urbs 350 lec 1

URBS
350
 Demography
and
Popula8on
 Growth

Abhishek
Tiwari
 Fall
2010


Warm‐up
Ques8ons

How
many
is
too
many,
i.e.
when
is
an
area
 overpopulated?
 What
do
we
mean
by
popula8on
composi8on
/
 structure
and
why
is
it
important?


© 2006 Population Reference Bureau

Malthus

•  Popula8on
growth
is
geometric
 •  Food
supply
growth
is
arithme8c

 •  Popula8on
will
grow
un8l
it
outstrips
the
ability
of
 the
land
to
provide
sufficient
food
 •  Famine,
diseases,
etc
will
ensue
and
popula8on
will
 fall
 •  Did
not
advocate
programs
to
help
the
poor
–
 poverty
is
inevitable
 •  Supported
“moral
restraint”
–
late
marriage
without
 premarital
sex

© 2006 Population Reference Bureau

Population Growth

Crisis Point

Resour ces

© 2006 Population Reference Bureau

Views
on
Popula8on
Growth

•  Malthus
‐‐
Pop
Growth
is
ul8mately
bad
 •  Economists
–
Popula8on
growth
leads
to
 economic
growth

 •  Durkheim
–
popula8on
growth
leads
to
 division
of
labor
 •  Marx
/
Engels
–
the
impact
of
pop
growth
 depends
on
the
geopoli8cal
context;
 capitalism
causes
poverty

© 2006 Population Reference Bureau

•  Demography
is
the
study
of
people,
 specifically
the
impact
of
popula8on
and
 changes
in
the
popula8on.

 •  Demographic
analyses
can
help
us
see
the
 rela8onship
between
different
popula8on
 characteris8cs
(e.g.
age
distribu8on
and
crime, 
 income
and
fer8lity,
immigrant
status
and
 mortality,
Socioeconomic
status
and
 happiness)

© 2006 Population Reference Bureau

•  As
world
popula8on
increases
and
levels
of
 urbaniza8on
increase,
there
are
increasingly
 fewer
areas
that
are
not
impacted
by
human
 popula8ons.

 •  Demography
helps
us
describe
popula8on
 level
changes
and
their
impact
on
the
social/ cultural
fabric
of
different
regions.




© 2006 Population Reference Bureau

•  In
many
instances
demographic
shi_s
have
a
 similar
impact
on
disparate
human
 popula8ons.
However,
culture,
geography
and
 other
factors
o_en
mediate
these
impacts
 with
some8mes
surprising
results.

 For
example,
rising
incomes
tend
to
reduce
birth
 rates,
though
this
has
not
been
the
case
in
 many
countries
in
the
middle
east.


© 2006 Population Reference Bureau

Demographic
and
Social
Policy
/ Planning 

•  Demographic
changes
both
impel
policy
(and
social
changes)
and
are
the
result
of
 policy
changes.

 
 For
example,
China’s
1‐Child
policy
has
helped
reduce
popula8on
growth
in
 China,
but
also
created
a
large
surplus
of
unmarried
males.
The
government
will
 likely
have
to
take
several
steps
to
address
this
issue
(e.g.
ease
1‐child
policy,
allow
 for
selec8ve
migra8on
of
women
from
other
countries,
etc.)


Also,
in
the
US,
demographic
trends
are
used
for:
 •  Congressional
appor8onment
and
distric8ng
 •  Provision
of
public
services
 •  Educa8onal
planning
 •  Assessing
environmental
impacts


© 2006 Population Reference Bureau

Demography
and
Business 

•  Marke8ng
products
and
services
(e.g.
based
on
age
 groups)
 •  Assessing
the
local
business
poten8al
of
companies,
 products
(e.g.
Target
might
conduct
a
demographic
 analysis
of
a
region
before
opening
a
store)
 •  Studying
the
business/investment
poten8al
of
a
 certain
area
(e.g.
developers
might
conduct
a
 demographic
analysis
before
inves8ng
in
 commercial/residen8al
property
in
a
certain
area)

© 2006 Population Reference Bureau

Basic
Demographic
Tools 


© 2006 Population Reference Bureau

Counts

•  Counts
–
Measurement
results
reported
in
 absolute
numbers.

Counts
are
8me
and
place
 specific.
 For
example:
X
number
of
people
live
in
 Northridge.



Rates






How
o_en
a
par8cular
demographic
event
occurrs
in
a
 popula8on
of
interest
within
a
specific
period
of
8me.
 Alterna8vely,
the
frequency
of
a
demographic
event
in
a
 given
8me
period
divided
by
the
number
of
people
who
 were
“at
risk”
for
that
demographic
event
in
the
8me
 period
of
interest.

 For
example:
The
job
placement
rate
of
CSU
Northridge
can
 be

calculated
by
dividing
the
number
of
gradua8ng
 students
in
a
given
year
who
are
looking
for
employment
 and
find
work
by
the
total
number
of
graduates
who
are
 looking
for
employment:

 #
of
students
finding
full
8me
employment
a_er
 gradua8on
/
Total
#
of
graduates
who
are
looking
for
 employment


Ra8os

•  The
rela8onship
of
one
popula8on
group
to
 another
or
to
the
en8re
popula8on.
We
can
 express
ra8os
of
counts,
rates,
or
percentages.
 Ra8os
can
also
help
us
compare
two
groups
 and
help
us
evaluate
the
rela8ve
risk
of
a
 par8cular
group
vis‐à‐vis
another.



Rates
and
Ra8o
Example 

Using
our
earlier
example:
1000
student
graduates
of
CSUN
in
2009
were
 looking
for
work.
Of
these
400
were
women.
Of
the
women
graduates,
 360
found
work
and
270
of
the
men
graduates
found
work.
What
is
the
 overall
job
placement
rate
for
both
men
and
women;
and
what
is
ra8o
of
 the
job
placement
rate
for
women
to
men
(and
what
can
we
infer
about
 the
likelihood
of
finding
work
as
a
func8on
of
gender).


 Total
#
finding
work
=
270
+
360
=
630



Job
placement
rate=630/100=63%
 Total
#
of
women
who
found
work/
Total
women
looking
for
work
 360/400=90%
 Total
#
of
men
who
found
work
/
Total
men
looking
for
work:

 
 270/600=45%
 Ra8o
of
job
placement
rate
(Men
to
Women):
90
to
45
(2:1).

 Interpreta8on:
Women
were
2
8mes
more
likely
to
find
work.


© 2006 Population Reference Bureau

WORLD
POPULATION
FACTS


Trends
in
Urbaniza8on,
by
Region

Urban Population
Percent

Source: United Nations, World Urbanization Prospects: The 2003 Revision (medium scenario), 2004.

World
Popula8on
Growth
Through
 Billions History

12 11 10 9 Old Stone 7 Age 8 6 5 4 3 2 1 Black Death — The Plague 1950 1900 1800 1975 New Stone Age Bronze Age Iron Age Modern Age Middle Ages 2000 Future 2100

1+ million 7000 6000 5000 4000 3000 2000 1000 A.D. A.D. A.D. A.D. A.D. A.D. years B.C. B.C. B.C. B.C. B.C. B.C. B.C. 1 1000 2000 3000 4000 5000

Source: Population Reference Bureau; and United Nations, World Population Projections to 2100 (1998).

World
Popula8on
Growth,
in
Billions

Number of years to add each billion (year)
All of Human History 130 (1930) 30 (1960) 15 (1975) 12 (1987) 12 (1999) 14 (2013) 14 (2027) 21 (2048) (1800)

Sources: First and second billion: Population Reference Bureau. Third through ninth billion: United Nations, World Population Prospects: The 2004 Revision (medium scenario), 2005.

Projected
Popula8on
Change,
by

Country

Percent Population Change, 2005-2050

Source: Population Reference Bureau, 2005 World Population Data Sheet.

Largest
Ci8es,
Worldwide

Millions
1950 2000 2015

Source: United Nations, World Urbanization Prospects: The 2003 Revision (medium scenario), 2004.

The
Classic
Demographic
Transi8on
Stages


Birth
and
Death
Rates,
Worldwide

Rates of birth, death, and natural increase per 1,000 population

Natural Increase

Source: United Nations, World Population Prospects: The 2004 Revision, 2005.

2009,
Selected
Indicators
(World)

Total
Popula8on
–
6.8
billion
 Total
fer8lity
rate
–
2.6

 IMR
–
46
per
1000
 48%
are
living
on
less
than
$2
/
day
 Younger
popula8ons
will
become
increasingly
 concentrated
in
Africa
and
Asia
(1950
–
Asia
(54%),
 Africa
(9%);
Asia
(53%),
Africa
(29%)
 •  %
of
popula8on
<
15
=
27%
and
%
of
pop
>
54
=

8

 •  Dependency
ra8o
=
(27+8)/
65
~
1
to
2
 •  •  •  •  • 

Demographic
Indicators

Popula8on
/
Density
 Popula8on
growth
–
fer8lity,
mortality,
immigra8on
 Age
structure

 Race
/
Ethnicity
composi8on
 Household
/
Family
size,
household
composi8on,
living
 arrangement
 •  Educa8onal
achievement
(e.g.
%
with
HS
degree
or
BA/ BS)
 •  Economic
indicators
(several)
–
GDP,
Per
capita,
Poverty
 rate,
Occupa8ons
/
Sectors,
Household
Income
 •  •  •  •  • 

Other
Demographic
indicators
 

•  •  •  •  •  •  •  •  Tenure
(homeownership,
renters)
 Marital
status
 Languages
 %
Homeless
 Health
status
 Crime
 Job
sectors
and
employment
 Travel
behavior


© 2006 Population Reference Bureau

Age
Structure


Age
structure
or
distribu8on

•  Propor8on
of
popula8on,
by
sex,
that
falls
into
a
par8cular
age
range.

 •  Tells
us
whether
the
popula8on
is
young,
aging
or
somewhere
in
 between.

 Important
implica8ons
for
economic
vitality
of
a
region
(Why?)
 •  Propor8on
of
popula8on
that
is
of
working
age
(those
between
16
and
 65)
 •  Age
dependency
ra8o
–
ra8o
of
working
age
to
non
working
age
(e.g.
6
 people
of
working
age
to
1
non
working
)


•  Other
implica8ons


  decreasing
ra8o
can
be
problema8c
(as
there
are
fewer
working
age
to
support
a
 non
working
popula8on.
   Countries
with
decreasing
fer8lity
and
increasing
life
expectancy
(e.g.
Japan)
 have
shrinking
dependency
ra8os,
crea8ng
a
huge
public
policy
dilemma
   Example:
Too
many
young,
unemployed
people
may
lead
to
more
crime



Age
Distribu8on
of
the
World’s
Popula8on

Population Structures by Age and Sex, 2005
Millions

Less Developed Regions Age
80+ 75-79 70-74 65-69 60-64 55-59 50-54 45-49 40-44 35-39 30-34 25-29 20-24 15-19 10-14 5-9 0-4

More Developed Regions

Male

Female

Male

Female

Source: United Nations, World Population Prospects: The 2004 Revision, 2005.

Fer8lity


The total fertility rate is the average number of children that would be born to a woman by the time she ended her childbearing years (15-49). The TFR assumes that the woman would conform to the age-specific fertility rates for a given year.

Fer8lity


•  General
fer)lity
rate:
#
of
live
births
/
#
of
Women
between
15‐49
X
K
 •  Age
specific
fer)lity
rate:
#
of
live
birth
to
women
between
___
/
#
of
 women
between
_____
X
K
 •  Crude
Birth
Rate:
Total
#
of
births
/
Total
Popula8on
X
K

 •  Fer8lity
rates
are
declining
everywhere.
Why?
 •  What
are
the
implica8ons
of
low
fer8lity
rates?


10
Places
With
the
Lowest
Total
Fer8lity
Worldwide

Average number of children per woman, 2000-2005

Source: United Nations, World Population Prospects: The 2004 Revision, 2005.

Diverging
Trends
in
Fer8lity
 Reduc8on
 

Average number of children per woman

Source: United Nations, World Population Prospects: The 2004 Revision, 2005.

Mortality


Mortality

•  Mortality
Rate:
#
of
deaths
/
Total
Popula8on
X
K

 •  Disease
Specific
Mortality
Rate:
#
of
deaths
from
a
 disease
/
Total
Pop
with
Disease
X
K
 •  Infant
mortality
rates:
#
of
infant
deaths
(<1)
/
Total
Live
 births
X
K
 •  Maternal
mortality
ra)o:
#
of
maternal
deaths
/
Total
#
 of
live
births
X
K
 Note:
K
is
a
constant
such
as
10,000
or
100,000.
We
 mul8ply
by
K
to
standardize
our
calcula8ons
so
rates
can
 be
express
in
terms
of

..per
10,000
or
per
100,000


Life
Expectancy

•  Life
expectancy:
average
number
of
addi8onal
years
 a
person
could
expect
to
live
if
the
age‐specific
death
 rates
for
a
given
year
prevailed
for
the
rest
of
his/her
 life.

•  Life
expectancies
are
possible
for
every
age
 
 For
example,
a
person
at
20
would
have
a
certain
life
 expectancy
(i.e.
addi8onal
number
of
years
they
can
be
 expected
to
live
 •  Life
expectancy
at
birth
(LEB)
is
a
commonly
reported
sta8s8c
 (in
the
US
LEB
is
around
79.
This
means
that

a
baby
born
 today
is
expected
to
live
8ll
79)


Life Expectancy at Birth, in Years

Trends
in
Life
Expectancy,
by
Region


Source: United Nations, World Population Prospects: The 2004 Revision (medium scenario), 2005.

Literacy Rates, by Sex, 2000-2004
Percent

Adult
Literacy,
by
Region


Source: UNESCO Institute for Statistics: accessed online at www.uis.unesco.org/TEMPLATE/html/Exceltables/education/ Literacy_Regional_April2006.xls on May 21, 2006.

Ra8o
of
Workers
to
Dependents,
by
 Region


Note: People 15 to 64 are considered to be workers; people 14 and younger and those over 65 are considered to be dependents. Source: United Nations, World Population Prospects: The 2004 Revision (medium scenario), 2005.

Availability of Doctors, Selected Countries
1997-2004*
Physicians per 1,000 people

* Data are for the most recent year available for each country. Source: World Bank, World Development Indicators 2006.

Changes
in
Household
Structure
 during
the
last
century


Households

•  Smaller
families

 •  Erosion
of
joint
families
 •  Increase
in
headship
rates
among
young
 adults
 •  Increase
in
single‐person
households
 •  Greater
propor8on
of
two‐income
households
 •  More
discre8onary
income
 •  Greater
gender
equality
and
more
female
 headed
households


Marriage

•  (before)
Union
of
two
families

(now)
union
 of
two
individuals
 •  Decline
in
Polygamy

 •  Reduc8on
in
domes8c
violence
 •  Increase
in
cohabita8on
 •  Delay
in
marriage
age


 •  Delay
in
age
when
having
first
child
 •  Increase
in
divorce,
ini8ated
by
both
genders


Children

•  As
families
moved
away
from
agriculture
the
 value
of
addi8onal
children
has
declined
 •  As
the
produc8ve
capacity
of
children
has
 reduced,
as
they
no
longer
can
be
used
as
 labor,
it
does
not
make
sense
to
have
more
 children
 •  Addi8onally,
reduc8ons
in
infant
and
child
 mortality
obviate
the
need
to
have
‘surplus’
 kids



Women

•  Fer8lity
change
 •  Increasing
age
for
first
marriage
(min.
 marriage
age
in
many
countries)
 •  Increasing
age
for
first
birth
 •  Increasing
labor/economic
par8cipa8on
 •  Increasing
literacy
levels
 •  Greater
number
of
female
headed
households
 •  Marriage
dissolu8on


Elderly

•  Increase
in
number
of
elderly
and
propor8on
of
 elderly
(i.e.
the
elderly
represent
an
increasing
 propor8on
of
the
popula8on)
 •  Greater
morbidity
burden
due
to
age
 •  Increasing
strain
on
working
age
popula8on
to
 care
for
the
elderly,
as
there
are
more
elderly
per
 working
age
person
 •  Reduc8on
in
quality
and
quan8ty
of
care
 provided
for
the
elderly,
as
younger
people
move
 away,
and
there
are
less
younger
people
due
to
 reduc8ons
in
fer8lity.



Urbaniza8on
Impacts

•  Encourage
nuclea8on
of
households
are
large
 households
are
untenable,
par8cularly
among
 low‐income
groups
with
limited
housing
 op8ons
in
an
urban
area
 •  Increases
exposure
to
pollu8on,
violence,
 stress,
unhealthy
foods
 •  Increases
exposure
to
non‐tradi8onal
ways
of
 living


Case
Study
Japan


Women
in
Japanese
Society

•  Japanese
women’s
par8cipa8on
in
poli8cs
and
 the
economy
(though
to
a
lesser
extent)
is
not
 tantamount
to
men
 •  Japan
ranks

43rd
in
the
UNDP
Gender
 Empowerment
measures,
though
its
11th
in
 the
overall
human
development
index

 •  As
more
women
have
joined
the
workforce
 there
has
been
a
decline
in
marriage
and
birth
 rates


Post‐war
family
system

•  Housewife
role
for
women
 •  Monogamously
married
with
2‐3
children
 •  Gendered
division
of
labor
 •  Provided
the
founda8on
on
which
post‐war
 economic
growth
flourished


Family
system
today

•  Family
forma8on
is
not
necessarily
seen
as
an
 impera8ve
 •  Survey
show
that
the
idea
of
roman8c
love
in
 marriage
is
important;
many
Japanese
indicate
 they
are
wai8ng
for
an
ideal
partner
 •  Since
Japanese
only
have
children
when
married
 (unlike
other
post‐industrial
countries),
and
 marriage
rates
are
low,
their
TRF
is
very
low
 •  Mothers
do
not
encourage
their
daughters
to
 follow
in
their
footsteps


Declining
TFR

•  Declines
in
fer8lity
mirror
that
of
other
post‐ industrial
countries
 •  However,
Japan
has
low
out‐of‐wedlock
births
 •  1970
–
2.1

 •  1995
–
1.42
 •  2004
–
1.29


A
high
stakes
game

•  High
demand
from
young
mothers
for
 coopera8on
from
their
husbands
for
child
 rearing
 •  Japanese
who
have
high
expecta8ons
for
their
 children’s
educa8on
tend
to
postpone
or
 abandon
the
idea
of
having
children
 •  Family
forma8on
is
a
high
stakes
project
that
 people
only
undertake
if
assured
of
a
high
 change
of
success
(contrast
with
US)


Ques8ons
to
consider

Do
women
bear
a
double
burden
in
a
modern
 capitalist
system,
as
they
are
expected
to
be
 individual
economic
agents
(just
like
men)
and
 also
shoulder
the
reproduc8ve
burden?
 Should
the
Japanese
encourage
out‐of‐wedlock
 birth?
 Should
those
who
choose
not
to
have
kids
pay
a
 premium
to
those
who
have
kids?
 What
about
paying
people
to
have
and
raise
 children?



IMMIGRATION


© 2006 Population Reference Bureau


Rural
‐
Urban

•  Between
1950
and
1995,
the
propor8on
of
 people
living
in
ci8es
increased
from
29%
to
 43%;
today
more
than
half
live
in
ci8es
 •  Massive
rural
to
urban
migra8on;
some
ci8es
 in
Asia
have
an
influx
of
nearly
a
million
 people
annually
 •  However,
In
some
areas
because
of
rising
 prices
in
urban
areas
the
trend
has
been
 reversed

© 2006 Population Reference Bureau

Ques8on
to
Consider

•  If
everybody
lives
in
ci8es,
who
will
produce
 the
food?
And
other
natural
resources?


© 2006 Population Reference Bureau

Causes
of
migra8on
‐
Economics

•  Structural
reordering
of
economies
–
the
 globalized
economy
favors
urban
areas
(i.e.
 ci8es
have
jobs)
 •  In
many
countries
the
removal
of
subsidies
 has
reduced
the
economic
viability
of
farming
 (though
not
as
much
in
the
US,
where
farmers
 con8nue
to
benefit
from
government
 largesse).


© 2006 Population Reference Bureau

Causes
of
Migra8on
‐
Economics

•  Work
transi8on
for
young
people
in
developed
 countries
is
delayed
because
of
higher
 educa8on;
in
contrast,
in
developing
countries
 young
people
are
more
likely
to
work
at
 younger
ages,
and
o_en
in
the
informal
or
 illegal
sector.



© 2006 Population Reference Bureau

Causes
of
migra8on
‐
Resources

•  Lack
of
access
to
environmental
resources
 (e.g.
forest
materials)
because
of
government
 policies

 •  Resource
deple8on
in
rural
areas
(e.g.
soil
 degrada8on,
deple8on
of
aquifers,
flooded
 farmlands,
deser8fica8on)


© 2006 Population Reference Bureau

Causes
of
Migra8on
‐
Conflict

•  Forced
migra8on
by
the
government
or
other
 groups
 •  Role
of
violence,
including
genocide
 •  Impact
of
conflict
on
natural
resources


© 2006 Population Reference Bureau

Issues

•  In
many
developing
countries
one
or
a
few
 urban
areas
account
for
the
majority
of
the
 GDP?
Why
might
this
be
a
problem?
 •  Out
migra8on
from
rural
areas
and
dropping
 fer8lity
rates
can
leave
countries
vulnerable
to
 global
economic
shocks
(akin
to
pu}ng
all
of
 your
eggs
in
one
basket)
Think
about
what
is
 happening
in
Iceland
today
(courtesy
of
the
 banking
sector)

© 2006 Population Reference Bureau

Issues

•  Uneven
development
trajectories
create
 economic
polariza8on.
In
many
instances
 remi~ances
and
urban‐rural
capital
flows
have
 failed
to
s8mulate
rural
development,
thus
 crea8ng
highly
uneven
development
 •  Poverty
and
concomitant
problems
o_en
 increase
in
urban
areas
because
of
in‐ migra8on

© 2006 Population Reference Bureau

Popula8on
Growth


© 2006 Population Reference Bureau

•  To
understand
popula8on
growth
and
decline
 we
need
to
understand
births,
deaths
and
 migra8on
and
the
processes
that
undergird
 these.



© 2006 Population Reference Bureau

A
primer
on
popula8on
growth

•  Popula8on
change
=
Births
–
Deaths
+
In
 migra8on
–
out
migra8on
 •  Births
are
determined
by
fer8lity
rates
 •  Deaths
are
determined
by
mortality
rates
 •  Migra8on
should
include
legal
and
illegal
 immigra8ons
(also
known
as
the
foreign
born)


© 2006 Population Reference Bureau

Popula8on
Forecas8ng

•  Linear
extrapola8on
 •  Shi_‐Share
 •  Geometric
expansion
 •  Exponen8al
Expansion
 •  Cohort
Component
(used
by
the
Census)


© 2006 Population Reference Bureau

Cohort
Component,
Need:



•  Age/Sex
specific
survival
rates

 •  Age/Sex
specific
birth
rates
 •  Age/Sex
specific
net
migra8on
rates


© 2006 Population Reference Bureau

© 2006 Population Reference Bureau

Simple
extrapola8on
methods

•  Small
data
requirements
 •  Simple
mathema8cal
structures
 •  Easy
to
apply
 •  Can
be
used
when
few
historical
data
are
 available


© 2006 Population Reference Bureau

Linear
Extrapola8on




Assumes
that
the
popula8on
will
increase
or
 decrease
by
the
same
number
of
persons
in
 each
future
year
as
the
average
increase
in
the
 base
period.

 Example:
Pop
increase
between
2000‐2001
will
 be
the
same
as
the
average
annual
increase
in
 the
years
between
1990‐2000.


© 2006 Population Reference Bureau

Geometric


Assumes
that
the
popula8on
will
grow
at
the
same
 annual
percentage
rate
during
the
projec8on
horizon
 as
the
base
period.

 The
annual
geometric
growth
rate
(r)
can
be
 calculated
as:

 
 
 
r
=
(Pl
/
Pb)1/y
–
1
 The
popula8on
projec8on
for
the
target
year
can
 be
calculated
as:

 









Pt
=
Pl
(1
+
r)z

© 2006 Population Reference Bureau

Exponen8al
Expansion

Assumes
that
popula8on
grow
con8nuously
,
i.e.
 con8nuous
compounding
(as
opposed
to
at
 specific
intervals).

 To
compute
the
growth
rate
(r)
we
use
the
 following:

 
 
 
 
 r
=
[ln
(Pl
/
Pb)]
/
y
 
 
 r
=
[ln
(5500
/
4500)]
/
10
=
.0200671

© 2006 Population Reference Bureau

Exponen8al
Expansion

To
predict
the
popula8on
at
the
target
year
(Pt)
 we
use
the
following:

















 
























Pt
=
Plerz








Pt
(2010)
=
5500
*
e(.0200671)(5)
 































=
6080


© 2006 Population Reference Bureau