15 page paper – PSYCH

15 page paper double spaced in APA format
Topic: Economic Inequality
Already have sources & bibliography

FORCE FIELD ANALYSIS

PURPOSE:
Force Field Analysis is an approach to conceptualizing community problems and to planning
actions to address those problems. It is one product of Kurt Lewin’s action research approach to
community and social problems. The process of carrying out a Force Field Analysis simulates
many of the dynamics involved in actual community work.

In this paper, you will focus on the problem in terms of multiple ecological levels of analysis, not
merely at the individual level. This Force Field Analysis Exercise is designed as a simulation of
a series of community meetings, to build skills in focused thinking, group interaction, and
positive movement regarding a problem or issue of genuine concern. While Force Field Analysis
is typically carried out in a group, to simplify the process for the purpose of this course you will
be completing it as an individual. Select discussion boards and assignments during the semester
will allow you to discuss your topic and get feedback from classmates and the professor in lieu
of working in groups. The purpose of those assignments will be to imagine yourselves as a
community group or coalition meeting addressing a community or social issue and to provide
feedback to your peers.

FORMAT:

• Approximately 15 double-spaced pages (1-inch margins, 12-pt Times New Roman font)
• The paper must follow APA Format. Refer to the OWL Purdue APA formatting cite and

documents posted on Black Board for examples of formatting your paper.
https://owl.english.purdue.edu/owl/resource/560/01/

• The following headings and subheadings must be used in your paper:
Community Problem and Context
Description of the Problem
Root Causes of the Problem
Goals
Driving and Restraining Forces
Action Plan
Action Plan Outline
Community Psychology Concepts
Implementation Start-up Details
Analysis of Obstacles
Evaluation of your Overall Plan
Action Letter

• Submit via Turn-It-In
• POINTS: 100

DEDUCTIONS:
Late papers will be penalized 5 points per day. Please refer to the academic integrity policy of
the university, as students who violate this policy will be penalized.
http://www.wpunj.edu/human-resources/faculty-and-professional-staff-handbook/academic-
integrity-policy-for-students.html

EXTRA CREDIT:
5 points for attending one individual writing center session. To get this extra credit, students are
required to have the reports of the tutoring session sent to this professor prior to the term paper
due date.

SEVEN-STEP PROCESS

Step 1: Selecting a Community Problem and Context (apx: 1 paragraph)

• Write a brief introductory paragraph to your paper identifying the problem and context.
• Choose a community problem or issue of interest. It is best to choose a topic you have at

least some direct experience or knowledge with.
• Choose a community problem or issue that you care about, and that you are genuinely

committed to finding ways to foster positive change. If citizens’ commitment to change is
not genuine, community problems soon appear impossible to address. In addition, Force
Field Analysis is much more fun if you choose an issue you care about!

• Suggested Topics: illness and health, homelessness, drug abuse (including alcohol and
tobacco), domestic violence, sexual assault, child abuse and neglect, violence among
youth, elder abuse, poverty, environmental problems, access to childcare, the impact of
divorce, and issues of injustice such as racism or sexism.

o Your final choice of community problem should be specific and tangible; for
instance, binge drinking among college students.

• Next, choose a community where this problem occurs.

Step 2: Describing the Problem (apx. 2-3 paragraphs)
• Describe the community problem in specific detail. Avoid blaming individuals for the

problem. The more specific you can be about the people affected by the problem, and
about the community context, the better you can devise useful responses to the problem.

• If possible, talk with people or groups who are experiencing the problem or affected by it
in their own lives.

• Address the following questions:
o What is the community context of the problem? For instance, is the community

rural, urban, suburban, or other? What is its racial and ethnic makeup? What age
groups are predominant? Are other community qualities relevant to this problem?

o What behaviors constitute the visible aspects of the problem? When and where do
these occur?

o Who is involved in or directly affected by this problem? How could those affected
by the problem be described in terms of age, gender, socioeconomic status, race,
ethnicity, or other dimensions of human diversity?

o What else is important to know about the problem?
• YOUR PAPER MUST CONTAIN A MINIMUM OF 2 PEER-REVIEWED

JOURNAL ARTICLES DISCUSSING THIS PROBLEM.

Step 3: Identifying Root Causes of the Problem (apx. 1-2 pages)

• Discuss root cases of the problem.

• Understanding a community problem involves understanding something about its causes.
A good theory of the root causes of a community problem provides a guide to efforts to
prevent or lessen that problem.

• “Root causes” are the most basic, most significant causes of a problem. Some may be
individual factors, but others are factors at higher levels of analysis, such as
organizational, locality, or macrosystem (e.g., economic and social-political factors).

• To identify root causes:
o Review the research and scholarly literature on causes, risk and protective factors;

§ YOUR PAPER MUST CONTAIN A MINIMUM OF 3 PEER-
REVIEWED JOURNAL ARTICLES DISCUSSING THESE
FACTORS

o If possible, interview persons in the community, especially those who have
experienced the problem directly, not just professionals;

o Use the “But Why?” technique:
§ “But Why?” begins with the community problem you defined earlier. Ask

yourself: “Why does this problem occur?” Each time you identify a cause
of the problem, ask yourself, “But why does that occur?” Keep asking
“But Why?” until you arrive at the underlying factors that seem to be roots
of the problem. Repeat the procedure as often as needed to identify the
causes of the problem at multiple ecological levels of analysis.

• Refer to the link for Chapter 17 in Community Tools posted on Black Board.

Step 4: Clarifying a Goal (apx. 1 page)

• From the list of root causes, choose one causal factor that you would like to change.
• Make sure the factor that you pick is changeable, that it can be altered in a constructive

way that lessens the problem in your community setting. You may eventually plan to
attain this goal with a prevention/promotion program, a social policy, or another action
initiative.

• Write down the factor selected. Make it as specific as possible.
• Next, write a Goal Statement: a description of how you would like to see this causal

factor changed, to resolve or lessen the community problem.
• Make your goal feasible: something you can imagine happening, but that also would

represent a real improvement in the situation in your community setting.
• Make your goal specific: measurable or identifiable, so that you and others will know

when it has been attained.

Step 5: Identifying Driving and Restraining Forces (apx. 1-2 pages)

• Discuss all the Driving and Restraining Forces you can identify concerning the
community and goal you have chosen. This step is the heart of Force Field Analysis.

• Driving Forces are those that can push your community toward the goal you specified in
the previous step. These may be resources such as committed persons, organizations, or
funding which can help attain the goal. Driving Forces may also be intangible resources
such as a shared sense of community that motivates individuals to work together.
Potential driving forces can also be persons or groups who are not now involved, but
could be useful in addressing the community problem. However, consider potential
driving forces only if you believe that they can be mobilized readily for work on the

problem. It is a very human error to overestimate the number or strength of those who
agree with you or who will work with you. Be realistic.

• Restraining Forces are factors that resist or obstruct movement toward the goal
situation. These also may be community forces, persons, or organizations. Root causes of
a problem are restraining forces. So is resistance to change, a powerful community force.
Any group or person who would be threatened in some way by progress toward the goal
situation may also be a Restraining Force. Those who oppose your definition of the
problem or its causes may also be Restraining Forces. Essentially, Restraining Forces are
the factors already present in the community that keep the problem in existence, even if
only by ignoring it.

Figure 1 illustrates the relation of driving and restraining forces to the current situation and the
goal.

FIGURE 1: DRIVING AND RESTRAINING FORCES

CURRENT GOAL
SITUATION SITUATION

DRIVING FORCES RESTRAINING FORCES

Step 6: Prioritizing Driving and Restraining Forces (2 sentences)

• This information should be included under ‘Step 5’ in your paper. Conclude your ‘Step 5’
section by identifying the 3 Driving Forces and 3 Restraining Forces that will be the
focus of your action plan.

• Choose up to three important Driving Forces for your community to strengthen, in order
to attain your goal. These will be the first focus of your action plan.

• Then choose up to three important Restraining Forces for your community to weaken or
work around, to attain your goal. These will be the second focus of your action plan.

Step 7: Action Plan

• When you have prioritized up to three Driving Forces and Restraining Forces for action,
you are ready to plan a community initiative to attain your goal by strengthening these
Driving Forces, weakening or working around these Restraining Forces, or doing both.

• Typically, you will focus on your prioritized list of Restraining Forces. From this list, you
will choose one or two of these forces that you can most feasibly reduce. Your Action
Plan should describe in detail how you intend to reduce these Restraining Forces, and
thereby impact on the problem situation you identified earlier.

• The Community Tool Box website is a valuable resource for this planning
(http://ctb.ku.edu).

PART I: (apx. 2 pages)
• The first part of your Action Plan write-up is the Action Plan Outline, which serves as

an overview of the overall plan you are proposing. This write-up should give a broad
view of what you would like to see happen and how it will take place, and it should
reflect a realistic timeline. Think of it as an Executive Summary, Overview, or Flow
Chart. You can write it out or use outline form—whatever will allow you to best convey
what you are intending.

• Also, use the Internet or make other contacts necessary to help you determine (to the
extent possible) whether something like what you have been proposing has been tried
before. It’s not impossible that your Force Field process might take you to some familiar
solutions, but these are likely to result in first order change. So, you want to try to
reassure yourselves that you are not carrying out something that has recently been tried
and has been unsuccessful. Things you learn in this search process often lead to small but
important modifications in plans.

o Cite relevant sources! You are permitted to use websites here and can also include
peer-reviewed journal articles if relevant.

PART II: (apx. 1-2 paragraphs)
• Specify the Community Psychology Concepts that you have integrated into your Action

Plan Outline. This is a very important section, as it gives you a chance to explain
principles that may underlie your Outline but not be explicit or obvious. You can draw
from the textbook or any related readings for this.

PART III: (apx. 2 pages in numbered outline format)
• The third part of the Action Plan write-up consists of the Implementation Start-Up

Details. This will consist of a list of numbered steps that specify exactly what it will take
to get your Action Plan started, making no assumptions with regard to time and
resources. It takes time to set up meetings, gather resources, obtain funds, design a
program, etc. Don’t omit any steps. If there are steps that are necessary but are things you
can’t accomplish directly, your plan should reflect how you are going to get the resources
or support to get done what needs to happen.

• As you play out these details, you may find yourself needing to revise aspects of your
Action Plan Outline, particularly your timeline. You might not find yourself getting too
far into your Action Outline. That’s no problem. Just be sure to keep Community
Psychology concepts, principles, and values in mind and don’t allow yourself to
compromise these in the name of expedience, just to get the plan done. Expedience is
what often dooms social action plans and leads to first-order change efforts that allow
problems to persist. Be concise!

PART IV: (apx. 1-2 pages)
• The next part of the write-up is the Analysis of Obstacles. For each step corresponding

to each number of your Implementation Details, you should provide an analysis of the
obstacles to it and propose ideas to get around those obstacles. If you find that there are

significant flaws in your plan, or that the obstacles identified seem highly difficult to
overcome, that is not a serious problem. Your realistic, honest analysis is required here.
The best outcome is when you and your team, not someone else, discover the obstacles.
Realistic and creative planning around obstacles is an essential part of the Force Field
Analysis process.

• You can either write this out as a separate section OR combine with Part III. If you
combine with Part III, be sure your heading reflects that.

PART V: (apx. 1 page)
• Finally, you should provide a brief overview of an Evaluation of your Overall Plan. It

should address the question, “How will you know that the goals of your plan have been
attained?” What will have changed to let you know that you are being successful? What
indicators will be useful to you? Here, you can look at the research methods and designs
in Chapters 3, 4 and 14 of the textbook to help you figure out appropriate ways to
determine whether your actions have been successful, and, in the spirit of action research,
where they might be falling short and require revision/rethinking.

ACTION LETTER

• Write a brief (2 pages, double spaced) Action Letter to an appropriate person, agency,

media outlet, etc., with several or all of the following goals.
o Define the specific problem or issue you are addressing.
o Illuminate aspects of a problem that have gotten too little attention. This may

include causes that have been overlooked. Cite sources of specific information.
o Suggest causal factors that may have been overlooked in solutions proposed to

date.
o Advocate a specific, feasible course of action to address these aspects of the issue.

Examples include a new policy, new practices or ways to carry out an existing
policy, or a new or modified community program. Recognize that your ideas will
have costs (e.g., money, time, collaboration among groups). Advocate your course
of action assertively.

o Indicate areas that you think should have more research and public discussion to
analyze the issue.

• Choose a person or organization you want to address, the more specific the better.
Examples of places to which one might direct a letter include a newspaper (in your
hometown, or the location of your university, or your college newspaper), your
representatives or senators in the state legislature or the U.S. Congress, someone at your
university, someone at a relevant state agency, the editor of a magazine, the head of a
corporation or business, a philanthropy or foundation, or the writer of one of the source
materials you read for the project. You are free to quote from class readings, to
acknowledge that your work arose out of the work from a class assignment, and to take a
forceful position.

• You are not obligated to send the letters, but each one should be sendable.

RESEARCH ARTICLE

Race, Neighborhood Economic Status,
Income Inequality and Mortality
Nicolle A Mode*, Michele K Evans, Alan B Zonderman

National Institute on Aging, National Institutes of Health, Department of Health and Human Services,
Baltimore, Maryland, United States of America

* nicolle.mode@nih.gov

Abstract
Mortality rates in the United States vary based on race, individual economic status and

neighborhood. Correlations among these variables in most urban areas have limited what

conclusions can be drawn from existing research. Our study employs a unique factorial

design of race, sex, age and individual poverty status, measuring time to death as an objec-

tive measure of health, and including both neighborhood economic status and income

inequality for a sample of middle-aged urban-dwelling adults (N = 3675). At enrollment, Afri-

can American and White participants lived in 46 unique census tracts in Baltimore, Mary-

land, which varied in neighborhood economic status and degree of income inequality. A

Cox regression model for 9-year mortality identified a three-way interaction among sex,

race and individual poverty status (p = 0.03), with African American men living below pov-

erty having the highest mortality. Neighborhood economic status, whether measured by a

composite index or simply median household income, was negatively associated with over-

all mortality (p<0.001). Neighborhood income inequality was associated with mortality

through an interaction with individual poverty status (p = 0.04). While racial and economic

disparities in mortality are well known, this study suggests that several social conditions

associated with health may unequally affect African American men in poverty in the United

States. Beyond these individual factors are the influences of neighborhood economic status

and income inequality, which may be affected by a history of residential segregation. The

significant association of neighborhood economic status and income inequality with mortal-

ity beyond the synergistic combination of sex, race and individual poverty status suggests

the long-term importance of small area influence on overall mortality.

Introduction
Mortality disparities across racial and economic groups in the United States (US) are well
established [1]. In 1995, African Americans had a 1.6 times greater overall mortality risk than
Whites; unchanged from the mortality disparity observed in 1950 [2]. Low socioeconomic sta-
tus (SES) is also associated with an increased mortality risk for the US population. For adults
over age 50, those in the lowest quartile of SES had 2.8 times the mortality risk as those in the
highest quartile of SES [3], and this disparity remained significant after controlling for major
risk factors (1.6 times). The influence of race and SES on mortality are difficult to parse because

PLOS ONE | DOI:10.1371/journal.pone.0154535 May 12, 2016 1 / 14

a11111

OPEN ACCESS

Citation: Mode NA, Evans MK, Zonderman AB
(2016) Race, Neighborhood Economic Status,
Income Inequality and Mortality. PLoS ONE 11(5):
e0154535. doi:10.1371/journal.pone.0154535

Editor: Donald R. Olson, New York City Department
of Health and Mental Hygiene, UNITED STATES

Received: October 2, 2015

Accepted: April 14, 2016

Published: May 12, 2016

Copyright: This is an open access article, free of all
copyright, and may be freely reproduced, distributed,
transmitted, modified, built upon, or otherwise used
by anyone for any lawful purpose. The work is made
available under the Creative Commons CC0 public
domain dedication.

Data Availability Statement: Data are available
upon request to researchers with valid proposals who
agree to the confidentiality agreement as required by
our Institutional Review Board. We publicize our
policies on our website https://handls.nih.gov.
Requests for data access may be sent to Alan
Zonderman (co-author) or the study manager,
Jennifer Norbeck at norbeckje@mail.nih.gov.

Funding: The Healthy Aging in Neighborhoods of
Diversity across the Life Span study is supported by
the Intramural Research Program (Z01-AG000513) of
the National Institute on Aging, National Institutes of
Health (MKE, ABZ). Support was also provided by
the National Institute on Minority Health and Health

http://crossmark.crossref.org/dialog/?doi=10.1371/journal.pone.0154535&domain=pdf

https://creativecommons.org/publicdomain/zero/1.0/

https://handls.nih.gov

African Americans bear a disproportionate burden of US poverty and low education. The pov-
erty rate for African Americans in the US is 26%, but it is only 10% for non-Hispanic Whites
[4]. Similarly, 15% of African Americans have less than a high school education, while 8% of
non-Hispanic Whites fall in this category [5].

The influence of economic status on overall health and mortality extends beyond the indi-
vidual to the neighborhood [6]. Place of residence in the US follows patterns of race and eco-
nomic position, often due to residential segregation [7]. While racial segregation has decreased
over the last 40 years [8], income segregation, especially for African Americans, has increased
[9]. Low neighborhood economic status has been associated with an increased risk of overall
mortality [10], and mortality from cancer [11] and cardiovascular disease [12]. Residing in
neighborhoods with the lowest economic status (lowest 20 or 25th percentile) corresponded
with a 17–26% increased risk of overall mortality after controlling for individual SES and dis-
ease risk factors [13, 14]. The influence of neighborhood can be direct, through walkability or
violent crime, or indirect, through social position or discrimination. Due to the complex ways
in which neighborhood can influence health, researchers have proposed composite indices
which include multiple aspects of the neighborhood milieu (e.g., [15, 16]). However, research-
ers have found similar patterns between neighborhood economic status and health using only
a single measure of poverty or median household income [17, 18]. Recently, Oka [19] demon-
strated that median household income alone accounted for the same neighborhood affluence-
deprivation continuum as composite measures for four large US cities at the census tract level.

In addition to average economic levels, neighborhood influences also include income dis-
parities within neighborhoods. A number of studies have linked high income inequality with
an increase in adverse health outcomes such as overall mortality [20, 21]. This has led some
authors to posit that the criteria of causal association between income inequality and health
has been reached [21]. The relative income hypothesis asserts that chronic upward compari-
sons are stressful [22] and adverse health outcomes are the result of the physical effects of
chronic stress and social sensitivity [23]. Furthermore, research has identified an interaction
between neighborhood economic status and income inequality on health. Two studies from
California found that mortality risks for residents with low-incomes were highest in high SES
neighborhoods [24, 25]. This association between income inequality and health is not univer-
sally supported [26]. Quality housing, access to healthy food, effective schools and a safe envi-
ronment available in a high economic status neighborhood should benefit low income
residents in the same area. These potential benefits have provided the foundation for projects
promoting the relocation of low-income families such as Moving to Opportunity, which was
conducted in five major cities across the US [27]. The project demonstrated limited success in
reducing mortality risk factors for low-income residents who moved to more affluent neigh-
borhoods [28].

Many studies of race, individual poverty and neighborhood economic status on mortality
are limited in their conclusions due to existing correlations among these primary factors [12,
13]. Our study adds to previous work by employing a unique factorial design of race, sex, age
and individual poverty status, measuring time to death as an objective measure of health, and
including both neighborhood economic status and income inequality for a population of mid-
dle-aged urban-dwelling adults. The purpose of the current study was to identify significant
individual and neighborhood components that correlate with mortality disparities. A second-
ary aim was to compare the explanatory power of neighborhood economic status by a compos-
ite index compared to median household income.

Race, Neighborhood Economic Status, Income Inequality and Mortality

PLOS ONE | DOI:10.1371/journal.pone.0154535 May 12, 2016 2 / 14

Disparities, National Institutes of Health (MKE). The
funders had no role in the study design, data
collection and analysis, or preparation of the
manuscript.

Competing Interests: The authors have declared
that no competing interests exist.

Methods

Study population
The Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study is a
prospective longitudinal cohort study of 3720 socioeconomically diverse African American
and White adults initially 30–64 years old. Participants were selected using an area probability
sample from thirteen local communities in Baltimore, Maryland, during 2004–2009. The local
communities were chosen to span diverse levels of income and socioeconomic status and pro-
vide a representative distribution of Baltimore residents. Participants were 30–64 years old at
enrollment, and selected based on a factorial crossed design of sex, race, 5-year age group, and
poverty status (above/below 125% of the federal poverty guidelines based on household size).
The factorial design allows analysis of the separate and combined associations of sex, race, and
poverty status on health outcomes [29]. Participants were limited to those who self-identified
as either non-Hispanic Black/African American or non-Hispanic White/Caucasian. Enroll-
ment dates were similar for both races, with a median start date of August 2006 for African
American participants and December 2006 for White participants. For this study, 43 partici-
pants were excluded who provided addresses that could not be geocoded accurately as were
two participants who had permanent addresses just outside the Baltimore City limits, resulting
in a study sample of 3675 people. Detailed descriptions of the protocol and methods have been
previously published [30]. Approval for data collection was obtained from the National Insti-
tutes of Health, National Institute of Environmental Health Sciences Institutional Review
Board. All participants provided written informed consent.

Mortality information
Participants were followed prospectively via matching to National Death Index data (NDI;
National Center for Health Statistics, Centers for Disease Control and Prevention). Individual
data for matching included name, date and state of birth, sex, race, maiden name, and social
security number. Minimal loss of follow-up was expected because 94% of the participants pro-
vided a social security number, and participants were actively contacted for follow-up visits
throughout the study period. NDI data were available from the date of HANDLS enrollment
(August 2004–March 2009) through December 31, 2013, providing up to 9 years of follow-up
(mean and median of 6.9 years). Details included date of death and primary cause (Interna-
tional Classification of Disease 10th revision).

Neighborhood-level information
The entire city of Baltimore, Maryland was included with census tracts used as small areas fol-
lowing the 2010 Census definitions. Census tracts include 4000 residents on average and are
adequately sized for detecting spatial gradients and trends over time in overall mortality [17].
Data for each tract came from the American Community Survey (ACS) 5-year estimate files:
2006–2010 (referred to as 2010) and 2009–2013 (referred to as 2013). Nineteen variables previ-
ously identified as related to health outcomes were selected to cover seven domains of social
condition and relative socioeconomic disadvantage: education, employment, housing, occupa-
tion, poverty, residential stability and financial security. These variables formed the list for pos-
sible inclusion in a neighborhood index (S1 Table). The Gini coefficient [31] from the ACS
2010 file was used as the measure of income inequality for each census tract. For this study, the
percent Gini was used (Gini � 100) and thus values range from 0 (equal incomes) to 100 (all
income held by one person). The percent Gini was used so model coefficients would describe
the result of a 1% increase in Gini value.

Race, Neighborhood Economic Status, Income Inequality and Mortality

PLOS ONE | DOI:10.1371/journal.pone.0154535 May 12, 2016 3 / 14

Index development: Neighborhood Economic Index (NEI)
The 19 selected neighborhood-level variables were included in a principal component analysis
(PCA) to select a set of variables for the index (see S1 Appendix). Retained standardized vari-
ables were summed to create the index value without individual weights for greater consistency
over time, with low values indicating low neighborhood economic level. Internal reliability was
assessed by Cronbach’s alpha with values greater than 0.90 indicating high reliability [32].
Polyserial correlations [33] of the neighborhood index with poverty status and education level
assess the level of redundancy between the index and individual socioeconomic indicators.

Statistical analyses
Cox proportional hazards models were used to estimate mortality hazard ratios (HR) and their
Wald 95% confidence intervals (CI). Exact age at entry and exit of the study were used as the
measurement of time for the models [34]. Enrollment in HANDLS was entry into the study and
exit was date of death or December 31, 2013, whichever occurred first. Backward variable selec-
tion was performed using likelihood ratio tests to identify significant interactions and build the
final model. Main effects of sex, race and poverty status were included a priori based on the
design of the study and not removed during variable selection. Models were built separately
using the NEI (Model 1) and neighborhood median income (Model 2), and Akaike information
criterion (AIC) values were compared between the two resulting models. The assumption of pro-
portionality was assessed by inspection and testing of the Schoenfeld residuals [35].

All analyses were performed in the R program [36] version 3.1.3 except for estimated interac-
tion HRs which were calculated in SAS/STAT software version 13.2 (SAS Institute Inc., Cary
NC). All p-values are two-tailed and values less than 0.05 were considered statistically significant.

Results

Index development: Neighborhood Economic Index (NEI)
Baltimore, Maryland has 200 census tracts and 198 of them contain at least one household.
The PCA identified six variables for the index: percent of households with unemployed, per-
cent of households with people out of the workforce, percent of households receiving food
stamps, percent of households earning less than $30,000 annually, percent of households with
no car and percent of households in poverty (details in S1 Appendix). NEI values were calcu-
lated as the sum of the six individually standardized variables, and varied from -16.6 to 10.3,
with a median value of 0.5 (mean = 0). The six variables had high internal reliability, with a
Cronbach’s alpha value of 0.95, and the method demonstrated high repeatability when con-
ducted on the ACS 2013 dataset (S1 Appendix). Correlation between the NEI and Gini Coeffi-
cient, both for ACS 2010, was low (r = -0.33) indicating that while lower income
neighborhoods were more likely to have higher income inequality, the variables were measur-
ing different aspects of economic status. Correlation between the NEI and median household
income for ACS 2010 was 0.83 (p<0.001).

HANDLS study population
The 3675 participants in HANDLS represent 60% African Americans and 40% Whites living in
Baltimore City, Maryland with 59% living at or above poverty status and 41% below (Table 1).
Participants ranged in age at enrollment from 30–64, with an average age of 48. Economic status
of participants included those with high incomes; 20% of those answering the detailed question-
naire had a total annual household income of $50,000 or more (13% of African Americans and
29% of Whites). From enrollment (2004–2009) through 2013, 324 participants died. The most

Race, Neighborhood Economic Status, Income Inequality and Mortality

PLOS ONE | DOI:10.1371/journal.pone.0154535 May 12, 2016 4 / 14

common cause of death was cardiovascular disease (N = 95) accounting for 29% of the total mor-
tality, followed by cancer (N = 75, 23%). These were the two most common causes of death for
both races, but Whites had almost equal numbers of cardiovascular disease and cancer deaths
(28 and 30) while over half (N = 67, 62%) of the deaths in African Americans were due to cardio-
vascular disease (S2 Table). HIV/AIDS deaths primarily occurred in African Americans below
poverty, but accounted for only 8% of the total deaths in the cohort.

At their initial visit, HANDLS participants lived in 46 unique census tracts within the city
limits of Baltimore, Maryland (S1 Fig). These 46 tracts had a mean NEI of -0.79 (standard devi-
ation = 4.6) and were not significantly different in NEI value than the entire 198 tracts of Balti-
more (t-test, p = 0.36). The included tracts had a neighborhood median income ranging from
$12,384 to $87,619 compared with Baltimore overall which ranged from $9412 to $133,548.
The 46 tracts had a median income level of $32,738 and the distribution was slightly positively
skewed (skewness = 1.04). The average NEI for all HANDLS participants was -1.13 (median =
-1.31, standard deviation = 4.2), with African American participants generally living in neigh-
borhoods with lower NEI values than Whites (t-test, p<0.001). The average Gini coefficient was 44 (median = 43, standard deviation = 6.5). NEI values had low correlations with individ- ual socioeconomic variables of poverty status (r = -0.33) and education level (r = 0.19).

There were 324 deaths among the 3675 participants between enrollment and the end of
2013. Participants were followed for 6.9 years on average for a total of 25,186 person-years.

Table 1. Characteristics of the Healthy Aging in Neighborhoods of Diversity Across the Life Span Study Participants, Baltimore, Maryland, 2004–
2013 (N = 3675).

African American White

Variable Above Poverty Below Poverty Above Poverty Below Poverty

Participants, no. 1156 1041 995 483

Men, % 47 44 48 40

Deaths, no. (%) 70 (6) 146 (14) 65 (7) 43 (9)

Age at enrollment, no. (%)

30–34 119 (10) 112 (11) 106 (11) 53 (11)

35–39 140 (12) 135 (13) 126 (13) 58 (12)

40–44 149 (13) 149 (14) 137 (14) 70 (14)

45–49 203 (18) 213 (20) 170 (17) 96 (20)

50–54 185 (16) 188 (18) 168 (17) 79 (16)

55–59 207 (18) 138 (13) 153 (15) 71 (15)

60–64 153 (13) 106 (10) 135 (14) 56 (12)

Education at enrollment, no. (%)

<9 years 43 (4) 74 (7) 62 (6) 73 (15)

9–11 years 249 (22) 367 (35) 205 (21) 154 (32)

High School / GED 431 (37) 373 (36) 283 (28) 138 (29)

Some College 321 (28) 192 (18) 201 (20) 66 (14)

College Degree 104 (9) 30 (3) 189 (19) 24 (5)

Missing 8 5 55 28

Neighborhood Economic Index Score, mean (sd) -1.1 (3.8) -3.2 (4.9) 0.7 (3.2) -0.6 (3.0)

Neighborhood Median Income, median $32,214 $30,239 $36,957 $35,200

Gini Coefficient, mean (sd) 44 (6) 47 (7) 43 (6) 41 (5)

BMI: Body mass index calculated as kg/m2, missing for 867 participants

Neighborhood Economic Index based on American Community Survey 5-year Estimate Data, 2006–2010

Gini Income Inequality Coefficient from American Community Survey 5-year Estimates, 2006–2010, multiplied by 100

doi:10.1371/journal.pone.0154535.t001

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PLOS ONE | DOI:10.1371/journal.pone.0154535 May 12, 2016 5 / 14

Model selection using NEI (Model 1) or neighborhood median income (Model 2) resulted in
the same general model structure (Table 2). The Cox regression models for overall mortality
identified a significant three-way interaction among sex, race and poverty status with African
American men living below poverty having the lowest survival and African American women
living above poverty the highest. There was a differential mortality risk between African Amer-
icans and Whites across sex and individual poverty status (Table 3). African American men liv-
ing below poverty had almost twice the mortality risk as their White counterparts (Model 1:

Table 2. Multivariable Cox Regression Analysis on Overall Mortality, Healthy Aging in Neighborhoods of Diversity across the Life Span Study, Bal-
timore, Maryland, 2004–2013 (N = 3675).

Variable Model 1 HR 95% CI Model 2 HR 95% CI

Sex

Male 1.51 0.92, 2.47 1.51 0.92, 2.48

Female (ref) 1.00 1.00

Race

African American 0.86 0.51, 1.44 0.83 0.49, 1.40

White (ref) 1.00 1.00

Poverty Status

Above (ref) 1.00 1.00

Below 0.42 0.09, 1.95 0.37 0.08, 1.72

Gini Coefficient 0.98 0.96, 1.01 0.98 0.95, 1.00

NEI 0.96 0.93, 0.98* – –

Neighborhood Median Income** – – 0.84 0.75, 0.95*

Sex × Race 0.97 0.49, 1.93 0.98 0.49, 1.93

Sex × Poverty 0.47 0.21, 1.06 0.47 0.21, 1.06

Race × Poverty 0.76 0.38, 1.54 0.81 0.40, 1.63

Poverty × Gini Coefficient 1.04 1.00, 1.07* 1.04 1.00, 1.07*

Sex × Race × Poverty 3.03 1.12, 8.19* 3.00 1.11, 8.11*

HR: Hazard ratio, CI: Confidence Interval, NEI: Neighborhood Economic Index

* p<0.05

**Neighborhood median income in units of 10,000 (e.g., 1 = $10,000)

doi:10.1371/journal.pone.0154535.t002

Table 3. Mortality Hazard Ratios and 95% Confidence Intervals for African Americans relative to
Whites by Sex and Poverty Status, Healthy Aging in Neighborhoods of Diversity across the Life Span
Study, Baltimore, Maryland, 2004–2013 (N = 3675).

Below Poverty Above Poverty

HR 95% CI HR 95% CI

Model 1: Neighborhood Economic Index

Male 1.95 1.09, 3.51 0.84 0.53, 1.33

Female 0.66 0.41, 1.06 0.86 0.51, 1.44

Model 2: Neighborhood median income

Male 1.99 1.11, 3.57 0.81 0.51, 1.29

Female 0.68 0.42, 1.08 0.83 0.49, 1.40

HR: Hazard ratio, CI: Confidence interval

Models included three-way interaction of sex, race and individual poverty status and two-way interaction of

individual poverty status and neighborhood Gini coefficient

doi:10.1371/journal.pone.0154535.t003

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PLOS ONE | DOI:10.1371/journal.pone.0154535 May 12, 2016 6 / 14

HR 1.95; CI: 1.09, 3.51 and Model 2: HR 1.99; CI: 1.11, 3.57). The Gini coefficient was signifi-
cantly related to overall mortality in an interaction with poverty status, although the combined
association was small. High Gini values were associated with higher HR for poverty status on
mortality than those for low Gini values. For African American men, those below poverty had
more than twice the mortality risk as those above poverty at the 75th percentile of income
inequality, but the increased risk for those below poverty was only 81% higher at the 25th per-
centile of income inequality (Model 1, high Gini values: HR: 2.37; CI: 1.60, 3.52 and low Gini
values: HR 1.81, CI: 1.14, 2.89).

Both NEI and median household income were significant when added to models separately.
NEI was significantly and negatively associated with overall mortality, indicating that partici-
pants in areas of higher economic level had a lower risk and thus greater survival than their
counterparts living in lower economic areas. The 75th percentile of NEI values for HANDLS
participants had a 20% decrease in mortality relative to those at the 25th percentile of NEI val-
ues (HR: 0.80, CI: 0.69, 0.91). Neighborhood median income, in units of $10,000, was signifi-
cantly and negatively associated with overall mortality. The 75th percentile of median
household income values for HANDLS participants had a 17% decrease in mortality relative to
those at the 25th percentile of median household income values (HR: 0.83, CI: 0.73, 0.94). Both
models had adequate fit upon testing and review of the Schoenfeld residuals. The AIC scores
for the NEI Model 1 of 4137.5 and neighborhood median household income Model 2 of 4139.0
indicate that the models performed similarly.

Discussion
This study uses the power of the HANDLS stratified sample to examine race, and individual
and neighborhood economic status as they relate to disparate rates in mortality. We found that
overall neighborhood economic status and income inequality for those below poverty were
independently related to mortality, beyond the synergistic effects of sex, race and individual
poverty status. While African American men living below poverty had the highest overall mor-
tality among the sex, race and individual poverty groups, higher levels of neighborhood eco-
nomic status were associated with decreased mortality for all. This effect held whether NEI or
neighborhood median household income was used as the measure of neighborhood economic
status. We showed that the NEI was an objective measure of neighborhood economic status
with high internal validity, consistency over short time periods, and low redundancy with indi-
vidual measures of socioeconomic status, although neighborhood median household income
had the same relationship with mortality and resulted in a similar model.

While individual factors of race, sex and individual poverty level are known to be related to
mortality, we identified a significant interaction among these variables. African American men
with household incomes below 125% of the federal poverty level had the highest risk of mortal-
ity compared to other race, sex and poverty groups in the study. Racial disparities in mortality
have persisted over the last century [37], and disparities due to poverty [38] and gender [39,
40] are persistent and profound. African American men have a lower life expectancy (71.8
years) than White men (76.5), but the synergistic association of these three variables in
HANDLS with mortality suggest that several social conditions associated with health may
unequally affect African American men in poverty.

African American men may experience exceptional barriers to maintaining their health in
their communities. African Americans in prison have lower mortality than non-institutional-
ized men; African American male prisoners aged 15–64 have an age adjusted mortality rate
43% lower than the general population [41]. Prison has a protective effect against the leading
causes of death that differentially impact non-institutionalized African American men. Prison

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PLOS ONE | DOI:10.1371/journal.pone.0154535 May 12, 2016 7 / 14

may also provide access to continuous adequate healthcare that manages existing conditions
and treats any new diseases that emerge during the term of confinement. While prison is an
unhealthy environment associated with greater mortality for women and for White men,
prison mitigates the disproportionate mortality rate suffered by African American men when
residing outside the prison walls. Gains in life expectancy and improvement in health status
during the last 60 years that resulted from governmental social and economic policies
improved the health of African Americans; however, African American men did not benefit as
much as African American females [42, 43].

Governmental economic policies that improved employment and income for African
Americans also differentially benefitted African American women, leaving many African
American men behind [44]. Unemployment in African American men is twice the rate for
White men in the US [45], and is associated with increased mortality [46]. Although the educa-
tion gap is narrowing nationally between African Americans and Whites, African Americans
continue to have lower standardized reading and math scores [47]. In Baltimore, African
American 4th grade students scored lower than Whites in reading assessments, males score
lower than females, and students qualifying for free/reduced lunch scored lower than those not
eligible [48]. For 2013–2014, the estimated 4 year national high school graduation rate for Afri-
can American males was 59% compared to 80% from white males [49]. In Maryland, the gap
between African American males and White males was 17%. Graduation rate disparities for
African American males exist at the undergraduate level and particularly at the graduate level
exemplified best by the 36 year stagnation in application and matriculation rates of African
American males in medical school [50]. Educational attainment’s relationship with mortality
has changed over time, but they continue to be strongly associated [51].

Racial and economic disparities are often confounded, which along with residential segrega-
tion yields racial and spatial differences in health [7]. In HANDLS, as in other studies of metro-
politan areas [52], African Americans were more likely to live in areas of lower economic status
regardless of their individual economic status. In the US overall, income segregation among
African Americans families is 60% greater than among White families [9]. The greater Balti-
more-Towson metropolitan area ranks 18th out of 117 metropolitan areas in the US in family
income segregation with 29% of the families living in either poor or affluent neighborhoods.
Baltimore has a long history of residential segregation by race. In 1911, Baltimore Mayor
Mahool signed a segregation law separating city blocks for use by African Americans and
Whites. Baltimore was one of the 239 urban areas with official ‘residential security maps’ used
by the US Federal Housing Administration and private lenders during 1934–1968 to identify
areas risky for mortgages, usually African American neighborhoods [53]. While the 1968 Fed-
eral Housing Law made discriminatory practices by lenders illegal, there is evidence that the
practices continue. The cities of Baltimore, MD and Washington, DC reached a settlement
with Wells Fargo regarding steering approximately 4000 African American and Hispanic bor-
rowers during 2004–2008 into subprime mortgages when non-Hispanic White borrowers with
similar credit profiles received prime rate loans [54]. The original redlined areas east and west
of downtown Baltimore [55] are some of the areas with the lowest NEI using 2006–2010 ACS
data (S1B Fig).

We identified a significant relationship between the NEI and mortality after accounting for
individual level variables of race, sex and poverty status. This finding is similar to the associa-
tion between neighborhood economic status and mortality observed in a recent larger study
[13], although the HANDLS cohort includes a broader range of economic levels for both races,
including 20% of those answering the questionnaire having an annual household income
greater than $50,000. The health impact of neighborhood economic status may be through dif-
ferences in access to healthy foods [56, 57], exposure to crime and stress [58], and differences

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PLOS ONE | DOI:10.1371/journal.pone.0154535 May 12, 2016 8 / 14

in access to health care [59], or other less well-established factors such as proximity to sources
of toxic pollutants [60], inadequate city services such as infrequent trash disposal, or lax
hygienic enforcement leading to rodent infestations. A study of census tracts in Alameda
County, California identified an interaction between neighborhood economic status and indi-
vidual income level on mortality [25]. Low-income individuals had the highest mortality risk
in the highest neighborhood economic status level. It could be that our inclusion of neighbor-
hood income inequality accounted for a possible interaction between these variables in the
HANDLS cohort.

The association between income inequality and mortality differed based on individual pov-
erty status. High levels of income inequality were associated with higher HR for poverty status
on mortality than for those with low levels of income inequality. There are well-known effects
of macro-level income inequality on health. A recent review concluded that large income dis-
parities damage health, and that countrywide income disparities are increasing over time [61].
In ecological studies in the US, the association of income inequality and mortality differs by the
racial composition of the area considered [62, 63], and the degree of racial segregation con-
founds the income inequality/mortality relationship among African Americans [64]. Poor Afri-
can American families have a higher degree of segregation in US urban areas than other poor
racial groups [65], which may lead to confounding in ecological studies. There are fewer
reports of the effects of micro-level inequality, and fewer still of the association of income
equality and individual-level differences in survival. Research reviews support an overall signif-
icant negative effect of inequality on health [21, 23], however, the results may depend on the
spatial aggregation considered [66] and whether perceived health or actual health outcomes
are used. Researchers have found an increased likelihood of coronary heart disease [67] and
obesity [21] for those living in areas with greater income inequality. These findings correspond
with the current study where the most common cause of death was cardiovascular disease.

This study has several limitations. The HANDLS sample is representative of the diverse
urban-dwelling population in Baltimore, Maryland, and may not be representative of African
Americans and Whites living in other areas, especially those in suburban or rural communities.
Independent demographic analyses of the HANDLS sample determined it representative of
urban populations from U.S. cities with similar population densities and racial distribution,
namely, Atlanta, GA; Bridgeport, CT; Bridgeton, NJ, Buffalo, NY; Camden, NJ; Carson, CA;
Chicago, IL; Cleveland, OH; Detroit, MI; Harrisburg, PA; Hartford, CT; Oakland, CA; Spring-
field, MS; and Trenton, NJ [68]. Also, several variables that may have further explained the
results, such as incarceration history or wealth, were not collected in the HANDLS study. The
neighborhood level information was compiled at the census tract level and may not represent
meaningful neighborhood units. However, census tract analysis has been as consistent as
smaller census blocks, and more sensitive to gradients and change than larger zip code group-
ings [17]. Finally, only neighborhood data at study enrollment was included. Participants may
have moved to better or worse neighborhoods during the follow-up period. The primary
strength of this study is the HANDLS design which includes people above and below poverty
for both races living in the same city.

Use of composite indices has been a natural solution to measuring the complex social and
economic factors in a small area which could affect health outcomes. While originally these
indices were based on previous research and theory [69], recently indices have been developed
more objectively using analytic approaches such as principal component analysis [16]. We
introduced the NEI as an empirically derived measure of neighborhood economic status sepa-
rate from racial neighborhood composition. For HANDLS, the NEI was consistent over two
time periods and had high internal reliability. The Cox model with the NEI was similar to that
using the median household income, supporting the results by Oka [19] who found that the

Race, Neighborhood Economic Status, Income Inequality and Mortality

PLOS ONE | DOI:10.1371/journal.pone.0154535 May 12, 2016 9 / 14

variation in neighborhood affluence-deprivation across urban cities could be accounted for by
median household income as well as by a composite index. We extend these findings by dem-
onstrating that neighborhood median income provided the same explanatory power as an
objectively derived index in terms of mortality for the HANDLS study.

This study leveraged the HANDLS study’s unique factorial design of race, sex, age and indi-
vidual poverty status, measuring time to death as an objective measure of health, and included
both neighborhood economic status and income inequality for a population of middle-aged
urban-dwelling adults. Our findings add to the current body of knowledge by describing the
combined association of race, sex and individual poverty with mortality in an adult cohort.
African American men living below 125% of the federal poverty level were disproportionately
likely to suffer early mortality. The additional neighborhood variables of economic status, as
measured by the NEI, and income inequality, as measured by the Gini coefficient significantly
added to the model, indicating the separate association of these variables with mortality.

Future research should examine in more detail the effect of neighborhood economic level
on mortality by taking into account movement of people over time, as well as examining possi-
ble interventions. While our findings support the use of median household income across
small areas as an indicator of overall neighborhood economic status, it should be explored if
these findings hold for suburban and rural environments.

Supporting Information
S1 Appendix. Neighborhood Economic Index Development.
(DOC)

S1 Fig. Locations of Healthy Aging in Neighborhoods of Diversity Across the Life Span Afri-
can American and White Participants in Baltimore, Maryland 2004–2009, with Gini Income
Inequality Coefficient (A) and Neighborhood Economic Index (B) by Census Tract.
(PDF)

S1 Table. Census Tract Variables and Principal Component Loadings for Inclusion in the
Neighborhood Economic Index, Baltimore, Maryland.
(DOC)

S2 Table. Detailed characteristics of Deaths to Participants in the Healthy Aging in Neigh-
borhoods of Diversity Across the Life Span Study, Baltimore, Maryland, 2004–2013
(N = 3675).
(DOCX)

Author Contributions
Conceived and designed the experiments: NAM MKE ABZ. Performed the experiments: NAM
MKE ABZ. Analyzed the data: NAM ABZ MKE. Contributed reagents/materials/analysis tools:
NAM ABZ MKE. Wrote the paper: NAM MKE ABZ.

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Economic Inequality and Economic Crisis:
A Challenge for Social Workers

Gertrude Schaffher Goldberg

To social workers, extreme economic inequality is primarily a violation of social justice,
but this article shows how growing economic inequality since the mid-1970s was not
only unjust, but also dysfunctional to the U.S. economy and linked to the recent econom-
ic crisis with its devastating effects, particularly on the social work clientele. The article
identifies interrelated changes in ideology, the market economy, and government policies
since the mid-1970s; contrasts the political economy of this period with the preceding
post-World War II decades when the trend was toward a “shared prosperity”; and shows
how increased economic inequality and political consequences that undermined democ-
racy itself contributed to the economic meltdown. The analysis has implications for the
direction of social reform and for broadening the constituency of social movements in
pursuit of the social work mission of social justice. How social workers can contribute to
such movements and to a reduction of economic and political inequality is explored.

KEY WORDS; economic crisis; economic inequality; political economy; social justice; social movements

I
n everyday practice social workers encounter
—and try to counter—the effects of severe
economic inequality. Dauy we witness the

devastating effects of economic crisis—loss of jobs
and shelter, increasing hunger, and decline in
income and living standards. Social workers may
be on the shorter end of the stick, our jobs threat-
ened by cutbacks, our earnings too low to sustain
middle-class lifestyles. Social workers, however,
usually do not consider economic inequality from
another angle: its harmful effects on the economy.
This article shows how increasing economic in-
equality has contributed to economic dysfunction
and economic crisis in the United States.

From the perspective of economic inequality,
the 65 years since World War II can be divided
into two periods: (1) the fint three decades
when inequality, though ever present, was dimin-
ishing and (2) the subsequent 30 years when its rise
culminated in economic crisis. The article begins
by contrasting the two periods with respect to the
distribution of income and wealth, wages, unem-
ployment, and poverty. It then describes the politi-
cal economy of the first period or the relationship
between the democratic system of government and
the capitalist economy. Although inequality re-
mained a fact of American ufe in the first period, it
was during this time that according to the British
economist Andrew Shonfield (1965), a “new

capitalism” emerged, one in which the advance in
national income benefited people unable to gain a
share of prosperity through their earnings. Shon-
field also called attention to “the conscious pursuit
of fuU employment” (p. 63), a policy that enabled
more people to earn higher incomes. In retrospect,
this era may have been an anomaly in the history
of capitalism, owing, in the case of the United
States, to the federal government’s more active role
in the economy in response to the highly unusual
conditions that preceded it: the Great Depression
and World War II. Furthermore, competition with
the Soviet Union forced the leader of the “Free
World” to demonstrate the superiority of the “new
capitalism.” With the demise of communism and
of competition, capitalism, like all monopolies, has
less need to please its constituents.

The trend toward “shared prosperity” came to
a halt in the niid-1970s when the nation took a
“great U-turn” (Harrison & Bluestone, 1985).
Some reasons for this reversal are identified, and
the consequent political economy, one more akin
to traditional capitalism, is described. Discussion
of the second postwar period shows how the in-
teraction between economic and pohtical inequal-
ity contributed to economic dysfunction and to
near coUapse of the economic system. A subse-
quent section focuses on the proximate causes of
the meltdown—the expansion of credit and the

doi: 10.1093/SW/SWS005 ® 2 0 ) 2 National Association of Sociai Workers 211

housing bubble, both fueled by rising economic
and political inequality, specifically, growing
control of government by wealth and a burgeon-
ing financial sector. The concluding sections
point to implications for social reform and action
by social workers.

RISING ECONOMIC INEQUALITY
Escalating economic inequality in the past 30
years comes as no surprise. Yet even those who are
cognizant of the economic divide can be shocked
by how wide it has become. We encounter egre-
gious inequality wherever we look—at wages,
income, wealth, poverty, and unemployment.

In the decades after World War II, real wages
rose steadily along with productivity (U.S. Bureau
of Labor Statistics [BLS], 2010, n.d.). Thus, the
nation’s wealth was shared to a greater extent than
in previous eras. In contrast, between the U-turn
and the meltdown, output per person or produc-
tivity grew 85 percent while average hourly wages
fell 13 percent (in constant dollars) ßLS, 2009a,
2009b). The real value of the minimum wage
declined 30 percent between 1968 and 2006
(Bernstein & Shapiro, 2006).

Not everyone’s wages suffered. While the
average worker lost ground, chief executive
officer (CEO) pay was skyrocketing. In 1978, the
average CEO took home 35 times more than the
average worker—itself no small divide. By 2005
the ratio had risen to 262 or sevenfold (Mishel,
Bernstein, & Allegretto, 2007).

At the peak of shared prosperity, in 1973, the
poorest 20 percent of households nonetheless had
only 4.3 percent of total income. By 2003, this
tiny share had shrunk 20 percent, whereas the
middle fifth or quintile lost even more ground.
The share of the top quintile grew at the expense
of the bottom 80 percent, and yearly since 2000,
it garnered about half the nation’s total income
(U.S. Census Bureau, 2010b). By contrast, in the
earlier era, the incomes at the bottom increased
more than those at the top. Moreover, all quin-
tiles grew at a higher rate in the earlier period
than after the U-turn (see Figures 1 and 2).

Particularly egregious are the enormous and
disproportionate income gains of the top 1
percent of households. According to a report of
the U.S. Congressional Budget Office (CBO)
(2010), the average after-tax income of these
richest Americans in 2007—-just prior to the

Figure 1: Change in Real Family Income,
by Quintile and Top 5%, 1949-197

116

1L
Bottom 20%

100

1
Second 20«

111

11
114

11
99

1
L

Top 20%

1
Top 5%Source: Analysis of U.S. Census Bureau data in Economic Policy Institute, The State of

Working America 1994-95 (1994) p. 37

Figure 2: Change in Real Family Income,
by Quintile and Top 5%, 1979-2005

-1

Bonom 20%
less than
S24,616

Second 20%
S24.616-
S45,021

IS•
Middle 20%

S4S,O21-
S6S,304

1
Founh 20%

S68.304-
S103,100

1
1

rop20S6
$103,100
and up

1
1
Top 5%

SIS4,S00
and up

Source: U.S. Census Bureau, Historical Income Tables, Table F.3.

financial collapse—was $1,319,700. This was an
increase of $976,120 over the 1979 average, com-
pared with increases of only 111,200 and $2,400
for the middle and bottom quintiles, respectively
(in 2007 constant dollars). Analyzing these data
from the CBO, Sherman and Stone (2010) of the
Center on Budget and Policy Priorities pointed
out that the gaps in after-tax income between the
richest 1 percent and the middle and poorest fifth
of the country more than tripled between 1979
and 2007. Sherman and Stone concluded that the
new data, along with prior research, “suggest
greater income concentration at the top of the
income scale than at any time since 1928” (p. 2)—
the eve of our prior, disastrous fmancial crash.

If the families who began at the bottom had
moved up the economic ladder, such mobility
would have brightened the picture of growing
inequality. Viewing the income mobility of
U.S. families over nearly four decades (1969 to
1996), Mishel et al. (2007) found that from one

212 Social Work VOLUME 57, N U M B E R 3 JULY 2012

decade to the next, about haff who began in the
bottom quintüe tended to stay there, while another
21 percent to 26 percent landed in the second
lowest—a total of about three-fourths stiE in the
bottom 40 percent of the income distribution.
About the same percentages pertain to those who
began each decade in the top quintüe and either
stayed there or landed in the next highest quintüe.

Wealth is even more top heavy than income,
and it has become increasingly concentrated in
recent years. In one short interval—1995 to 2004
—when aggregate household net wealth nearly
doubled, almost all the net gains went to the top
quartOe of the income distribution p i , 2007). By
2004, the richest one-tenth owned 71 percent of
private wealth (Wolff, 2007). Top Heavy is the apt
titie of a study of the increasing inequality of
wealth in this country by Edward Wolff (1995), a
leading scholar of the subject.

During the period of shared prosperity, unem-
ployment, though not low, was less than it was in
ensuing decades, averaging 4.8 percent from 1949
to 1973, compared with 6.5 percent from 1974 to
2008 (Council of Economic Advisors, 1962,
2010). Unemployment not only spells lost income
for workers and increasing inequality; it also
means loss of potential output to the economy
(Ginsburg, 1995). Moreover, yean of relatively
high unemployment have contributed to stagnat-
ing wages. (When unemployment is high and
there are many more jobseekers than available
jobs, employers can hire the workers they need
without raising wages or providing attractive ben-
efits and working conditions.) The convene is
true when the labor market tightens. When un-
employment dipped slightly below 4 percent in
the 1990s—hardly fuU employment, particularly
for minority men—wages and benefits rose, espe-
cially for low-wage workers, and this occurred
despite counter-pressures from globalization
(Bemstein & Baker, 2003; Pollin, 2007). Unem-
ployment, of coune, reduces incomes and tax reve-
nues and increases government outlays to benefit
jobless workers, thus contributing to budget deficits.

Along with wages, income shares, and unem-
ployment, progress against poverty went into
reverse. The U.S. poverty rate was cut in half
between 1959 and 1973. Instead of falling with
rising total output and national income, the
poverty rate was almost 13 percent higher in 2007
than in 1973 (U.S. Census Bureau, 2010c).

Inequality marches on: between 2008 and 2009,
the number of millionaires increased by 1.1
million (Spectrum, 2010) while the poverty count
rose by 3.7 million (U.S. Census Bureau, 2010c).
Poverty is expected to keep company with reces-
sion, but an increase in millionaires?

To meet the severe challenges of the Great
Depression and World War II, the federal govern-
ment exerted more control over the economy. As
a result, the American people became accustomed
to a government that was larger and more active
than it was prior to the Depression. Government
spending and taxing policies reduced the severity
of recessions and mildly redistributed income.
Social welfare measures enacted in the 1930s, par-
ticularly unemployment compensation, served as
economic stabüizers, expanding during recessions
and thereby reducing the contraction of consumer
spending that would otherwise have wonened a
downturn. New Deal regulatory poUcies, meant
to reduce the disastrous financial speculation that
led to the stock market crash of 1929, were main-
tained in the first postwar era. The progressive,
higher tax rates of World War II were continued
in peacetime, and rising real wages were the quid
pro quo for relative labor peace. “Say what you
want about the violations of free-market econom-
ics” (p. 64), wrote progressive economist Robert
Kuttner (2007), “a system that produced nearly
three decades of egalitarian economic growth at
an average annual growth rate of 3.8% cannot be
all bad” (p. 64). International comparison of the
two periods on such measures as unemployment
and growth in world economic output favor the
earlier one (Skidelsky, 2009). For example, the
growth rate of global gross domestic product was
one-third lower between 1980 and 2009 than
from 1951 to 1980.

Three Republican Presidents—Dwight Eisen-
hower, Richard Nixon, and Gerald Ford—left
the New Deal and the Fair Deal, the New Fron-
tier, and the Great Society “virtually intact”
(Bums, 1989, see also, Griffiths, 1982). The fint
Republican president after 16 years of Democratic
rule, Eisenhower repealed none of the major New
Deal laws, and, in fact, disability insurance was
enacted under his aegis. Eisenhower is considered
conservative, yet one revisionist account of his
presidency emphasizes its public works programs
and holds that Eisenhower viewed his highway
program as both infrastructure improvement and

GOLDBERG / Economie înequatïty and Eeonomie Crisis 213

job creation (Wilson, 2009). Political scientist
Hugh Wilson considered this active labor market
policy akin to the employment of jobless worken
during the Great Depression. Unemployment
insurance, by contrast, is passive labor market
policy.

The period also saw incremental growth in the
welfare state, notably expansion of social insurance
through wider coverage of the elderly population,
initiation of disabihty and health insurance (Medi-
care), and indexing or adjusting retirement bene-
fits to rise in the cost of living. Toward the end of
the period, public assistance grew to include food
stamps, health care (Medicaid), and, for a time,
“welfare rights,” an oxymoron before and after
this time. Government-subsidized housing also
grew in the 1960s. Nonetheless, even as income
support was expanding, pohtical scientist Harold
Wilensky (1965) dubbed the United States a
“reluctant welfare state.” Wilensky wrote, “We
move toward the welfare state but we do it with
ill grace, carping and complaining all the way”
(p. xvii).

To call attention to progress in the decades fol-
lowing World War II is not to overlook the great
inequality that persisted, particularly for African
Americans. The black poverty rate was at its
lowest in 1973, when it was still 3.7 times the
white rate. From 1954 to 1973, black unemploy-
ment averaged 9.2 percent, twice the white
average (U.S. Department of Labor, 1974). Yet it
is important to point out that in the 1960s, the
pohtical and civO inequalities of race and gender
were reduced by such landmark measures as the
Civü Rights Act of 1964 (P.L. 88-352) and the
Voting Rights Act of 1965 (P.L. 89-110).

An important exception to the maintenance of
New Deal reforms—one that would facilitate
return to traditional, hard-edged capitalism—was
the successful attack on labor immediately after
World War II. The Wagner Labor Act of 1935
(P.L. 74-198)—the Magna Carta of Labor—was
greatly weakened by the Taft-Hartley Act of 1947
(also known as the Labor Management Relations
Act) passed over the veto of President Harry
Truman by a Republican-controlled Congress.
Actually, the attack on labor that culminated in
the Taft-Hartley Act began in the late 1930s
(Piven & Cloward, 1977). Taft-Hartley prohibited
many forms of strikes, secondary boycotts and
closed shops. Particularly important was its

requirement that union officers sign noncommu-
nist affidavits. Along with the accelerated anti-
communism ofthe 1950s, this resulted in the loss
to the labor movement of its most progressive
leaders, those more inchned to organize women
and minorities in the expanding service sector
(Schrecker, 2000; Yates, 1997). A labor move-
ment temporarily strengthened by alignment with
New Deal Democrats was weakened and less able
to resist later efforts by capital to turn back the
clock. Nonetheless, in the postwar yean labor
bargained for substantial economic gains for its
membership that enabled many blue-coUar
workers to achieve a middle-class lifestyle.

STAGNATION A N D CHANGE OF COURSE

By the late 1960s, the war-shattered economies of
Europe and Japan had recovered, leaving a com-
placent U.S. manufacturing sector insufficiently
competitive. The 1973 oil embargo of the
Organization of Petroleum Exporting Countries
created inflationary pressures at the same time that
the economy was stagnating. This perplexing new
phenomenon, inflation and stagnation together,
was called stagflation. Inflation \vas also related to
the government’s failure to raise taxes to pay for
the Vietnam War. These developments contribut-
ed to a “profit squeeze,” a drop of 40 percent in
the average net after-tax profit rate of domestic
nonfinancial corporations between 1965 and the
second half of the 1970s (Bowles, Gordon, &
Weisskopf, as cited in Harrison & Bluestone,
1985). Other challenges to the U.S. economy
cited by economist Richard Wolff (2009) include
technological innovation, globalization, increased
immigration, and rising labor-force participation
of women. However, the effects of some of these
are debatable, as is their timing in relation to the
U-turn. Although technological advancement dis-
places jobs in one sector, it may create employ-
ment in another. A surge in immigration was not
a factor at the time. Moreover, research on the
employment effects of immigration on various
population groups is inconclusive (Goldberg,
2002). Women’s employment, particularly labor
market entry of mothers with young children,
was partly a response to, rather than a cause of,
their husbands’ displacement and lower wages,
and it was also a necessity for the increasing
numbers of divorced, separated, and never-
married mothers. Women’s entry also created jobs

214 Social Work VOLUME 57, N U M B E R 3 JULY 2012

in child care, fast-foods, the automotive industry,
and so forth, and they seldom displaced men.
Indeed, women had to fight hard to be hired in
jobs tradidonally taken by men. In any case, eco-
nomic woes shattered faith in the reigning
Keynesian economic paradigna that prescribed a
larger and more strategic government sector, and
the eclipse of Keynesianism gave impetus to the
revival of market supremacy and laissez-faire gov-
ernment policies.

In an effort to reduce its competitive disadvan-
tage, business could have stepped up investment
to increase productivity and innovation. Instead,
most businesses adopted alternative strategies
that increased inequahty (Harrison & Bluestone,
1985). In response to the profit squeeze, business
squeezed labor—through wage freezes and new
work arrangements that increased the flexibility
with which worken could be hired, fired, and
scheduled. Globalization—transfer of capital and
business operations to lower-wage areas of the
world—was another strategy that followed rather
than preceded the U-turn, and it was encouraged
both by federal tax policies that give more favor-
able treatment to income earned abroad than
stateside and government financing of overseas
manufacturing plants. Still another strategy was to
abandon production for paper profits, again re-
sulting in manufacturing job losses. For example.
General Electric sold off its consumer apphance
manufacturing division and concentrated on its
more profitable credit corporation (Phillips, 2002).
Similarly, General Moton emphasized financial
services over auto production (Wolff, 2009). Still
another strategy was to lobby govemment to
reduce taxes and regulations.

Ideological Change
Through an unprecedented political mobilization,
the business community and its allies in the media
and academia sought to relegitimate the free
market and to effect a return to a govemment that
keeps its hands off the economy. This process was
initiated in 1973 and 1974 by a small group of
Washington’s most influential corporate lobbyists
(Edsall, 1984). At the beginning of the 1970s, a
handful of Fortune 500 companies had lobbyists
in the District of Columbia, but by the end of
the decade, 80 percent were represented there
(Greider, 1992). Political action committees
(PACs) were established to get around restrictions

on individual campaign donations, and by the end
of the 1970s, business PACs gready outpaced
labor unions as major contributors to pohtical
campaigns (Greider, 1992).

Corporations began to advertise their ideas
in the media and to pour money into new and
refurbished foundations and think tanks to
develop and promulgate the revived ideology of
laissez-faire (Goldberg & Collins, 2001). Social
theory reconstructed the poor, recasting them as
an “unworthy” and undeserving “underclass.”
This campaign culminated in the 1996 repeal of
Aid to Families with Dependent Children
(AFDC) (for examples of recasting the poor, see
Gilder, 1981; Murray, 1984).

Antigovernment Ideology in the Oval
Office
In 1980, Republicans succeeded in uniting the in-
terests of their fiscally conservative, pro-business
base with a portion of the Democrats’ New Deal
coalition. As Edsall (1991) observed, such issues as
affirmative action, the welfare expansion, school
busing, women’s liberation, gay rights, abortion,
and perceived high taxes had become offensive
to numerous, former Democratic voters (1991).
Many white people, including blue-coUar workers,
defected from the party they associated with these
policies, particularly because it was no longer seen
as the purveyor of prosperity.

The 1980 election of Ronald Reagan landed a
principal proponent of limited govemment in the
White House. The watchword of his administra-
tion, set forth in Reagan’s inaugural speech, was:
“Govemment is not the solution to our problem;
govemment is the problem” (Reagan, 1981).
What followed were the antüabor, antiwelfare,
pro-business, tax-reduction policies known as
Reaganomics. Of particular interest to this discus-
sion is Reagan’s refusal to reappoint Paul Volker
as Federal Reserve chairman because Volker be-
lieved that financial markets must be regulated.
Instead, Reagan chose deregulation advocate Alan
Greenspan. The choice of Greenspan, as Nobel
laureate Joseph Stightz (2010) observed, signaled
that “dereguladon ideology … had taken hold”
( p . XVÜ).

Centrist Democrats
The period following the U-tum, like earlier ex-
cessively money-driven eras, featured a centrist, if

GOLDBERG / Economic Inequality and Economic Crisis 215

not right-leaning. Democratic party. Historian
Arthur Schlesinger, Jr. (1986) compared President
Jimmy Carter to President Grover Cleveland,
another conservative Democrat and businessman
who served two terms during the Gilded Age. Al-
though Carter initially expanded the Comprehen-
sive Employment and Training Act (P.L. 93-203),
the fint substantial government job creation
program since the Great Depression, and proposed
relatively liberal welfare reform, he became less
progressive later in his term. Carter’s (1979)
“Crisis of Confidence” speech to the nation pre-
saged Ronald Reagan’s much deeper denigration
of government’s capacity to solve problems. The
later Carter years also included the beginning of
deregulation and a military buUd-up that crescen-
doed under his Republican successor.

Democrat Bill Clinton, despite a progressive,
populist penona, presided over the repeal of
AFDC and the quintessential New Deal banking
regulation, the Banking Act of 1933 (or the Glass-
Steagall Act) (P.L. 73-66). Repeal meant that
commercial and investment banks were no longer
separated and that the high-risk culture of the
latter that traditionally managed rich people’s
money would prevail. Globalization policies that
largely ignored workers’ rights and environmental
protection were also carried on by Clinton, virtu-
ally without change &om his Repubhcan prede-
cessor George Walker Bush.

Plutocracy
Former Nixon advisor Kevin Phillips (2002) de-
scribed “the relentless takeover of U.S. pohtics
and policymaking by large donors to federal cam-
paigns and propaganda organs” (p. 322). This, of
course, signifies the emergence of plutocracy and
consequent blunting of the capacity of a demo-
cratic government to reduce economic inequality
through regulatory and redistributive policies.

The increasing amounts of money spent in
election campaigns is a barometer of this change.
In 1976, winning Senate incumbents spent an
average of 1610,000; in 1986, $3 million; and by
2000, $4.4 mühon, a more than sevenfold increase
(Common Cause Congressional Hearing, as cited
in Phillips, 2002). In 1996, candidates who raised
the most money won 92 percent of the time in
the Senate and 88 percent in the House. At the
turn of the century, John McCain, then an advo-
cate of campaign finance reform, called the system

“an elaborate influence-peddling scheme by
which both parties conspire to stay in office by
seUing the country to the highest bidder” (Phil-
hps, 2002, p. 325). The recent Supreme Court
decision that government may not ban election
spending by corporations can only increase capi-
tal’s stranglehold on democracy.

“Financialization”
The influence of the financial sector was
exemplified by President-elect Bill Clinton’s
abandonment of the populism of his presidential
campaign. Candidate Chnton promised an
economy that “put people first.” However, even
before taking office, Clinton recognized that rich
people were “running the economy” and that
“we help the bond market Pay lowering deficits]
and we hurt the people who voted us in” (Wood-
ward, as cited in PoUin, 2003, p. 91). Robert
Rubin, co-senior partner of Wall Street giant
Goldman Sachs, head of Clinton’s National Eco-
nomic Council and later his treasury secretary, was
only one of several advisors urging the
president-elect to focus on deficit reduction
(Rubin 8c Weisberg, 2003).

The great increase of election contributions
from the financial sector was concurrent with its
rising prominence in the economy. Robert
Rubin had been a fundraiser for the democrats
since the early 1980s (Rubin & Weisberg, 2003).
Contributions to poHdcal campaigns from finance,
insurance, and real estate (FIRE) rose from what
Phillips (2002) described as “peanuts” in the early
1980s to the election cycle of 2000 when it was
collectively the largest donor. It was also the
biggest spender on lobbying—more than $200
million in 1998 (estimate by the Center for Re-
sponsive Politics). That was the same year that Wall
Street lobbied heavily and successftiUy for repeal of
Glass-Steagall (Phillips, 2002; see also, Kuttner,
2007). Big money spent on elections and lobbying
paid off—in the hands-off policy of government.

Actually, Wall Street had it both ways: deregu-
lation and government protection. The Gramm-
Leach-Bliley Act of 1999 (also known as the
Financial Services Modernization Act of 1999)
(P.L. 106-102) extended Federal Deposit Insurance
Corporation guarantee to investment banking. As
Johnson and Kwak (2010) pointed out, bank em-
ployees and shareholders could reap profits from
increasingly dsky activities, “but now the federal

216 Social Work VOLUME 57, N U M B E R 3 JULY 2012

government was on the hook for potential losses”
(p. 134). Only a few years later, the govemment
did bau them out.

The big campaign donations and lobbying that
bought deregulation for FIRE were financed with
off-the-chart FIRE salaries. The top 50 hedge and
private equity fund managers earned an average of
$588 million in 2007, 19,000 times that of the
average worker (S. Anderson, Cavanagh, Collins,
Lapham, & Pizzigati, 2008). By the mid-1990s
FIRE was responsible for a larger proportion of
the total economy than manufacturing (Phillips,
2002). The economy and politics had been
“financialized.”

The Media and Inequality
The more economic inequality in a society, the
less open and free are its mass media. This is the
conclusion drawn from research on the media in
100 democratic nations (Petrova, 2008). Because
the economic interests of the wealthy are inimical
to those of the vast majority of voters, it is in their
interest to limit the range of policy options
covered in the media.

Contributing to that limitadon in the United
States was increasing “media monopoly.” Between
1983 and 2004, the number of corporations con-
trolling most of the newspapers, magazines, radio
and television stations, book pubHshen, and movie
companies shrank from 50 to five (Bagdikian,
2004). The media watchdog. Fairness and Accuracy
in Reporting (FAIR) held that “mergers in the
news industry have accelerated, further limiting the
spectrum of viewpoints that have access to mass
media” (FAIR, n.d.). The viewpoint of the media
was largely that of their owners.

Wage-setting Institutions
In studying “the collapse of low-skill wages”
economist David HoweU (1997) found that the
culprit was not primarily technological innova-
tion. Low-wage workers actually improved their
skills, but their wages nonetheless fell. The culprit
is policy changes leading to the decline of wage-
setring institutions, namely the federal minimum
wage and the labor movement. The steep drop in
the real value of the minimum wage has already
been noted, as have political changes that weak-
ened the labor movement, even in the period of
shared prosperity. Including 35 percent of wage
and salaried workers at its height, union

membenhip had already dechned by one-third
between 1950 and 1973.

Ronald Reagan declared war on labor by firing
striking federal air controllen, denying food
stamps to strikers not already on the roUs, and
making antüabor appointments to the National
Labor Relations Board. By 2004, the percentage
of union members among wage and salary
workers (union density) was only 12.5 percent,
just over half of the 1973 figure (G. Mayer,
2004). Govemment and business policies that
contributed to diminished employment in manu-
facturing—labor’s former stronghold—were addi-
tional reasons for greatly reduced union density.
Union members have higher wages and better
workplace benefits (Mishel et al., 2007). Thus,
reduced union density, like decrease in the
minimum wage, increased economic inequality.

ECONOMIC INEQUALITY AND ECONOMIC
MELTDOWN
In explaining the meltdown, economist Arthur
MacEwan (2009) emphasized the “nexus of
faetón” that have been identified in this discus-
sion: “growing concentration of political and
social power in the hands of the wealthy; the as-
cendance of a perverse leave-it-to-the-market
ideology which was an instrument of that power
and rising inequality, which both resulted from
and enhanced that power” (p. 23). This perspec-
tive takes into account both the commanding
heights of the economy and its lower reaches.
Arising from this “nexus of factors” are develop-
ments proximate to the meltdown that wül be
discussed in detaü later—the expanding role of
credit, increased deregulation, and the housing
bubble.

The approach taken here gives some weight to
agency, that it was a choice on the part of U.S.
business to make workers pay the price for the
profit squeeze instead of rising to its challenge
through innovation. By contrast, others on the
left hold that the factors associated with the melt-
down are endemic to capitalism—extreme eco-
nomic inequality, the consequent inabüity of
some consumers to meet their needs through
their earnings, a vast accumulation of profits creat-
ing “a giant pool of money” in the hands of
capital and lack of sufficient productive investment
outlets for it (Blumberg & Davidson, 2008 on the
“giant pool of money”; Foster, 2008; Magdoff &

GOLDBERG / Economic Inequality and Economic Crisis 217

Sweezy, 1988). The tendency of such analysts is to
regard the combination of sustained growth and
equity after World War II as unique in the history
of capitalism, only temporarily displacing its struc-
tural contradictions (Vidal, 2009).

The contrasting perspective—on agency and
choice—is consistent with the view that the polit-
ical economies of capitalist countries are not
homogeneous. Others, for example, are less wary
of “big government.” Cross-national study shows
that wealthy capitalist countries differ substantially
with respect to poverty prevention and the size
and scope of their welfare states (Esping-
Andersen, 1999; Goldberg, 2002, 2010). Despite
retrenchment in nearly all welfare states in recent
years, the relative poverty rates (percentage of the
population with less than 50 percent of median
income) in 2000 were 7.3 percent and 8.4 percent
in France and Germany, respectively, compared
with over twice these rates, or 17.0 percent, in the
United States. Canada and the United Kingdom,
though often compared to the United States in
welfare state typologies (Esping-Andersen, 1999),
had considerably lower poverty rates (12.4 percent
and 13.7 percent, respectively). Lower rates,
ranging from 5.4 percent to 6.6 percent, were
found in the Netherlands, Denmark, Finland,
Norway, and Sweden (Luxembourg Income
Study, n.d.). In these capitalist countries, the range,
level, and coverage of social welfare benefits such
as subsidized child care, paid parental leave, elder
care, sickness insurance, and public pensions are
wide, and the extent to which government
income transfers reduce poverty based on market
income alone also differs greatly. Culture and polit-
ical traditions make a difference. Rugged individu-
alism is a recurring, if not persisting, value in the
United States, and so, from its founding, is wariness
of the power of a central government.

PREDATORY LENDING A N D OTHER

REGULATORY FAILURES

Economic conditions created necessitous prospec-
tive borrowers and, owing to the recent accumu-
lation of a “giant pool of money,” a financial
sector with a compulsion to lend, even at
increasing risk. AHve and well in contemporary
America, victim-blaming has it that greed and
overconsumption led to increased borrowing,
indebtedness, and bankruptcy. To the contrary.
Harvard law professor Elizabeth Warren and

Amelia Warren Tyagi (2003) found that in 2000,
the average middle-class family with two children
and the male parent earning the median income
spent less (inflation adjusted) on food, clothing,
and appliances than their counterparts in 1973 but
more on health insurance and housing—the latter
to gain access to better, safer schooling for their
children. A second car and child care for the now-
typical two-earner family drove the expenses of the
average family in 2000 up still further. At the later
date, reasons for borrowing and indebtedness in-
cluded downsizing and lower wages. More than
doubling in the last 30 years of the century, single-
mother families swelled the ranks of indebted con-
sumers (U.S. Census Bureau, 2010a, Table 4).

In the 1980s the credit card industry began ag-
gressively marketing its services to a wider range
of consumers: middle-class people, worken un-
employed by corporate downsizing and recessions,
college students, retirees, the working poor, and
the recendy bankrupt. The result was huge profits
for lenders and rising indebtedness of ordinary
folks. Consumer debt rose from 67 percent of dis-
posable personal income in 1973 to 30 percent
more than disposable income in 2005 (Mishel
et al., 2007).

From the nation’s earliest days, states had pro-
tected citizens from aggressive lenders by liiruting
the amount of interest that could be charged on
consumer loans. This changed when a 1978
Supreme Court decision {Marquette Nat. Bank of
Minneapolis v. First of Omaha Service Corp) permit-
ted lenders in a state with liberal usury or
interest-rate ceilings to lend at those rates to con-
sumers in states with more restrictive ceilings.
After the Marquette decision, banks aggressively
and successfully lobbied state legislators for liberal-
ization of state interest-rate ceilings (Ellis, 1998;
Manning, 2000). Following this, credit cards were
issued to people who previously would have been
denied credit altogether, or certainly large
amounts. The result was a huge increase in per-
sonal bankruptcies (EUis, 1998).

With the collapse of regulatory control over in-
terest rates, high subprime mortgage rates became
possible. Banks fat with profits from credit card
lending applied the same aggressive marketing
techniques they had used to increase credit cards
to the sale of subprime and other unconventional
mortgages that required little or no proof of
income and assets (Warren & Tyagi, 2003).

218 Soeiat Work VOLUME 57, N U M B E R 3 JULY 2012

Dereguladon of finance abetted predatory lending.
Some buyen who qualified for convendonal terms
were nonetheless induced to take out subprime
mortgages because the interest rates on these were
higher. African Americans were targeted by preda-
tory lenders. In fact, middle-class African American
neighborhoods had higher rates of subprime mort-
gages than poor white neighborhoods (Warren &
Tyagi, 2003).

Intended to minimize the risk of these sub-
prime mortgages were the complex financial in-
struments known as derivatives. According to the
editors of the New York Times, derivadves were
“at the heart of the bubble, the bust, the bail-
outs.” (“Congress passes financial reform,” 2010,
p. A26; see also Stiglitz, 2009). Credit-default
swaps, a form of derivatives, are packages of mort-
gage loans for which banks that bought subprime
mortgages sought insurance. Because insurance
was regulated, the sellen of insurance on these
loans called them “credit default swaps” to escape
regulation. In 1998, the head ofthe Commodity
Futures Trading Commission proposed regulating
these derivatives but was roundly opposed by Bill
Clinton’s Treasury Secretary Robert Rubin, his
deputy Lawrence Summen (later head of the Na-
tional Economic Council), and Federal Reserve
chief Alan Greenspan Qohnson & Kwak, 2010;
Kuttner, 2007; SdgÜtz, 2009).

Lenden were encouraged to extend credit to
riskier borrowen because they felt protected by
securitization of the insurance on their packages
of mortgage loans. Between 1998 and 2005, the
number of subprime loans tripled, and the number
securitized increased 600 percent (C. Mayer &
Pence, as cited in Johnson & Kwak, 2010). What
turned out to be false security was the result of the
dubious assumptions on which the experts based
their computer-generated estimates of default:
average defaults at an earher time when the assets
and income of borrowen were carefriUy scrutinized
(Blumberg & Davidson, 2008).

As long as housing prices rose, borrowen could
refinance when their mortgages became unafford-
able, and this, in tum, created more business for
the lenden. When the housing bubble bunt and
prices began to fall, it was no longer possible to
escape through refinancing, and many borrowen
were unable to cover their mortgage payments
through their regular incomes. When people de-
faulted on their mortgages, the value of credit-

default swaps fell steeply, their values could not
be determined, no one would buy them, and
some banks were left holding huge amounts of
“toxic assets” (MacEwan, 2009). The stage was set
for a federal bailout.

Leveraged buyouts (LBOs), another failure of
reguladon that spread in the 1980s, used tax-
deductible borrowed money to take over a target-
ed company with its own assets as collateral—an
example of making paper profits rather than im-
proving products and productivity. LBOs wrecked
good companies hke the once highly profitable
Simmons Mattress Company, destroyed jobs, and
at the same time, netted millions for the equity
groups that acquired companies through hostile
takeovers (Creswell, 2009). Congress and the
Securities and Exchange Commission could have
prevented hostue takeoven but did not. Kuttner
(2007) considered this an example of “a move
away from the prudent habits of an earher era—
one that remembered the excesses of the 1920s”
(p. 98). Forgetting the consequences of earher
free-wheehng periods is one explanation of the
wildly speculative behavior that emerged on Wall
Street before the crisis. Some observen consider
this a recurring process in capitahsm (Fox, 2009;
Minsky, 1986). The United States is particularly
prone to historical amnesia in this and other areas.

RECOVERY A N D REFORM

The prescription for recovery and refomi can be
inferred from this analysis. Reregulation of the fi-
nancial sector; measures to reduce control of poh-
tics by economic ehtes; and a stronger, more
progressive labor movement are needed if we are
to reduce the fundamental problem of economic
inequahty. Policies to reduce inequality include
the following: increases in social welfare, both the
range of needs covered and the level of benefits,
and the assurance of living-wage jobs for all who
want to work. With increased income; broader
and more adequate coverage of health care,
housing, and child care; and availabüity and af-
fordability of public transportation, lower- and
middle-income consumen could meet their needs
without feehng obhged to borrow beyond their
capacities.

Full employment is more consonant with the
work ethic and penonal well-being than income-
support alone. To achieve this goal, govemment
can create hving-wage jobs that repair and recreate

GOLDBERG / Economic Inequality and Economic Crisis 219

flagging social and physical infrastructures as well
as green the economy. Such jobs, many of which
can be fiUed by the social work cuéntele, would
begin to meet our vast, unmet needs for child and
elder care, affordable housing, public transporta-
tion, retrofitting energy-guzzling structures, and
development of an alternative fuel infrastructure
(Baiman et al., 2009; Bell, Ginsburg, Goldberg,
Harvey, & Zaccone, 2007; Ginsburg 8c Goldberg,
2007).

Such job creation resembles the New Deal
work programs planned and administered by
social workers Harry Hopkins and Aubrey Wil-
liams. Path breaking though they were, these
work programs did not employ women and mi-
norities in proportion to their need (Rose, 2010)
We can improve on the New Deal model by em-
phasizing jobs in the social—child and elder care,
education, health care—along with the physical in-
frastructure. A new industrial pohcy to revive U.S.
manufacturing would create jobs, increase oppor-
tunities for productive investment outlets, and
decrease dependence on the financial sector
(Pollin & Baker, 2009). These changes would
require a substantial involvement of the federal
govemment.

How we can afford these changes? A tax on fi-
nancial transactions is a frequendy proposed
revenue source, as is decreasing military spending
to genuine defense needs, such as dismantling of
costly military bases around the world, not to
mention unjustified foreign wars. High on the list
is discontinuance of the Bush tax cuts that were
expected to cost the U.S. Treasury $2.5 trillion
between 2001 and 2010, over half of which ben-
efitted the richest 5 percent of taxpayers (Center
for Tax Jusrice, 2009). Before these tax reduc-
tions, the federal budget was not only balanced,
but also in surplus.

Ideology played a prominent role in economic
and political changes that increased inequality and
contributed to the meltdown. Reform requires a
different set of values. President Franldin Roosevelt
took advantage of financial collapse and its severe
aftermath to articulate different values: “The money
changers have fled from their high seats in the
temple of our civuization. We may now restore that
temple to the ancient tmths… [to] social values
more noble than mere monetary profit” (Roose-
velt, 1933). New Deal deeds often fell short of lofty
New Deal values, but these values were nonetheless

important underpinnings of the less-than-perfect
reforms that found their way into the statute books.

Is the ideology of the free or unregulated
market and hands-off govemment in decline? The
money changers, despite failures that nearly im-
ploded the world economy, remain in the temple.
In the view of some knowledgeable observers, the
power of Wall Street has increased Qohnson &
Kwak, 2010). So far, it has fared better than Main
Street. The stock market recovered, but unem-
ployment hit the double-digit mark in October
2009 and continued to hover near 10 percent for
months. Financial interests are opposed to reregu-
lation. By late 2009, lobbyists representing banks
and other business interests working on financial
regulation outnumbered consumer advocates 25
to one Qohnson & Kwak, 2010), and financial in-
terests spent nearly 1600 mülion to weaken regula-
tory reform (“Congress passes financial reform,”
2010). Yet Congress enacted the first regulatory
legislation in a generation in July 2010. Although
the legislation may not go far enough to hmit the
speculative practices that preceded the meltdown,
it has a powerful consumer protection component.
The real question is how effectively the new law
will be implemented. Financial interests are pre-
paring a “lobbying blitz” hoping to succeed in im-
plementation where they fell short in blocking
enactment (Lichtblau, 2010). Wall Street still
cooks up exotic schemes. After the meltdown,
bankers were planning to buy “‘hfe settlements,'”
insurance poUcies that elderly people sell for
cash—$400,000 for a SI miUion policy was one
figure. These poUcies would be packaged into
bonds and resold to investon who would receive
the payouts when insurees die (f. Anderson, 2009).
The perpetrators of these and similar schemes,
such as taking out mortgages for dead people,
would be at home in Gogol’s satire of a would-be
landowner who purchased “deal souls” or de-
ceased peasants from their masters as collateral for
the purchase of land.

WHAT CAN SOCIAL WORKERS DO?

Social workers need to be concemed with a
wider range of policy and advocacy issues than
their current repertoire, including some that were
important in the profession’s infancy. A critical
issue is control of the political system by econom-
ic ehtes. More social workers should become in-
formed about political organizations and more

220 Social Work VOLUME 57, N U M B E R 3 JULY 2012

actively involved in them. NASW’s Political
Action for Candidate Election is one way to work
for candidates who support social work’s policy
agenda. It is particularly important to become in-
volved with organizations that seek to Umit the
pohtical power of wealth, thus facüitating election
of officials less beholden to economic elites and
freer to support measures to reduce inequality. A
task for social work educators is to increase stu-
dents’ understanding of how democracy is under-
mined by the heavy hand of money.

Although some social workers were in the fore-
front of government job creation in the 1930s,
the profession thereafter has been more concerned
with welfare than with work. Unemployment,
even at half the current rate, leaves millions jobless
or marginally employed, not to mention the
social and economic effects of loss of income and
a valued social role. Social worken could contrib-
ute to the reduction of inequality by participating
in organizations that advocate direct job creation
by government. Successful living-wage campaigns
and efforts to raise the minimum wage and the
Earned Income Tax Credit would decrease in-
equality. A stronger labor movement would also
contribute to this goal and be a powerful voice
for the working class. A way to do this is to
support the Employee Free Choice Act of 2009
(H.R. 1409) that would make it easier for
worken to join unions and reduce firing and
harassment of those who take part in union orga-
nizing. Another would be for more social workers
to join unions and, as members, to advocate
for labor’s comniitment to reforms benefiting
workers generally, not just union memben.

Social workers are well aware of the country’s
abysmally low poverty standard that, at $21,756
for a family of four (2009), excludes all but the
extremely poor. Their advocacy of a higher stan-
dard could result in increasing the beneficiaries
and constituencies for reform. We could follow
the European model by defining poverty in terms
of inequality rather than lack of bare necessities.
Wealthy European democracies have long defined
poverty as excessive inequality or an income less
than 50 percent of the median. In recent yean,
most of these countries nations have adopted a
higher relative standard, less than 60 percent of
the median. In 2004, that would have meant nearly
one in four Americans was poor (Luxembourg
Income Study, n.d.). One-fourth of a nation would

be harder to ignore than the 14 percent counted as
poor by the official U.S. standard (2009). An alter-
native, developed by social worker Diana Pearce,
realistically estimates family expenses in different
geographic areas. In 2010, meeting basic needs or
achieving self-sufficiency in the Bronx, the
New York City borough with the lowest living
costs, required $60,934 for a family of three, over
triple the official standard of $18,310 (Pearce,
2010). Beginning in 2011, the Census Bureau will
use a supplemental poverty measure (SPM) intend-
ed to measure a broader set of expenditures but not
expected to replace the current standard. Social
worken should evaluate the SPM, determine
whether it or another measure should replace the
official standard, and advocate for their choice.

The high cost of meeting basic family needs
shows that numerous families above the median
income, including many social workers, are hard-
pressed and vulnerable to predatory lending. Who
was protecting families against these predaton? In
earlier days, some setdements would have taken
on that role, and they advocated as well for con-
sumer protection and regulatory measures. In
addition to consumer education, social worken
should press for implementation of recently
enacted consumer protection laws.

Revening the continuing march toward egre-
gious economic inequality requires a movement
comparable in scope and commitment to the
great mobilizations that brought civu and political
rights to all our people. Social movements are
thought to consist of both direct beneficiaries and
conscience constituents (Edwards & McCarthy,
2004), but this analysis of the relationship
between economic inequality and economic dys-
function implies a blurring of this distinction. If
great inequality harms the economy and puts
much of the population at risk, then reducing
economic injustice would aid the income groups
that have lost the most ground since the great re-
venal of the 1970s and those who collectively
have lost trillions of doUan in homes, wealth, and
jobs as a result of the economic crisis. Much of
the rest of the population who are less directly af-
fected by the crisis would, nonetheless, stand to
benefit from a more stable economy and less lop-
sided distribution of income.

With this penpective social worken might be
more likely to identify their interests with those of
their clients—as some did in the social worken’

GOLDBERG / Economic Inequality and Economic Crisis 221

rank and fue movement in the 1930s (Ehrenreich,
1985). In addition to becoming politicized by rec-
ognizing their own position in the economic
system and their stake in economic justice, social
workers might be more likely to engage in politi-
cal socialization of their clients: the reframing of
social experience or consciousness raising such as
that which led women to seek political redress of
gender inequality. Social workers could also “bear
witness” to the suffering wrought by inequality
and the unemployment crisis and could encour-
age their clients to do so as well.

In meeting their ethical obligation to challenge
social injustice, social worken can appeal not orüy
to a substantial portion of the public that faUs
short of self-sufficiency. They can also appeal to
Americans in all economic strata, who stand to
gain from an economy that is at once more just
and more stable.

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Work Education annual program meeting, November 6,
2009, San Antonio, TX. The author thanks Julie Gooper
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comments on an earlier version of this article.

Original manuscript received June 7, 2010
Final revision received November 18, 2010
Accepted November 22, 2010
Advance Access Publication August 30, 2012

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367

PJSS 15 (3) pp. 367–386 Intellect Limited 2016

Portuguese Journal of Social Science
Volume 15 Number 3

FREDERICO CANTANTE, RENATO MIGUEL CARMO, NUNO DE
ALMEIDA ALVES AND ANTÓNIO FIRMINO DA COSTA
CIES, ISCTE – Instituto Universitário de Lisboa

Trends in income inequality:

Comparing the United States

and Portugal1

ABSTRACT

This article presents a comparative analysis of the United States and Portugal in
terms of economic inequality from the early twentieth century to the present decade.
We use different measures of inequality from several statistical sources. The arti-
cle revolves around three complementary points. The first is a synchronic and
diachronic analysis of economic inequalities in Portugal and the United States, the
second is the issue of redistribution of income and the final analysis addresses the
evolution of top incomes in both countries.

INTRODUCTION

The article addresses economic inequality in Portugal and the United States
and revolves around three different points. We first conduct a synchronic
and diachronic analysis of economic inequality in the two countries using
Organization for Economic Cooperation and Development (OECD) countries
as a reference. What is the position of these two countries regarding economic
inequality in the OECD universe? How did income inequality evolve in the
last three decades in Portugal and the United States? Did they go through
similar patterns or were there important differences between them? The anal-
ysis then focuses on the issue of income redistribution. How big is the impact

KEYWORDS

economic inequality
top incomes
redistribution
Portugal
United States
OECD

1. This study was carried
out at the Observatório
das Desigualdades
(Inequality
Observatory, CIES,
ISCTE-Instituto
Universitário de Lisboa)
and was supported
by the Fundação
Luso-Americana para
o Desenvolvimento
(Luso-American

PJSS_15.3_Cantante_367-386.indd 367 2/22/17 3:19 PM

Frederico Cantante | Renato Miguel Carmo …

368 Portuguese Journal of Social Science

of redistributive mechanisms in Portugal and the United States? Which redis-
tributive mechanisms are more important in each country? The third point is
an analysis of top incomes and their growth in the two countries over the long
term. Is the intensity of income concentration at the top similar in Portugal
and the United States? Have these inequality measures been historically stable
or did they change quite significantly over the last century? To what extend
has income concentration at the top been one of the main forces behind rising
economic inequality in Portugal and the United States?

Income inequality has been the main focus of several studies of Portuguese
and US societies. The uneven distribution of wages and income, which mainly
rely on educational and class inequality, has been highlighted as the core
explanation for the increase of economic inequality in Portugal over the last
decades (Carmo et al. 2015; Cantante 2014; Costa et al. 2015; Martins et al.
2014; Rodrigues et al. 2012). This analytical perspective has been comple-
mented by an analysis of redistribution policies, the impacts of which are
considered comparatively low (Alves 2012; Rodrigues et al. 2012). Regarding
the United States, most studies have highlighted the role of income and
wealth concentration at the very top as the main driver of economic inequality
(Piketty 2013; Krugman 2007; Piketty and Saez 2007).

This article will discuss and foster some of these analytical footsteps,
developing a direct comparative analysis of these two very different countries
for the first time: countries that share a common structural feature of high
internal economic inequalities. For that, several measures of inequality and a
variety of sources will be used.

A comparative analysis of a particular social fact or phenomenon entails
examining the comparability of empirical universes of reference from a meth-
odological and theoretical point of view. The cross-referencing, opposition
or synthesis of information on two or more empirical study referents means
questioning the pertinence and admissibility of this exercise on the basis of
the profile or characteristics of the universes compared. So, how can a study
that chooses economic inequality as a central subject use as empirical refer-
ences two countries with aggregate income levels that are so very different?

With a gross domestic product (GDP) of 10,830.3 billion ($11,594.4bn) in
2011 the United States was the country with the highest aggregate income in
the world. It was higher than the GDP of the entire euro area and substan-
tially higher than that of China. Portugal’s GDP on the other hand was
184.0bn ($270.1bn). To get a clearer idea of the size of US GDP, it is around

63 times that of Portugal. This aggregate income gap could be attributed to
another substantial difference in scale between the two countries: popula-
tion. While the population of Portugal was around 10.5 million according to
the 2011 census, that of the United States was approximately 308.7 million
(2010 census). In other words, the US population is 29.4 times larger than
Portugal’s. In spite of this huge demographic difference, it is much smaller
than that in economic share. The disproportion between the aggregate
income in the United States and Portugal is much greater than the demo-
graphic disparity.

This means that GDP per inhabitant in the United States is much higher
than in Portugal. In 2011, Portugal’s per capita GDP was 19,500 purchasing
power standards (PPS),2 77% of that in the 27 EU countries (EU27=100%),
while in the United States it was 37,100 PPS, 48% higher than the EU27. For an
idea of the magnitude of this economic indicator in the United States, per capita
GDP in Germany was 30,300 PPS, ‘only’ 21% higher than the EU average.

Development
Foundation). The
content of the article
represents only the
views of its authors.

2. PPS is an artificial
currency unit.
Theoretically, one
PPS can buy the same
amount of goods
and services in each
country. However,
price differences
across borders mean
different amounts
of national currency
units are needed for
the same goods and
services depending on
the country. PPS are
derived by dividing any
economic aggregate of
a country in national
currency by its
respective purchasing
power parities. PPS
is the technical term
used by Eurostat for
the common currency
in which national
accounts aggregates
are expressed when
adjusted for price
level differences using
PPPs. Thus, PPPs can
be interpreted as the
exchange rate of the
PPS against the euro.
(Eurostat).

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Aggregate economic income indicators, such as GDP or gross national
income (GNI) per capita,3 can be used as approximate predictors of the stand-
ard of living of a country’s population. If we analyse the Human Development
Index (HDI), we find that macro-economic indicators tend to be associated
with differences in living standards. It is enough to compare the GNI per
capita in countries with a very high HDI with those that have a medium or
low HDI. This is not a linear ratio, however, and there are cases in which living
standards (e.g. health and education) are higher than a country’s economic
wealth and vice versa. One of the reasons for this is the internal distribution of
income. A country may be very rich, but if income is concentrated in a minor-
ity of the population, the standard of living and well-being of the majority will
tend not to correspond to this level of income. The oil-exporting countries in
the Middle East are a good example of this type of disparity.

The use of indicators like GDP or GNI when characterizing a coun-
try’s economic well-being and associated standards of living is a panoramic
approach to their social reality. These are significant structural indicators
because they provide information about ‘how much is produced and the aver-
age income generated or distributed in a country, which, if used properly, can
generate material well-being’ (Ramos 2013: 37). But a look at the economic
pie tells us nothing about how it is sliced up. Refining our analysis of the
social well-being and standard of living of a country’s population also means
focusing on its income distribution structure, especially in terms of dispos-
able income. Although there is a huge difference between the aggregate prod-
uct generated in Portugal and the United States, both countries have very
high levels of inequality in the distribution of income. While it is true that
the amount of income produced and the way it is allocated per inhabitant
is a feature that clearly sets Portugal and the United States apart among the
OECD countries, domestic economic inequality brings them closer together.

ECONOMIC INEQUALITY AS A STRUCTURAL FEATURE OF SOCIETIES

Several studies have underscored the idea that economic inequality tends
to have negative effects on the functioning of societies and the population’s
living standards. The Spirit Level by Richard Wilkinson and Kate Pickett was
perhaps one of the most important and effective contributions to the dissemi-
nation of this argument (2009). They demonstrate that in the OECD countries
the societies with higher levels of economic inequality are also those with the
worst performance in such a variety of areas as levels of trust, life expectancy,
infant mortality, obesity, children’s educational performance and murder rate,
among others. Based on the above universe of countries, this theory defends
that rather than aggregate income, an indicator that cannot be correlated to
these types of social problems, economic inequality has multidimensional
negative impacts on the way these societies are structured.

The view that inequality is not harmless and tends to have adverse effects
on the community is now more widely accepted by academe and a number
of international institutions. A good example of this is the fact that the United
Nations Development Programme (UNDP) has produced a human develop-
ment index adjusted to a country’s degree of economic inequality. The UNDP
estimates that economic inequality in countries worldwide results in an aver-
age 23.3% reduction in their human development index (HDI). This figure
was 33.5% in the countries with a low HDI in 2012, 24.2% in those with a
medium HDI, 20.6% in those with a high HDI and 10.8% in those with the

3. Gross domestic
product is the result
of production within
a country, even
contributions from
non-residents. Gross
national income is ‘the
income received by a
country’s residents,
regardless of where the
production processes
in which they involved
occur’ (Ramos 2013: 34).

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highest HDI. In this last group, the United States is one of the countries
that showed the greatest loss, dropping thirteen places in the HDI rankings
(United Nations Development Programme 2013).

If internal economic inequality has a negative effect on the functioning of
societies and people’s general living standards, it must be taken into account
when measuring well-being and social development. These statistical correla-
tions make even more sense when comprehensively backed up by reflection
on the structural nature of inequality and an analysis of the social processes
that cause it to multiply. Following Pierre Bourdieu’s theoretic and conceptual
heritage, Alain Bihr and Roland Pfefferkorn claim social inequalities tend to
be passed down from one generation to the next (2008), to interact with each
other and accumulate. In other words, they are systemic. Inequality carries a
social history as baggage and potentially extends to different spheres of life in
society (Carmo 2010). Inequality tends to condition social mobility processes
and reduce the scope of opportunities within people’s reach. The social
inequality production and reproduction processes, the intensity and sense of
which also depend on the way institutions deal will them (e.g. school or public
policies), have a potential effect on people’s life conditions and available
opportunities. From the point of view of social structuring processes, inequal-
ity has a potentially harmful effect on social mobility, development and use
of skills and talents, tending to reproduce phenomena like poverty and social
exclusion. Inequality of economic, educational or relational resources influ-
ences inequality of opportunities (Dubet 2010).

The systemic negative effects of inequality, especially from an economic
viewpoint, can also be analysed from a perspective of collective action and
the influence wielded by lobbies in institutions and public policies. This is
one of the analytical lines followed by Joseph Stiglitz (2012). He contends the
economic elite in the United States has been imposing its interests and world-
view on politics, thereby ensuring public policies help reproduce and intensify
social inequality and perpetuate their dominant position in the social structure.
Tax policies that favour the wealthy or channel revenue to them are exam-
ples of rich people’s ideological, legal and institutional control of political deci-
sion making. Stiglitz believes the takeover of political power by the country’s
economic elite has helped reduce levels of trust and social cohesion, stiffen
social structures (reducing equal opportunities) and weaken the tax revenue
needed for public investment in education, infrastructure or technology. The
most structural effect of inequality is, however, the creation of institutional,
legal, political and cognitive conditions that guarantee its reproduction:

The more egalitarian societies work harder to preserve their social cohe-
sion; in the more unequal societies, government policies and other insti-
tutions tend to foster the persistence of inequality.

(Stiglitz 2012: 77)

Social and economic inequalities can be politically, legally and institution-
ally increased or reduced. In other words, the structuring of inequalities is not
unequivocal, the way they evolve and interact does not follow a logic inde-
pendent of the way society deals with them, especially the way public poli-
cies include and act on them. It is therefore necessary to bear in mind that
the reproduction and accumulation of inequalities are not a teleological fatal-
ity, a self-explanatory – self-referential social dynamic – but rather a possi-
bility moulded by a number of other variables. In certain legal, political and

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institutional frameworks, inequality can therefore decrease and not be repro-
duced. Tax policies are a particularly effective tool in mitigating economic
inequality in terms of market and disposable income (Alvaredo et al. 2013;
Atkinson et al. 2010), although the institutions that regulate the labour market
and education resources are also important factors that help define how
income is distributed (OECD 2011; Krugman 2007).

As inequality is an important feature of any society and a factor that influ-
ences society’s social, economic and political structuring processes, an analy-
sis of inequalities in general and economic inequality in particular is a basic
theoretical and methodological tool in a comparison of countries. In this case,
we are comparing two societies with high degrees of economic inequality.

It is important to include a brief methodological note before discussing
the different issues. The facts and arguments in this study are essentially
based on a secondary analysis of official statistical sources or data produced
by researchers and international institutions. In some cases, the information
is directly comparable as the data are harmonized, though this is not always
so. In these cases, we provide the available information while referring to the
methodological differences behind the production of the statistics in question.

The impossibility of comparing data may simply be due to the fact they
do not exist in one of the countries or that the periods for which information
exists do not exactly coincide. When this happens, we combine a comparison
of the available information with a presentation of the data for only one of
the countries. As a rule, however, we present statistics that can be compared.

TWO SOCIETIES WITH A HUGE GAP BETWEEN RICHEST AND POOREST

The OECD has been warning of greater economic inequality in a number of
its member countries in recent decades. It did so first in ‘Growing unequal?
Income distribution and poverty in OECD countries’ (2008) and has contin-
ued in more recent works, such as ‘Divided we stand: Why inequality keeps
rising’ (2011). In both studies, the United States and Portugal are among the
OECD countries with the highest levels of economic inequality. The data in
the more recent survey show the United States and Portugal (plus Israel) at
the top of the second group of countries with the greatest economic inequal-
ity, behind Chile, Mexico and Turkey. The degree of inequality in disposable
income in these last three countries vastly exceeds that of the other members
with Gini coefficients of 0.4 (or in Chile close to 0.5).4

The data in Table 1 are an update of the information in the report
mentioned above and refer to disposable monetary income per equivalent
adult, i.e. the economic resources of households after social transfers, taxes
and social security contributions.5

In 2010, the Gini coefficient was 0.380 in the United States and 0.344 in
Portugal. These figures are the fourth- and sixth-highest in OECD countries
and are way above the average. An analysis of the extent of economic inequal-
ity in the two countries can be based on another two measures.

The S80/S20 ratio is a measure of inequality that compares the ratio
between total income received by the top and the bottom quintile. In the
United States, the income of the 20 per cent richest was 7.9 higher than the 20
per cent poorest, while in Portugal the ratio was 5.7.

An analysis of economic inequality using ratios can also use smaller groups
(quantiles) for comparing distribution of income, e.g. the richest 10% and the
poorest 10 per cent (S90/S10). Table 1 shows that the degree of economic

4. The Gini coefficient
is a measure that
synthesises the
dispersion of a certain
indicator in a single
figure. When measuring
income inequality,
the coefficient is 0 if
all individuals have
the same income,
or 100 or 1 if all the
income is concentrated
in one person. It
thus measures
the dispersion of
income based on a
hypothetical reference
scenario of perfect
equality. It is more
sensitive to incomes
closer to mean incomes
and less sensitive to
the disparities between
the two extremes.

5. In recent years, the
OECD has been using
a scale of equivalence
that consists of
adjusting each
individual’s income to
the size of his or her
household based on a
scale of ‘equivalence
elasticity’ of 0.5.
This means that the
income of the people
in the household
is adjusted by the
square root of the
size of the household.
For example, in a
household of four
people, each one’s
income would
correspond to the
division of the
household’s total
income by two (the
square root of four).
This method does not,
however, distinguish
between adults and
children and means
that ‘a household’s
economic needs
increase less than
proportionally with its
size’ (OECD 2008: 41–42).

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Source: Statistics, List of key indicators (OECD).

Note 1: Countries ranked in descending order of Gini coefficient.

Note 2: The data on Chile, Hungary, Ireland, Japan, New Zealand, Switzerland and
Turkey are for 2009.

Table 1: Measures of inequality in disposable income in the OECD countries
(2010).

Gini coefficient S80/S20 S90/S10

Chile 0.508 13.8 30.0
Mexico 0.466 12.7 28.5
Turkey 0.411 8.4 15.1
United States 0.380 7.9 15.9
Israel 0.376 7.8 13.6
Portugal 0.344 5.7 9.3
United Kingdom 0.341 5.6 10.0
Spain 0.338 6.6 13.1
Greece 0.337 6.0 10.8
Japan 0.336 6.2 10.7
Australia 0.334 5.7 8.9
Ireland 0.331 5.4 9.1
Canada 0.320 5.3 8.9
Estonia 0.319 5.3 8.8
Italy 0.319 5.6 10.2
New Zealand 0.317 5.1 8.0
South Korea 0.310 5.7 10.5
Poland 0.305 4.8 7.7
France 0.303 4.5 7.2
Switzerland 0.298 4.6 7.3
Netherlands 0.288 4.3 6.9
Germany 0.286 4.3 6.7
Hungary 0.272 4.0 6.0
Luxembourg 0.270 3.9 5.6
Sweden 0.269 4.0 6.1
Austria 0.267 3.9 5.9
Belgium 0.262 3.9 5.6
Slovakia 0.261 3.8 5.9
Finland 0.260 3.7 5.4
Czech Rep. 0.256 3.6 5.4
Denmark 0.252 3.6 5.3
Norway 0.249 3.7 6.0
Slovenia 0.246 3.6 5.3
Iceland 0.244 3.5 5.3

OECD 34 0.313 – 9.4

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inequality in the United States measured with this indicator is much higher
than in Portugal. The income of the richest 10% was 15.9 times greater than
that of the poorest 10%, while in Portugal it was 9.3, similar to the average for
OECD countries (9.4).

The figures for these three measures of inequality in the United States are
higher than in Portugal. Although Portugal’s inequality levels are higher than
in most of the OECD countries in the Gini coefficient and S80/S20 ratio, its
figure for the S90/S10 ratio is in line with the other OECD members.

This information refers to the last year for which data was available
for each country and enables us to conduct a synchronic analysis. It is also
useful to include diachronic information, however. Figure 1 shows changes in
economic inequality in the United States, Portugal and OECD between 1980
and 2010. While there is information available for almost all these years for
the United States, this is not the case for Portugal or the average of the OECD
countries.

The Gini coefficient for economic inequality in Portugal in 1980 was
around 14% higher than in the United States: 0.350 against 0.307. Between
1980 and 1993, when the Gini coefficient was 0.369, economic inequality in
the United States increased by around 20%, and then fell slightly until 1999.
It then increased irregularly and the figure in 2010 (0.380) was around 24%
higher than in 1980.

Inequality in Portugal fell during the 1980s. There was a considerable rise
in inequality in the first half of the 1990s followed by a slight drop in the
second half. In spite of this change in direction, economic inequality was at a
higher level at the end of the 1990s than at the beginning:

The reduction in inequality in the 1980s is closely associated with a more
accentuated growth in incomes at the lower end of the scale. The rise in
inequality in the 1990s was mainly due to changes at the upper end of

Figure 1: Inequality of disposable income (Gini coefficient), United States, Portugal and OECD (1980–2010).

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6. Specific public policies
aimed to provide
income to the most
fragile fringes of the
Portuguese society,
namely the ones with
very low or no income
at all and the elderly
populations that earn
survival pensions.

the scale, where we find the households that benefited most from the
economic growth.

(Rodrigues 2007: 305)

The first years of the new millennium witnessed an increase in economic inequal-
ity and the Gini coefficient was 0.385 in 2004, about 17 per cent higher than in
1990 (0.329). From then until 2009 there was a progressive reduction in economic
inequality in the country. Rodrigues et al. (2012) attribute this in part to social
policies aimed at assisting the more disadvantaged strata of the population, such
as Social Insertion Income and Elderly People’s Subsidy.6 In 2009, the Gini coef-
ficient was 0.339, but increased to 0.344 in 2010. A comparison of the Gini coef-
ficient in Portugal in 1980 and 2010 shows that it fell by around 1.7 per cent.

Figure 1 indicates several trends. First, it shows that the level of inequality
in the two countries over the period in question was always higher than the
OECD average. Second, it demonstrates that inequality increased in Portugal
in the 1990s and 2000s, while in the United States it fell slightly or stabi-
lized, especially between 1994 and 2000. Third, between 2004 and 2008–09
there was a substantial reduction in economic inequality in Portugal, while
the 2000s in the United States witnessed an increase. An increase in economic
inequality in 2010 interrupted the downward trend in Portugal and there was
also a rise in inequality in the United States compared to 2008 (no informa-
tion is available in the United States for 2009). We find that there was greater
growth in economic inequality in the United States than in Portugal, being
10.5 per cent higher in the United States than in Portugal in 2010.

INCOME INEQUALITY AND MONETARY REDISTRIBUTION

The previous section provided information on inequality in disposable income,
i.e. the household’s income after taxes, social security contributions and social
transfers. It is analytically enlightening to determine the level of economic
inequality before the state’s redistribution and to measure the role played by
the state in mitigating market inequality (economic resources before redistri-
bution by the state).

This can be done by comparing the Gini coefficient for economic inequal-
ity with market income and disposable income. In 2010, Portugal was the
seventh-highest OECD country (plus Russia) in terms of market income
inequality for the population aged between 18 and 65, behind the United
States. An analysis of inequality of disposable income shows that Portugal
was still the seventh most unequal country of this universe of countries, while
the United States was the third, after Chile and Russia.

The fact that the United States rose in the economic inequality rank-
ings and Portugal’s position remained the same when we move from market
income to disposable income shows that the impact of state redistribution is
higher in Portugal than in the United States. Figure 2 shows the decrease in
the Gini coefficient resulting from the effect of taxes and social security and
also social transfers from the state to households in the OECD countries and
Russia. State redistribution in Slovenia, Ireland, Belgium, Finland, Denmark,
Austria and Luxembourg results in a reduction of more than 35% in economic
inequality. In the Czech Republic, Norway, France, Slovakia and Sweden the
impact varies between 35% and 30%. State redistribution in Portugal reduced
economic inequality by around 26.6%, which was considerably more than in
the United States, where it was 19.9%.

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Unlike South Korea or Canada, where the effect of state redistribution is
fairly limited but inequality levels are relatively low, the United States (along
with Chile, Israel and Russia) had both high economic inequality and low
levels of monetary redistribution. The average impact of state redistribution
was around 25 per cent in the OECD countries (OECD 2012).

According to Joumard et al. (2012), there is a positive relationship between
market economic inequality in the OECD countries and the impact of redis-
tribution policies (social transfers and taxes) for the total population. This
relationship is not linear, however. Indeed, most of the countries with redistri-
bution policies that reduce economic inequality more have comparatively low
market income inequality. This is the case in the northern European countries,
the Czech Republic and Belgium.

This conclusion is confirmed when we look at the impact of state redistri-
bution in countries with high economic inequality. Redistribution policies in
Portugal and the United States reduce economic inequality by less than 10% –
below the OECD average – and in Chile by less than 5%.

When analysing the effects of state redistribution we must distinguish
between those of monetary transfers and of taxes.

Monetary transfers to households account for around three-quarters of the
reduction in economic inequality in the OECD countries (2012). According to

Source: Authors’ calculations based on the Statistics database, List of key indicators (OECD).

Note 1: There are no available Gini coefficient data on market income for Hungary, Mexico or Turkey and so these
countries have not been included in Figure 2. The data for Ireland, Japan, New Zealand and Switzerland are
from 2009.

Note 2: We have used the same method as the OECD for measuring the impact of redistribution policies (OECD
2011: 268–70).

Figure 2: Reduction in economic inequality associated with redistributive policies, pop. aged 18–65, OECD
countries and Russia (2010) (%).

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7. Carlos Farinha
Rodrigues et al. (2012)
reached similar
conclusions about
Portugal. They state
that in 2009 Portugal
had one of the lowest
efficacy and efficiency
rates associated with
social contributions in
a universe of 15 EU-27
countries (2012: 177).

8. Alves (2012) doesn’t
include the old age
pensions in the
redistributive process,
whereas Joumard et al.
(2012) do. This may
indicate that old age
pension have a low
redistributive impact.

9. The impact of taxes
on reducing income
inequality depends
on the size and
progression of the tax
burden.

Joumard et al. (2012), these payments had reduced economic inequality in
these countries by around 19% by 2010 and there was ‘no clear link between
the degree of market income inequality and the redistributive impact of trans-
fers’ (2012: 10). In countries like the Czech Republic, Finland, Sweden and
Denmark monetary transfers have high impacts on reducing inequality, while
Portugal and the United States are in the group with the lowest impacts in this
regard: a 4.3% reduction in Portugal and 4.1% in the United States against an
OECD average of 7.9%.7

Portugal and the United States are similar in terms of the low impact of
monetary transfers on reducing market economic inequality, although the
reasons for the small size of the impact are different. According to these
authors, in the United States it is due to the small amount of monetary trans-
fers compared to the OECD average, while in Portugal it is because of the
‘lower progressivity’ of these transfers (2012: 11). Alves (2012) agrees that the
impact of monetary transfers in Portugal is low; nevertheless, he states that this
fact is explained by the small volume of social transfers to the bottom groups,
not because of the way it is channelled. According to him, Portugal is one of
the European Union members with the more progressive social transfers.8

On the subject of the effects of taxes and social security contributions in
reducing economic inequality, Joumard et al. (2012) conclude that there are
no significant differences among the OECD countries.9 Even so, the United
States, along with Australia, Denmark, Germany, Israel and Italy, is in the
group of countries in which the difference between inequality levels before and
after income tax was the greatest. In other words, they are the OECD coun-
tries in which taxes have the highest impact on reducing economic inequality.
The United States is the only OECD country in which taxes actually have a
similar impact on reducing economic inequality to that of monetary transfers
to households (Joumard et al. 2012; Förster and Whiteford 2009). The mitigat-
ing effect of taxes on economic inequality in Portugal is also higher than the
OECD average (Joumard et al. 2012).

The relatively high impact of taxes on reducing economic inequality in the
United States shown in this study is quite surprising, considering the country’s
tax policy has been held as one of the main causes of income being concen-
trated at the top and of economic inequality in general (Stiglitz 2012; Krugman
2007). Piketty and Saez (2007) used government data to analyse the progres-
siveness of the US tax system on the basis of its impact on income concen-
tration in the top groups. They conclude there has been a reduction in the
progressive nature of tax in the United States in recent decades and that this
has favoured an increase in income concentrated in the top percentile and frac-
tiles. On the one hand, the ‘federal tax system reduced income concentration
the most in the 1960s and 1970s when income concentration was relatively
low’; on the other hand, ‘the federal tax system has a relatively modest effect
on the top 0.1 per cent income share in recent years when income inequality
has become higher’ (Piketty and Saez 2007: 14–15). According to the authors,
the reduction in the progressive nature of the US tax system was due to the
reduction in marginal rates on top incomes, the system of exemptions and tax
benefits and the taxation of capital income at lower marginal rates.

As a complement to these approaches, we show the personal income tax
rates of the highest brackets in the OECD countries in 2012. The amount to
which these rates apply varies substantially from one country to another and
the rate actually charged may vary on the basis of exemptions, tax benefits
and the taxable income structure for each individual or tax unit.

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10. In Portugal a rate of
46.5% was charged
on gross income over
€153,330 a year in 2012,
plus an additional
charge of 2.5%. Income
in the top bracket (over
€80,000) was taxed at
48% in 2013. A surtax
of 3.5% was charged
on all taxpayers
plus an additional
solidarity charge of
2.5% on taxable income
between €80,000 and
€250,000. All income
over €250,000 was
subject to an additional
5 per cent solidarity
charge.

Source: OECD Tax Database (OECD).

Table 2: Top statutory personal income tax rates in the OECD countries (%) (2012).

Denmark 60.2
Sweden 56.6
Belgium 53.7
Netherlands 52.0
Spain 52.0
France 50.7
Japan 50.0
Austria 50.0
United Kingdom 50.0
Finland 49.0
Greece 49.0
Portugal 49.0
Italy 48.6
Ireland 48.0
Israel 48.0
Canada 48.0
Australia 47.5
Germany 47.5
Iceland 46.2
United States 41.9
South Korea 41.8
Switzerland 41.7
Luxembourg 41.3
Slovenia 41.0
Norway 40.0
Chile 40.0
Turkey 35.7
New Zealand 33.0
Poland 32.0
Mexico 30.0
Estonia 21.0
Slovakia 19.0
Hungary 16.0
Czech Rep. 15.0

In 2012, Denmark was the OECD country in which the tax rate on the top
income bracket was the highest at 60.2%. This rate was 50% or more in eight
countries. As in Finland and Greece, the highest gross income bracket in Portugal
was taxed at 49%.10 The rate in the United States was 41.9%. Among the coun-
tries analysed in Table 2, ten had top rates of 40% or less. The Czech Republic
(15%), Hungary (16%), Slovakia (19%) and Estonia (21%) had the lowest rates.

Our analysis of the impacts of taxes and social transfers on reduc-
ing economic inequality is based on different methodological strategies,

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378 Portuguese Journal of Social Science

11. As in Alvaredo et al.
(2013), OECD (2011),
Alvaredo (2010) and
Atkinson et al. (2010),
we have not used
data on top incomes
including capital gains
in the United States in
our direct comparison
between the two
countries. One of the
reasons for this is that
there is no information
on the distribution of
capital gains declared
for Portugal (Alvaredo
2010: 564–65).

conceptual definitions and information sources influencing the conclusions
reached. It is therefore necessary to regard this type of information with
caution and compare the different methodological approaches and analytical
perspectives available in the literature.

Instruments such as the Inquérito às Condições de Vida e Rendimento (Survey
on Income and Living Conditions) in Portugal and the Current Population
Survey in the United States gather empirical information for analysis of the
main trends in income distribution. From a methodological point of view,
however, they are not the most reliable or appropriate instruments for meas-
uring and analysing the groups at the top end of the income bracket. Such
phenomena as sample underrepresentation of these groups, their propensity
for under-declaring income or refusal to participate in surveys explain this
limitation. Tax data have therefore been used to analyse the top incomes. It
is this kind of information that we will use in the next section to compare the
top incomes in Portugal and the United States.

GREATER CONCENTRATION OF INCOME AT THE TOP

Ever since Thomas Piketty published his seminal work Les Hauts Revenus en
France au 20ème Siècle (2001), a number of researchers have been producing
studies on top incomes based on government tax data for many countries.
These data are estimates based on tax sources and complement statistical
information from surveys. The analysis that will be carried out in this article
relies on statistical information gathered in the World Top Incomes Database.

Table 3 shows levels of concentration of pre-tax income of several groups
in the top income brackets in Portugal and the United States (excluding capi-
tal gains).11 The latest available data for Portugal refer to 2005. As preliminary
information for 2011 is available for the United States, we will present its data
from 2005 and 2011. The degree of concentration of income in the top quan-
tiles is significantly more pronounced in the United States than in Portugal
in all the groups analysed. While in 2005 the richest 10% in Portugal had

Source: Alvaredo, Facundo, Anthony B. Atkinson, Thomas Piketty and Emmanuel Saez,
The World Top Incomes Database, http://topincomes.g-mond.parisschoolo-
feconomics.eu.

Note: Pre-tax figures.

Table 3: Income share held by the top quantiles, United States and Portugal (%).

United States Portugal

Difference %
between United

States and PT
in 2005

2005 2011 2005
10% richest 44.94 46.54 38.25 17.5
5% richest 33.12 33.91 26.01 27.3
1% richest 17.68 17.43 9.77 81.0
0.5% richest 13.72 13.34 6.42 113.7
0.1% richest 7.76 7.36 2.48 212.9
0.01% richest 3.29 3.29 0.69 376.8

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Trends in income inequality

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38.3% of the total income, in the United States they had 44.9%, a concen-
tration level 17.5% greater than Portugal. The more we narrow the range of
income groups, the greater the difference between the levels of concentration
in the two countries. The richest 1% in the United States accounted for 17.7%
of the country’s total income while in Portugal they accounted for 9.8% (81%
difference). The difference in level of concentration between the two countries
grows if we compared fractions of the richest 1% group. While in Portugal the
richest 0.01% accounted for around 0.7% of total income, they accounted for
3.3% in the United States (a difference of around 377%).

One of the advantages of tax data is the possibility of using them to build
wide-ranging historical series. We now look at statistical information on the
evolution of income concentration levels in the top groups.

Figure 3 shows the share of total income of the richest 1% and 0.1% in
Portugal and the United States. The data for the United States refer to 1913–
2011, while those for the richest 1% and 0.1% in Portugal refer to 1976–2005
and 1936–2005, respectively.

Between 1913 and the Wall Street Crash in 1929 there was not only a
high level of income concentration in these groups but it was also tending to
grow. This timeframe was part of the so-called Gilded Age, which began in
the late nineteenth century and witnessed the emergence of great fortunes,
low taxation on income and wealth and deregulation of the financial markets
(Krugman 2007). From 1929 onwards, the economic and financial shock
caused by the Great Depression and Franklin D. Roosevelt’s New Deal,
income concentration began a downward trend in the top groups. This trend
lasted until the United States entered the Second World War, when there
was a highly pronounced reduction in concentration of income in the richest
groups of the population. Over the next 30 years, the share of income held
by the richest remained relatively low. This was the result of the structur-
ing effect of the measures taken to sustain the war economy between 1941
and 1945 (e.g. control and levelling of salaries), a progressive tax policy and
the bargaining power of the trade unions. The late 1970s and 1980s marked
the beginning of an ongoing increase in the concentration of income in the
top groups. According to several authors, this was associated with Ronald
Reagan’s policy of deregulating the financial sector, which helped a restricted
number of professional groups directly or indirectly linked to financial services
to increase their wealth (Stiglitz 2012; Horn et al. 2009; Krugman 2007).This
increase in concentration of income in the top tail of the distribution was
accompanied by a rise in the preponderance of wage income in the economic
resources of these groups (Piketty 2013; Piketty and Saez 2003).

The available data allows us to analyse the performance of top incomes in
the United States during the current financial crisis. According to Emmanuel
Saez (2013a), between 2007 and 2009, the real average income of the rich-
est 1% fell by 36.3%, which was higher than the country’s average reduc-
tion (17.4%). This represents a 23.5% decrease to 18.1% of their share of total
income. This fall was largely due to loss of capital income, which fell from
$895 billion in 2007 to $236bn in 2009. If we consider capital income, the
share of income held by the richest 10% fell from 49.7% to 46.5%. However, if
we exclude capital income from the analysis, there is hardly any change, as it
went from 45.7 to 45.5%. In aggregate terms, 49% of total income losses in the
period were borne by the richest 1% (Saez 2013a). This trend began to turn
around in 2009, however. The real average income of the richest 1% increased
11.7% between 2009 and 2011, while for the remaining population it fell 0.4%.

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380 Portuguese Journal of Social Science

12. Between 1939 and 1941,
this inequality measure
rose from 4.6 per cent
to the 5.2 per cent
mentioned.

According to the author’s preliminary data (Saez 2013b), this trend grows
stronger if we take 2012 into account. The income of the richest 1% increased
19.6% from 2011 to 2012, while that of the rest of the population rose only 1%.
He states that the income of the richest 1% grew 31.4% between 2009 and 2012,
while that of the remaining 99% increased only 0.4%. This means that 95% of
the gains in income in the first three years of recovery went to the richest.

Where Portugal is concerned, Figure 3 shows that levels of income concen-
tration in the 1930s and 1940s were much higher than in 2005. In 1936 the
richest 0.1% were estimated to receive 5.2% of the population’s total income.
Although Portugal did not take part in the Second World War, these figures
went down during the period. The share of total income in the hands of the
richest 0.1% fell from 5.2% in 1941 to 3.1% in 1946. During this period, the
marginal rates on the highest incomes went from 8.5% to 30% (Alvaredo
2010).12 Between 1950 and 1970 there was a slight drop in the level of income
concentration in this group, and this trend accelerated after that (also for the
richest 1%) until a break in the series in 1982.

Since the series restarted in 1989 concentration of income has increased
progressively in the two quantiles analysed in Figure 3. The marginal rates on
the highest incomes did not undergo any significant changes in the period,
which, according to Alvaredo, indicates the taxation framework was not a
decisive factor in the increase of top incomes (2010: 13). A study by Rodrigues
et al. (2012) makes an initial approach to this phenomenon. According to
these authors, wage inequality grew deeper between 1985 and 2009 and the
concentration of this income in the top quantiles increased sharply by 50.7%
in the richest 1%, 60.9% in the richest 0.1% and 126.7% in the richest 0.01%.
In other words, the employment market was a source of inequality and

Source: Alvaredo, Facundo, Anthony B. Atkinson, Thomas Piketty and Emmanuel Saez, The World Top Incomes
Database, http://topincomes.g-mond.parisschoolofeconomics.eu.

Note: Pre-tax figures.

Figure 3: Income share of the richest 1 per cent and 0.1 per cent in the United States and Portugal (1913–2011).

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concentration of economic resources in very small groups of the population
with relatively well-defined occupations (Cantante 2013).

After showing the data on concentration of income at the top in the two
countries, we now conduct a brief comparative analysis of these trends.

A comparison between the group of the richest 1% in Portugal and the
United States is only possible after 1976. In that year, income concentration
for these groups in the United States and Portugal was similar: about 7.9% in
both countries. In 1989, these groups’ share of the income had fallen slightly
(6.8%) in Portugal while in the United States it has risen quite significantly to
12.6%. From 1989 to 2005, the variation rate of these indicators increased a
bit more in Portugal than in the United States: 42.8% and 40.2%, respectively.
Although this rise was slightly more accentuated in Portugal than in the
United States, the extent of the concentration of income in the top 1% in 2005
was much greater in the United States than in Portugal: 17.7% to 9.8%.

Regarding the concentration of income in the 0.1% group, we find that
breadth of this phenomenon was greater in Portugal than in the United States
from the mid-1940s to early 1970s. Indeed, this occurs not only in comparison
with the United States, but with countries like Spain, France or the United
Kingdom (Alvaredo 2010). From 1980 onwards, there was a much sharper
increase in this indicator in the United States than in Portugal (which was not
the case for the richest 1%). It was in this period that the United States stood
out as the most unequal in terms of distribution of income (and wealth) in the
most developed countries in the world and the fourth-highest of all OECD
countries, behind Chile, Mexico and Turkey. As mentioned above, the data
shown here for the United States do not include capital gains. If we take this
income component into account, the level of concentration of income in the
top groups increases substantially. For example, in 2011 the richest 1% had
around 20% of total US income, and between 1980 and 2007 their share of the
income grew by around 135% (Alvaredo et al. 2013).

CONCLUSION

Portugal and the United States are two countries in which income distribu-
tion is quite unequal. This gap is more pronounced in the United States than
in Portugal, but if we place them in the universe of OECD countries we find
their profiles are fairly similar. Economic inequality is a structural phenom-
enon with important, multi-dimensional impacts on the way societies work.
Although economic inequality may be reproduced or intensified by social,
economic, institutional and political dynamics, this trend is not inevitable. A
diachronic analysis of economic inequality in the two countries shows just
that, as the extent of this phenomenon varies considerably over the years.
Consider, for example, the increase in inequality in the United States prior to
the 1929 crisis or in the late 1970s and early 1980s, two periods that witnessed
tax reductions and deregulation of the financial markets. On the other hand,
we can see the equalization of income distribution for several decades under
the New Deal and later in the war economy in the United States or on a
smaller scale in Portugal between 2004 and 2009.

The increase of top income concentration is one of the most notable
phenomena resulting from the analysis of income distribution. The increase
of income inequality in most of the OECD countries in the last decade can
be explained in part by this dynamic. Both in Portugal and the United States
the market income held by these groups has increased significantly in recent

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382 Portuguese Journal of Social Science

decades. The data presented in this article shows that top income concentra-
tion has been more intense in the United States than in Portugal. If we look at
the very top income groups (1 per cent fractiles), we conclude they have been
pushing up overall inequality in a more profound way in the United States
than in Portugal.

As in most advanced countries, top income concentration has put pressure
on the state’s ability to reduce disposable income inequality. Although the
phenomenon of economic inequality may be associated with issues as diverse
as labour and trade union rights or access to education, this study essentially
addresses redistribution policies in Portugal and the United States on the
basis of social payments and taxation. Our conclusion is that, in general terms,
Portugal has higher economic redistribution levels than the United States,
although both countries average below European and OECD countries. While
the data from population surveys in the United States shows that the state’s
redistribution has not managed to reduce inequality in disposable income in
the last decade, Portugal experienced a progressive reduction in economic
inequality in the second half of the 2000s. This trend was mainly due to poli-
cies on the transfer of income to more disadvantaged households, such as the
Social Insertion Income and Elderly People’s Subsidy.

The redistributive role of taxes and social transfers in the two countries
is quite different. While in Portugal the reduction in economic inequality
is essentially due to social transfers, in the US taxes and monetary trans-
fers to households have equivalent weights in the redistribution process.
Nonetheless, analyses by authors such as Joseph E. Stiglitz, Paul Krugman,
Thomas Piketty and Emmanuel Saez have been demonstrating that the US
tax policy has in recent decades resulted in a considerable increase in the
concentration of income at the very top. As we show in this article, top rates of
income tax are considerably lower in the United States than in most European
countries, including Portugal. Nevertheless, both in Portugal and the United
States – but also in most OECD countries – there is a big difference between
top rates regarding income as a whole and capital income taxes (Piketty 2013).
Capital income earners, who are typically the richest among the rich, benefit
from tax systems that tend to be harsher on labour revenue and which are
more beneficial to wealth and wealth income. This fact isn’t easy to capture
using the available data, but it forms a legal frame that boosts income inequal-
ity and reinforces the concentration of income and wealth at the very top.

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SUGGESTED CITATION

Cantante, F., Carmo, R. M., de Almeida Alves, N. and da Costa, A. F. (2016),
‘Trends in income inequality: Comparing the United States and Portugal’,
Portuguese Journal of Social Science, 15: 3, pp. 367–86, doi: 10.1386/
pjss.15.3.367_1

CONTRIBUTOR DETAILS

Frederico Cantante is a Ph.D. student in sociology. He has an undergradu-
ate degree in law and in sociology. He is a research assistant at CIES-IUL
and in the Observatory of Inequalites. His main research interests are social
and economic inequalities. His recent publications include: ‘The persistence of
class inequality: The Portuguese labour force at the turn of the millennium’,
Sociological Research Online, 20: 4 (2015), pp. 1–17 (with Renato Miguel do
Carmo and Margarida Carvalho) and, Cantante, F. (2014), ‘Desigualdades

PJSS_15.3_Cantante_367-386.indd 384 2/21/17 3:43 PM

http://www.oecd.org/els/soc/dividedwestandwhyinequalitykeepsrising.htm

https://www.oecd.org/tax/public-finance/49417295

https://eml.berkeley.edu/~saez/saez-UStopincomes-2011

https://eml.berkeley.edu/~saez/saez-UStopincomes-2012

http://hdr.undp.org/en/2013-report

Trends in income inequality

www.intellectbooks.com 385

Económicas Multi-Escalares: Portugal No Contexto Global’ (‘Multi-scale
economic inequalities: Portugal in the global context’) Análise Social,
212:XLIX&3, pp. 534–66.

Contact: CIES, ISCTE – Instituto Universitário de Lisboa, Edifício ISCTE-IUL,
Avenida das Forças Armadas 1649-026, Lisboa, Portugal.
E-mail: frederico.cantante@iscte.pt

Renato Miguel Carmo is a sociologist at CIES-ISCTE – Instituto Universitário
de Lisboa. He is coordinator of the Inequality Observatory and member of
the European network Inequality Watch. His research interests are social and
spatial inequalities, with such issues as social exclusion, territorial marginaliza-
tion, spatial mobility and social capital at the core of his individual and collec-
tive research projects. His most recent publications are (with M. Carvalho and
F. Cantante) ‘The persistence of class inequality: The Portuguese labour force
at the turn of the millennium’, Sociological Research Online, 20: 4 (2015); (with
F. Cantante and N. Alves) ‘Time projections: Youth and precarious employ-
ment’, Time & Society, 23: 3, pp. 337–357 (2014); and (with S. Santos) ‘Social
capital and sociodemographic changes: From non-differentiation to multi-
focalisation’, Sociologia Ruralis, 54: 2, pp. 186–205 (2014).

Contact: CIES, ISCTE – Instituto Universitário de Lisboa, Edifício ISCTE-IUL,
Avenida das Forças Armadas 1649-026, Lisboa, Portugal.
E-mail: renato.miguel.carmo@gmail.com

Nuno de Almeida Alves is head of the department of Social Research
Methods at ISCTE – University Institute of Lisbon and a member of CIES,
ISCTE – Instituto Universitário de Lisboa. He has conducted research on chil-
dren and young people, with particular focus on the use of information tech-
nologies and impact of job precariousness on transitions to adulthood. He
has published several books and articles in this area and on other themes,
including: (with D. Cairns, A. Alexandre and A. Correia), Youth Unemployment
and Job Precariousness: Political Participation in the Austerity Era, Basingstoke:
Palgrave Macmillan (2016); (edited with A. Delicado, A. Alves, T. Carvalho
and D. Carvalho), Infâncias Digitais, Lisbon: Fundação Calouste Gulbenkian
(2015); and (with A. Delicado, A. Alves and T. Carvalho), ‘Internet, children
and space: Revisiting generational attributes and boundaries’, New Media &
Society, 17: 9, pp. 1436–53 (2015).

Contact: CIES, ISCTE – Instituto Universitário de Lisboa, Edifício ISCTE-IUL,
Avenida das Forças Armadas 1649-026, Lisboa, Portugal.
E-mail: nalmeidaalves@iscte.pt

António Firmino da Costa has a Ph.D. in sociology, professor at the Department
of Sociology at ISCTE – Instituto Universitário de Lisboa, researcher at CIES,
ISCTE – Instituto Universitário de Lisboa, co-ordinator of the Knowledge
Society, Competencies and Communication research group (CIES) and direc-
tor of the Inequality Observatory, chairman of the Portuguese Sociological
Association (APS) Ethics Council. He was Vice-Rector for Research at ISCTE –
Instituto Universitário de Lisboa from 2010–13, co-ordinator of the sociology
doctoral programme at ISCTE-IUL (2003–11), director of CIES from 2000–06
and editor of Sociologia: Problemas e Práticas from 1995–2000. His research
interests include social inequality, science and society, literacy and education,

PJSS_15.3_Cantante_367-386.indd 385 2/22/17 3:21 PM

http://www.intellectbooks.com

Frederico Cantante | Renato Miguel Carmo …

386 Portuguese Journal of Social Science

cultural identities and urban cultures, and research methodology. His recent
publications include: (with E. Pegado, P. Ávila and A. R. Coelho), ‘Evaluating
the Portuguese national reading plan: Teachers’ perceptions on the impact in
schools’, Educational Research for Policy and Practice, 14: 2, pp. 119–38 (2015);
(with R. M. Carmo [eds]) Desigualdades em Questão: Análises e Problemáticas,
Lisbon: Mundos Sociais (2015); (with J. T. Lopes and A. Caetano [eds]),
Percursos de Estudantes no Ensino Superior: Fatores e Processos de Sucesso e
Insucesso, Lisbon: Mundos Sociais (2014).

Contact: CIES, ISCTE – Instituto Universitário de Lisboa, Edifício ISCTE-IUL,
Avenida das Forças Armadas 1649-026, Lisboa, Portugal.
E-mail: antonio.costa@iscte.pt

ERRATUM

The author details have been amended since the original publication of this
article, where only one of the authors was attributed. The publisher apolo-
gizes for this error.

Frederico Cantante, Renato Miguel Carmo, Nuno de Almeida Alves and
António Firmino da Costa have asserted their right under the Copyright,
Designs and Patents Act, 1988, to be identified as the authors of this work in
the format that was submitted to Intellect Ltd.

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articles for individual use.

8. Inequality and Economic Growth

JOSEPH E. STIGLITZ

Introduction
IN THE middle of the twentieth century, it came to be believed that ‘a rising tide
lifts all boats’: economic growth would bring increasing wealth and higher liv-
ing standards to all sections of society. At the time, there was some evidence
behind that claim. In industrialised countries in the 1950s and 1960s every
group was advancing, and those with lower incomes were rising most rapidly.

In the ensuing economic and political debate, this ‘rising-tide hypothesis’
evolved into a much more specific idea, according to which regressive eco-
nomic policies—policies that favour the richer classes—would end up bene-
fiting everyone. Resources given to the rich would inevitably ‘trickle down’
to the rest. It is important to clarify that this version of old-fashioned
‘trickle-down economics’ did not follow from the postwar evidence. The ‘ris-
ing-tide hypothesis’ was equally consistent with a ‘trickle-up’ theory—give
more money to those at the bottom and everyone will benefit; or with a
‘build-out from the middle’ theory—help those at the centre, and both those
above and below will benefit.

Today the trend to greater equality of incomes which characterised the
postwar period has been reversed. Inequality is now rising rapidly. Contrary
to the rising-tide hypothesis, the rising tide has only lifted the large yachts,
and many of the smaller boats have been left dashed on the rocks. This is
partly because the extraordinary growth in top incomes has coincided with
an economic slowdown.

The trickle-down notion—along with its theoretical justification, marginal
productivity theory—needs urgent rethinking. That theory attempts both to
explain inequality—why it occurs—and to justify it—why it would be benefi-
cial for the economy as a whole. This chapter looks critically at both claims.
It argues in favour of alternative explanations of inequality, with particular
reference to the theory of rent-seeking and to the influence of institutional
and political factors, which have shaped labour markets and patterns of
remuneration. And it shows that, far from being either necessary or good for
economic growth, excessive inequality tends to lead to weaker economic per-
formance. In light of this, it argues for a range of policies that would
increase both equity and economic well-being.

The great rise of inequality
Let us start by examining the ongoing trends in income and wealth. In the
past three decades, those at the top have done very well, especially in the

Published by John Wiley & Sons Ltd, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA

US. Between 1980 and 2014, the richest 1 per cent have seen their avera

real income increase by 169 per cent (from $469,403, adjusted for inflation, to
$1,260,508) and their share of national income more than double, from
10 per cent to 21 per cent. The top 0.1 per cent have fared even better. Over
the same period, their average real income increased by 281 per cent (from
$1,597,080, adjusted for inflation, to $6,087,113) and their share of national
income almost tripled, from 3.4 to 10.3 per cent.1

Over the same thirty-four years, median household income grew by only
11 per cent. And this growth actually occurred only in the very first years of
the period: by 2014 it was only .7 per cent higher than in 1989, after peaking
in 1999.2 But even this underestimates the extent to which those at the bottom
have suffered—their incomes have only done as well as they have because
hours worked have increased. Median hourly compensation (adjusted for
inflation) increased by only 9 per cent from 1973 to 2014, even though at the
same time productivity grew by 72.2 per cent (Figure 1). (To understand how
significant this divergence of productivity and wages is, consider that from
1948 to 1973 both increased at the same pace, about doubling over the per-
iod.)3 And these statistics underestimate the true deterioration in workers’
wages, for education levels have increased (the percentage of Americans
who are college graduates has nearly doubled since 1980, to more than
30 per cent),4 so that one should have expected a significant increase in wage
rates. In fact, average real hourly wages for all Americans with only a high
school diploma have decreased in the past three decades.5, 6

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Figure 1: Wages, productivity and average incomes in the US (1973–2014)
Notes: (left panel) Data are for average hourly compensation of production/nonsupervisory
workers in the private sector and net productivity of the total economy. ‘Net productivity’ is
the growth of output of goods and services minus depreciation per hour worked. EPI analysis
of data from the BEA and BLS (see technical appendix for more detailed information).
Sources: Economic Policy Institute (left panel); The World Wealth and Income Database.
Facundo Alvaredo, Tony Atkinson, Thomas Piketty, Emmanuel Saez and Gabriel Zucman
(right panel)

135

INEQUALITY AND ECONOMIC GROWTH

In the first three years of the so-called recovery from the Great Recession
of 2008–2009—in other words, since the US economy returned to growth—
fully 91 per cent of the gains in income went to the top 1 per cent. By 2014,
the rest of the income distribution had experienced a bit more of a boost,
but even accounting for that, 58 per cent of the gains in total income have
gone to the top 1 per cent since 2009. (During that period, the income of the
bottom 99 per cent has grown by just 4 per cent.)7 Presidents Bush and
Obama both tried a trickle-down strategy—giving large amounts of money
to the banks and the bankers. The idea was simple: by saving the banks and
bankers, all would benefit. The banks would restart lending. The wealthy
would create more jobs. This strategy, it was argued, would be far more
efficacious than helping homeowners, businesses or workers directly. The
US Treasury typically demands that when money is given to developing
countries, conditions be imposed on them to ensure not only that the money
is used well, but also that the country adopts economic policies that (accord-
ing to the Treasury’s economic theories) will lead to growth. But no condi-
tions were imposed on the banks—not even, for example, requirements that
they lend more or stop abusive practices. The rescue worked in enriching
those at the top; but the benefits did not trickle down to the rest of the
economy.

The Federal Reserve, too, tried trickle-down economics. One of the main
channels by which quantitative easing was supposed to rekindle growth was
by leading to higher stock market prices, which would generate higher
wealth for the very rich, who would then spend some of that, which in turn
would benefit the rest.

As Yeva Nersisyan and Randall Wray argue in their chapter in this vol-
ume, both the Fed and the Administration could have tried policies that
more directly benefited the rest of the economy: helping homeowners, lend-
ing to small and medium-sized enterprises and fixing the broken credit
channel. These trickle-down policies were relatively ineffective—one reason
why seven years after the US slipped into recession, the economy was still
not back to health.

Wealth is even more concentrated than income—by one estimate more
than ten times so. The wealthiest 1 per cent of Americans hold 41.8 per cent
of the country’s wealth; the top 0.1 per cent alone control more than
22 per cent of total wealth.8 Just one example of the extremes of wealth in
America is the Walton family: the six heirs to the Walmart empire command
a wealth of $145 billion, which is equivalent to the net worth of 1,782,020
average American families.9

Wealth inequality too is on the upswing. For the four decades before the
Great Recession, the rich were getting wealthier at a more rapid pace than
everyone else. Between 1978 and 2013 the share of wealth owned by the top
1 per cent rose dramatically, from less than 25 per cent to its current level
above 40 per cent; the share of the top 10 per cent from about two-thirds to
well over three-quarters.10 By 2010, the crisis had depleted some of the

136

JOSEPH E. STIGLITZ

richest Americans’ wealth because of the decline in stock prices, but many
Americans also had had their wealth almost entirely wiped out as their
homes lost value. After the crisis, the average wealthiest 1 per cent of house-
holds still had 165 times the wealth of the average American in the bottom
90 per cent—more than double the ratio of thirty years ago.11 In the years of
‘recovery’, as stock market values rebounded (in part as a result of the Fed’s
lopsided efforts to resuscitate the economy through increasing the balance
sheet of the rich), the rich have regained much of the wealth that they had
lost; the same did not happen to the rest of the country.

Inequality plays out along ethnic lines in ways that should be disturbing
for a country that had begun to see itself as having won out against racism.
Between 2005 and 2009, a huge number of Americans saw their wealth dras-
tically decrease. The net worth of the typical white American household was
down substantially, to $113,149 in 2009, a 16 per cent loss of wealth from
2005. But the recession was much worse for other groups. The typical
African American household lost 53 per cent of its wealth—putting its assets
at a mere 5 per cent of the median white American’s. The typical Hispanic
household lost 66 per cent of its wealth.13

Probably the most invidious aspect of America’s inequality is that of
opportunities: in the US a young person’s life prospects depend heavily on
the income and education of his or her parents, even more than in other
advanced countries.14 The ‘American dream’ is largely a myth.

A number of studies have noted the link between inequality of outcomes
and inequality of opportunities.15 When there are large inequalities of
income, those at the top can buy for their offspring privileges not available to
others, and they often come to believe that it is their right and obligation to
do so. And, of course, without equality of opportunity those born in the bot-
tom of the distribution are likely to end up there: inequalities of outcomes
perpetuate themselves. This is deeply troubling: given our low level of equal-
ity of opportunity and our high level of inequality of income and wealth, it is
possible that the future will be even worse, with still further increases in
inequality of outcome and still further decreases in equality of opportunity.

A generalised international trend
While the US has been winning the race to be the most unequal country (at
least within developed economies), much of what has just been described
for it has also been going on elsewhere. In the past twenty-five to thirty
years the Gini index—the widely used measure of income inequality—has
increased by roughly 29 per cent in the United States, 17 per cent in
Germany, 9 per cent in Canada, 14 per cent in UK, 12 per cent in Italy and
11 per cent in Japan (Figure 2).16 The more countries follow the American
economic model, the more the results seem to be consistent with what has
occurred in the United States. The UK has now achieved the second highest
level of inequality among the countries of Western Europe and North

137

INEQUALITY AND ECONOMIC GROWTH

America, a marked change from its position before the Thatcher era
(Figures 2 and 3). Germany, which had been among the most equal coun-
tries within the OECD, now ranks in the middle.

The enlargement of the share of income appropriated by the richest
1 per cent has also been a general trend, and in Anglo-Saxon countries it
started earlier and it has been more marked than anywhere else (Figure 3).
In rich countries, such as the US, the concentration of wealth is even more
pronounced than that of income, and has been rising too. For instance, in
the UK the income share of the top 1 per cent went up from 5.7 per cent in
1978 to 14.7 per cent in 2010, while the share of wealth owned by the top
1 per cent surged from 22.6 per cent in 1970 to 28 per cent in 2010 and the

Figure 2: Gini coefficient of income inequality in OECD countries (after-tax and
transfer)
Note: income refers to disposable income adjusted for household size.
Source: OECD, In It Together: Why Less Inequality Benefits All, OECD, Paris, 2015, p. 2

4
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Germany
Japan
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Figure 3: Income share of the richest 1 per cent in some major industrialised coun-
tries
Source: The World Wealth and Income Database (latest data available at http://www.wid.
world/ (accessed 12 May 2016))

138

JOSEPH E. STIGLITZ

http://www.wid.world/

top 10 per cent’s wealth share increased from 64.1 per cent to 70.5 per cent
over the same period.17

Also disturbing are the patterns that have emerged in transition econo-
mies, which at the beginning of their movement to a market economy had
low levels of inequality in income and wealth (at least according to available
measurements). Today, China’s inequality of income, as measured by its
Gini coefficient, is roughly comparable to that of the United States and
Russia.18 Across the OECD, since 1985 the Gini coefficient has increased in
seventeen of twenty-two countries for which data is available, often dramati-
cally (Figure 2).

Moreover, recent research by Piketty and his co-authors has found that
the importance of inherited wealth has increased in recent decades, at least
in the rich countries for which we have data. After displaying a decreasing
trend in the first postwar period, the share of inheritance flows in disposable
income has been increasing in the past decades.19

Explaining inequality
How can we explain these worrying trends? Traditionally, there has been lit-
tle consensus among economists and social thinkers on what causes inequal-
ity. In the nineteenth century, they strived to explain and either justify or
criticise the evident high levels of disparity. Marx talked about exploitation.
Nassau Senior, the first holder of the first chair in economics, the Drum-
mond Professorship at All Souls College, Oxford, talked about the returns to
capital as a payment for capitalists’ abstinence, for their not consuming.20 It
was not exploitation of labour, but the just rewards for their forgoing con-
sumption. Neoclassical economists developed the marginal productivity the-
ory, which argued that compensation more broadly reflected different
individuals’ contributions to society.

While exploitation suggests that those at the top get what they get by tak-
ing away from those at the bottom, marginal productivity theory suggests
that those at the top only get what they add. The advocates of this view have
gone further: they have suggested that in a competitive market, exploitation
(e.g. as a result of monopoly power or discrimination) simply couldn’t persist,
and that additions to capital would cause wages to increase, so workers
would be better off thanks to the savings and innovation of those at the top.

More specifically, marginal productivity theory maintains that, due to com-
petition, everyone participating in the production process earns remuneration
equal to her or his marginal productivity. This theory associates higher
incomes with a greater contribution to society. This can justify, for instance,
preferential tax treatment for the rich: by taxing high incomes we would
deprive them of the ‘just deserts’ for their contribution to society, and, even
more importantly, we would discourage them from expressing their talent.21

Moreover, the more they contribute—the harder they work and the more
they save—the better it is for workers, whose wages will rise as a result.

139

INEQUALITY AND ECONOMIC GROWTH

The reason why these ideas justifying inequality have endured is that
they have a grain of truth in them. Some of those who have made large
amounts of money have contributed greatly to our society, and in some
cases what they have appropriated for themselves is but a fraction of what
they have contributed to society. But this is only a part of the story: there
are other possible causes of inequality. Disparity can result from exploita-
tion, discrimination and exercise of monopoly power. Moreover, in general,
inequality is heavily influenced by many institutional and political factors—
industrial relations, labour market institutions, welfare and tax systems, for
example—which can both work independently of productivity and affect
productivity.

That the distribution of income cannot be explained just by standard eco-
nomic theory is suggested by the fact that the before-tax and transfer distri-
bution of income differs markedly across countries. France and Norway are
examples of OECD countries that have managed by and large to resist the
trend of increasing inequality (Figures 2 and 3). The Scandinavian countries
have a much higher level of equality of opportunity, regardless of how that
is assessed. Marginal productivity theory is meant to have universal applica-
tion. Neoclassical theory taught that one could explain economic outcomes
without reference, for instance, to institutions. It held that a society’s institu-
tions are simply a fac�ade; economic behaviour is driven by the underlying
laws of demand and supply, and the economist’s job is to understand these
underlying forces. Thus, the standard theory cannot explain how countries
with similar technology, productivity and per capita income can differ so
much in their before-tax distribution.

The evidence, though, is that institutions do matter. Not only can the
effect of institutions be analysed, but institutions can themselves often be
explained, sometimes by history, sometimes by power relations and some-
times by economic forces (like information asymmetries) left out of the stan-
dard analysis.22 Thus, a major thrust of modern economics is to understand
the role of institutions in creating and shaping markets. The question then is:
what is the relative role and importance of these alternative hypotheses?
There is no easy way of providing a neat quantitative answer, but recent
events and studies have lent persuasive weight to theories putting greater
focus on rent-seeking and exploitation. We shall discuss this evidence in the
next section, before turning to the institutional and political factors which
are at the root of the recent structural changes in income distribution.

Rent-seeking and top incomes
The term ‘rent’ was originally used to describe the returns to land, since the
owner of the land receives these payments by virtue of his or his ownership
and not because of anything he or she does. The term was then extended to
include monopoly profits (or monopoly rents)—the income that one receives
simply from control of a monopoly—and in general returns due to similar

140

JOSEPH E. STIGLITZ

ownership claims. Thus, rent-seeking means getting an income not as a
reward for creating wealth but by grabbing a larger share of the wealth that
would have been produced anyway. Indeed, rent-seekers typically destroy
wealth, as a by-product of their taking away from others. A monopolist who
overcharges for her or his product takes money from those whom she or he is
overcharging and at the same time destroys value. To get her or his monopoly
price, she or he has to restrict production.

Growth in top incomes in the past three decades has been driven mainly in
two occupational categories: those in the financial sector (both executives and
professionals) and non-financial executives.23 Evidence suggests that rents have
contributed on a large scale to the strong increase in the incomes of both.

Let us first consider executives in general. That the rise in their compensa-
tion has not reflected productivity is indicated by the lack of correlation
between managerial pay and firm performance. As early as 1990 Jensen and
Murphy, by studying a sample of 2,505 CEOs in 1,400 companies, found that
annual changes in executive compensation did not reflect changes in corpo-
rate performance.24 Since then, the work of Bebchuk, Fried and Grinstein
has shown that the huge increase in US executive compensation since 1993
cannot be explained by firm performance or industrial structure and that,
instead, it has mainly resulted from flaws in corporate governance, which
enabled managers in practice to set their own pay.25 Mishel and Sabadish
examined 350 firms, showing that growth in the compensation of their CEOs
largely outpaced the increase in their stock market value. Most strikingly,
executive compensation displayed substantial positive growth even during
periods when stock market values decreased.26

There are other reasons to doubt standard marginal productivity theory.
In the United States the ratio of CEO pay to that of the average worker
increased from around 20 to 1 in 1965 to 354 to 1 in 2012.27 There was no
change in technology that could explain a change in relative productivity of
that magnitude—and no explanation for why that change in technology
would occur in the US and not in other similar countries. Moreover, the
design of corporate compensation schemes has made it evident that they are
not intended to reward effort: typically, they are related to the performance
of the stock, which rises and falls depending on many factors outside the
control of the CEO, such as market interest rates and the price of oil. It
would have been easy to design an incentive structure with less risk, simply
by basing compensation on relative performance, relative to a group of com-
parable companies.28 The struggles of the Clinton administration to intro-
duce tax systems encouraging so-called performance pay (without imposing
conditions to ensure that pay was actually related to performance) and dis-
closure requirements (which would have enabled market participants to bet-
ter assess the extent of stock dilution associated with CEO stock option
plans) clarified the battle lines: those pushing for favourable tax treatment
and against disclosure understood well that these arrangements would have
facilitated greater inequalities in income.29

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INEQUALITY AND ECONOMIC GROWTH

For specifically the rise in top incomes in the financial sector, the evidence
is even more unfavourable to explanations based on marginal productivity
theory. An empirical study by Philippon and Reshef shows that in the
past two decades workers in the financial industry have enjoyed a huge
‘pay-premium’ with respect to similar sectors, which cannot be explained by
the usual proxies for productivity (such as the level of education or unob-
served ability). According to their estimates, financial sector compensations
have been about 40 per cent higher than the level that would have been
expected under perfect competition.30

It is also well documented that banks deemed ‘too big to fail’ enjoy a rent
due to an implicit state guarantee. Investors know that these large financial
institutions can count, in effect, on a government guarantee, and thus they
are willing to provide them funds at lower interest rates. The big banks can
thus prosper not because they are more efficient or provide better service
but because they are in effect subsidised by taxpayers. There are other rea-
sons for the super-normal returns to the large banks and their bankers. In
certain of the activities of the financial sector, there is far from perfect com-
petition. Anti-competitive practices in debit and credit cards have amplified
pre-existing market power to generate huge rents. Lack of transparency (e.g.
in over-the-counter Credit Default Swaps (CDSs) and derivatives) too have
generated large rents, with the market dominated by four players.31 It is not
surprising that the rents enjoyed in this way by big banks translated into
higher incomes for their managers and shareholders.

In the financial sector even more than in other industries, executive com-
pensation in the aftermath of the crisis provided convincing evidence against
marginal productivity theory as an explanation of wages at the top: the
bankers who had brought their firms and the global economy to the brink of
ruin continued to receive high rates of pay—compensation which in no way
could be related either to their social contribution or even their contribution
to the firms for which they worked (both of which were negative). For
instance, a study that focused on Bear Sterns and Lehman Brothers in 2000–
2008 has found that the top executive managers of these two giants had
brought home huge amounts of ‘performance-based’ compensations (esti-
mated at around $1 billion for Lehman and $1.4 billion for Bear Stearns),
which were not clawed back when the two firms collapsed.32

Still another piece of evidence supporting the importance of rent-seeking in
explaining the increase in inequality is provided by those studies that have
shown that increases in taxes at the very top do not result in decreases in growth
rates. If these incomes were a result of their efforts, we might have expected those
at the top to respond by working less hard, with adverse effects on GDP.33

The increase in rents34

Three striking aspects of the evolution of most rich countries in the past
thirty-five years are (a) the increase in the wealth-to-income ratio; (b) the

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JOSEPH E. STIGLITZ

stagnation of median wages; and (c) the failure of the return to capital to
decline. Standard neoclassical theories, in which ‘wealth’ is equated with
‘capital’, would suggest that the increase in capital should be associated with
a decline in the return to capital and an increase in wages. The failure of
unskilled workers’ wages to increase has been attributed by some (especially
in the 1990s) to skill-biased technological change, which increased the pre-
mium put by the market on skills. Hence, those with skills would see their
wages rise, and those without skills would see them fall. But recent years
have seen a decline in the wages paid even to skilled workers. Moreover, as
my recent research shows,35 average wages should have increased, even if
some wages fell. Something else must be going on.

There is an alternative—and more plausible—explanation. It is based on
the observation that rents are increasing (due to the increase in land rents,
intellectual property rents and monopoly power). As a result, the value of
those assets that are able to provide rents to their owners—such as land,
houses and some financial claims—is rising proportionately. So overall
wealth increases, but this does not lead to an increase in the productive
capacity of the economy or in the mean marginal productivity or average
wage of workers. On the contrary, wages may stagnate or even decrease,
because the rise in the share of rents has happened at the expense of wages.

The assets which are driving the increase in overall wealth, in fact, are
not produced capital goods. In many cases, they are not even ‘productive’
in the usual sense; they are not directly related to the production of goods
and services.36 With more wealth put into these assets, there may be less
invested in real productive capital. In the case of many countries where
we have data (such as France) there is evidence that this is indeed the
case: a disproportionate part of savings in recent years has gone into the
purchase of housing, which has not increased the productivity of the ‘real’
economy.

Monetary policies that lead to low interest rates can increase the value of
these ‘unproductive’ fixed assets—an increase in the value of wealth that is
unaccompanied by any increase in the flow of goods and services. By the
same token, a bubble can lead to an increase in wealth—for an extended
period of time—again with possible adverse effects on the stock of ‘real’ pro-
ductive capital. Indeed, it is easy for capitalist economies to generate such
bubbles (a fact that should be obvious from the historical record,37 but which
has also been confirmed in theoretical models.38 ) While in recent years there
has been a ‘correction’ in the housing bubble (and in the underlying price of
land), we cannot be confident that there has been a full correction. The
increase in the wealth–income ratio may still have more to do with an
increase in the value of rents than with an increase in the amount of produc-
tive capital. Those who have access to financial markets and can get credit
from banks (typically those already well off) can purchase these assets, using
them as collateral. As the bubble takes off, so does their wealth and society’s
inequality. Again, policies amplify the resulting inequality: favourable tax

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treatment of capital gains enables especially high after-tax returns on these
assets and increases the wealth especially of the wealthy, who disproportion-
ately own such assets (and understandably so, since they are better able to
withstand the associated risks).

The role of institutions and politics
The large influence of rent-seeking in the rise of top incomes undermines the
marginal productivity theory of income distribution. The income and wealth
of those at the top comes at least partly at the expense of others—just the
opposite conclusion from that which emerges from trickle-down economics.
When, for instance, a monopoly succeeds in raising the price of the goods
which it sells, it lowers the real income of everyone else. This suggests that
institutional and political factors play an important role in influencing the
relative shares of capital and labour.

As we noted earlier, in the past three decades wages have grown much
less than productivity (Figure 1)—a fact which is hard to reconcile with mar-
ginal productivity theory39 but is consistent with increased exploitation. This
suggests that the weakening of workers’ bargaining power has been a major
factor. Weak unions and asymmetric globalisation, where capital is free to
move while labour is much less so, are thus likely to have contributed signif-
icantly to the great surge of inequality.

The way in which globalisation has been managed has led to lower wages
in part because workers’ bargaining power has been eviscerated. With capi-
tal highly mobile—and with tariffs low—firms can simply tell workers that
if they don’t accept lower wages and worse working conditions, the com-
pany will move elsewhere. To see how asymmetric globalisation can affect
bargaining power, imagine, for a moment, what the world would be like if
there was free mobility of labour, but no mobility of capital. Countries
would compete to attract workers. They would promise good schools and a
good environment, as well as low taxes on workers. This could be financed
by high taxes on capital. But that’s not the world we live in.

In most industrialised countries there has been a decline in union
membership and influence; this decline has been especially strong in the
Anglo-Saxon world. This has created an imbalance of economic power and a
political vacuum. Without the protection afforded by a union, workers have
fared even more poorly than they would have otherwise. Unions’ inability
to protect workers against the threat of job loss by the moving of jobs
abroad has contributed to weakening the power of unions. But politics has
also played a major role, exemplified in President Reagan’s breaking of the
air traffic controllers’ strike in the US in 1981 or Margaret Thatcher’s battle
against the National Union of Mineworkers in the UK.

Central bank policies focusing on inflation have almost certainly been a
further factor contributing to the growing inequality and the weakening of
workers’ bargaining power. As soon as wages start to increase, and

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especially if they increase faster than the rate of inflation, central banks
focusing on inflation raise interest rates. The result is a higher average level
of unemployment and a downward ratcheting effect on wages: as the econ-
omy goes into recession, real wages often fall; and then monetary policy is
designed to ensure that they don’t recover.

Inequalities are affected not just by the legal and formal institutional
arrangements (such as the strength of unions) but also by social custom,
including whether it is viewed as acceptable to engage in discrimination.

At the same time, governments have been lax in enforcing anti-
discrimination laws. Contrary to the suggestion of free-market economists,
but consistent with even casual observation of how markets actually
behave, discrimination has been a persistent aspect of market economies,
and helps explain much of what has gone on at the bottom. The
discrimination takes many forms—in housing markets, in financial markets
(at least one of America’s large banks had to pay a very large fine for its
discriminatory practices in the run-up to the crisis) and in labour markets.
There is a large literature explaining how such discrimination persists.40, 41

Of course, market forces—the demand and supply for skilled workers,
affected by changes in technology and education—play an important role as
well, even if those forces are partially shaped by politics. But instead of these
market forces and politics balancing each other out, with the political pro-
cess dampening the increase in inequalities of income and wealth in periods
when market forces have led to growing disparities, in the rich countries
today the two have been working together to increase inequality.

The price of inequality
The evidence is thus unsupportive of explanations of inequality solely
focused on marginal productivity. But what of the argument that we need
inequality to grow?

A first justification for the claim that inequality is necessary for growth
focuses on the role of savings and investment in promoting growth, and is
based on the observation that those at the top save, while those at the bot-
tom typically spend all of their earnings. Countries with a high share of
wages will thus not be able to accumulate capital as rapidly as those with a
low share of wages. The only way to generate savings required for long-
term growth is thus to ensure sufficient income for the rich.

This argument is particularly inapposite today, where the problem is, to
use Bernanke’s term, a global savings glut.42 But even in those circumstances
where growth would be increased by an increase in national savings, there
are better ways of inducing savings than increasing inequality. The govern-
ment can tax the income of the rich, and use the funds to finance either pri-
vate or public investment; such policies reduce inequalities in consumption
and disposable income, and lead to increased national savings (appropriately
measured).

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A second argument centres on the popular misconception that those at the
top are the job creators, and giving more money to them will thus create
more jobs. Industrialised countries are full of creative entrepreneurial people
throughout the income distribution. What creates jobs is demand: when there
is demand, firms will create the jobs to satisfy that demand (especially if we
can get the financial system to work in the way it should, providing credit
to small and medium-sized enterprises).

In fact, as empirical research by the IMF has shown, inequality is associ-
ated with economic instability. In particular, IMF researchers have shown
that growth spells tend to be shorter when income inequality is high. This
result holds also when other determinants of growth duration (like external
shocks, property rights and macroeconomic conditions) are taken into
account: on average, a 10-percentile decrease in inequality increases the
expected length of a growth spell by one half.43 The picture does not change
if one focuses on medium-term average growth rates instead of growth
duration. Recent empirical research released by the OECD shows that
income inequality has a negative and statistically significant effect on
medium-term growth. It estimates that in countries like the US, the UK and
Italy, overall economic growth would have been six to nine percentage
points higher in the past two decades had income inequality not risen.44

There are different channels through which inequality harms the econ-
omy.45 First, inequality leads to weak aggregate demand. The reason is easy
to understand: those at the bottom spend a larger fraction of their income
than those at the top.46 The problem may be compounded by monetary
authorities’ flawed responses to this weak demand. By lowering interest
rates and relaxing regulations, monetary policy too easily gives rise to an
asset bubble, the bursting of which leads in turn to recession.47

Many interpretations of the current crisis have indeed emphasised the
importance of distributional concerns.48 Growing inequality would have led to
lower consumption but for the effects of loose monetary policy and lax regula-
tions, which led to a housing bubble and a consumption boom. It was, in short,
only growing debt that allowed consumption to be sustained.49 But it was
inevitable that the bubble would eventually break. And it was inevitable that,
when it broke, the economy would go into a downturn.

Second, inequality of outcomes is associated with inequality of opportu-
nity. When those at the bottom of the income distribution are at great risk of
not living up to their potential, the economy pays a price not only with
weaker demand today, but also with lower growth in the future. With
nearly one in four American children growing up in poverty,50 many of
them facing not just a lack of educational opportunity but also a lack of
access to adequate nutrition and health, the country’s long-term prospects
are being put into jeopardy.

Third, societies with greater inequality are less likely to make public
investments which enhance productivity, such as in public transportation,
infrastructure, technology and education. If the rich believe that they don’t

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JOSEPH E. STIGLITZ

need these public facilities, and worry that a strong government which could
increase the efficiency of the economy might at the same time use its powers
to redistribute income and wealth, it is not surprising that public investment
is lower in countries with higher inequality. Moreover, in such countries tax
and other economic policies are likely to encourage those activities that bene-
fit the financial sector over more productive activities. In the United States
today returns on long-term financial speculation (capital gains) are taxed at
approximately half the rate of labour, and speculative derivatives are given
priority in bankruptcy over workers. Tax laws encourage job creation abroad
rather than at home. The result is a weaker and more unstable economy.
Reforming these policies—and using other policies to reduce rent-seeking—
would not only reduce inequality; it would improve economic performance.

It should be noted that the existence of these adverse effects of inequality
on growth is itself evidence against an explanation of today’s high level of
inequality based on marginal productivity theory. For the basic premise of
marginal productivity is that those at the top are simply receiving just
deserts for their efforts, and that the rest of society benefits from their activi-
ties. If that were so, we should expect to see higher growth associated with
higher incomes at the top. In fact, we see just the opposite.

Reversing inequality
A wide range of policies can help reduce inequality. Policies should be
aimed at reducing inequalities both in market income and in the post-tax-
and-transfer incomes. The rules of the game play a large role in determining
market distribution—in preventing discrimination, in creating bargaining
rights for workers, in curbing monopolies and the powers of CEOs to exploit
firms’ other stakeholders and the financial sector to exploit the rest of soci-
ety. These rules were largely rewritten during the past thirty years in ways
which led to more inequality and poorer overall economic performance.
Now they must be rewritten once again, to reduce inequality and strengthen
the economy, for instance, by discouraging the short-termism that has
become rampant in the financial and corporate sector.51

Reforms include more support for education, including pre-school;
increasing the minimum wage; strengthening earned-income tax credits;
strengthening the voice of workers in the workplace, including through
unions; and more effective enforcement of anti-discrimination laws. But there
are four areas in particular that could make inroads in the high level of
inequality which now exists.52

First, executive compensation (especially in the US) has become excessive,
and it is hard to justify the design of executive compensation schemes based
on stock options. Executives should not be rewarded for improvements in a
firm’s stock market performance in which they play no part. If the Federal
Reserve lowers interest rates, and that leads to an increase in stock market
prices, CEOs should not get a bonus as a result. If oil prices fall, and so

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profits of airlines and the value of airline stocks increase, airline CEOs
should not get a bonus. There is an easy way of taking account of these
gains (or losses) which are not attributable to the efforts of executives: basing
performance pay on the relative performance of firms in comparable circum-
stances. The design of good compensation schemes that do this has been
well understood for more than a third of a century,53 and yet executives in
major corporations have almost studiously resisted these insights. They have
focused more on taking advantages of deficiencies in corporate governance
and the lack of understanding of these issues by many shareholders to try to
enhance their earnings—getting high pay when share prices increase, and
also when share prices fall. In the long run, as we have seen, economic
performance itself is hurt.54

Second, macroeconomic policies are needed that maintain economic stabil-
ity and full employment. High unemployment most severely penalises those
at the bottom and the middle of the income distribution. Today, workers are
suffering thrice over: from high unemployment, weak wages and cutbacks
in public services, as government revenues are less than they would be if
economies were functioning well.

As we have argued, high inequality has weakened aggregate demand. Fuel-
ling asset price bubbles through hyper-expansive monetary policy and dereg-
ulation is not the only possible response. Higher public investment—in
infrastructures, technology and education—would both revive demand and
alleviate inequality, and this would boost growth in the long-run and in the
short-run. According to a recent empirical study by the IMF, well-designed
public infrastructure investment raises output both in the short and long term,
especially when the economy is operating below potential. And it doesn’t
need to increase public debt in terms of GDP: well-implemented infrastruc-
ture projects would pay for themselves, as the increase in income (and thus in
tax revenues) would more than offset the increase in spending.55

Third, public investment in education is fundamental to address inequality.
A key determinant of workers’ income is the level and quality of education. If
governments ensure equal access to education, then the distribution of wages
will reflect the distribution of abilities (including the ability to benefit from
education) and the extent to which the education system attempts to compen-
sate for differences in abilities and backgrounds. If, as in the United States,
those with rich parents usually have access to better education, then one gener-
ation’s inequality will be passed on to the next, and in each generation, wage
inequality will reflect the income and related inequalities of the last.

Fourth, these much-needed public investments could be financed through
fair and full taxation of capital income. This would further contribute to
counteracting the surge in inequality: it can help bring down the net return
to capital, so that those capitalists who save much of their income won’t see
their wealth accumulate at a faster pace than the growth of the overall econ-
omy, resulting in growing inequality of wealth.56 Special provisions provid-
ing for favourable taxation of capital gains and dividends not only distort

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the economy, but, with the vast majority of the benefits going to the very
top, increase inequality. At the same time they impose enormous budgetary
costs: 2 trillion dollars from 2013 to 2023 in the US, according to the
Congressional Budget Office.57 The elimination of the special provisions for
capital gains and dividends, coupled with the taxation of capital gains on
the basis of accrual, not just realisations, is the most obvious reform in the
tax code that would improve inequality and raise substantial amounts of
revenues. There are many others,58 such as a good system of inheritance and
effectively enforced estate taxation.

Conclusion: redefining economic performance
We used to think of there being a trade-off: we could achieve more equality,
but only at the expense of overall economic performance. It is now clear
that, given the extremes of inequality being reached in many rich countries
and the manner in which they have been generated, greater equality and
improved economic performance are complements.

This is especially true if we focus on appropriate measures of growth. If
we use the wrong metrics, we will strive for the wrong things. As the inter-
national Commission on the Measurement of Economic Performance and
Social Progress argued, there is a growing global consensus that GDP does
not provide a good measure of overall economic performance.59 What
matters is whether growth is sustainable, and whether most citizens see their
living standards rising year after year.

Since the beginning of the new millennium, the US economy, and that of
most other advanced countries, has clearly not been performing. In fact, for
three decades, real median incomes have essentially stagnated. Indeed, in
the case of the US, the problems are even worse and were manifest well
before the recession: in the past four decades average wages have stagnated,
even though productivity has drastically increased.

As this chapter has emphasised, a key factor underlying the current eco-
nomic difficulties of rich countries is growing inequality. We need to focus
not on what is happening on average—as GDP leads us to do—but on how
the economy is performing for the typical citizen, reflected for instance in
median disposable income. People care about health, fairness and security,
and yet GDP statistics do not reflect their decline. Once these and other
aspects of societal well-being are taken into account, recent performance in
rich countries looks much worse.

The economic policies required to change this are not difficult to identify.
We need more investment in public goods; better corporate governance,
antitrust and anti-discrimination laws; a better regulated financial system;
stronger workers’ rights; and more progressive tax and transfer policies. By
‘rewriting the rules’ governing the market economy in these ways, it is pos-
sible to achieve greater equality in both the pre- and post-tax and transfer
distribution of income, and thereby stronger economic performance.60

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Acknowledgements
The author is indebted to Eamon Kircher-Allen and Deberati Ghosh for
research assistance. Financial support from INET and the Roosevelt Institute
Project on Inequality, supported by the Ford Foundation, the Bernard and
Irene Schwartz Foundation, and the John D. and Catherine T. MacArthur
Foundation, is gratefully acknowledged.

Notes
1 Source: T. Piketty and E. Saez, ‘Income inequality in the United States, 1913–1998’,
Quarterly Journal of Economics, vol. 118, no. 1, 2003, pp. 1–39, Tables A3 and A6 –
Updated version downloaded from http://eml.berkeley.edu/~saez/ (accessed 22
December 2015). Figures are in real 2014 dollars and include capital gains.

2 Source: US Census Historical Table H-6. It should be clear that median wages
could have declined, even though in a panel study, most individuals (families)
would have seen an increase in their wages, if there were a sufficiently large
number of new entrants into the labour force, and if these new entrants had
much lower skills/education than those previously in the labour force.

3 See J. Bivens, L. Mishel and H. Shierholz, Understanding the Historic Divergence
Between Productivity and a Typical Worker’s Pay, Economic Policy Institute briefing
paper No. 406, 2 September 2015.

4 US Census Data on educational attainment, http://www.census.gov/hhes/
socdemo/education/ (accessed 22 December 2015).

5 See The State of Working America, 12th ed by the Economic Policy Institute,
http://www.stateofworkingamerica.org/chart/swa-wages-table-4-14-hourly-wages-
education/ (accessed 22 December 2015).

6 At one time, such results were explained as a result of skill-biased technical
change (see G. Violante, ‘Skill-biased technical change’, in S. Durlauf and L.
Blume, eds, The New Palgrave Dictionary of Economics, New York, Palgrave
Macmillan, 2008, http://www.dictionaryofeconomics.com/article?id=pde2008_S0
00493&goto=skillbiased&result_number=3340 (accessed 6 May 2016) in which
case those without skills would see their wages decline, but those with skills
should see their wages increase. But an (appropriately) weighted average wage
should still rise. (See J. E. Stiglitz, New Theoretical Perspectives on the Distribution of
Income and Wealth among Individuals, paper presented at an IEA/World Bank
Roundtable on Shared Prosperity, Jordan, 10–11 June 2014 and to be published in
Inequality and Growth: Patterns and Policy, Volume 1: Concepts and Analysis, New
York, Palgrave Macmillan, 2016. Data over the past fifteen years, however, dur-
ing which even the wages of skilled workers have stagnated, implies that some-
thing else is going on.

7 Piketty and Saez, ‘Income inequality’ (updated version downloaded from http://
eml.berkeley.edu/~saez/ (accessed 22 December 2015)).

8 E. Saez and G. Zucman, ‘Wealth inequality in the United States since 1913:
evidence from capitalized income tax data’, forthcoming in Quarterly Journal of
Economics (revised October 2015). As the authors show, wealth share estimates
vary slightly depending on how and whether capital gains are included in the
estimate.

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JOSEPH E. STIGLITZ

http://eml.berkeley.edu/~saez/

http://www.census.gov/hhes/socdemo/education/

http://www.stateofworkingamerica.org/chart/swa-wages-table-4-14-hourly-wages-education/

http://www.dictionaryofeconomics.com/article?id=pde2008_S000493&goto=skillbiased&result_number=3340

http://eml.berkeley.edu/~saez/

9 J. Harkinson, ‘The Walmart heirs are worth more than everyone in your city com-
bined’, Mother Jones, 3 October 2015, http://www.motherjones.com/politics/
2014/10/walmart-walton-heirs-net-worth-cities (accessed 22 December 2015).

10 Saez and Zucman, ‘Wealth inequality’.
11 Ibid.
12 That this is the case can be clearly seen by examining what has happened to dif-

ferent kinds of wealth since the end of the crisis. Stocks, which are disproportion-
ately owned by the wealthy, have done very well. Stock market values in the
United States increased by $13 trillion from January 2009 to December 2013,
according to data from the Center for Research in Security Prices. Meanwhile,
home values, which account for much of middle-class wealth, have not enjoyed a
strong recovery: 13.4 per cent of American homes were still underwater as of the
third quarter of 2015, according to real estate company Zwillow—their owners
owe more on their mortgages than the market says their houses are worth. For a
concise discussion of this, see P. Dreier, ‘What housing recovery?’, The New York
Times, 8 May 2014, http://www.nytimes.com/2014/05/09/opinion/what-
housing-recovery.html?ref=opinion&_r=0 (accessed 22 December 2015).

13 See P. Taylor, R. Kochhar, R. Fry, G. Velasco and S. Motel, ‘Wealth gaps rise to
record highs between whites, blacks and Hispanics’, 2011, Pew Research Center
report, http://www.pewsocialtrends.org/files/2011/07/SDT-Wealth-Report_7-
26-11_FINAL (accessed 22 December 2015).

14 M. Corak, ‘Income inequality, equality of opportunity, and intergenerational
mobility’, Journal of Economic Perspectives, vol. 27, no. 3, Summer 2013, pp. 79–102.

15 Ibid.
16 OECD Income and Poverty Statistics, http://stats.oecd.org/Index.aspx?DataSet-

Code=IDD# (accessed 22 December 2015) . See also OECD, In It Together: Why
Less Inequality Benefits All, Paris, OECD, 2015.

17 Piketty, T., Capital in the 21st Century, supplementary materials, Tables S9.2 and
S10.1: piketty.pse.ens.fr/en/capital21c2, (accessed 14 April 2016).

18 The comparison is made using World Bank data. Some caution should be exer-
cised in comparing different countries’ Gini coefficients: in addition to the well-
known flaws in the measure, different databases have used slightly different
methodologies or income data to arrive at their respective figures, and thus fig-
ures are different depending on the data source. Nevertheless, many different
studies confirm these broad trends. One should also be particularly cautious in
interpreting differences in Gini coefficients between developed and developing
countries: Kuznets (‘Economic growth and income inequality’, The American Eco-
nomic Review, vol. XLV, no. 1, March 1955, pp. 1–28) put forward a persuasive
set of reasons why one might expect inequality to increase in the initial stages
of development, as some parts of the country and some groups in the country
are better able to seize new opportunities and pull away from others. Eventu-
ally, the laggards catch up. China’s growth in inequality over the past thirty
years is consistent with Kuznets’ hypothesis; that of the advanced countries is
not.

19 T. Piketty and G. Zucman, ‘Wealth and inheritance in the long-run’, in A. Atkin-
son and F. Bourguignon, eds, Handbook of Income Distribution, vol. 2, Amsterdam,
Elsevier-North Holland, 2015, pp. 1303–1368.

20 See N. Senior’s 1836 An Outline of the Science of Political Economy, London, Richard
Griffin & Co.

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The Walmart Heirs Are Worth More Than Everyone in Your City Combined

http://www.nytimes.com/2014/05/09/opinion/what-housing-recovery.html?ref=opinion&_r=0

http://www.pewsocialtrends.org/files/2011/07/SDT-Wealth-Report_7-26-11_FINAL

http://stats.oecd.org/Index.aspx?DataSetCode=IDD

21 For a recent application of this argument in defence of inequality, see N. G. Man-
kiw, ‘Defending the one percent’, Journal of Economic Perspectives, vol. 27, no. 3,
Summer 2013, pp. 21–34.

22 I recognised this early in my own work on information asymmetries, in a major
controversy with Steven N. S. Cheung over whether the institution of sharecrop-
ping (which I argued could be explained by information asymmetries) mattered
(see J. E. Stiglitz, ‘Incentives and risk sharing in sharecropping’, The Review of Eco-
nomic Studies, vol. 41, no. 2, 1974, pp. 219–55 and S. Cheung, ‘Transaction costs,
risk aversion and the choice of contractual arrangements’, Journal of Law and Eco-
nomics, vol. 19, no. 1, 1969). North has perhaps done more to bring institutional
analysis into the mainstream than anyone else: see D. C. North, Institutions, Insti-
tutional Change and Economic Performance, Cambridge, Cambridge University
Press, 1990.

23 J. Bakija, A. Cole and B. T. Heim, ‘Job and income growth of top earners and the
causes of changing income inequality: evidence from U.S. tax return data’, 2012,
http://web.williams.edu/Economics/wp/BakijaColeHeimJobsIncomeGrowthTop
Earners (accessed 22 December 2015).

24 See M. Jensen and K. Murphy, ‘Performance pay and top-management incen-
tives’, The Journal of Political Economy, vol. 98, no. 2, 1990, pp. 225–64.

25 L. Bebchuk and J. Fried, Pay without Performance: The Unfulfilled Promise of Execu-
tive Compensation, Cambridge, MA, Harvard University Press, 2006; L. Bebchuk
and Y. Grinstein, The Growth of Executive Pay, NBER Working Paper No. 11443,
June 2005.

26 L. Mishel and N. Sabadish, CEO Pay and the Top 1 Per Cent, Economic Policy
Institute Brief 332, 2012; J. Bivens and L. Mishel, ‘The pay of corporate executives
and financial professionals as evidence of rents in the top 1 percent incomes’,
Journal of Economic Perspectives, vol. 27, no. 3, Summer 2013, pp. 57–78.

27 AFL-CIO, CEO-to-Worker Pay Ratios around the World, 2013, http://www.aflcio.
org/Corporate-Watch/Paywatch-Archive/CEO-Pay-and-You/CEO-to-Worker-
PayGap-in-the-United-States/Pay-Gaps-in-the-World (accessed 22 December 2015).

28 I had written a series of theoretical and policy papers arguing this in the 1980s.
See e.g. B. J. Nalebuff and J. E. Stiglitz, ‘Prizes and incentives: towards a general
theory of compensation and competition’, The Bell Journal of Economics, vol. 14,
no. 1, 1983, pp. 21–43 and J. E. Stiglitz, ‘The design of labor contracts: economics
of incentives and risk-sharing’, in H. Nalbantian, ed., Incentives, Cooperation and
Risk Sharing, Totowa, NJ, Rowman & Allanheld, 1987, pp. 47–68, reprinted in The
Selected Works of Joseph E. Stiglitz, Volume II: Information and Economic Analysis:
Applications to Capital, Labor, and Product Markets, Oxford, Oxford University
Press, 2013, pp. 432–46.

29 The author was a participant in some of these battles. For a more extensive dis-
cussion of them, and their consequences, see J. E. Stiglitz, Roaring Nineties, New
York, W. W. Norton, 2003. There were other later battles, for example concerning
say in pay and other reforms in corporate governance. For a discussion of the
kinds of reforms in tax and corporate governance laws that might make a differ-
ence, see J. E. Stiglitz, Rewriting the Rules, Hyde Park, NY, The Roosevelt Institute,
May 2015.

30 T. Philippon and A. Reshef, ‘Wages and human capital in the US financial
industry: 1909–2006’, The Quarterly Journal of Economics, vol. 127, no. 4, 2012,
pp. 1551–609.

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JOSEPH E. STIGLITZ

http://web.williams.edu/Economics/wp/BakijaColeHeimJobsIncomeGrowthTopEarners

http://www.aflcio.org/Corporate-Watch/Paywatch-Archive/CEO-Pay-and-You/CEO-to-Worker-PayGap-in-the-United-States/Pay-Gaps-in-the-World

31 D. Baker and T. McArthur, The Value of the ‘Too Big to Fail’ Big Bank Subsidy, Cen-
ter for Economic and Policy Social Research Issue Brief, September 2009. For a
different view, see United States Government Accountability Office, Large Bank
Holding Companies: Expectations of Government Support, 2014, GAO-14-621,
Washington, DC, United States General Accounting Office, which argues that
funding advantages existed before the recent financial crash but disappeared
afterwards.

32 See L. Bebchuk, A. Cohen and A. Spamaan, ‘The wages of failure: executive com-
pensation at Bear Stearns and Lehman 2000–2008’, Yale Journal on Regulation, vol.
27, 2010, pp. 257–82.

33 Philippon and Reshef, ‘Wages and human capital’.
34 This section is based on J. E. Stiglitz, New Theoretical Perspectives on the Distribu-

tion of Income and Wealth among Individuals, 2015, NBER Working Paper 21191.
35 Ibid.
36 Though they may be reflected in GDP, and may be related in particular to the

value of housing services.
37 See C. Reinhardt and K. Rogoff, This Time Is Different: Eight Centuries of Financial

Folly, 2009, Princeton, NJ, Princeton University Press.
38 See, for instance, K. Shell and J. E. Stiglitz, ‘Allocation of investment in a dynamic

economy’, Quarterly Journal of Economics, vol. 81, no. 4, 1967, pp. 592–609; F. Hahn,
‘Equilibrium dynamics with heterogeneous capital goods’, Quarterly Journal of Eco-
nomics, vol. 80, no. 4 1966, pp. 633–46; and Stiglitz, New Theoretical Perspectives.

39 As we noted earlier, skill-biased technological change might be able to explain
declines in unskilled labour; but it is hard to reconcile either the timing of wage
changes, or the stagnation even of skilled wages in recent years, with such theo-
ries. Moreover, average wages should have increased. It is, of course, possible that
average productivity increased while marginal productivity did not. (This cannot,
of course, happen in the Cobb–Douglas production function so beloved by
macroeconomists.) But I have seen no evidence for this sudden change in technol-
ogy—and no theory for why this might have happened.

40 America’s mass incarceration policies have also been an important instrument of
discrimination. See M. Alexander, The New Jim Crow: Mass Incarceration in the Age
of Colorblindness, New York, The New Press, 2010.

41 For a recent account of this literature, see K. Basu, Beyond the Invisible Hand:
Groundwork for a New Economics, Princeton, NJ, Princeton University Press, 2010.
See also J. E. Stiglitz, ‘Approaches to the economics of discrimination’, American
Economic Review, vol. 62, no. 2, 1973, pp. 287–95 and J. E. Stiglitz, ‘Theories of dis-
crimination and economic policy’, in G. von Furstenberg, Ann R. Horowitz, and
Bennett Harrison, eds, Patterns of Racial Discrimination, Lexington, MA, D. C.
Heath and Company Lexington Books, 1974, pp. 5–26.

42 I have argued elsewhere (‘Monetary policy in a multipolar world’, in J. E. Stiglitz
and R. S. Gurkaynak, eds, Taming Capital Flows: Capital Account Management in an
Era of Globalization, IEA Conference Volume No. 154, New York, Palgrave
Macmillan, 2015) that the problem is not really a savings glut: there are huge
needs for investment on the global level. Unfortunately, the global financial sys-
tem is unable to intermediate—to ensure that the available savings is used to
finance the real global investment needs. The consequence is the ‘paradox of
thrift’: savings leads to inadequate aggregate demand.

153

INEQUALITY AND ECONOMIC GROWTH

43 A. Berg and J. Ostry, Inequality and Unsustainable Growth: Two Sides of the Same
Coin? IMF Staff Discussion Note No. 11/08, April 2011, International Monetary
Fund.

44 F. Cingano, Trends in Income Inequality and Its Impact on Economic Growth, OECD
Social, Employment and Migration Working Papers, no. 163, Dec. 2014, OECD
Publishing.

45 The discussion below emphasises three channels. There are others. The increased
instability noted earlier has adverse consequences for growth. Extremes of
inequality, especially when they seem unjustified, undermine societal trust, and
this hurts growth. To the extent that inequality arises from distortionary rents,
these distortions also hurt economic performance.

46 K. E. Dynan, J. Skinner and S. P. Zeldes, ‘Do the rich save more?’ Journal of Politi-
cal Economy, vol. 112, no. 2, 2004, pp. 397–444.

47 This and other arguments in this section are developed at greater length in my
book The Price of Inequality: How Today’s Divided Society Endangers Our Future,
New York, W. W. Norton, 2012.

48 A. Jayadev, ‘Distribution and crisis: reviewing some of the linkages’, in G.
Epstein and M. Wolfson, eds, Handbook on the Political Economy of Crisis, Oxford,
Oxford University Press, 2013, pp. 95–112. See also The Stiglitz Report: Reforming
the International Monetary and Financial Systems in the Wake of the Global Crisis, with
Members of the Commission of Experts of the President of the United Nations
General Assembly on Reforms of the International Monetary and Financial Sys-
tem, New York, The New Press, 2010; and J. E. Stiglitz, Freefall: America, Free Mar-
kets, and the Sinking of the World Economy, New York, W. W. Norton, 2010.

49 See for example A. Barba and M. Pivetti, ‘Rising household debt: its causes and
macroeconomic implications—a long period analysis’, Cambridge Journal of Eco-
nomics, vol. 33, no. 1, 2009, pp. 113–37.

50 See http://www.childstats.gov/americaschildren/eco1a.asp (accessed 22 Decem-
ber 2015).

51 Stiglitz, Rewriting the Rules.
52 In the last chapter of my book The Price of Inequality, I outline twenty-one such

policies, affecting both the distribution of income before taxes and transfers and
after.

53 See, for instance, B. J. Nalebuff and J. E. Stiglitz, ‘Prizes and incentives: towards a
general theory of compensation and competition’, The Bell Journal of Economics,
vol. 14, no. 1, 1983, pp. 21–43.

54 See e.g. J. E. Stiglitz, Roaring Nineties, New York, W. W. Norton, 2003. More
recently, I and my colleagues at the Roosevelt Institute have explained how other
changes in tax and regulatory policy have contributed to short-sighted and dis-
honest corporate behaviour (see Stiglitz, Rewriting the Rules)

55 IMF, ‘Is it time for an infrastructure push? The macroeconomic effects of public
investment’, World Economic Outlook, October 2014, pp. 75–114, http://www.
imf.org/external/pubs/ft/weo/2014/02/pdf/c3 (accessed 22 December
2015). Note that the balanced budget multiplier itself provides a framework in
which governments can increase investment and stimulate the economy today,
without incurring any increase in current deficits—but lowering future deficits
and the debt/GDP ratio.

56 T. Piketty, Capital in the 21st Century, Cambridge, MA and London, Harvard
University Press, 2014.

154

JOSEPH E. STIGLITZ

http://www.childstats.gov/americaschildren/eco1a.asp

http://www.imf.org/external/pubs/ft/weo/2014/02/pdf/c3

57 More precisely, these are the estimated costs (‘tax expenditures’) associated
with these special provisions. See Congressional Budget Office, The Distribution
of Major Tax Expenditures in the Individual Income Tax System, May 2013,
p. 31, http://cbo.gov/sites/default/files/cbofiles/attachments/TaxExpenditures_
One-Column (accessed 22 December 2015). This figure includes the effects of
the ‘step-up of basis at death’ provision, which reduces the taxes that heirs pay
on capital gains. Not including this provision, the ten-year budgetary cost of pref-
erential treatment for capital gains and dividends is $1.34 trillion. These calcula-
tions do not, however, include the value of the fact that the tax on capital gains
is postponed until realisation.

58 See J. E. Stiglitz, Reforming Taxation to Promote Growth and Equity, Roosevelt Insti-
tute White Paper, May 2014, http://rooseveltinstitute.org/sites/all/files/
Stiglitz_Reforming_Taxation_White_Paper_Roosevelt_Institute (accessed 22
December 2015).

59 The Commission’s report was released in 2009, and published as J. Stiglitz, A.
Sen and J. P. Fitoussi, Mismeasuring Our Lives, New York, The New Press, 2010.
The OECD has since continued work in this vein with its Better Life Initiative
(http://www.oecd.org/statistics/betterlifeinitiativemeasuringwell-beingandprogress.
htm (accessed 22 December 2015)) and its High Level Expert Group on the mea-
surement of economic and social progress, convened in 2013.

60 See Stiglitz, Rewriting the Rules.

155

INEQUALITY AND ECONOMIC GROWTH

http://cbo.gov/sites/default/files/cbofiles/attachments/TaxExpenditures_One-Column

http://rooseveltinstitute.org/sites/all/files/Stiglitz_Reforming_Taxation_White_Paper_Roosevelt_Institute

http://www.oecd.org/statistics/betterlifeinitiativemeasuringwell-beingandprogress.htm

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Erica King

PSY3450-80

[December 17th, 2017]

Prof. DiMatteo

Annotated Bibliography

The community problem I chose to identify is economic inequality. Economic inequality is defined as the way income is distributed in an uneven manner among the U.S. Economic inequality doesn’t receive enough attention and people that aren’t part of the static don’t care. This is also because it’s more common in urban communities. The gap from the rich and poverty keep growing larger. Due to this problem, the urban community also faces other challenges. These challenges include homelessness, unemployment, and so on. I would evaluate this problem by adding jobs, more resources to help people ween of governmental help, and push those to do things they wanted to do to provide a better environment for their families.

Goldberg, G.S. (2012). Economic Inequality and Economic Crisis: A Challenge for Social Workers, Vol 57, No.3, pp.211-214. This article speaks of the role of social workers as it relates to the clients they serve that are effected by economic inequalities. The economic inequalities are more prominent amongst urban communities. Social workers service clients that have been effected by homelessness and unemployment. Social workers have been providing housing and employment resources to their clients as a result of social inequalities. These services have drastically increased over the past three decades due to the rise in economic inequalities.

Cantante, F. (2016). Trends in Income Inequality: Comparing the United States and Portugal, Portuguese Journal of Social Science, 15:3, pp 367-86. This article does a comparison between economic inequalities within the United States and Portugal. The comparison shows that there is differences and similarities amongst the two countries. The main is difference is that the United States has a political stance on why their economy has inequalities. The similarity between them is their high mortality rate primarily in lower economic neighborhoods. The two countries are ranked the highest with economic inequalities.

Stiglitz, J.E. (2014). Inequality and Economic Growth. Pp 134-149. This article is about how economic growth influences our society by providing increased wealth and higher learning standards to everyone. Resources made available to rich people would also be made available to poor people. Inequality, is rising rapidly within the United States. Marginal productivity theory explains why it occurs and the justification for it. Excessive inequalities tend to lead to a weaker economic performance has been proven by this theory.

Mode, N. (2016). Race, Neighborhood Economic Status, Income Inequality and Mortality, 11:5, pp 1-14. Mortality rates have increased mostly in urban communities due to its economic status. People whom reside in urban communities tend to have lower paying jobs, increased unemployment and homelessness in their neighborhoods. Statistics show that African American males primarily reside in urban neighborhoods are below the poverty line. Race plays a role in economic inequality. A census conducted in 1995, suggests that African Americans were 1.6 times greater at a mortality risk than any other race due to lower socioeconomic status.

Saiz, I. (2017). Tackling Inequality through the Sustainable Development Goals: human rights in practice. International Journal of Human Rights, 21:8, pp 1029-1049. This article is about how human rights have been effected by economic inequality. Future reports speak of decreasing inequalities within the countries. Basic human rights have been minimized as a result of economic inequality. This presents as a global problem.

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