Poverty figures: Black Americans and White Americans,

Some idiot European wrote earlier about the USA


...the blacks still
live in ghettos.




*All* black Americans live in ghettos??? Have you ever been here????


There are many more white people in poverty in the US than black
people in poverty by a multiple of approximately 3. Do the math. (If
you can)


http://www.press.uchicago.edu/Misc/Chicago/649288.html


"..Much of the research and media attention on African Americans is on
the black poor. Welfare debates, discussions of crime and safety, urban



policy initiatives, and even the cultural uproar over things like rap
music are focused on the situation of poor African Americans. With more



than one in four African Americans living below the official poverty
line (versus approximately one in nine whites), this is a reasonable
and warranted bias. But rarely do we hear the stories of the other
three-fourths, or the majority of African Americans, who may be the
office secretary, the company's computer technician, a project manager
down the hall, or the person who teaches our children. The growth of
the black middle class has been hailed as one of the major triumphs of
the civil rights movement...."

PeeJay


And then our Australian idiot responded with this gem: in response to
the fact that there are more Whites in absolute numbers in poverty in
the US than absolute numbers of Blacks by a "multiple of
approximately 3".

1 in 4 is slightly more than double
1 in 9.

Fred Bloggs

Source: U.S. Census Bureau
Contact: Housing and Household Economic Statistics Information Staff at
(301)763-3242
Last revised: August 29, 2006
URL: http://pubdb3.census.gov/macro/03200...w01_100_06.htm


[2005 Numbers in thousands]


__________________________________________________ _________________

Number
in
Population poverty %

White alone
Total .................... 235,430 24,872 10.6

Black alone.................. 36802 9168 24.9
Total


Ratio of number of White people in poverty to Black people in poverty
in USA:

24872M/9168M = 2.7

2.7 rounded to whole number = "multiple of approximately 3"

PJ O'Donovan schrieb:
Some idiot European wrote earlier about the USA


....plonk....

In article . com,
says...
Some idiot European wrote earlier about the USA


...the blacks still
live in ghettos.




*All* black Americans live in ghettos??? Have you ever been here????


There are many more white people in poverty in the US than black
people in poverty by a multiple of approximately 3. Do the math. (If
you can)


http://www.press.uchicago.edu/Misc/Chicago/649288.html


"..Much of the research and media attention on African Americans is on
the black poor. Welfare debates, discussions of crime and safety, urban



policy initiatives, and even the cultural uproar over things like rap
music are focused on the situation of poor African Americans. With more



than one in four African Americans living below the official poverty
line (versus approximately one in nine whites), this is a reasonable
and warranted bias. But rarely do we hear the stories of the other
three-fourths, or the majority of African Americans, who may be the
office secretary, the company's computer technician, a project manager
down the hall, or the person who teaches our children. The growth of
the black middle class has been hailed as one of the major triumphs of
the civil rights movement...."

PeeJay


And then our Australian idiot responded with this gem: in response to
the fact that there are more Whites in absolute numbers in poverty in
the US than absolute numbers of Blacks by a "multiple of
approximately 3".

1 in 4 is slightly more than double
1 in 9.

Fred Bloggs

So explain it, peabrain? Why is it so that if you are black you are more
than twice as likely to live in poverty as if you are white?

Source: U.S. Census Bureau
Contact: Housing and Household Economic Statistics Information Staff at
(301)763-3242
Last revised: August 29, 2006
URL: http://pubdb3.census.gov/macro/03200...w01_100_06.htm


[2005 Numbers in thousands]


__________________________________________________ _________________

Number
in
Population poverty %

White alone
Total .................... 235,430 24,872 10.6

Black alone.................. 36802 9168 24.9


Total


Ratio of number of White people in poverty to Black people in poverty
in USA:

24872M/9168M = 2.7

2.7 rounded to whole number = "multiple of approximately 3"

And let's do the numbers on total populations:
235430/36802= 6.4 (approximately). Therefore, out of a population nearly
6.5 times as large, only 2.7 times as many whites are living in poverty
as blacks. Just so you grasp this point peabrain, that means that if you
are black, you have more than twice the likelihood to be born into a
family that lives below the poverty line. Gee that must make you proud
to be a cracker, peabrain.

On 2 Dec 2006 04:02:00 -0800, "PJ O'Donovan" wrote:

And then our Australian idiot responded with this gem: in response to
the fact that there are more Whites in absolute numbers in poverty in
the US than absolute numbers of Blacks by a "multiple of
approximately 3".

1 in 4 is slightly more than double
1 in 9.

Ummm... PJ, this idiot is actually correct.
--
---
DFM - http://www.deepfriedmars.com
---
--

1 in 4 is slightly more than double
1 in 9.

Fred Bloggs


Ummm... PJ, this idiot is actually correct.

DFM

Sure the idiot is simplistically right to the extent that the axiom
applies

But It's obvious the idiot can't comprehend the comparative absolute
arithmetic effect of lower rates of incidence from that axiom when
applied to an even larger rate of increase in comparable universe
magnititude.

Might be the result of a convoluted "antipodean school of arithmetic"
they learn down under.
Dave Frightens Me wrote:
On 2 Dec 2006 04:02:00 -0800, "PJ O'Donovan" wrote:

And then our Australian idiot responded with this gem: in response to
the fact that there are more Whites in absolute numbers in poverty in
the US than absolute numbers of Blacks by a "multiple of
approximately 3".

--
---
DFM - http://www.deepfriedmars.com
---
--

On 2 Dec 2006 13:39:55 -0800, "PJ O'Donovan" wrote:

1 in 4 is slightly more than double
1 in 9.

Fred Bloggs


Ummm... PJ, this idiot is actually correct.

DFM

Sure the idiot is simplistically right to the extent that the axiom
applies

But It's obvious the idiot can't comprehend the comparative absolute
arithmetic effect of lower rates of incidence from that axiom when
applied to an even larger rate of increase in comparable universe
magnititude.

Nice humour, but isn't it supposed to be funny?
--
---
DFM - http://www.deepfriedmars.com
---
--

Understanding Differences in Black and White Child Poverty Rates
by Robert Rector, Kirk A. Johnson, and Patrick F. Fagan
Center for Data Analysis Report #01-04
INTRODUCTION
High rates of child poverty in the United States are a continuing
concern. The fact that poverty is considerably more common among black
children than it is among white children has intensified this concern.
In 1999, according to the U.S. Bureau of the Census, 33.1 percent of
black children lived in poverty compared with 13.5 percent of white
children.1

This CDA Report attempts to identify the primary causes of child
poverty in the United States, using the National Longitudinal Survey of
Youth, a representative sample of Americans produced by the U.S.
Department of Labor.2 We also examine the differences in black and
white child poverty and seek to uncover the causes of those
differences. This analysis reveals the following:

The major underlying factors producing child poverty in the United
States are welfare dependence and single parenthood.

Race per se is not a factor in producing child poverty; race alone does
not directly increase or decrease the probability that a child will be
poor.

When a black child is compared with a white child raised in identical
circumstances, both children will have the same probability of living
in poverty.

Similarly, when whites with high levels of single parenthood and
welfare dependence (matching those typical in the black community) are
compared to blacks, the poverty rates for both groups are nearly
identical.

Black American children are more likely to live in poverty than are
white children, primarily because black children are far more likely to
live in single-parent families and to be on welfare.

Black and white Americans differ dramatically in marriage patterns and
welfare dependence. In 1999, 68.8 percent of black American children
were born out of wedlock. By contrast, the out-of-wedlock birth rate
for white Americans was 26.7 percent.3 Similarly, black children were
five times more likely to be dependent on welfare from the Aid to
Families with Dependent Children (AFDC) program4 than white children.
Since single parenthood and welfare dependence are the primary factors
producing child poverty in the United States, any meaningful strategy
to reduce the disparities in black and white child poverty must focus
on increasing marriage and reducing welfare dependence among blacks.

DESCRIPTION OF SAMPLE AND VARIABLES
This study analyzes differences in black and white child poverty based
on data from the National Longitudinal Survey of Youth (NLSY), a
large-scale multi-year national survey funded by the U.S. Department of
Labor and other federal agencies. The NLSY is a statistically valid
sample of 12,686 young men and women who were between the ages of 14
and 22 when they were first interviewed in 1979. These individuals have
been re-interviewed continually since then and are now in their
thirties and forties. This Heritage study covers events in the lives of
these individuals between 1979 and 1996.

The NLSY records births to these individuals and provides detailed
information on the children in each year after birth. The survey thus
provides a wealth of data on children born in the United States during
the past two decades.5 The NLSY data document not only family income
year by year, but also underlying conditions such as employment,
welfare use, educational attainment, and marriage or divorce. Thus, the
NLSY provides a robust set of data with which to analyze the causes of
child poverty.

This analysis focuses on the following variables derived from the NLSY
data.

Time in poverty: The time a child has lived in poverty as a percentage
of the total years of the child's life. Thus, if the child is 10 years
old and has lived in poverty five of those years, the time in poverty
would be 50 percent.

Time on welfa The percentage of months of the child's life spent in
a household receiving Aid to Families with Dependent Children (AFDC)
benefits. Thus, if the child is 120 months old and has lived in a
family on AFDC for 30 of those months, the time on welfare would be 25
percent.

Time in a single-parent home: The percentage of a child's life spent in
a single-parent home as opposed to a married-couple home. Thus, if a
child has lived with a never-married mother all his life, the time
spent in a single-parent home would be 100 percent.

Mother's math and verbal skill level: The mother's math and verbal
performance level relative to the rest of the population. To compute
this score, all individuals were ranked, based on math and verbal skill
levels, into percentiles from 0 to 100. A parent's percentile score of
30 means that 29 percent of the population had scores below the parent
and 70 percent had scores above.6

Number of children: The number of children ever born to the child's
mother.

Mother's age at first birth: The mother's age at first birth, with age
counted in years above age 15. Thus, if a mother has a score of 5, she
was 20 years old at the time of first birth.

Regional variables: A set of four variables measuring the percent of
time a child has lived in each region.7

Rural residence: A dichotomous variable measuring whether the child
lived in a non-urban area in 1996

Racial groups: Black, white, and other.8
DESCRIPTIVE STATISTICS
Table 1 and Chart 1 show the statistical means for the variables listed
above for both black and white children in the NLSY. Black children
lived in poverty for 46.9 percent of the time since birth, while white
children lived in poverty for 13.0 percent of their lives. (Note: NLSY
poverty figures in Table 1 do not match the Census figures noted above
because the figures measure different concepts. The Census figures
measure the percent of children who were poor in a single year: 1999.
The NLSY figures measure the average percent of time children in the
sample lived in poverty since birth.)9


Black children on average spent 49.4 percent of their lives in
single-parent families, compared with 12.8 percent for white children.
While black children on average spent 27.7 percent of their lives
receiving AFDC, the figure was 5.4 percent for white children. Black
mothers in the NLSY had math and verbal skill levels at the 19.7
percentile. By contrast, the average white mother had skill levels at
the 52.5 percentile.

Black mothers in the NLSY sample gave birth to their first child at an
average age of 19.9 years, while white mothers on average had first
births at 23.4 years. Black mothers had, on average, 3.05 children
while white mothers had 2.6 children. Black children spent more time
residing in the South than did white children (56.9 percent to 30.1
percent).

Regression Analysis
The goal of this analysis is to determine the proximate social and
economic causes of child poverty in the United States. In addition, the
authors seek to determine whether a child's race affects the frequency
of poverty independent of other social and economic variables. In other
words, is a black child more likely to experience poverty than a white
child with similar characteristics in terms of time on welfare,
residence in single-parent homes, number of siblings, and other
variables?
To answer these questions, a regression analysis was performed with
"time in poverty" as the dependent variable. The independent variables
used to explain the probability of poverty were race, time on welfare,
time in a single-parent home, mother's math and verbal ability level,
number of children in the family, age of mother at first birth,
regional residence, and rural residence.

Some might suggest that time in poverty in an abstract sense could be
treated as an independent variable and time on welfare as the dependent
variable, contending that since only low-income persons receive
welfare, it is a lack of income that causes welfare dependence rather
than the opposite. Such an assessment is based on a lack of
understanding of the operation of welfare programs.

For most of the history of Aid to Families with Dependent Children, a
practical precondition for receipt of benefits has been that a mother
worked little or not at all. Typically, only about 6 percent to 10
percent of AFDC mothers were employed while receiving benefits, and
those who were employed generally worked few hours. Thus, to be on AFDC
in most cases meant the family was without earned income. Since the
value of the AFDC benefits was generally below what the mother could
potentially earn from employment and below the poverty threshold, being
on welfare led to an increased rate of poverty.

Moreover, more generous monthly welfare benefits are linked to larger
caseloads and greater periods of time spent on welfare. Dr. June
O'Neill, former director of the Congressional Budget Office, has found
that a 50 percent increase in monthly AFDC and Food Stamp benefit
levels leads to a 75 percent increase both in the number of women
enrolled in AFDC and in the number of years spent on AFDC. Thus,
conventional welfare programs, by pulling mothers out of the labor
force, reduce earned income and dramatically increase child poverty.10

Finally, when the welfare system entices a woman out of the job market,
she loses work experience that could lead to future wage increases. The
loss of work experience thus can reduce future earnings potential and
increase the prospects of further poverty even after the family has
left welfare. Overall, rather than a lack of income inducing
non-employment and dependence, it is the lack of earnings inherent in
welfare dependence that produces the family's poverty.



The results of the regression are shown in Table 2. The R square of the
regression is .64, indicating that the model is able to explain 64
percent of the variation in child poverty in the NLSY sample. Time on
welfare and time in a single-parent home were found to have strong
significant effects in determining the amount of time a child would
live in poverty. The number of children in the family, the mother's
math and verbal skill level, and the age of the mother at first birth
also had clear significant effects on child poverty rates, although the
magnitude of these effects was smaller than the magnitude of welfare
dependence and single-parent variables. More children in the family led
to more time in poverty. By contrast, higher ability levels of the
mother and being older at first birth led to decreases in child
poverty.




The regional variables show mixed results. In each case, residence in
the South, Northeast, and West was compared with the base or default
condition of residing in the North Central region. Residing in the
South, where wage rates historically have been lower than in the rest
of the country, had a statistically significant effect in raising
poverty rates. Residing in the Northeast also had a smaller but still
significant effect. By contrast, residing in the West did not have a
statistically significant effect on child poverty. Residing in a rural
area raised the probability of child poverty by a small but
statistically significant amount.

Finally, the regression included three racial categories: white, black,
and other. White was treated as the default or baseline condition
against which black and other were compared. The lack of effect of the
racial variables is striking. Both black and other race were shown to
be very weak variables without statistically significant effects on
poverty. Thus, race per se was found to have no direct bearing on child
poverty. If a black child is compared to a white child who is identical
with respect to the other variables shown, the poverty rate of the two
children will be, on average, nearly identical.

As Table 1 shows, blacks have higher levels of nearly all the variables
that contribute directly to child poverty in the regression. Blacks
have higher rates of welfare dependence, single parenthood, more
children per family, and lower parental math and verbal skill levels.
Blacks give birth at a younger age and are more likely to live in the
low-wage South.11 It is the differences in these variables,
particularly welfare dependence and single parenthood, that cause the
large differences in child poverty between blacks and whites.

Relative Importance of Factors
Although the regression in Table 2 shows that a number of variables
have a statistically significant influence in determining child
poverty, as noted, some variables have far more effect than others do.
Chart 2 shows the relative importance of each of the variables in
explaining child poverty.12 The numbers on the chart show, in general
terms, how these variables affect time in poverty.





Time on welfare accounts for roughly half of the child poverty observed
in the United States. By contrast, the number of children in the family
is about one-fifth as powerful as a poverty determinant, accounting for
about 11.5 percent of the variance in poverty among children.

As Chart 2 shows, time on welfare and time in single-parent families
are overwhelmingly the strongest determinants of child poverty--51.1
percent and 22.7 percent, respectively. Together, they account for
roughly three-quarters of the differences in child poverty explained by
the model. The other variables play a more modest role, while race, as
noted, has no significant, independent effect.


Estimated Effects of Variables on Child Poverty
In order to estimate the concrete effects of each variable on child
poverty, the authors reran the regression using only the nine
independent variables shown to be significant in Table 2. The results
of this modified regression are shown in Table 3. Holding the other
independent variables constant, the results for each of the nine
variables are as follows:
A 10 percent increase in time on welfare leads to a 6.9 percentage
point increase in a child's time in poverty.

A 10 percent increase in time spent in a single-parent family leads to
a 2.1 percentage point increase in a child's time in poverty.

A 10 percent increase in a mother's math and verbal ability level leads
to a 1.6 percentage point decrease in a child's time in poverty.

An increase of one in the number of siblings in a family causes, on
average, an increase of 3.1 percentage points in a child's time in
poverty.

Each additional year in the mother's age at first birth decreases a
child's time in poverty by 0.38 percentage points. Thus, a child whose
mother first gave birth at age 25 can expect to experience, ceteris
paribus, 3.8 percent less time in poverty than can a child whose mother
first gave birth 10 years younger at age 15.

A 10 percent increase in time residing in the South increases a child's
time in poverty, on average, by 0.5 percentage points.

A 10 percent increase in time residing in the Northeast increases a
child's time in poverty, on average, by 0.2 percentage points.13

Residing in a rural area in the last year of the analysis increases
poverty 2.1 percentage points.
In each case, the magnitude of the individual effects of each
independent variable is determined by holding the other variables
constant. This means, for example, that a child who has one sibling
will, on average, experience 3.1 percent more poverty when compared to
a child with no siblings who is identical with respect to the other
independent variables.




Examples of Family Types
Table 4 shows the expected average time in poverty for children raised
in various representative family situations. (The figures are based on
the results of the modified regression model shown in Table 3.) Example
1 is an extremely poverty-prone family. The mother in this example has
a below-average math and verbal ability level equal to the 25th
percentile of the general population. (This is low for the general
population but fairly typical for mothers living in poverty.)14 There
are four children in the family, and the mother gave birth to her first
child at age 15. The family resides in a rural area in the South. The
mother has never been married, and the family has been on welfare for
75 percent of the time since the child was born. Children raised in
these conditions, on average, would spend 96 percent of their lives in
poverty.
Table 4: Child Poverty Rates for Representative Families

Children of Never-Married Mothers
(Mother has not been married at any time since the child was born)
Time in Poverty

Example 1) Never-married mother; four children in family; mother has
below average math and verbal skills (=25th percentile); first child
was born when mother was 15 years old; family lives in rural area in
the South; family has been on AFDC in 75% of the years since the child
was born. 96%

Example 2) Never-married mother; two children in family; mother has
below average math and verbal skills (=25th percentile); first child
was born when mother was 20 years old; family lives in a city in North
Central U.S.:
Case a) family on AFDC in 50% of years since the child was born
64%

Case b) family on AFDC in 25% of years since the child was born
46%
Children of Sometimes Married Mothers
(Mother has been married for part of the time since the child was born)

Example 3) Child has lived in a single-parent home for 50% of its
life; two children in family; first child was born when mother was 25
years old;
mother has average math and verbal skills (=50th percentile); family
lives in a city in North Central U.S.:

Case a) family on AFDC in 25% of years since the child was born
30%

Case b) family has never been on AFDC
13%
Children in Intact Families
(Mother and father have been married at all times since the child's
birth)

Example 4) Mother has been married throughout the life of the child;
two children in the family; mother has below average math and verbal
skills (=25th percentile); first child was born when mother was 25
years old; family lives in a city in North Central U.S.:

Case a) family on AFDC in 5% of the years since the child was born
10%

Case b) family has never been on AFDC
6%
Example 5) Mother has been married throughout the life of the child;
two children in the family;
mother has average math and verbal skills (=50th percentile); first
child was born when mother was 25 years old; family lives in a city in
North Central U.S.; family has never been on AFDC 2%

Example 6) Mother has been married throughout the life of the child;
two children in the family; mother has above average math and verbal
skills (=75th percentile); first child was born when mother was 25
years old; family lives in a city in North Central U.S.; family has
never been on AFDC 0%


Example 2, Case B, also represents a highly poverty-prone family,
though the circumstances are less extreme than in Example 1. Again, the
child has been born out of wedlock and the mother has not subsequently
married. The mother has below-average math and verbal skill levels
equal to the 25th percentile of the population. There are two children
living in the family; the first child was born when the mother was 20
years old. The family lives in a city in the North Central United
States. The family has been on AFDC for 25 percent of the time since
the child was born. Children living in these circumstances typically
would be in poverty some 46 percent of the time. This example is quite
typical of the 9 percent of children who live with never-married
mothers.

At the bottom of the table are poverty-resistant families. In Example
5, the mother was married at the time of the child's birth and has
remained married throughout the child's life. There are two children in
the family. The mother has an average math and verbal skill level
(equal to the 50th percentile of the general population). The family
lives in a city in the North Central United States and has never been
on welfare. The average time in poverty for children raised in these
conditions would be about 2 percent of the child's life. The majority
of children raised in these circumstances would never experience
poverty at all.

The importance of both single parenthood and welfare dependence in
determining the level of child poverty is again obvious. A final point
that should be reemphasized is that the average poverty rate for
children in the various scenarios would not be affected by race. On
average, the poverty rate would be the same for both white and black
children raised in each of the family scenarios in Table 4.

THE LINKAGE BETWEEN SINGLE PARENTHOOD AND WELFARE DEPENDENCE
The determinant variables affecting poverty do not exist in isolation
from each other. Families that have high scores on one factor that
increases poverty are likely to possess high scores on other
poverty-inducing factors as well. In particular, welfare dependence and
single parenthood are closely intertwined. Welfare dependence is
extremely rare among married couple families but is relatively common
in single-parent families. Indeed, residing in a single-parent home
could be considered almost a necessary precondition to long-term
welfare dependence. This point is illustrated in Chart 3. The chart
divides children into four groups.

Out-of-Wedlock Never Married: Children born out of wedlock whose mother
has never married after the birth of the child. On average, children in
this group have spent 44.5 percent of their lives on AFDC.

Out-of-Wedlock Subsequent Marriage: Children born out of wedlock whose
mother married subsequent to the child's birth. On average, children in
this group have spent 20.4 percent of their lives on AFDC.

Within Wedlock Divorced: Children born to married parents who later
divorced. On average, children in this group have spent 10.7 percent of
their lives on AFDC.

Within Wedlock Marriage Intact: Children born to parents who were
married at the time of birth and have remained married. Children in
this group, on average, have spent only 2.5 percent of their lives on
AFDC.





Welfare dependence (receipt of AFDC benefits) is 1,700 percent more
common among children residing with never-married mothers than among
children born to married couples where the marriage has remained
intact.

The linkage between single parenthood and welfare dependence is further
illustrated in Chart 4. The first three groups (children of
never-married mothers, children born out of wedlock with a subsequent
marriage, and children born within wedlock whose parents later divorce)
constitute broken or never-formed families. Children in these three
groups represent 34 percent of all children within the NLSY. However,
these same children comprise 85 percent of all time spent on welfare.
By contrast, children born inside wedlock to parents whose marriage has
remained intact constitute two-thirds of all children in the NLSY but
account for only 15 percent of all time on welfare.



Poverty and Racial Discrimination
Many argue that blacks have higher rates of child poverty because they
are victims of pervasive racial discrimination. However, the fact that
black children do not have higher poverty rates than whites raised in
similar circumstances argues against that view. The reality that
poverty rates are the same for black and white children raised in
similar circumstances suggests that society treats both groups equally
and that discrimination has no direct impact on poverty differences.
However, one could argue that while racial discrimination has no direct
effect on poverty differences, it does have a substantial indirect
effect. Those holding this view could maintain that past and present
racial discrimination has played a strong role in producing the current
high levels of single parenthood and welfare dependence among blacks.
The higher levels of black single parenthood and dependence in turn
yielded higher rates of black poverty.

According to this view, one could argue that racial discrimination has
reduced the earnings capacity of black men relative to whites, and thus
made marriage by black men less likely. The fact that black men are
less likely to marry in turn contributes to the 69 percent black
out-of-wedlock birth rate and the corresponding high child poverty
rate.

The historical evidence, however, weighs heavily against this view. For
example, black male earnings today are more than four times higher than
the wages of black men in 1940, after adjusting for inflation.15
Similarly, black male wages have risen relative to white male wages,
from 45 percent of white male wages in 1940 to some 80 percent today.16

Yet, despite their very low earnings in both absolute and relative
terms, black men in 1940 had much higher marriage rates than do black
men today. In 1940, 86 percent of black children were born inside
marriage compared with 31 percent today. Thus, notwithstanding very low
wages and restricted job opportunities, black men in earlier periods
maintained high rates of marriage, and black illegitimacy was quite
low. As wages and job opportunities for black men increased, black
marriage paradoxically declined and out-of-wedlock child-bearing
increased greatly. It seems very difficult, therefore, to attribute the
present high level of black single parenthood to low black male
earnings induced by racial discrimination in the labor market.

One could similarly argue that racial discrimination in hiring limits
the employment opportunities and earnings potential of black single
mothers, and thus makes them more likely to be on welfare than whites.
Heightened welfare dependence in turn yields higher poverty for black
children. However, the wage rates of black women are virtually
identical to those of white women who have the same amount of
education, skill levels, and work experience.17 The parity in earnings
between similar black and white women is strong evidence that the labor
market does not discriminate in favor of white women relative to black
women. Racial discrimination in labor markets is thus largely
ineffective as an explanation for the higher rates of welfare
dependence among black as opposed to white single mothers.

Arguments about the long-term, indirect effects of racial
discrimination on poverty remain complex and controversial.
Nonetheless, one critical point about poverty remains clear and
indisputable: Today, single parenthood and welfare dependence are the
primary causes of child poverty. Whatever one's view about the
underlying causes of the high current levels of single parenthood and
dependence among blacks, it is evident that the present racial
disparities in child poverty cannot be significantly reduced without
reducing existing racial disparities in marriage and welfare
dependence. Thus, while reasonable individuals might disagree about the
underlying causes of the decline in marriage and the growth in welfare
dependence, they can and should agree on the importance of reducing
these social problems.

CONCLUSION
Child poverty is a continuing American problem. This report has
examined the causes of child poverty and the factors that contribute to
racial differences in child poverty. The analysis reveals that welfare
dependence and single parenthood are the major underlying factors
producing child poverty. Race per se is not a significant factor in
directly increasing child poverty: Black children have the same poverty
rate as white children who are raised in similar circumstances. Black
children are more likely to be poor than white children primarily
because they are more likely to live in single-parent homes and to be
on welfare.

Those who are sincerely interested in reducing child poverty must focus
on reducing the principal causes of that poverty: welfare dependence
and single parenthood. Those interested in reducing the current
disparities in black and white poverty must focus on altering the
principal causes of that disparity: the higher levels of single
parenthood and dependence among blacks.

Robert Rector is a Senior Research Fellow in Welfare and Family Issues,
Kirk A. Johnson is a Senior Policy Analyst in the Center for Data
Analysis, and Patrick F. Fagan is William H. G. FitzGerald Senior
Fellow in Family and Cultural Issues at The Heritage Foundation.


--------------------------------------------------------------------------------

APPENDIX: TECHNICAL SPECIFICATIONS

DATA
Data used in this analysis are taken from the National Longitudinal
Survey of Youth (NLSY), produced by the U.S. Department of Labor's
Bureau of Labor Statistics. The NLSY is a sample of 12,686 individuals
between the ages of 14 and 22 in 1979. Every subsequent year or two,
these individuals are re-interviewed and asked a series of follow-up
questions. Data are collected on labor force participation, marriage,
fertility, drug use, education, and program participation issues, among
others. The answers to these questions help researchers ascertain the
demographic and economic choices of young people born in the late 1950s
to early 1960s.

Since marriage and fertility issues are of great importance to young
people, a variety of questions on specific dates and times of marriage,
divorce, and childbirth are asked. As the children of the NLSY sample
aged, separate questions were asked beginning in 1986. Data from both
the original NLSY cohort and the NLSY child and young adult data set
(NLSY-C) are used in this analysis, with information from the
interviews in years 1979 to 1996. (At the time of publication, 1998
NLSY data had been released, but this extra interview year has not been
included in the analysis.)

MODEL AND SPECIFICATION
The model presented in this report is a weighted least squares linear
regression model often used in social and economic research.18 A
weighted regression is used to help correct for stratifications made in
the sample design. For example, the NLSY has a low-income oversample
(one of several stratifications) embedded within the survey. Because
the actual percentage of low-income individuals in the population is
relatively small but the survey designers are interested in the
behavior of these individuals in particular, there are more individuals
among the NLSY survey participants as a proportion than there appear in
the overall population. Thus, the survey designers assign a sampling
weight to the individuals in the NLSY to take into consideration the
sampling design.

As noted above, this analysis utilizes data from the children of the
original NLSY; it also utilizes information from their mothers to
ascertain what is associated with a child's time spent in poverty. To
construct the dependent variable, the weighted least squares model uses
data on the percentage of time a child will spend below the official
poverty line from his or her birth up to 1996. The NLSY has poverty
variables for each year the survey was administered, and these annual
data provide the basis for the percent time in poverty dependent
variable. The technical definitions of the independent variables for
the final model (Table 3) are as follows.

Percent Time Spent in a Single-Parent Family: Within the main section
of the NLSY, there is an "event history" database that shows when the
parents married and divorced. In the NLSY-C (child and young adult
questionnaires), there are dates of birth. From these data, we know how
much time, in months, is spent in a two-parent versus a single-parent
family.

Percent Time Spent on AFDC: The time a family spends on government
assistance/Aid to Families with Dependent Children (AFDC) has a direct
bearing on the length of time a child will be in poverty.
Some may argue that the direction of the relationship may be in
question (time on welfare influencing time in poverty versus time in
poverty influencing time in welfare). To validate the model
specification statistically, analysts in the Center for Data Analysis
conducted a series of statistical tests of these hypotheses. The
statistical test included the time on welfare variable first on the
right-hand side of the weighted least squares equation (independent
variable) and the time in poverty variable as the dependent variable on
the left-hand side. This is the manner in which the equation is
originally specified. As a secondary test, the positions of the two
variables were reversed (time in poverty now on the right-hand side and
time on welfare on the left).

The results were revealing. The inference of time on welfare
influencing time in poverty is much more statistically robust, in terms
of explanatory power, than the alternative hypothesis. Thus, the
original specification of time on welfare influencing time in poverty
is retained.

Mother's Math and Verbal Skill Level: In 1980, NLSY sample members were
given the Armed Forces Qualifying Test (AFQT).19 It measures basic
academic ability.

Number of Children Ever Born to Mother: By 1996, the mothers in the
NLSY survey are in their late thirties at least, exceeding their prime
birthing years. This measure should therefore be reasonably close to
the total number of children born to this cohort of mothers.

Number of Years Past Age 15 for First Birth of Mother: This variable
posits the notion that younger mothers typically have more financial
challenges than do older, more established mothers, even if married.
Operationally, this variable is defined by subtracting 15 from the age
of the woman at child-birth. For example, a woman who gave birth to her
first child at 20 would have a variable value of 5. The 15-year-old
figure was chosen because that is the age used on government labor
surveys for entering the labor force.

Regional Variables: These variables measure the percentage of the
child's life spent in different regions.

Lives in a Rural Area: This variable determines whether there exists an
urban-rural gap in poverty in the last year of the survey.

Race Variables: In the first model specification (Table 2), the race of
the mother was added. As noted in the report, race variables are not
statistically significant at any major level, the general standard
being at least a 95 percent level (in this case, the variable was not
even significant at a 90 percent level).20 The variables were therefore
excluded from the final model specification (similarly, the West
regional variable was excluded from the analysis). Significance is
determined by critical t values (also known as a t-test).21
All percentage-based variables (e.g., percent time in poverty, percent
time on AFDC) are represented as whole percentages rather than decimals
(e.g., 24.5 rather than .245) for consistency within the results. Such
a convention, however, does nothing to change the interpretation of the
results.

Eliminating variables from the first model (Table 2) to the second
(Table 3) occurred through an analysis of the t-test. If the
significance level associated with the t value rose above .10 (or,
conversely, fell below 90 percent), the variable was excluded from the
final model. Thus, both of the race variables and the West regional
variable were stricken from the final model.



Endnotes




1. U.S. Bureau of the Census, Poverty in the United States 1999,
Current Population Reports Series P60-210 (Washington, D.C.: U.S.
Government Printing Office, September 2000), pp. 28, 29. The
conventional Census poverty figures are artificially inflated by the
fact that welfare benefits such as Food Stamps, the Earned Income Tax
Credit (EITC), and public housing are not counted as income. If Food
Stamps, the EITC, and public housing subsidies are counted as income,
and Medicaid is partially counted, the poverty rate falls to 21.6
percent for black children and 9.0 percent for white children. Ibid.,
pp. 29, 31. No matter how poverty is calculated, a large disparity
between blacks and whites will remain. For an assessment of the
measurement of poverty, see Robert Rector, Kirk Johnson, and Sarah
Youssef, "The Extent of Material Hardship and Poverty in the United
States," Review of Social Economy, September 1999, pp. 352-387.

2. The National Longitudinal Survey of Youth, produced by the U.S.
Department of Labor's Bureau of Labor Statistics, was first conducted
in 1979. Participants between the ages of 14 and 22 in 1979 were
re-interviewed in subsequent years. See Appendix for more on the
methodology. For additional information on the NLSY, see
http://stats.bls.gov/nlshome.htm.

3. Sally Curtin et al., "Births: Preliminary Data for 1999," National
Vital Statistics Reports, U.S. Department of Health and Human Services,
National Center for Health Statistics, Vol. 48, No. 14 (August 8,
2000), p. 2.

4. In 1997, the AFDC program was renamed the Temporary Assistance to
Needy Families (TANF) program.

5. There were 6,120 children born to NLSY recipients between 1979 and
1996. In 1996, the average age of these
children was nine years.

6. In the NLSY, math and verbal skill or ability level is measured by
the Armed Forces Qualifying Test (AFQT).

7. Variables are provided for South, Northeast, and West. North Central
was the default condition. The variables measure the percent of the
child's life spent in each region.

8.


Recent Heritage Studies
Importing Poverty: Immigration and Poverty in the United States: A Book
of Charts by Robert E. Rector
October 25, 2006


Welfare Reform at 10: Analyzing Welfare Caseload Fluctuations,
1996-2002 by Michael J. New, Ph.D.
August 17, 2006


The Collapse of Marriage and the Rise of Welfare Dependence by Jennifer
A. Marshall, Robert Lerman, Ph.D., Barbara Dafoe Whitehead, Ph.D., Hon.
Wade Horn, Ph.D., Robert Rector
August 15, 2006



Contact An Expert
MEDIA INFORMATION LINE:
(202) 675-1761
Fax: 202.544.6979

MEDIA CONTACTS:

Matthew Streit
Senior Media Associate
E-mail
desk: 202.608.6156
cell: 202.439.0271

Aerica Veazey
International Communications Associate
E-mail
desk: 202.608.6153
cell: 202.439.6175

Elizabeth Fulk
Senior Media Associate
E-mail
desk: 202.608.6157
cell: 202.445.4041

FOR OP-EDS:

Paul Gallagher
Manager of Editorial Services
E-mail
desk: 202.608.6151
cell: 410-591-1123

Sign up to receive PolicyWire
Email:

RSS Feeds | Careers | Site Map | Privacy Policy | Copyright
©2006 The Heritage Foundation General Inquiries: 202.546.4400
Media Relations: 202.675.1761


Fred Bloggs wrote:
In article . com,
says...
Some idiot European wrote earlier about the USA


...the blacks still
live in ghettos.




*All* black Americans live in ghettos??? Have you ever been here????


There are many more white people in poverty in the US than black
people in poverty by a multiple of approximately 3. Do the math. (If
you can)


http://www.press.uchicago.edu/Misc/Chicago/649288.html


"..Much of the research and media attention on African Americans is on
the black poor. Welfare debates, discussions of crime and safety, urban



policy initiatives, and even the cultural uproar over things like rap
music are focused on the situation of poor African Americans. With more



than one in four African Americans living below the official poverty
line (versus approximately one in nine whites), this is a reasonable
and warranted bias. But rarely do we hear the stories of the other
three-fourths, or the majority of African Americans, who may be the
office secretary, the company's computer technician, a project manager
down the hall, or the person who teaches our children. The growth of
the black middle class has been hailed as one of the major triumphs of
the civil rights movement...."

PeeJay


And then our Australian idiot responded with this gem: in response to
the fact that there are more Whites in absolute numbers in poverty in
the US than absolute numbers of Blacks by a "multiple of
approximately 3".

1 in 4 is slightly more than double
1 in 9.

Fred Bloggs

So explain it, peabrain? Why is it so that if you are black you are more
than twice as likely to live in poverty as if you are white?

Source: U.S. Census Bureau
Contact: Housing and Household Economic Statistics Information Staff at
(301)763-3242
Last revised: August 29, 2006
URL: http://pubdb3.census.gov/macro/03200...w01_100_06.htm


[2005 Numbers in thousands]


__________________________________________________ _________________

Number
in
Population poverty %

White alone
Total .................... 235,430 24,872 10.6

Black alone.................. 36802 9168 24.9


Total


Ratio of number of White people in poverty to Black people in poverty
in USA:

24872M/9168M = 2.7

2.7 rounded to whole number = "multiple of approximately 3"

And let's do the numbers on total populations:
235430/36802= 6.4 (approximately). Therefore, out of a population nearly
6.5 times as large, only 2.7 times as many whites are living in poverty
as blacks. Just so you grasp this point peabrain, that means that if you
are black, you have more than twice the likelihood to be born into a
family that lives below the poverty line. Gee that must make you proud
to be a cracker, peabrain.

In article ,
says...
On 2 Dec 2006 13:39:55 -0800, "PJ O'Donovan" wrote:

1 in 4 is slightly more than double
1 in 9.

Fred Bloggs


Ummm... PJ, this idiot is actually correct.

DFM

Sure the idiot is simplistically right to the extent that the axiom
applies

But It's obvious the idiot can't comprehend the comparative absolute
arithmetic effect of lower rates of incidence from that axiom when
applied to an even larger rate of increase in comparable universe
magnititude.

Nice humour, but isn't it supposed to be funny?

It would help if it made sense, but then that's true of anything
peabrain drafts himself.

In article .com,
says...



CONCLUSION
Child poverty is a continuing American problem. This report has
examined the causes of child poverty and the factors that contribute to
racial differences in child poverty. The analysis reveals that welfare
dependence and single parenthood are the major underlying factors
producing child poverty. Race per se is not a significant factor in
directly increasing child poverty: Black children have the same poverty
rate as white children who are raised in similar circumstances. Black
children are more likely to be poor than white children primarily
because they are more likely to live in single-parent homes and to be
on welfare.

Those who are sincerely interested in reducing child poverty must focus
on reducing the principal causes of that poverty: welfare dependence
and single parenthood. Those interested in reducing the current
disparities in black and white poverty must focus on altering the
principal causes of that disparity: the higher levels of single
parenthood and dependence among blacks.

Absolutely correct, except that it doesn't answer the question of why
there are so many more blacks living in poverty than whites, does it
peabrain? Nor does it explain how the "1 in 9" whites living in poverty
is a larger proportion than the "1 in 4" of the earlier report you
regurgitated.

Next time you're in touch with Party Central, you'd best make sure they
send explanatory notes along with their list of approved URLs. You don't
seem to be able to manage sufficient resources to raise your sights
above your own feet.


Robert Rector is a Senior Research Fellow in Welfare and Family Issues,
Kirk A. Johnson is a Senior Policy Analyst in the Center for Data
Analysis, and Patrick F. Fagan is William H. G. FitzGerald Senior
Fellow in Family and Cultural Issues at The Heritage Foundation.


--------------------------------------------------------------------------------

APPENDIX: TECHNICAL SPECIFICATIONS

DATA
Data used in this analysis are taken from the National Longitudinal
Survey of Youth (NLSY), produced by the U.S. Department of Labor's
Bureau of Labor Statistics. The NLSY is a sample of 12,686 individuals
between the ages of 14 and 22 in 1979. Every subsequent year or two,
these individuals are re-interviewed and asked a series of follow-up
questions. Data are collected on labor force participation, marriage,
fertility, drug use, education, and program participation issues, among
others. The answers to these questions help researchers ascertain the
demographic and economic choices of young people born in the late 1950s
to early 1960s.

Since marriage and fertility issues are of great importance to young
people, a variety of questions on specific dates and times of marriage,
divorce, and childbirth are asked. As the children of the NLSY sample
aged, separate questions were asked beginning in 1986. Data from both
the original NLSY cohort and the NLSY child and young adult data set
(NLSY-C) are used in this analysis, with information from the
interviews in years 1979 to 1996. (At the time of publication, 1998
NLSY data had been released, but this extra interview year has not been
included in the analysis.)

MODEL AND SPECIFICATION
The model presented in this report is a weighted least squares linear
regression model often used in social and economic research.18 A
weighted regression is used to help correct for stratifications made in
the sample design. For example, the NLSY has a low-income oversample
(one of several stratifications) embedded within the survey. Because
the actual percentage of low-income individuals in the population is
relatively small but the survey designers are interested in the
behavior of these individuals in particular, there are more individuals
among the NLSY survey participants as a proportion than there appear in
the overall population. Thus, the survey designers assign a sampling
weight to the individuals in the NLSY to take into consideration the
sampling design.

As noted above, this analysis utilizes data from the children of the
original NLSY; it also utilizes information from their mothers to
ascertain what is associated with a child's time spent in poverty. To
construct the dependent variable, the weighted least squares model uses
data on the percentage of time a child will spend below the official
poverty line from his or her birth up to 1996. The NLSY has poverty
variables for each year the survey was administered, and these annual
data provide the basis for the percent time in poverty dependent
variable. The technical definitions of the independent variables for
the final model (Table 3) are as follows.

Percent Time Spent in a Single-Parent Family: Within the main section
of the NLSY, there is an "event history" database that shows when the
parents married and divorced. In the NLSY-C (child and young adult
questionnaires), there are dates of birth. From these data, we know how
much time, in months, is spent in a two-parent versus a single-parent
family.

Percent Time Spent on AFDC: The time a family spends on government
assistance/Aid to Families with Dependent Children (AFDC) has a direct
bearing on the length of time a child will be in poverty.
Some may argue that the direction of the relationship may be in
question (time on welfare influencing time in poverty versus time in
poverty influencing time in welfare). To validate the model
specification statistically, analysts in the Center for Data Analysis
conducted a series of statistical tests of these hypotheses. The
statistical test included the time on welfare variable first on the
right-hand side of the weighted least squares equation (independent
variable) and the time in poverty variable as the dependent variable on
the left-hand side. This is the manner in which the equation is
originally specified. As a secondary test, the positions of the two
variables were reversed (time in poverty now on the right-hand side and
time on welfare on the left).

The results were revealing. The inference of time on welfare
influencing time in poverty is much more statistically robust, in terms
of explanatory power, than the alternative hypothesis. Thus, the
original specification of time on welfare influencing time in poverty
is retained.

Mother's Math and Verbal Skill Level: In 1980, NLSY sample members were
given the Armed Forces Qualifying Test (AFQT).19 It measures basic
academic ability.

Number of Children Ever Born to Mother: By 1996, the mothers in the
NLSY survey are in their late thirties at least, exceeding their prime
birthing years. This measure should therefore be reasonably close to
the total number of children born to this cohort of mothers.

Number of Years Past Age 15 for First Birth of Mother: This variable
posits the notion that younger mothers typically have more financial
challenges than do older, more established mothers, even if married.
Operationally, this variable is defined by subtracting 15 from the age
of the woman at child-birth. For example, a woman who gave birth to her
first child at 20 would have a variable value of 5. The 15-year-old
figure was chosen because that is the age used on government labor
surveys for entering the labor force.

Regional Variables: These variables measure the percentage of the
child's life spent in different regions.

Lives in a Rural Area: This variable determines whether there exists an
urban-rural gap in poverty in the last year of the survey.

Race Variables: In the first model specification (Table 2), the race of
the mother was added. As noted in the report, race variables are not
statistically significant at any major level, the general standard
being at least a 95 percent level (in this case, the variable was not
even significant at a 90 percent level).20 The variables were therefore
excluded from the final model specification (similarly, the West
regional variable was excluded from the analysis). Significance is
determined by critical t values (also known as a t-test).21
All percentage-based variables (e.g., percent time in poverty, percent
time on AFDC) are represented as whole percentages rather than decimals
(e.g., 24.5 rather than .245) for consistency within the results. Such
a convention, however, does nothing to change the interpretation of the
results.

Eliminating variables from the first model (Table 2) to the second
(Table 3) occurred through an analysis of the t-test. If the
significance level associated with the t value rose above .10 (or,
conversely, fell below 90 percent), the variable was excluded from the
final model. Thus, both of the race variables and the West regional
variable were stricken from the final model.



Endnotes




1. U.S. Bureau of the Census, Poverty in the United States 1999,
Current Population Reports Series P60-210 (Washington, D.C.: U.S.
Government Printing Office, September 2000), pp. 28, 29. The
conventional Census poverty figures are artificially inflated by the
fact that welfare benefits such as Food Stamps, the Earned Income Tax
Credit (EITC), and public housing are not counted as income. If Food
Stamps, the EITC, and public housing subsidies are counted as income,
and Medicaid is partially counted, the poverty rate falls to 21.6
percent for black children and 9.0 percent for white children. Ibid.,
pp. 29, 31. No matter how poverty is calculated, a large disparity
between blacks and whites will remain. For an assessment of the
measurement of poverty, see Robert Rector, Kirk Johnson, and Sarah
Youssef, "The Extent of Material Hardship and Poverty in the United
States," Review of Social Economy, September 1999, pp. 352-387.

2. The National Longitudinal Survey of Youth, produced by the U.S.
Department of Labor's Bureau of Labor Statistics, was first conducted
in 1979. Participants between the ages of 14 and 22 in 1979 were
re-interviewed in subsequent years. See Appendix for more on the
methodology. For additional information on the NLSY, see
http://stats.bls.gov/nlshome.htm.

3. Sally Curtin et al., "Births: Preliminary Data for 1999," National
Vital Statistics Reports, U.S. Department of Health and Human Services,
National Center for Health Statistics, Vol. 48, No. 14 (August 8,
2000), p. 2.

4. In 1997, the AFDC program was renamed the Temporary Assistance to
Needy Families (TANF) program.

5. There were 6,120 children born to NLSY recipients between 1979 and
1996. In 1996, the average age of these
children was nine years.

6. In the NLSY, math and verbal skill or ability level is measured by
the Armed Forces Qualifying Test (AFQT).

7. Variables are provided for South, Northeast, and West. North Central
was the default condition. The variables measure the percent of the
child's life spent in each region.

8.


Recent Heritage Studies
Importing Poverty: Immigration and Poverty in the United States: A Book
of Charts by Robert E. Rector
October 25, 2006


Welfare Reform at 10: Analyzing Welfare Caseload Fluctuations,
1996-2002 by Michael J. New, Ph.D.
August 17, 2006


The Collapse of Marriage and the Rise of Welfare Dependence by Jennifer
A. Marshall, Robert Lerman, Ph.D., Barbara Dafoe Whitehead, Ph.D., Hon.
Wade Horn, Ph.D., Robert Rector
August 15, 2006



Contact An Expert
MEDIA INFORMATION LINE:
(202) 675-1761
Fax: 202.544.6979

MEDIA CONTACTS:

Matthew Streit
Senior Media Associate
E-mail
desk: 202.608.6156
cell: 202.439.0271

Aerica Veazey
International Communications Associate
E-mail
desk: 202.608.6153
cell: 202.439.6175

Elizabeth Fulk
Senior Media Associate
E-mail
desk: 202.608.6157
cell: 202.445.4041

FOR OP-EDS:

Paul Gallagher
Manager of Editorial Services
E-mail
desk: 202.608.6151
cell: 410-591-1123

Sign up to receive PolicyWire
Email:

RSS Feeds | Careers | Site Map | Privacy Policy | Copyright
©2006 The Heritage Foundation General Inquiries: 202.546.4400
Media Relations: 202.675.1761


Fred Bloggs wrote:
In article . com,
says...
Some idiot European wrote earlier about the USA


...the blacks still
live in ghettos.




*All* black Americans live in ghettos??? Have you ever been here????


There are many more white people in poverty in the US than black
people in poverty by a multiple of approximately 3. Do the math. (If
you can)


http://www.press.uchicago.edu/Misc/Chicago/649288.html


"..Much of the research and media attention on African Americans is on
the black poor. Welfare debates, discussions of crime and safety, urban



policy initiatives, and even the cultural uproar over things like rap
music are focused on the situation of poor African Americans. With more



than one in four African Americans living below the official poverty
line (versus approximately one in nine whites), this is a reasonable
and warranted bias. But rarely do we hear the stories of the other
three-fourths, or the majority of African Americans, who may be the
office secretary, the company's computer technician, a project manager
down the hall, or the person who teaches our children. The growth of
the black middle class has been hailed as one of the major triumphs of
the civil rights movement...."

PeeJay


And then our Australian idiot responded with this gem: in response to
the fact that there are more Whites in absolute numbers in poverty in
the US than absolute numbers of Blacks by a "multiple of
approximately 3".

1 in 4 is slightly more than double
1 in 9.

Fred Bloggs

So explain it, peabrain? Why is it so that if you are black you are more
than twice as likely to live in poverty as if you are white?

Source: U.S. Census Bureau
Contact: Housing and Household Economic Statistics Information Staff at
(301)763-3242
Last revised: August 29, 2006
URL: http://pubdb3.census.gov/macro/03200...w01_100_06.htm


[2005 Numbers in thousands]


__________________________________________________ _________________

Number
in
Population poverty %

White alone
Total .................... 235,430 24,872 10.6

Black alone.................. 36802 9168 24.9


Total


Ratio of number of White people in poverty to Black people in poverty
in USA:

24872M/9168M = 2.7

2.7 rounded to whole number = "multiple of approximately 3"

And let's do the numbers on total populations:
235430/36802= 6.4 (approximately). Therefore, out of a population nearly
6.5 times as large, only 2.7 times as many whites are living in poverty
as blacks. Just so you grasp this point peabrain, that means that if you
are black, you have more than twice the likelihood to be born into a
family that lives below the poverty line. Gee that must make you proud
to be a cracker, peabrain.

In article ,
says...
In article .com,
says...



CONCLUSION
Child poverty is a continuing American problem. This report has
examined the causes of child poverty and the factors that contribute to
racial differences in child poverty. The analysis reveals that welfare
dependence and single parenthood are the major underlying factors
producing child poverty. Race per se is not a significant factor in
directly increasing child poverty: Black children have the same poverty
rate as white children who are raised in similar circumstances. Black
children are more likely to be poor than white children primarily
because they are more likely to live in single-parent homes and to be
on welfare.

Those who are sincerely interested in reducing child poverty must focus
on reducing the principal causes of that poverty: welfare dependence
and single parenthood. Those interested in reducing the current
disparities in black and white poverty must focus on altering the
principal causes of that disparity: the higher levels of single
parenthood and dependence among blacks.
This should read:
Absolutely correct, except that it doesn't answer the question of why
there are so many more blacks living in poverty than whites, does it
peabrain? Nor does it explain how the "1 in 9" whites living in poverty
is a larger proportion than the "1 in 4" blacks of the earlier report you
regurgitated.

Next time you're in touch with Party Central, you'd best make sure they
send explanatory notes along with their list of approved URLs. You don't
seem to be able to manage sufficient resources to raise your sights
above your own feet.

Source: U.S. Census Bureau
Contact: Housing and Household Economic Statistics Information Staff at
(301)763-3242
Last revised: August 29, 2006
URL: http://pubdb3.census.gov/macro/03200...w01_100_06.htm


[2005 Numbers in thousands]


__________________________________________________ _________________

Number
in
Population poverty %

White alone
Total .................... 235,430 24,872 10.6

Black alone.................. 36802 9168 24.9


Total


Ratio of number of White people in poverty to Black people in poverty
in USA:

24872M/9168M = 2.7

2.7 rounded to whole number = "multiple of approximately 3"

And let's do the numbers on total populations:
235430/36802= 6.4 (approximately). Therefore, out of a population nearly
6.5 times as large, only 2.7 times as many whites are living in poverty
as blacks. Just so you grasp this point peabrain, that means that if you
are black, you have more than twice the likelihood to be born into a
family that lives below the poverty line. Gee that must make you proud
to be a cracker, peabrain.