures the ecological assets that a given population or product requires to produce the natural resources it consumes (including plant-based food and fiber products, livestock and fish products, timber and other forest products, space for urban infrastructure) and to absorb its waste, especially carbon emissions.

The Ecological Footprint tracks the use of productive surface areas. Typically these areas are: cropland, grazing land, fishing grounds, built-up land, forest area, and carbon demand on land.

On the supply side, a city, state or nation’s biocapacity represents the productivity of its ecological assets (including cropland, grazing land, forest land, fishing grounds, and built-up land). These areas, especially if left unharvested, can also serve to absorb the waste we generate, especially our carbon emissions from burning fossil fuel.

Both the Ecological Footprint and biocapacity are expressed in global hectares—globally comparable, standardized hectares with world average productivity.

Each city, state or nation’s Ecological Footprint can be compared to its biocapacity, or that of the world.

If a population’s Ecological Footprint exceeds the region’s biocapacity, that region runs a biocapacity deficit. Its demand for the goods and services that its land and seas can provide—fruits and vegetables, meat, fish, wood, cotton for clothing, and carbon dioxide absorption—exceeds what the region’s ecosystems can regenerate. In more popular communications, we also call this “an ecological deficit.” A region in ecological deficit meets demand by importing, liquidating its own ecological assets (such as overfishing), and/or emitting carbon dioxide into the atmosphere. If a region’s biocapacity exceeds its Ecological Footprint, it has a biocapacity reserve.

Conceived in 1990 by Mathis Wackernagel and William Rees at the University of British Columbia, the Ecological Footprint launched the broader Footprint movement, including the carbon Footprint, and is now widely used by scientists, businesses, governments, individuals, and institutions working to monitor ecological resource use and advance sustainable development. The most prominent calculations are those produced for countries. We call those the National Footprint and Biocapacity Accounts.

A rich and accessible introduction to the theory and practice of the approach is available in the book Ecological Footprint: Managing Our Biocapacity Budget (2019). The European Commission provides a short summary here. Fuller methodological explanations and applications to national policy are available in a Nature Sustainability paper (2021), an two MDPI papers, one on the national accounts method, and the other one on its implications.

What Is the Gini Index?

The Gini index, or Gini coefficient, measures income distribution across a population. Developed by the Italian statistician Corrado Gini in 1912, it often serves as a gauge of economic inequality, measuring income distribution or, less commonly, wealth distribution among a population.

The coefficient ranges from 0 (or 0%) to 1 (or 100%), with 0 representing perfect equality and 1 representing perfect inequality. Values over 1 are theoretically possible due to negative income or wealth.

Key Takeaways

• The Gini index is a measure of the distribution of income across a population.
• A higher Gini index indicates greater inequality, with high-income individuals receiving much larger percentages of the population's total income.
• Global inequality, as measured by the Gini index, has steadily increased over the past few centuries and spiked during the COVID-19 pandemic.
• Because of data and other limitations, the Gini index may overstate income inequality and can obscure important information about income distribution.

Watch Now: What Is the Gini Index?

Understanding the Gini Index

A country in which every resident has the same income would have an income Gini coefficient of 0. Conversely, a country in which one resident earned all the income, while everyone else earned nothing, would have an income Gini coefficient of 1.

The same analysis can apply to wealth distribution (the "wealth Gini coefficient"), but because wealth is more difficult to measure than income, Gini coefficients usually refer to income and appear simply as the "Gini coefficient" or "Gini index," without specifying that they refer to income. Wealth Gini coefficients tend to be much higher than those for income.

Even in affluent countries, the Gini index measures net income rather than net worth, so the majority of a nation's wealth can still be concentrated in the hands of a small number of people even if income distribution is relatively equal.

The Gini coefficient is an important tool for analyzing income or wealth distribution within a country or region, but it should not be mistaken for an absolute measurement of income or wealth. A high-income country and a low-income one can have the same Gini coefficient, as long as incomes are distributed similarly within each: For instance, Turkey and the U.S. both have income Gini coefficients of around 0.39-0.40, according to the Organisation for Economic Co-operation and Development (OECD), despite Turkey's vastly lower gross domestic product (GDP) per person.

Graphical Representation of the Gini Index

The Gini index is often represented graphically through the Lorenz curve, as depicted below, which shows income (or wealth) distribution by plotting the population percentile by income on the horizontal axis and cumulative income on the vertical axis. The Gini coefficient is equal to the area below the line of perfect equality (0.5 by definition) minus the area below the Lorenz curve, divided by the area below the line of perfect equality. In other words, it is double the area between the Lorenz curve and the line of perfect equality.

The Gini Index Around the World

Global Gini

The Gini coefficient experienced sustained growth during the 19th and 20th centuries. In 1820, the global Gini coefficient stood at 0.50, while in 1980 and 1992, the figure was 0.657.

Source: World Bank

COVID-19 is likely to have a further negative impact on income equality. According to the World Bank, the Gini coefficient has increased about 1.5 points in the five years following major epidemics, such as Ebola and Zika. Economists believe COVID-19 triggered an annual 1.2- to 1.9-percentage-point increase in the Gini coefficient for 2020 and 2021.

Gini Within Countries

Below are the income Gini coefficients of every country for which the CIA World Factbook provides data:

Some of the world's poorest countries have some of the world's highest Gini coefficients, while many of the lowest Gini coefficients are found in wealthier European countries. However, the relationship between income inequality and GDP per capita is not one of perfect negative correlation, and the relationship has varied over time.

Michail Moatsos of Utrecht University and Joery Baten of Tuebingen University show that from 1820 to 1929, inequality rose slightly—then tapered off—as GDP per capita increased. From 1950 to 1970, inequality tended to fall off as GDP per capita rose above a certain threshold. From 1980 to 2000, inequality fell with higher GDP per capita then curved back up sharply.

Limitations of the Gini Index

Though useful for analyzing economic inequality, the Gini coefficient has some shortcomings.

The metric's accuracy is dependent on reliable GDP and income data. Shadow economies and informal economic activity are present in every country. Informal economic activity tends to represent a larger portion of true economic production in developing countries and at the lower end of the income distribution within countries. In both cases, this means that the Gini index of measured incomes will overstate true income inequality. Accurate wealth data is even more difficult to come by due to the popularity of tax havens.

Another flaw is that very different income distributions can result in identical Gini coefficients. Because the Gini attempts to distill a two-dimensional area (the gap between the Lorenz curve and the equality line) down to a single number, it obscures information about the "shape" of inequality. In everyday terms, this would be similar to describing the contents of a photo solely by its length along one edge, or the simple average brightness value of the pixels.

Though using the Lorenz curve as a supplement can provide more information in this respect, it also does not show demographic variations among subgroups within the distribution, such as the distribution of incomes across age, race, or social groups. In that vein, understanding demographics can be important for understanding what a given Gini coefficient represents. For example, a large retired population pushes the Gini higher.

What Country Has the Highest Gini Index?

South Africa, with a Gini coefficient of 63.0, is currently recognized as the country with the highest income inequality. The World Population Review attributes this massive inequality to racial, gender, and geographic discrimination, with white males and urban workers in South Africa earning much better salaries than everyone else.

What Does a Gini Index of 50 Mean?

The Gini index ranges from 0% to 100%, with 0 representing perfect equality and 100 representing perfect inequality. A Gini of 50 marks the halfway point and can generally be perceived as a place where income is not fairly distributed—only 15 countries in the world have a Gini of 50 or more.

Is the U.S. Gini Coefficient High or Low?

The U.S. has a Gini coefficient of 41.1, which is a high reading for such a developed economy. Economists blame rising income inequality in the U.S. on factors such as technological change, globalization, the decline of unions, and the eroding value of the minimum wage.

The Bottom Line

If the gap between rich and poor continues to increase, the evaluation of the income gap can become more important. And the Gini index can provide a great starting point when it comes to measuring that income inequality. Knowing the Gini index numbers is no panacea, but this measure does provide a way to quantify and track the direction in which a society is moving, which may open the door for dialogue and potential solutions.

But keep in mind, there are limitations associated with using this measure. The coefficient is only as reliable as the data used to calculate it and it only provides a single-digit reading, which doesn't take different groups in the sample into account.

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