social inequality in the world essay

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Poverty and Inequality in the World, Essay Example

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Poverty and inequality are two matters at all times influencing one another. Undoubtedly, where there is poverty there is also inequality happening on a social level. These two terms, applied when discussing society in its entirety, are utilized to describe how inequality on an economical level affects social statuses, making room for let us say lucky groups, the ones able to afford almost anything and the unlucky, those who can barely make it from one day to another. Thereof, these two terms describe the cause and effect of the economic system, however complex it might be.

The main actors included in this process are, actually, the people living in the society and, also, the system at work in the society, by means of which people can or cannot get advantage insofar as to make their lives better. The actors included in the inequality process are, therefore, people on the one hand and, on the other hand, the economic system active in a particular society. This is exactly why the matter could not be discussed generally, but applied to each country in part.

The main focus of each scholar is that of identifying the most efficient strategies by means of each poverty to be avoided and inequality disposed of. However, given the complexity of the problem and the variety of variables which influence it, my standpoint is that no general strategy can be found, no strategy which, if applied anywhere, could solve such a sensitive matter. More precisely, distinct solutions should be sought and applied, afterwards, in each country in part. I do not ignore the fact that relevant insights could be derived from one country which could aid solve the problem in another country, but that is not, under no circumstance, enough. In other words, global citizenship philosophy should be understood as the point of departure for the struggle of highlighting the efficient solutions towards eliminating inequality in societies.

Thereof, the main question I wish to bring to debate is that of identifying whether it would be more relevant that a united team of researchers would study a corpus of distinct societies in order to put together a strategy which would help eliminate inequality or that the same team of researchers would study the same country and its society, irrespective of the other insights derived from distinct societies, with the same scope. This question parts from the discussions in ”Globalization. A very short introduction”, by Manferd B. Steger. This made me realize that such a scope implies a numerous of variables to be taken into consideration and, however, contextualization, especially at a time in which globalization is rapidly escalating.

Probably, the most important aspect of such a research consists of the capabilities of the specialists of identifying the exact characteristics of each society in part which would affect, in any way, the rise of inequality. The presupposition stands clear. Each society has characteristics that influence the economic process, some of which are the great historical moments it went through, the collective mentality, the political system, the social intake of the differences between people, from the ways in which one can go from one social status to another until the way in which women are being viewed in comparison to men. Thereof, the question I propose stands relevant from the point of view that the strategy which, for example, would be applicable in a society in which women are expected to be paid far less than men occupying the very same positions would not be efficient in a society in which women are already highly emancipated and are not expected to be stay-at-home mothers for a long period of time.

Steger, B. “Manfred. Globalization: A Very Short Introduction.”

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Essay on Social Inequality

Students are often asked to write an essay on Social Inequality in their schools and colleges. And if you’re also looking for the same, we have created 100-word, 250-word, and 500-word essays on the topic.

Let’s take a look…

100 Words Essay on Social Inequality

Social inequality: a divide in society.

Social inequality refers to the unfair and unjust differences in the way people are treated in a society. It can be based on factors like wealth, power, gender, race, caste, religion, or other characteristics.

Causes of Social Inequality

There are many factors that contribute to social inequality, including:

Economic inequality: The unequal distribution of wealth, income, and resources among different groups of people.
Discrimination: The unfair treatment of people based on their race, gender, caste, religion, or other characteristics.
Lack of opportunity: The unequal access to education, employment, and other opportunities that can help people improve their lives.

Consequences of Social Inequality

Social inequality has many negative consequences, including:

Poverty: Social inequality can lead to poverty, as people who are discriminated against or lack opportunities may have difficulty finding jobs and earning a decent income.
Health problems: Social inequality can also lead to health problems, as people who are poor or discriminated against may not have access to adequate healthcare.
Crime: Social inequality can also lead to crime, as people who are poor or discriminated against may be more likely to turn to crime as a way to survive.

Addressing Social Inequality

There are many things that can be done to address social inequality, including:

Promoting economic equality: Governments can take steps to promote economic equality, such as by raising the minimum wage, providing tax breaks for low-income families, and investing in affordable housing.
Ending discrimination: Governments and individuals can take steps to end discrimination, such as by passing anti-discrimination laws and promoting diversity and inclusion.
Expanding opportunities: Governments and individuals can take steps to expand opportunities for people who are disadvantaged, such as by providing access to education, job training, and healthcare.

By working together, we can create a more just and equitable society for all.

250 Words Essay on Social Inequality

What is social inequality.

Social inequality is when people in a society do not have equal rights, opportunities, or resources. This means some people have more money, better education, or more power than others. It’s like being in a race where some people have to wear heavy shoes, making it unfair.

Types of Social Inequality

There are many types of social inequality. Some people are treated unfairly because of their skin color, which is called racial inequality. Others might face problems because they are women, which is known as gender inequality. Then, there are those who are looked down upon because they come from a poor family, which is economic inequality.

Effects of Social Inequality

Social inequality can make life very hard for some people. For example, if you do not have much money, you might not be able to go to a good school. This can make it hard for you to get a good job when you grow up. It can also make people feel sad or left out because they are treated differently.

What Can We Do?

Everyone can help fight social inequality. We can start by treating everyone the same, no matter what they look like or where they come from. Schools can teach kids about why it’s important to be fair. And, people can work together to help those who do not have as much, like donating to charities or volunteering.

Social inequality is a big problem, but if we all work together, we can make the world a fairer place for everyone.

500 Words Essay on Social Inequality

Social inequality is when people in a society do not have equal rights, opportunities, or resources. Imagine a race where some runners have to wear heavy backpacks while others don’t. The race is unfair because not everyone has the same chance to win. In the same way, in our society, not everyone starts from the same place or has the same chances to succeed.

There are many kinds of social inequality. One major type is economic inequality, which is about the differences in wealth and income. Some people have a lot of money and can buy whatever they want, while others struggle to pay for basic needs like food and a home. Another type is racial inequality, where people are treated differently because of their race. Gender inequality is also common, where men and women are not given the same opportunities or respect.

Social inequality does not just happen; it is caused by many factors. One big cause is the way society’s rules and laws are set up, which can favor some people over others. For example, if a country’s laws make it harder for women to work or own property, this creates gender inequality. Another cause is discrimination, where people are treated unfairly because of things like their race, gender, or religion. Lastly, economic systems can cause inequality when they allow some people to become very rich while others stay poor.

Social inequality can have many bad effects on people and society. People who face inequality might not be able to get good jobs or education, which makes it hard for them to improve their lives. This can lead to poverty and even affect their health. For society, inequality can cause problems like crime and violence, as people who feel treated unfairly might turn to these as a way to express their frustration or to survive.

What Can Be Done?

Fighting social inequality is not easy, but there are things that can be done. Governments can create laws and policies that give everyone equal chances, like making sure all children can go to good schools or making it illegal to pay women less than men for the same work. People can also help by standing up against discrimination and supporting groups that work to make society more fair. Education is key, as understanding the causes and effects of inequality can help us find ways to fix it.

In conclusion, social inequality is a big problem that affects many aspects of life. It’s about not having the same chances because of things like how much money you have, your race, or your gender. It’s caused by unfair laws, discrimination, and economic systems. It can lead to poverty, poor health, and even crime. But by changing laws, fighting discrimination, and educating people, we can work towards a society where everyone has the same opportunities to succeed.

That’s it! I hope the essay helped you.

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21 Social Inequality Examples

Rosa Panades (PhD)

Dr. Panades is a multifaceted sociologist with experience working in a variety of fields, from familiy relations, to teenage pregnancy, housing, women in science or social innvovation. She has worked in international, european and local projects, both in the UK and in Spain. She has an inquisitive and analytical mind and a passion for knowledge, cultural and social issues.

Rosa holds a PhD in Sociology on the topic of young fatherhood from the University of Greenwich, London.

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Chris Drew (PhD)

This article was peer-reviewed and edited by Chris Drew (PhD). The review process on Helpful Professor involves having a PhD level expert fact check, edit, and contribute to articles. Reviewers ensure all content reflects expert academic consensus and is backed up with reference to academic studies. Dr. Drew has published over 20 academic articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education and holds a PhD in Education from ACU.

Social inequality is “the condition where people have unequal access to valued resources, services and positions in society” (Kerbo, 2003, p. 11).

It is broader than just wealth inequality because it also includes factors like discrimination and access to government support.

When social inequality occurs, there is an uneven distribution of resources between individuals or groups, and this happens in almost all societies. These resources and rights go from education, to power, status and so on.

Social inequality is the result of social hierarchy or stratification , with class, gender, race, ethnicity , or sexuality being part of the experience of social inequality. According to theories like the Davis-Moore thesis , it’s also an inevitable feature of society.

Social Inequality Definition

In the field of sociology, unlike economics, social inequality is taken to include differences on many levels: income, resources, power, status, social capital, as well as in levels of social inclusion and exclusion (Warwick-Booth, 2018).

When social inequality occurs, there is an unequal distribution of and unequal access to material and non-material goods:

Material goods could be income, but also things like housing.
Non-material social goods refer to intangible things such as access to social networks or social status .

In this sense, social inequality is a multi-faceted approach to uneven differences in access to resources for different social positions or statuses within a group or society.

Thus, dimensions like gender, sexuality, ethnicity or class all impact on being able to access, or not, social goods and resources as well as opportunities.

Social inequality is important because it has an impact on people’s life chances, in their living conditions, their work opportunities and the overall life outcomes of both individuals and groups (Suter, 2014).

Social Inequality Examples

Wealth inequality: Wealth plays a major role in social perpetuating inequality. People with higher net worth have greater access to resources, can out-bid poorer people for access to limited resources, and can buy access to people in power.
Income inequality: Income inequality functions in a similar way to wealth inequality, but refers to unequal distribution of money in the workforce. For example, the wage differential between CEOs and workers has spiked in recent decades, which has exacerbated social inequalities.
Access to basic education: Access to basic education is unequal when wealthier neighborhoods have better primary schools, or when lack of public transit to schooling acts as a substantial barrier for poorer people.
Access to higher education: Inequal access to education can be a result of factors such as geographical barriers and financial barriers. Without higher education, it is harder to achieve social mobility .
Age inequality : Also known as ageism , this refers to discrimination against people based on their age. For example, it occurs in relation to access to employment for those over the age of 50.
Deprived neighborhoods: Deprived neighborhoods are an example of how it is not only individuals who suffer inequality. Sometimes, whole areas can be affected by the unequal distribution of rights and resources. This happens, for example, when some neighborhoods have restricted access to hospitals and transport.
Housing inequality: Having access to a house, or living in sufficient accommodation, is both a cause and a consequence of social inequality. Living in a social housing, for example, is related to being at the bottom of the social hierarchy.
Racial inequality: Inequality based on race can be a result of systemic and intergenerational racism, a discriminatory attitude by which access to rights has not been distributed equally across people of different races, and which has been passed down through generations of deprivation.
Gender inequality: Inequality based on gender is called sexism, a discriminatory attitude by which women are more likely to be worse off in the equality scales. For example, they tend to earn less than men for the same jobs.
Health access inequality: Inequal access to healthcare is most starkly shown by the rural-urban divide (where rural people often need to travel to cities to receive care) and the class divide, where working-class people often find funding to be a barrier to access to quality care ( see more social determinants of health here ).
Caste systems: Traditional caste societies deny access to jobs based on your ascribed status at birth. Furthermore, they may deny people from marrying one another across castes.
Geographical inequality: Geographical inequality can be within a nation (e.g. the rural-urban divide) as well as globally (e.g. developing vs developed nations).
Citizenship status: People may face limited protections based upon their citizenship. While it’s generally accepted that a tourist in a country shouldn’t access some public services covered by taxation, when non-citizens are denied human rights like access to a lawyer, we might start to consider citizenship status as a dimension of inequality in a society.
Child poverty: Child poverty is a key driver of social inequality. People born into poverty can experience malnutrition, poorer educational results, and lower overall lifetime earnings on average.
Power and status inequality: Access to powerful people is unequally distributed. People who are privileged on the social hierarchy have higher social status and consequently have more access to people in powerful political and corporate positions. There is also inequal power distribution between men and women, as demonstrated by the glass ceiling phenomenon .
LGBT discrimination: Historically, LGBT people have faced discrimination that has affected their ability to do many things heterosexual people can access, including starting and raising a family, and accessing healthcare as spouses.
Intergenerational inequality: This occurs when one generation in society has had greater access to resources than others at similar points in their lives. For example, in the UK and Australia, baby boomers had free higher education, which was denied to future generations who had to pay for it. This affected future generations’ prospects in a way that did not affect baby bookers.
Incarceration rates: Taking a look at incarceration rates versus rates in which different racial groups commit crimes can demonstrate how people of color are more likely to be imprisoned if they are caught committing a crime.
Service inequality: Unequal access to services can be seen across many vectors of society, including the rural-urban divide and rich-poor divide.
Discriminatory laws: Laws that entrench discrimination, such as segregation laws , can be a source of social inequality.
Indigenous inequality: Fist nations groups have long suffered from inequal access to resources in society. One demonstration of this is the lack of clean drinking water in many first nations communities in Canada.

Case Studies

1. social inequality and gender.

Gender is a key dimension of social inequality, as for a variety of reasons, the unfair treatment of people based on their gender still happens in contemporary society.

There are three main areas in which gender inequality can be found: health, education, and the workplace.

For example, in relation to health, although women live longer than men, they have more ill health throughout their lives.

In terms of education, there is still segregation in certain subjects, for example, computing or engineering are still dominated by men. Finally, in the workplace, we find that is called the glass ceiling , which stops women from progressing in their careers.

2. Social inequality and ethnicity

Racism is the expression of social inequality based on a person’s, or a group, race or ethnicity.

It has been shown that people of ethnic minority backgrounds experience higher rates of unemployment, they are more likely to be prosecuted by the criminal justice, and also be victims of crime, live in inadequate housing, have bad mental and physical health or be excluded from education. These are examples of institutional racism .

All of these cause social inequality in the middle and longer term and slims down ethnic minorities’ life chances.

3. Social inequality and health

There is a clear relation between social inequality and health, for multiple reasons.

For example, income determines being able to afford things like gym membership or fresh fruit, which keeps people healthier..

Occupation also has a role in health inequality a life expectancy, for example, teachers live longer than plumbers.

Finally, in countries in which there is no universal health coverage those with higher incomes will have greater access to services, from health promotion, to prevention or treatment.

4. Social inequality and age

Ageism refers to stereotypes (how we think), prejudice (how we feel) and discrimination (how we act) towards others or oneself based on age.

While ageism can be directed towards younger or older people, in terms of inequality, it is in older groups that the focus will be put on. People who are older may experience discrimination in the workplace, for example, in terms of accessing jobs which can lead to higher rates of unemployment.

Furthermore, older people with small pensions have less spending power and thus less access to certain resources, for example, paying for leisure and cultural activities , thus putting them at a disadvantage.

5. Social inequality and income or wealth

While social inequality is not solely based on income or wealth, money, whether from the job one does or from access to family wealth, plays a role in accessing resources.

This greater access to resources mean that some people at a greater advantage than others, for example, in relation to good health and educations. As has been explained, this difference in access to resources is at the heart of social inequality and it impacts on people’s life changes, hence its importance.

Social inequality is a complex subject due to its transversal nature: as it has been pointed out, it is more than just having more or less money. In social inequality there are many factors at play, such as gender, age or ethnicity as well as other aspects like class or neighborhood.

The importance of fighting off social inequality lies in its cumulative nature and in how it determines people’s life chances, sometimes for generations.

Doob, C. B. (2019). Social inequality and social stratification in US society. London: Routledge.

Hurst, C.; Fitz Gibon, H. & Nurse, A. (2016) Social Inequality: Forms, Causes, and Consequences . New York: Routledge

Kerbo, H. R. (2003). Social stratification and inequality. Class conflict in historical, comparative, and global perspective . Boston: McGrawHill.

Thompson, R. (2019). Education, Inequality and Social Class. Expansion and Stratification in Educational Opportunity . New York: Routledge.

Warwick-Booth, L. (2018). Social Inequality . New York: Sage

Wisdom, S., Leavitt, L., & Bice, C. (Eds.). (2019). Handbook of research on social inequality and education . London: IGI Global.

Rosa Panades (PhD) #molongui-disabled-link Manifest Functions in Sociology (10 Examples)
Rosa Panades (PhD) #molongui-disabled-link Latent Functions in Sociology (with 10 Examples)
Rosa Panades (PhD) #molongui-disabled-link 15 Oppression Examples
Rosa Panades (PhD) #molongui-disabled-link 10 Institutional Discrimination Examples

Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 23 Achieved Status Examples
Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 15 Ableism Examples
Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 25 Defense Mechanisms Examples
Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 15 Theory of Planned Behavior Examples

Poverty and Social Inequalities

Categories: Prejudice Social Injustice

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Words: 527 |

Published: Mar 20, 2024

Words: 527 | Page: 1 | 3 min read

Defining poverty and social inequalities, the cycle of poverty and social inequalities, addressing poverty and social inequalities.

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Institution for Social and Policy Studies

Advancing research • shaping policy • developing leaders, when there is so much poverty in the world, why should we also worry about inequality.

Collage of 8 images of Anne Phillips speaking behind a microphone in a classroom

According to the most recent census data, 36.8 million Americans live in poverty , slightly more than 11 percent of the population. Nearly half of the world’s population — about 3.5 billion people — fall below the poverty line for middle-income countries , and 8.5 percent are considered living below the extreme poverty line for low-income countries.

At the same time, inequality has exploded over recent decades . From 1979 to 2020, incomes for the most affluent .01 percent of households in the United States grew 17 times faster than for people earning in the bottom 20 percent. According to the Congressional Budget Office, the richest 1% in 2021 earned almost 139 times as much as the bottom 20%. According to the Federal Reserve, the top 10% of households possess two-thirds of the country’s wealth, defined as total assets less debts. The bottom 10% of households possess 2.5%.

“Poverty is not new,” said Anne Phillips , emeritus professor at the London School of Economics’ Department of Government. “Inequality is not new. These are clearly things we should worry about. But should we worry more about poverty or the inequality?”

Phillips, known for her contributions to political theory, democracy, representation, equality, and feminism, spoke last month at the Institution for Social and Policy Studies (ISPS), part of the Program on Ethics, Politics, and Economics’ (EP&E) Robert H. Litowitz Lecture Series. The series was established to honor a scholar who died while attending Yale Divinity School, continuing to explore his interests in public ethics and policy that cross disciplines and bridge diverse religious traditions and cultures.

“We are tremendously grateful for the opportunity to host these lectures as a fruit of Robert Litowitz’s vision and generous spirit,” said Ana De La O, EP&E director and ISPS faculty fellow. “We are also honored to welcome his sister, Laurie Litowitz, an international artist, visiting us from her home in Mexico.”

Phillips began her lecture with a discussion of American philosopher Harry Frankfurt, who argued that people who care about other people having more than them when they have sufficient resources to live a decent life become trapped in envy and distracted from what really matters.

As a further example of reasons for worrying less about inequality, she cited Shekhar Aiyar, a scholar who has held senior positions in the International Monetary Fund and recently wrote about how India and China have raised more than a billion people out of poverty.

“From a global perspective, the dominant public discourse about liberalism’s malign impact on economic inequality is alarmingly blinkered,” Aiyar said in an essay published earlier this year. “The sharp rise of within-country inequality in rich countries needs urgent remedy but applies to a set of countries that constitutes only about one-fifth of the global population.”

Phillips noted further that the extreme concentration of wealth, particularly in the top .01%, can create a sense of helplessness and can make the idea of equalizing incomes or wealth seem like a “ludicrous pipe dream.”

She argued nonetheless that the reduction in absolute poverty does not negate the importance of addressing rising economic inequality within countries. Indeed, she said, the very fact that absolute poverty is declining while economic inequality is rising sharply provides a strong case for focusing on inequality, rather than dismissing it as a secondary concern.

“Focusing only on poverty encourages the delusion, particularly characteristic of Euro-American thinking, that we already do have — and had for decades and centuries — equality in our fundamental status,” she said. “We tell a story about ourselves in which ideas of all humans being born equal supposedly form the basis of our societies and democracies.”

Phillips argued that inequality is not just about disparities in income or wealth but also power dynamics.

“Inequality is a social relation, and it’s about social classes, property, and power,” she said. “It’s not just that some people have more income, wealth — things— than others. But that what they have gives them power over others. So, the question is not then whether wealth can be prevented from converting itself into power or superior social status. Wealth is power. It is power over those who lack it.”

Phillips warned that material inequality threatens the foundation of democratic societies, arguing that focusing solely on poverty alleviation can create a dynamic of “patrons and victims rather than equals.” Instead, she advocated for engaging with people as agents of change, emphasizing the need to address both poverty and inequality to foster a more just and equitable society.

Phillips fielded questions from an engaged audience of students and faculty. She noted the difficulties in addressing inequality within a capitalist society and stressed the need to maintain vigilance and address both poverty and inequality through comprehensive, systemic changes. Her 2021 book, “Unconditioned Equals,” explores why equality should not depend on a common understanding of “human nature” but must be extended to everyone.

“Giving up on the challenges of inequality is a dangerous move,” Phillips said. “Perhaps especially if you think that the thing that really matters is simply ensuring our political and social status as equals.”

Watch a video of the complete lecture.

Rising inequality: A major issue of our time

Subscribe to global connection, zia qureshi zia qureshi senior fellow - global economy and development.

May 16, 2023

Income and wealth inequality has risen in many countries in recent decades. Rising inequality and related disparities and anxieties have been stoking social discontent and are a major driver of the increased political polarization and populist nationalism that are so evident today. An increasingly unequal society can weaken trust in public institutions and undermine democratic governance. Mounting global disparities can imperil geopolitical stability. Rising inequality has emerged as an important topic of political debate and a major public policy concern.

High and rising inequality

Current inequality levels are high. Contemporary global inequalities are close to the peak levels observed in the early 20th century, at the end of the prewar era (variously described as the Belle Époque or the Gilded Age) that saw sharp increases in global inequality.

Over the past four decades, there has been a broad trend of rising income inequality across countries. Income inequality has risen in most advanced economies and major emerging economies, which together account for about two-thirds of the world’s population and 85 percent of global GDP (Figure 1). The increase has been particularly large in the United States, among advanced economies, and in China, India, and Russia, among major emerging economies.

Figure 1. Inequality has risen in most advanced and major emerging economies Richest 10% income share, 1980-2020

Source: Author, using data from World Inequality Database . Note: Pre-tax national income. Some data points are extrapolated.

Beyond these groups of countries, the trend in the developing world at large has been more mixed, but many countries have seen increases in inequality. In regions such as Latin America, the Middle East and North Africa, and sub-Saharan Africa, income inequality levels on average have been relatively more stable, but inequality was already at high levels in these regions—the highest in the world.

Wealth inequality within countries is typically much higher than income inequality. It has followed a rising trend across countries since around 1980, similar to income inequality. Higher wealth inequality feeds higher future income inequality through capital income and inheritance.

The increase in inequality has been especially marked at the top end of the income distribution, with the income share of the top 10 percent (and even more so that of the top 1 percent) rising sharply in many countries. This was so particularly up to the global financial crisis of 2008-09. Those in low- and middle-income groups have suffered a loss of income share, with those in the bottom 50 percent typically experiencing larger losses of income share. These trends in inequality have been associated with an erosion of the middle class and a decline in intergenerational mobility , especially in advanced economies experiencing larger increases in inequality and a greater polarization in income distribution.

While within-country inequality has been rising, inequality between countries (reflecting per capita income differences) has been falling in recent decades. Faster-growing emerging economies, especially the large ones such as China and India, have been narrowing the income gap with advanced economies. Global inequality—the sum of within-country and between-country inequality—has declined somewhat since around 2000, with the fall in between-country inequality more than offsetting the rise in within-country inequality. As within-country inequality has been rising, it now accounts for a much larger part of global inequality (about two-thirds in 2020, up from less than half in 1980). Looking ahead, how within-country inequality evolves will matter even more for global inequality.

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The interplay between the evolution of within-country inequality and between-country inequality, coupled with the differential growth performance of emerging and advanced economies, in recent decades presents an interesting picture of middle-class dynamics at the global level (as depicted by the well-known “ elephant curve ” of the incidence of global economic growth). It shows, for the period since 1980, a rising middle class in the emerging world and a squeezed middle class in rich countries. It also shows an increasing concentration of income at the very top of the income distribution globally.

Drivers of rising inequality

Shifting economic paradigms are altering distributional dynamics. Transformative technological change, led by digital technologies, has been reshaping markets, business models, and the nature of work in ways that can increase inequality within economies. While the specifics differ across countries, this has been happening broadly through three channels: more unequal distribution of labor income with rising wage inequality as technology shifts labor demand from routine low- to middle-level skills to new, higher-level skills; shift of income from labor to capital with increasing automation and a decoupling of wages from firm profitability; and more unequal distribution of capital income with rising market power and economic rents enjoyed by dominant firms in increasingly concentrated and winner-takes-all markets. These dynamics are more evident in advanced economies but could increasingly impact developing economies as the new technologies favoring capital and higher-level skills make deeper inroads there.

Globalization (international trade, offshoring) also has contributed to rising inequality within economies, especially in advanced economies by negatively affecting wages and jobs of lower-skilled workers in tradable sectors. These sectors increasingly extend beyond manufacturing as digital globalization expands the range of activities, including services, deliverable across borders.

In emerging economies, technology is reshaping how international trade affects national inequality. The new technologies, born in advanced economies, are shifting manufacturing and global value chains toward higher capital and skill intensity. Leading manufacturing firms located in emerging economies and engaged in exporting are adopting these technologies in order to be able to compete, diminishing employment generation and wage growth prospects for less-skilled workers from this higher-productivity segment of industry in economies whose factor endowments would warrant less capital- and skill-intensive technologies—and thus limiting the potential of international trade to reduce inequality within these economies by boosting demand for their more abundant factor endowment (less-skilled workers). Meanwhile, smaller firms that absorb most such workers in these economies remain engaged in low-productivity activities, many in the informal economy and in petty service sectors.

Globalization has been a force in recent decades for reducing inequality between economies by expanding export opportunities for emerging economies and spurring their economic growth. But globalization’s role in promoting international economic convergence faces new challenges as technological change alters production processes and trade patterns (more on this below).

Other broad trends in recent decades affecting the distribution of income and wealth include changes in institutional settings such as economic deregulation, increasing financialization of economies coupled with a high concentration of financial income and wealth, and erosion of labor market institutions such as minimum wage laws and collective bargaining. Moreover, the redistributive role of the state has been weakening with declining tax progressivity and with transfer programs facing the pressure of tighter fiscal constraints.

Role of public policy

Large and persistent increases in inequality within economies are not an inevitable consequence of forces such as technological change and globalization. Much depends on how public policy responds to the new dynamics that these forces generate. In the midst of these common forces of change, the rise in inequality has been uneven across countries. The difference lies largely in countries’ institutional and policy settings and how they have responded. In general, looking across countries, public policy has been behind the curve. It has been slow to rise to the new challenges to promote more inclusive outcomes from economic change.

Public policy to reduce inequality is often viewed narrowly in terms of redistribution―taxes and transfers. This is indeed an important element, especially in view of the erosion of the state’s redistributive role in recent decades. But there is a much broader policy agenda of “predistribution” that can make the growth process itself more inclusive and produce better market outcomes—by promoting wider access to new opportunities for firms and workers and enhancing their capabilities to adjust as market dynamics shift.

This latter agenda of reforms spans competition policy and regulatory frameworks to keep markets competitive and inclusive in the digital age; innovation ecosystems and technology policies to put innovation to work for broader groups of people; digital infrastructure and literacy to reduce the digital divide; education and (re)training programs to upskill and reskill workers while addressing inequalities in access to these programs; and labor market policies and social protection systems to enable workers to obtain a fair share of economic returns and to support them in times of transition. In many of these reform areas, the new dynamics that economies are facing call for fresh thinking and significant policy overhaul.

Outlook for inequality

Absent more responsive policies to combat inequality, the current high levels of inequality are likely to persist or even rise further. Artificial intelligence and related new waves of digital technologies and automation could increase inequality further within countries. Even as new technologies increase productivity and produce greater economic affluence, and new jobs and tasks emerge to replace those displaced and so prevent large technological unemployment, inequality could reach much higher levels. The economic fallout of the COVID-19 pandemic has reinforced some of the inequality-increasing dynamics. Also, a high and increasing concentration of wealth can exacerbate income inequality in a mutually reinforcing cycle.

Technological change also poses new challenges to global economic convergence that has reduced inequality between countries in the past couple of decades. Faster growth in emerging economies led by export of manufactures has depended greatly on their comparative advantage in labor-intensive manufacturing based on large populations of low-skill, low-wage workers. This source of comparative advantage increasingly will erode as automation of low-skill work expands. Emerging economies face the challenge of recalibrating their growth models as technology disrupts traditional pathways to growth and development.

Emerging economies’ growth prospects also face other headwinds, including the scarring effects of the pandemic and global supply chain disruptions exacerbated by the war in Ukraine and an unsettled global geopolitical environment, which would hit the more trade-dependent economies harder. If growth in emerging economies falters, the decline in between-country inequality will slow, which could stall or even reverse the modest decline in global inequality observed since about 2000 if within-country inequality continues to mount.

Climate change is another factor that could worsen inequality within and between countries. Low-income groups and countries are more vulnerable to the impacts of climate change and have less capacity to cope with them.

Income and wealth inequality is elevated. In the absence of policies to counter recent trends, inequality could rise to still higher levels. High and rising inequality entails adverse economic, social, and political consequences. Policymakers must pay more attention to the changing distributional dynamics in the digital age and harness the forces of change for more inclusive prosperity. History tells us that large and unabated rises in inequality can end up badly.

How can the world address inequality? 7 experts explain

Leave no one behind. Image: Priscilla Du Preez/Unsplash

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The COVID-19 pandemic has exacerbated socioeconomic inequalities.
Mitigating inequality requires a mix of bottom-up and top-down changes that address the underlying social and economic systems.
Seven experts shine a light on creating a future that leaves no one behind.

The COVID-19 pandemic has exacerbated socioeconomic inequalities within and across countries. The policy responses designed to mitigate them in the form of either relief and recovery packages or welfare protections have mostly proved to be short-term fixes. In the long-term, however, the distributional consequences of the pandemic between and within countries, as in during previous pandemics and recessions, are bound to widen inequality.

According to the World Inequality Database 2020 update, Latin America and the Middle East stand as the world’s most unequal regions, with the top 10% of the income distribution capturing 54% and 56% of the average national income respectively. Despite Gulf countries (Bahrain, Kuwait, Oman, Qatar, UAE, Saudi Arabia) having among the highest GDP per capita levels, they have also marked extreme inequality levels, with little variation since the 1990s. However, the starkest change has been the rise in concentration of incomes in the US, with the top 10% witnessing an increase from 34% to 45% of the national income between 1980 and 2019.

The data are an indicator that countries with strong investments in public services, social protection, and labour market policies have the lowest inequality levels, with Europe standing as the most equal of all regions driven by its redistribution and progressive taxation, seen in the Commitment to Reducing Inequality Index .

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How covid deepened gender inequality - this week's radio davos podcast, 5 shocking facts about inequality, according to oxfam’s latest report, imf head: how governments can prevent widening inequality.

Looking at global inequality beyond purely from an income distribution lens, it is critical to take into consideration multidimensional factors such as social mobility, gender equality, livelihood infrastructure, technology access, the voice of civil society, privacy, social and environmental protections, progressive tax laws and labour rights when examining the how societies perform on reducing inequality and serving public interest.

The COVID crisis has forced us to reimagine our shared futures as the world attempts to rebuild. From proposals relating to basic income and collecting the tax deficit to the more emerging debate on inheritance for all , the asymmetric impact of the pandemic and divergent recovery beckon a universal call for us to build back broader .

Mitigating inequality will now demand a mix of bottom-up and top-down changes that recognize the social and economic systems aggravating inequality are a matter of choice. Where do we go from here?

We asked seven global experts from the World Economic Forum Expert Network to provide their perspective on how we can build a better future where we leave no one behind. Here’s what they said.

‘It is particularly crucial to increase the minimum wage'

Tak Niinami, Chief Executive Officer, Suntory Holdings and Senior Economic Advisor to the Prime Minister of Japan

The pandemic has made it apparent that Japan also faces the issue of inequality. A widening in the gap must be prevented by all means as it would bring social unrest and social divide. In the short-term, given Japan’s comparatively low wages, it is particularly crucial to increase the minimum wage and thoroughly implement an “equal pay for equal work” policy to bridge the gap between regular and non-regular workers.

The acceleration of redistribution of wealth is also imperative. Taxation on assets and capital gains should be increased so that this resource can be utilized to fund NPOs (nonprofit organizations) that can take measures against issues such as poverty and isolation.

Furthermore, in the long-term, I believe education is key in mitigating inequality. The widening education gap can spill over from generation to generation, creating a chain effect that must be avoided. Technology can prove to be a solution if it can be applied to ensure equal opportunities, enabling high-quality education to anyone and anywhere, no matter where you live.

‘ Well-funded and quality universal healthcare must be the legacy of the pandemic ’

Deepak Xavier, Head of Inequality Advocacy and Campaigns, Oxfam International

The world risks the greatest rise of inequality since records began , and today it is inequality that perpetuates COVID-19, which is ending so many lives. The grotesque inequality in accessing healthcare is proving fatal. To be without a hospital bed or medical oxygen in the face of a pandemic is frightening enough. However, for most of the world that has long been the case. Pre-pandemic 10,000 people were dying daily due to lack of access to healthcare.

Progress on universal healthcare is achievable – as countries such as Costa Rica have shown . Implementing a fair and progressive tax system to avoid concentration of wealth to the top 10% is one way to provide a fiscal boost. A 0.5% extra tax on the wealth of the richest 1% alone could raise $418bn each year which could be redistributed towards resilient healthcare systems. Issuing US$1 trillion of IMF’s Special Drawing Rights (SDRs) global reserve asset would dramatically increase the funds available to countries – for example, the Ethiopian government will have access to an additional $630 million — enough to increase its health spending by 45%.

Well-funded and quality universal healthcare must be the legacy of the pandemic: to save lives and better tackle future pandemics.

'Support our people outside of the "nine to five".'

Leslie Parker, Partner and Member of the Board of Directors, Kearney

It used to be that there was very little crossover between our work and personal lives. Since COVID, that has changed. The new work-from-home model has given us intimate access to our colleagues’ personal lives – and surfaced a whole new set of inequalities.

We see family members juggling caring responsibilities with the demands of their jobs. We see people who live alone, who might not physically encounter another human being that week. We see housemates sitting three to a table, trying to work at the same time. And we see laptops propped on kitchen counters, stacks of boxes and pairs of knees, as people search for an elusive quiet space or change of scenery.

The ability to work from home is an incredibly privileged position for many. But with working patterns and norms changed beyond all recognition, we need policies that take on these and other new inequalities – including lack of choice over working location – into account. It’s not enough to dish out some grants for home office equipment. What about some let-up from home schooling or eldercare, or help to tackle loneliness? Why not help our teams create better connections with one another that can offer more than the virtual happy hour and more time behind a laptop? We need to go beyond one-dimensional Diversity, Equity, Inclusion programmes and policies, and really support our people outside of the ‘nine to five’.

At Kearney we have taken a first step by asking employees around the world to tell us what would improve their lives and how we can help as leaders. We are already seeing wellbeing, both physical and mental, as a major theme. We introduced more mental and physical health programmes with free classes available to employees, redesigned our future work model strategies to allow for flexibility of working hours and location (no longer adopting five-days-a-week office model), offered an option to go to co-working spaces to employees whose current situation is not supportive of their work or mental health and improved coaching and mentoring guidelines in the absence of in-person onboarding and support.

‘ Promote more transparent and accountable systems ’

Ibrahima Hathie, Distinguished Fellow, Initiative Prospective Agricole et Rurale (IPAR), Senegal and Southern Voice network member

Sustainable Development Goal 10 of the 2030 Agenda seeks to “reduce inequality within and among countries”. Yet, the goal’s targets and indicators focus on horizontal inequality and exclusion of the vulnerable and marginalized population from opportunities. The United Nations’ overarching principle of “ Leave No One Behind ” reflects this orientation and calls for a transformative agenda. However, it fails to address deep-rooted social, economic, and political systemic problems that preserve and often amplify vertical inequalities.

A path to achieving this must seek to reduce the political influence of elites in the formulation and implementation of public policies. It would promote more transparent and accountable systems. Tackling inequalities between countries is also imperative if we are to face the consequences these have on the most vulnerable in developing countries. Addressing overlapping disadvantages through a comprehensive development strategy can be an excellent response to horizontal inequalities. Vertical inequalities require more: progressive economic institutions with pro-poor taxation, investment, and trade.

In Senegal, for example , the government should choose and invest heavily in food value chains, funding of research of these value chains, training of family farmers, agricultural entrepreneurs, technicians, and engineers and introduce multisector governance to ensure smooth coordination to achieve the goals set out by the Malabo Declaration . This would lead to increased industrial development, improved health and nutrition, and decent and abundant jobs for young people and women.

‘The basic fundamentals of knowledge creation and collaboration must be addressed’

Marie McAuliffe, Head, Migration Research Division, International Organization for Migration

In addition to measures on improving social protection of migrant workers, reducing costs of international remittance transfers, and bolstering migrants' rights throughout the migration process, the fundamentals of knowledge creation and collaboration must be addressed. Affected communities impacted by increasing inequality must be part of processes aimed at formulating effective responses.

Developing country experts and research institutions must be able to meaningfully participate in researching, proposing, designing, and evaluating solutions according to their priorities and needs. A much greater focus on leveraging opportunities to undertake participatory and collaborative research with (and for) marginalized populations is needed. Only then can the programmatic and policy responses designed to reduce inequality globally be truly sustainable.

We advocated this approach as part of consultations on the UN Research Roadmap on COVID-19, which makes a strong case for participatory research to support long-term global transformations. In 2017, IOM invited the world’s leading migration researchers from around the world to join in sharing their expertise and knowledge in support of the 2018 global compact on safe, orderly and regular migration. As a consequence, the resolution on the Global Compact for Safe, Orderly and Regular Migration was adopted by the United Nations General Assembly in 2018.”

‘Increase public investments in the formal and informal care economies’

Susan Ferguson, Women Representative for India, UN Women

The COVID-19 crisis in India has impacted millions, not only those suffering from the disease, but also those who care for them. As always, women have taken on the heavy burden of caring for the sick and finding ways to meet their family’s basic needs. A recent Oxfam report shows that Indian women and girls put in 3.26 billion hours of unpaid care work every day — a contribution of at least ₹19 trillion a year to the Indian economy.

Yet in India, duties performed at home have historically not been considered “work,” because of unequal gender and caste norms. And now, with after the second wave of COVID-19, the combination of illness, unpaid care, economic slowdown and lack of access to financing for female entrepreneurs means that many women are unable to return to work.

If these trends aren’t reversed, they will have a devastating impact on the economy and further exacerbate gender inequality. For this generation of women to emerge relatively unscathed from this pandemic and be able to return to the workforce, we must invest seriously in education and livelihoods of women and girls in India. UN Women’s Second Chance Education programme is a prime example of how we can and must focus on women’s livelihoods right now, before the equality gaps widen even more. Another way to mitigate the inequality crisis would be to increase public investments in the formal and informal care economies and tap into the job creation potential of the care economy.

In the end, it will come down to changing attitudes. Whether it’s at home, in the office or in the fields, we must stop taking women’s work for granted.

Don’t use the pandemic as a justification to discriminate and exclude

Melody Patry, Advocacy Director, Access Now

From Singapore to Jamaica, governments are scrambling for solutions to help the world return to a pre-virus normality. Vaccine certificates — or “passports” — that record and authenticate vaccination statuses, however, are short-term fixes that potentially pose long-term risks to human rights. These fast-tracked stopgaps are a blueprint for exclusion and discrimination, and present serious and disproportionate threats to the privacy and security of millions of people.

COVID-19 and its reverberations already impact our most vulnerable and underserved individuals and communities — from limited health care, to increased economic instability — we cannot allow techno-solutionism to exacerbate the divide further.

Global leaders, and their industry counterparts, must stop, recalibrate, and ensure technology plays a positive, cornerstone role in pandemic recovery. As laid out by U.N. Special Procedures on the eve of RightsCon 2021 , "we need to act together to embrace the fast-pace expansion of digital space and technological solutions that are safe, inclusive and rights-based."

World Economic Forum Strategic Intelligence , in partnership with the Institute for Global Prosperity , University College London (UCL) launched the transformation map on Inequality .

The experts cited in this article are part of the World Economic Forum Expert Network .

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Inequality – Bridging the Divide

Today, wherever people live, they don’t have to look far to confront inequalities. Inequality in its various forms is an issue that will define our time. Confronting inequalities has moved to the forefront of many global policy debates as a consensus has emerged that all should enjoy equal access to opportunity. ‘ Leave no one behind ’ serves as the rallying cry of the 2030 Agenda for Sustainable Development.

Overall, since the 1990s total global inequality (inequality across all individuals in the world) declined for the first time since the 1820s. Reinforcing this trend, we have mostly seen income inequality between countries decline. Yet income inequality within countries has risen, this is the form of inequality people feel on a daily basis.

Inequalities are not only driven and measured by income, but are determined by other factors - gender, age, origin, ethnicity, disability, sexual orientation, class, and religion. These factors determine inequalities of opportunity which continue to persist, within and between countries. In some parts of the world, these divides are becoming more pronounced. Meanwhile, gaps in newer areas, such as access to online and mobile technologies , are emerging. The result is a complex mix of internal and external challenges that will continue to grow over the next twenty-five years.

Income inequality between countries has improved

For the most part we have seen income inequality between countries improve in the last 25 years , meaning average incomes in developing countries are increasing at a faster rate. This can be accredited to strong economic growth in China and other emerging economies in Asia. However, the gap between countries is still considerable. For example, the average income of people living in North America is 16 times higher than that of people in sub-Saharan Africa.

Income inequality within countries is getting worse

Income inequality between countries has improved, yet income inequality within countries has become worse. Today, 71 percent of the world’s population live in countries where inequality has grown. This is especially important because inequalities within countries are the inequalities people feel day to day, month to month, year to year. This is how people stack up and compare themselves with their neighbours, family members, and society. Since 1990, income inequality has increased in most developed countries and in some middle-income countries, including China and India.

While inequality has gone up in the majority of countries over the past three decades, it has fallen in a few. In Latin America and the Caribbean, there has been a considerable decline, although levels remain high. In Africa and Asia, trends have been more varied, with greater similarities between emerging economies or landlocked developing countries, and between rural or urban areas, than within regions.

The very top

Despite progress in some regions, income and wealth are increasingly concentrated at the top. An Oxfam report shows that in the 10 years since the financial crisis, the number of billionaires has nearly doubled, and the fortunes of the world’s super-rich have reached record levels. In 2018, the 26 richest people in the world held as much wealth as half of the global population (the 3.8 billion poorest people), down from 43 people the year before.

This matters because rapid rises in incomes at the top are driving and exacerbating within country income inequality. From 1990 to 2015, the share of income going to the top 1 per cent of the global population increased in 46 out of 57 countries with data. Meanwhile, in more than half of the 92 countries with data, the bottom 40 per cent receive less than 25 per cent of overall income.

In your society, who you are, matters

There are also inequalities within communities – and even families. Up to 30 per cent of income inequality is due to inequality within households. When it comes to women and girls, progress is uneven. In many ways gender inequalities have been shrinking – the gender pay gap , for instance, has decreased for some women in certain occupations over the last couple of decades. However, at the same time, women and girls put in 12.5 billion hours of unpaid care work each and every day — a contribution to the global economy of at least $10.8 trillion a year, more than three times the size of the global tech industry.

Groups such as indigenous peoples, migrants and refugees, and ethnic and other minorities continue to suffer from discrimination, marginalisation, and lack of legal rights. This is pervasive across developing and developed countries alike and is not tied to income. For example, social protection has been significantly extended globally, yet persons with disabilities are up to five times more likely than average to incur catastrophic health expenditures. Additionally, a UNDESA report found that at the current rate of progress observed from the 1990s to the 2010s, it will take more than four decades to close the stunting gap between ethnic groups.

More than income

The measurements and impacts of inequality go far beyond income and purchasing power. Inequalities of opportunity affect a person’s life expectancy and access to basic services such as healthcare, education, water, and sanitation. They can curtail a person’s human rights, through discrimination, abuse and lack of access to justice. In 2018, we saw the world’s 12th consecutive year of decline in global freedom, with 71 countries suffering net declines in political and civil liberties.

High levels of inequality of opportunity discourage skills accumulation, choke economic and social mobility, and human development and, consequently, depress economic growth. It also entrenches uncertainty, vulnerability and insecurity, undermines trust in institutions and government, increases social discord and tensions and trigger violence and conflicts. There are growing evidence that high level of income and wealth inequality is propelling the rise of nativism and extreme forms of nationalism.

In addition, the evolution of issues such as climate change , technology , and urbanisation raise urgent policy challenges. For example, climate change is exacerbating environmental degradation, increasing the frequency and intensity of extreme weather events, and by no means impacting people uniformly. If climate change continues unaddressed it will increase inequality within countries and may even reverse current progress in reducing inequality between countries. Meanwhile, technology can be a great equaliser – by enhancing connectivity, financial inclusion, access to trade and public services, for instance – but those yet to be connected may experience further marginalisation as a result, especially as progress is slowing , even reversing, among some constituencies. With a global trend toward urbanisation, cities are becoming a growing site for inequalities. They find high levels of wealth and modern infrastructure coexist with pockets of severe deprivation, often side by side. This makes gaping and increasing levels of inequality all the more glaring within cities.

Tackling inequalities

Rising inequality is not the only way forward. For example, between 2010 and 2016, the incomes of the poorest 40 percent of the population grew faster than those of the entire population in 60 out of 94 countries with data. This shows inequality is neither inevitable nor irreversible.

There is a clear need to pursue inclusive, equitable, and sustainable growth, ensuring a balance among economic, social, and environmental dimensions of sustainable development. However, inequality takes many forms and varies significantly across countries. While Goal 10 of the Sustainable Development Goals (SDG 10) and its targets provide a framework, the fight against inequality must be rooted in country-contexts, economic imperatives, and political realities. There is no scope for a one-size fits all approach, and national policies and institutions matter.

FOR MORE INFORMATION

Sustainable Development Goals

UNDESA | World Social Report 2020 Inequality in a Rapidly Changing World

UNDESA | Inequality

UNDP | Human Development Report 2019

UNDP | Global Multidimensional Poverty Index

UN University | World Income Inequality Database

World Bank | Poverty and Shared Prosperity 2016

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The Sociology of Social Inequality

Key Concepts
Major Sociologists
News & Issues
Research, Samples, and Statistics
Recommended Reading
Archaeology

Social inequality results from a society organized by hierarchies of class, race, and gender that unequally distributes access to resources and rights.

It can manifest in a variety of ways, like income and wealth inequality, unequal access to education and cultural resources, and differential treatment by the police and judicial system, among others. Social inequality goes hand in hand with social stratification .

Social Inequality Overview

Social inequality is characterized by the existence of unequal opportunities and rewards for different social positions or statuses within a group or society. It contains structured and recurrent patterns of unequal distributions of goods, wealth, opportunities, rewards, and punishments.

Racism , for example, is understood to be a phenomenon whereby access to rights and resources is unfairly distributed across racial lines. In the context of the United States, people of color typically experience racism, which benefits white people by conferring on them white privilege , which allows them greater access to rights and resources than other Americans.

There are two main ways to measure social inequality:

Inequality of conditions
Inequality of opportunities

Inequality of conditions refers to the unequal distribution of income, wealth, and material goods. Housing, for example, is inequality of conditions with the homeless and those living in housing projects sitting at the bottom of the hierarchy while those living in multi-million dollar mansions sit at the top.

Another example is at the level of whole communities, where some are poor, unstable, and plagued by violence, while others are invested in by businesses and government so that they thrive and provide safe, secure, and happy conditions for their inhabitants.

Inequality of opportunities refers to the unequal distribution of life chances across individuals. This is reflected in measures such as level of education, health status, and treatment by the criminal justice system.

For example, studies have shown that college and university professors are more likely to ignore emails from women and people of color than they are to ignore those from white men, which privileges the educational outcomes of white men by channeling a biased amount of mentoring and educational resources to them.

Discrimination of an individual, community, and institutional levels is a major part of the process of reproducing social inequalities of race, class, gender , and sexuality. For example, women are systematically paid less than men for doing the same work.

2 Main Social Inequality Theories

There are two main views of social inequality within sociology. One view aligns with the functionalist theory, and the other aligns with conflict theory.

Functionalist theorists believe that inequality is inevitable and desirable and plays an important function in society. Important positions in society require more training and thus should receive more rewards. Social inequality and social stratification, according to this view, lead to a meritocracy based on ability.
Conflict theorists, on the other hand, view inequality as resulting from groups with power dominating less powerful groups. They believe that social inequality prevents and hinders societal progress as those in power repress the powerless people to maintain the status quo. In today's world, this work of domination is achieved primarily through the power of ideology, our thoughts, values, beliefs, worldviews, norms, and expectations, through a process known as cultural hegemony .

How Social Inequality Is Studied

Sociologically, social inequality can be studied as a social problem that encompasses three dimensions: structural conditions, ideological supports, and social reforms.

Structural conditions include things that can be objectively measured and that contribute to social inequality. Sociologists study how things like educational attainment, wealth, poverty, occupations, and power lead to social inequality between individuals and groups of people.

Ideological supports include ideas and assumptions that support the social inequality present in a society. Sociologists examine how things such as formal laws, public policies, and dominant values both lead to social inequality, and help sustain it. For example, consider this discussion of the role that words and the ideas attached to them play in this process.

Social reforms are things such as organized resistance, protest groups, and social movements. Sociologists study how these social reforms help shape or change social inequality that exists in a society, as well as their origins, impact, and long-term effects.

Today, social media plays a large role in social reform campaigns and was harnessed in 2014 by British actress Emma Watson , on behalf of the United Nations, to launch a campaign for gender equality called #HeForShe.

Milkman, Katherine L., et al. “ What Happens before? A Field Experiment Exploring How Pay and Representation Differentially Shape Bias on the Pathway into Organizations. ” Journal of Applied Psychology , vol. 100, no. 6, 2015, pp. 1678–1712., 2015, doi:10.1037/apl0000022

“ Highlights of Women's Earnings in 2017 .” U.S. Bureau of Labor Statistics , Aug. 2018.

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The great wealth wave

The tide has turned – evidence shows ordinary citizens in the western world are now richer and more equal than ever before.

by Daniel Waldenström + BIO

Recent decades have seen private wealth multiply around the Western world, making us richer than ever before. A hasty glance at the soaring number of billionaires – some doubling as international celebrities – prompts the question: are we also living in a time of unparalleled wealth inequality? Influential scholars have argued that indeed we are. Their narrative of a new gilded age paints wealth as an instrument of power and inequality. The 19th-century era with low taxes and minimal market regulation allowed for unchecked capital accumulation and then, in the 20th century, the two world wars and progressive taxation policies diminished the fortunes of the wealthy and reduced wealth gaps. Since 1980, the orthodoxy continues, a wave of market-friendly policies reversed this equalising historical trend, boosting capital values and sending wealth inequality back towards historic highs.

The trouble with the powerful new orthodoxy that tries to explain the history of wealth is that it doesn’t fully square with reality. New research studies, and more careful inspection of the previous historical data, paint a picture where the main catalysts for wealth equalisation are neither the devastations of war nor progressive tax regimes. War and progressive taxation have had influence, but they cannot count as the main forces that led to wealth inequality falling dramatically over the past century. The real influences are instead the expansion from below of asset ownership among everyday citizens, constituted by the rise of homeownership and pension savings. This popular ownership movement was made possible by institutional changes, most important democracy, and followed suit by educational reforms and labour laws, and the technological advancements lifting everyone’s income. As a result, workers became more productive and better paid, which allowed them to get mortgages to purchase their own homes; homeownership rates soared in the West from the middle of the century. As standards of living improved, life spans increased so that people started saving for retirement, accumulating another important popular asset.

Today, the populations of Europe and the United States are substantially richer in terms of real purchasing-power wealth than ever before. We define wealth as the value of all assets, such as homes, bank deposits, stocks and pension funds, less all debts, mainly mortgages. When counting wealth among all adults, data show that its value has increased more than threefold since 1980, and nearly 10 times over the past century. Since much of this wealth growth has occurred in the types of assets that ordinary people hold – homes and pension savings – wealth has also become more equally distributed over time. Wealth inequality has decreased dramatically over the past century and, despite the recent years’ emergence of super-rich entrepreneurs, wealth concentration has remained at its historically low levels in Europe and has increased mainly in the US.

Among scholars in economics and economic history, a new narrative is just beginning to emerge, one that accentuates this massive rise of middle-class ownership and its implications for society’s total capital stock and its distribution. Capitalism, it seems, did not result in boundless inequality, even after the liberalisations of the 1980s and corporate growth in the globalised era. The key to progress, measured as a combination of wealth growth and falling or sustained inequality, has been political and institutional change that enabled citizens to become educated, better paid, and to amass wealth through housing and pension savings.

I n his book Capital in the Twenty-First Century (2014), Thomas Piketty examined the long-run evolution of capital and wealth inequality since industrialisation in a few Western economies. The book quickly received wide acclaim among both academics and policymakers, and it even became a worldwide bestseller.

Piketty’s narrative outlined wealth accumulation and concentration as following a U-shaped pattern over the past century. At the time of the outbreak of the First World War, wealth levels and inequality peaked as a result of an unregulated capitalism, low taxation or democratic influence. During the 20th century, wartime capital destruction and postwar progressive taxes slashed wealth among the rich and equalised ownership. Since 1980, however, goes Piketty’s narrative, neoliberal policies have boosted capital values and wealth inequality towards historic levels.

Immediately after publication, Capital generated fierce debate among economists, focused primarily on the book’s theoretical underpinnings. For example, Piketty had sketched a couple of ‘fundamental laws’ of capitalism, defining the economic importance of aggregate wealth. The first law stated that the share of capital income in total income (the other share coming from labour) is a function of how much capital there is in the economy and its rate of return to capital owners. The second law stated that the amount of capital in the economy, measured as its share in total output, is determined by the balance between saving to accumulate capital and income growth. While these laws were actually fairly uncontroversial relationships, almost definitions, they laid out a mechanistic view of inequality trends that attracted considerable attention and scrutiny among Piketty’s fellow theoretical economists.

My work arrives at a striking new conclusion for the history of wealth and inequality in the West

However, what the academic debate cared less about was the empirical side of the analysis. Almost nothing was said about the historical data and the empirical conclusions underlying the claims about U-shaped patterns and main driving forces. The void in critical scrutiny exposed a widespread disinterest among mainstream economists in history and the fine-grained aspects of source materials, measurement and institutional contexts.

In recent years, a new strand of historical wealth inequality research has emerged from universities around the world. It offers a more nuanced empirical picture, including new data and revised evidence, pointing to different results and interpretations. In Piketty’s book, most of the analysis centred on the historical experiences of France, and then there was additional evidence presented for the United Kingdom and Germany (together making up Europe) and the US. Newer work reexamines and extends the historical wealth accumulation and inequality trends. Some of these contributions also revise the earlier data series, such as those analysing Germany and the UK. Other studies expand the empirical base by incorporating previously unexplored countries, such as Spain and Sweden. A number of ongoing research projects into the history of wealth distribution examine more new countries, including Switzerland, the Netherlands and Canada. Their findings will soon be added to this historical wealth database.

My work with new data, published in my book Richer and More Equal (2024), arrives at a new conclusion for the history of wealth and inequality in the West. The new results are striking. Data show that we are both richer and more equal today than we were in the past. An accumulation of housing wealth and pension savings among workers in the middle classes emerges as the main factor producing greater equality: today, three-fourths of all private assets are either homes or long-term pension and insurance savings.

U nderlying the change in personal wealth formation over the 20th century are a number of political and economic developments. The democratisation of the Western world began with the extension of universal suffrage during the 1910s. This movement initiated a process of reforming the educational system, to extend basic schooling to the population and facilitating access to higher education. New labour laws improved working life by restricting the working hours per day, allowing unions to be active. Better training and nicer workplaces raised worker productivity and earnings, creating opportunity for working- and middle-class households to purchase their own homes. The improved living standards also led to longer lives. Between the 1940s and today, life expectancy at birth increased by almost 20 years in Western countries, most of which were spent in retirement. Pension systems started evolving during the postwar era, both as public-sector unfunded systems based on promises about a future income, and as private-sector funded systems where individual pension funds were accumulated as part of people’s long-term saving.

At the core of the new findings are three empirical observations.

The first is that the populations in Western countries are richer today than ever before in history. By rich, again, I mean having a high level of average wealth in the adult population. Why this measure of riches captures relevant aspects of welfare is because higher wealth permits a lot of good things in life. It allows for higher consumption, more savings and larger investment for future prosperity. It also promises better insurance against unforeseen events. Figure 1 below illustrates the growth in the average real per-capita wealth in a selection of Western countries over the past 130 years. It is dramatic. During the first half of the past century, the average wealth in the Western population hovered at a stable level. Since the end of the Second World War, asset values started to increase, doubling the level in only a couple of decades. From 1950 to 2020, average wealth in the West increased sevenfold.

Over the past 130 years, a monumental shift in wealth composition has taken place

A fact to notice specifically is how wealth has grown each single postwar decade up to the present day. For several reasons, this consistency of growth is a marvel. It affirms the robustness of the result: we are wealthier today than in history, and this fact does not depend on the choice of start or end date but holds regardless of the time period considered. The steady increase in wealth is not confined to investment-driven growth in Europe’s early postwar decades. Neither does it hinge on the market liberalisations of the 1980s and ’90s. However, it is notable how the lifting of regulations and the historically high taxes since the 1980s are indeed associated with the highest pace of value-creation that the Western world has ever experienced.

Line graph showing the rise in average wealth (in thousand 2022 US dollars) from 1900 to 2022, with a sharp increase post-1950.

Figure 1: rising real average wealth in the Western world. Note: wealth is expressed in real terms, meaning that it is adjusted for the rise in consumer prices and thus expresses change in purchasing power. The line is an unweighted mean of the average wealth in the adult population in six countries (France, Germany, Spain, Sweden, the UK and the US) expressed in constant 2022 US dollars. Source: Waldenström (2024, Chapter 2)

A second fact coming out of the historical evidence is that wealth in the aggregate has changed in its appearance. The composition of assets people hold tells us about the economic structure of society and what functions wealth plays in the population. For example, whether most assets are tied to the agricultural economy or to industrial activities signifies the degree of economic modernisation in the historical analysis. The importance of ordinary people’s assets in the aggregate signifies the degree to which workers take part in the value-creation processes of the market economy. Figure 2 below displays the division across asset classes in the aggregate portfolio since the end of the 19th century. It is evident that, over the past 130 years, a monumental shift in wealth composition has taken place. A century ago, wealth comprised primarily agricultural land and industrial capital. Today, the majority of personal wealth is tied up in housing and pension funds.

A graph showing the distribution of elite vs people’s wealth from 1900 to 2010, with people’s wealth rising over time.

Figure 2: the aggregate composition of assets: from elite wealth to people’s wealth . Note: unweighted average of six countries (France, Germany, Spain, Sweden, the UK and the US). Source: Waldenström (2024, Chapter 3)

The transformation of wealth composition has strong distributional implications. Individual ownership data, often called microdata, show how ownership structures across wealth distribution bear a pattern of who owns what. Historically, the rich held agricultural estates and shares in industrial corporations. This is especially true over the long term of history, but it remains so now too. In contrast, the working population acquires wealth in their homes and long-term savings in pension funds. Homeownership rates today range from 50 to 80 per cent. Labor-force participation rates are even higher. In substance, this tells us that housing and work-related pension funds are assets that dominate the ownership of ordinary people in the lower and middle classes, which in turn links the relative aggregate importance of housing and pension funds for wealth inequality.

L ooking closer at the relationship between the share of a country’s citizens who own their homes and the level of wealth inequality, the distributional pattern becomes evident. Figure 3 below plots countries according to their homeownership rates and wealth inequality, as measured by the common Gini coefficient that ranges from 0 (no inequality) to 1 (one individual owns everything), using recent wealth and homeownership surveys. Countries with higher levels of homeownership have lower wealth inequality. The straight line in the figure has a negative slope, which suggests that raising the homeownership rate by 10 points leads to an expected reduction in wealth inequality by 0.04 Gini points. As an example, France has a lower homeownership than Italy ( 60 per cent compared with 70 per cent), and a higher wealth inequality (0.67 versus Italy’s 0.61).

Scatter plot showing the relationship between wealth inequality (Gini index) and homeownership rates for various countries with a red trend line.

Figure 3: homeownership and wealth inequality in Europe and the US. Source: Waldenström (2024, Chapter 6)

The historical shift in the nature of wealth, from being elite-centric to more democratic, can thus be expected to have profound implications for the distribution of wealth. Figure 4 below presents the most recent data from European countries and the US. They reveal in graphical form how wealth inequality has decreased substantially over the past century. The wealthiest percentile once held around 60 per cent of all wealth. The share ranged from 50 per cent of wealth in the US and Germany to 70 per cent in the UK.

Most wealth today is in homes and pensions, assets predominantly of low- and middle-wealth households

Since the first half of the 20th century, the tide has turned. A great wealth equalisation took place throughout the Western world. From the 1920s to the 1970s, wealth concentration fell steadily. In the 1970s, wealth equalisation stopped, but then Europe and the US follow separate paths. In Europe, top wealth shares stabilise at historically low levels, perhaps with a slight increasing tendency. As of 2010, the richest 1 per cent in society holds a share of total wealth at around 20 per cent in Europe. That is roughly one-third of its share of national wealth from a century earlier. Countries like the UK, the Netherlands, Italy and Finland have top percentile shares of around 16-18 per cent. A bit higher are countries like Spain, Denmark, Norway and Sweden with top shares at around 21-24 per cent. Germany has an even higher share, around 27 per cent, and Switzerland’s richest percentile group owns about 30 per cent of all wealth.

This stability of post-1970 top wealth shares may seem contradictory when contrasted with the large increases in aggregate wealth values over recent decades. However, it is consistent with most of the asset ownership patterns documented above, with most of wealth today being in housing and pensions, assets predominantly held by low- and middle-wealth households.

The US wealth concentration experience is somewhat different. Wealth inequality in the beginning of the 20th century was somewhat lower in the US than in most European countries, perhaps reflecting being a younger nation with less established elite structures. The equalisation trend also happened in the US, but it was less pronounced than in Europe. Today, US wealth concentration is currently much higher than in Europe. This situation, as the figure below shows, is the result of several years of steady increase. In historical perspective, however, even the current US level of wealth inequality is lower than it was before the Second World War, and it pales in comparison with the extreme levels of wealth concentration that the people of Europe experienced 100 years ago.

Line graph titled ‘The Great Wealth Equalization over the Twentieth Century’ showing the top 1% wealth share in six countries from 1900 to 2010.

Figure 4: the great wealth equalisation over the 20th century. Source: Waldenström (2024, Chapter 5)

H ow can we account for these historical trends showing a steady growth in average household wealth and, at the same time, wealth inequality falling to historically low levels, where it has remained in Europe but has risen lately in the US? One approach is to break down the top wealth shares into the accumulation of wealth in the top and bottom groups of the distribution. In other words, we decompose the change in top wealth shares by documenting the changes in absolute wealth holdings in the numerator and denominator of the top wealth-share ratio. Figure 5 below shows these numbers, and they are striking.

During no historical time period during the past century did the wealth amounts of the rich fall on average. The falling wealth concentration from 1910 to 1980 was instead the result of wealth accumulating faster in the middle classes than in the top. Since 1950, wealth holdings have actually grown in the entire population. Between 1950 and 1980, it grew faster among the lower groups in the wealth distribution, explaining the continued equalisation. After 1980, wealth has instead grown faster in the top percentile than in the lower classes, which accounts for the halt of the long equalisation trend and a slight upward trend in the top wealth share, driven by the US development, whereas the European countries remained at its historically low levels.

Bar chart showing average yearly changes from 1910–2010 in the 1% wealth share, middle class wealth, and rich people’s wealth.

Figure 5: Western wealth growth: the middle class vs the rich. The graph shows a six-country average (France, Germany, Spain, Sweden, the UK, the US) of the average annual growth rate of real (inflation-adjusted) net wealth per adult individual in the top 1 per cent and the lower 90 per cent of the wealth distribution during three time periods. Source: Waldenström (2024, Chapter 6)

Looking at the specific factors that could account for these trends in wealth growth and wealth inequality, there are some that match the evidence better than others. According to the orthodox narrative, the main explanation was the shocks to capital during the world wars and postwar capital taxes, all of which are believed to have created equality through lowering the top of the wealth distribution. In this telling, the physical capital destruction in wars reduced the fortunes of the rich, and the immediate postwar hikes in capital taxes and market regulations, such as price controls and capital market restrictions, prevented the entrepreneurs from rebuilding their wealth.

Wealth and inheritance taxes reached almost confiscatory levels in the early 1970s

However, the thesis has some issues. One is that the evidence shows little difference between belligerent and non-belligerent countries. During both wars, the wealth share of the top 1 per cent fell equally in belligerent countries like France and the UK as in non-belligerent Sweden. Including the immediate postwar years, which were heavily influenced by wartime turbulence, does not change this pattern. Germany’s data from the wars is less clear, but it appears that the country experienced larger losses than others, reducing top wealth shares. Spain, which stayed out of both world wars but fought a civil war in the 1930s, saw the wealth share of the richest 1 per cent remain virtually unchanged between 1936 and 1939, according to preliminary estimates. Looking at the US, top wealth shares fell during both wars.

Analysing instead the changes in absolute wealth held by the rich and by the rest reinforces the conclusion that wars were not a devastating moment for capital owners. In fact, the fortunes of the elite did not shrink significantly, except in France during the First World War and seemingly in Germany during both wars. In other cases, the capital values of the rich remained almost constant, and the wealth equalisation observed can be attributed to growing ownership among groups below the top tier.

Progressive tax policies after the Second World War offer another potential explanation for the wealth-equalisation trend. Capital taxation increased rapidly between the 1950s and the 1980s in most Western countries. Wealth and inheritance taxes reached almost confiscatory levels in the early 1970s, and this coincided with stagnating business activities, few startups, slowed economic growth, and an exodus of prominent entrepreneurs from high- to low-tax countries. Few studies have been able to analyse systematically the extent to which these taxes prevented the rise of new large fortunes, but studies of later periods suggest that there are good grounds to believe they did.

A general problem for the factors above – which focus on shocks to the capital of the rich and thus lowering the top of wealth distribution as the primus motor behind the great wealth equalisation of the 20th century – is that the evidence presented in Figure 5 above shows that it was instead the lifting of the bottom of the distribution that accounted for the equalisation. Let us therefore shift focus and examine the two main channels through which this happened: the accumulation of homeownership and saving for retirement.

At the turn of the 20th century, owning a decent home and saving for retirement were luxuries enjoyed by only a select few – maybe a couple of tens of millions in Western countries. Today, the once-elusive dreams of home ownership and pensions have become a reality for several hundreds of millions of people. Homeownership rates went from 20-40 per cent in the first half of the former century to 50-80 per cent in the modern era. Retirement savings also increased in the postwar period, reflecting the longer life spans that came with the general improvement of living standards. Funded pensions and other insurance savings comprised 5-10 per cent of household portfolios around 1950, but this share increased to 20-40 per cent in the 2000s.

The most crucial equalisation resulted from expanded wealth ownership among ordinary citizens

History demonstrates that the significant wealth equalisation over the past century was primarily driven by a massive increase in homeownership and retirement savings. But what initiated this accumulation of assets by households? The most comprehensive evidence highlights the role of political changes and economic developments that explicitly included new groups in the productive market economy. Firstly, the 1910s and ’20s witnessed a broad wave of political democratisation, extending universal suffrage to the Western world. Following this regime shift, a series of reforms transformed the economic reality for the masses. Educational attainment was expanded, and higher education became accessible to broader segments of society. New labour laws improved workers’ rights, making workplaces safer and reducing working hours. These changes enhanced workers’ productivity and real incomes. Simultaneously, the financial system evolved by offering better services to this new constituency of potential customers, including cheaper loans, savings plans, mutual funds and other financial services.

Thus, the primary drivers behind the great wealth equalisation of the 20th century were not wars or the redistributive effects of capital taxation. While these factors had some impact, the most crucial equalisation resulted from expanded wealth ownership among ordinary citizens, particularly through homeownership and pension savings, and the institutional shifts that enabled the accumulation of these assets.

A general lesson from history is that wealth accumulation is a positive, welfare-enhancing force in free-market economies. It is closely linked to the growth of successful businesses, which leads to new jobs, higher incomes and more tax revenue for the public sector. Various historical, social and economic factors have contributed to the rise of wealth accumulation in the middle class, with homeownership and pension savings being the primary ones.

As a closing remark, it should be recognised that the story of wealth equalisation is not one of unmitigated success. There are still significant disparities in wealth within and among nations, generating instability and injustice. Over the past years, wealth concentration has increased in some countries, most notably in the US. The extent to which this is due to productive entrepreneurship generating products, jobs, incomes and taxes, or to forces that exclude groups from acquiring personal wealth causing tensions and erosive developments in society, is a question that needs to be studied more. However, at this point it is still vital to acknowledge the progress toward greater equality that has been made in our past and understand how it has happened. Only then can we be in a stronger position to lay the foundation for further advancements in our quest for a more just and prosperous world.

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Social Inequality in the United States Essay

Introduction, inequality in america today.

Social inequality refers to the difference in the quality of life experienced by different people in the same community, usually between the rich and poor. Continued experience with this inequality leads to the establishment of class structures or social stratification. America is a prime example of such a society. Indeed, it is not hard to see that there are people who have so much wealth and receive big incomes, whereas others have too little wealth and receive close-to-non-income.

Is the U.S. truly the land of equality?

Despite the example mentioned above, it would be erroneous to classify America as a truly unequal society. This is because it has been in the American tradition to reduce the gap between its rich and poor. Indeed, American society provides equal opportunities for members of different structures to increase their wealth so they can all be better off. This scenario makes America a true land of quality; which is achieved through the provision of an enabling environment. As a result, poor people in America have a higher chance of climbing the class ladder than their counterparts in other parts of the world (The Economist, 2006).

The reason, the American society has been concentrating on increasing its economic productivity as a way of helping its poor escape poverty. Contrary other countries, including the rich ones in Europe, have concentrated on taking wealth from the rich through higher taxation as a way of helping their poor. Also, it is noticeable that American poor have been getting into better lives than their counterparts in other parts of the world; the rich have been getting richer. On the other hand, the rich in other parts of the world have seen their wealth rise slightly remain stagnant whereas the poor see their plights stay the same. This is despite the efforts made by respective governments to reduce the gap between the two groups.

Recent reports indicate that national wealth going to the richest one percent increased from eight percent in 1980 to sixteen percent in 2004, whereas the percentage of national wealth going to the poor one percent increased by a slimmer margin (NPR, 2007). This has been taken by many people to mean that America’s wealthy have been taking the entire national income home, whereas the poorer are getting even more destitute. But this is an utter exaggeration because it can easily be established that America’s poor have been experiencing better lives at a higher rate than their European counterparts; this is indicated by fact of increased home and motor vehicle ownership, education attainment, and the overall quality of life (NPR, 2007). The rising gap between the rich and poor in America is making many people claim that American inequality is increasing rapidly. However, critics are ignoring the fact the productivity of American society has resulted in rising living standards for all citizens.

The United States, therefore, serves as a society that is unequal but is applying the necessary measures to ensure that the gap between the rich and poor is bleached through methods that will leave all groups better-off. This method is none other than rooting for economic growth that provides opportunities to all in society. Other countries in the world, especially those in Europe have some lessons to learn from America, failure of which will lead to exacerbation of their inequality crisis.

The Economist (2006). America Inequality . Web.

Berliner, U. (2007). Haves and Have-Nots . Web.

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Social Class and Income Inequality in the United States: Ownership, Authority, and Personal Income Distribution from 1980 to 2010

Geoffrey t wodtke.

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Author Contact Information Geoffrey T. Wodtke, Department of Sociology, University of Toronto, 725 Spadina Avenue, Toronto, ON M5S 2J4, Canada. [email protected]

This study outlines a theory of social class based on workplace ownership and authority relations, and it investigates the link between social class and growth in personal income inequality since the 1980s. Inequality trends are governed by changes in between-class income differences, changes in the relative size of different classes, and changes in within-class income dispersion. Data from the General Social Survey are used to investigate each of these changes in turn and to evaluate their impact on growth in inequality at the population level. Results indicate that between-class income differences grew by about 60 percent since the 1980s and that the relative size of different classes remained fairly stable. A formal decomposition analysis indicates that changes in the relative size of different social classes had a small dampening effect and that growth in between-class income differences had a large inflationary effect on trends in personal income inequality.

Keywords: social class, income inequality, ownership, authority, time-series analysis

The distribution of personal income in the U.S. has become substantially more unequal since the early 1980s, reversing a general trend of declining inequality that dated back to the 1930s. During the 1980s and early 1990s, incomes in the lower half of the distribution stagnated and then declined, while incomes at the top of the distribution increased. During the late 1990s and 2000s, incomes in the lower part of the distribution ceased declining but did not rebound from the losses of previous decades, while top incomes continued their ascent ( McCall and Percheski 2010 ; Morris and Western 1999 ; Piketty and Saez 2003 ).

An individual's position within the ownership and authority structure of an economic organization is a central determinant of personal income ( Dahrendorf 1959 ; Marx 1978 ; Proudhon 2011 ; Wright 1979 , 1985 ). At a simple level, there are four distinct groups defined by their position within workplace ownership and authority relations: proprietors, who own the means of production and control the activities of others; managers, who do not own the means of production but do control the activities of others; workers, who control neither the means of production nor the activities of others; and independent producers, who own and operate small firms by themselves. These groups are referred to as social classes, and they are thought to possess antagonistic interests and to frequently engage in conflict with one another ( Wright 1979 ; Wright and Perrone 1977 ). Social classes are linked to the distribution of personal income through supply and demand for different factors of production, economic rents that emerge from market distortions and incentive problems, and the balance of intergroup bargaining power ( Marx 1976 ; Proudhon 2011 ; Wright 1979 , 1985 , 1997 ).

Despite the centrality of social classes in theories of personal income distribution, they have not played an important role in empirical attempts to explain the recent growth in income inequality. Prior studies have instead focused on the effects of disaggregate occupations ( Mouw and Kalleberg 2010 ; Weeden et al. 2007 ), skill-biased technical change and increasing returns to education ( Autor, Levy, and Murnane 2003 ), institutional change and its impact on low-wage workers ( Card, Lemieux, and Riddell 2004 ; DiNardo, Fortin, and Lemieux 1996 ), and demographic shifts ( Borjas 1994 ; Easterlin 1980 ). No definitive explanation for changes in the distribution of personal income has emerged from this extensive volume of research, and prior models of distributional trends leave considerable room for improvement ( McCall and Percheski 2010 ; Morris and Western 1999 ).

Among the few recent studies related to social class and income inequality are several that investigate changes in the functional, rather than personal, distribution of income and find that the labor share declined relative to the capital share since the early 1980s ( Kristal 2010 , 2013 ; Lin and Tomaskovic-Devey 2013 ; Piketty 2014 ). 1 In addition, several other recent studies provide evidence of an association between social class and rising personal income inequality. For example, research on executive compensation reveals a pattern of strong earnings growth for upper management ( Frydman and Jenter 2010 ; Goldstein 2012 ); recent work on inequality of capital ownership suggests that it is rising ( Piketty 2014 ); and research on economic elites indicates that earnings from financial investments have become an increasingly important source of income for this group over the past several decades ( Nau 2013 ; Volscho and Kelly 2012 ).

While these studies suggest an important relationship between social class and changes in the distribution of personal income, they do not link a well-defined social class typology to growth in personal income inequality nor do they provide a precise accounting of how changes in factor shares, capital concentration, or executive compensation contributed to growth in personal income inequality at the population level. These various trends may correspond, but a significant impact for changes in social class inequality on patterns of personal income distribution cannot simply be assumed. Rather, the link between social classes and growing personal income inequality must be subjected to rigorous empirical investigation.

Several other studies have directly linked growth in personal income inequality to class typologies defined in terms of large occupational groups with similar skill requirements, job tasks, and career trajectories ( Morgan and Cha 2007 ; Morgan and Tang 2007 ; Weeden et al. 2007 ). But social class divisions based on exclusionary relations of production and occupational class divisions based on the technical division of labor are distinct forms of stratification, and the occupational class typologies used in prior research have only a tangential link to workplace ownership and authority ( Kalleberg and Griffin 1980 ). The few empirical studies of personal income distribution that explicitly model the returns to ownership and authority rely exclusively on cross-sectional data that predate the recent increase in inequality ( Halaby and Weakliem 1993 ; Kalleberg and Griffin 1980 ; Robinson and Kelley 1979 ; Wright 1979 ; Wright and Perrone 1977 ). As a result, previous research provides little information about the link between social classes and growth in personal income inequality since the early 1980s.

Beyond being largely ignored in empirical research on trends in personal income inequality, the concept of social class has also recently come under attack as a number of social scientists increasingly question its relevance to contemporary patterns of social stratification ( Clark and Lipset 1991 ; Kingston 2000 ; Pakulski and Waters 1996 ). According to post-class theory, the link between social class and patterns of inequality has weakened over time—that is, while historically important, social class divisions are no longer significant determinants of material inequalities in post-industrial society. Although the strong claims of post-class theorists have provoked spirited rebuttals ( Hout, Brooks, and Manza 1993 ; Wright 1996 ), neither side of this debate provides an empirical assessment of the relationship between social class and the distribution of personal income over time.

This study contends that a class-analytic theory based on workplace ownership and authority relations offers an improved basis for explaining growth in personal income inequality since the 1980s. Growth in personal income inequality is governed by (1) changes in between-class income differences, (2) compositional changes in the relative size of social classes, and (3) changes in residual, or within-class, income dispersion. This study investigates each of these trends in turn and provides a formal decomposition that evaluates their relative impact on growth in personal income inequality at the population level. In addition, it evaluates whether accounting for social class divisions based on ownership and authority improves the fit of models based on human capital characteristics, aggregate occupational classes, and dissaggregate occupational classes. It also uses multivariate decomposition methods to evaluate the relative impact of human capital, occupational, and social class differences on growth in personal income inequality. Results from the General Social Survey (GSS) indicate that social class differences are essential for understanding contemporary trends in the distribution of personal income. More specifically, social class models capture important distributional changes with large effects on population-level trends in income inequality that are obscured in alternative models based on human capital characteristics and occupations.

This study makes several contributions to theory and research on social class and income inequality. First, it outlines a simple class-analytic framework for the analysis of long-term changes in personal income distribution. Second, it tests several key implications of this framework using nationally representative time-series data and provides population-based estimates of changes in social class structure and social class inequality since the 1980s. Third, it extends previous research on the functional distribution of income by examining social class differences in the personal distribution of income and by directly linking these differences to growth in personal income inequality. Finally, this study extends prior research on skill-biased technical change and shifts in the occupational structure by comparing the proposed class-analytic framework with these alternative explanations for growth in personal income inequality.

OWNERSHIP, AUTHORITY, AND SOCIAL CLASS

The term “class” is perhaps the most disputed and confused concept in the social sciences ( Wright 1979 ). Descriptive conceptions of class use categories like “the rich,” “the poor,” or “the one percent” to describe an individual's location within a distribution of some valued resource (e.g., Piketty 2014 ). Occupational conceptions of class focus on an individual's position within the technical division labor and its effects on their attitudes, behavior, and access to valued resources (e.g., Featherman and Hauser 1978 ; Weeden and Grusky 2005 ). Social, or relational, conceptions of class focus on how relationships between individuals at the site of production shape the distribution of valued resources, influence economic interests, and promote intergroup conflict (e.g., Dahrendorf 1959 ; Wright 1985 ). To distinguish between these different conceptions of class, I use the term “occupational class” to refer to positions within the technical division of labor and the term “social class” to refer to positions defined in terms of workplace social relations.

This study adopts a conception of social class based on workplace ownership and authority relations. Ownership refers to control over the physical means of production, and authority refers to control over other individuals involved in the production process. Social classes are defined as conflict groups with objectively antagonistic interests that emerge from their position within workplace ownership and authority relations. At a high level of abstraction, social classes are composed of proprietors, managers, workers, and independent producers. Proprietors own the means of production and control the activities of workers. Managers do not own the means of production, but they do control the activities of workers. Workers lack control over the means of production and over the activities of others within the production process, and they labor under the direction of proprietors and managers. Independent producers control the means of production within a self-operated enterprise but do not control the activities of others.

This social class typology is informed by several approaches to class analysis within the conflict theoretical framework (e.g., Dahrendorf 1959 ; Marx 1976 , 1978 ; Wright 1979 , 1985 , 1997 ). 2 Marx (1976) , for example, held that social class divisions are based on differences in property ownership and that exploitation, defined as the appropriation of workers’ surplus labor by property owners, polarizes class interests and provokes conflict between them. Dahrendorf (1959) , by contrast, viewed differences in authority as the defining feature of class structure and argued that domination, or the control over others’ behavior by those in positions of authority, is the mechanism driving social class conflict. Similarly, Wright (1979 , 1985 , 1997 ) developed several social class models based on differences in ownership and authority, among other factors, such as skills, and argued that class conflict is rooted in exploitation, now redefined as a process in which some classes, by virtue of their exclusionary control over different resources, appropriate part of the social surplus produced through the efforts of others.

The theoretical framework guiding this analysis builds on these prior approaches, as well as others (e.g., Roemer 1982 ; Screpanti 2003 ; Tomaskovic-Devey 2014 ), by defining exploitation and domination—the conditions that give rise to antagonistic interests and thus promote conflict between social classes—in counterfactual terms. Specifically, exploitation and domination are defined in terms of counterfactual comparisons between feasible alternative enterprises. An alternative enterprise is feasible when it can be realized without changing technologies or resource endowments but merely by changing the way a firm is socially organized. Exploitation, then, is said to exist in a firm with unequal property and authority relations if democratizing these social relations would increase the material welfare of workers and decrease the material welfare of proprietors and managers. Domination is similarly defined in counterfactual terms, except the outcome of interest is not material welfare but rather the scope for self-determination. Specifically, domination is said to exist in a firm with unequal property and authority relations if democratizing these relations would increase the self-determination of workers and decrease the self-determination of proprietors and managers. Under these conditions, the interests of different social classes are polarized. Proprietors and managers have an objective interest in maintaining the unequal social relations from which they benefit, while workers have an objective interest in challenging the social relations from which they suffer. Independent producers, who operate small enterprises by themselves, do not have interests that objectively conflict with workers, proprietors, or managers.

Although many theorists in the class-analytic tradition (e.g., Marx 1978 ; Wright 1979 , 1985 ) assume that the mere existence of unequal ownership and authority relations leads to exploitation and domination, the counterfactual approach highlights the contingent nature of these phenomena: a democratic transformation of workplace ownership and authority relations need not give rise to the pattern of effects on material welfare and self-determination described previously. For example, worker participation in management may introduce inexperienced personnel to the decision-making process, which could harm productivity and thereby decrease, rather than increase, the material welfare of workers. In addition, self-determination may not be appreciably enhanced among workers if supplanting hierarchical with horizontal management requires high levels of peer monitoring, supervision, and control to sustain comparable levels of productivity. Finally, because incentives to innovate, save, and invest are sensitive to the strength of property rights, an economy with widespread proliferation of democratic firms may grow at a slower rate than an economy based exclusively on private ownership of firms, possibly leading to lower, rather than higher, levels of material welfare for workers over the long term. In other words, the level and growth rate of economic output is endogenous to the social relations of production.

The presence or absence of exploitation and domination is therefore an empirical question, the answer to which depends on extant social class inequalities and the sensitivity of these inequalities to changes in workplace social relations. Research comparing individuals in conventional versus democratically organized firms is rather limited and plagued by selection problems, but there is at least some empirical evidence suggesting that exploitation and domination are fairly common conditions. Economic models of utility maximizing agents in a competitive market economy imply that the earnings of members in a worker-owned and managed cooperative firm would exceed the earnings of workers in a capitalist firm where those who supply the firm's capital and manage production operations enjoy the residual returns ( Craig and Pencavel 1992 , 1995 ). Consistent with these models, empirical research suggests that cooperative members tend to be slightly more productive and to have higher levels of compensation, job security, and job satisfaction than their counterparts in capitalist firms ( Bartlett et al. 1992 ; Blasi, Conte, and Kruse 1996 ; Burdin and Dean 2009 ; Craig and Pencavel 1992 , 1995 ; Levine and Tyson 1990 ; Kruse and Blasi 1995 ; Kruse, Freeman, and Blasi 2010 ). Another implication of these models is that, other factors being equal, owners and managers in capitalist firms would have lower levels of material welfare if their enterprises were reorganized and operated as cooperatives.

Nevertheless, the counterfactual approach suggests that exploitation and domination are likely contingent conditions that vary across time, space, and firms. Moreover, even when exploitation and domination are definitively present in a firm, the process by which the objectively antagonistic interests linked to the presence of these conditions are translated into overt intergroup conflict is itself contingent and variable. This process likely depends on the severity of exploitation and domination in a given actor's firm; the severity of exploitation and domination in other firms across the economy; the accuracy with which social actors perceive the severity of exploitation and domination both in their own firm and across other firms; and the value that individuals place on enhancing their material welfare and self-determination. These contingencies imply, for example, that overt social class conflict is more likely when exploitation and domination are both severe and widespread across firms; when these conditions are accurately perceived by the individuals involved; and when these individuals highly value material welfare and self-determination. In contrast, social class conflict is less likely when exploitation and domination are not severe or are relatively infrequent conditions across firms, making horizontal moves to non-exploitative and non-oppressive firms a conflict mitigating possibility; when individuals fail to perceive the presence of severe and widespread exploitation and domination; or when individuals place less value on material welfare and self-determination.

The counterfactual approach also clarifies the importance of gradational differences among social classes. Specifically, gradational differences in ownership and authority are thought to moderate the effects of workplace democratization on material welfare and self-determination. For example, the negative effects of democratizing workplace ownership and authority relations for proprietors and managers would not be evenly distributed among members of these groups. They would likely be much more pronounced for large proprietors and high-level managers than for small proprietors and low-level managers simply because those at the top of the ownership and authority structure have more to lose. Thus, the level of antagonism between workers, managers, and proprietors should be an increasing function of gradational differences in ownership and authority. These gradational differences among social classes are termed class strata.

Finally, the counterfactual approach underscores the conceptual distinction between social classes (i.e., conflict groups with objectively antagonistic interests based on their position within workplace social relations) and other production-based groups defined in terms of occupational or skill differences. According to this approach, occupational and skill inequalities do not lead to exploitation, domination, and the consequent antagonistic interests that define social class divisions for several reasons. First, because skills are inalienable, an alternative enterprise without skill inequality does not satisfy the feasibility condition given that it could only be realized by changing resource endowments (i.e., the supply of skills) and not merely by changing social relations within the firm. 3 Second, because occupational differences reflect, at least in part, technological conditions and specialized skill requirements within the production process, an alternative enterprise without occupational differences also does not satisfy the feasibility condition because reorganizing the technical division of labor would require changing both resource endowments and technologies. Thus, skill and occupational differences are not directly linked to exploitation or domination, and they are treated as conceptually distinct from social class divisions.

Although this theoretical framework is closely informed by several alternative approaches to class analysis, it remains distinctive in several regards. It differs from neo-Durkheimian ( Weeden and Grusky 2005 ) and neo-Weberian theories of class ( Erikson and Goldthorpe 1992 ; Featherman and Hauser 1978 ) in that it views occupational groups based on the technical division of labor and conflict groups based on the social relations of production as distinct phenomena with independent effects on material welfare, attitudes, and behavior. It differs from traditional Marxist theories of class primarily in its conflicting view on authority, which for Marx was not a unique basis for class divisions. On this point, the approach outlined here has much in common with neo-Marxist theory (e.g., Wright 1985 ), whose emphasis on rights and powers over both the means of production and “organizational assets” resonates with the proposed framework's focus on ownership and authority. However, the approach outlined in this study differs from other elements of neo-Marxist theory—in particular, the latter's equation of skill inequalities with social class divisions along with its conception of exploitation as an unconditional, rather than contingent, feature of capitalist firms.

The theoretical tradition most consistent with the proposed class-analytic framework is arguably the anarchist tradition, and specifically, the work of Proudhon (1994 , 2011) . Few social theories have been as misunderstood as anarchism. In popular discourse, the term is often equated with chaos or disorder, but in fact, anarchist theory contains an elaborate and incisive analysis of the causes of economic inequality, the most important of which are thought to be ownership, authority, and the conflict generated by these social relations ( McKay 2011 ). Proudhon (1994 , 2011) argued, among other things, that unequal ownership and authority, but not skill differences, engender exploitation, domination, and intergroup conflict; that certain forms of ownership, such as that characteristic of independent producers or small proprietors, do not lead to exploitation and domination; that social class conflict is erratic rather than progressive in its course; and finally, that a collection of independent producers and worker-directed cooperative firms operating within a competitive market, as opposed to state ownership and management of production, would approximate an economic system free of exploitation, domination, and social class conflict. In different ways, these ideas are all reflected in the counterfactual approach outlined here.

This approach has several specific advantages over alternative conceptions of exploitation, domination, and social class. First, it avoids the labor theory of value. In other words, there is no assumption that the value of a commodity is intrinsically determined by the labor required to produce it. This flawed assumption complicates approaches to exploitation that define it terms of labor transfers (e.g., Marx 1976 ; Roemer 1982 ). Second, the counterfactual approach accommodates the possibility that the level and growth rate of economic output may be endogenous to the social relations of production. This type of endogeneity complicates approaches to exploitation that define it in terms of “surplus appropriation,” which implicitly assume a highly invariant level of economic output across different modes of production (e.g., Wright 1984 , 1985 , 1997 ). Finally, the counterfactual approach avoids normative assumptions about the overall desirability of different institutional arrangements, organizational forms, or resource distributions. It simply provides an analytic device for explaining why individuals that occupy different positions within the social relations of production might be expected to think and behave in conflicting ways.

SOCIAL CLASS STRUCTURE AND INCOME INEQUALITY

A variety of different mechanisms link property ownership and authority to personal income, including the supply and demand for different factors of production, economic rents that emerge from market distortions and incentive problems, the balance of bargaining power between social classes, and state institutions. Several perspectives within the conflict theoretical framework suggest that these distributional mechanisms are shaped primarily by three interrelated forces, with important consequences for social class structure and social class inequality: the intensity of market competition, technological development, and class-based political conflict ( Marx 1976 , 1978 ; Proudhon 1994 , 2011 ; Wright 1985 , 1997 ).

First, market competition is thought to have a paradoxical tendency to reduce the number of competitors and to promote concentration of the means of production among an increasingly selective group of proprietors and managers. A natural consequence of market competition is that larger and better endowed enterprises use their advantages to eliminate or absorb inferior firms. As a result, the means of production may become more and more concentrated among a shrinking group of large proprietors and high-level managers over time. A paradoxical shift toward greater economic concentration, then, is thought to follow periods of heightened market competition, and this is expected to reduce the relative number of proprietors and managers, generate rent income for large proprietors and high-level managers, and weaken the bargaining position of workers. The sudden emergence and rapid escalation of foreign competition with American business during the 1970s is well documented ( Bluestone and Harrison 1982 ), and consistent with arguments about the paradoxical effects of competition, most indicators show that the pace of industrial monopolization and capital concentration accelerated in subsequent decades ( Foster, McChesney, and Jonna 2011 ; Piketty 2014 ).

Second, although technological development should lead to greater output, lower costs, and a general increase in material welfare, it may also have contradictory effects that render these positive impacts more elusive for certain social classes ( Marx 1976 ; Proudhon 1994 , 2011 ). Specifically, technological change may promote economic concentration because it conveys a competitive advantage to larger and better endowed firms who are capable of financing and implementing the new technology. Technology may also be used to subvert organization and collective action on the part of workers, and it often enhances the scope for capital mobility, both of which increase competition among workers and shift the fulcrum of bargaining power in favor of large proprietors and high-level managers ( Bluestone and Harrison 1982 ; Proudhon 2011 ). In addition, because technological development often displaces workers, periods of rapid innovation may yield a chronic oversupply of labor, which suppresses wages and further enhances the bargaining power of proprietors and managers ( Proudhon 2011 ).

The recent period of growing income inequality is marked by two types of technological development thought to exert these types of contradictory effects: (1) improvements in transportation and communication, such as high-speed air travel, high-volume shipping, and rapid telecommunications, and (2) advances in automation and computers. Improvements in transportation and communication technology have increasingly allowed production operations to be conglomerated, geographically dispersed, and swiftly relocated ( Bluestone and Harrison 1982 ; Levinson 2008 ). Growing capital mobility since the 1970s is evidenced by increased employment losses due to plant relocations, shutdowns, and cutbacks; the disproportionate increase in foreign versus domestic investment; and the transfer of manufacturing employment from the Northeast and Midwest to the South and abroad ( Bluestone and Harrison 1982 ). Advances in automation and computers are also linked to worker displacement and declines in worker bargaining power. For example, evidence suggests that these technologies lowered aggregate demand for workers performing routine manual or cognitive tasks ( Autor, Levy, and Murnane 2003 ) and were implemented by industrial managers in ways designed to undermine worker organization ( Noble 1984 ).

Finally, in addition to changes in the competitive environment and technology, the escalation or abatement of organized political activities on the part of different social classes may affect income distribution through their influence on the institutional landscape. Research on class-based forms of collective action indicates that the 1970s and 1980s were a period of unprecedented political mobilization by large proprietors and high-level managers ( Mizruchi 2013 ; Useem 1984 ). Business political activity, including the practice of anti-union tactics, subvention of political candidates, establishment of nonprofit policy organizations, and use of issue advertising, greatly intensified during this period. For example, worker firings during union election campaigns increased roughly threefold between 1976 and 1986 ( Schmitt and Zipperer 2009 ), and between the late 1960s and early 1980s, the number of corporate political action committees increased from about 100 to more than 1,000 ( Useem 1984 ). Although it is difficult to draw direct causal connections between shifts in class-based political activity and institutional change, the weight of the evidence suggests a strong correspondence. The political mobilization of large proprietors and high-level managers during the 1970s and 1980s was closely followed by a set of institutional changes, such as de-unionization, regressive reforms to the tax code, and freezes in the nominal minimum wage, thought to depress worker compensation and shift income toward those in positions of ownership and authority ( Morris and Western 1999 ).

Several hypotheses emerge from the foregoing discussion. Growing economic concentration, the technological displacement of workers, and shifts in relative bargaining power suggest a substantial increase in between-class income differences driven by growing incomes for managers and proprietors together with stagnating or declining incomes for workers and independent producers. These divergent income trajectories are anticipated to be even more pronounced for the highest-earning upper strata of proprietors and managers because economic concentration, technological change, and shifts in bargaining power are thought to be most consequential for large enterprises and those near the top of workplace authority hierarchies. By extension, changes in income differences between social classes, and especially between social class strata, are anticipated to have a large inflationary effect on trends in personal income inequality since the 1980s.

Changes to the competitive environment and technology also suggest several different trends in the relative size of social classes since the 1980s. Specifically, growing economic concentration implies a decline in the proportion of proprietors and independent producers, and a corresponding increase in the proportion of workers. The effect of economic concentration and technological development on the relative number of managers, however, is somewhat less clear. For example, growing economic concentration may give rise to increasingly complex administrative bureaucracies, which would increase aggregate demand for managers and exert upward pressure on their relative number over time. By contrast, economic concentration and technological development may also improve the efficiency with which managerial labor is utilized. When production is automated and organized within a smaller number of larger enterprises, fewer individuals may be needed to supervise and direct the activities of workers. In addition, as large firms become more insulated from competition and begin to saturate the markets for their products, it may become increasingly difficult for them to generate new revenue. In this situation, firms might seek to boost profits by aggressively cutting costs, and managers at the middle or bottom of authority hierarchies, who are responsible for a disproportionately large share of a firm's wage bill, may be targeted for removal. These forces would exert downward pressure on the proportion of managers over time.

In sum, the evolution of market competition and technological development suggest a decline in the proportion of independent producers; a decline in the proportion of proprietors; stagnation or perhaps a slight decline in the proportion of managers; and an increase in the proportion of workers since the 1980s. These changes are anticipated to have a small dampening effect on trends in personal income inequality because they involve shifts in the composition of the population away from social classes that typically earn highly variable incomes well above the population average toward a social class whose members typically earn less variable incomes closer to the population average.

ALTERNATIVE THEORIES

The post-class perspective.

In sharp contrast to class-analytic theory, the post-class perspective contends that technological, competitive, and political changes have attenuated, rather than amplified, between-class income differences, and expanded, rather than contracted, the relative number of proprietors, managers, and independent producers ( Bell 1973 ; Pakulski and Waters 1996 ; Pakulski 2005 ). First, according to this perspective, technological development has transformed production from a system based on large capital-intensive enterprises into a system in which scale economies are less important and small dynamic firms flourish ( Bell 1973 ; Pakulski and Waters 1996 ). These changes, in turn, are held to promote a progressive redistribution of productive wealth and a “reduction in the saliency of property in structuring...patterns of economic allocation” ( Pakulski and Waters 1996 :75). Technological development is also thought to enhance demand for skilled managerial decision-making as a result of the growing complexity of production operations. Thus, according to this perspective, ownership of the means of production has become more decentralized, a large number of small firms have entered increasingly competitive markets, and demand for managerial tasks has increased, leading to a decline in income for proprietors, an increase in income for managers, and comparatively faster growth in the number of proprietors, managers, and independent producers relative to workers.

The post-class perspective also argues that “the significance of class as a basis for political identification and behavior and as a force for change has been declining” ( Pakulski and Waters 1996 :132). According to this view, the effects of class-based politics on state and labor market institutions intensified during the early twentieth century, but “a reversal of this trend took shape between 1960 and 1990” (133). Owing to a purported disconnect between social class and partisanship together with a decline in class-based political organizations, “politics...is ceasing to be a distributive game monopolized by corporate actors” (142). If the ability of proprietors and managers to influence income distribution through political activism has waned rather than intensified over recent decades, their income shares would be expected to stagnate or decline.

Thus, post-class theory is essentially a negation of the class-analytic perspective. It predicts stagnating or declining income differences based on workplace ownership and authority, which implies a null or dampening effect of changes in between-class income differences on trends in personal income inequality. It also predicts an increase in the relative number of proprietors, managers, and independent producers, and a decline in the relative number workers, which implies a small inflationary effect of changes in relative class size on growth in personal income inequality.

Skill-biased Technological Change

Unlike post-class theory, the skill-biased technological change perspective does not provide competing, or mutually exclusive, hypotheses with respect to class-analytic theory. Rather, it points toward a set of alternative and potentially confounding human capital factors, such as education and other cognitive abilities, which must be addressed alongside social class in research on personal income distribution. This perspective contends that the introduction of new technologies, such as personal computers, has increased demand for analytic skills and displaced large numbers of workers who perform routine tasks ( Autor, Katz, and Kearney 2008 ; Autor, Levy, and Murnane 2003 ). Because highly educated workers are thought to have realized relatively larger gains in productivity through the introduction of computers, the well-documented increase in the income returns to education provides considerable evidence of skill-biased technical change ( Autor, Katz, and Kearney 2008 ). Additional support for this perspective comes from studies finding that workers who use computers on the job earn higher wages than comparable workers who do not use computers ( Krueger 1993 ), that highly educated workers are more likely to use computers ( Card and DiNardo 2002 ), and that occupation-based measures of skill reveal increasing demand for abstract reasoning abilities and declining demand for routine skills ( Autor, Katz, and Kearney 2008 ; Autor, Levy, and Murnane 2003 ). The class-analytic perspective hypothesizes that additionally accounting for workplace ownership and authority in models based on education and other human capital characteristics will provide an improved explanation of changes in personal income distribution since the 1980s.

Occupational Class Models

Occupational classes refer to aggregate or disaggregate groups of functionally, technically, or contractually similar jobs ( Erikson and Goldthorpe 1992 ; Featherman and Hauser 1978 ; Weeden and Grusky 2005 ). Occupational class divisions based on the technical division of labor are conceptually and empirically distinct from social class divisions based on workplace ownership and authority ( Kalleberg and Griffin 1980 ; Wright 1979 ). Although ownership and authority relations at the site of production are partly expressed through occupational differences, prior research shows that social class divisions are common within occupational classes, that occupational divisions have become deeply embedded within social classes, and that social versus occupational class differences in job rewards are unique and separable ( Kalleberg and Griffin 1980 ; Wright 1979 ).

Aggregate occupational classes are, at least in part, proxies for human capital, and thus may be linked to growing income inequality through skill-biased technical change ( Weeden at al. 2007 ). Aggregate occupational classes may also be connected to different forms of rent extraction insofar as they are institutionalized in societal-level patterns of unionization, collective bargaining, and other forms of social closure ( Morgan and Cha 2007 ; Morgan and Tang 2007 ; Weeden et al. 2007 ). Because of de-unionization and the proliferation of occupational closure movements since the 1980s, income differences between aggregate occupational classes are anticipated to have increased over time. Consistent with these arguments, prior research documents a modest degree of income divergence between classes in several different aggregate occupational typologies ( Morgan and Cha 2007 ; Morgan and Tang 2007 ; Weeden et al. 2007 ).

A number of researchers contend that disaggregate, rather than aggregate, occupational classes are more closely associated with material inequalities ( Grusky and Sorensen 1998 ; Weeden and Grusky 2005 ). The starting point for the disaggregate approach is the “unit occupation,” which is defined as a small group of “technically similar jobs that is institutionalized in the labor market” ( Grusky 2005 :66). According to this perspective, unit occupations are more strongly linked to income inequality than are aggregate occupational classes because the forces of supply and demand, social closure, and institutionalization operate primarily at the disaggregate level. Thus, because of shifting demand for occupations requiring different types of human capital and the growing use of licensure, registration, and certification to erect steep barriers to occupational entry, income differences between disaggregate occupational classes are anticipated to have grown substantially over time. Consistent with this perspective, prior studies document steady growth in income differences between classes in disaggregate occupational typologies ( Mouw and Kalleberg 2010 ; Weeden at al. 2007 ). The class-analytic perspective outlined in this study hypothesizes that additionally accounting for social class divisions in models based on both aggregate and disaggregate occupational class divisions will provide an improved explanation of changes in personal income distribution.

Data and Measures

I use data from the 1980 to 2010 waves of the GSS, which contain demographic, employment, and income data from nationally representative samples of non-institutionalized adults in the U.S. ( Smith et al. 2011 ). The GSS is well-suited for this study because, unlike other omnibus national surveys, it contains reasonably accurate measures of both social class and personal income from repeated cross-sections of the population throughout the recent period of growing inequality. The GSS waves of interest were collected annually from 1980 to 1994—except in 1981 and 1992—and biennially thereafter. I focus on the period from 1980 to 2010 because it brackets recent growth in income inequality and because it is the period for which data on ownership, authority, and personal income are available from sufficiently large samples in the GSS. 4 The 1980 to 2010 cumulative analytic sample consists of 22,071 respondents who were 18 to 65 years old and worked full-time at the date of their interviews. Parallel analyses of data that also included part-time respondents or that excluded respondents in agricultural industries produced similar results.

Social Class

The GSS asks respondents whether they are self-employed or work for someone else. This question is used to distinguish between employees who do not own the means of production and individuals with sufficient assets to at least gainfully employ themselves. The GSS also asks respondents whether their job involves supervising others. 5 Together, these two items are used to sort respondents into the four social class positions: proprietors (self-employed and supervise others), independent producers (self-employed and do not supervise others), managers (work for someone else and supervise others), and workers (work for someone else and do not supervise others).

This study further classifies proprietors and managers into different class strata using a GSS item that asks respondents who report supervising others whether any of their subordinates are themselves supervisors. This question indicates whether managers occupy positions closer to the top of the workplace authority hierarchy, and it provides an approximate measure of the size of proprietors’ firms (since larger firms are more likely than smaller firms to have multilevel authority structures). Large versus small proprietors and high- versus low-level managers are differentiated according to whether their subordinates also supervise others at work.

Personal market income is the dependent variable of interest. This includes income earned during the previous year from an individual's job, business, or investments. 6 The GSS measures personal market income using interval response categories, and dollar values are imputed based on interval midpoints. For the last open-ended interval capturing the highest incomes, dollar values are estimated using a Pareto approximation ( Hout 2004 ). 7 Nominal incomes are adjusted for price inflation over time using the Consumer Price Index, with the adjusted values expressed in 2011 dollars. Following convention with self-reported income data (e.g., Card and DiNardo 2002 ), full-time respondents who report implausibly low annual incomes are truncated (<5000 real dollars). All analyses are based on the natural log transformation of income.

The covariates included in multivariate analyses are age, race, gender, education, verbal ability, parental education, geographic region, and urbanicity. Age is measured in years and expressed as a series of dummy variables for “18 to 25,” “26 to 35,” “36 to 45,” “46 to 55,” and “56 to 65” years to account to potential nonlinearities; race is expressed as a series of dummy variables for “black,” “white,” and “other” race respondents; and gender is coded 1 for female and 0 for male. Geographic region is expressed as a series of dummy variables for “Northeast,” “Midwest,” “South,” and “West.” Urbanicity is also expressed as a series of dummy variables for residence in an urban, suburban, or rural area. Both respondent and parental education are measured in years and recoded as a series of dummy variables for “less than high school,” “high school graduate,” “some college,” and “college graduate” also to account for potential nonlinearities. Verbal ability is measured with scores on the Gallup-Thorndike verbal intelligence test—a widely used ten-item vocabulary assessment with desirable psychometric properties ( Alwin 1991 ; Thorndike 1942 ; Yang and Land 2006 ). All of these covariates are potentially powerful joint predictors of both social class attainment and personal income. 8

This study also analyses both aggregate and disaggregate occupational classes. Aggregate occupational classes are measured using a 9-category version of the Featherman-Hauser typology ( Featherman and Hauser 1978 ), which is preferred over similar others (e.g., Erikson and Goldthorpe 1992 ) because it can be precisely measured in the GSS and because prior research suggests that it provides a better fit to U.S. data on material inequalities ( Weeden and Grusky 2005 ). This typology classifies census occupational codes into the following broad categories: professional occupations, managerial and administrative occupations, sales occupations, clerical occupations, craft occupations, service occupations, operatives, general laborers, and agricultural occupations. 9

Disaggregate occupational classes are measured following methods developed by Weeden and Grusky (2005) . These classes are constructed to reflect “institutionalized boundaries as revealed by the distribution of occupational associations, unions, and licensing arrangements, as well as the technical features of the work itself” (156). Measurement of this typology involves collapsing Standard Occupational Classification (SOC) codes into 127 occupational micro-classes. 10 Specifically, this typology is based on the 1970 SOC codes. Because GSS waves collected after 1991 only contain 1980 SOC codes, I reconcile these different classifications by back-coding more recent data into the 1970 SOC scheme. This involves multiplying each observation by the number of 1970 SOC codes that contribute to the 1980 SOC code and then assigning weights to each record in the expanded dataset equal to the proportion of the 1980 SOC code drawn from the constituent 1970 SOC code.

The analysis proceeds in three steps. First, I analyze changes in the relative size of social classes, changes in between-class income differences, and changes in within-class income dispersion. Second, I evaluate the effects of these changes on trends in personal income inequality using a formal decomposition analysis. Finally, I compare the fit of income models based on human capital inputs, occupational class divisions, and social class divisions, and then provide a multivariate decomposition that evaluates the net effects of these different factors on trends in personal income inequality.

To investigate changes in the relative size of social classes, I estimate and plot class proportions, denoted by π jt = P ( C t = j ), over time. In this notation, C t is a polytomous variable with j = 1,...,,4 categories representing the social class positions defined previously, and t denotes the time period. To investigate changes in between-class income differences, I estimate denotes the time period. To investigate changes in between-class income differences, I estimate and plot trends in mean log income for each social class position, denoted by μ jt = E ( Y t | C t = j ). Because divergent income trends between social classes may be due to confounding factors, such as increasing returns to education or other skills that are correlated with class attainment, I also estimate multivariate regressions that model mean log income as a function of social class, individual covariates, and fixed-effects for disaggregate occupations. Covariate-adjusted estimates of mean log income for each social class position are estimated and plotted across time with individual covariates and occupational dummy variables set to their sample means. To investigate changes in within-class income dispersion, I estimate and plot the variance of log income within each social class j at time t , denoted by σ j t 2 = V a r ( Y t ∣ C t ) .

Next, I evaluate the effects of compositional, between-class, and within-class changes on trends in personal income inequality with a formal decomposition analysis of the total variance of log income, denoted by V t = Var ( Y t ). The variance of log income is a scale-invariant measure of inequality that is subgroup decomposable and has a convenient functional relationship with other common inequality metrics, such as the Gini index ( Allison 1978 ). At a given time period, this measure can be decomposed as follows:

where the between-class ( B t ) and within-class ( W t ) components are expressed as weighted sums of class-specific means and variances, and r j t 2 = ( μ j t − ν t ) 2 is the squared deviation of mean log income for social class j at time t ( μ jt ) from the population mean at time t ( ν t ) ( Western and Bloome 2009 ; Western, Bloome, and Percheski 2008 ).

With time-series data, the change in income inequality from time t = 0 (the baseline time period) to t = t ′ (a post-baseline time period) can be decomposed into the sum of a compositional effect, δ P ; a between-class effect, δ B ; and a within-class effect, δ W . Specifically, the change in income inequality is given by

where the compositional effect of changes in the relative sizes of social classes is δ P = ∑ j ( π j t ′ − π j 0 ) ( r j t ′ 2 + σ j t ′ 2 ) ; the between-class effect of changes in mean income for different social classes is δ B = ∑ j π j 0 ( r j t ′ 2 − r j 0 2 ) ; and the effect of changing income dispersion within social classes is δ W = ∑ j π j 0 ( σ j t ′ 2 − σ j 0 2 ) . I estimate each of these quantities and scale them by the change in total variance, which gives the proportionate impact of compositional, between-class, and within-class effects on trends in personal income inequality.

To investigate whether social class divisions based on workplace ownership and authority provide an improved explanation of trends in personal income distribution beyond more conventional models based on human capital characteristics, aggregate occupational classes, or disaggregate occupational classes, I compare the fit of a variety of income models with different sets of predictors. Specifically, I evaluate whether adding predictors for social class to models of personal income based on human capital characteristics and occupational class divisions significantly improves goodness of fit. Goodness of fit is measured with the Akaike information criterion (AIC), the Bayesian information criterion (BIC), and the adjusted- R 2 statistic ( Akaike 1974 ; Schwarz 1978 ; Theil 1961 ). These fit statistics penalize models with larger numbers of parameters and thus work to identify a parsimonious model with maximum explanatory power. The BIC has the most severe penalty for additional parameters, followed by the AIC and then adjusted- R 2 , which has the least severe penalty. Lower values of the AIC and BIC, and higher values of adjusted- R 2 , indicate superior model fit.

Finally, I evaluate the net effects of social class, occupational class, and human capital on growth in personal income inequality by combining multivariate decomposition methods with variance function regression ( Western and Bloome 2009 ). In analyses of income inequality that involve d covariates with levels l 1 , l 2 ... l d , the data are organized in a decomposition table, where each observation is assigned to one of the L = l 1 × l 2 × ... × l d cells in the cross-classification of all covariates. Similar to the decomposition analysis described previously, temporal trends in personal income inequality can be decomposed into the effects of changes in cell proportions, means, and variances.

Variance function regression is used to simultaneously model the cell means and variances at each time period, and the net effects of social class, occupational class, and education on trends in income inequality are quantified with counterfactual variances that fix model coefficients at their baseline values. Specifically, the variance function regression model is expressed as

where C t is a vector of dummy variables for social classes, R t is a vector of dummy variables for education, and Q t is a vector of dummy variables for aggregate occupational classes. I focus on aggregate occupational classes in this analysis because the GSS lacks the data needed for a multivariate decomposition based on disaggregate occupations. 11 Equation 3 is estimated from a least squares regression of log income on social class, aggregate occupational class, and education, stratified by time. Then, squared residuals are computed from this regression, and Equation 4 is estimated from a gamma regression of the squared residuals on social class, aggregate occupational class, and education, also stratified by time.

The net effects of social class, occupational class, and education on trends in personal income inequality are quantified by plotting counterfactual variances that fix specific regression coefficients at their baseline values. For example, to measure the net effect of changes in mean income between social class positions, I estimate and plot the following counterfactual variance: V t β 0 = ∑ l = 1 L π l t ( r ~ l t 2 + σ l t 2 ) , where the adjusted between-cell mean differences, r ~ l t = μ ~ l t − ν t , are calculated from u ~ l t = α t + β 0 C l t + γ t X l t + η t Q l t . In this notation, X lt , C lt , and Q lt denote the values of these variables associated with cell l at time t in the multivariate decomposition table. The counterfactual variance is interpreted as the level of income inequality that would have been observed had net differences in mean income between social classes remained constant since the baseline time period. I evaluate the statistical significance of these effects on trends in income inequality by using bootstrap methods to test the null hypotheses that H 0 : V t β 0 ≥ V t . 12

To avoid problems associated with data sparseness, observations are pooled within decades and estimates are computed separately for the 1980s, 1990s, and 2000s in all analyses. This ensures a sufficient number of observations in each social class at each time period, improves the precision of estimates, and still allows for an informative, albeit less fine-grained, tracking of change over time. More complex analyses, including models based on fully nonparametric functions of time, provide similar point estimates for the trends of interest and do not significantly improve goodness of fit. Multiple imputation with ten replications is used to fill in missing values for all variables, and combined estimates are reported throughout ( Rubin 1987 ).

Trends in the Relative Size of Social Classes

Figure 1 displays trend estimates of social class proportions. The upper panel of the figure displays trends for all social classes on the same scale, and the lower panel displays trends for the two smallest classes—proprietors and independent producers—using a magnified scale on the right vertical axis. Results indicate that the social class structure was fairly stable over the past three decades in question. Between the 1980s and 2000s, slight increases were found for the proportions of workers (53 to 57 percent) and independent producers (4 to 6 percent), while slight decreases were found for the proportions of managers (35 to 31 percent) and proprietors (8 to 6 percent).

Trends in the Relative Size of Social Class Positions

Figure 2 displays trend estimates for the relative size of different social class strata. The upper panel displays estimates for all class strata, and the lower panel displays trends for the smallest strata on a magnified scale. These estimates reveal trends similar to those in Figure 1 . Between the 1980s and 2000s, slight decreases were found for the proportions of both large proprietors (3 to 2 percent) and small proprietors (5 to 3 percent), and for the proportions of both high-level managers (11 to 9 percent) and low-level managers (23 to 22 percent).

Trends in the Relative Size of Social Class Strata

These trends are difficult to reconcile with the post-class perspective and are consistent, at least in part, with class-analytic theory. The steady growth observed for the proportion of independent producers conflicts with class-analytic hypotheses, but this trend may simply reflect well-documented growth in the number of nominally self-employed contingent workers, such as freelancers, homeworkers, and temporary contractors, rather than growth in the number of independent small business owners ( Dale 1986 ; Kalleberg 2011 ). Nominally self-employed contingent workers differ from conventionally employed workers only in that they sell their labor power to an employer under a different type of contractual arrangement, and thus observed trends in the proportion of independent producers may be entirely consistent with class-analytic theory. This trend may also be associated with the widespread proliferation of high-speed communication technologies and personal computers, which allow employers to contract a variety of labor services from contingent workers located outside of the firm. Without more detailed data, however, this explanation remains somewhat speculative.

Trends in Income Differences between Social Classes

Figure 3 displays unadjusted trends in mean log income. The upper panel of the figure displays estimates separately for each social class position, and the lower panel displays estimates separately for each class stratum. These estimates reveal a pronounced divergence of personal income between positions in the workplace ownership and authority structure.

Unadjusted Income Trends by Social Class Position and Strata

Specifically, the upper panel of Figure 3 shows that incomes for proprietors increased substantially between the 1980s and 2000s. Point estimates suggest that proprietor incomes increased by about 30 percent, on average, during this period (i.e., 11.27 – 10.97 = 0.30). In contrast, incomes for managers and workers increased by about 8 percent percent, respectively, while incomes for independent producers declined by about 5 percent. The lower panel of Figure 3 suggests that income growth was considerably greater for the upper rather than lower strata of proprietors and managers between the 1980s and 2000s. Incomes increased, on average, by about 20 percent for high-level managers and by only about 4 percent for low-level managers. Similarly, incomes increased by about 60 percent for large proprietors and by only 7 percent for small proprietors.

Figure 4 displays covariate-adjusted trends in mean log income. These estimates come from multivariate regressions that include predictors for social class, individual covariates, and disaggregate occupations. They capture divergent income trends between social classes that are not simply due to confounding factors like increasing returns to education or occupational differences in skill, prestige, and the extent of social closure. The upper panel of the figure indicates that income differences between social class positions increased over time, net of these other factors. Specifically, covariate-adjusted point estimates indicate that personal incomes for proprietors and managers increased by 27 percent and 11 percent, respectively, while incomes for workers increased by 8 percent and incomes for independent producers were stagnant. The lower panel of Figure 4 displays covariate-adjusted trends in mean log income separately by social class strata. It indicates that growth in between-class income inequality—net of individual and occupational differences—was driven primarily by pronounced income gains for large proprietors and high-level managers, consistent with the proposed class-analytic theory.

Covariate-adjusted Income Trends by Social Class Position and Strata

Figure 5 displays trends in total income inequality between social classes as indicated by the mean squared deviation of the estimated class means from the estimated population mean. This metric provides a single number summary of changes in between-class income differences over time. It is scaled to equal one in the 1980s, and all values thereafter represent proportionate changes since this time period. Point estimates indicate that income differences between social class positions increased by 66 percent and that income differences between social class strata nearly doubled since the 1980s. Total income inequality between social classes, however, did not increase monotonically during this period: it declined modestly from the 1980s to the 1990s and then increased substantially thereafter.

Trends in Between-group Income Differences

As a comparative reference, Figure 5 also displays estimates quantifying growth in income differences between education levels and between aggregate occupational classes. Point estimates indicate that income differences between education levels and between aggregate occupational classes increased by 82 percent and 13 percent, respectively, since the 1980s. These results suggest that the overall magnitude of growth in social class inequality was much greater than growth in aggregate occupational inequality and was comparable to growth in educational inequality, although growth in income differences between education levels was monotonic and far exceeded growth in social class inequality prior to the 1990s.

Trends in Income Dispersion within Social Classes

Figure 6 displays trends in within-class income dispersion. The upper panel of the figure displays residual variances for each social class position, and the lower panel displays residual variances for each social class stratum. These estimates indicate that income differences increased not only between social classes but also within them. The most pronounced increase in within-class income dispersion occurred among proprietors, with the variance of log income rising by about 50 percent for this group. In contrast, income dispersion among independent producers, workers, managers increased by about 10, 20, and 30 percent, respectively. The pronounced increase in income dispersion among proprietors was driven primarily by disproportionate income growth at the top of the distribution.

Trends in Within-class Income Dispersion

Decomposition of Trends in Personal Income Inequality

Figure 7 displays trends in personal income inequality as indicated by the total variance of log income. These estimates indicate that the total variance increased by about 10 percent, from 0.45 to 0.49, between the 1980s and 1990s, and then increased by another 15 percent, from 0.49 to 0.57, between the 1990s and 2000s. Over the entire period, the total variance of log income increased by about 27 percent. Total variance estimates from the GSS suggest a higher level of income inequality overall than estimates based on other data sources, such as the Current Population Survey (CPS). This disparity is due to a greater frequency of low incomes in the GSS. For example, the first, fifth, and tenth percentiles of the personal income distribution in the GSS are about $7,500, $12,000, and $16,000, respectively, while the same percentiles in the CPS are $9,500, $15,000, and $19,000. Above the tenth percentile, the two distributions are similar. This suggests that midpoint imputation of incomes from the GSS interval measurement procedure may be less accurate in the lower tail of the distribution. Nevertheless, these differences are fairly modest, and the time trend in total income inequality estimated from the GSS is similar to trends estimated from other data sources, including the CPS.

Trends in Total Income Inequality

Table 1 presents results from a formal decomposition of trends in personal income inequality. The upper panel of the table reports results from a decomposition by social class position. Results from this analysis indicate that compositional changes in the relative sizes of social classes had a small dampening effect and that changes in between-class income differences had a large inflationary effect on trends in income inequality, particularly from the 1990s onward. For example, point estimates indicate that growth in between-class income differences explains 18 percent of the overall increase in personal income inequality between the 1980s and 2000s, and 33 percent of the increase between the 1990s and 2000s. Between the 1980s and 1990s, however, changes in between-class income differences had a nontrivial dampening effect, and despite the strong inflationary effect of subsequent changes in between-class income differences, growth in within-class income dispersion consistently had the largest effect on trends in personal income inequality.

Notes: Sample includes respondents who are 18 to 65 years old and work full-time in the 1980 to 2010 GSS waves. Results are based on 10 multiple imputation datasets. Confidence intervals are based on quantiles of 500 bootstrap sample estimates.

The lower panel of Table 1 reports results from a decomposition by social class strata. Results from this analysis indicate that changes in between-strata income differences had a substantial inflationary effect on trends in personal income inequality. Similar to the effects of social class position, the inflationary effect of growth in between-strata income differences occurs specifically from the 1990s onward. Point estimates indicate that growth in between-strata income differences explains 29 percent of the overall increase in personal income inequality between the 1980s and 2000s, and 55 percent of the increase between the 1990s and 2000s. But between the 1980s and 1990s, changes in between-strata income differences had a modest dampening effect on the trend in total inequality. Results also indicate that changes in within-strata income dispersion had a large inflationary effect and that compositional changes in the relative size of different social class strata had a small dampening effect. In sum, these results indicate that growing income differences between positions in the workplace ownership and authority structure had a substantial impact on trends in personal income inequality, especially between the 1990s and 2000s.

Human Capital, Occupational, and Social Class Models of Personal Income

Table 2 presents goodness of fit statistics for models of personal income based on human capital characteristics, occupational class divisions, and social class divisions. These models are stratified by decade and thus focus on changes in income distribution over time. The first panel of the table compares a standard human capital model that includes predictors for education and demographic characteristics to models that additionally include predictors for social class. Results indicate that accounting for the social relations of production improves goodness of fit: models with dummy variables for a respondent's position in the workplace ownership and authority structure have significantly lower AIC and BIC values, and higher adjusted R 2 values. The second and third panels of Table 2 compare aggregate and disaggregate occupational class models to models that additionally include predictors for social class divisions. As before, results indicate that models accounting for workplace ownership and authority improve goodness of fit. Finally, the fourth and fifth panels of the table show that models including predictors for social class divisions in addition to covariates representing both human capital characteristics and occupational class divisions also provide an improved fit to the data. Although the gains in explanatory power associated with accounting for workplace ownership and authority may appear modest in practical terms (e.g., 2 to 5 percentage point increases in adjusted R 2 ), they are comparable to the gains achieved by disaggregating occupational classes (e.g., 4 to 8 percentage point increases in adjusted R 2 ), which are widely held to represent a notable improvement in the explanatory power of occupational class models ( Grusky and Sorensen 1998 ; Weeden and Grusky 2005 ). 13

Goodness of Fit Statistics for Models of Personal Income Distribution

Notes: Sample includes respondents who are 18 to 65 years old and work full-time in the 1980 to 2010 GSS waves. The F-statistic tests the hypothesis that all parameters associated with social class are equal to zero. Results are based on 10 multiple imputation datasets. All models are stratified by decade. Bold font indicates the best fitting model according to each goodness of fit statistic.

* p < 0.05

** p < 0.01, and

p < 0.001 for F-test that all social class parameters are equal to zero.

Table 2 highlights the best fitting model according to each goodness-of-fit criterion in bold font. According to the AIC and adjusted R 2 measures, the model providing an optimal balance between explanatory power and parsimony is in fact the most complex model considered in this analysis. It includes predictors for human capital characteristics, disaggregate occupational classes, and social class strata. The BIC, which includes a more severe penalty for the number of parameters and thus tends to favor more parsimonious models, indicates that the model with predictors for human capital characteristics, aggregate occupational classes, and social class strata provides the best fit. These results indicate that models of personal income based only on human capital characteristics and occupational classes, including highly disaggregate unit occupations, are suboptimal in that they fail to capture notable income differences between positions in the workplace ownership and authority structure.

Figure 8 displays counterfactual variance estimates that quantify the net effects of changes in income differences between social classes, aggregate occupational classes, and education levels on trends in total income inequality. These estimates are based on a multivariate decomposition combined with variance function regression. They extend the results presented in Table 2 by directly linking them to growth in income inequality at the population level.

Counterfactual Estimates of Total Income Inequality

Recall that the total variance of log income increased by 27 percent, from 0.45 to 0.57, between the 1980s and 2000s. In contrast, the counterfactual estimates quantifying the between-class effect indicate that the variance of log income would have increased by only 23 percent, from 0.45 to 0.55, if net income differences between social class positions had remained unchanged at their 1980s level. Similarly, the counterfactual estimates quantifying the between-strata effect indicate that the variance of log income would have increased by only 20 percent, from 0.45 to 0.54, if net income differences between social class strata had remained unchanged over time. In other words, these estimates indicate that changes in the returns to ownership and authority account for approximately 15 to 25 percent of the growth in personal income inequality since the 1980s, net of educational and aggregate occupational effects. 14

The counterfactual estimates quantifying the between-education effect indicate that the variance of log income would have increased by about 24 percent, from 0.45 to 0.56, if net income differences between education levels had remained unchanged at their 1980s level. This suggests that increasing returns to ownership and authority had an effect on trends in personal income inequality comparable to that of increasing returns to education. The counterfactual variance estimates quantifying the effects of education and social class also indicate that increasing returns to education were particularly impactful between the 1980s and 1990s, while increasing returns to ownership and authority had a more pronounced influence between the 1990s and 2000s. Estimates quantifying the between-occupation effect indicate that changes in income differences between aggregate occupational classes had a negligible impact on trends in total income inequality, net of education and social class effects. This suggests that growing income differences between social classes had a larger impact on trends in personal income inequality than did changes in income differences between aggregate occupational classes.

Since the 1980s, personal income inequality has increased substantially in the U.S.

Although several theoretical traditions suggest that social classes—defined in terms of ownership and authority relations within production—are closely linked to the distribution of personal income, they have not played a major role in empirical attempts to explain this trend. The present study investigates social class effects on growth in personal income inequality, and it evaluates whether social class models improve upon existing explanations for this trend that emphasize the importance of human capital and occupational classes.

Results indicate that income differences between social classes increased by about 60 percent since the 1980s. This increase was driven primarily by growing incomes for high-level managers and large proprietors together with stagnating incomes for workers and independent producers. Results also indicate that the proportions of workers and independent producers increased, while the proportions of proprietors and managers declined during this period. A formal decomposition analysis that directly evaluates the effects of these trends on personal income inequality suggests that changes in the relative size of social classes had a small dampening effect and that growth in between-class income differences had a significant inflationary effect, particularly from the 1990s onward. Finally, results indicate that accounting for social class divisions based on workplace ownership and authority improves the explanatory power of models based on human capital characteristics and occupational class divisions, which have thus far dominated research on trends in inequality.

This study makes a number of contributions to theory and empirical research on class structure and income inequality. First, it outlines a simple theoretical framework for the analysis of social class that has several advantages over alternative approaches. In particular, this framework implies a parsimonious social class typology that can be easily measured in empirical research; it maintains the conceptual and empirical distinctions between social classes (i.e., conflict groups based on exclusionary relations of production) and occupational classes (i.e., groups of individuals in functionally or technically similar jobs); it contains an explicit, flexible, and testable theory of the conditions—exploitation and domination—that are thought to engender observed patterns of social class conflict; and finally, it provides an account of the social forces, including shifts in the competitive environment, technological development, and class political activism, that govern trends in the material welfare of different social classes over time.

Second, this study tests several key implications of this theoretical framework using time-series data from a large national survey, and it directly links changes in social class structure and social class inequality to trends in the distribution of personal income at the population level. This analysis responds to calls for historical investigations of social class inequality ( Wright 1997 ), addresses arguments that social classes have dissolved in modern society ( Pakulski and Waters 1996 ), and extends industry-level research on the functional distribution of income ( Kristal 2010 , 2013 ; Lin and Tomaskovic-Devey 2013 ) by using an individual-level model to precisely document social class effects on changes in the personal distribution of income. This type of individual-level, population-based evidence directly linking social classes to trends in personal income inequality is largely absent from the literature on social stratification in the U.S.

The weight of the evidence from this analysis casts considerable doubt on post-class theory, is generally consistent with the proposed class-analytic framework, and resonates with recent research on the capital share of national income, wealth concentration, and executive compensation (e.g., Piketty 2014 ). It indicates that income divergence between social classes can explain a practically and statistically significant proportion of growth in personal income inequality at the population level, particularly during the period from the 1990s to the 2000s when inequality was driven upward primarily by increasing incomes at the top of the distribution.

The explanatory power of the social class model, however, is not overwhelming. Between the 1980s and 1990s, when real declines at the bottom of the distribution were also an important driver of growth in inequality, results suggest a negligible impact for social class differences and instead point toward the importance of increasing returns to education. Moreover, across all three decades, results consistently suggest an important role for unobserved factors in explaining this trend. Indeed, within-class (i.e., residual) income dispersion was the main driver of growing inequality throughout the period under consideration. Together, these findings suggest that social class differences are but one part of a multifaceted and historically contingent explanation for growth in income inequality, where, for example, technological changes may have been skill-biased during certain periods and capital-biased during others.

Third, this study compares the proposed class-analytic theory with alternative models for growth in income inequality based on human capital and occupational differences. Results indicate that growing income differences between social classes are largely obscured in alternative models, including those based on highly disaggregate occupations. These findings suggest that critiques of “big class” models ( Grusky and Sorensen 1998 ; Weeden and Grusky 2005 ), which argue that class analysis can be salvaged by focusing on “structuration” at the level of disaggregate occupations, are somewhat misguided. In particular, these critiques conflate social classes based on workplace ownership and authority relations with occupational classes based on the technical division of labor. Although the technical division of labor partially reflects these social relations, the present study indicates that they are in fact conceptually and empirically distinct forms of stratification. Social classes cannot be conveniently disaggregated into small occupational groups, and social class differences in personal income cut across the technical division of labor. This suggests that future research on material inequalities, political attitudes, and consumption practices can be improved by jointly modeling the effects of both social and occupational class divisions. In other words, disaggregate occupational class models should complement, rather than replace, “big” social class models.

Although this study provides a number of important contributions to theory and research on social class and income inequality, it is not without limitations. In particular, it does not evaluate the more specific claims of class-analytic theory about the underlying changes responsible for long-term trends in social class structure and social class inequality, such as technological development, class political mobilization, and growing economic concentration. The results presented here suggest a correspondence between these changes and social class differences in personal income, but more detailed data are needed to rigorously evaluate the causal links between them.

In addition, this study relies on a measure of social class that may imperfectly capture differences in ownership and authority. For example, it remains unclear whether self-employment and supervisory data accurately classify wealthy rentiers who live almost entirely off of investment income and are not directly engaged in economic activity. Pure rentiers represent only a small fraction of large proprietors, but if the measurement approach used here omits this group, it may understate growth in between-class income differences over time because rentiers often earn enormously large incomes.

Finally, this analysis is based on an inexact measure of personal market income. The GSS uses a single survey item based on a series of graduated intervals to measure total money income from a respondent's main job. This is a less sophisticated instrument than those used by other national surveys, such as the CPS. It omits the value of in-kind benefits and earnings from secondary employment, and results suggest that it may understate incomes in the lower tail of the distribution. To attenuate concerns about income measurement in the GSS, I attempted to corroborate key substantive findings with data from the CPS. The CPS uses a more sophisticated measurement procedure for personal income, but it lacks the data needed to precisely measure social class. Although this precludes an exact replication with the CPS, analyses of these data using an occupation-based proxy measure of social class are generally consistent with findings from the GSS. 15

These limitations highlight important directions for future research. In particular, future research should focus on whether the trends documented in this study are directly related to patterns of technological development, economic concentration, and class-based political activism. This might be accomplished by linking individual data from the GSS to information on industrial concentration from the Economic Census or to information on corporate investment in the political process from the Federal Election Commission. These data could be used to test whether regional or inter-industry differences in social class inequality are associated with levels of market concentration or with corporate political investment. Future research should also investigate social class inequality from a longitudinal rather than an independent time-series perspective—for example, by using data from the Panel Study of Income Dynamics to examine social class differences in lifetime income across birth cohorts. In addition, future research should consider the relationship between race, gender, and social class over time, perhaps with a focus on whether status group disparities in social class attainment are linked to persistent racial and gender differences in personal income.

These limitations notwithstanding, the present study documents a significant relationship between social class and trends in personal income inequality over the past three decades, indicating that class-analytic theory remains important for understanding contemporary patterns of social stratification. As social scientists work to better understand the causes and consequences of growing income inequality, rigorous integration of class-analytic theory with quantitative empirical research will be essential.

Supplementary Material

Acknowledgments.

*The author would like to thank David Harding, Yu Xie, Sarah Burgard, Jeffrey Smith, Sheldon Danziger, Mark Mizruchi, Robert Andersen, John Myles, and participants in the Michigan Inequality Workshop for their comments on previous drafts on this study. The author also thanks Kim Weeden for technical assistance with occupational coding. This research was supported by the NSF Graduate Research Fellowship (grant number DGE 0718128) and by the NICHD under grants to the Population Studies Center at the University of Michigan (grant numbers T32 HD007339 and R24 HD041028).

The personal distribution of income shows how income, regardless of its source, is divided between individuals, while the functional distribution of income shows how income is divided between various sources—in particular, between the productive factors of labor and capital. That is, the functional distribution describes the share of total income that comes from payments to labor versus capital. As a measure of total income inequality, the functional distribution is limited because it contains no information about the distribution of factor income across individuals. As a measure of social class inequality, the functional distribution is also limited because it includes all salaries, benefits, and bonuses paid to firm executives in the labor share. This is problematic not only because managers are thought to occupy a social class position distinct from that of non-managerial workers but also because many of these executives are owners or majority shareholders in their companies and isolating the components of their income that accrue to labor versus capital is fundamentally ambiguous. Detailed analyses of labor's share show that it has been “buoyed up” over time by large compensation payments to managers, many of whom likely own at least part of the business they operate ( Elsby, Hobijn, Sahin 2013 ; Piketty 2014 ).

Furthermore, slight variations on this typology have been used in several prior studies of ownership, authority, and individual-level outcomes ( Halaby and Weakliem 1993 ; Kalleberg and Griffin 1980 ; Robinson and Kelley 1979 ; Wright and Perrone 1977 ).

In this context, “inalienable” means that skills (i.e., different types of abilities or talents) are embodied in individuals and cannot be readily dispossessed. It does not imply that the subjective valuation of skills is independent of the interactions between individuals in a firm or market.

Questions about personal income and workplace authority were jointly included in just three waves of the GSS during the 1970s, and in these waves, they were asked of only a random subset of respondents. As a result, the GSS lacks the data needed to support an analysis of social class and personal income inequality during the 1970s.

The GSS uses a split-ballot survey design, and questions about supervisory authority are typically asked of a random 50 to 75 percent subset of respondents.

Research on income measurement suggests that business income may be underreported by as much as 30 percent in surveys ( Hurst, Li, and Pugsley 2010 ). This type of measurement error would result in substantial underestimation of between-class income differences at any single point in time, but it would only impact an analysis of trends if the magnitude of measurement error changed over time.

I also preformed parallel analyses using a constant multiple adjustment in which topcoded incomes are replaced with 1.4 times the topcode threshold. Results (not shown) were very similar to those based on the Pareto approximation.

I also conducted analyses that included controls for several different measures of social and cultural capital, such as the frequency of social interactions with others, the number of organizational memberships, and an index of “high” cultural consumption. Most of these measures are only available in a handful of GSS waves, which precludes their inclusion in the full analysis described here. Nevertheless, results from the selected waves in which these measures are available provide no evidence that social class effects on trends in personal income inequality are simply due to the potentially confounding influence of social and cultural capital.

In addition to this 9-category version, I also conducted analyses using a 12-category version of the Featherman-Hauser typology that incorporates distinctions between employed versus self-employed professionals, managers, and administrators, and between farmers and farm laborers. Results from this analysis are nearly identical to those presented in the main text. I focus on the 9-category version because it maintains a cleaner distinction between social relations and technical divisions.

The original Weeden-Grusky typology has 126 occupational classes. My implementation of this typology includes an additional class for military occupations plus a residual category for a small number of respondents with missing occupational codes.

With a 127 disaggregate occupational classes, 4 education levels, 4 social classes, and T time periods, the multivariate decomposition table would have 127 × 4 × 4 × T cells. Even with a small number of time periods, the GSS does not have enough observations to sufficiently populate such a high-dimensional table.

Specifically, I compute a 95 percent confidence interval for V t β 0 − V t based on 2.5 and 98.5 percentiles of a sampling distribution estimated from 500 bootstrap replications. If this confidence interval falls entirely below zero, then the null hypothesis is rejected.

The gains in explanatory power associated with disaggregating occupational classes can be obtained by comparing model (D) with model (G) and model (J) with model (M) in Table 2 .

For example, when scaled by the change in observed variance, the difference between the change in observed variance and the change in the counterfactual variance for the between-class and between-strata effects are, respectively, ((0.57 – 0.45) − (0.55 – 0.45))/(0.57 – 0.45) = 0.14 and ((0.57 – 0.45) − (0.54 − 0.45))/(0.57 – 0.45) = 0.25.

These results are reported in the Online Supplement , which also documents the precise coding of both aggregate and disaggregate occupational classes.

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