Measuring Poverty and Inequality
Do free markets and globalization foster greater or lesser poverty and
inequality in the developing world? Does international development
assistance to third world nations alleviate or exacerbate the conditions of
poverty? Do welfare state social policies significantly reduce poverty
in developed nations? What impact did the US 1995 welfare reform act have on
the nation's poor? Are the relatively high rates of poverty in the United
States due to the dysfunctional behavior of the poor, to racism and
discrimination, or to stingy social policies? How do these factors
account for the (alleged) feminization of poverty in the United States? Is
it true what they say, "The rich are getting richer and the poor, poorer"?
The arguments, policy analyses, political debates and academic research
concerning these questions rely on measurements of the incidence of poverty.
Poverty rates generally measure the percent of the population living in
households whose annual income (or, as we shall see, annual expenditure)
falls below a predetermined poverty threshold. There are two different
approaches to determining the standard of living that constitutes poverty:
absolute poverty thresholds define a level below which households lack
basic necessary goods and services, while relative
thresholds measure the percentage of the population living at a standard
well below the average of their fellow citizens. Neither strategy for
defining poverty is ideal. Poverty is inherently a relative
concept and absolute standards of measuring it are often arbitrary, but the
relative thresholds measure inequality more than they measure a consistent
level of deprivation. For these and other reasons, debates about
poverty often end up being debates about the measurement of poverty.
Liberal scholars often argue that poverty rate statistics underestimate the
true dimensions of poverty and that higher poverty thresholds should be used
(see Chossudovsky, 1999 and Mangum, 2003), while conservatives often argue
that the statistics exaggerate poverty, either because the thresholds are
set too low or because the measure of income and consumption do not include
all the resources available to the families who are classified as poor
(Rector and Hederman, 2004).
Measuring Poverty in Developing Nations.
Since the early 1980s, the standard measures of poverty in low and middle
income developing nations have been indicators designed by the World Bank.
The Bank’s poverty rate measure is defined as the percentage of a country's
population living in households consuming less than $1 or $2 per day per
capita. The $1 consumption threshold is referred to as "extreme
poverty" and a $2 threshold is used as the more general poverty indicator.
Both threshholds are expressed in constant dollars and are adjusted for
price differences between countries, using measures of national currencies’
purchasing power parity (PPP). In a country where the average family size
of 4 persons, this would be a family poverty threshold of $1424 per year.
In some countries the poverty measures are based on the number of persons
with incomes below a poverty threshold, but in the poorest nations (where
subsistence agriculture and non-cash economies predominate) the indicators
are typically based on estimates of consumption -- the value of the goods
and services consumed by persons, derived from survey responses to questions
about food consumption.
In 2001, the Bank estimated that 21% of the populations of the world’s
developing nations lived in extreme poverty, a total of 1.1 billion people,
a reduction from 1.2 billion in 1990 and 1.5 billion in 1981.
Regional trends in the international poverty rate (Figure 1) indicate that
poverty has declined dramatically in most of Asia (particularly in China and
India) over the past two decades, has increased in Africa and (since 1989)
in the former Soviet Union countries, and has held relatively constant
throughout the Middle East and Latin America. In China alone,
400 million fewer people lived in poverty in 2001 than did so in 1980, with
most of the decline occurring in the early 1980s. Although the poverty
rate for sub-Saharan Africa has increased only marginally, the number of
poor persons in that region nearly doubled, from 164 to 316 million (Chen
and Ravallion 2000).
The World Bank’s annual “World Development Report” is a widely respected
source of statistical information on trends in poverty and related social
conditions. There, and on its website, the Bank reports detailed
information national accounts (e.g., GDP, income and trade data), business
conditions, governmental policies and developmental assistance in addition
to the poverty data. The United Nations provides similar data and a
similar report: the annual and regional “Human Development Report”.
Although much of the data is the same, the tone of the reports do reflect
the ideologies of the countries in control of the organizations. The
World Bank tends to see poverty and as something to be addressed by economic
development; the United Nations stresses that addressing poverty and
inequality will have the side benefit of promoting economic development.
In September, 2000, the United Nations adopted the “Millennium Declaration,”
setting eight broad development goals for developing nations related to
various aspects of poverty, education, gender inequality, health, and
environment (see table 1). Forty-eight development indicators,
including the $1 a day poverty rate, are used to measure progress toward the
goals. For poverty, the goal is to reduce the $1 poverty rate by half,
from nearly 28% in 1990 to 14% in 2015.
It is generally the position of the World Bank and the International
Monetary Fund that the solutions to poverty in the developing world are to
be found in policies involving free market reforms and addressing the
political corruption typical of many of the world’s poorest nations.
African countries generally rank among the world’s poorest nations and their
governments typically rank as the most corrupt, as measured by Transparency
International’s surveys of international business leaders.
Poorer nations tend to be more corrupt than wealthy nations, but whether
political corruption is the cause or the effect of poverty, however, is a
matter of much dispute. Bob Geldof, activist and organizer of the Live
Aid and Live 8 concerts argues that "Africa is not mired in corruption, it
is mired in poverty. Corruption is a by-product of poverty, just like dying
of famine or Aids." (BBC News, 2005). The free market policies
advocated by the World Bank and the International Monetary Fund (IMF) are
also subject of much controversy. Critics of the World Bank and the
IMF’s argue that the organizations’ advocacy of market reforms –such as
privatization , reduced government subsidies, free trade and reduced
business regulation, result in reductions in necessary social services and
increased poverty and inequality.
As we see in figure 3, low poverty rates and economic development, as
measured by per capita GDP, are related conditions, but not necessarily the
same thing. The dramatic reductions in East and South Asian poverty
(shown in figure 1) since the 1980s can be credited to free market
reforms in China and India. On the other hand, the rising levels of
extreme poverty in the former Soviet bloc (Eastern Europe and Central Asia)
also followed the substantial market reforms following the fall of
In Latin America where poverty rates have remained steady for the past two
decades only two countries have managed to achieve substantial reductions in
poverty: Chile and Guyana (see figure 3b).
Both of these countries have pursued what have been the most aggressive free
market economic policies of any
countries in the world, in the case of the Guyana under the impetus of IMF\World
Bank structural adjustment policies.
Issues of data reliability.
While both the United Nations and World Bank strive to provide accurate and
reliable measures of poverty and other social and economic indicators, much
of the data is of uncertain quality. Many of the poorest nations –
such as Zaire or Zimbabwe – lack the bureaucratic infrastructure to conduct
accurate demographic counts and those poor nations with large governmental
bureaucracies – such as China or Cuba – often produce data designed merely
to make regional or local bureaucracies look good.
Constructing the poverty measure involves two steps: determining the
distribution of income (or consumption) across a country’s households
(determine how many households live at each income level), and defining what
the $1 and $2 a day standard means in local currency. In the case of
the World Bank’s poverty measure, for example, the base data are derived
from national surveys of household consumer expenditure or income conducted
at widely varying intervals in each country (approximately every six years
in India, annually or biennially in China, rarely or never in many of the
poorest nations). Typically, the household consumption surveys ask a
member of the household to report the household’s food consumption and other
purchases over the previous week or month. The data are then
extrapolated into yearly figures. Similar surveys of household income
are generally used in more developed countries (income surveys are less
appropriate in countries with a large subsistence or non-cash economy).
The base data provide estimates of the percentage of households living at
each level of consumption or income and are used to estimate the poverty
rate using national standards and to generate measures of economic growth
and income distribution (such as the GINI index or Lorenz curve).
The quality of, and methods of collecting, these base data can vary wildly
from country to country and cross-country and time-series comparisons of the
data are often highly suspect. In many countries, the local population
can be highly suspicious of governmental officials who come asking
questions, while in others it may be suspected that forms are completed by
enumerators who never leave their offices. When household survey data is
not available, but general national income measures are, the Bank uses
estimates based on the assumption that the income distribution is the same
as in neighboring countries. To estimate the poverty rates for years
when there were no household surveys, the Bank assumes all incomes levels
have increased or decreased at the national growth rate (Reddy and Pogge,
2005, 26). Thus, the estimates report reductions in poverty whenever a
country experiences national economic growth. This makes the data
highly suspect for scholars who argue that globalization and international
investment produce uneven economic growth.
Next, one has to determine what level of national consumer expenditure
corresponds to the World Bank’s $1 and $2 a day standards.
This requires an estimate of each country’s “purchasing power parity”, or
PPP. To attain this measure requires both additional household surveys
to determine what commodities people in the country typically consume and
business surveys of the price of those commodities.
Measuring Poverty in Wealthy Nations.
When the World Bank estimates the total world population living below the $1
a day level, it not unreasonably assumes that no one the developed world
would fall below the standard. Beginning in 1983, the Luxembourg
Income Study (LIS) began compiling a collection a household income surveys
conducted (usually) annually by many of the world's wealthiest countries.
The LIS database now includes income surveys from 29 countries. Under the
direction of Timothy Smeeding and Lee Rainwater, the LIS center adjusts the
national survey data to provide for consistent measures across nations.
From these data, LIS reports a variety of statistical measures of national
Unlike the World Bank poverty measures, the poverty indicator most commonly
reported by the LIS is a relative measure: the percent of persons living in
families below 50% (or some other percentage) of the national median family
income, adjusted for family size. Unlike the US measure discussed
below, the LIS measure is based disposable income (income after taxes) and
includes some "near-cash" income, such as (in the US case) food stamps.
Smeeding and Rainwater have used these data in a series of reports and a
book (2003) addressing international differences in child poverty, calling
attention to the high rates of child poverty (consistently the highest rates
of child poverty) in the United States (see figure 4).
Measuring Poverty in the United States.
In 1963, Molly Orshansky, an economist at the Social Security Administration
undertook the task of determining just how many people in the United States
were poor (Fisher, 1997). Although conservative and liberal scholars
have debated the merits of the indicator ever since, the US poverty rate
statistic that she developed remains today as one of the most commonly used
measures of the nation's economic health.
To measure the poverty rate, it was first necessary to determine a standard
for classifying people as poor. Orshansky relied on studies of food
budgets that had been conducted by the Department of Agriculture in the mid
1950s. The USDA had developed an "Economy Food Plan", essentially a
food budget designed to meet the basic nutritional needs of families.
A 1955 study of family budgets had determined that Americans spent an
average of one-third of their budget on food. For 1963, the Economy
Food Plan cost a family of four (two adults and two children) an average of
$1,033 per year. Multiplying that by 3, Orshansky set $3,100 as the
poverty threshold for a family of four. Since 1963, the poverty
threshold, adjusted for family size, has been adjusted for changes in the
Consumer Price Index (note: not for changes in cost of the food budget).
The U.S. Bureau of Labor and the Census Bureau report the poverty statistics
annually based on the Current Population Survey (CPS). The survey is
conducted in March of each year, measuring the family incomes of the
previous year for a national sample of approximately 77,000 families.
For 2004, the resulting poverty threshold for a family of four stood at
$19,157. Persons living in four person families where the total family
income is less than $19,157 are thus classified as poor and those with
higher incomes are classified as not poor. In 2003, 35 million
Americans were classified as poor, 12.5% of the total population (25 million
families were poor, 10.8% of the families).
The US poverty rate fell sharply in the 1960s, reaching its lowest point in
1973; since then it has fluctuated in a narrow range (see figure 5).
Poverty trends generally reflect changes in the economy: The declines in the
1990s reflect the economic prosperity of the Clinton administration years;
the increases before and after those years the economic downturns of the two
Because the CPS survey includes many demographic questions about age, family
structure and marital status, race and ethnicity, the data allow for very
detailed analysis of the demographics of poverty.
In figure 6, for example, we see that much of the disparity in black and
white family poverty (but not Hispanic and white) can be accounted for by
the differences family structure. While conservatives
often point to the increase in single parent families as the reason for the
persistence of poverty in America, liberals see government policies as a
Thus Senator Daniel Moynihan (1987) often called attention the disparity in
trends in poverty rates for children and the elderly. In the 1960s,
poverty rates fell for both groups, but after the early 1970s, the child
poverty rate began to increase while the elderly poverty rate continued to
decline -- to the point where the elderly are now less poor than the
population as a whole (see figure 7). These trends, Moynihan argued
could be explained by the substantial increases in Social Security and
Supplemental Security Income benefits for the elderly after 1970 and the
steady decline in AFDC and other program benefits that targeted families
Problems with the Poverty Statistic.
There have been many complaints that the poverty statistics either
overestimate or underestimate the true poverty rate: liberals say that
poverty is higher than the numbers indicate; conservatives say that the
numbers exaggerate the poverty rate, although these claims are made more or
less strenuously depending on which party is in power.
Liberals often complain that the poverty thresholds are too low.
Although food was one-third of a family budget in the 1950s, it is one-sixth
now; taking that into account, they say, would suggest a higher threshold.
Liberals often argue that the poverty thresholds are adjusted for price
inflation, rather than income. Because, incomes generally rise faster
than prices, the poverty threshold are much lower today compared to the
median family income than they were in the 1960s. Also, the poverty
measures do not fully capture what we mean by poverty. Families with
incomes above the poverty line may nevertheless be deeply in debt, perhaps
because of large medical bills.
Conservatives argue that the thresholds are set too high because the
Consumer Price Index that is used to adjust the poverty threshold has been
shown to exaggerate the level of inflation as much as one percent per year.
They also note that the definition of income used in the measure does not
include non-cash income such as Food Stamp benefits, public housing, or
Medicaid benefits. Because the income measure is based on pre-tax income, it
does not take into account the Earned Income Tax Credit (EITC) benefits that
many families with children receive.
Although there is some basis for both claims, one has to understand that
poverty is inherently subjective concept to begin with; there is no such
thing as a true poverty rate. Most of the complaints about the poverty
rate statistic concern its validity (whether or not the statistic measures
what it is supposed to measures), but questions about the statistic's
reliability (the consistency of the measurement) are often more to the
Consider the conclusion that might be drawn from the trends in child and
elderly poverty rates in figure 6. Because families with
children are much more likely to receive EITC and Food Stamp benefits (which
are not counted as income) than are the elderly, the disparity in poverty is
not as great as the data indicate. And because the EITC benefits were
first offered in the 1980s and substantially increased in the first year of
the Clinton administration, child poverty has declined at a faster rate than
the data show. On the other hand, because many of the elderly poor
have savings and assets that do not enter into the calculation of the
poverty rate, the poverty rate statistic may overestimate their level of
Measuring Income Inequality
The income data used to derive the poverty measurements can also be used to
address many other issues related to trends in income inequality. Thus
figure 8 shows trends in the share of aggregate family income for the
richest 5% of households and the poorest 40%. Since 1980, the
richest households have seen their share of household income steadily
Note, however, that conservatives sometimes object that the income
distribution data reflect changes in household composition: the highest
income groupings tend to comprise large households that the lower income
groupings. The top household income quintile, for example, contains
24.6% of the population, the bottom quintile, only 14.3%. (see Rector and
One of the peculiarities in the Census surveys is that the households and
families are defined at the time of the survey, while the incomes are the
earnings of members of households over the previous year. At the time
of the CPS survey (e.g., March 2004) respondents are asked for the names
(and relationships) of all members of the household and the earnings of each
of those members over the previous year (January to December, 2003).
Thus, a family could be classified as having been poor in 2003 solely
because the primary wage earner died or left the family in January of 2004.
As the rate of family disruptions have increased overtime, this may be the
cause of relatively small increases in the poverty rate.
Much of the research on poverty relies on data obtained from the Panel Study
of Income Dynamics conducted by the Institute for Social Research at the
University of Michigan. Unlike the CPS and other Census surveys, the
panel study re-interviews the same families each year (or biannually),
permitting analyses of the duration of poverty status and welfare
participation. Using these data, Katherine Bradbury and Jane Katz
report evidence that income mobility has declined in the the US in the
1990s: Families are more likely to remain in the same "income quintile" than
they were in the past (see table 2). More than half of the families in
the poorest income quintile were still poor ten years later; more than half
of those in the richest quintile remained rich. (Bradbury and Katz 2002)
The annual US poverty data are based on a CPS sample of approximately 75,000
families. Although this is a very large sample size (and with a
relatively high response rate) in comparison to many other surveys and
polls, the sample size is often not large enough to provide reliable data
for small demographic groups or regions. For the US population as a
whole, the sampling error (based on a 90% confidence interval) is
approximately +\-.2 percent. Thus, if the reported poverty rate is
11.8%, we can be 90% sure that the true rate is between 11.6 and 12.0%.
For subpopulations in the survey (e.g., children, or two parent
households) the sampling errors are greater, depending on the sample size.
The annual poverty reports do include state-level poverty data, but to
compensate for the small sample size (especially for the smaller states),
three-year averages are used. The Decennial Census uses a much
larger (census long-form) sample, providing data for smaller subpopulations
and cities and counties. Often in educational research, the percent of
students who are eligible for the federal school lunch program is used as an
indirect measure of the level of poverty in a school or school district.
It is commonly reported the women earn less than men; in the 1970s, much was
made of the fact that women earned 59 cents for every dollar that a man was
paid. Near the top of table 3, we see that when comparing male
and female full-time workers, female workers earn seventy cents for every
dollar male workers earn. When we compare female and male workers at
similar ages or education attainment, however, the disparities are more
complex. The disparity between men and women declines sharply with
age. Differences in education, however, do not seem to consistently
account for the disparity. Note that the earnings reported in table 3
are for year-round full-time employees, in effect controlling for
differences in part time work between men and women.
Additional controls, such as seniority and occupation, might account for
more of the disparity permitting us to assess the degree to which equally
situated and qualified men and women earn different salaries. Notice,
though, that controlling for some factors may not be enough: Even though the
earnings for women in the youngest age group are most similar to male
earnings, younger women tend to have higher levels of education than men of
the same age.
Spinning Poverty Statistics.
It’s not really true what they say: “You can prove anything you want with
statistics.” It is true that you can find and\or present statistics in
support of just about any claim, but it takes more than just the statistics
to reach any conclusion. To “prove” something with statistics usually
takes at least two things: the statistics and some reasoning.
When people make bogus claims that something is true, it is usually the
reasoning, not the statistics, that is at fault. Consider the
between talk show host Bill O'Reilly and one of his radio show callers:
CALLER: Hi, Bill.
CALLER: Let's see, poverty is up since Bush took office.
O'REILLY: That's not true.
CALLER: It is true.
O'REILLY: I have the stats right here, Larry.
CALLER: I just looked at the figures. Gun crime is up since George Bush took
O'REILLY: All right, Larry, hold it, hold it, hold it. Let's deal with one
at a time. The only fair comparison is halfway through Clinton's term,
halfway through Bush's term, OK? That's the only fair comparison. You gotta
go real time.
CALLER: Bill, I --
O'REILLY: Poverty is down, Larry, one full percent in real time from 1996,
halfway through Clinton, 2004, halfway through Bush. That is the truth,
Larry, and if you're not willing to acknowledge that's the truth, this
conversation is over.
O’Reilly’s claim, repeated at least two times on his “no-spin zone” Fox News
broadcasts, is based on just two entirely accurate statistics combined with
a lot of very faulty reasoning. O'Reilly’s statistics are accurate:
Bush's fourth year poverty rate is lower than Clinton's fourth year poverty
rate (see figure 9). And O’Reilly’s interpretation of the two
numbers is based on an entirely reasonable premise: it would be unfair to
compare what President Bush has achieved in four years with what it took
President Clinton four years to achieve. Where he goes wrong is in using the
rate at the end of the first term rather than the change in the rate: the
poverty rate went down 1.2% in Clinton’s first term; up 1.4% in Bush’s first
term. Viewed another way: O’Reilly gives Bush credit for the decline
in the poverty rate since the midpoint of Clinton’s term in office, but all
of that decline -- and more took -- place while Clinton was in office.
The truth is that the poverty rate goes up and down regardless of who
the president is and social and economic events and trends well outside
the control of either the president or Congress have much more to do
changes in the poverty rates than any policies the presidents pursued.
If President Clinton does deserve credit for policies that resulted in
an eight year decline in poverty, why didn’t those policies continue to
have the same beneficial effect during the Bush years?
Surprisingly, O’Reilly did not resort to the more common method office
holders use to misrepresent statistical trends that are going the wrong
way: the average. The average annual poverty rate for the eight
years of the Clinton administration was 13.5; for the Bush
administration’s first four years, 12.1 – even better one could compare
Bush’s numbers to the average annual rate in just the first four years
of the Clinton presidency.
BBC News (2005), “G8 leaders 'real stars of show'” 2 July,
Katharine Bradbury and Jane Katz, "Are lifetime incomes growing more
unequal? New evidence on family income mobility in the
1990s suggests that the answer may be yes," Regional Review, Quarter
4 (2), pp 3-5.
Chen, Shaohua and Martin Ravallion (2000), “How have the world’s poorest fared since the early 1980s?
Policy Research Working Paper
3341, World Bank, 2000
Michel Chossudovsky (1999). "Global Falsehoods: How the World Bank and the
UNDP Distort the Figures on Global Poverty" The Transnational Foundation For
Peace and Future Research
Deaton, A. S. and Kozel, V. (2004), “Data and
Dogma: The Great Indian Poverty Debate”, Princeton University, mimeo
Gordon M. Fisher (1997). "The Development of the Orshansky Poverty
Thresholds and Their Subsequent History as the Official U.S. Poverty
Measure," US Census Bureau - Poverty Measurement Working Papers
Garth L. Mangum, Stephen L. Mangum and Andrew M. Summ, (2003) The
Persistence of Poverty in the United States (The Johns Hopkins
Lee Rainwater and Timothy M. Smeeding. (2003). Poor Kids in a Rich
Country: America's Children in Comparative Perspective (Russell Sage
Media Matters for America
“O'Reilly defended false Clinton-Bush poverty comparison as ‘the only
accurate measuring stick’” http://mediamatters.org/items/200509160002
Moynihan, Daniel Patrick. (1987). Family and Nation (Harcourt
Robert Rector and Rea Hederman, Jr. (2004) "Two Americas: One Rich, One
Poor? Understanding Income Inequality in the United States," The
Heritage Foundation backgrounder #1791 August 24
Reddy, Sanjay G.. and Camelia Minoiu (2005),
“Chinese Poverty: Assessing the Impact Assumptions”, available on
Reddy, Sanjay G.. and Camelia Minoiu (2005b), “Has World Poverty Really
Fallen During The 1990s?”, available on
Reddy, Sanjay g. and Thomas W. Pogge (2005), “How Not to Count the Poor”
Version 6.2 http://www.columbia.edu/~sr793/count.pdf
U.S. Census Bureau (2004), "Income, Poverty, and Health Insurance Coverage
in the United States: 2003" Current Population Reports, P60-226, U.S.
Government Printing Office, Washington, DC.