economic disparity essay

• Share full article

Advertisement

Supported by

Is Economic Inequality Really a Problem?

Yes, but the answer is less obvious than you might think.

By Samuel Scheffler

Dr. Scheffler is a professor of philosophy.

It is impossible to ignore the stark disparities of income and wealth that prevail in this country, and a great many of us are troubled by this state of affairs.

But is economic inequality really what bothers us? An influential essay published in 1987 by the philosopher Harry Frankfurt suggests that we have misidentified the problem. Professor Frankfurt argued that it does not matter whether some people have less than others. What matters is that some people do not have enough. They lack adequate income, have little or no wealth and do not enjoy decent housing, health care or education. If even the worst-off people had enough resources to lead good and fulfilling lives, then the fact that others had still greater resources would not be troubling.

When some people don’t have enough and others have vastly more than they need, it is easy to conclude that the problem is one of inequality. But this, according to Professor Frankfurt, is a mistake. The problem isn’t inequality as such. It’s the poverty and deprivation suffered by those who have least.

Professor Frankfurt’s essay didn’t persuade all his fellow philosophers, many of whom remained egalitarians. But his challenge continued to resonate and, in 2015, even as concerns about economic inequality were growing in many corners of society, he published a short book in which he reaffirmed his position.

And Professor Frankfurt, it seems, has a point. Those in the top 10 percent of America’s economic distribution are in a very comfortable position. Those in the top 1 percent are in an even more comfortable position than those in the other 9 percent. But few people find this kind of inequality troubling. Inequality bothers us most, it seems, only when some are very rich and others are very poor.

Even when the worst-off people are very poor, moreover, it wouldn’t be an improvement to reduce everyone else to their level. Equality would then prevail, but equal misery is hardly an ideal worth striving for.

We are having trouble retrieving the article content.

Please enable JavaScript in your browser settings.

Thank you for your patience while we verify access. If you are in Reader mode please exit and  log into  your Times account, or  subscribe  for all of The Times.

Thank you for your patience while we verify access.

Already a subscriber?  Log in .

Want all of The Times?  Subscribe .

• Search Search Please fill out this field.

What Is Economic Inequality?

Understanding economic inequality, is economic equality desirable.

• Exploring the Reasons
• Economic Inequality and COVID-19

Economic Inequality and Health

Fixing economic inequality, the bottom line, what is economic inequality definition, causes, and key statistics.

Amy Fontinelle has more than 15 years of experience covering personal finance, corporate finance and investing.

Katrina Ávila Munichiello is an experienced editor, writer, fact-checker, and proofreader with more than fourteen years of experience working with print and online publications.

Economic inequality refers to disparities among individuals' incomes and wealth. And those differences can be great. Forbes counted a record 2,781 billionaires in the world as of 2024. Meanwhile, the World Bank estimates that more than 700 million people globally are living on less than $2.15 per day. That's actually a big improvement from 1990, when over 1.9 billion people lived in extreme poverty and the world had only 269 billionaires.

Some will look at these numbers as evidence that a rising tide lifts all boats. Over the past 30 years, global wealth has increased; overall, living standards have improved. And others will look at these numbers and think it's inexcusable that anyone lives in poverty when the world's billionaires are worth a combined $14.2 trillion. Of course, both statements can be simultaneously true.

Key Takeaways

• A basic definition of economic inequality refers to the disparities in incomes and wealth in a society.
• Most Americans believe in meritocracy, the idea that people advance in wealth and status through hard work, not privilege, but inequality of opportunity can limit upward mobility.
• The COVID-19 pandemic has highlighted economic inequalities. Chronically marginalized groups are contracting and dying from the virus at higher rates, and those who can't afford health insurance—as well as workers in demanding and dangerous but low-paid "essential" jobs—are at greater risk.
• Well-educated and well-informed people disagree about whether economic inequality should be reduced, to what extent, and through what means.

Disparities like these—and the ones many people see in their everyday lives, where people experiencing homelessness or housing insecurity live in tent cities only miles from fancy condos—give rise to questions about economic inequality. What is it? How and why does it happen? Is it the natural order of things, or is the system rigged? Should attempts be made to make things more equal—for instance, by increasing taxes on higher incomes , as Sweden has? And is the pandemic going to make this inequality worse?

We don't have the answers. The causes of economic inequality are multifarious, and our society hasn't reached a consensus on what, if anything, to do about it, with political deadlock keeping things as status quo for the time being. What we can offer is some background and insight on the state of economic inequality in this country.

The essence of economic equality is how much money the least well off make compared to the most well off—and how wealth is distributed in a society. What assets do people own to tide them over during difficult times and to help them invest in new opportunities? These differences matter for several reasons.

Let's look first at the psychological aspect of economic inequality. We all compare ourselves to others. How satisfied we are with our income or net worth depends not just on how low or high those figures are, nor purely on what we can buy with our incomes or how comfortable our wealth makes us.

Instead, our satisfaction depends, in part, on how our income and wealth compare to that of others: our neighbors, colleagues, friends, siblings, classmates, and bosses. Let's take an accountant we'll call Lorenzo as an example. Lorenzo may be perfectly happy earning $70,000 a year in his accounting job—but only until he learns that his colleague and fellow accountant Sebastian is earning $80,000. The inequality feels unfair. It makes him unhappy; maybe even angry.

Lorenzo confronts Sebastian, asking him what he's doing to earn an extra $10k a year. He points out that they both have the same amount of experience, they started working at the firm at around the same time, and they do the same job.

In response, Sebastian says that it's a bigger deal that their CEO earns $60 million. Plus, their friend Marco, who works in customer service through a contractor their firm hires, only makes $20 an hour and doesn't get the same benefits as they do. No health insurance. No 401(k). Only 10 days of paid time off per year, and he has to choose between using those for vacation, personal time, or sick leave.

A big driver of economic inequality is a persistent wealth and income gap observed between men and women and with whites and non-whites. While these gaps have been closing in recent years, pervasive racism beginning with slavery and continuing through the Jim Crow era has led to enormous inequalities between white and black households that remain to this day.

Lorenzo has an explanation for Marco's position and pay. Marco didn't go to college, whereas Lorenzo and Sebastian worked hard in high school and got into good universities. On top of that, they both became certified public accountants , which meant putting in a lot of extra work, taking extra exams, and spending a lot of money to get their certifications. It wouldn't make sense for Marco to earn $75,000. He didn't do any of that. That's the way the system works.

Most Americans would agree. They would say that even though Lorenzo and Sebastian are both single and Marco is supporting his partner and two children—so, arguably, Marco needs the higher income more than Lorenzo and Sebastian do—they don't like the idea of "from each according to his ability, to each according to his needs." That's the communist credo, and communism, after taking hold in the Soviet Union in 1917, led to millions of government-ordered executions, mass starvation, war, and widespread human misery. (However, there are those who would argue that the problem is not the communist philosophy itself, but its historical implementation under brutal dictators.)

Back to our accountants. Lorenzo doesn't think it's fair to give $15,000 of his $70,000 salary to Marco so they can each earn an equal $55,000 a year. Sebastian doesn't want to give up that kind of money, either. Although he doesn't have a partner or kids, he does have a mortgage to pay, and he wants to go back to school to earn an MBA . That's not cheap. He doesn't want to support someone else's kids. If he were only going to earn $55,000 a year, he wouldn't have bothered to become a CPA.

How Does Economic Inequality Happen?

We've seen that one reason economic inequality is a problem is that we compare ourselves to others. We feel bad when we find out that other people have more than we do, especially when we're similar to those people. People need incentives to work hard, and they feel they deserve to keep what they earn. They also believe in meritocracy, the idea that people advance in wealth and status through hard work, not through privilege. But how would Lorenzo and Sebastian feel if they learned more about Marco's life story?

Marco grew up in a semi-rural community. The schools he attended were slightly below average, and he didn't have any choice about where to get his education. His dad stocked shelves at the local grocery store. His mom was a restaurant server. Neither of his parents finished high school. They couldn't help him with his homework. They often worked nights and weekends. Marco's grandparents watched him during those times, and he played with the neighborhood kids. In high school, he got a job as a busboy at the restaurant where his mom worked. His friends were good kids, but none of them ever talked about going to college. Most adults in their lives were not college graduates. No one expected Marco or his friends to go to college or enter a white-collar profession.

Lorenzo and Sebastian both grew up in cities. Sebastian's parents lived in an upper-middle-class neighborhood with great public schools. Lorenzo's parents took advantage of a school choice program to get him into better schools. Both boys' teachers saw promise in them and encouraged them to take advanced classes. They didn't always get straight As, but they did get good enough grades to get into name-brand colleges. Plus, all their friends were going to college. Their teachers expected them to go and helped them prepare.

For these three men, inequality of opportunity led to where they are today. None of them did anything wrong. Nor did their parents do anything wrong. But Sebastian benefited from the intergenerational wealth that allowed him to grow up in a nice area with quality schools. Lorenzo benefited from having access to those schools and growing up alongside kids like Sebastian whose parents expected their children to attend college and pursue corporate careers with good pay and benefits. Marco had none of these advantages.

This example is just one way economic inequality can happen. However, it happens, the life consequences are substantial.

Source: Board of Governors of the Federal Reserve System.

How the COVID-19 Pandemic Has Exposed Economic Inequality

The everyday threat of COVID-19—a highly contagious, sometimes deadly virus that no one is known to have lasting immunity to—has made more people aware of the economic inequalities in our society. Examples are accumulating: There's the legacy of abuse and marginalization of Latinx Americans, black Americans, and Native Americans, all groups getting infected and dying from the virus at rates far higher than whites. And there's the low pay received by workers in demanding and dangerous jobs. Meat processors and slaughterers, who earn a mean hourly wage of $15.00 as of May 2020 ($31,210 annually), according to the U.S. Bureau of Labor Statistics, have been disproportionately infected by COVID-19 outbreaks at work.

On March 19, 2020, Christopher Krebs, director of the U.S. Department of Homeland Security's Cybersecurity and Infrastructure Security Agency, issued a memorandum identifying the "essential critical infrastructure workers," commonly referred to as "essential workers," whose jobs are key for protecting public health and safety and economic and national security. "The industries they support represent, but are not necessarily limited to, medical and healthcare, telecommunications, information technology systems, defense, food and agriculture, transportation and logistics, energy, water and wastewater, law enforcement, and public works," the memo states.

This list is not a mandate, but it provides advice to the states on who should keep going to work and who should stay home to help prevent the spread of the disease. The goal? To "flatten the curve," to avoid overwhelming the healthcare system such that sick people cannot receive potentially life-saving treatment. The memo also encourages remote work where possible and provides strategies to reduce the spread of disease among those who cannot work remotely.

Following the release of a memo from Homeland Security regarding essential workers and COVID, there's been evidence that many employers have not provided adequate protection to keep essential workers from catching and spreading COVID-19. In part, the problem can be attributed to the global lack of pandemic preparedness and, according to national press reports, massive shortages in personal protective equipment, even for medical providers. But what is also evident is that economic inequality has made a bad situation much worse for many workers.

Some have continued going to their high-risk jobs because they feel they have no choice: Their families rely on their wages. A 62-year-old California woman told the Los Angeles Times how she kept going to her $13.58-an-hour job washing laundry at a nursing home even though her husband, who has underlying heart problems, didn't want her to. She said she had to support her family; they all got the virus.

Situations like these have led some to say that those deemed essential workers are really being treated as expendable workers. Hazard pay, where it's been offered, has been deemed insufficient; it may also soon prove temporary. Some employers, perhaps most notoriously airlines, have even forbidden their workers to wear face masks and kept them in the dark about on-the-job exposure to the virus.

Some people have gone to work with COVID-19 symptoms because their employers don't provide the pay, benefits, or sick leave they need to take time off and get healthcare. Millions have been forced into unemployment by stay-at-home orders, so while they may be safer from the coronavirus, they don't have money to pay their bills unless they have robust emergency savings, and most people don't . The unemployed also may not have health insurance to get treatment if they get sick, since affordable, high-quality health insurance in the United States is often tied to employment, even with the Affordable Care Act (ACA).

Let's return to the story of our fictional workers. Marco, a customer service representative at an office that has closed down due to the pandemic, is technically able to work from home. But the company doesn't have enough work for all its reps because business has slowed so much. So he has been let go and is struggling to collect unemployment compensation from an overloaded system. Meanwhile, Lorenzo and Sebastian have continued to perform their well-paid accounting jobs from home. They also still have the health insurance that their employer never offered Marco because he works through a contractor and is not an employee of the firm. He does have an Affordable Care Act exchange plan, but he's not sure how he'll keep paying the premiums.

Going without health insurance is a huge risk for anyone, but it's an extra risk for Marco, who suffers from asthma. In fact, so do lots of the people he grew up with, maybe because many of their parents smoked, maybe because the outdoor air quality downwind of the chemical plant near their neighborhood was poor. Lorenzo and Sebastian didn't have these disadvantages. They've also got some luck on their side, and they don't have underlying health conditions.

This is yet another aspect of economic inequality that's become starker due to the pandemic: the higher prevalence of underlying health conditions such as asthma and high blood pressure in lower-income individuals and people of color because they are marginalized their entire lives. These populations are at an even more elevated risk of dying in the pandemic because their underlying health conditions predispose them to adverse outcomes from COVID-19 and they're also more likely to be exposed to it at work.

Is economic inequality something we should try to fix? In the United States, this question has become a heated political issue. It encompasses issues such as progressive taxation , universal healthcare coverage , unemployment insurance , basic income , Medicaid , and COBRA health insurance . Some people think the United States should adopt more elements of the Nordic model and strengthen its social safety net. Others feel this model is too socialist and prefer a more capitalist model . They don't want to pay the higher taxes that would be required to fund more social programs, and they argue that filling the gaps through the work of private charities is a better solution.

A 2018 academic study found that a combination of both taxes and charitable giving is necessary to meet a community's needs. It also found that Republicans and Democrats differ in the total amount of income redistribution they think society needs and the amount they're willing to allocate to taxes versus donations.

Most people are willing to pay taxes, but they differ in how much they're willing to pay to reduce economic inequality. Lorenzo and Sebastian like to think that the taxes they're paying on the money they are still earning are helping people like Marco right now through federal and state income security programs. Some of their tax dollars also help support their grandparents through Social Security and Medicare .

In addition, Lorenzo and Sebastian are each currently donating 10% of their pay to local nonprofits that are helping people who are unemployed get through the pandemic. They feel a need to contribute to their local community since part of the reason they're able to keep working comes down to luck, and they don't think others who are out of work should suffer because of bad luck.

Which Country Has the Most Economic Inequality?

Brazil has the most economic inequality as of 2024, with a Gini coefficient of 52.9. Colombia, Angola, and Panama also stand out with extremely high levels of inequality. The United States is ranked #28 in economic inequality, with a Gini coefficient of 39.7.

How Do You Measure Economic Inequality?

Economic inequality is measured by the Gini coefficient, a mathematical index that measures the wealth disparity of a country. A Gini coefficient of zero indicates a perfectly equal society (everyone has exactly the same wealth level). A Gini coefficient of 1 (or 100%) is a perfectly unequal society, where one individual holds all wealth.

Why Is Economic Inequality a Problem for Society?

Countries with high levels of income inequality may have a large population living in poverty, with negative consequences for public health and crime. Moreover, high levels of inequality can degrade social cohesion and lead to political polarization, and harm economic growth. These problems can have negative effects, even for those members of society who are relatively well-off.

Economic inequality is a tricky issue. Some level of inequality may be natural. Marco didn't choose the circumstances he was born into any more than Lorenzo and Sebastian did. But societal forces may have determined the circumstances they were born into, then perpetuated their unequal circumstances, even as other forces also helped Marco get a job that pays relatively well for someone without a college degree. But then, why shouldn't Marco have had access to the same opportunities his coworkers did? The issues of fairness and equality of opportunity lie beneath the issue of economic inequality and the degree to which it's natural, inevitable, acceptable, or even desirable. It's up to each of us to decide what we want economic equality or inequality to look like, then vote and spend our dollars accordingly.

Forbes. " World's Billionaires List: The Richest in 2024 ."

World Bank. " Poverty: Overview ."

Forbes. " The World's Billionaires: 25th Anniversary Timeline ."

World Bank Group. " Piecing Together the Poverty Puzzle ," Page 2.

Karl Marx. " Critique of the Gotha Program ." Progress Publishers, 1970.

Federal Reserve Board of Governors. " Improving the Measurement of Racial and Ethnic Disparities in the Survey of Consumer Finances ."

Centers for Disease Control and Prevention. " Introduction to COVID-19 Racial and Economic Disparities ."

Centers for Disease Control and Prevention. " COVID-19 Among Workers in Meat and Poultry Processing Facilities—19 States, April 2020 ."

U.S. Bureau of Labor Statistics. " 51-3023, Slaughterers and Meat Packers ."

U.S. Department of Homeland Security. " Memorandum on Identification of Essential Critical Infrastructure Workers During COVID-19 Response ."

Vox. " 'I Did Not Sign Up for the Military. I Signed Up for Walmart' ."

New York Times. " 'At War With No Ammo’: Doctors Say Shortage of Protective Gear Is Dire ."

Los Angeles Times. " The Price of Being 'Essential': Latino Workers Bear Brunt of Coronavirus ."

Milwaukee Independent. " Expendable Workers: Being Called 'Essential' Only Describes the Work and Not the People Doing It ."

Los Angeles Times. " 15 Deaths in the Airline Industry in 9 Days Linked to Coronavirus. Why Are Planes Still Flying? "

Current Opinion in Allergy and Clinical Immunology. " Asthma and Ethnic Minorities: Socioeconomic Status and Beyond ."

The American Journal of the Medical Sciences. " Racial Differences in Hypertension: Implications for High Blood Pressure Management ."

Economic Policy Institute. " Not Everybody Can Work From Home ."

Sage Journals. " The Politics of Donations: Are Red Counties More Donative Than Blue Counties? "

The New York Times. " How Political Ideology Influences Charitable Giving ."

World Population Review. " Economic Inequality By Country 2024 ."

International Monetary Fund. " Introduction to Income Inequality ."

• Terms of Service
• Editorial Policy
• Privacy Policy

Economic Inequality

By: Joe Hasell , Pablo Arriagada , Esteban Ortiz-Ospina and Max Roser

How are incomes and wealth distributed between people? Both within countries and across the world as a whole?

On this page, you can find all our data, visualizations, and writing relating to economic inequality.

This evidence shows us that inequality in many countries is very high and, in many cases, has been on the rise. Global economic inequality is vast and compounded by overlapping inequalities in health, education, and many other dimensions.

But economic inequality is not rising everywhere. Within many countries, it has fallen or remained stable. And global inequality – after two centuries of increase – is now falling too.

The large differences we see across countries and over time are crucial. They show us that high and rising inequality is not inevitable, and that the extent of inequality today is something that we can change.

Explore Data on Economic Inequality

Interactive visualization requires JavaScript.

About this data

This data explorer provides a range of inequality indicators measured according to two different definitions of income obtained from different sources.

• Data from the World Inequality Database relates to inequality before taxes and benefits.
• Data from the World Bank relates to either income after taxes and benefits or consumption, depending on the country and year.

Further information about the definitions and methods behind this data can be found in the article below, where you can also explore and compare a much broader range of indicators from different sources:

OWID Data Collection: Inequality and Poverty

Explore a wide range of indicators on inequality and poverty and compare sources.

Research & Writing

How has income inequality within countries evolved over the past century?

While the steep rise of inequality in the United States is well-known, long-run data on the incomes of the richest shows countries have followed a variety of trajectories.

Income inequality before and after taxes: How much do countries redistribute income?

The redistribution of income achieved by governments through taxes and benefits varies hugely.

Income Inequality Over the Long-run

How has inequality in the United Kingdom changed over the long run?

How unequal were pre-industrial societies?

Global inequality.

The history of global economic inequality

Global Inequality of Opportunity

Global economic inequality: what matters most for your living conditions is not who you are, but where you are

How is inequality defined and measured.

Joe Hasell and Pablo Arriagada

Measuring inequality: what is the Gini coefficient?

Interactive charts on economic inequality, cite this work.

Our articles and data visualizations rely on work from many different people and organizations. When citing this topic page, please also cite the underlying data sources. This topic page can be cited as:

BibTeX citation

Reuse this work freely

All visualizations, data, and code produced by Our World in Data are completely open access under the Creative Commons BY license . You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

The data produced by third parties and made available by Our World in Data is subject to the license terms from the original third-party authors. We will always indicate the original source of the data in our documentation, so you should always check the license of any such third-party data before use and redistribution.

All of our charts can be embedded in any site.

Our World in Data is free and accessible for everyone.

Help us do this work by making a donation.

• Search Menu
• Sign in through your institution
• Author Guidelines
• Submission Site
• Open Access
• Why Submit?
• About International Studies Review
• About the International Studies Association
• Editorial Board
• Advertising and Corporate Services
• Journals Career Network
• Self-Archiving Policy
• Dispatch Dates
• Journals on Oxford Academic
• Books on Oxford Academic

Article Contents

Introduction, theoretical predictions, what the empirical evidence says, empirical challenges, acknowledgments.

• < Previous

On the Impact of Inequality on Growth, Human Development, and Governance

• Article contents
• Figures & tables
• Supplementary Data

Ines A Ferreira, Rachel M Gisselquist, Finn Tarp, On the Impact of Inequality on Growth, Human Development, and Governance, International Studies Review , Volume 24, Issue 1, March 2022, viab058, https://doi.org/10.1093/isr/viab058

• Permissions Icon Permissions

Inequality is a major international development challenge. This is so from an ethical perspective and because greater inequality is perceived to be detrimental to key socioeconomic and political outcomes. Still, informed debate requires clear evidence. This article contributes by taking stock and providing an up-to-date overview of the current knowledge on the impact of income inequality, specifically on three important outcomes: (1) economic growth; (2) human development, with a focus on health and education as two of its dimensions; and (3) governance, with emphasis on democracy. With particular attention to work in economics, which is especially developed on these topics, this article reveals that the existing evidence is somewhat mixed and argues for further in-depth empirical work across disciplines. It also points to explanations for the lack of consensus embedded in data quality and availability, measurement issues, and shortcomings of the different methods employed. Finally, we suggest promising future research avenues relying on experimental work for microlevel analysis and reiterate the need for more region- and country-specific studies and improvements in the availability and reliability of data.

La desigualdad es un desafío importante para el desarrollo internacional. Esto es así desde una perspectiva ética y debido a que la mayor desigualdad se percibe como perjudicial para los resultados políticos y socioeconómicos clave. Aun así, los debates informados requieren pruebas claras. Esta revisión contribuye estudiando la situación y ofreciendo un resumen actualizado del conocimiento actual sobre el impacto de la desigualdad de ingresos, específicamente en tres resultados importantes: (1) el crecimiento económico; (2) el desarrollo humano, con un enfoque en la salud y la educación como dos de sus dimensiones; y (3) la gobernanza, con énfasis en la democracia. Prestando especial atención al trabajo en economía que se desarrolla particularmente sobre estos temas, este ensayo demuestra que las pruebas existentes están mezcladas de alguna manera y argumenta a favor de promover el trabajo empírico en profundidad en todas las disciplinas. También señala las explicaciones para la falta de consenso que están integradas en la calidad y la disponibilidad de los datos, los problemas de medición y los defectos de los diferentes métodos empleados. Finalmente, sugerimos prometedoras vías de investigación para el futuro que dependen del trabajo experimental para el análisis a pequeña escala, y reiteramos la necesidad de realizar más estudios específicos de la región y el país, así como mejoras en la disponibilidad y la confiabilidad de los datos.

L'inégalité est un défi majeur du développement international. Il en est ainsi d'un point de vue éthique et parce qu'une plus grande inégalité est perçue comme allant au détriment des principaux résultats socio-économiques et politiques. Toutefois, des preuves claires sont nécessaires pour débattre en connaissance de cause. Cette analyse y contribue en faisant le bilan et en offrant une présentation à jour des connaissances actuelles sur l'impact de l'inégalité des revenus, en particulier sur trois résultats importants: (1) la croissance économique, (2) le développement humain, en se concentrant sur la santé et l’éducation en tant que deux de ses dimensions, et (3) la gouvernance, en mettant l'accent sur la démocratie. Cet essai accorde une attention particulière aux travaux en économie qui sont particulièrement développés sur ces sujets et révèle que les preuves existantes sont quelque peu mitigées et plaide pour un travail empirique plus approfondi dans toutes les disciplines. Il met également en évidence des explications du manque de consensus inhérent à la qualité et à la disponibilité des données, aux problèmes de mesure et aux lacunes des différentes méthodes employées. Enfin, nous suggérons des pistes de recherches futures prometteuses qui s'appuieraient sur des travaux expérimentaux pour l'analyse au niveau micro et nous réitérons la nécessité de réaliser davantage d’études spécifiques aux régions et aux pays et d'améliorer la disponibilité et la fiabilité des données.

Recent decades have witnessed sharp rises in inequality of income and wealth in many countries (though neither globally nor everywhere) as well as in the observed level of inequality of opportunities in access to basic services, such as health and education. Concern with these trends is paramount in Goal 10 of the Sustainable Development Goals approved by the United Nations General Assembly in 2015, aiming at “reducing inequality within and among countries.” The COVID-19 pandemic, which has both reflected and exacerbated inequalities, further spotlights this objective.

Pursuing this goal can obviously be justified from an ethical perspective. The case is also made in instrumental terms, with reference to potential negative effects of inequality on a variety of socioeconomic and political outcomes. The World Development Report (2006) drew attention to the implications of high levels of inequality for long-term development ( World Bank 2006 ). Indeed, economists in particular have long been concerned with the relationship between equity and efficiency 1 ; interestingly, the old classical view, contrary to the 2006 report, suggests a contradiction between equality and development.

Informed policy debate requires clear evidence on these impacts. This analytical essay provides a “state-of-art” on research on this big question. While recent reviews of the literature tend to focus on the impact of inequality on one specific outcome, we have a broader scope; we aim to bring new clarity to the debate by taking stock of the current knowledge on the effects on three important outcomes: (1) economic growth; (2) human development, with a focus on health and education as two of its dimensions; and (3) governance, with emphasis on democracy. While we start by highlighting how the various processes are connected, we address the impacts of inequality on these outcomes separately, developing an overview of the core arguments and underlying mechanisms, and of the existing evidence, with a particular focus on cross-country insights.

We draw in particular on the large and well-developed literature on these topics in economics while also taking key insights from other disciplines. 2 Our focus is on broad outcomes that are of particular importance for international development and that received great attention in studies examining the impact of inequality across disciplines. The effects of inequality on economic growth have been extensively debated in economics, the main disciplinary focus of this article. However, health and education—two important channels with high policy relevance—have also been the object of investigation in public health studies. Moreover, the field of political science has greatly contributed to the debate addressing the effects of inequality on political aspects, including those related to democratic governance. 3

Building on previous reviews focusing on specific outcomes (e.g., Voitchovsky 2011 ; Neves and Silva 2014 ; O'Donnell, van Doorslaer, and van Ourti 2015 ; Scheve and Stasavage 2017 ), but adopting the broader outlook of the seminal review by Thorbecke and Charumilind (2002) , this article provides an updated and comprehensive perspective on the consequences of inequality in three core areas of concern for international studies. 4

We combine the main theoretical arguments on the impact of inequality and underlying transmission channels in a general framework, providing a simplified view while emphasizing the connections between different processes. Overall, our review of an extensive body of work suggests there is no clear consensus emerging from the empirical evidence, and we argue there is room for additional in-depth work to uncover the effects through specific mechanisms of transmission. In particular, there is no consensus from the results of studies using reduced-form equations to examine the effect on growth, and less work has been dedicated to exploring the channels of transmission. Moreover, the negative link between inequality and secondary school enrolment is confirmed by the evidence, but further research is needed in terms of other education outcomes. The economic and public health literatures disagree on whether the negative effect of inequality on health is confirmed by the existing evidence, and there are mixed results emerging from political scientists for the effects of inequality on democracy and political participation. We advance the underlying explanations for this state of affairs, related to the challenges inherent in data quality and availability, measurement issues, and shortcomings of the different estimation methods employed, and suggest avenues for further research.

In the second section, we offer an outline of the main theoretical predictions of the effects of inequality on socioeconomic outcomes and on governance, presenting different channels of transmission. The third section follows the same structure and reviews the existing empirical evidence. We reflect on key empirical challenges of estimating the effects of inequality in the fourth section. The fifth section concludes.

Several theoretical explanations exist across disciplines for the effects of inequality on socioeconomic and political outcomes. Before we describe in more detail these channels of influence and the resulting outcomes, we highlight a broader set of arguments, which act as a roadmap for the rest of the section.  Figure 1 provides a schematic overview.

Diagram with main outcomes of inequality

Source : Authors’ elaboration.

Starting from the left- to the right-hand side, the diagram represents different channels of transmission of the effects of higher levels of inequality, their intermediate effects, and the resulting positive or negative impact on our three outcomes of interest: growth, 5 human development, and democracy. We broadly divide these channels according to their underlying drivers: the poor, the population at large or the average, and the wealthy.

Overall, the diagram suggests that high inequality has predominantly harmful effects on our three outcomes of interest, according to theoretical explanations advanced in the literature. The dominant view then runs contra the expectations of the classical theorists, i.e., that inequality has a positive impact on growth, via savings and investment (shown at the top of  figure 1 ). We highlight six main transmission channels.

First, inequality affects incentives for savings and investment and the overall level of institutional quality through its influence on policy making and increased political instability, and consequent effects on property rights and the regulatory framework. This has implications for growth both directly and indirectly via governance.

Second, by favoring private over public investment, inequality affects investment in public goods, namely health and education, with implications across the three outcomes. Third, and related, inequality results in underinvestment on human capital resulting from credit constraints, and high fertility, which affects education levels and overall economic growth.

Fourth, high taxation will be demanded by a well-endowed median voter and the likelihood of transition to and stability of democracy will also depend on the pressure for redistribution, which is higher with lower levels of equality. Moreover, and fifth, a small middle class will affect the demand not only for democracy but also for manufactures.

Finally, high levels of polarization will lead to weak social cohesion via their effects on social capital, as well as low trust and potential high levels in violent crime, which affect health directly and indirectly via investment in public health. Additionally, the concentration of power on the rich leads to increased probability of political violence and affects political engagement.

Some of these channels affect all of the outcomes. For instance, the effect through investment in public goods has detrimental effects on human development, and on growth and democracy. Moreover, the resulting polarization and social discontent, which increase the chances of political violence, again negatively impact the three outcomes. However, there is also some indication that, when it comes to growth, the effect might be ambiguous depending on the predominance of the effects of transmission mechanisms. The channel through savings (and investment) points to a potential positive effect, while the different effects through public investment, taxation, the structure of demand, imperfect credit markets, fertility, and social discontent suggest potential negative consequences for growth.

This section uncovers more details about these different theoretical predictions. It starts by introducing the main hypotheses advanced for the effects of inequality on growth. While the approach in this article considers the three outcomes separately, we recognize that they are not disjointed or orthogonal and refer to the links between them. Nevertheless, a full discussion of these interlinkages is beyond the scope of this article. As suggested in  figure 1 and described in more detail below, some of these channels point to the impact of inequality on our remaining outcomes of interest, namely education and health, or governance. We return to them in the remaining two subsections, where we expand to consider the insights from other strands of literature.

How Inequality Affects Growth

An extensive literature examines the effects of inequality on growth, 6 highlighting multiple channels of transmission. 7 The early studies, referred to as the classical approach, argued that there is a positive effect of inequality on growth, explained via savings or incentives. However, subsequent work questioned this view, challenging some of its assumptions and proposing different channels of influence. Most of this work has predicted a negative effect of inequality. We briefly outline these channels in the next paragraphs and refer to Bourguignon (2015) , Neves and Silva (2014) , and Voitchovsky (2011) for complementary detail and reviews. 8

High inequality is growth enhancing

We start by drawing attention to the view of classical economists on income inequality, according to which there was a contradiction between equality and development (for a discussion of the trade-off between efficiency and equity, see Thorbecke 2016 ). Adam Smith defended that inequality had benefits based on arguments of (1) “trickle-down effects”—the increase in wealth will eventually benefit the poor, (2) incentive effects—inequality is necessary to encourage competition and to provide incentives for innovation, and (3) social stability—the different ranks in wealth distribution ensure peace and stability in society ( Walraevens 2021 , 3–6). The famous Kuznets curve ( Kuznets 1955 ), shaped like an inverted U-relationship between growth and inequality (as per capita income increases), seemed to reinforce this view. 9

Developed in the 1950s and 1960s, the so-called classical approach followed a similar line of thinking, based on arguments related to savings and incentives. The prominent work by Kaldor (1956) suggests a positive link between inequality and growth via saving rates, based on the assumption that the higher the level of income, the higher is the marginal propensity to save ( Aghion, Caroli, and García-Peñalosa 1999 , 1620). At the core of this assumption that the rich have a higher marginal propensity to save relative to the poor are two hypotheses: (1) consumption smoothing cannot occur unless the subsistence level of consumption is achieved, and therefore the poor cannot save, and (2) the possibility to save is conditioned by the previous generations, which leads to a concentration of savings in rich households ( Thorbecke and Charumilind 2002 , 1483).

Under this assumption, the redistribution of resources toward the rich leads to higher savings, which, in turn, improves growth via investment. This link is particularly important if one considers limited borrowing possibilities, initial setup costs, and the large investments involved in risky and high-return opportunities ( Aghion, Caroli, and García-Peñalosa 1999 , 1620; Voitchovsky 2011 , 558). Big investment projects involve large sunk costs, and therefore investment relies on the concentration of wealth in individuals to be able to afford them.

A second argument drew on the role of incentives and on the trade-off between efficiency and social justice mentioned earlier ( Aghion, Caroli, and García-Peñalosa 1999 , 1620). At the microlevel, in a simple moral hazard model, if output depends on unobserved effort, then setting a constant reward (in the form of wage) discourages effort, whereas linking the reward to output can be inefficient due to agents’ risk aversion. The same argument maintains at the aggregate level, assuming identical agents and/or perfect capital markets. As explained by Aghion, Caroli, and García-Peñalosa (1999 , 1620), redistribution will have a direct negative effect on growth as well as a negative indirect effect through the reduction in the incentives to accumulate wealth (resulting from redistribution through income tax).

High inequality has a negative effect on growth

Credit market imperfections and fertility.

The effects of inequality on growth via credit market imperfections and via fertility are linked by their focus on the circumstances of the poor and on human capital investment ( Voitchovsky 2011 ). The first channel addresses the impact of credit imperfections on investment decisions. If one considers the high fixed costs associated with, for instance, education, limitations on the access to credit may lead to underinvestment in human capital, which implies a negative impact on growth ( Neves and Silva 2014 , 3). This was the argument resulting from the Galor and Zeira (1993) model. Assuming that credit markets are imperfect and that investment in human capital is indivisible, they conclude that the distribution of wealth has an impact on aggregate investment in human capital and therefore on growth, both in the short and in the long run.

The reasoning behind the link between inequality and growth through fertility was similar. Poor families might not have the resources to invest in their children's education and, thus, their income depends on having bigger families; for richer families, it might be optimal to invest more in education and, consequently, to have fewer children ( Gründler and Scheuermeyer 2018 , 295). In this line of thinking, de la Croix and Doepke (2003) argued that a high fertility differential between the rich and the poor lowered average education. Thus, inequality leads to lower levels of human capital accumulation via the increased fertility differential and, therefore, to lower growth.

Taxation and regulatory policies

Seminal work by Alesina and Rodrik (1994) as well as Persson and Tabellini (1994) pointed to a negative link between inequality and growth through government expenditure and taxation, combining endogenous growth theory with political economy insights. They proposed two different mechanisms that Perotti (1996 , 151) termed “political” and “economic,” respectively. The Alesina and Rodrik (1994) model drew on the median voter theorem and considered tax revenues equally distributed among all individuals. Given that the tax rate is proportional to income, individuals with a lower share of capital income (relative to labor income) prefer higher taxes. Thus, the more equitable the distribution in the economy, the better endowed is the median voter, and the lower the equilibrium level of taxation. A lower rate of tax corresponds to a higher growth rate, which led them to conclude that there is an inverse relationship between inequality and subsequent economic growth.

Persson and Tabellini (1994) reached the same conclusion considering the role of incentives for productive accumulation and for growth. According to them, the incentives necessary for private savings and investment rely on individuals’ ability to “appropriate privately the fruits of their efforts” ( Persson and Tabellini 1994 , 600), which are in turn influenced by tax and regulatory policies. Inequality gives rise to policies that do not protect property rights or allow full appropriation of returns to investment and is therefore associated with lower economic growth.

Still, this result was defied by Li and Zou (1998) . They offered a more general framework than that proposed by Alesina and Rodrik (1994) , considering that government spending could be directed not only to production services—which entered the production function—but also to consumption services—which entered the utility function. Adding this extension, they showed that a more equal distribution could lead to lower growth via higher taxation and that the effect of income inequality on growth is, therefore, ambiguous.

The view outlined in Alesina and Rodrik (1994) and in Persson and Tabellini (1994) was also challenged by an alternative perspective suggesting that redistributive policies might also have a positive effect on growth in the presence of imperfect credit and insurance markets and that the popular support for these policies decreases with inequality ( Bénabou 2000 ). When combined, these two mechanisms could lead to multiple steady states, while the correlation with growth depends on the balance between incentive distortions and credit constraints ( Neves and Silva 2014 , 4). Voitchovsky (2011 , 556) lists the criticism toward the median voter argument and highlights how the channel through redistribution does not gather consensus.

The structure of demand

Zweimüller (2000) described the role of redistribution on growth through innovation. Building on the assumption of hierarchical preferences, the distribution of income affects the structure of demand: poor people spend mainly on basic needs whereas rich people spend on luxury goods. According to the author, inequality affects growth through its effect on the time path faced by an innovator. When a new and expensive good is introduced in the market, only rich consumers can afford it, until the increasing demand drives the price–wage ratio down (due to economies of scale), opening up the market to mass consumers ( Voitchovsky 2011 , 557). The optimal consumption levels of those affected by redistribution dictate the overall effect of changes in income inequality on long-run growth ( Zweimüller 2000 ). An earlier study by Murphy, Shleifer, and Vishny (1989) had already highlighted the importance of the middle class to the consumption of domestic manufactures and, therefore, to industrialization.

Sociopolitical instability and rent seeking

Another group of studies suggested a link between inequality and growth through sociopolitical instability, drawing attention to the effects on property rights. According to Alesina and Perotti (1996) , social unrest—resulting from social discontent caused by income inequality—can lead to an increasing probability of political violence as well as policy uncertainty and threats to property rights, which, in turn, have a negative impact on investment and thus on growth. Keefer and Knack (2002) claimed that income inequality leads to instability in government policies, namely those related to security of property rights, which affects the decisions of economic actors, and consequently slows the rate of growth. Relatedly, the Glaeser, Scheinkman, and Shleifer (2003) model showed a detrimental effect of inequality on property rights through the subversion of political regulatory and legal institutions by the rich for their own benefit.

The effect depends

Finally, we highlight contributions suggesting that different mechanisms might be present at different points. Galor and Moav (2004) proposed a unified theory between the credit market imperfections and the saving rate channels described earlier. According to them, the positive effect of inequality on growth suggested by classical theories corresponded to early stages of industrialization when physical capital accumulation is the primary driver of economic growth. However, at later stages, human capital accumulation becomes the main determinant of growth and credit constraints are largely binding, which explains the negative link between inequality and growth through credit market imperfections. As credit constraints become less binding due to wage increases, the aggregate effect of income distribution on growth is less significant.

A decade later, Halter, Oechslin, and Zweimüller (2014) presented a parsimonious theoretical model that takes into account both a short-term and a long-term effect of asset inequality. According to them, the short-term effect is positive and it occurs through an economic channel, whereas the long-term effect is negative and stems from a political economy channel.

How Inequality Affects Education and Health

Inequality can have both positive and negative effects on education.

While the literature examining the effects of education on inequality is extensive, the same is not true for studies looking at the other direction of causality. We distinguish between the arguments on the effects of inequality through expenditure on education and through school enrolment and attainment.

The provision of education depends on the willingness of citizens to redistribute resources via taxation, in line with Alesina and Rodrik (1994) and Perotti (1996 ). According to this political economy mechanism, increasing inequality will lead to lower availability of resources, as the rich will prefer not to contribute to public education, favoring private schools ( Mayer 2001 , 5). 10 Gutiérrez and Tanaka (2009) modeled the effect of inequality on school enrolment, and the preferred tax rate and expenditure per student focusing on parents’ decisions in developing countries. According to the authors, beyond a certain level of inequality, there is no longer support for public education. The model shows that, when considering the fact that parents can make a choice of sending their children either to work or to private or public schools, high inequality results in exiting public education, which has implications for the tax rate and expenditure per student. 11

According to the credit market imperfections’ channel discussed in section “How Inequality Affects Growth,” inequality creates obstacles in terms of access to education. In the presence of imperfect credit markets, the distribution of wealth affects the aggregate investment in human capital ( Galor and Zeira 1993 ; García-Peñalosa 1995 ). Additionally, inequality can affect enrolment by determining the number of poor who are able to substitute the return of child labor for school attendance ( Gutiérrez and Tanaka 2009 , 56). The Tanaka (2003) model shows that in contexts of high inequality, there is low support for public provision of schooling, which, in equilibrium, leads to a higher level of child labor.

The expected returns to the family from schooling will also affect the demand for education, as educated children are likely to have higher future income ( Birdsall 1999 , 17). If inequality is induced in part by increased returns to schooling, then there will be an incentive for children to stay in school and one could expect a positive relationship between an increase in inequality and educational attainment ( Mayer 2001 ; Thorbecke and Charumilind 2002 ; Dabla-Norris et al. 2015 ). 12

Inequality negatively affects health

The interest in understanding how income inequality affects health has instigated a broad range of work both in economics and in the fields of public health and sociology, 13 and different hypotheses are available. Generally, they suggest that inequality negatively affects health. Following O'Donnell, van Doorslaer, and van Ourti (2015) and Leigh, Jencks, and Smeeding (2011) , we distinguish between hypotheses that imply that the health of all individuals is affected and those that do not require that the health of every individual in society is under threat. 14

The first group of hypotheses proposes three different channels: public goods provision, social capital, and violent crime. 15 The effect through public goods provision can be negative or positive ( Leigh, Jencks, and Smeeding 2011 , 390). There will be a negative effect if inequality causes a reduction in the average value of publicly provided goods due to more heterogeneous preferences or if it enables the rich to acquire more political influence and, consequently, to pressure for a reduction in public spending on health. However, it can also be positive, given that as inequality increases among voters, the median voter will tend to support spending on health.

The effect through social capital builds on the assumption that income inequality leads to decreased social cohesion and, therefore, affects health through social 16 and psychosocial support, mechanisms of informal insurance, and diffusion of information ( O'Donnell, van Doorslaer, and van Ourti 2015 , 1501). Low trust can lead to disbelief about the improvements in health via public spending and links to higher mortality via smaller friendship networks as well ( Leigh, Jencks, and Smeeding 2011 , 390). Finally, although only a small percentage of deaths in developed countries results from violent crime, Leigh, Jencks, and Smeeding (2011 , 389) highlight the potentially larger secondary effects via increased stress about experiencing crime in the future. 17

In the second group of hypotheses, health depends on income at the individual level. The Wagstaff and van Doorslaer (2000) seminal review describes different interpretations. First, the absolute income hypothesis, which was also termed the “income artefact” hypothesis, suggests that the observed correlation between inequality and health is a result of the concave relationship between income and health; that is, the health gains of an additional unit of income are diminishing in an individual's income level. The term “artefact” applies to the fact that a redistribution of income leads to an increase in average population health even though there is no effect on the health of any individual, given their income. Second, the relative income hypothesis builds on the idea that psychosocial effects that result from individuals comparing their income with that of others (the mean income of the population or the community) affect health. Third, the deprivation hypothesis is a variation of the relative income hypothesis, and it argues that the crucial aspect is the extent of deprivation measured by the income gap. Fourth, and related, the relative position hypothesis states that what is important is the position of the individual in the income distribution.

How Inequality Affects Democratic Governance

In this section, we delve more deeply into the relationship between inequality and governance outcomes, democracy in particular, which have attracted considerable attention, especially within political economy and political science (see Bermeo 2009 ; Karl 2000 ). We start by focusing on the effects on democratic stability and democratic transition and then zoom in on the effects on political participation.

First, we refer back to the link between inequality and growth through political instability and social conflict described in section “High inequality has a negative effect on growth”. As highlighted by Fukuyama (2011 , 84), “[a] more likely reason why inequality is bad for growth is directly political: highly unequal countries are polarized between rich and poor, and the resulting social conflict destabilizes them, undermines democratic legitimacy, and reduces economic growth.” The summary in Thorbecke and Charumilind (2002 , 1486) suggests two main mechanisms: the relative deprivation hypothesis and resource mobilization. According to the first, discontent resulting from the gap between individual expected and achieved well-being leads to collective political violence. Inequality might deepen the grievances of certain groups or reduce the opportunity cost of engaging in violent conflict ( Dabla-Norris et al. 2015 , 9). Nevertheless, the second mechanism points to the ability of dissident groups to organize themselves as the key element.

The theoretical literature largely suggests negative effects of inequality on the likelihood of transition to and stability of democracy. It attributes an important role to democratic values and access to education, which are more likely to characterize citizens and the situation in equal societies, and to the middle class, which is more likely to promote tolerance and avoid extremist positions ( Houle 2015 , 145).

Two of the most prominent arguments for the link between inequality and democracy were presented in Boix (2003) and Acemoglu and Robinson (2006) . 18 The former argues that increasing levels of economic equality lead to a higher probability of democracy through redistribution. According to the theoretical predictions, the pressure for redistribution from the poor decreases with higher levels of equality, which means that a turn to democracy would be less costly for the holders of the most productive assets; that is, the payment of tax is less costly than repression.

The Acemoglu and Robinson (2006) predictions indicate a nonlinear, inverted U-shaped relationship. On the one hand, greater intergroup inequality increases the appeal of a revolution for citizens to increase their share in the income of the economy, thus increasing the likelihood of democracy. On the other hand, higher inequality also means higher aversion to democracy by elites as their tax burden is greater, thus discouraging democratization. Accordingly, the authors suggested that, for high levels of equality, there is no incentive for citizens to challenge the system and the interests of the elites are preserved. In societies with high levels of inequality, citizens try to rise up against the system, but this meets great repression from the elite, leading to a repressive non-democracy or a revolution, in certain cases. Therefore, the likelihood of democracy is higher for middle levels of inequality.

However, Houle (2009) highlighted three problems with these theories. First, they do not apply to transitions that are driven from above (e.g., from intra-elite competition). Second, the net effect of inequality is ambiguous because it makes redistribution more costly for the elites but, at the same time, it increases the population's demand for regime change. Finally, they ignore collective action problems and the challenges of mobilizing the population. More recently, Ansell and Samuels (2010) departed from Boix (2003) and Acemoglu and Robinson (2006) and proposed a contractarian approach that placed the focus on the citizens’ demand for protection against expropriation. According to these authors, democracy emerges from land equality and income inequality.

We briefly refer to a related group of studies examining the link from inequality to institutional quality and refer to Chong and Gradstein (2019) for details. Chong and Gradstein (2007 , 2019 ) argue that there is double causality: while inequality leads to subversion of institutions through the political power of the elite, poor institutional quality also causes a higher level of inequality. Furthermore, Kotschy and Sunde (2017) have proposed that inequality interacts with political institutions in shaping institutional quality. Some have also suggested that a link exists between inequality and corruption, via self-reinforcing mechanisms and social norms (e.g., Jong-sung and Khagram 2005 ) as well as via low trust (e.g., Rothstein and Uslaner 2005 ). 19

Finally, a strand of studies in political science has argued that there is a link between inequality and political participation. As reviewed in Solt (2008) , the theoretical predictions lead to different possible outcomes of economic inequality on political engagement 20 : a negative effect, a positive effect, or an effect that depends on the level of income of the individual. The first outcome is a result of the concentration of power: societies that are more unequal have a higher concentration of power, which has implications for how the issues that separate the rich from the poor are addressed in the political sphere. The rich will have a lower need to engage in the political process whereas the poor will feel removed from politics. The prediction of a positive effect results from the fact that the divergence in the views of the rich and the poor will be more apparent in societies with higher inequality, which should lead to higher participation in the political process. Finally, the last prediction hinges on the fact that political engagement entails the use of resources. Thus, with higher levels of inequality, one should expect greater engagement from the rich, who have more resources available, and lower political engagement from the poor. 21

We now move on to discuss the main insights from empirical analyses following the structure of the previous section. Although we focus here on cross-country analysis, which makes up a significant part of the evidence base, we also refer to studies examining these links at the regional level, especially in the United States.

Direct link

where |$g$| is the average annual growth rate, frequently measured as the log difference of gross domestic product (GDP) per capita; INEQ is a measure of income inequality (usually the Gini coefficient); Z m is a set of other variables commonly used in standard growth regressions; and u is the usual error term. This was then estimated, typically using basic ordinary least squares. To avoid reverse causation, inequality was measured at the beginning of the time span for growth, which usually considers a period of twenty to thirty years, and in some cases, authors employed instrumental variables to address endogeneity concerns.

Summary of results from selected empirical work testing the link between inequality and growth

Notes : DS, Deininger and Squire (1996) ; LIS, Luxemburg Income Study; OLS, ordinary least squares; 2SLS, two-stage least squares; WLS, weighted least squares; 3SLS, three-stage least squares; LSDV, least squares dummy variable; FE, fixed effects; RE, random effects; Sys-GMM, system GMM; Diff-GMM, difference GMM.

Source : Authors’ elaboration, inspired from Cingano (2014) and Neves and Silva (2014) .

The aim was to estimate the coefficient of the income inequality variable δ , and most of these studies found a negative effect of inequality on growth. Persson and Tabellini (1994) obtained evidence for this effect using historical panel data and postwar cross-sectional analysis. Both the studies by Alesina and Rodrik (1994) and Clarke (1995) confirm this relationship using data from, among others, Jain (1975) and Lecaillon et al. (1984) . Clarke (1995) showed that this was robust to different measures and empirical specifications.

Given the challenges imposed by scarce data, some authors turned to an analysis between states in the United States. Partridge (1997) tested the robustness of the Persson and Tabellini (1994) findings, and the results suggested a positive link between inequality and subsequent growth when considering either the Gini coefficient or the share of income of the middle quintile. 23 Using tax data at the state level for the period 1940–1980, Panizza (2002) warned that both the data and the methodology used led to significant differences in the estimated coefficients for the effect of inequality on growth.

While the quality and reliability of the data are important challenges pertaining to early studies ( Knowles 2005 ), the introduction of an improved and expanded dataset by Deininger and Squire (1996) led to a surge in new studies using panel estimators. In contrast with previous work, these studies found a positive link between inequality and growth. Li and Zou (1998) showed that the coefficient for lagged Gini has a positive sign and is significant in most growth regressions. Forbes (2000) confirmed this result using similar data and generalized method of moments (GMM) estimators. 24 Still, using the same dataset, Deininger and Squire (1998) found a negative effect of initial income inequality on growth, although the coefficient lost significance once they add regional dummies to the specification.

Offering a starting point to reconcile the differing views, some studies have argued that the relationship between inequality and growth depends on other factors. According to Barro (2000) , the effect of inequality on growth depends on the level of income of the country: panel evidence suggests growth-enhancing effects of inequality in richer countries (GDP per capita: above $2,000, 1985 US dollars) and negative effects in poorer countries (below $2,000). Moreover, Banerjee and Duflo (2003) have raised concerns about the functional form used in the literature, arguing against using a linear specification for the relationship between inequality and growth. Their empirical work suggests an inverted U-shaped function between changes in inequality and lower future growth rates. Using a small sample of industrialized countries, Voitchovsky (2005) showed empirical support for the hypothesis that the profile of inequality influenced its relationship with growth: top-end inequality seems to have a positive effect and bottom-end inequality a negative effect.

The debate has continued in the literature ever since. Cingano (2014) lends support to a negative effect of inequality on growth using data from the Organization for Economic Co-operation and Development (OECD) income distribution dataset. Additionally, the author suggests that reducing inequality by focusing on income disparities at the bottom of the income distribution has a greater positive effect on growth than by focusing on the top of the distribution. The Castelló-Climent (2010) results concur with this when considering the full sample of countries, but the results also find support for the argument of a differentiated effect according to the level of development. Halter, Oechslin, and Zweimüller (2014) argue that there is a time dimension to the link between inequality and growth, showing a positive coefficient for the current Gini coefficient and a negative coefficient for lagged Gini.

Some studies have used data from an additional dataset proposed by Solt (2009) , the Standardized World Income Inequality Database (SWIID). Yet, results also mirror the lack of consensus of earlier work. Applying system GMM, work from the International Monetary Fund finds a robust negative effect of inequality on growth ( Ostry, Berg, and Tsangarides 2014 ; Berg et al. 2018 ). While Gründler and Scheuermeyer (2018) concur with this result, Jäntti, Pirtillä, and Rönkkö (2020) raise concerns about the results in Berg et al. (2018) , resulting from the use of the SWIID dataset. El-Shagi and Shao (2019) criticize previous studies using system GMM and argue for the advantages of using a least-squares dummy variable estimation instead. In contrast, their results show a positive effect of inequality on growth over the medium term, primarily driven by market-based inequality.

Barro's (2000) view that the effect depends on the level of development in the country, confirmed in later analysis by the same author using the WIID dataset ( Barro 2008 ), has also been verified in some recent work. Gründler and Scheuermeyer (2018) see a negative and significant marginal effect of net inequality on growth in poor economies, which is, however, nonsignificant in high-income countries. 25

Channels of transmission

As discussed in section “How Inequality Affects Growth,” the theory proposes different channels through which inequality may affect growth. Although these specific mechanisms have received less attention in empirical work, we highlight the main findings, also summarized in  table 2 .

Summary of empirical evidence on the different channels linking inequality and growth

Starting with the savings channel, while there is evidence of a positive link between inequality and personal savings when using household micro-data, studies based on cross-country aggregate data have found mixed results (see references in Thorbecke and Charumilind, 2002 ). Barro (2000) found that the investment ratio does not depend significantly on inequality. The channel via market imperfections and borrowing constraints found support in Deininger and Squire (1998) , who added that the effect through the investment in human capital seems more important than that via physical capital, as well as to some extent in Perotti (1996 ). 26 This channel also suggests that asset inequality matters for growth ( Ravallion 2001 , 1810), shown in both Birdsall and Londoño (1997) and Deininger and Olinto (2000) .

Moreover, there is published support for the channels related to sociopolitical instability ( Perotti 1996 ). Using data from a sample of seventy-one countries over the period 1960–1985, Alesina and Perotti (1996) found that a wealthy middle class is associated with lower levels of political instability, conducive to higher investment. Keefer and Knack (2002) showed evidence of a negative effect of inequality on growth and suggested that property rights are an important channel for this relationship.

Perotti (1996 ) confirmed the link between inequality and growth via fertility. Testing the same hypothesis, de la Croix and Doepke (2003) used Deininger and Squire's (1996) improved dataset and showed that the negative and significant effect of initial inequality on subsequent growth does not survive the inclusion of the differential fertility variable, which is negative and significant. They interpret this as meaning that the differential fertility is an important factor explaining the link between inequality and growth.

The fiscal policy channel received less support by Perotti (1996 ) while Persson and Tabellini (1994) also obtained coefficients with the expected sign but statistically insignificant for the links from inequality to redistributive policies and from redistribution to growth. Sylwester (2000) showed results from cross-country analysis that indicated that higher inequality is associated with higher subsequent expenditures for public education relative to GDP, which in turn has a negative effect on current growth but a long-term positive impact.

Recent studies have shown evidence that corroborates the theoretical effects via human capital accumulation ( Berg et al. 2018 ), via credit market imperfections ( Gründler and Scheuermeyer 2018 ), and via fertility ( Berg et al. 2018 ; Gründler and Scheuermeyer 2018 ) as channels through which inequality affects growth. Using data from twenty-one OECD countries over the period 1870–2011, Madsen, Islam, and Doucouliagos (2018) find support for the hypothesis that income inequality affects growth through different channels, namely savings, investment, education, and ideas production. Additionally, they concur with the arguments on differentiated effects. Although the negative impacts are significant in financially underdeveloped countries, there is little effect of inequality on the four outcomes in countries with highly developed financial markets.

Education and Health

In a recent paper, Castells-Quintana, Royuela, and Thiel (2019) estimated the effects of the Gini coefficient on the human development index (HDI) and found a negative effect in the long run, whereas in the short run the results change for different components of the index: a positive effect on income and a negative effect on educational outcomes. Moreover, they concur with the aforementioned studies that found distinct effects depending on the level of development. We are not aware of any other studies pursuing a similar analysis for the HDI, but in the remainder of this section, we discuss the empirical results on the link between inequality and education and health. We summarize the main conclusions in  table 3 .

Summary of empirical evidence on the different hypotheses on the effects of inequality on education and health

Although there is an extensive body of empirical literature examining education as a determinant of income inequality, the evidence on the link from income inequality to educational outcomes is scarcer ( Thorbecke and Charumilind 2002 , 1488; Gutiérrez and Tanaka 2009 , 56). However, there is evidence that income inequality is reproduced in inequality in education, both in terms of achievements in primary and secondary school and in terms of access to tertiary education (see Buchmann and Hannum 2001 and references in Stewart 2016 ).

Regarding the links proposed in the theoretical work reviewed in the previous section, Sylwester (2000) reported a positive link between inequality and public expenditures on education. Considering the demand side, some studies have found a negative link between inequality and secondary school enrolment. Flug, Spilimbergo, and Wachtenheim (1998) and Easterly (2007) used cross-country analysis, while Esposito and Villaseñor (2018) used data from the 2010 Mexican Census. The study by Madsen, Islam, and Doucouliagos (2018) shows a negative impact of inequality on the combined primary, secondary, and tertiary school enrolment rate in financially underdeveloped countries (using a sample from OECD). Concurring with these findings, Berg et al. (2018) show a negative correlation between inequality and human capital, measured as the average years of primary and secondary schooling. Checchi (2003) provided support for the link between inequality and growth via borrowing constraints and showed evidence of a negative effect of inequality on access to secondary education. 27 Finally, using data from the United States for the period 1970–1990, Mayer (2001) found that the increase in inequality aggravates the gap in educational attainment between rich and poor children.

Given that the literature is extensive and stems from different fields of literature (including, public health), we summarize the main conclusions from different reviews, which distinguish between aggregate level and multilevel studies as well as cross-country and within-country empirical analyses. 28 Wagstaff and van Doorslaer (2000) highlighted that studies at the population level are limited in what they can reveal about the effects on individual health and that data at the individual level are required to disentangle the effects of the different hypotheses described in section “Inequality negatively affects health.” Still, existing evidence on these different channels remains inconclusive.

Lynch et al. (2004) found weak support for a direct effect of income inequality on health, although inequality contributes directly to some health outcomes (e.g., homicides). Furthermore, they underlined that the reduction of income inequality via income rises for the more disadvantaged contributes to improved health of these individuals and increases average population health. Rowlingson (2011) concludes that there is some evidence of an independent effect on health and social problems, but in line with Subramanian and Kawachi (2004) , also highlights the lack of consensus in the results and the need for further work. Still, from a systematic review of 155 published peer-review studies, Wilkinson and Pickett (2006) concluded that there is a link between greater income inequality and poorer health. Almost ten years later, the authors provided further support for the existence of a causal link between income inequality and health and reinforced their argument of the size of status and social class differences as an important mechanism ( Pickett and Wilkinson 2015 ).

The conclusions from the economics literature have pointed to no evidence of a causal relationship ( Nolan and Valenzuela 2019 ). From a detailed review of the literature, Deaton (2003 , 150) argued that “the stories about income inequality affecting health are stronger than the evidence” and that there is no robust evidence showing that income inequality in itself is an important determinant of population health, although it had effects through poverty. The review in Leigh, Jencks, and Smeeding (2011) concurred. However, they warned that given the data challenges and the limitations of the methods used to test the link between inequality and health, one should not jump to definite conclusions. Focusing on morbidity and mortality, the comprehensive review of empirical literature by O'Donnell, van Doorslaer, and van Ourti (2015) concludes that even though population health is negatively associated with income inequality, there is little evidence to support the hypothesis of a negative impact of income inequality on health.

We start this section by noting that the focus on voting underlying the political economy mechanism linking inequality and growth suggests that the effects should be observed in democracies ( Houle 2015 , 143). Thus, some of the early empirical literature on the relationship between inequality and growth also tested whether this effect was dependent on the regime type (e.g., see Alesina and Rodrik 1994 ; Persson and Tabellini 1994 ; Clarke 1995 ; Perotti 1996 ; Deininger and Squire 1998 ).

The results were mixed. Persson and Tabellini (1994) suggested that the negative link between inequality and growth is only present in democracies and that the transmission channel through government redistributive policies should be further investigated. However, Perotti (1996 ) counterargued that, although the data showed a stronger relationship between equality and growth in democracies, the effect of the democracy variable did not appear to be robust. Further criticism was advanced by Knack and Keefer (1997) , who, after some regime reclassification and deletion of doubtful observations, concluded that there is no evidence of a differential effect of inequality on growth in democracies and non-democracies. Østby (2013) and Stewart (2016) argued that there is compelling evidence for the link between horizontal inequality (i.e., inequality among groups) and civil conflict as well as other forms of group violence. However, more recent reviews suggest that the evidence on the link between inequality and political violence is mixed ( Lengfelder 2019 ).

We now turn to what the empirical evidence on the government outcomes described in section “How inequality affects democratic governance” shows, and summarize the main conclusions in  table 4 . Using data from two panels on the periods 1950–1990 and 1850–1980, Boix (2003) showed empirical evidence for a positive link between equality (proxied by an adjusted Gini coefficient) and democratization and, particularly, democratic consolidation. In an extension of this analysis, Boix and Stokes (2003) concluded that economic equality, proxied by farm ownership (distribution of agricultural property) and literacy rates (quality of human capital), has a positive effect on both the probability of a democratic transition and the stability of democracy.

Summary of empirical evidence on the effects of inequality on different governance outcomes

Others found low support for a significant link between the two (e.g., Bollen and Jackman 1985 ). 29 Barro (1999) showed a negative, but only marginally significant coefficient for the effect of inequality on democracy, proxied as electoral rights and civil liberties, for the period 1972–1995. However, when entered alongside the share of income accruing to the middle class, the coefficient is nonsignificant. The empirical analysis in Houle (2009) went against previous results on the negative link between inequality and democracy and showed a weak positive and nonsignificant relationship. Using the capital share of the value added in the industrial sector as a measure of inequality to overcome the data limitations in previous studies, the author also did not find support for Acemoglu and Robinson (2006) ’s inverted U-shaped relationship but rather for a weakly U-shaped one.

More recently, Haggard and Kaufman (2012) used causal process observation to examine the association between inequality and transitions to and from democratic rule and found limited evidence supporting the link via distributive conflict between elites and masses. Additionally, the evidence in Scheve and Stasavage (2017) does not support the hypothesis of a link between wealth inequality and democracy. Dorsch and Maarek (2020) offer an explanation for the abundancy of null results found for the link between inequality and democratization, showing that higher levels of inequality are associated with higher probabilities of democratic improvements following economic downturns (“windows of opportunity”). However, following growth periods, the effect of inequality is null or small and negative.

Considering a broader approach to governance, we briefly refer to the literature linking inequality and institutional quality. 30 Both Easterly (2007) and Chong and Gradstein (2007 ) tested the causal relationship between these variables using an instrumental variables approach and system GMM methods, respectively, and found support for the effect of inequality on institutions. More recently, Kotschy and Sunde (2017) showed evidence of the importance of equality as a determinant of the effect of democratic institutions on institutional quality, measured by an index of economic freedom and an indicator of civil liberties. 31 It has also been shown that countries with more income inequality have more corruption ( Jong-Sung and Khagram 2005 ), and, in particular, survey evidence links perceptions of corruption and inequality to lower political trust ( Uslaner 2017 ).

Finally, there is evidence from advanced industrial democracies of a negative link between inequality and political participation ( Lengfelder 2019 ). Solt (2008) showed a negative effect of economic inequality on political engagement, namely political interest, the frequency of political discussion, and participation in elections among all citizens except the richest, using data from advanced industrial countries. Using cross-sectional data from OECD countries and within-country data for Germany and a range of methods, the recent study by Schäfer and Schwander (2019) finds support for the negative link between economic inequality and political participation. Relatedly, empirical work suggests that economic inequality harms support for democracy (e.g., Andersen 2012 ; Krieckhaus et al. 2014 ) and political inequality (e.g., Houle 2018 ). Still, there appears to be limited evidence of an effect of inequality on electoral turnout ( Stockemer and Scruggs 2012 ; Cancela and Geys 2016 ).

The lack of consensus in the literature, especially about the effect of inequality on growth, is notable. What explains this divergence, and what can be done to contribute to the existing knowledge? In this section, we discuss the key empirical challenges of estimating the effects of inequality: data quality and availability, conceptual and measurement issues, and the methodological difficulties of dealing with confounding variables and endogeneity.

Data quality and availability

Early studies drew on secondary datasets provided, for example, by the World Bank ( Jain 1975 ) or the International Labour Office ( Lecaillon et al. 1984 ). The expanded dataset proposed by Deininger and Squire (1996) was crucial in opening possibilities for panel methods. Additionally, databases offering secondary data compilations on income inequality provided by the United Nations University World Institute for Development Economics Research, WIID (based on household surveys), and SWIID, developed by Solt (2020) and resulting from multiple imputations of the WIID data, have been frequently used in empirical studies. The World Inequality Database ( WID.world 2017 ) has emerged as an additional database providing data on income shares captured by top income groups.

Atkinson and Brandolini (2001 , 2009 ) and Ferreira, Lustig, and Teles (2015) offer comprehensive analyses on secondary datasets on income distribution, drawing attention to issues of data quality and consistency linked to differences in the definitions used, sources of data, and the processing used to obtain “ready-made” income distribution statistics. 32 Atkinson and Brandolini (2001 ) focused mainly on the Deininger and Squire dataset and on data for OECD member countries. Jenkins (2015) follows a similar line of reasoning and compares the WIID and the SWIID, noting that for the latter it is also critical to consider issues relating to the quality of imputations. Jäntti, Pirtillä, and Rönkkö (2020) stress that, in most developing countries, the actual redistribution is only rarely measured, so figures in the SWIID reflect questionable imputations.

As demonstrated in Atkinson and Brandolini (2001 , 2009 ) and Jenkins (2015) , issues of noncomparability have consequences for econometric analysis and for trends over time. Voitchovsky (2011 , 566) warns that data scarcity and limitations in terms of data availability may lead to a trade-off between sources of bias and precision in inequality studies. Ravallion (2001 , 1809) notes, however, that measurement errors, including those resulting from comparability problems, will have a greater impact on analyses that allow for country fixed-effects rather than on standard growth regressions given that the signal-to-noise ratio is likely to be low for changes in measured inequality.

The challenges are even more striking for tests that require data at the individual level, namely those related to the relative hypotheses linking inequality to health. These hypotheses also lead to questions about the appropriate reference groups—how they are defined and formed—as well as in terms of endogeneity, as the position of the individual in relation to the reference may be affected by group membership ( O'Donnell, van Doorslaer, and van Ourti 2015 , 1505).

Concept and measurement of inequality

Issues of concept and measurement are also consequential. 33 Atkinson and Brandolini (2001 ) provide a useful summary of eight parameters to be chosen when defining an income distribution, among which are the unit of observation, concept of resource (e.g., income versus expenditure), and tax treatment of income. These closely link to measurement choices. Different mechanisms require a specific concept of inequality and this should be reflected in the measure of inequality used in the empirical analysis ( Voitchovsky 2011 , 567). Additionally, different parts of the distribution receive importance depending on the inequality measure used, and even the concept of income is open to measurement issues ( Deaton 2003 , 135).

Knowles's (2005) account of the relationship between inequality and growth illustrates these concerns. The author warns that the results in previous studies should be regarded with some degree of caution given that they failed to measure inequality in a consistent manner, mixing measures of the distributions of income before and after tax and the distribution of expenditure. Considering six different measures of inequality (three Gini coefficients and three top ten income shares), a recent study by Blotevogel et al. (2020) shows that the choice of the inequality indicator has important implications for the results obtained in empirical analysis, namely when considering different transmission channels between inequality and growth. In terms of the link between inequality and democratic governance, there is a concern that frequently used measures do not capture interclass inequality, which precludes the testing of theoretical hypotheses that hinge on this ( Houle 2015 , 147).

Criticism has also been directed at specific measures, in particular the widely used Gini coefficient. In light of the observations above, Gini coefficients will provide different information depending on how they are calculated, for example, if based on net income or on gross income ( Houle 2015 , 147). Moreover, some have argued that the use of absolute rather than relative measures might better capture perceptions of inequality on the ground (e.g., Bosmans et al. 2014 ; Atkinson and Brandolini 2004 ; Niño-Zarazúa, Roope, and Tarp 2017 ).

Estimation methods

A review of empirical studies on the inequality–growth link highlights contrasting findings between the early cross-country studies and those that employed panel estimation techniques, after the Deininger and Squire (1998) dataset became available. Some explanations have been advanced for this divergence.

Measurement error may affect the estimation results in cross-country estimation (country- or regional-specific measurement error), and also in panel data estimation, given that inequality tends to be persistent over time; thus, this method relies on more limited time-series variation in the data. The coefficients in cross-country studies may be biased due to time-invariant omitted variables ( Voitchovsky 2011 , 565), while if we consider that inequality is related to underlying determinants of development that are persistent, then fixed-effect estimates may be biased upward when considering long-run effects ( Castells-Quintana, Royuela, and Thiel 2019 , 454).

Additional explanations included the argument for the misspecification of the linearity in the effect of inequality and growth ( Banerjee and Duflo 2003 ) and the suggestion that the two methods capture different time effects, given the short- and long-term lag structures in panel and cross-country analyses, respectively ( Voitchovsky 2011 , 565).

Finally, several concerns have been raised regarding the use of different instruments to tackle reverse causality in the relationship between inequality and growth (see Easterly 2007 ) as well as health ( O'Donnell, van Doorslaer, and van Ourti 2015 , 1505) and democracy ( Houle 2015 , 147). While different attempts have been made using instrumental variable approaches, finding a valid instrument for inequality is certainly not straightforward. Furthermore, even if GMM has often been used to try to tackle these issues, Roodman (2009) warns about the risk of instrument proliferation and the possibility for generating false-positive results. As an illustration, he reexamined the analysis in Forbes (2000) and raised concerns over the positive effect of inequality on growth found in the original paper.

This review combined the different theoretical hypotheses concerning the impact of inequality on three core socioeconomic and political outcomes in a simplified framework and highlighted the mixed empirical evidence. We summarize the main conclusions as follows. First, in line with previous findings, the debate on whether there is a positive or a negative effect on growth remains open, with recent studies mirroring the disagreement in decades of empirical work. With the exception of the classical approach, most of the transmission channels between inequality and growth point to a negative effect of inequality. However, the evidence from reduced-form equations is not consensual and the channels of transmission have received less attention.

Second, while there seems to be some consensus in the evidence that there is a negative link between inequality and secondary school enrolment, there is need for further research in terms of other education outcomes. Although theory generally points toward a negative effect of inequality on health, the existing evidence does not provide clear support to this relationship, in the economic literature in particular, and there is a lot to be uncovered in terms of the mechanisms of transmission at the individual level. Third, theoretical predictions and empirical evidence show mixed results for the effects of inequality on democracy and political participation.

In understanding the diversity and divergence in theoretical and empirical results, a number of empirical challenges remain. Problems with data quality and availability are well understood in the literature, as are those related to the concept and measurement of inequality, and the shortcomings of different estimation methods.

In terms of potential avenues for future work, our review points for one to the value of further attention to different transmission channels (highlighted in  figure 1 ). We first propose a methodological suggestion. While advances in econometric analysis will shed light on the analysis across countries, this could be complemented with the use of experimental work to understand specific channels in particular contexts. While not a substitute for empirical cross-country analysis, experiments can be employed to understand microlevel behavior. The controlled nature of this work avoids biases in econometric studies and mitigates issues of endogeneity and measurement errors.

The second avenue relates to the focus of the analysis. While this review mainly concentrated on cross-country analysis, there is indication that disaggregating the level of analysis might provide useful insights in terms of channels of transmission and underlying cases. For instance, it might be that in Africa, competition over natural resources is the main driver of inequality and in turn slower growth, while in Latin America, inequality may be the main driver for political instability. Furthering regional and country-specific analysis might help dig deeper into these effects.

Finally, despite the existing efforts to compile new—and improve on the existing—secondary datasets, problems persist with the available data. Thus, in light of the importance of data availability and reliability for the analysis of the trends and effects of inequality, we stress that earlier calls for more and better data continue to be both relevant and important for progress in our search for better understanding of the impact of inequality.

Equity here refers to equality of opportunities to pursue a life of one's choosing and protection from extreme deprivation in outcomes ( World Bank 2006 , 18–19). Efficiency refers to economic efficiency, underpinning economic growth ( Thorbecke 2016 ).

Given the multidimensionality of inequality and that its effects are in focus in different disciplines, we follow an interdisciplinary approach. Yet, in the empirical section, we focus on strands of work that employ similar (quantitative) methodologies.

We focus on the main arguments that have attracted attention in these disciplines and have made a concerted effort to address the gender citation gap that exists, for instance, in international relations scholarship (e.g., Maliniak, Powers, and Walter 2013 ).

Throughout, we refer to “income inequality” and “inequality” interchangeably. Although we recognize the multidimensionality of the concept, we focus on literature considering income inequality, which remains a dominant measure ( Stewart 2016 , 64), and refer to more extensive work on other aspects, in particular, the relevance of poverty rates (e.g., Ravallion 2012 ), inequality of opportunity (e.g., Marrero and Rodriguez 2013 ; Ferreira et al. 2018 ), gender inequality (e.g., Bandiera and Natraj 2013 ; Kabeer 2015 ), and horizontal inequalities ( Stewart 2005 ).

We use “growth” and “economic growth” interchangeably.

We highlight that there is expanding work on different facets of economic performance, such as growth volatility (e.g., Iyigun and Owen 2004 ) or the occurrence of crises (e.g., Morelli and Atkinson 2015 ).

Kuznets (1955) argued that the early stages of the development process would experience rising inequality, which would then fall as the country reached higher levels of per capita income. This relationship, known as the “Kuznets curve,” and other work looking at this direction of causality are not covered here.

See also a review of early studies in Bénabou (1996) and Aghion, Caroli, and García-Peñalosa (1999 ) and a more recent overview in Ehrhart (2009) .

Sandmo (2015) reviews the history of theories of income distribution, from Adam Smith until the 1970s.

For a summary of theoretical work on the choice between a public and a private education system, see García-Peñalosa (1995) .

Gutiérrez and Tanaka (2009) review previous theoretical models.

Additional mechanisms relate to social comparison and include relative deprivation and gratification in the context of neighborhood and school effects, and economic segregation ( Mayer 2001 ). The first refers to the fact that people compare themselves with those who are more disadvantaged, which in the case of children can lead to feeling less willing to study or stay in school and in the case of parents can cause stress and alienation. The second suggests that increases in inequality are likely to lead to more geographic segregation as the rich and poor have less in common. See Mayer (2001 , 4–7) for more details.

See Deaton (2003 ) and Lynch et al. (2004) for detailed descriptions of the emergence of debate on the link between income inequality and health.

We do not cover studies on the link between inequality and homicides and between inequality and life satisfaction and happiness ( Graham 2014 ).

Lynch et al. (2004 , 15–16) refer to additional nuances, related to the effects of inequality through psychosocial processes and through the differential accumulation of exposures deriving from material sources rather than from perceptions of disadvantage. They also mention the weak and strong versions of this hypothesis proposed by Mellor and Milyo (2002) .

For a study on the effects of inequality on group participation, see La Ferrara (2002) .

Thorbecke and Charumilind (2002) review the evidence and causal mechanisms linking inequality and crime.

For a review of the theoretical arguments developed earlier, see Bollen and Jackman (1985) .

This line of reasoning can be linked to the work by Glaeser, Scheinkman, and Shleifer (2003) mentioned in section “How inequality affects growth,” which discusses the negative effects of inequality on growth through institutional subversion (including corruption).

For further details, see Solt (2008 , 48–50).

It is also useful to refer here to studies examining the impact of inequality on electoral turnout (e.g., Stockemer and Scruggs 2012 ), support for democracy (e.g., Andersen 2012 ; Krieckhaus et al. 2014 ), and, more generally, political inequality (e.g., Houle 2018 ).

A more complete list of studies is available from the authors.

Studies in the 1990s also focus on determining whether there was a differential effect of inequality on growth in democracies and non-democracies ( Persson and Tabellini 1994 ; Alesina and Rodrik 1994 ; Perotti 1996 ; Clarke 1995 ; Deininger and Squire 1998 ). We discuss this in Section ”Governance.”

Two recent studies build on Forbes (2000) , attempting to overcome some of the remaining estimation challenges. Aiyar and Ebeke (2020) draw attention to the importance of considering equality of opportunity and find empirical support for their hypothesis that the negative effect of income inequality is greater in countries with low levels of equality of opportunity (measured by intergenerational mobility). Scholl and Klasen (2019) replicate Forbes’ (2000) finding but show that it disappears once they control for the experience of transition countries.

Islam and McGillivray (2020) highlight the increasing interest in wealth inequality and investigate its effect on growth using wealth data from Forbes Magazine and Credit Suisse over the period 2000–2012. The results suggest a negative effect.

Perotti (1996 ) empirically tested the channels of transmission, estimating different structural models: first, using each of these channels in a growth model and, then, estimating the effects of inequality on each of the channels.

With the exception of Flug, Spilimbergo, and Wachtenheim (1998) , all these studies employ the Gini coefficient as one of their measures of inequality. Flug, Spilimbergo, and Wachtenheim (1998) used the ratio of the income shares of the top quintile to the bottom two quintiles of the population, and the shares of income accruing to the top quintile and the lowest quintile were used, respectively, by Easterly (2007) and Checchi (2003) . In their robustness checks, Esposito and Villaseñor (2018) used the Atkinson and Theil indices.

We do not offer a comprehensive overview of the measures used in the literature. According to the review in Lynch et al. (2004) , the majority of the studies employ the Gini coefficient or different shares of income. In the list of studies reviewed by these authors, we counted sixty-nine out of ninety-eight using the Gini as (one of) the measure(s) of inequality.

The review of the initial studies in Bollen and Jackman (1985) argued that problems of specification, measurement, and sample composition led to inconclusive results in the existing empirical analyses.

Savoia, Easaw, and McKay (2010) reviewed the arguments linking inequality to institutional quality directly and via democracy and argued that the limited existing work suggests a negative link between inequality and institutions, noting there is a need for further research.

When considering the role of governance (using different indicators), the estimates in Islam and McGillivray (2020) indicate that improved governance may contribute to reduced wealth inequality and higher growth.

See also discussions of these shortcomings in Deaton (2003 ), Voitchovsky (2011) , and Houle (2015) .

As illustrated in section “What the empirical evidence says,” issues of concept and measurement for our outcome variables also matter to consideration of theories and hypothesis testing.

This study was prepared within the project “The impacts of inequality on growth, human development, and governance - @EQUAL.” Support by the Novo Nordisk Foundation Grant NNF19SA0060072 is acknowledged.

We are grateful to the editors and three anonymous referees for insightful and useful suggestions. We thank Anustup Kundu for excellent research assistance as well as Klarizze Puzon, Miguel Niño-Zarazúa, Carlos Gradín, and participants at an internal project workshop for valuable comments. The usual caveats apply.

Acemoglu Daron , Robinson James A. . 2006 . Economic Origins of Dictatorship and Democracy . Cambridge, MA : Cambridge University Press .

Google Scholar

Google Preview

Aghion Philippe , Caroli Eve , García-Peñalosa Cecilia . 1999 . “ Inequality and Economic Growth: The Perspective of the New Growth Theories .” Journal of Economic Literature 37 ( 4 ): 1615 – 60 .

Aiyar Shekhar , Ebeke Christian . 2020 . “ Inequality of Opportunity, Inequality of Income and Economic Growth .” World Development 136 : 105115 .

Alesina Alberto , Rodrik Dani . 1994 . “ Distributive Politics and Economic Growth .” The Quarterly Journal of Economics 109 ( 2 ): 465 – 90 .

Alesina Alberto , Perotti Roberto . 1996 . “ Income Distribution, Political Instability, and Investment .” European Economic Review 40 ( 6 ): 1203 – 28 .

Andersen Robert . 2012 . “ Support for Democracy in Cross-National Perspective: The Detrimental Effect of Economic Inequality .” Research in Social Stratification and Mobility 30 ( 4 ): 389 – 402 .

Ansell Ben , Samuels David . 2010 . “ Inequality and Democratization: A Contractarian Approach .” Comparative Political Studies 43 ( 12 ): 1543 – 74 .

Atkinson Anthony B. , Brandolini Andrea . 2001 . “ Promise and Pitfalls in the Use of ‘Secondary’ Data-Sets: Income Inequality in OECD Countries as a Case Study .” Journal of Economic Literature 39 ( 3 ): 771 – 99 .

Atkinson Anthony B. , Brandolini Andrea . 2004 . “ Global World Inequality: Absolute, Relative or Intermediate? ” Paper prepared for the 28th General Conference of The International Association for Research in Income and Wealth, Cork, Ireland, August 22–28, 2004 .

Atkinson Anthony B. , Brandolini Andrea . 2009 . “ On Data: A Case Study of the Evolution of Income Inequality across Time and across Countries .” Cambridge Journal of Economics 33 ( 3 ): 381 – 404 .

Bandiera Oriana , Natraj Ashwini . 2013 . “ Does Gender Inequality Hinder Development and Economic Growth? Evidence and Policy Implications .” The World Bank Research Observer 28 ( 1 ): 2 – 21 .

Banerjee Abhijit V. , Duflo Esther . 2003 . “ Inequality and Growth: What Can the Data Say? ” Journal of Economic Growth 8 ( 3 ): 267 – 99 .

Barro Robert J. 1999 . “ Determinants of Democracy .” Journal of Political Economy 107 ( S6 ): S158 – 83 .

Barro Robert J. . 2000 . “ Inequality and Growth in a Panel of Countries .” Journal of Economic Growth 5 : 5 – 32 .

Barro Robert J. . 2008 . “ Inequality and Growth Revisited .” ADB Working Paper Series on Regional Economic Integration 11. Asian Development Bank (ADB), Philippines. Accessed November 16, 2020. https://www.adb.org/sites/default/files/publication/28468/wp11-inequality-growth-revisited.pdf .

Bénabou Roland . 1996 . “ Inequality and Growth .” In NBER Macroeconomics Annual 1996 , Volume 11, edited by Bernanke Ben S. , Rotemberg Julio J. , 11 – 92 . Cambridge, MA : MIT Press .

Bénabou Roland . 2000 . “ Unequal Societies: Income Distribution and the Social Contract .” American Economic Review 90 ( 1 ): 96 – 129 .

Berg Andrew , Ostry Jonathan D. , Sangarides Charalambs G. , Yakhshilikov Yorbol . 2018 . “ Redistribution, Inequality, and Growth: New Evidence .” Journal of Economic Growth 23 ( 4 ): 259 – 305 .

Bermeo Nancy . 2009 . “ Poverty Inequality and Democracy (II): Does Electoral Democracy Boost Economic Equality? ” Journal of Democracy 20 ( 4 ): 21 – 35 .

Birdsall Nancy . 1999 . “ Education: The People's Asset .” Center on Social and Economic Dynamics Working Paper 5. Accessed August 13, 2020. https://www.researchgate.net/publication/5059764_Education_The_People's_Asset .

Birdsall Nancy , Londoño Juan Luis . 1997 . “ Asset Inequality Matters: An Assessment of the World Bank's Approach to Poverty Reduction .” The American Economic Review 87 ( 2 ): 32 – 37 .

Blotevogel Robert , Imamoglu Eslem , Moriyama Kenji , Sarr Babacar . 2020 . “ Measuring Income Inequality and Implications for Economic Transmission Channels .” IMF Working Paper WP/20/164 . Washington, DC : International Monetary Fund .

Boix Carles . 2003 . Democracy and Redistribution . Cambridge : Cambridge University Press .

Boix Carles , Stokes Susan C. . 2003 . “ Endogenous Democratization .” World Politics 55 ( 4 ): 517 – 49 .

Bollen Kenneth A. , Jackman Robert W. . 1985 . “ Political Democracy and the Size Distribution of Income .” American Sociological Review 50 ( 4 ): 438 – 57 .

Bosmans Kristof , Decanq Koen , Decoster André . 2014 . “ The Relativity of Decreasing Inequality between Countries .” Economica 81 ( 322 ): 276 – 92 .

Bourguignon Francois . 2015 . “ Revisiting the Debate on Inequality and Economic Development .” Revue d'économie politique 5 : 633 – 63 .

Buchmann Claudia , Hannum Emily . 2001 . “ Education and Stratification in Developing Countries: A Review of Theories and Research .” Annual Review of Sociology 27 ( 1 ): 77 – 102 .

Cancela Joao , Geys Benny . 2016 . “ Explaining Voter Turnout: A Meta-Analysis of National and Subnational Elections .” Electoral Studies 42 : 264 – 75 .

Castelló-Climent Amparo. 2010 . “ Inequality and Growth in Advanced Economies: An Empirical Investigation .” The Journal of Economic Inequality 8 : 293 – 321 .

Castells-Quintana David , Royuela Vicente , Thiel Fabian . 2019 . “ Inequality and Sustainable Development: Insights from an Analysis of the Human Development Index .” Sustainable Development 27 ( 3 ): 448 – 60 .

Checchi Daniele 2003 . “ Inequality in Incomes and Access to Education: A Cross-Country Analysis (1960–95) .” Labour 17 ( 2 ): 153 – 201 .

Chong Alberto , Gradstein Mark . 2007 . “ Inequality and Institutions .” Review of Economics and Statistics 89 ( 3 ): 454 – 65 .

Chong Alberto , Gradstein Mark . 2019 . “ Institutional Persistence, Income Inequality, and Individual Attitudes .” The Journal of Economic Inequality 17 ( 3 ): 401 – 13 .

Cingano Federico . 2014 . “ Trends in Income Inequality and Its Impact on Economic Growth .” OECD Social, Employment and Migration Working Papers 163 . Paris : OECD Publishing .

Clarke George R.G. 1995 . “ More Evidence on Income Distribution and Growth .” Journal of Development Economics 47 ( 2 ): 403 – 27 .

Dabla-Norris Era , Kochhar Kalpana , Suphaphiphat Nujin , Ricka Frantisek , Tsounta Evridiki . 2015 . “ Causes and Consequences of Income Inequality: A Global Perspective .” IMF Discussion Note SDN/15/13 . Washington, DC : International Monetary Fund .

De La Croix David , Doepke Matthias . 2003 . “ Inequality and Growth: Why Differential Fertility Matters .” American Economic Review 93 ( 4 ): 1091 – 113 .

Deaton Angus 2003 . “ Health, Inequality, and Economic Development .” Journal of Economic Literature 41 ( 1 ): 113 – 58 .

Deininger Klaus , Olinto Pedro . 2000 . “ Asset Distribution, Inequality, and Growth .” Policy Research Working Paper 2375 . Washington, DC : The World Bank .

Deininger Klaus , Squire Lyn . 1996 . “ A New Data Set Measuring Income Inequality .” The World Bank Economic Review 10 ( 3 ): 565 – 91 .

Deininger Klaus , Squire Lyn . 1998 . “ New Ways of Looking at Old Issues: Inequality and Growth .” Journal of Development Economics 57 ( 2 ): 259 – 87 .

Dorsch Michael T. , Maarek Paul . 2020 . “ Economic Downturns, Inequality, and Democratic Improvements .” European Journal of Political Economy 62 ( C ): 1 – 21 .

Easterly William . 2007 . “ Inequality Does Cause Underdevelopment: Insights from a New Instrument .” Journal of Development Economics 84 ( 2 ): 755 – 76 .

Ehrhart Christophe . 2009 . “ The Effects of Inequality on Growth: A Survey of the Theoretical and Empirical Literature .” ECINEQ Working Paper Series 2009-107. ECINEQ - Society for the Study of Economic Inequality. Accessed November 16, 2020. http://www.ecineq.org/milano/WP/ECINEQ2009-107.pdf .

El-Shagi Makram , Shao Liang . 2019 . “ The Impact of Inequality and Redistribution on Growth .” Review of Income and Wealth 65 ( 2 ): 239 – 63 .

Esposito Lucio , Villaseñor Adrián . 2018 . “ Wealth Inequality, Educational Environment and School Enrolment: Evidence from Mexico .” The Journal of Development Studies 54 ( 11 ): 2095 – 118 .

Ferreira Francisco H.G. , Lakner Christoph , Lugo Maria Ana , Özler Berk . 2018 . “ Inequality of Opportunity and Economic Growth: How Much Can Cross-Country Regressions Really Tell Us? ” Review of Income and Wealth 64 ( 4 ): 800 – 27 .

Ferreira Francisco H.G. , Lustig Nora , Teles Daniel . 2015 . “ Appraising Cross-National Income Inequality Databases: An Introduction .” The Journal of Economic Inequality 13 : 497 – 526 .

Fields Gary . 1989 . “ A Compendium of Data on Inequality and Poverty for the Developing World .” Unpublished manuscript, Cornell University .

Flug Karnit , Spilimbergo Antonio , Wachtenheim Erik . 1998 . “ Investment in Education: Do Economic Volatility and Credit Constraints Matter? ” Journal of Development Economics 55 ( 2 ): 465 – 81 .

Forbes Kristin J. 2000 . “ A Reassessment of the Relationship between Inequality and Growth .” American Economic Review 90 ( 4 ): 869 – 87 .

Fukuyama Francis . 2011 . “ Poverty, Inequality, and Democracy: Dealing with Inequality .” Journal of Democracy 22 ( 3 ): 79 – 89 .

Galor Oded , Zeira Joseph . 1993 . “ Income Distribution and Macroeconomics .” The Review of Economic Studies 60 ( 1 ): 35 – 52 .

Galor Oded , Moav Omer . 2004 . “ From Physical to Human Capital Accumulation: Inequality and the Process of Development .” Review of Economic Studies 71 ( 4 ): 1001 – 26 .

García-Peñalosa Cecilia . 1995 . “ The Paradox of Education or the Good Side of Inequality .” Oxford Economic Papers 47 ( 2 ): 265 – 85 .

Glaeser Edward , Scheinkman Jose , Shleifer Andrei . 2003 . “ The Injustice of Inequality .” Journal of Monetary Economics 50 ( 1 ): 199 – 222 .

Graham Carol . 2014 . “ Concluding Remarks. How Inequality Matters to Well-Being .” In Happiness and Economic Growth: Lessons from Developing Countries , edited by Clark Andrew E. , Senik Claudia , 249 – 66 . Oxford : Oxford University Press .

Gründler Klaus , Scheuermeyer Philipp . 2018 . “ Growth Effects of Inequality and Redistribution: What Are the Transmission Channels? ” Journal of Macroeconomics 55 : 293 – 313 .

Gutiérrez Catalina , Tanaka Ryuichi . 2009 . “ Inequality and Education Decisions in Developing Countries .” The Journal of Economic Inequality 7 : 55 – 81 .

Haggard Stephan , Kaufman Robert R. . 2012 . “ Inequality and Regime Change: Democratic Transitions and the Stability of Democratic Rule .” American Political Science Review 106 ( 3 ): 495 – 516 .

Halter Daniel , Oechslin Manuel , Zweimüller Josef . 2014 . “ Inequality and Growth: The Neglected Time Dimension .” Journal of Economic Growth 19 ( 1 ): 81 – 104 .

Houle Christian 2009 . “ Inequality and Democracy: Why Inequality Harms Consolidation But Does Not Affect Democratization .” World Politics 61 ( 4 ): 589 – 622 .

Houle Christian . 2015 . “ Does Inequality Harm Economic Development and Democracy?: Accounting for Missing Values, Noncomparable Observations, and Endogeneity .” In The Oxford Handbook of the Politics of Development , edited by Lancaster Carol , Walle Nicolas Van de , 140 – 61 . New York : Oxford University Press .

Houle Christian . 2018 . “ Does Economic Inequality Breed Political Inequality? ” Democratization 25 ( 8 ): 1500 – 18 .

Islam Md. Rabiuk , McGillivray Mark . 2020 . “ Wealth Inequality, Governance and Economic Growth .” Economic Modelling 88 ( C ): 1 – 13 .

Iyigun Murat F. , Owen Ann L. . 2004 . “ Income Inequality, Financial Development, and Macroeconomic Fluctuations .” The Economic Journal 114 ( 495 ): 352 – 76 .

Jain Shail . 1975 . The Size Distribution of Income: A Compilation of Data . Washington, DC : World Bank .

Jäntti Markus , Pirtillä Jukka , Rönkkö Risto . 2020 . “ Redistribution, Inequality, and Growth Revisited: Comment on ‘Redistribution, Inequality, and Growth: New Evidence’ .” WIDER Working Paper 2020/117 . Helsinki : UNU-WIDER .

Jenkins Stephen P. 2015 . “ World Income Inequality Databases: An Assessment of WIID and SWIID .” The Journal of Economic Inequality 13 : 629 – 71 .

Jong-sung You , Khagram Sanjeev . 2005 . “ A Comparative Study of Inequality and Corruption .” American Sociological Review 70 ( 1 ): 136 – 57 .

Kabeer Naila 2015 . “ Gender, Poverty and Inequality: A Brief History of Feminist Contributions in the Field of International Development .” Gender & Development 23 ( 2 ): 189 – 205 .

Kaldor Nicholas . 1956 . “ Theories of Distribution .” The Review of Economic Studies 23 ( 2 ): 83 – 100 .

Karl Terry Lynn . 2000 . “ Economic Inequality and Democracy Instability .” Journal of Democracy 11 ( 1 ): 149 – 56 .

Keefer Philip , Knack Stephen . 2002 . “ Polarization, Politics and Property Rights: Links between Inequality and Growth .” Public Choice 111 : 127 – 54 .

Knack Stephen , Keefer Philip . 1997 . “ Does Inequality Harm Growth Only in Democracies? A Replication and Extension .” American Journal of Political Science 41 ( 1 ): 323 – 32 .

Knowles Stephen . 2005 . “ Inequality and Economic Growth: The Empirical Relationship Reconsidered in the Light of Comparable Data .” Journal of Development Studies 41 ( 1 ): 135 – 59 .

Kotschy Rainer , Sunde Uwe . 2017 . “ Democracy, Inequality, and Institutional Quality .” European Economic Review 91 ( C ): 209 – 28 .

Krieckhaus Jonathan , Son Byunghwan , Bellinger Nisha Mukherjee , Wells Jason M. . 2014 . “ Economic Inequality and Democratic Support .” The Journal of Politics 76 ( 1 ): 139 – 51 .

Kuznets Simon . 1955 . “ Economic Growth and Income Inequality .” The American Economic Review 45 ( 1 ): 1 – 28 .

La Ferrara Eliana . 2002 . “ Inequality and Group Participation: Theory and Evidence from Rural Tanzania .” Journal of Public Economics 85 ( 2 ): 235 – 73 .

Lecaillon Jacques , Paukert Felix , Morrison Christian , Germadis Dimitri . 1984 . Income Distribution and Economic Development: An Analytical Survey . Geneva : International Labour Office .

Leigh Andrew , Christopher Jencks , Smeeding Timothy M. . 2011 . “ Health and Economic Inequality .” In The Oxford Handbook of Economic Inequality , edited by Nolan Brian , Salverda Wiemer , Smeeding Timothy M. , 384 – 405 . New York : Oxford University Press .

Lengfelder Christina 2019 . “ Exploring Dynamics of Inequality in Human Development .” 2019 UNDP Human Development Report, Background Paper NO. 3-2019. United Nations Development Programme (UNDP). Accessed June 6, 2020. http://hdr.undp.org/en/content/exploring-dynamics-inequality-human-development .

Li Hongyi , Zou Heng-fu . 1998 . “ Income Inequality Is Not Harmful for Growth: Theory and Evidence .” Review of Development Economics 2 ( 3 ): 318 – 34 .

Lynch John , Smith George Davey , Harper Sam , Hillemeier Marianne , Ross Nancy , Kaplan George A. , Wolfson Michael . 2004 . “ Is Income Inequality a Determinant of Population Health? Part 1. A Systematic Review .” The Milbank Quarterly 82 ( 1 ): 5 – 99 .

Madsen Jakob B. , Islam Md. Rabiuk , Doucouliagos Hristos . 2018 . “ Inequality, Financial Development and Economic Growth in the OECD, 1870–2011 .” European Economic Review 101 ( C ): 605 – 24 .

Maliniak Daniel , Powers Ryan , Walter Barbara F. . 2013 . “ The Gender Citation Gap in International Relations .” International Organization 67 ( 4 ): 889 – 922 .

Marrero Gustavo A. , Rodríguez Juan G. . 2013 . “ Inequality of Opportunity and Growth .” Journal of Development Economics 104 ( C ): 107 – 22 .

Mayer Susan E. 2001 . “ How Did the Increase in Economic Inequality between 1970 and 1990 Affect Children's Educational Attainment? ” American Journal of Sociology 107 ( 1 ): 1 – 32 .

Mellor Jennifer M. , Milyo Jeffrey . 2002 . “ Income Inequality and Health Status in the United States .” The Journal of Human Resources 37 ( 3 ): 510 – 39 .

Morelli Salvatore , Atkinson Anthony B. . 2015 . “ Inequality and Crises Revisited .” Economia Politica 32 : 31 – 51 .

Murphy Kevin M. , Shleifer Andrei , Vishny Robert . 1989 . “ Income Distribution, Market Size and Industrialization .” The Quarterly Journal of Economics 104 ( 3 ): 537 – 64 .

Neves Pedro Cunha , Silva Sandra Maria Tavares . 2014 . “ Inequality and Growth; Uncovering the Main Conclusions from the Empirics .” The Journal of Development Studies 50 ( 1 ): 1 – 21 .

Niño-Zarazúa Miguel , Roope Lawrence , Tarp Finn . 2017 . “ Global Inequality: Relatively Lower, Absolutely Higher .” Review of Income and Wealth 63 ( 4 ): 661 – 84 .

Nolan Brian , Valenzuela Luis . 2019 . “ Inequality and Its Discontents .” Oxford Review of Economic Policy 35 ( 3 ): 396 – 430 .

O'Donnell Owen , van Doorslaer Eddy , van Ourti Tom . 2015 . “ Health and Inequality .” In Handbook of Income Distribution , Volume 2B, edited by Atkinson Anthony B. , Francois Bourguignon , 1419 – 533 . Amsterdam : Elsevier .

Østby Gudrun . 2013 . “ Inequality and Political Violence: A Review of the Literature .” International Area Studies Review 16 ( 2 ): 206 – 31 .

Ostry Jonathan D. , Berg Andrew , Tsangarides Charalambos G. . 2014 . “ Redistribution, Inequality, and Growth .” IMF Staff Discussion Note SDN/14/02 . Washington, DC : International Monetary Fund .

Panizza Ugo . 2002 . “ Income Inequality and Economic Growth: Evidence from American Data .” Journal of Economic Growth 7 : 25 – 41 .

Partridge Mark D. 1997 . “ Is Inequality Harmful for Growth? Comment .” The American Economic Review 87 ( 5 ): 1019 – 32 .

Paukert Felix . 1973 . “ Income Distribution at Different Levels of Development: A Survey of the Evidence .” International Labour Review 108 : 97 – 125 .

Perotti Roberto . 1996 . “ Growth, Income Distribution, and Democracy: What the Data Say .” Journal of Economic Growth 1 : 149 – 87 .

Persson Torsten , Tabellini Guido . 1994 . “ Is Inequality Harmful for Growth? ” The American Economic Review 84 ( 3 ): 600 – 21 .

Pickett Kate E. , Wilkinson Richard G. . 2015 . “ Income Inequality and Health: A Causal Review .” Social Science & Medicine 128 : 316 – 26 .

Ravallion Martin 2001 . “ Growth, Inequality and Poverty: Looking Beyond Averages .” World Development 29 ( 11 ): 1803 – 15 .

Ravallion Martin . 2012 . “ Why Don't We See Poverty Convergence? ” American Economic Review 102 ( 1 ): 504 – 23 .

Roodman David . 2009 . “ A Note on the Theme of Too Many Instruments .” Oxford Bulletin of Economics and Statistics 71 ( 1 ): 135 – 58 .

Rothstein Bo , Uslaner Eric M. . 2005 . “ All for All: Equality, Corruption, and Social Trust .” World Politics 58 ( 1 ): 41 – 72 .

Rowlingson Karen 2011 . “ Does Income Inequality Cause Health and Social Problems? ” Joseph Rowntree Foundation, York. Accessed October 4, 2021. https://www.jrf.org.uk/file/41359/download?token=VV7qsS1J&filetype=full-report .

Sandmo Agnar . 2015 . “ The Principal Problem in Political Economy: Income Distribution in the History of Economic Thought .” In Handbook of Income Distribution , Volume 2, edited by Atkinson Anthony B. , Bourguignon Francois , 3 – 65 . Amsterdam : Elsevier .

Savoia Antonio , Easaw Joshy , McKay Andrew . 2010 . “ Inequality, Democracy, and Institutions: A Critical Review of Recent Research .” World Development 38 ( 2 ): 142 – 54 .

Schäfer Armin , Schwander Hanna . 2019 . “ ‘Don't Play If You Can't Win’: Does Economic Inequality Undermine Political Equality .” European Political Science Review 11 ( 3 ): 395 – 413 .

Scheve Kenneth , Stasavage David . 2017 . “ Wealth Inequality and Democracy .” Annual Review of Political Science 20 : 451 – 68 .

Scholl Nathalie , Klasen Stephan . 2019 . “ Re-Estimating the Relationship between Inequality and Growth .” Oxford Economic Papers 71 ( 4 ): 824 – 47 .

Solt Frederick . 2008 . “ Economic Inequality and Democratic Political Engagement .” American Journal of Political Science 52 ( 1 ): 48 – 60 .

Solt Frederick . 2009 . “ Standardizing the World Income Inequality Database .” Social Science Quarterly 90 ( 2 ): 231 – 42 .

Solt Frederick . 2020 . “ Measuring Income Inequality across Countries and over Time: The Standardized World Income Inequality Database .” Social Science Quarterly 101 ( 3 ): 1183 – 99 .

Stewart Frances . 2005 . “ Horizontal Inequalities: A Neglected Dimension of Development .” In Wider Perspectives on Global Development , edited by Shorrocks Anthony F. , 101 – 35 . London : Palgrave Macmillan .

Stewart Frances . 2016 . “ Changing Perspectives on Inequality and Development .” Studies in Comparative International Development 51 : 60 – 80 .

Stockemer Daniel , Scruggs Lyle . 2012 . “ Income Inequality, Development and Electoral Turnout—New Evidence on a Burgeoning Debate .” Electoral Studies 31 ( 4 ): 764 – 73 .

Subramanian S.V. , Kawachi Ichiro . 2004 . “ Income Inequality and Health: What Have We Learned So Far? ” Epidemiologic Reviews 26 ( 1 ): 78 – 91 .

Sylwester Kevin 2000 . “ Income Inequality, Education Expenditures, and Growth .” Journal of Development Economics 63 ( 2 ): 379 – 98 .

Tanaka Ryuichi 2003 . “ Inequality as a Determinant of Child Labor .” Economics Letters 80 ( 1 ): 93 – 97 .

Thorbecke Erik 2016 . “ Inequality and the Trade-Off between Efficiency and Equity .” Journal of Human Development and Capabilities 17 ( 3 ): 460 – 64 .

Thorbecke Erik , Charumilind Chutatong . 2002 . “ Economic Inequality and Its Socioeconomic Impact .” World Development 30 ( 9 ): 1477 – 95 .

Uslaner Eric M. 2017 . “ Political Trust, Corruption, and Inequality .” In Handbook on Political Trust , edited by Zmerli Sonja , van der Meer Tom W.G. , 302 – 15 . Chelton : Edward Elgar Publishing .

Voitchovsky Sarah 2005 . “ Does the Profile of Income Inequality Matter for Economic Growth? Distinguishing between the Effects of Inequality in Different Parts of the Income Distribution .” Journal of Economic Growth 10 : 273 – 96 .

Voitchovsky Sarah . 2011 . “ Inequality and Economic Growth .” In The Oxford Handbook of Economic Inequality , edited by Nolan Brian , Salverda Wiemer , Smeeding Timothy M. , 549 – 74 . New York : Oxford University Press .

Wagstaff Adam , van Doorslaer Eddy . 2000 . “ Income Inequality and Health: What Does the Literature Tell Us? ” Annual Review of Public Health 21 : 543 – 67 .

Walraevens Benoît . 2021 . “ Adam Smith's View of Economic Inequality .” Cambridge Journal of Economics 45 ( 1 ): 209 – 24 .

WID.world . 2017 . “ World Inequality Database .” Accessed January 26, 2021. https://wid.world .

Wilkinson Richard G. , Pickett Kate E. . 2006 . “ Income Inequality and Population Health: A Review and Explanation of the Evidence .” Social Science & Medicine 62 ( 7 ): 1768 – 84 .

World Bank . 2006 . World Development Report 2006: Equity and Development . Washington, DC : World Bank .

Zweimüller Josef . 2000 . “ Schumpeterian Entrepreneurs Meet Engel's Law: The Impact of Inequality on Innovation-Driven Growth .” Journal of Economic Growth 5 : 185 – 206 .

Email alerts

Citing articles via.

• Recommend to your Library

Affiliations

• Online ISSN 1468-2486
• Print ISSN 1521-9488
• Copyright © 2024 International Studies Association
• About Oxford Academic
• Publish journals with us
• University press partners
• What we publish
• New features  
• Open access
• Institutional account management
• Rights and permissions
• Get help with access
• Accessibility
• Advertising
• Media enquiries
• Oxford University Press
• Oxford Languages
• University of Oxford

Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide

• Copyright © 2024 Oxford University Press
• Cookie settings
• Cookie policy
• Privacy policy
• Legal notice

This Feature Is Available To Subscribers Only

Sign In or Create an Account

This PDF is available to Subscribers Only

For full access to this pdf, sign in to an existing account, or purchase an annual subscription.

The changing landscape of economic opportunity by race and class in America

Subscribe to the center for economic security and opportunity newsletter, new data and policy implications, quinn sanderson and quinn sanderson research intern - economic studies , center for economic security and opportunity gabriela campos gabriela campos research intern - economic studies , center for economic security and opportunity.

August 8, 2024

This is a summary of an event held on July 31, 2024. You can watch full video of the event here .

On Wednesday, July 31, the Center for Economic Security and Opportunity (CESO) at Brookings hosted a webinar on the changing landscape of opportunity in America. The webinar focused on new research from Raj Chetty, Will Dobbie, Benjamin Goldman, Crystal Yang of Opportunity Insights, and Sonya Porter of the U.S. Census Bureau. Their research looked at data from 57 million children to show how opportunity is changing by race and class in America and identified the sociological forces that are driving these trends. The presentation was followed by a panel discussion moderated by Abigail Wozniak of the Federal Reserve Bank of Minneapolis.

The webinar began with an analysis of the geography of upward mobility in the United States and how historical factors including different rates of slavery have continued to influence economic mobility. This analysis motivated the group to ask: Can opportunity be changed? The answer is a resounding yes. The data, which uses tax information to analyze changes in outcomes for children born between 1978 and 1992, reveals that over that period, the Black-white gap in upward mobility has significantly narrowed, largely due to increased opportunities for Black children to escape poverty. On the other hand, the class gap among white children has widened, with greater disparities emerging between those from low- and high-income families.

The research also found a significant shift in the geography of economic opportunity across the United States. Historically, coastal regions offered greater pathways to upward mobility, especially for low-income families. However, the study found that these areas have experienced a decline in mobility, particularly affecting low-income white children. In contrast, regions like the Southeast and industrial Midwest have shown improvements in mobility for low-income Black children, highlighting the evolving regional dynamics in economic mobility.

Additionally, the report showed that these divergent trends in mobility by race and class were primarily driven by changes in the communities where children were raised. The study emphasized that childhood environments, measured by parental employment rates, played a crucial role in these shifts. Improvements in local employment conditions positively impacted the economic prospects of children, illustrating the importance of community-level factors in shaping economic mobility.

The study also highlighted the significant influence of children’s specific social networks on their economic outcomes. Data from Facebook showed that these networks, often segregated by race and class, are pivotal in shaping prospects and, if leveraged more intentionally, could potentially bring about greater opportunities for upward mobility across stratified groups. The findings indicate that children’s outcomes are profoundly affected by the economic status of parents within their immediate social circles. This segregation within social networks shows the critical role of social capital and interactions in determining access to opportunities, further emphasizing the importance of social environment on a child’s economic mobility trajectory. In essence, the study reveals that a child’s economic prospects are not only influenced by their family’s economic status, but also by the economic status of those they interact with on a regular basis.

The report emphasized that improvements in economic mobility are not a zero-sum game; benefits for one group do not come at the expense of another. Areas with better opportunities for children born to low-income Black families also tended to be those where mobility deteriorated the least for their white counterparts The discussion highlighted the importance of focusing on youth by investing in targeted job training and mentorship programs. Additionally, they stressed the need to target social communities rather than just neighborhoods, as social interactions are crucial in fostering economic opportunity. The implication for policy is that investing in social capital alongside financial and human capital is crucial in efforts to improve upward mobility, with the findings from the report emphasizing that such change can occur over relatively short time periods. This holistic approach can significantly improve economic opportunities and reduce disparities across racial and socioeconomic lines.

After the presentation on the findings of the report, the panel discussed main takeaways and their thoughts for further research, data investigation or linkage, and policy implications. Panelists included Robert Doar, President of American Enterprise Institute, Sherri Chisholm, Executive Director of Leading on Opportunity, Xavier de Souza Briggs , Senior Fellow in Brookings Metro, and Raj Chetty, Professor of Economics at Harvard University and Director of Opportunity Insights.

Sherri Chisholm began with comments about an important example of success when investing in economic mobility: the progress of Charlotte, NC. Charlotte, in a 2014 report from Opportunity Insights, was ranked 50th out of the 50 largest commuting zones on the ability for change in intergenerational mobility. In the new 2024 study, Charlotte moved into the third spot for change in intergenerational mobility. Chisholm discussed that this progress was encouragement to keep going and an affirmation to recognize the continual needs of the community.

Xavier de Souza Briggs echoed this positive takeaway, emphasizing that it is inspiring to see opportunity for advancement in economic mobility and that this research can set the record straight: that change in mobility is possible in a short amount of time. He also noted the power of data and the effectiveness of combining different sources to dig into patterns that can maximize the value of policy interventions.

Doar commented on the potential of big data, like the sources used in the Opportunity Insights report, to examine questions on social and economic mobility, namely: what can help the next generations? He called attention to the importance of a work-based safety net as a potential policy implication from the report’s findings, noting that parental employment seems to come with wide-ranging benefits for children, extending beyond simply financial resources.

Finally, Chetty answered further questions about his team’s report and its implications for policy. He acknowledged the inherent challenges in predicting economic mobility; researchers must wait for people to grow up, and it is always difficult to predict if current trends will continue, as the nature of social interactions may be changing with the advent of technology or there may be diverse long-term impacts on communities, such as from the recessions of 2008 and 2020. He noted the lack of distinction in trends for other race and ethnic groups in their mobility and pointed interested viewers to www.opportunityatlas.org where the data used for the analysis is available, including breakdowns by gender and marital status. Ultimately, Chetty reiterated an important takeaway: In the U.S., there are growing class gaps and shrinking racial gaps, and they are changing due to the social environment. He also re-emphasized that social mobility is not a zero-sum game, and that progress for one group does not come at the expense of another. In fact, he pointed out that we are all in this together, and that when people in our communities do better, we all have the potential to do better.

Related Content

Richard V. Reeves, Ember Smith

April 26, 2024

Simon Hodson

May 8, 2024

Ishva Mehta

April 8, 2024

The Brookings Institution is financed through the support of a diverse array of foundations, corporations, governments, individuals, as well as an endowment. A list of donors can be found in our annual reports published online  here . The findings, interpretations, and conclusions in this report are solely those of its author(s) and are not influenced by any donation.

Economic Studies

North America

Center for Economic Security and Opportunity

Wendy Edelberg, Noadia Steinmetz-Silber

July 31, 2024

Jeffrey C. Fuhrer

July 29, 2024

Online only

1:00 pm - 2:30 pm EDT

Home — Essay Samples — Economics — Economic Inequality — Poverty and Economic Inequality: Current American Issues

Poverty and Economic Inequality: Current American Issues

• Categories: Economic Inequality Income Inequality Poverty in America

About this sample

Words: 681 |

Published: Aug 30, 2022

Words: 681 | Page: 1 | 4 min read

Table of contents

Economic inequality and its multifaceted impact, public perception of economic inequality, works cited:.

• American Psychological Association. (2010). Publication manual of the American Psychological Association (6th ed.).
• Barnett, A. (2017). Academic initiative: What it is and why it matters. The Student Room. https://www.thestudentroom.co.uk/university/applying/ucas-application/ucas-personal-statements/academic-initiative-what-it-is-and-why-it-matters
• Lerner, M. (2012). Moral development. In V. S. Ramachandran (Ed.), Encyclopedia of Human Behavior (2nd ed., Vol. 3, pp. 198-202). Elsevier.
• National Honor Society. (2023). About Us.
• Pruitt, S. (2018). How volunteering can help you professionally. Forbes. https://www.forbes.com/sites/samanthapruitt/2018/05/03/how-volunteering-can-help-you-professionally/?sh=5b4418e1317f
• Senior Living Residences. (2023). Our Communities.
• Turnitin. (2023). What is plagiarism?
• UNICEF. (2023). About us.
• VolunteerMatch. (2023). Volunteer opportunities.

Cite this Essay

Let us write you an essay from scratch

• 450+ experts on 30 subjects ready to help
• Custom essay delivered in as few as 3 hours

Get high-quality help

Prof Ernest (PhD)

Verified writer

• Expert in: Economics Social Issues

+ 120 experts online

By clicking “Check Writers’ Offers”, you agree to our terms of service and privacy policy . We’ll occasionally send you promo and account related email

No need to pay just yet!

Related Essays

6 pages / 2557 words

3 pages / 1512 words

3 pages / 1259 words

2 pages / 930 words

Remember! This is just a sample.

You can get your custom paper by one of our expert writers.

121 writers online

Still can’t find what you need?

Browse our vast selection of original essay samples, each expertly formatted and styled

Related Essays on Economic Inequality

Poverty and economic inequality are persistent and complex issues that have significant impacts on individuals, communities, and societies. According to the World Bank, over 700 million people worldwide live in extreme poverty, [...]

The debate over raising the minimum wage has been a hot topic in recent years, with proponents arguing that it will help lift workers out of poverty and stimulate the economy, while opponents claim that it will lead to job [...]

Economic inequality is an existed phenomenon in economy, which belongs to the gap between the rich and the poor. Like dividing a cake, every piece of cake which is held by people is not on average, so the inequality is happened [...]

The documentary "Inequality For All" directed by Jacob Kornbluth sheds light on the pressing issue of economic inequality in the United States. The film follows former Secretary of Labor Robert Reich as he discusses the widening [...]

Introduction:In Jonathan Swift's satirical essay, "A Modest Proposal," the author employs a unique logic to address the dire economic and social conditions in Ireland during the 18th century. Swift's use of irony and [...]

This film happens in 2008. During that time, the world had a big economy. In 2011, the Wall Street has a big revolution and demonstration. Breaking the serious gap between the rich and the poor in the US society. The film [...]

Related Topics

By clicking “Send”, you agree to our Terms of service and Privacy statement . We will occasionally send you account related emails.

Where do you want us to send this sample?

By clicking “Continue”, you agree to our terms of service and privacy policy.

Be careful. This essay is not unique

This essay was donated by a student and is likely to have been used and submitted before

Download this Sample

Free samples may contain mistakes and not unique parts

Sorry, we could not paraphrase this essay. Our professional writers can rewrite it and get you a unique paper.

Please check your inbox.

We can write you a custom essay that will follow your exact instructions and meet the deadlines. Let's fix your grades together!

Get Your Personalized Essay in 3 Hours or Less!

We use cookies to personalyze your web-site experience. By continuing we’ll assume you board with our cookie policy .

• Instructions Followed To The Letter
• Deadlines Met At Every Stage
• Unique And Plagiarism Free

Economic Inequality - Essay Samples And Topic Ideas For Free

Economic inequality, reflecting disparities in income and wealth among individuals and groups, is a persistent issue with significant social, political, and economic implications. Essays on this topic could explore the causes and consequences of economic inequality, analyzing the role of policies, institutions, and societal norms. Discussions might delve into the impact of economic inequality on social mobility, political power, and societal cohesion. The discourse may also explore potential solutions, such as progressive taxation, educational reform, and labor market policies, aimed at reducing inequality and promoting economic justice. We have collected a large number of free essay examples about Economic Inequality you can find at PapersOwl Website. You can use our samples for inspiration to write your own essay, research paper, or just to explore a new topic for yourself.

Economic Inequality and Governmental Responsibility

Ever since the emergence of civilization several hundreds of years ago, social inequality has been a prevalent aspect of many societies across the world. This social structure developed as a result of several factors, amongst them political and economic status in the society. During the early stages of civilization, social and political status was closely related whereby the few powerful political leaders tended to be wealthier than the lesser politically influential majority. Although this dynamic is still prevalent in developing […]

Neoliberalism and Economic Inequality in Different Countries

Over the past few decades, the world economy has expanded rapidly under the influence of neoliberalism. However, neoliberalism is controversial, some people hold a positive attitude towards it, while others hold a negative attitude. Not all developed and developing countries will benefit from the new liberal process. Over time, more and more problems have surfaced as a result of the free market. In fact, today, with the spread of neoliberalism, economic and social inequality still exists in society, which has […]

Comparison of Capitalism and Socialism

Our world is steadily evolving, while the wealthy can keep up, the poor stay left behind. With the introduction of the internet we are constantly connected to the rest of the world. This is both beneficial and detrimental to the world. With this expansion of the global market we have become interdependent however we also have access to an abundance of resources. Capitalism is based around the idea of competition, who can work the hardest whereas communism is based around […]

We will write an essay sample crafted to your needs.

Racial Inequality in America

The United States has been struggling with racial inequality for decades, and the media has been paying more attention to this issue. Race can impact the likelihood of graduating high school, attending college, or even maintaining a livable income as an adult (Back and Solomos, 2020). An individual's racial ethnicity is a factor when determining these outcomes and is worth noting. If you are skeptical of your race's role in the number of options you have, look no further than […]

Structural-Functionalist, Marxist and Symbolic Interactionist Theories

Throughout time, society has been studied on both the micro and macro levels by sociologists which has resulted in three main theories to emerge from their findings. These three theories include the Structural-Functionalist, Marxist (social conflict) and Symbolic Interactionist theories. Each theory is unique in its own way and can accurately illustrate how social factors and human behavior are altered by society. When comparing these theories it is important to look and discuss three perspectives of each theory which include […]

Racism in Criminal Justice System

Scott Woods once said, The problem is that white people see racism as conscious hate, when racism is bigger than that. Racism is a complex system of social and political levers and pulleys set up generations ago to continue working on the behalf of whites at other people's expense, whether whites know/like it or not. Racism is an insidious cultural disease. It is so insidious that it doesn't care if you are a white person who likes black people; it's […]

What is Racial Inequality?

Racial inequality is systematically different from racial discrimination and racism. Racial discrimination involves the treatment of racial inequality while racial inequality involves the consequences of inequality such as, income, education, health, etc. Racism often involves these two processes, but modern forms of racial inequality and discrimination are not necessarily the direct consequences of modern racism (Pager and Shepherd, 2008). Racist sociology studies that relationships between these three phenomena when, how, why and to what extent? In the post-civil rights era […]

U.S. Income Inequality

Throughout the history of capitalism, income inequalities between the upper and lower classes have caused many debates even revolutions in Russia, France, China, and others. The mass workers are subjected to the dominant ideology of elites, so the top ten percent earn a large amount of money while the lower class barely survives. The middle class came about which filled some of the disparity in income between the two classes. However, the middle-class today is losing some ground as job […]

Gender Inequality and Feminism

Gender inequality is a concept which has been occurring over a number of years and due to gender differences it fuels up gender inequality, which gave rise to gender socialization. Gender socialization is the process of learning gender roles which emerge from society and nowadays social media, throughout this process men and women learn their roles in society. The most common attribute we ascribe to women is that they can be vulnerable and sensitive, on the other hand, men hear […]

Why is Sociological Imagination Important

Final Paper During the entirety of this semester we have focused on different aspects of social inequality. After being introduced to the chapters provided in the text, you can conclude that social inequality focuses specifically on economic, racial and gender inequality. These three components allow us to see how there is inequality based on one’s wealth/income and physical characteristics as well as the unequal treatment based on gender. As each chapter has shown great significance and insight of why our […]

America is Suffering from Poverty

United states of America haves a population of 325.7 million people. As Americans we love Sunday night football, Drake concerts, watching Donald Trump run our country into a hole andoursocial networks. Although we have several interests we cannot let it entertain us from the fact that America is suffering from poverty. Poverty is the state of being awfully poor. What decent country puts more focus on their Instagram poststhan their bank account funds? According to World Bank, in 2013 769 […]

Jacksonian Democrats

In this paper I will be evaluating the interpretations and arguments set forth by three prominent historians regarding the Jacksonians and explain my own personal views. Throughout the Age of Jackson, a new political party started. Historians have many views of who the Jacksonians were. The three major historians that wrote on this topic where Arthur Schlesinger, Bray Hammond, and Edward Pessen. These men have different point of views from one another and some of their arguments are better than others. […]

Automation Will Crash Democracy

Around the world, technology is constantly disrupting the workforce, with automation poised to displace humans in the fields of medicine, agriculture, and beyond. Will the rise of robots fuel a new wave of “us versus them” populism capable of undermining democracy? For some, the answer is yes. They argue that as people lose jobs to robots, the gap between the rich and poor widens, distrust in government and democratic institutions grows, and populist ideas become more attractive to those who […]

Income Inequality and Economic Growth in Pakistan

In time series data, which indicates that increasing income inequality is likely to spur higher levels of GDP, certain examples become apparent. For instance, Shahbaz (2010) employed a time series data on Pakistan for the period 1971-2005, using the ARDL bound test approach, to determine the relationship between income inequality and economic growth in Pakistan. The results show that income inequality is positively and significantly related in both long-run and short-run with economic growth in Pakistan. Gelan and Price (2003) […]

The Existence of Racial

The existence of racial and ethnic inequalities in American society are still present. People of color face structural barriers when it comes to securing quality housing, income inequality, and employment. Statistically, African American's have struggled in each of these categories, while whites haven't been nearly affect with these types of conditions. The persistent disparity between the white and black population are seen in homeownership. According to Urban Institute, "Between 1999 and 2015, white young adults ages 18 to 34 had […]

The Problems on Income Inequality

In this part, we continue to briefly summarize our empirical analyses based on the ARDL model techniques adopted. The findings of this study are summarized below. Firstly, the objectives of the study were analyzed using cointegration analysis tests and the ARDL bound test on the national level data, covering the period of 2004-2016. The first step taken in the cointegration test involved carrying out a unit root test for each variable and determining their order of integration. The results indicated […]

Hunger Games and in Real Life

The novel The Hunger Games by Suzanne Collins presents themes that are real even in today's society such as inequality. The themes make what would qualify for good writing research topic proposal. This paper presents my writing research topic proposal based on the social issues presented in The Hunger Games. My general/broad topic focusses on inequality The subtopics directly related to the broad topic include income inequality between men and women in the United States, the effects of political inequality […]

Analysis of the Minimum Wage

The discussion about whether or not to raise minimum wage laws has been at an unsurpassed high in the United States. There has been a lot of points made about what good can come to those who are working a minimum paying job, and there has also been points made over the negative effects it could have on other American workers. The purpose of this research paper is to discuss both sides of this discussion together. I will first talk […]

Causes of Unequal Economy in South Africa

My term paper explores the historical and institutional factors that have led South Africa to be known as the most unequal economy in the world. It will look at the South African economy through a historical lens, specifically examining how inequality within its economy has shifted from the end of the Apartheid regime up to modern day. The paper focuses on identifying and analyzing social factors that have contributed to an unequal economy in South Africa. This includes gender, race, […]

Modern Democracy

Establishing and maintaining any governmental regime requires an endless amount of factors that are difficult to achieve, but preserving a functioning democratic regime can be even harder. There are numerous components that are needed to achieve and uphold a successful establishment, but the ones of utmost importance are proper education, free and fair elections, political trust and legitimacy, and socioeconomic order and development, because they are all directly related to one another. The world has seen countless examples of failed […]

An Analysis of Ira Katznelson’s Affirmative Action Proposals

For political scientist Ira Katznelson (Columbia University), racism in the United States is not only a historical evil, it is a present-day, government-institutionalized evil. In his book When Affirmative Action Was White: An Untold History of Racial Inequality in Twentieth-Century America, Katznelson argues that the only way for United States society to bridge the gap created between minorities, specifically African Americans, and whites is for the federal government to actively create policies that favor minorities. Katznelson justifies this claim by […]

A Utopian Society for One

Toward Human Health and Happiness: A Utopian Society for One The ideal society is not like the ocean it consumes every drop of water, but there is no treasure, uniqueness or identity. However, Utopia is the imagined place or state of things where everything is perfect. It can be a personal, cultural and social idea that must rely on an individual's unique priorities and principles. It does not require a consideration of what is good for most and it is […]

Globalization’s Effects on Salta’s Viticulture Industry

Today's world economy is constantly shifting, changing, and adapting. With the increased interconnectedness of markets and communication, effectively every current industry looks remarkably distinct from what they looked like a hundred years ago. The distribution of these changes, however, are not uniform, and agricultural industries in particular see this imbalance. Globalization and technological advances may diminish agriculture's intrinsic variability, but this inconsistency can never be completely erased. This is most exemplified in the grape growing industry. Grapes are a sensitive […]

Information and Communication Technologies

Introduction Over the past few decades, information and communication technologies (ICTs) have played an important role as a key solution for comprehensive development, poverty elimination, and the empowerment of groups discriminated against in society. The ICT sector presents tremendous opportunities for women. However, for women to seize these opportunities equally as men, the gender stereotypes and biases that prevent them from pursuing or making it big in STEM-related fields need to be addressed. Women are still under-represented in this sector. […]

History of Philippines and Country Analysis

Pre Colonization Before colonization the Philippines was inhabited by migrants groups that settled sporadically across the nation. Eventually these small groups developed into larger settlements known as barangays, independently of each other with no centralized government, acting within defined social hierarchy (History of the Philippines). As the islands developed maritime ports, trade relations were established between the islands and with neighboring East Asian countries, their biggest exporters being Japan and China. Ancient inhabitants of the islands became a minority and […]

Role of Women and Men in Professional Sphere

On June 10, 1963, the equal pay act bill was passed preventing any business to unfairly wage workers based on sex. The law states that “No employer having employees subject to any provisions of this section shall discriminate, within any establishment in which such employees are employed, between employees on the basis of sex by paying wages to employees in such establishment at a rate less than the rate at which he pays wages to employees of the opposite sex […]

Postwar Welfare State

The establishment of the postwar welfare state: A measurement to control the collateral effects of the World War Two After the uncountable catastrophes that occurred during the Second World War, the belief that life was meaningless permeated around Europe. When the level of misery is so aggravated, people are more susceptible to accept drastic solutions. In order to prevent this from happening, many Western European governments decided to establish public welfare systems to control desperation and avoid any radical approach. […]

The Government has Blood on its Hands

An example of visualizing the Aids crisis and gay art was Gran Fury’s The government has Blood on its Hands. It is a political poster that says the name of its title at the top and “one aids death every half hour” all in the same sans serif font with bold black capital letters. The main subject matter of the piece is in the middle of the two sentences. It is a large, red hand print that appears to be […]

The Echoes of Economic Disparities: Reflecting on “Inequality for All”

In the mosaic of contemporary socio-economic discourse, few topics are as pervasive and polarizing as economic inequality. The film "Inequality for All" presents a compelling exploration of this topic, delving deep into the crevices of the American economic landscape to shed light on the widening gap between the rich and the poor. Using a blend of data, personal stories, and expert insights, the film encapsulates the complexities of the issue while igniting a discourse about its long-term implications. To begin, […]

Economic Hurdles in a Market-Driven Wonderland

In the bustling marketplace of a small town, where vendors' shouts fill the air and the scent of fresh produce mingles with the aroma of street food, lies a microcosm of a market economy. While this vibrant scene showcases the dynamism and efficiency of market-driven systems, it also subtly reveals the inherent flaws that can undermine such an economy. The world of Alice's Wonderland, with its whimsical characters and surreal adventures, serves as an allegorical backdrop to explore the less […]

1. Tell Us Your Requirements

2. Pick your perfect writer

3. Get Your Paper and Pay

Hi! I'm Amy, your personal assistant!

Don't know where to start? Give me your paper requirements and I connect you to an academic expert.

short deadlines

100% Plagiarism-Free

Certified writers