INEQUALITY: CAUSES AND CONSEQUENCES
INTERNATIONAL MONETARY FUND 1
June 2015
SDN/15/13
I M F S T A F F D I S C
U S S I ON N O T
E
Causes and Consequences
of Income Inequality:
A Global Perspective
Era Dabla-Norris, Kalpana Kochhar, Nujin
Suphaphiphat, Frantisek Ricka, Evridiki Tsounta
I N T E R N A T I O N A L M O N E T A R Y F U N D
CAUSES AND CONSEQUENCE OF INEQUALITY
2 INTERNATIONAL MONETARY FUND
INTERNATIONAL MONETARY FUND
Strategy, Policy, and Review Department
Causes and Consequences of Income Inequality: A Global Perspective
Prepared by Era Dabla-Norris, Kalpana Kochhar, Frantisek Ricka,
Nujin Suphaphiphat, and Evridiki Tsounta
(with contributions from Preya Sharma and Veronique Salins)
1
Authorized for distribution by Siddharh Tiwari
June 2015
JEL Classification Numbers: D63, D31, 015, H23,
Keywords: Inequality, Gini coefficient, cross-country analysis
Author’s E-mail Addresses: [email protected]
1
Frank Wallace and Zhongxia Zhang provided excellent research assistance. We also thank Ricardo
Reinoso and Christiana Weekes for editorial assistance.
DISCLAIMER: This Staff Discussion Note represents the views of the authors and does
not necessarily represent IMF views or IMF policy. The views expressed herein should
be attributed to the authors and not to the IMF, its Executive Board, or its
management. Staff Discussion Notes are published to elicit comments and to further
debate.
INEQUALITY: CAUSES AND CONSEQUENCES
INTERNATIONAL MONETARY FUND 3
CONTENTS
EXECUTIVE SUMMARY _________________________________________________________________________________ 4
II. MACROECONOMIC CONSEQUENCES: WHY WE CARE ____________________________________________ 6
III. STYLIZED FACTS: WHAT DO WE KNOW ABOUT INEQUALITY OF OUTCOMES AND
OPPORTUNITIES? _______________________________________________________________________________________ 9
IV. INEQUALITY DRIVERS ____________________________________________________________________________ 18
A. Factors Driving Higher Income Inequality ___________________________________________________________ 18
B. Empirical Analysis ___________________________________________________________________________________ 22
V. POLICY DISCUSSION AND FINAL REMARKS _____________________________________________________ 30
ANNEX I. DEFINITIONS AND SOURCES OF VARIABLES ____________________________________________ 33
FIGURES
1. Income Inequality and Social Mobility ________________________________________________________________ 8
2. Global Inequality and Distribution of Income _______________________________________________________ 10
3. Change in Net Gini Index, 1990–2012 _______________________________________________________________ 11
4. Change in Gross Gini and Income Decile ____________________________________________________________ 12
5. Top 1% Income Share _______________________________________________________________________________ 13
6. Estimated Corporate Profits _________________________________________________________________________ 13
7. Change in Income Share, 1990–2009 ________________________________________________________________ 13
8. Disconnect: Real Average Wage and Productivity ___________________________________________________ 14
9. Poverty Rates by Regions ___________________________________________________________________________ 15
10. Top 1% and Bottom 90% Wealth Distribution, 1980–2010 ________________________________________ 15
11. Wealth and Income Inequality in Advanced and Emerging Market Economies, 2000 _____________ 16
12. Inequalities in Health by Quintile, 2010–12 ________________________________________________________ 17
13. Education Gini and Outcomes by Income Decile __________________________________________________ 17
14. Financial Inclusion in Advanced and Developing Countries _______________________________________ 18
15. Technological Progress and Skill Premium in OECD Countries ____________________________________ 19
16. Trade and Financial Openness _____________________________________________________________________ 20
17. Union Rate by Country Group _____________________________________________________________________ 21
18. Change in Top Tax Rate and Top 1 Percent Income Share ________________________________________ 22
19. Impact of Change in Financial Deepening on Inequality ___________________________________________ 23
20. Decomposition of the Change in Market (Gross) Income Inequality ______________________________ 27
21. Change in Income Share of the Bottom 10 Percent and Middle Decile ____________________________ 28
TABLES
1. Regression Results of Growth Drivers _________________________________________________________________ 7
2. Regression Results of Inequality Drivers ____________________________________________________________ 25
3. Regression Results on Determinants of Poverty Change ____________________________________________ 29
BOXES
1. Assessing the Drivers of Income Inequality Around the World _____________________________________ 24
2. Drivers of Poverty ___________________________________________________________________________________ 29
References ____________________________________________________________________________________________ 34
CAUSES AND CONSEQUENCE OF INEQUALITY
4 INTERNATIONAL MONETARY FUND
EXECUTIVE SUMMAR
Y
“We should measure the health of our society not at its apex, but at its base.” Andrew Jackson
Widening income inequality is the defining challenge of our time. In advanced economies, the gap
between the rich and poor is at its highest level in decades. Inequality trends have been more mixed
in emerging markets and developing countries (EMDCs), with some countries experiencing declining
inequality, but pervasive inequities in access to education, health care, and finance remain. Not
surprisingly then, the extent of inequality, its drivers, and what to do about it have become some of
the most hotly debated issues by policymakers and researchers alike. Against this background, the
objective of this paper is two-fold.
First, we show why policymakers need to focus on the poor and the middle class. Earlier IMF work
has shown that income inequality matters for growth and its sustainability. Our analysis suggests
that the income distribution itself matters for growth as well. Specifically, if the income share of the
top 20 percent (the rich) increases, then GDP growth actually declines over the medium term,
suggesting that the benefits do not trickle down. In contrast, an increase in the income share of the
bottom 20 percent (the poor) is associated with higher GDP growth. The poor and the middle class
matter the most for growth via a number of interrelated economic, social, and political channels.
Second, we investigate what explains the divergent trends in inequality developments across
advanced economies and EMDCs, with a particular focus on the poor and the middle class. While
most existing studies have focused on advanced countries and looked at the drivers of the Gini
coefficient and the income of the rich, this study explores a more diverse group of countries and
pays particular attention to the income shares of the poor and the middle class—the main engines
of growth. Our analysis suggests that
Technological progress and the resulting rise in the skill premium (positives for growth and
productivity) and the decline of some labor market institutions have contributed to inequality in
both advanced economies and EMDCs. Globalization has played a smaller but reinforcing role.
Interestingly, we find that rising skill premium is associated with widening income disparities in
advanced countries, while financial deepening is associated with rising inequality in EMDCs,
suggesting scope for policies that promote financial inclusion.
Policies that focus on the poor and the middle class can mitigate inequality. Irrespective of the
level of economic development, better access to education and health care and well-targeted
social policies, while ensuring that labor market institutions do not excessively penalize the poor,
can help raise the income share for the poor and the middle class.
There is no one-size-fits-all approach to tackling inequality. The nature of appropriate policies
depends on the underlying drivers and country-specific policy and institutional settings. In
advanced economies, policies should focus on reforms to increase human capital and skills,
coupled with making tax systems more progressive. In EMDCs, ensuring financial deepening is
accompanied with greater financial inclusion and creating incentives for lowering informality
would be important. More generally, complementarities between growth and income equality
objectives suggest that policies aimed at raising average living standards can also influence the
distribution of income and ensure a more inclusive prosperity.
INEQUALITY: CAUSES AND CONSEQUENCES
INTERNATIONAL MONETARY FUND 5
I. CONTEXT
1. Rising inequality is a widespread concern. Inequality within most advanced and emerging
markets and developing countries (EMDCs) has increased, a phenomenon that has received
considerable attention—President Obama called widening income inequality the “defining challenge
of our time.” A recent Pew Research Center (PRC 2014) survey found that the gap between the rich
and the poor is considered a major challenge by more than 60 percent of respondents worldwide,
and Pope Francis has spoken out against the “economy of exclusion.” Indeed, the PRC survey found
that while education and working hard were seen as important for getting ahead, knowing the right
persons and belonging to a wealthy family were also critical, suggesting potential major hurdles to
social mobility. Not surprisingly then, the extent of inequality, its drivers, and what to do about it
have become some of the most hotly debated issues by policymakers and researchers alike.
2. Why it matters. Equality, like fairness, is an important value in most societies. Irrespective of
ideology, culture, and religion, people care about inequality. Inequality can be a signal of lack of
income mobility and opportunity―a reflection of persistent disadvantage for particular segments of
the society. Widening inequality also has significant implications for growth and macroeconomic
stability, it can concentrate political and decision making power in the hands of a few, lead to a
suboptimal use of human resources, cause investment-reducing political and economic instability,
and raise crisis risk. The economic and social fallout from the global financial crisis and the resultant
headwinds to global growth and employment have heightened the attention to rising income
inequality.
3. This note. The objective of the note is two-fold. First, it shows why policymakers need to
focus on the poor and the middle class. Building on earlier IMF work which has shown that income
inequality matters for growth, we show that the income distribution itself matters for growth as well.
In particular, our findings suggest that raising the income share of the poor and ensuring that there
is no hollowing-out of the middle class is good for growth through a number of interrelated
economic, social, and political channels. Second, we investigate what explains the divergent trends in
inequality developments across advanced economies and EMDCs, with a particular focus on the
poor and the middle class. In that context, we are filling a gap in the literature since existing studies
typically focus only on advanced economies or a smaller sample of EMDCs. This approach allows us
to suggest policy implications depending on the underlying drivers, and country-specific policy and
institutional settings.
4. Roadmap. Section II provides an overview of the macroeconomic implications of high
inequality of outcomes and opportunities and shows why policymakers’ focus on the income shares
of poor and the middle class can prove growth-enhancing. Section III provides a rich documentation
of recent trends in both monetary and nonmonetary indicators of inequality across advanced
economies and EMDCs, while Section IV investigates the drivers of the rise in inequality, including
from an empirical perspective. Section V concludes and discusses policy implications.
CAUSES AND CONSEQUENCE OF INEQUALITY
6 INTERNATIONAL MONETARY FUND
II. MACROECONOMIC CONSEQUENCES: WHY WE CARE
5. Outcomes and opportunities. The discourse on inequality often makes a distinction
between inequality of outcomes (as measured by income, wealth, or expenditure) and inequality of
opportunities―attributed to differences in circumstances beyond the individual’s control, such as
gender, ethnicity, location of birth, or family background. Inequality of outcomes arises from a
combination of differences in opportunities and individual’s efforts and talent. At the same time, it is
not easy to separate effort from opportunity, especially in an intergenerational context. For instance,
parental income, resulting from their own effort, determines the opportunity of their children to
obtain an education. It is in this spirit that Rawls (1971) argued that the distribution of opportunities
and of outcomes are equally important and informative to understand the nature and extent of
inequality around the world.
6. Is inequality a necessary evil? Some degree of inequality may not be a problem insofar as
it provides the incentives for people to excel, compete, save, and invest to move ahead in life. For
example, returns to education and differentiation in labor earnings can spur human capital
accumulation and economic growth, despite being associated with higher income inequality.
Inequality can also influence growth positively by providing incentives for innovation and
entrepreneurship (Lazear and Rosen 1981), and, perhaps especially relevant for developing
countries, by allowing at least a few individuals to accumulate the minimum needed to start
businesses and get a good education (Barro 2000).
7. Why is rising inequality a concern? High and sustained levels of inequality, especially
inequality of opportunity can entail large social costs. Entrenched inequality of outcomes can
significantly undermine individuals’ educational and occupational choices. Further, inequality of
outcomes does not generate the “right” incentives if it rests on rents (Stiglitz 2012). In that event,
individuals have an incentive to divert their efforts toward securing favored treatment and
protection, resulting in resource misallocation, corruption, and nepotism, with attendant adverse
social and economic consequences. In particular, citizens can lose confidence in institutions, eroding
social cohesion and confidence in the future.
8. Income distribution matters for growth. Previous IMF studies have found that income
inequality (as measured by the Gini coefficient, which is 0 when everybody has the same income and
1 when one person has all the income) negatively affects growth and its sustainability (Ostry, Berg,
and Tsangarides 2014; Berg and Ostry 2011). We build on this analysis by examining how
individuals’ income shares at various points in the distribution matter for growth drawing on a large
sample of advanced economies and EMDCs (Table 1).
2
A higher net Gini coefficient (a measure of
2
This analysis is based on a sample of 159 advanced, emerging, and developing economies for the period 1980–
2012 using a simple growth model (with time and country fixed effects) in which growth depends on initial income
(convergence hypothesis), lagged GDP growth, and inequality (as measured by net Gini or the income shares
accruing to various quintiles) estimated using system GMM. Augmenting this model with standard growth
determinants, such as human and physical capital, does not affect our main findings. See Annex for data sources.
INEQUALITY: CAUSES AND CONSEQUENCES
INTERNATIONAL MONETARY FUND 7
inequality that nets out taxes and transfers) is associated with lower output growth over the medium
term, consistent with previous findings. More importantly, we find an inverse relationship between
the income share accruing to the rich (top 20 percent) and economic growth. If the income share of
the top 20 percent increases by 1 percentage point, GDP growth is actually 0.08 percentage point
lower in the following five years, suggesting that the benefits do not trickle down. Instead, a similar
increase in the income share of the bottom 20 percent (the poor) is associated with 0.38 percentage
point higher growth. This positive relationship between disposable income shares and higher growth
continues to hold for the second and third quintiles (the middle class). This result survives a variety
of robustness checks, and is in line with recent findings for a smaller sample of advanced economies
(OECD 2014).
In the remainder of this section, we discuss potential channels for why higher income
shares for the poor and the middle class are growth-enhancing.
Table 1. Regression Results of Growth and Income Distribution
Source: Solt Database; World Bank; UNU-WIDER World Income Inequality Database; and IMF staff
calculations.
Note: Standard errors in parentheses, *p < 0.1; **p < 0.05; ***p < 0.01. Estimated using system GMM,
which instruments potentially endogenous right-hand-side variables using lagged values and first
differences. The regressions include country and time dummies to respectively control for time-
invariant omitted-variable bias and global shocks, which might affect aggregate growth but are not
otherwise captured by the explanatory variables.
Variables (1) (2) (3) (4) (5) (6)
Lagged GDP Growth 0.145*** 0.112*** 0.118*** 0.113*** 0.097*** 0.114***
(0.033) (0.030) (0.031) (0.031) (0.030) (0.031)
GDP Per Capita Level (in logs) -1.440*** -2.198*** -2.247*** -2.223*** -2.122*** -2.222***
(0.361) (0.302) (0.307) (0.308) (0.304) (0.307)
N
et Gini -0.0666*
(0.034)
1st Quintile 0.381**
(0.165)
2nd Quintile 0.325**
(0.146)
3rd Quintile 0.266*
(0.152)
4th Quintile 0.0596
(0.180)
5th Quintile -0.0837*
(0.044)
Constan
t
17.34*** 18.82*** 18.12*** 17.45*** 19.41*** 25.32***
(3.225) (2.579) (2.713) (3.058) (4.203) (3.496)
Country Fixed Effects Yes Yes Yes Yes Yes Yes
Time Dummies Yes Yes Yes Yes Yes Yes
#. of Observations 733 455 455 455 455 455
#. of Countries 159 156 156 156 156 156
Dependent Variable: GDP Growth
CAUSES AND CONSEQUENCE OF INEQUALITY
8 INTERNATIONAL MONETARY FUND
9. Inequality affects growth drivers.
Why would widening income disparities matter
for growth? Higher inequality lowers growth by
depriving the ability of lower-income
households to stay healthy and accumulate
physical and human capital (Galor and Moav
2004; Aghion, Caroli, and Garcia-Penalosa
1999). For instance, it can lead to under-
investment in education as poor children end
up in lower-quality schools and are less able to
go on to college.
3
As a result, labor productivity
could be lower than it would have been in a
more equitable world (Stiglitz 2012). In the
same vein, Corak (2013) finds that countries
with higher levels of income inequality tend to
have lower levels of mobility between
generations, with parent’s earnings being a more important determinant of children’s earnings
(Figure 1). Increasing concentration of incomes could also reduce aggregate demand and
undermine growth, because the wealthy spend a lower fraction of their incomes than middle- and
lower-income groups.
4
10. Inequality dampens investment, and hence growth, by fueling economic, financial, and
political instability.
Financial crises. A growing body of evidence suggests that rising influence of the rich and
stagnant incomes of the poor and middle class have a causal effect on crises, and thus directly
hurt short- and long-term growth.
5
In particular, studies have argued that a prolonged period of
higher inequality in advanced economies was associated with the global financial crisis by
intensifying leverage, overextension of credit, and a relaxation in mortgage-underwriting
standards (Rajan 2010), and allowing lobbyists to push for financial deregulation (Acemoglu
2011).
Global imbalances. Higher top income shares coupled with financial liberalization, which itself
could be a policy response to rising income inequality, are associated with substantially larger
3
Widening income disparities can depress skills development among individuals with poorer parental education
background, both in terms of the quantity of education attained (for example, years of schooling) and its quality (that
is, skill proficiency). Educational outcomes of individuals from richer backgrounds, however, are not affected by
inequality (Cingano 2014).
4
See Carvalho and Rezai (2014) for a discussion of the empirical and theoretical underpinnings of this assertion.
5
In a theoretical setting, Kumhof and Ranciere (2010) and Kumhof and others (2012) show that rising inequality
enables investors to increase their holding of financial assets backed by loans to workers, resulting in rising debt-to-
income ratios and thus financial fragility. The latter can eventually lead to a financial crisis.
Figure 1. Income Inequality and Social Mobility
Sources: Corak (2013); Organisation of Economic Co-
operation and Development; and IMF staff calculations.
0.1
0.2
0.3
0.4
0.5
20 25 30 35
Income Inequality, 1980s (more inequality -----> )
Intergenerational earnings elasticity,
1960s-1990s ( less mobility -----> )
INEQUALITY: CAUSES AND CONSEQUENCES
INTERNATIONAL MONETARY FUND 9
external deficits (Kumholf and others 2012). Such large global imbalances can be challenging for
macroeconomic and/or financial stability, and thus growth (Bernanke 2011).
Conflicts. Extreme inequality may damage trust and social cohesion and thus is also associated
with conflicts, which discourage investment. Conflicts are particularly prevalent in the
management of common resources where, for example, inequality makes resolving disputes
more difficult; see, for example, Bardhan (2005). More broadly, inequality affects the economics
of conflict, as it may intensify the grievances felt by certain groups or can reduce the
opportunity costs of initiating and joining a violent conflict (Lichbach 1989).
11. Inequality can lead to policies that hurt growth. In addition to affecting growth drivers,
inequality could result in poor public policy choices. For example, it can lead to a backlash against
growth-enhancing economic liberalization and fuel protectionist pressures against globalization and
market-oriented reforms (Claessens and Perotti 2007). At the same time, enhanced power by the
elite could result in a more limited provision of public goods that boost productivity and growth,
and which disproportionately benefit the poor (Putnam 2000; Bourguignon and Dessus 2009).
12. Inequality hampers poverty reduction. Income inequality affects the pace at which growth
enables poverty reduction (Ravallion 2004). Growth is less efficient in lowering poverty in countries
with high initial levels of inequality or in which the distributional pattern of growth favors the non-
poor. Moreover, to the extent that economies are periodically subject to shocks of various kinds that
undermine growth, higher inequality makes a greater proportion of the population vulnerable to
poverty.
III. STYLIZED FACTS: WHAT DO WE KNOW ABOUT
INEQUALITY OF OUTCOMES AND OPPORTUNITIES?
13. Measuring inequality. Income inequality—the most widely cited measure of inequality of
outcomes—is typically measured by the market (gross) and net (after tax and transfers from social
insurance programs) Gini, and by tracking changes in the income shares of the population (for
example, by decile/quintile). Information on the assets held by the wealthiest offers a
complementary perspective on monetary inequality. Inequality of opportunities is often measured
by tracking health, education and human development outcomes by income group, or by examining
access to basic services and opportunities. In this section, we document recent trends in both
monetary and nonmonetary indicators of inequality across a large sample of advanced and EMDCs.
Inequality of outcomes: Income
14. Global inequality remains high. Global inequality ranges from 0.55 to 0.70 depending on
the measure used (Figure 2). The high level of global inequality reflects sizeable per capita income
disparities across countries, which account for around three quarters of global inequality (Milanovic
2013). Some measures of global inequality exhibit a declining trend in the last few decades in
response to rising incomes for those living in China and India, where hundreds of millions of people
have been lifted out of poverty. However, other measures of global income inequality—adjusted for
CAUSES AND CONSEQUENCE OF INEQUALITY
10 INTERNATIONAL MONETARY FUND
top incomes which tend to be underreported in most household surveys—appear to be broadly
stable since the early 1990s.
Figure 2. Global Inequality and the Distribution of Income
Sources: Lakner and Milanovic (2013); Milanovic (2013); and IMF staff calculations.
Note: Unweighted inter-country inequality (blue line) is calculated across GDPs obtained from household surveys of all
countries in the world, without population-weighting. The population-weighted inter-country inequality (red line) takes into
account population weights. Finally, the global inequality concept (green dotted line) focuses on individuals, instead of
countries. The calculation is based on household surveys with data on individual incomes or consumption.
15. Globally, the middle class and the top 1 percent have experienced the largest gains.
Examining changes in real incomes between 1998 and 2008 at various percentiles of the global
income distribution, Lakner and Milanovic (2013) show that the largest gains acrued for the global
median income (50th percentile) earners and for the top 1 percent. This coincides with the rapid
growth of the middle class in many emerging market economies, and the concentration of top
earners in advanced economies, respectively. Moreover, income gains rapidly decrease after the
50th percentile and become stagnant around the 80th–90th global percentiles before shooting up
for the global top 1 percent (Krugman 2014). In what follows, we focus on recent trends in within-
country inequality which drives these global developments.
16. Widening income inequality within countries. Measures of inequality based on Gini
coefficients of gross and net incomes have increased substantially since 1990 in most of the
developed world (Figure 3). Inequality, on average, has remained stable in EMDCs, albeit at a much
higher level than observed in advanced economies. However, there are large disparities across
EMDCs, with Asia and Eastern Europe experiencing marked increases in inequality, and countries in
Latin America exhibiting notable declines (although the region remains the most unequal in the
world).
6
Redistribution, gauged by the difference between market and net inequality, played an
important, albeit partial, role in cushioning market income inequality in advanced economies. During
6
See Tsounta and Osueke (2014) and IMF (2014b) for a discussion of the declining inequality trends in Latin America
and Middle East and North Africa regions, respectively.
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
1950 1970 1990 2010
Gini coefficient
Global inequality
Population-weighted
inter-country inequality
Unweighted inter-
country inequality
Three concepts of inter-national income inequality
Distribution of income at different points in time, 1988-2008
INEQUALITY: CAUSES AND CONSEQUENCES
INTERNATIONAL MONETARY FUND 11
1990–2012, market inome inequality in advanced economies increased by an average of 5¼ Gini
points compared to a 3 Gini point increase in the net Gini coefficient.
Figure 3. Change in Net Gini Index, 1990–2012
Sources: Solt Database; and IMF staff calculations.
Note: LAC =Latin America and the Caribbean; MENA = Middle East and North Africa; and SSA = Sub-Saharan Africa.
1/ Change in net Gini from 1990 to 2012 is expressed as a percentage. For missing values, data for the most recent
year were used.
17. Income deciles under the microscope. Changes in income inequality across advanced
economies and EMDCs have been driven by different developments in income shares by deciles.
Figure 4 shows that rising income inequality (positive numbers on the vertical axes) in most
advanced and many emerging market economies has been driven primarily by the growing income
share of the top 10 percent (see also Piketty and Saez (2003) for the United States). Indeed, the top
10 percent now has an income close to nine times that of the bottom 10 percent. These effects have
been magnified by the crisis (OECD 2014). The story is somewhat different in EMDCs. Rising
inequality for this group of countries is primarily explained by a shift in incomes of the “upper
middle class to the upper class” (for example, in China and South Africa). Figure 4 shows that in
EMDCs with falling inequality (negative numbers on the vertical axis), the main beneficiaries (that is,
with the largest increase in their income shares, shown on the horizontal axis) were those at both
the bottom and the middle of the income distribution (for example, Peru and Brazil).
18. Top 1 percent on the rise. The top 1 percent now account for around 10 percent of total
income in advanced economies. (Figure 5; Piketty and Saez 2011; Alvadero and others, 2013). While
data on top income shares is scant for most EMDCs, available evidence suggests that the share of
top incomes has risen in China and India. The growing share of the top 1 percent in advanced
economies reflects both higher inequality in labor incomes as well as capital gains—returns from
investments (Atkinson, Piketty, and Saez 2011). Indeed, about half of the income of the top 1
percent constitutes non-labor income compared with 30 percent for the top 10 percent as a whole.
For instance, corporate profits have been translated into strikingly high executive salaries and
(-5.0) – (0)%
(0) – 5.0%
5 - 26%
% Change in Net Gini 1/
37.2
35.5 37.2
47.3
49.7
28.9
46.3
United States
United Kingdom
Germany
Brazil
India
China
Russia
(-36.0) – (-5.0)%
Not Enough Data
Current 2012
level of Gini (Net)
Asia (42.44)
Europe (30.63)
LAC (44.22)
MENA (42.22)
SSA (42.66)
CAUSES AND CONSEQUENCE OF INEQUALITY
12 INTERNATIONAL MONETARY FUND
bonuses, exacerbating income inequality (Brightman 2014), a pattern that is observed across both
advanced and large emerging market economies (Figure 6).
Figure 4. Change in Gross Gini and Income Decile
Sources: Milanovic WYD Database; Solt Database; and IMF staff calculations.
Note: The horizontal axis shows the income decile with the largest change in the income share between the latest and
earliest available data (typically 2010s versus 1980s). The vertical axis shows the change in the gross Gini for the
corresponding period. AEs = advanced economies; CIS = Commonwealth of Independent States; LAC = Latin America
and Caribbean; MENA = Middle East and North Africa; SSA = sub-Saharan Africa.
Europe Asia CIS LAC MENA SSA
CHN
IND
IDN
MYS
LKA
ALB
BIH
BGR
HUN
AZE
BLR
KAZ
TKM
UKR
ARG
BRA
CHL
COL
CRI
DOM
ECU
GTM
JAM
MEX
PAN
PER
URY
VEN
DZA
EGY
IRN
JOR
PAK
TUN
ZAF
-24
-16
-8
0
8
16
01234567891011
Change in Gross Gini
Income Decile
Emerging Markets
([1988-93] - [2005-08])
North America Other AEs Europe Asia
HKG
ISR
JPN
KOR
SGP
TWN
AUT
BEL
CYP
CZE
DNK
EST
FIN
FRA
DEU
GRC
IRL
ITA
LVA
LUX
NLD
NOR
PRT
SVK
SVN
ESP
SWE
CHE
GBR
CAN
USA
AUS
NZL
-4
-2
0
2
4
6
8
10
12
14
01234567891011
Change in Gross Gini
Income Decile
Advanced Economies
(1988-2008)
INEQUALITY: CAUSES AND CONSEQUENCES
INTERNATIONAL MONETARY FUND 13
Figure 5. Top 1% Income Share
(1980–2010)
Figure 6. Estimated Corporate Profits 1/
(Index)
Sources: World Top Incomes Database; and IMF staff
calculations.
Sources: Bloomberg, L.P.; and IMF staff calculations.
1/ Corporate profits are taken as a proxy for estimated
earnings.
Note: Emerging markets include Brazil, Chile, China, India,
Indonesia, Korea, Mexico, Philippines, Russia, South Africa,
Thailand, and Turkey.
19. Middle class squeeze. A shift in the allocation of labor income towards the higher and
lower ends of the distribution has resulted in a
shrinkage of the income share accruing to the
middle 20 percent in many advanced
economies (Australia, Canada, and Sweden are
important exceptions), and some large
emerging market economies (Autor, Katz, and
Kearney 2006; Figure 7). Indeed, pretax incomes
of middle-class households in the United States,
the United Kingdom, and Japan have
experienced declining or stagnant growth rates
in recent years. Additional pressures on the
middle class reflect a declining share of labor
income—the predominant source of income for
the majority of households. Indeed, average
wages have risen at a slower pace than
productivity growth amid large economic rents
(for example, high profitability and large increase in executive compensation) accruing to the top
end of the income distribution (Figure 8).
-5
0
5
10
15
20
US
UK
Germany
France
Sweden
Japan
India
South Africa
Indonesia
China
1980 change in 1980-1990
change in 1990-2000 change in 2000-2010
0
100
200
300
400
500
600
700
800
900
1000
2000 2002 2004 2006 2008 2010 2012
Advanced Economies
Emerging Markets
Figure 7. Change in Income Share, 1990–2009
(Average change, percent)
Sources: WDI database; and IMF staff calculations.
Note: Emerging markets include Argentina, Brazil, China,
India, Russia, and South Africa.
-2
-1
0
1
2
3
4
Advanced Economies Emerging Markets
Middle 20 percent Top 20 percent
CAUSES AND CONSEQUENCE OF INEQUALITY
14 INTERNATIONAL MONETARY FUND
20. Sources behind the middle class squeeze vary. In advanced economies, the largest driver
has been the declining share of middle-skilled occupations relative to low- and high-skilled
occupations (Autor, Kerr, and Kugler 2007; Goos, Manning, and Salomons 2009). In EMDCs, the
middle class squeeze in some countries reflects income polarization (Duclos, Esteban, and Ray 2004;
Zhang and Kanbur, 2011). In China, for example, more than one-third of all wealth is concentrated in
the top 1 percent, while the majority of the population remains poor despite strong economic
growth (Hairong 2014). Widespread informality and persistently large geographical differences in
economic performance have also played a particularly important role in shaping income inequality
in EMDCs.
21. Poverty has declined in many countries, but is on the rise in advanced economies. In
many EMDCs, poverty—measured in terms of the share of population living below a pre-defined
poverty line—has declined, despite rising income inequality in some (Figure 9). In contrast, recent
data suggest that poverty rose in advanced countries since the 1990s (OECD 2011). The ratio of the
Figure 8. Disconnect: Real Average Wage and Productivity
Sources: The Conference Board; International Labour Organization; and IMF staff calculations.
Note: Earnings reflect gross remuneration—in cash and in kind—paid to employees deflated by the consumer price index.
Labor productivity represents real output per hours worked.
90
100
110
120
130
2005 2012
Hungary
90
100
110
120
130
2005 2012
Mexico
90
100
110
120
130
2005 2012
Czech Republic
90
100
110
120
130
2005 2012
Slovak Republic
90
100
110
120
130
2005 2012
Korea
90
100
110
120
130
2005 2012
United States
90
100
110
120
130
2005 2012
United Kingdom
90
100
110
120
130
2005 2012
Germany
90
100
110
120
130
2005 2012
Japan
90
100
110
120
130
2005 2012
Italy
90
100
110
120
130
2005 2012
Netherlands
90
100
110
120
130
2005 2012
Spain
Labor Productivity Real Average Wage Index
Selected Advanced Economies
Selected Emerging Markets
INEQUALITY: CAUSES AND CONSEQUENCES
INTERNATIONAL MONETARY FUND 15
earnings of the 90th percentile to the earnings of the 10th percentile—another method of
measuring inequality among the bottom 90 percent—grew in most advanced economies over the
period between 1980 and 2011 (Autor 2014), particularly in the United States and the United
Kingdom.
Figure 9. Poverty Rates by Regions
Source: Tsounta and Osueke (2014).
Note: EM = Emerging market economies.
1/ National coverage of poverty headcount (percent of population living in households with consumption or income per
person below the poverty line of $76 per month or $2.5 per day).
Inequality of outcomes: Wealth
22. Rising concentration of global wealth. Estimates suggest that almost half of the world’s
wealth is now owned by just 1 percent of the population, amounting to $110 trillion—65 times the
total wealth of the bottom half of the world’s population (Fuentes Nieva and Galasso 2014).
7
For
instance, a third of the total wealth in the United States is held by 1 percent of the population
(Figure 10, left panel). In most countries with available data, the share held by the 1 percent
wealthiest population is rising at the expense of the bottom 90 percent population (Figure 10, right
panel).
7
Wealth or net worth is defined as the value of financial assets plus real assets (principally housing) owned by
households, less their debts.
Poverty rate
1
, 2010
(Percent of population)
Change in Poverty Rate (since 2000)
(Percent of population)
0 20406080
Sub-Sahara Africa
Latin America
EM Europe
EM Asia
Advanced Economies
-15 -10 -5 0 5
Sub-Sahara Africa
Latin America
EM Europe
EM Asia
Advanced Economies
Figure 10. Top 1% and Bottom 90% Wealth Distribution, 1980–2010
Sources: Piketty (2014); and IMF staff calculations.
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
France United
Kingdom
United
States
Sweden Europe
1980 2010
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
France United
Kingdom
United
States
Sweden Europe
1980 2010
Top 1 percent Bottom 90 percent
CAUSES AND CONSEQUENCE OF INEQUALITY
16 INTERNATIONAL MONETARY FUND
23. Inequality is more extreme in wealth
than income. In both advanced economies and
EMDCs, income Ginis, on average, are half the
size of wealth Ginis (Figure 11). Possible
explanations for the higher wealth Ginis include
stagnant wage growth, which makes it difficult
for middle- and lower-income workers to set
aside money for saving, and a lower propensity
to consume by the rich.
8
While many studies
suggest that growing wealth inequality in
advanced economies is largely driven by rising
wealth concentration at the top (Piketty 2014;
Saez 2014), various explanations have been
posited for the rise in EMDCs, ranging from
wealth polarization between urban and rural
areas in China to inequality among class and
caste in India (Zhong and others 2010; Credit
Suisse 2013).
Inequality of Opportunity: Health Services
24. Inequality in health outcomes is widespread in developing economies. While health
outcomes are broadly similar across income groups in advanced countries, large disparities exist in
EMDCs (Figure 12, left panel). For example, the infant mortality rate is twice as high in the poor than
in the rich households (in terms of wealth) in emerging market economies. Similarly, female
mortality rates tend to be disproportionately higher for lower-income groups.
25. Inequality in health care access and use is more pervasive in developing countries.
Commonly used indicators to gauge access and use of health care are generally favorable in
advanced countries, irrespective of the income level of the population. For EMDCs, however, data on
access to skilled health personnel for births suggest that there are large disparities in health access
across income levels within developing countries, and to a lesser extent in emerging market
countries (Figure 12, right panel). However, even in advanced economies, income inequality is
increasingly being reflected in lower life expectancy. This is particularly striking in the United States,
where income today is a stronger predictor of life expectancy than it was a generation ago (Murray,
Lopez, and Alvarado 2013).
8
Based on national balance sheets in nine advanced economies, Piketty and Zucman (2014) find that wealth-income
ratios have doubled over the past 40 years.
Figure 11. Wealth and Income Inequality in
Advanced and Emerging Market Economies,
2000
Sources: Davies and others (2008); Luxembourg Income
Study Database; Organisation for Economic Co-operation
and Development; Socio-Economic Database for Latin
America and the Caribbean; World Bank; and IMF staff
calculations.
Note: Emerging markets include China, India, Pakistan,
Thailand, Turkey, Argentina, Mexico, Indonesia, and Brazil.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Advanced Economies Emerging Markets
Wealth Gini Income Gini
INEQUALITY: CAUSES AND CONSEQUENCES
INTERNATIONAL MONETARY FUND 17
Figure 12. Inequalities in Health by Quintile, 2010–12
Sources: WHO, Global Health Observatory Data Repository; and IMF staff calculations.
Note: AEs = advanced economies; DCs = developing countries; EMs = emerging market economies.
1/ Numbers are median values of income groups based on the latest data available (2010–12).
2/ AEs only include data for Canada in 1996.
Inequality of opportunity: Education
26. Declining education inequality in EMDCs. The education Gini—a measure of the variation
of average years of education for different income levels—has declined significantly in EMDCs, over
the last 60 years (Figure 13, left panel). This is largely driven by improvements in access at the lower-
end of the income distribution (Castello-Climent and Domenech 2014). Despite this improvement,
education outcomes remain much worse for disadvantaged groups, partly because of pro-rich
biases in the incidence of public spending (Dabla-Norris and Gradstein 2004). Indeed, almost 60
percent of the poorest youth population (aged 20–24 years) in sub-Sahara Africa has fewer than 4
years of schooling compared to 15 percent in the richest quintile (Figure 13, right panel). In contrast,
education inequality, on average, is unchanged in most advanced economies over the last decade,
although rising university costs have contributed to lower access to education by the poor in some
countries. In the United States, for instance, college costs grew must faster than most households’
income since 2001 (Federal Reserve 2014).
Figure 13. Education Gini and Outcomes by Income Decile
Sources: Castelló-Climent and Doménech (2014); World Inequality Database on Education; and IMF staff calculations.
Note: EM = emerging market economies.
1/ Latest available data (2000–12).
0
10
20
30
40
50
60
70
Q1 (poorest) Q2 Q3 Q4 Q5 (richest)
EMs DCs AEs 2/
InfantMortality Rate per 1000 1/
0
10
20
30
40
50
60
70
80
90
100
Q1 (poorest) Q2 Q3 Q4 Q5 (richest)
EMs DCs
Births Attended by Skilled Health Personnel,
percent (median)
0
0.1
0.2
0.3
0.4
0.5
0.6
1950 1960 1970 1980 1990 2000 2010
Advanced Economies
Emerging Markets
Education Gini (percent)
0
10
20
30
40
50
60
Sub-Sahara
Africa
Arab States EM Asia Latin America
and
Caribbean
EM Europe
Poorest Quintile
Richest Quintile
Percentage of population (aged 20-24) with less than
four years of education 1/
CAUSES AND CONSEQUENCE OF INEQUALITY
18 INTERNATIONAL MONETARY FUND
Inequality of opportunities: Financial services
27. Disparities in financial services access. There are large disparities in the use of financial
services between advanced economies and EMDCs and across income levels within a country (Figure
14). More than 80 percent of adults in advanced economies have an account at a formal financial
institution—twice more than in EMDCs. Within EMDCs, the share of adults with an account or a loan
at a formal financial institution is largely skewed toward the top income earners. The rest rely on
their own limited savings to invest in education or become entrepreneurs, suggesting that financial
inequality and income inequality go hand in hand. In many EMDCs, low-income households and
small-scale firms often face challenges in accessing financial services due to lack of financial
knowledge, complicated processes, onerous paperwork, and other market failures. Moreover,
available financial products tend to be more limited and relatively costly.
Figure 14. Financial Inclusion in Advanced and Developing Countries
(Percent of total, 2011)
Sources: World Bank, Global Financial Inclusion Database; and IMF staff calculations.
Note: AEs = advanced economies; DCs = developing countries; EMs = emerging market economies.
IV. INEQUALITY DRIVERS
A. Factors Driving Higher Income Inequality
28. Global trends: the good side of the story. Over the past four decades, technology has
reduced the costs of transportation, improved automation, and communication dramatically. New
markets have opened, bringing growth opportunities in countries rich and poor alike, and hundreds
of millions of people have been lifted out of poverty. However, inequality has also risen, possibly
reflecting the fact that growth has been accompanied by skill-biased technological change, or
because other aspects of the growth process have generated higher inequality. In this section, we
discuss potential global and country-specific drivers of income inequality across countries.
29. Technological change. New information technology has led to improvements in
productivity and well-being by leaps and bounds, but has also played a central role in driving up the
0
20
40
60
80
100
DCs EMs AEs DCs EMs AEs
Bottom 40% income Top 60% income
Adults with an account at a
formal financial institution
0
2
4
6
8
10
12
14
16
18
DCs EMs AEs DCs EMs AEs
Bottom 40% income Top 60% income
Adults borrowed from a financial institution
in the past year
INEQUALITY: CAUSES AND CONSEQUENCES
INTERNATIONAL MONETARY FUND 19
skill premium, resulting in increased labor income inequality (Figure 15). This is because
technological changes can disproportionately raise the demand for capital and skilled labor over
low-skilled and unskilled labor by eliminating many jobs through automation or upgrading the skill
level required to attain or keep those jobs (Card and Dinardo 2002; Acemoglu 1998). Indeed,
technological advances have been found to have contributed the most to rising income inequality in
OECD countries, accounting for nearly a third of the widening gap between the 90th and the 10th
percentile earners over the last 25 years (OECD 2011). Evidence from larger emerging market
economies also shows a similar trend of a growing earnings gap between high- and low-skilled
workers despite a large rise in the supply of highly educated labor (which should reduce the gap).
30. Trade globalization: two sides of a coin. Trade has been an engine for growth in many
countries by promoting competitiveness and enhancing efficiency. Nonetheless, high trade and
financial flows between countries, partly enabled by technological advances, are commonly cited as
driving income inequality (Figure 16). In advanced economies, the ability of firms to adopt labor-
saving technologies and offshoring has been cited as an important driver of the decline in
manufacturing and rising skill premium (Feenstra and Hanson 1996, 1999, 2003). Trade openness
could potentially have mixed effects on the wages of unskilled labor in advanced countries. It raises
the skill premium, but could also increase real wages by lowering (import) prices (Munch and
Skaksen 2009). At the same time, increased trade flows could lower income inequality in EMDCs by
increasing demand and wages for abundant lower-skilled workers. Thus, disentangling the impact of
trade on inequality is challenging as it depends on relative factor abundance and productivity
differences across countries, and the extent to which individuals obtain income from wages or
capital.
Figure 15. Technological Progress and Skill Premium in OECD Countries
Source: Organisation of Economic Co-operation and Development.
1/ Skill premium measures the relative earnings from employment after completing tertiary education compared to the
earnings after completing upper- and post-secondary non-tertiary education.
0
200
400
600
800
1000
1200
1400
1600
1800
1990 1995 2000 2005
Australia
Euro (PPP weighted)
Korea
UK
USA
100
125
150
175
200
225
250
100
125
150
175
200
225
250
Australia
Belgium
Canada
Denmark
Finland
Germany
Hungary
Ireland
Italy
Korea
Spain
Sweden
UK
US
1997-2001
2002-2007
Use of Information and Communication Technology (ICT)
ICT capital services per hour worked, 1990 = 100
Skill Premium in Selected Economies 1/
Uppersecondary or post-secondary non-tertiary education = 100
CAUSES AND CONSEQUENCE OF INEQUALITY
20 INTERNATIONAL MONETARY FUND
31. Financial globalization. Financial globalization can facilitate efficient international
allocation of capital and promote international risk sharing. At the same time, increased financial
flows, particularly foreign direct investment (FDI) and portfolio flows have been shown to increase
income inequality in both advanced and emerging market economies (Freeman 2010). One potential
explanation is the concentration of foreign assets and liabilities in relatively higher skill- and
technology-intensive sectors, which pushes up the demand for and wages of higher skilled workers.
In addition, FDI could induce skill-specific technological change, be associated with skill-specific
wage bargaining, and result in more training for skilled than unskilled workers (Willem te Velde
2003). Moreover, low-skill, outward FDI from advanced economies may in effect be relatively high-
skilled, inward FDI in developing economies (Figini and Görg 2011), thus exacerbating the demand
for high-skilled workers in recipient countries. Financial deregulation and globalization have also
been cited as factors underlying the increase in financial wealth, relative skill intensity, and wages in
the finance industry, one of the fastest growing sectors in advanced economies (Phillipon and
Reshef 2012; Furceri and Loungani 2013).
32. Financial deepening. Financial deepening can provide households and firms with greater
access to resources to meet their financial needs, such as saving for retirement, investing in
education, capitalizing on business opportunities, and confronting shocks. Financial deepening
accompanied by more inclusive financial systems can thus lower income inequality, while improving
the allocation of resources (Dabla-Norris and others 2015). Theory, however, suggests that financial
development could benefit the rich in the early stages of development, but the benefits become
more broadly shared as economies develop (Greenwood and Jovanovic 1990). Indeed, some studies
have found that financial development, measured as the relative share of the banking and stock
market sectors in the economy, boosts top incomes the most in the early stages of development
(Roine, Vlachos, and Waldenström 2009). Moreover, inequality can increase as those with higher
incomes and assets have a disproportionately larger share of access to finance, serving to further
increase the skill premium, and potentially the return to capital (Claessens and Perotti 2007).
Figure 16. Trade and Financial Openness
(Percent of GDP)
Sources: IMF, International Financial Statistics; IMF, World Economic Outlook database; and IMF staff calculations.
1/ Trade openness is measured by total imports and exports as a percentage of GDP.
2/ Financial openness is measured by total assets and liabilities as a percentage of GDP.
0
10
20
30
40
50
60
70
80
90
1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Trade Openness 1/
Advanced Economies
Emerging Markets
Developing Economies
0
20
40
60
80
100
120
140
160
180
0
50
100
150
200
250
300
350
400
450
500
1970 1975 1980 1985 1990 1995 2000 2005 2010
Financial Openness 2/
Advanced Economies (LHS)
Emerging Markets (LHS)
Developing Economies (RHS)
INEQUALITY: CAUSES AND CONSEQUENCES
INTERNATIONAL MONETARY FUND 21
33. Changes in labor market institutions.
More flexible labor market institutions can foster
economic dynamism by reallocating resources to
more productive firms and enabling firm
restructuring. However, greater flexibility can
pose challenges for workers, especially those
with low skills, and hence play an important role
in explaining inequality developments (Alvadero
and others 2013). A decline in trade union
membership (union rate) could reduce the
relative bargaining power of labor, exacerbating
wage inequality (Frederiksen and Poulsen 2010;
Wilkinson and Pickett 2010; Figure 17).
9
Jaumotte
and Osorio-Buitron (2015) and forthcoming IMF
work finds that a reduction in the minimum wage
relative to the median wage is associated with higher inequality in advanced economies, while a
decline in unionization rate is strongly associated with the rise of top income shares. Moreover,
some studies have pointed to the role of wage dispersion and a higher share of part-time and
temporary employment in driving inequality in labor earnings in some advanced economies (OECD
2012). For many labor market policies, such as reforms to employment protection legislation, the
impact on inequality is less clear cut as they affect both the dispersion of earnings and the level of
employment in sometimes conflicting ways.
10
In many EMDCs, the combination of rigid hiring and
firing and employment protection regulations and weak income protection systems often
encourages informality, fueling wage inequality. However, evidence from a large sample of countries
suggests that de facto labor market regulations (such as minimum wages, unionization, and social
security contributions), on average, tend to improve the income distribution (Calderón and Chong
2009; OECD 2011).
34. Redistributive policies. Governments in advanced economies have historically mitigated
inequality through public policy—primarily progressive taxes and social transfers such as public
retirement benefits (CBO 2011). However, many advanced countries have now seen an increase in
net income inequality, indicating gaps in existing tax-and-transfer systems to counteract rising
market inequality. The progressivity of tax systems has declined in some advanced economies over
the past few decades, with the result being that high-income households and corporations now face
9
There is a difference between coverage rate of collective bargaining agreement and union density because in many
advanced economies multi-employer bargaining and public policies extending the negotiated contract to
nonorganized firms guarantee coverage rates in excess of density rates.
10
Stronger labor market institutions could increase unemployment rates, reduce the wage differential between high-
skill and low-skill workers, and affect the labor share of income. The overall impact on income inequality, however,
can be ambiguous: they increase unemployment, which tends to raise inequality, they can reduce wage dispersion,
which tends to lower it, and they increase the wage share, which can have an ambiguous effect on inequality.
Figure 17. Union Rate by Country Group
(Percent)
Sources: Organisation of Economic Co-operation and
Development; and IMF staff calculations.
0
10
20
30
40
50
60
70
80
90
Max Min Median
1990
1990
1990
1990
1990
2012 2012 2012 2012
2012
North
America
Nordic
Countries
Europe
East Asia
Pacific
Emerging
Markets
CAUSES AND CONSEQUENCE OF INEQUALITY
22 INTERNATIONAL MONETARY FUND
lower effective tax rates (Hungerford 2013).
11
Indeed, Figure 18 indicates that rising pre-tax
income concentration at the top of the
distribution in many advanced economies has
also coincided with declining top marginal tax
rates (from 59 percent in 1980 to 30 percent
in 2009). Conditional cash transfers have
become an important policy tool for directing
resources towards the lower end of the
distribution in EMDCs (IMF 2014a), but their
redistributive impact varies widely across
countries, reflecting both differences in the
size and progressivity of these transfers.
35. Education. Education can play an
important role in reducing income inequality,
as it determines occupational choice, access
to jobs, and the level of pay, and plays a
pivotal role as a signal of ability and productivity in the job market. From a theoretical perspective,
the human capital model of income distribution (Mincer, 1958; Becker and Chiswick, 1966) suggests
that while there is an unambiguously positive association between educational and income
inequality, the effect of increased educational attainment on income inequality could be either
positive or negative depending on the evolution of rates of return to education (that is, the skill
premium). Moreover, there can be opposing forces at play stemming from “composition” (that is,
increasing the share of high-wage earners) and “wage compression” (that is, decline in the returns to
higher education relative to lower levels) effects.
Overall, the evidence suggests that the inequality
impact of education depends on various factors, such as the size of education investments by
individuals and governments and the rate of return on these investments. It is in this spirit that Rajan
(2015) notes that “prosperity seems increasingly unreachable for many, because a good education,
which seems to be today’s passport to riches, is unaffordable for many in the middle class.”
B. Empirical Analysis
36. This section investigates the drivers of income inequality.
12
The discussion above
suggests that a variety of inter-related factors can impact inequality and have potentially differential
effects across countries and income groups. In
this section, using a simple panel econometric
11
Tax regimes can influence the mix of compensation, tilting it towards lower taxed forms of compensation, and
thereby boost disposable income, particularly at the top. For example, capital gains are often taxed at a lower rate
than other income and, in a few countries, they are not taxed at all. Stock options also benefit from preferential tax
treatment in many advanced economies.
12
We are unable to also investigate the drivers of wealth inequality due to data unavailability for a broad sample of
advanced economies and EMDCs.
Figure 18. Change in Top Tax Rate and Top 1
Percent Income Share
(1960–04 to 2005–09)
Sources: World Top Incomes Database; and IMF staff
calculations.
-4
-2
0
2
4
6
8
10
-50 -40 -30 -20 -10 0 10
Change in Top 1% Income Share (points)
Change in Top Marginal Tax Rate (points)
INEQUALITY: CAUSES AND CONSEQUENCES
INTERNATIONAL MONETARY FUND 23
approach with year and country fixed effects, we investigate the drivers of within country changes in
income inequality for a sample of almost 100 advanced economies and EMDCs over the period
1980–2012 (see Box 1 for empirical specification). In contrast to other studies, we focus on a large
group of countries to assess whether the determinants of inequality vary across advanced, emerging
markets and developing economies, and across different measures of inequality. In addition to the
Gini coefficients of both market and net inequality, we build on our earlier result that the income
distribution itself matters for growth by examining the determinants of the disposable income
shares (after tax) of the poor (bottom 10 percent), the middle-class (fifth decile), and the rich (top 10
percent). This allows us to focus on the factors driving income concentration in recent years,
especially changes in the income shares of the poor and the middle class.
37. Drivers of gross and net inequality. Table 2 (Columns 1 and 2) presents the results of the
regression analysis for gross and net inequality. Our results on the role of globalization and
technological progress in driving inequality are broadly in line with the findings in the literature. In
particular, trade openness is associated with lower inequality (albeit not in a statistically significant
way), while greater financial openness and technological progress are associated with rising income
inequality, likely reflecting the fact these disproportionately benefit high-tech and labor-skilled
sectors. Indeed, we find that financial globalization and technological progress are associated with an
increase in the top 10 percent disposable income share across all countries (Column 3).
38. Differential impacts of financial deepening across country groups. The impact of
financial deepening, as proxied by the ratio of private credit to GDP, on both market and net
inequality varies across advanced economies and EMDCs, in line with Roine, Vlachos, and
Waldenström 2009. In particular, our results
suggest that financial deepening is associated
with higher income inequality in EMDCs. This
likely reflects the fact that while financial
deepening has accelerated over the past two
decades, the record on financial inclusion
may not have kept apace in these countries.
Indeed, Figure 19 indicates that financial
deepening was associated with higher market
and net income inequality in countries with
low levels of financial inclusion (typically
EMDCs), possibly reflecting that large
amounts of credit are often concentrated
among the largest firms and wealthier
households. By contrast, financial deepening
is associated with less of an increase in
market inequality (and lower net inequality)
in advanced economies, reflecting easier
access to credit for households and firms.
Figure 19. Impact of Change in Financial
Deepening on Inequality
(Average in percentage points, 1990s–2011)
Source: World Bank, Global Financial Inclusion Database; World
Bank, World Development Indicators; and IMF staff
calculations.
Note: High (low) inclusion refers to countries above (below)
the median value of the sample in terms of the proportion of
the population with an account at a formal financial institution.
-0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
Market Gini Net Gini Top 10% Income
Share
High inclusion countries
Low inclusion countries
CAUSES AND CONSEQUENCE OF INEQUALITY
24 INTERNATIONAL MONETARY FUND
∗
∗
Box 1. Assessing the Drivers of Income Inequality Around the World
Our empirical approach is based on a simple model of within-country variation in inequality, controlling
for differences in levels across countries using five-year panels over the period 1980–2012. Specifically,
the analysis builds on Jaumotte, Lall, and Papageorgiou (2013) and is based on the following
specification:
in which
refers to the relevant inequality measure used for country i at time t, trade proxies
for trade globalization, measured as the sum of exports and imports as a share of a country’s GDP,
financial captures financial globalization, measured as the sum of foreign assets and liabilities relative to
GDP, and technology measures the share of information and communication technology (ICT) capital in
the total capital stock. Credit captures domestic financial market development, and is proxied by the ratio
of private credit to GDP. Since the effect of financial development could vary across advanced economies
and EMDCs, we also include an interaction term between the credit variable and a dummy variable which
takes the value of 1 for advanced economies, and zero otherwise. Given data limitations, and in line with
Mincer’s (1958) wage specification, we use the average years of education in the population aged 15 and
older as a proxy for the skill premium. As noted in the literature, the effect of skill-biased technological
change could vary across advanced economies and EMDCs. To capture this, we also include an
interaction term between the skill premium variable and a dummy variable that takes the value of 1 for
advanced economies, and zero otherwise. We also include a measure of labor market flexibility from the
World Economic Forum that measures the extent by which regulations govern firing and hiring, collective
bargaining, and minimum wages.
Additional control variables attempt to capture aspects of inequality of opportunities, including the
beginning of period education Gini (a proxy for access to education);
the quality and availability of health
system is measured by the beginning of period female mortality (aged 15–60) rate. Given data limitations,
as a proxy for redistributive policies, we include the beginning of period Fraser Institute index that
measures total government spending as a share of GDP (see also Perotti [1992]).
,
The terms
and
represent a full set of time and country dummies, respectively, and ε
it
captures all the omitted factors.
Country fixed effects allow us to focus on within-country changes instead of cross-country level
differences. In addition, time dummies are included to capture the impact of common global shocks such
as business cycles or growth spurts. All specifications include lagged GDP growth and share of
employment in agriculture and industry as additional controls. Lagged GDP growth is included in the
specifications as there could be a two way causality between output growth and inequality.
While causality is difficult to establish with full confidence, the results survive a variety of robustness
checks for omitted variables, endogeneity problems, and estimation methods and are broadly in line with
findings from the literature that focus on smaller country samples. For example, we checked the
robustness of our results by including dummies for financial crises, GDP per capita, and alternative
measures of the skill premium, trade, and financial openness. For some Organisation for Economic Co-
operation and Development (OECD) countries with available tax and benefits data, we also considered
alternative measures for redistributive policies as well as top marginal personal income-tax rates. The
results, not reported here but available upon request, suggest that lower marginal tax rates are
associated with higher market and net inequality and a higher income share of the top 10 percent.
INEQUALITY: CAUSES AND CONSEQUENCES
INTERNATIONAL MONETARY FUND 25
39. Higher skill premium is associated with widening inequality in advanced economies. In
advanced economies, increases in the skill premium exacerbate market income inequality, reflecting
the fact that education gains accrue disproportionately at the higher end of the income
distribution.
13
The statistically insignificant effect of the skill premium in driving net income
inequality, however, could reflect the fact that the net Gini is underestimating increases in inequality
at the top of the distribution (Kakwani 1980). Indeed, an increase in the skill premium is associated
13
Our specification uses the average years of education in the population as a proxy for skills; see also Card and
DiNardo (2000), essentially implying that the skill premium is determined solely by the supply of skills. Similar results
were obtained using alternative measures, such the ratio of earnings from employment after completing tertiary
education compared to the earnings after completing upper- and post-secondary education for a smaller sample of
OECD countries (available upon request).
Table 2. Regression Results of Inequality Drivers
Sources: Fraser Institute; IMF, World Economic Outlook; Solt Database; UNU-WIDER World Income Inequality
Database; World Bank; World Economic Forum; and IMF staff calculations.
Note: Standard errors in parentheses, *p < 0.1; **p < 0.05; and ***p < 0.01. Estimated using fixed-effects panel
regressions with robust standard errors clustered at the country level. Additional controls include lagged GDP
growth and share of employment in agriculture and industry. Income shares represent disposable (after tax)
incomes or consumption based on household data. AEs = advanced economies.
Variables
Market Gini
(1)
Net Gini
(2)
Top 10%
(3)
5th Income Decile
(4)
Bottom 10%
(5)
Trade openness -0.025 -0.008 -0.011 0.002 0.005
(0.017) (0.014) (0.014) (0.003) (0.005)
Financial openness 0.098*** 0.047** 0.026** -0.002 -0.008*
(0.016) (0.019) (0.011) (0.002) (0.004)
Technology 56.85* 15.03 31.11* -3.775 -11.51***
(31.01) (30.01) (15.81) (3.572) (3.587)
Financial deepening 0.050** 0.026** 0.022*** -0.004 -0.002
(0.021) (0.011) (0.007) (0.001) (0.002)
AEs * Financial deepening -0.049** -0.033** -0.03*** 0.007*** 0.004*
(0.021) (0.014) (0.008) (0.002) (0.002)
Skill Premium -0.413 -1.351 -0.475 0.063 -0.083
(0.726) (0.859) (0.670) (0.110) (0.139)
AEs * Skill Premium 1.165** 0.555 1.184*** -0.131** 0.024
(0.521) (0.556) (0.346) (0.064) (0.057)
Education Gini 6.085 -3.245 12.52 -1.906 -3.370*
(10.94) (11.39) (8.104) (1.364) (1.721)
Labor Market Institutions 0.803*** 0.497 0.338* -0.045 -0.140**
(0.291) (0.320) (0.195) (0.036) (0.063)
Female Mortality 0.021** 0.015* 0.026 -0.005*** 0.001
(0.009) (0.009) (0.032) (0.002) (0.002)
Government Spending -0.26 -0.426*** -0.349*** 0.046*** 0.0332
(0.162) (0.145) (0.103) (0.017) (0.023)
Country Fixed Effects Yes Yes Yes Yes Yes
Time Dummies Yes Yes Yes Yes Yes
#. of Observations 361 361 220 220 220
#. of countries 97 97 67 67 67
Adjusted R-squared 0.386 0.246 0.491 0.412 0.225
CAUSES AND CONSEQUENCE OF INEQUALITY
26 INTERNATIONAL MONETARY FUND
with a significantly higher disposable income share of the top 10 percent. This effect is found to be
statistically insignificant in EMDCs, and is in line with studies that find an absence of a correlation
between income differentials and the quantity of skills in these countries, likely reflecting large
differences in factor endowments and capacity to absorb new technologies across EMDCs (Behar
2013).
40. Easing of labor market regulations is associated with higher market inequality and
income share of the top 10 percent. In particular, a decline in organized labor institutions and the
resultant easing of labor markets measured by an increase in labor market flexibilities index by 8½
percent—from the median to 60
th
percentile—is associated with rising market inequality by 1.1
percent. The relationship between the top 10
th
percentile income share and easing of labor market
regulations is also positive and statistically significant (Column 3) for our sample of countries, likely
reflecting the fact that labor market flexibility benefits the rich and reduces the bargaining power of
lower-income workers. This result confirms Jaumotte and Osorio-Buitron (2015) and forthcoming
IMF work which find that weakening of unions is associated with a higher top 10 percent income
share for a smaller sample of advanced economies.
14
Indeed, empirical estimations using more
detailed data for OECD countries (not reported here, but available upon request) suggest that, in
line with Jaumotte and Osorio-Buitron (2015) and forthcoming IMF work, more lax hiring and firing
regulations, lower minimum wages relative to the median wage, and less prevalent collective
bargaining and trade unions are associated with higher market inequality. The impact of labor
market institutions on inequality, however, is somewhat blunted by government actions as shown by
the statistically insignificant coefficient in the net Gini regression (Table 2, Column 2).
41. Government actions can contribute to greater equality. In particular, we find that an
increase in our proxy for government redistributive spending relative to total spending by 7.1
percent (that is, a shift from the median value to the 60
th
percentile) is associated with a 0.6 percent
decrease in income inequality. While total government spending can be a poor proxy for the
progressivity of tax-transfer systems, this result continues to hold for other measures of
redistribution for a smaller sample of OECD countries (not reported here, but available upon
request), suggesting that the composition of government spending is important for reducing
inequality.
15
Moreover, healthier societies, as proxied by a lower female mortality rate, tend to have
lower income inequality. While causality is difficult to establish, the latter finding suggests that
greater and more equal access to quality health services allows people to be more productive, thus
lowering income disparities.
42. Overall contributors to changes in inequality. Based on the estimated models, the
contributions of the various factors to the change in the market Gini coefficient can be calculated.
16
14
This finding is also in line with recent research that finds that wage inequality falls during periods when union
density is increasing and rises when union membership is in decline (World Bank 2013).
15
Joumard, Pisu, and Bloch (2012) look at the role of taxes and transfers while OECD (2012b) looks at how education
policies, progressive taxes and transfers can tackle inequality.
16
These estimates are calculated as the average annual change in the respective variable multiplied by the
corresponding coefficient estimate in Table 2, Column 1.
INEQUALITY: CAUSES AND CONSEQUENCES
INTERNATIONAL MONETARY FUND 27
We find that less-regulated labor markets, financial deepening, and technological progress largely
explain the rise in market income inequality in our full sample over the last 30 years (Figure 20).
Globalization (that is, financial openness) has played a smaller but reinforcing role, while
improvements in health outcomes mitigated around ½ percent of the almost 3 percentage points
average increase in the Gini coefficient. The relative importance of the skill premium, globalization,
technological progress, and financial deepening in driving inequality, however, varies across
advanced economies and EMDCs.
43. What has been driving income shares of the poor and the middle class? Given the
importance of the poor (bottom 10 percent) and the middle class for boosting growth, we
investigate what explains changes in the income shares for these income groups across different
countries. On average, the income shares of the poor and the middle class have risen much more
slowly than that of the top 10 percent, which explains the rising income inequality observed in many
countries. Looking more closely into the determinants (Table 2, Columns 4 and 5, and Figure 21), we
find:
Better access to education (as captured by declining educational inequality), improved health
outcomes, and redistributive social polices help raise the income share of the poor and the
middle class irrespective of the level of economic development of a country.
17
By contrast,
easing of labor market regulations and technological progress dampen the income share of the
poor and the middle class, consistent with other studies. This result is not surprising, since the
poor are often disproportionally employed in lower-paying and less secure jobs (often in the
informal sector) and tend to benefit more from labor market regulations such as minimum
wages and firing restrictions. This points to the policy role of making education more accessible
(Bruckner, Dabla-Norris, and Gradstein 2015), while ensuring that changes in labor market
institutions do not excessively penalize lower-income individuals. Moreover, to the extent that
17
In a recent speech, Rajan (2015) refers to economic inclusion—easing access to quality education, nutrition, health
care, finance, and markets to all our citizens, as a “necessity for sustainable growth,” in addition to “obviously, a
moral imperative.”
Figure 20. Decomposition of the Change in Market (Gross) Income Inequality
(Gini points, current versus mid-1980s)
Source: IMF staff calculations.
Note: EMDCs = emerging market and developing countries.
-10123
Better Health Outcomes
Globalization
Techn ology
Financial Deepening
Labor Market flexibility
Change in Market Gini
-20246
Better Health Outcomes
Financial Deepening
Technology
Globalization
Labor Market flexibility
Skill premium
Change in Market Gini
-10123
Better Health Outcomes
Globalization
Financial Deepening
Techn ology
Labor Market flexibility
Change in Market Gini
All countries Advanced economies EMDCs
CAUSES AND CONSEQUENCE OF INEQUALITY
28 INTERNATIONAL MONETARY FUND
redistributive policies can play a role in reducing inequality, they can be supported by making
the tax systems more efficient and progressive and improving targeted spending.
There are important differences in inequality drivers between advanced economies and EMDCs,
suggesting the need to tailor policies to country-specific conditions. In particular, we find that
financial deepening has played a role in raising the income shares of the poor and the middle
class in advanced economies, but not in EMDCs, likely reflecting differences in credit allocation
and the extent of financial inclusion. In contrast, reducing gaps in access to education has been
one of the most important drivers of higher income shares for the bottom 10 percent and the
middle class in EMDCs. A complementary way to look at the income share of the poor is to
examine the drivers of the interplay between inequality and the poverty rate—defined as the
population living below $2 a day (Box 2). Our findings suggest that greater equality in access to
education lifts the poverty elasticity of economic growth.
Financial globalization and a higher skill premium have accounted for a more significant share of
the widening income gap between the top 10 percent and the poor and the middle class in
advanced economies than in developing countries. Policies to raise skills and reforms to increase
human capital are thus important for improving living standards and reducing labor income
inequality in advanced economies. In contrast to conventional wisdom, our results suggest that
globalization has played a less significant role in driving down income shares of the bottom 10
percent and the middle class in EMDCs (see also Box 2), suggesting that the benefits of
globalization discussed earlier potentially outweigh the costs in some of these countries.
Figure 21. Change in Income Share of the Bottom 10 Percent and
Middle Decile
(Gini points, current to mid-1980s)
Source: IMF staff calculations.
Note: EMDCs = emerging market and developing countires; Globalization = financial globalization.
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Labor market
flexibility
Social
policies
Globalization Financial
deepening
Better health
outcomes
Skill premium Technology Access to
education
All countries Advanced Economies EMDCs
INEQUALITY: CAUSES AND CONSEQUENCES
INTERNATIONAL MONETARY FUND 29
Box 2. Drivers of Poverty
Another way to look at the income shares of the poor is to examine the drivers of poverty rate—defined as the
population living below $2 a day (PPP-adjusted)—and look at the interplay between poverty and inequality.
The literature points to various sources for poverty reduction, including higher economic growth (Kraay 2006)
and a rise in the income share of the poor (Ravallion 2004). A large strand of the literature also explores how
inequality affects poverty reduction via its growth impact; see for example, Bourguignon (2003) and Fosu
(2010).
Using a sample of almost 100 EMDCs for the period 1985–2010, we investigate what is behind the declining
share of people living below the $2 a day poverty line over the last 30 years. Following Bourguignon (2003), we
first investigate the importance of inequality and growth on poverty reduction. Our results suggest that while
the impact of the change in inequality, as measured by the Gini, does not appear to be significant per se,
higher initial inequality lowers the growth elasticity of poverty reduction (Table 3, Column 1). Moreover, a
higher initial level of education inequality dampens the growth elasticity of poverty, while a higher
employment growth in manufacturing, as seen in emerging market economies in Asia for instance, is
associated with a lower share of the population living below the poverty line (Column 2). We also find that
greater trade openness can amplify the growth elasticity of poverty, albeit not in a statistically significant way,
while financial openness amplifies it in a significant way (Column 3).
Table 3. Regression Results on Determinants of Poverty Change
Sources: Solt Database; UNU-WIDER World Income Inequality Database; World Bank; World Economic
Outlook; and IMF staff calculations.
Note: Heteroskedasticity-consistent standard errors in parentheses, *p < 0.1; **p < 0.05; ***p < 0.01.
Prepared by Veronique Salins
Variables (1) (2) (3)
GDP per capita growth -0.278*** -0.323*** -0.256***
0.094 0.086 0.086
Initial Gini * GDP Per Capita Growth 0.005** 0.003 0.005**
0.002 0.002 0.002
Change in Gini 0.296
(0.356)
Initial Education Gini * GDP Per Capita Growth 0.609**
(0.230)
Employment in the Industrial Sector Growth -4.096***
(0.926)
Change in Trade Openness 1.009
(1.153)
Change in Trade Openness * GDP Per Capita Growth -0.151
(0.107)
Change in Financial Openness 0.509
(0.640)
Change in Financial Openness * GDP Per Capita Growth -0.515***
(0.122)
Constant 0.122 0.100 0.110
(0.155) (0.153) (0.189)
#. of Observations 282 180 272
R-squrared 0.422 0.403 0.526
Adjusted R-squared 0.405 0.371 0.506
Population Share Living Below $2/day
(percentage change)
CAUSES AND CONSEQUENCE OF INEQUALITY
30 INTERNATIONAL MONETARY FUND
44. Caveats. We should of course be cautious about drawing definitive policy implications from
cross-country regression analysis, as different policies are likely to have varying effects across
countries and at different points in time
. Measurement limitations in comparing inequality across
time and countries also need to be considered. In addition, it is hard to go from the sorts of
correlations presented in the note to firm statements about causality as there can be a two-way
causality running from growth-to-income inequality. Indeed, in-depth country-specific analyses
suggest that a number of inter-related factors drive growth, the income level, and income inequality
.
Despite these limitations, our analysis points to a policy role for tackling inequality.
V. POLICY DISCUSSION AND FINAL REMARKS
45. No one-size-fits-all. Policymakers around the world need to consider policies to tackle
inequality. Raising the income share of the poor, and ensuring that there is no hollowing-out of the
middle class is actually good for growth. Our empirical analysis also suggests that the drivers of
inequality and their impact differ across countries for different income groups. As such, the nature of
appropriate policies would necessarily vary across countries, and would also need to take into
account country-specific policy and institutional settings, and capacity/implementation constraints.
Recent work by the World Bank (2015) also highlights the importance of adopting a psychological
and social perspective on policymaking that takes into account what policy is implemented and
how.
46. Squaring equity and efficiency concerns. Lowering income inequality does not need to
come at the cost of lower efficiency. Previous IMF work has shown that there does not need to be a
stark efficiency-equity tradeoff (Ostry, Berg, and Tsangarides 2014). Redistribution through the tax
and transfer system is found to be positively related to growth for most countries, and is negatively
related to growth only for the most strongly redistributive countries. This suggests that the effect of
redistribution on enhanced opportunities for lower-income households and on social and political
stability could potentially outweigh any negative effects on growth through a damping of incentives.
47. Fiscal policy can be an important tool for reducing inequality. Fiscal policy plays a
critical role in ensuring macrofinancial stability and can thus help avert/minimize crises that
disproportionately hurt the disadvantaged population. At the same time, fiscal redistribution, carried
out in a manner that is consistent with other macroeconomic objectives, can help raise the income
share of the poor and middle class, and thus support growth. Fiscal policy already plays a significant
role in addressing income inequality in many advanced economies, but the redistributive role of
fiscal policy could be reinforced by greater reliance on wealth and property taxes, more progressive
income taxation, removing opportunities for tax avoidance and evasion, better targeting of social
benefits while also minimizing efficiency costs, in terms of incentives to work and save (IMF 2014a).
In addition, reducing tax expenditures that benefit high-income groups most and removing tax
relief—such as reduced taxation of capital gains, stock options, and carried interest—would increase
equity and allow a growth-enhancing cut in marginal labor income tax rates in some countries. In
EMDCs, better access to education and health services, well-targeted conditional cash transfers and
more efficient safety nets can have a positive impact on disposable incomes of the poor (Bastagli,
Coady and Gupta 2012). In many cases, this increasing public spending would need to be
INEQUALITY: CAUSES AND CONSEQUENCES
INTERNATIONAL MONETARY FUND 31
undertaken in tandem with rising revenue mobilization, reduced tax loopholes, and tax evasion, and
lower less- well-targeted spending (such as oil subsidies).
48. Education policies are key. In a world in which technological change is increasing
productivity and simultaneously mechanizing jobs, raising skill levels is critical for reducing the
dispersion of earnings. Improving education quality, eliminating financial barriers to higher
education, and providing support for apprenticeship programs are all key to boosting skill levels in
both tradable and nontradable sectors. These policies can also help improve the income prospects
of future generations as educated individuals are better able to cope with technological and other
changes that directly influence productivity levels. In advanced economies, with an already high
share of secondary or tertiary graduates among the working-age population, policies that improve
the quality of upper secondary or tertiary education would be important. In developing countries
with currently low levels of education attainment, policies that promote more equal access to basic
education (for example, cash transfers aimed at encouraging better attendance at primary schools,
or spending on public education that benefits the poor) could help reduce inequality by facilitating
the accumulation of human capital, and making educational opportunities less dependent on socio-
economic circumstances.
49. Fostering financial inclusion safely. Financial deepening in EMDCs needs to be
accompanied by greater inclusion to make a dent in inequality. Governments have a central role to
play in alleviating impediments to financial inclusion by creating the associated legal and regulatory
framework (for example, protecting creditor rights, regulating business conduct, and overseeing
recourse mechanisms to protect consumers), supporting the information environment (for example,
setting standards for disclosure and transparency and promoting credit information-sharing systems
and collateral registries), and educating and protecting consumers. Country experiences also
suggest that policies such as granting exemptions from onerous documentation requirements,
requiring banks to offer basic accounts, and allowing correspondent banking are useful in fostering
inclusion. The promotion of credit without sufficient regard for financial stability, however, can result
in crises, as evidenced by the subprime mortgage crisis in the United States, with disproportionately
adverse effects on the poor and the middle class. Moreover, it illustrates the broader point that deep
social issues cannot be resolved purely with an infusion of credit. Policies thus need to strike a
balance between fostering prudence stability, and inclusion, while encouraging innovation and
creativity.
50. Well-designed labor market policies and institutions can reduce inequality
, and, at the
same time, not be a drag on efficiency. Policies that reduce labor market imperfections and
institutional failures that affect job creation can help support poor and middle-income workers. For
instance, appropriately set minimum wages, spending on well-designed active labor market policies
aimed at supporting job search and skill matching can be important. Better use of in-work benefits
for social benefit recipients also help reduce income disparities. Moreover, policies that reduce labor
market dualism, such as gaps in employment protection between permanent and temporary
workers—especially young workers and immigrants—can help to reduce inequality, while fostering
greater market flexibility. More generally, labor market policies should attempt to avoid either
excessive regulations or extreme disregard for labor conditions. Labor market rules that are very
CAUSES AND CONSEQUENCE OF INEQUALITY
32 INTERNATIONAL MONETARY FUND
weak or programs that are nonexistent can leave problems of poor information, unequal power, and
inadequate risk management untreated, penalizing the poor and the middle class (World Bank
2012). In contrast, excessively stringent regulations can compound market imperfections with
institutional failures, and weigh on job creation and efficiency.
51. In EMDCs, making labor markets more inclusive and creating incentives for lowering
informality is a key challenge. Workers in these countries often lack equal access to productive job
opportunities and do not benefit evenly from economic growth. Many individuals with low skills, in
particular, remain trapped in precarious jobs, often in the informal and unregulated economy. In
such jobs, even full-time employment tends to be insufficient to lift households out of poverty. Thus,
creating accessible, productive, and rewarding jobs is key to escaping poverty and reducing
inequality. Informal workers need to have the necessary legal, financial, and educational means to
access formal sector employment. Higher formal sector employment also requires better incentives
for firms to become formal. Policies to reduce tax, financial, and regulatory constraints can expand
formal sectoral employment by reducing the incentives for firms to operate informally, both by
increasing the benefits of participating in the formal sector and by reducing the costs of doing so
(Dabla-Norris and Inchauste 2008).
52. Complementarities between growth and income equality objectives. Reforms aimed at
raising average living standards can also influence the distribution of income. Indeed, tackling
inequality goes beyond the remit of labor, social welfare, financial inclusion, and tax policies. The key
to minimizing the downside of both globalization and technological change in advanced economies
is a policy agenda of a race to the top, instead of a race to the bottom—an agenda that includes
policies to encourage innovation, reduce burdensome product market regulations that stifle
competition and technology diffusion, move goods produced upwards in the value chain, and
ensure that this rise benefits everyone. In developing countries, raising agricultural productivity,
rapid accumulation of capital, and technology diffusion in labor-intensive sectors can substantially
lift growth and ensure that the fruits of prosperity are more broadly shared (Dabla-Norris and others
2013). Sustaining growth in emerging market economies will require more intensive patterns of
growth, greater flexibility to shift resources within and across sectors, and the capacity to apply
more knowledge and skill-intensive production techniques. Policies to improve skills for all, to
ensure that a nation’s infrastructure meets its needs, and to encourage innovation and technology
adoption are thus all essential to driving growth and ensuring a more inclusive prosperity.
INEQUALITY: CAUSES AND CONSEQUENCES
INTERNATIONAL MONETARY FUND 33
ANNEX I. DEFINITIONS AND SOURCES OF VARIABLES
This annex provides the definition and the sources of the main variables used in the econometric
analysis (Table A1).
Table A1. Data Description
Indicator Name Description Data Source Period
Market Gini Gini index of distribution of income before taxes
and transfers
Standardized World Income Inequality
database
1980-2011
Net Gini Gini index of distribution of income after taxes
and transfers
Standardized World Income Inequality
database
1980-2011
Gini growth Growth of the Gini index of inequality in equalized
household market income
Standardized World Income Inequality
database
1980-2011
Shares of income
(deciles/quintiles)
Share of net income accruing to each decile /
quintile of the income distribution
UNU-WIDER database 1980-2012
Poverty Headcount ratio
growth
Growth of the share of the population living with
$2 per day or less
World Bank’s Povcal database 1980-2012
GDP growth Annual growth of real GDP World Bank’s World Development
Indicators database
1980-2013
GDP per capita Real GDP per capita based on constant local
currency
World Economic Outlook 1980-2012
GDP per capita growth Annual percentage growth rate of GDP per capita
based on constant local currency
World Bank’s World Development
Indicators database
1980-2011
Trade Openness Exports plus imports (goods and services), in
percent of GDP
WEO Database 1980-2013
Financial Openness External assets plus liabilities, in percent of GDP External Wealth of Nations Database,
WEO Database
1980-2013
Credit Domestic credit to the private sector in percent of
GDP
World Bank’s World Development
Indicators database
1980-2012
Industrial employment
growth
Growth of the employment in industry as a
percentage of total employment
World Bank’s World Development
Indicators database
1980-2012
Government spending Simple average of the three relevant sub-indexes
(transfers and subsidies, public consumption and
public investment) of the size-of-the-government
index
Fraser Institute 1980-2010
Technology Share of information and communication
technology capital in the total capital stock
Jorgenson, Dale and Khuong Vu (2011) 1980-2010
Labor market institutions Simple average of firing and hiring and collective
bargaining indexes
World Economic Forum 1980-2010
Education gini Gini index of distribution of educational
attainment
World Bank’s Education Statistics 1980-2010
Skill Premium Average number of total years of schooling Barro-Lee education attainment
dataset
1980-2013
Female mortality Probability of dying between the ages of 15 and
60 for women
World Bank’s World Development
Indicators database
1980-2010
Economic variables
Inequality and Poverty variables
CAUSES AND CONSEQUENCE OF INEQUALITY
34 INTERNATIONAL MONETARY FUND
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