Philippine Institute for Development Studies
Agricultural Growth and Rural Incomes: Rural Performance Indicators and Consumption Patterns Arsenio M. Balisacan DISCUSSION PAPER SERIES NO. 94-12
The PIDS Discussion Paper Series constitutes studies that are preliminary and subject to further revisions. They are being circulated in a limited number of copies only for purposes of soliciting comments and suggestions for further refinements. The studies under the Series are unedited and unreviewed. The views and opinions expressed are those of the author(s) and do not necessarily reflect those of the Institute. Not for quotation without permission from the author(s) and the Institute.
August 1994 For comments, suggestions or further inquiries please contact: The Research Information Staff, Philippine Institute for Development Studies 3rd Floor, NEDA sa Makati Building, 106 Amorsolo Street, Legaspi Village, Makati City, Philippines Tel Nos: 8924059 and 8935705; Fax No: 8939589; E-mail: publications@pidsnet.pids.gov.ph Or visit our website at http://www.pids.gov.ph
l__t|:_.
_''', _.:"
;_:._+.-_
_. •
_
_L__i__l__.,_|_i_i_ .'.'.'..'._-_' • _--:'. _.:%%,." ::'.-:.-::-:5"'"-::-:-::-:::-::-::"::-::5+:,:::-:-:-:-:5:-:::-:-:-:"-
"'"+'::;::::-"¥::-_::-:-:
::::_::Z'-'::
I
The PIDS Discussion Paper Series constitutes studies that are preliminary and subject to further revisions. They are being circulated in a limited number of copies only for purposes of soliciting comments and suggestions for further refinements. The studies under the Series are unedited and unreviewed. The views and opinions expressed are those of the author(s) and do not necessarily reflect those of the Institute. Not for quotation without permission from the author(s) and the Institu|e.
August
1994
For comments, su_sestlons or further inquiries please contact: Dr, Marie B. Lamberte, PhJllplolne Institute for Development Studies 3rd Floor, NEDA sa Makati Building, 106 Amorsolo Street, Legas0i Village, MaKati 122g, Metro Manila, Philippines Tel No: 8106261 ; Fax No: (632) 8161091
\.
IIII
ill Ilia
Agricultural
Growth and Rural Incomes: Rural Performance Indicators and Consumption Patterns Arsenio
M째
Balisacan
SUMMARY Usual indicators of rural _ performance tend to be systematically biased downward owing to the shifting of initially rural areas to urban areas as population increases and/or economic activity expands. While this was not a serious problem for intertemporal comparison of rural poverty in the 1960s and 1970s, this was not the case in the 1980s and "1990s. A large number of initially rural areas in 1980 became urban areas in 1990 when they were found to satisfy the criteria for "urban" areas. This reclassification, in addition to net migration from rural to urban areas, reduced the population share of rural areas from 62 percent in 1988 to 50 percent in 1991. In contrast, the estimated rural population share based on fixed rural areas was virtually the same -- 64 percent -- during the same period. The implication of this adjustment on rural poverty estimates is remarkably important. Estimates based on fixed physical rural areas show a substantial reduction of rural poverty from 1985 to 1991. Head count poverty fell from 56 percent in 1985 to 48 percent in 1988 and 41 percent in 1991. The poverty gap and the distribution-sensitive indices reveal the same pattern. The usual procedure, on the other hand, of calculating rural poverty directly from rural population counts based on national surveys shows a much less significant reduction, with head count poverty falling only from 59 percent in 1985 to 50 percent in i988 and then slightly rising to 52 percent in 1991. The reclassification of physical areas over time has also an implication on rural-urban migration. Many studies have commonly attributed the high urban population growth in less developed countries to rapid migration of population from rural to urban areas. Data on rural-urban migration have been based mainly on published national population censuses. If reclassification of physical areas is the one largely driving the commonly observed high growth of the urban population, as in the case of the Philippines, then the rural-urban migration story in the development literature is somewhat exaggerated. The little rural poverty reduction in the second half of the 1960s and in the 1970s is surprising considering that agricultural growth was fairly impressive by international standards. This may suggest that rapid agricultural growth is not enough to get rural development moving. Sustained reduction of rural poverty demands an institution of interrelated policy reforms and programs aimed at enhancing the intersectoral employment linkages of agricultural income growth, increasing labor and total factor productivity, and
building
the
human
capital
of
the
poor.
It appears that the initial distribution of assets and incomes considerably influences the response of rural (and urban) areas to stimulus provided byagricultural growth. There is little research to bank on for a deeper understanding of this issue. Counterfactual analysis using economywide models that realistically capture the economic structure of the Philippine economy, including size distribution of factor/asset endowments, are needed if further insights are to be gained. The analysis requires actually estimating the parameters of these models using Philippine data. The estimation of consumer demand system that distinguishes various consumer groups, pursued in this paper, is meant to bridge the information gap on the demand side of economic models designed for analyzing the efficiency and distributional effects of technological change as well as certain economic policy reforms. Parameter estimates of the almost ideal demand system (AIDS) using Philippine data show substantial differences in the demand responses by various population groups to changes in household incomes. For both rural and urban areas, the expenditure elasticity of demand for cereals, housing, and services falls with household income, while that for meat and marine products, beverages, fuel, and clothing is almost invariant to the level of household income. In the case of cereals, the expenditure elasticity is considerably lower for urban areas than for rural areas, especially for high income quintiles. These results have an important implication for the analysis of technological change (cr of economic pricing policies), nutrition, poverty and income distribution. For example, a technological change in agriculture that increases the income of the poor, the large majority of whom are located in rural areas, may improve their nutritional status as a result of the increase in their consumption of cereals. The supply side, especially on agricultural supply response, also requires further work. The effort has to move beyond estimating static supply response functions and include as well a characterization of the dynamics of capital accumulation and technological change in agriculture. Only then can one have a better understanding of the dynamics of rural development.
Agricultural
Growth
and
Indicators
Rural
and
Performance
Patterns
M. Balisacan
Introduction The
growth
present
and
rural
paper
is
incomes
by which
agricultural
various
groups
effort
is
the
rural
performance
for
various
Section
two
of
of consumer
parameter
estimates for
agricultural
2.
of
analyzing
systems. incorporated and
and
(and
section
efficiency
economic
welfare
Part
defined
the
examines
and the mechanisms
areas.
response
rural
agricultural
study
of
consumer
of
demand
of
reports
into
this
population.
construction
In future
of
behavioral
urban)
three
of
indicators
estimation
discusses
be
work,
rural
on
the
the
demand
a simulation
model
distributional
effects
of
growth.
GrowthJ
PerfolzmanGe
Indioators
usual
including
rural
PZD_/amb/a6
1993
June
supply
demand
will
the
rural
the
while
Aqricultural
The
in
on
This
growth
changes
as
groups paper
study
consistently
well
indicators,
estimation
designed
of
agricultural
this
larger
Philippines.
population
as
systems
a
development
construction
of
of
of agricultural
of
relationships
performance
part in the
the farm-nonfarmlinkages
the
Rural
consumption
Arsenio
I.
Incomes:
Urbanization.
indicators poverty
and
of
_nd
intertemporal,
income
Rural
rural
distribution,
are
performance, technically
2
flawed. Income
First, and
the
within
rural
years.
the
and
as well The
qualifying
population
density
as villages
also
as an
and/or
economic
classified
as
problematical
urban,
indicators.
growth
expansion
of
urbanization, x993
nonfarm thereby
in
for some
or
at least
town
and
centers
of
as another with
a
kilometer
having
at
any
six
and/or
area
as
least
district,
establishments
personal
an
of the
time.
later.
the
As
services),
rural this
be
may
not
be
bias
on rural
to
size
sustained
similarly
incomes.
physical
trends,
performance
rapid, a
of
grows will
urbanization
that
is,
area
say,
leads and
sector"
population
While
example, regions
"rural
initially
downward
employment reducing
cities
square
1971,
of measuring,
a systematic
per
Since
over
expands,
for purposes
Suppose,
agricultural
physical
sooner
capitals
area.
shifting
activity
to create
O%me
the
places
municipalities
and
with
all
density
centers
recreational
urban
definition,
population
areas.
density,
and
for
substantially
provincial
capitals
of
Family
of data
adjacent
500 persons
urban
importantly,
by
lb/2_
as
the
included
and
and
these
in
source
areas
centers
to
manufacturing,
almost
p_/a,
at least
main
cities
added
town
contiguous
qualify
More
FIES
areas"
has changed
Urban
(Manila
all
of
the
as provincial
of population
(commercial,
FIES,
chartered
1965
inhabitants,
regardless
1961 of
"urban
indicators,
Manila
criterion,
it tends
(FIES),
boundaries
municipalities.
can
Survey
In the
municipalities)
2,500
of
household
Metropolitan
well
definition
Expenditures
intertemporal over
the
rapid
This
induces
"rural
areas."
3
To
the
extent
areas
that
than
in
household
non-urbanizing
geographically
expanding
in contracting
rural
constraints
the
growing Thus,
to
areas,
while
say,
development
rural
income
growth
commonly
attributed 1993). on
physical
to
Data
published areas
is
the
2.1
published _rDelubl_6
Jumt
i
and
shows
population _9_3
one
if they rural
areas
and
censuses
to such
movement.
to
If
Rural
urban
that
much!
also
High for
urban
example, 1993,
been
based
reclassification
the
an
(Mills
have
commonly
the rural-urban
is vastly
has
stories. is,
as
in spurring
time
migration
driving
data,
suggest
migration
censuses.
then
the gains The
over
are
rapidly
do not matter
countries
rural-urban
to that
the
are successful
poverty,
in
if there
to
seem
migration
largely
Physical
rural
slow
lags
would
rural-urban
literature
Urbanization
Table
rapid on
so
urban-based.
developed
growth,
development
as
physical
population
high-urban-population in the
even
less
relative
is initiallyrural-based,
on rural-urban
in
the
urbanizing
incidence
to fall
considerable
and reducing
growth
from
censuses,
of
in
is particularly
registered
programs,
implication
population
mainly
are
faster poverty
tends
labor
stimulus
reclassification
important
Nijkamp
are
in population
rural
The
of
or if there
reduction
reported,
areas This
movement
rise
areas,
urban
areas.
the growth
in poverty
incomes
of
observed
migration
story
exaggerated.
Areas
population
(hereafter
counts
referred
to
based as
on
Census
4
Report). rural
It also and
urban
geographical the
estimates
percent
in 1990.
percent
accounts
for
Rural
One various
were
also
the
share
growing
data
Income
due
PX_/o_/26
of
for
during Juno
and
1985,
to
absence
a cause
place
for
conducted
underrepresentation
is
_99_
in
1960,
68
in 1990.
Indicators:
of
implausibility
The
Report
in
the
this
period.
and
data
1979,
the
owing
in certain data
significant shown
from
1972
country physical mainly
section
is
the
undertaken
in
similar
which to
sectors
changes below,
of
63
population.
results
one
64
Issues
(FIES)
Although
generated
FIES
this
Surveys
1991.
and
in
problems,
As
that
Measurement
analysis
the
69
share
1970,
not
in total
and
and
areas,
areas
of households
concern,
for
of urban
1975
of reliable
Clearly,
in
areas,
Data
of
population
urban
Expenditures
technical
1980,
to
the
1988,
share
percent
of physical
to
of population.
in
Census
rural
according
a population
66 .percent
physical
reclassifying
census
the
51 percent
fixed
censuses
1970 had
1970,
percent
from
1971,
published
in
areas
is reclassification
Family 1965,
70
and
Poverty
1961,
rural
population
set
in the
for
involves
population
used
percent
was
it
of
various
that
estimates
estimation
In contrast,
in 1980,
movement
in the
68
areas
as a whole,
2.2
The
show
1960,
rural
areas.
definition
percent
of
population
areas
urban-rural
These
presents
were
not
was
the
substantial of
to the
in the
surveys
society. •
early
1980s
economy
took
agricultural
growth
in
5
the
Philippines
international
during standards,
figures
on
to this
development.
The
the
for
a number
data
are,
of
(wages,
shares
income the
from
transfers
they
on
FIES,
A potential
of a household
of
_
the
of
inappropriate incomes
for
households to the
for
to each
PZ_/a_Iz6
_
1_3
sources
and
is not
with
LFS
another
be
to
each
simply
sum
the
quarterly
bracket
to
In rural
areas,
income
groups.
For
be
Remittances
and
income
especially
seasonallty high-income
incomes
1992). data
is
with is
those
of
figure
brackets
from
is considerable, there
the
income
available It
annual
families
that
the
no
array
groups,
are
large.
household.
for
in
Thus,
with
data
There
for
in the same
such
is not matched
at an
from self-
LFS
tabulated
quarter.
arrive
from
comparable
income up
earnings
income,
the
expected
the
These
(Balisacan
not
data
1980s. 2
of household
from
may
income
incomes
gifts.
1980s
distribution
of family
annual
for incomes,
low-income
sources
in one quarter
do not stay
next.
farming
bias
in
workers'
and
the
upward
household
distribution
in
problem
income
other
constructed
the
early
by
indicative
quarterly
and
to
have
income
and entrepreneurial
were
biased
the
only
important
indices
systematically
1970s
impressive
to
and
provides
remittances, not
was
useful
poverty
late
excluding
were
but
the
salaries,
crops,
poverty
based
in
be
(LFS)
limited
thereby
1970s,
while
years
period
would
of rural
Survey
however,
employment), as
Force
1965-80
it
responses
Labor
employment
the
may
be
household since
some
one quarter dependent
on
especially may
be
less
6
"jumping
around"
households is much
from
one
are typically
income
less.
wide
minimizing
the
low-income quarterly
in urban
Fortunately,
sufficiently
and
for
to another
where
income
around" in
this
each bracket
for
for
is deemed
bracket
are
few,
possibly
paper,
the
these
of income
each
brackets
problem
because
seasonality
range
number _ of
Thus,
incomes
areas
the
the
"jumping
groups.
bracket
much
average
reasonable
is thus
of
the
of
the
for poverty
calculations. The
identification
indicator
of
preferable
economic
to the
perfect;
households current
permanent access their
use
of
of
as
are
able
the
to
1991);
to that
issue line
credit
or threshold. as the
which
a person
cannot
goods
and services,
basic
consumption
needs,
paper
has
the
adopted
judged
official
consumption
household
is
welfare.
borrow
from
future
earnings
consumption
current
income.
extremely
by their
minimum
a predetermined for the
poverty
lines
amount
the
is
thus
welfare
current
income.
construction a poverty
of income
consumption fulfillment
for
reflects
It
purposes,
adequate
to
to their
is the
For practical
are
In reality,
much
identification
importantly
then
limited.
matters
is given
necessary
most
a broad
markets
critical
attain
of
capital
that
opportunity
of
use
that
is
consume"
the
assumes
than
in poverty
is defined
indicator
Current
better
poor
involves
Conceptually,
to
consumption.
A related
threshold
income
consumption
of a poverty
poor
consumption
"opportunity
(Atkinson
the
resources.
current
However,
finance
of
below
bundle
of certain
nutrition. 1988
of
estimated
This by
7
the
government's
inter-agency
Determination period
(TWG). 3
covered
poverty
by
lines
the
are
development. for
a
lines
tend
to increase
There on the
head
large
poor
remain
(H)
persons
poverty
index
transfer
held
on
fixed
Poverty for
course,
possible
with
correlates
(1991)
low-income
have
but
the that of
demonstrated
countries,
growth,
real
poverty
will
do very
they
Its
in the
aggregation
in
Philippines,
studies
First, may
j whose poor
issues
a measure
Second,
from
poverty.
of
al.
of
to
advantage
poor that
but
it
the
This
index
has
the
depth
of
measured
does is
simply
to
poverty
will
to transfers:
for
the poverty j
not
data
including
is
poor.
insensitive
of the
on the familiar
This
insensitive
are below
less is
deemed
poorer
it is also
focused
poverty.
is
become
incomes i
it
the have
of the population
person
same.
i and
et
publications,
as
number
a poor the
are
related
economic
unsettled
shortcomings.
poverty:
is,
Group
countries.
Most
proportionate serious
with
all government
count
of
Working
lines
It
Ravallion
number
are also
poor.
virtually
study.
However,
for
poverty
positively
that,
slowly
Real
Technical
line,
an income
change
measured
easily
understood
and
communicated. A
class
proposed
PID6/a_/36
of
poverty
by Foster,
J%_t
1993
Greet,
measures
employed
and Thorbecke
in
(1984).
this
paper
This
is
is given
that by:
1
where
q
is
poverty
line
family and
is, the
a
measure
u
measure
giving
special
case
is a member sensitive
to
poverty. within
of the
the
poor
income
Where resulting
of
u=2, the
the
gap
whenever
group
Juno
Ie9_
to
the
larger
families. a
As
"Rawlsian"
the
poor.
(for
e=0).
H is
(PG)
a
gap
(for
u=l).
This
measure
is
poor
and
their
degree
of
the
insensitive
owing
weights
to a redistribution equal
weights
are
the
income
gaps
is distributionally
resulting income
indices,
one.'
of
among
the
thepoverty
of measures
number
parameter
poor:
poorest
n_ is
population,
The
measures
measure,
i,
approaches
poorest
of poverty
family
the
index,
of income
attached
to
the
deficits.
a transfer
poorer
PZ_/amb/26
the
P. measure
squared
poverty
a
the
the
P.
below
in the
poorest to the
large,
to
P. class
both
given
poverty
It is, however,
various
for
only
persons
the
fall
of
aversion.
to
very
incomes
income
of
poverty
given
class
familiar
capita
emphasis
weight
whose
number
of
becomes
of this
per
total
is the
of
persons
the
importance
greater
Another
of
is
is the
the
value
y_
n
is
indicates
number
z,
size,
uZ0
the
the
f Z-Yl] _
measure, shortfalls. measured
of income Its
P2, in
drawback
sensitive. (1)
poverty
is
the
using
place that
For
is then
Unlike
takes
themselves,
this
from it
is
example,
simply
head
the
count index
a poor not
and
mean the
decreases
household as
the
easy
to to
_
9
interpret
as H and
a ranking
of dates,
P_ should
reflect
poverty.
It
measure way
the
All
a
weighted
being
in usual
of physical
(r) and
of
areas
for
P_
the
in
to order
are
the
_ is the
poverty
rural
PXDB/a_I_/_6
J_u_o
Z993
the
per
se
in terms
of
severity
of
that
distributions
is that
makes
the
in abetter
subgroup
poverty
poverty This
attempt
decomposabl_
to
level
levels,
property
get
an
indicators
order owing
in
is simply
the
weights
proves
to
of magnitude to
the
some
be of
shifting
time. of
population for
of
(population)
poverty
(u) sectors
index
terms
additively
P. class
of
poverty
measures
into
rural
is
P,= where
to bear
or policies
number
shares.
our
over
point
measures.
the aggregate
decomposition urban
ranking
precise
the
of
key
groups,
ability
population
useful
The
the
alternative
their
bias
their
its
average
extremely the
but
sense:
the
socio-economic
not
members
following
Nonetheless,
well
is
useful,
than
PG.
u
share
sector
of rural
i with
areas.
a population
(2) Let
P_,_ (i=r,u)
share
of _'
be
after
l0
a
change.
It
aggregate
can
be
poverty
easily
checked
that
the
change
first
gains
term
to
the
poverty,
on the poor
term
population third
is
for
their
the
population
to
the
to
the
and
all terms
total
base
change
the
contribution
to
the
change
period
change
in
population
of in
level
aggregate The in
poverty.
possible
intrasectoral
The
correlation
changes
in poverty.
of contribution
of rural
is
= where
c is the
the
changes
aggregate the
of
shares.
urban-rural
from
for r, the
(3)
is
sector
arising
shifts
i=r,u
side
contribution
residuals,
Collecting areas
each
distribution
term
between
is
right-hand
within
controlling
seoond
observed
is:
•
The
in
proportionate
contribution
(4)
of r to the total
change
in P.. By
definition,
fixed
physical
owing
to
rural
areas
at are
reclassification,
measured
poverty
context,
e'
population
pzJN_t.Jm/2a
P_-P.=0
_m_
is
index
_Ls91_
based
on
as the for
date
different
P_,_ would
interpreted
distributions
a given
fixed
from be
t.
If
reported
different
shifting population physical
at
areas.
share rural
rural
from
rural
this
based areas.
date areas
P.,_, the In
this
on rural It
can
ii
then
be shown
areas,P_.=,
that
is
rural
poverty
urban
poverty p/,,, =
useful
above
rural
2.3
procedure
to estimate
incomes
(or
t for fixed
rural
the
for
fixed
physical
urban
areas
is
[(i-_) / (1-_ 1)]P.,u
is
only
an
P_._ directly
expenditures)
for
approximation.
from
the
(6) It
distribution
population
of
would
be
of household fixed
physical
areas.
Rural
Poverty
Table
2 summarizes
income
data.
Indicators:
Results
rural-poverty
The estimates
referred
estimates to as FIES
on rural
population
distributions
reported
set
estimates,
referred
as
of
estimates,
is
based
physical
areas
of
Census.
Thus,
while
"shifting do,
physical
simply
Similarly,
The
at date
physical
thereby
on
rural
villages the
areas"
providing
to
a
Fixed
FIES
FIES.
Physical
The
the
1970
estimates
do
not
control
indicator
of
the
other (FPA)
for
in
above,
FIES
Areas
distributions
noted
the
are based
defined
problem better
on
estimates
in the
population as
based
fixed
Population
FPA
for
the
estimates
intertemporal
rural
poverty. In both to
1965;
the
FIES change
and
FPA
was
estimates,
statistically
rural
poverty
significant
fell for
from
all
1961
poverty
12
indices.
However,
implying did
that
not
with
the
sector,
on
areas,
economy
thereby
to
mainly
in
from
reclassification was
the
1991
FIES
the
same
set
"rural" became
1991,
of
on
the
based
on
The
1980 the
A
number
large
urban
migration
from
rural
to
rural
areas
from
PX_S/emb/_6
of FIES
June
_9o3
in
1990
of
areas.
when This
areas
Both
villages
initially
they
The
were
areas,
62 percent
reduced in 1988
indicate
a
falling
discrepancy
for the while censuses into
to
and
that
for
applied
to
and
in
1980
satisfy
the
in addition the
from
1985
"urban"
areas
reclassification,
urban
50
arising
rural found
rural
from
index
census,
census.
in
nonfarm
in
rising
count
frame
population
in classifying
for
share
sampling
1990
increase
1991.
physical
criteria
areas
net
of
in
rural
growth.
estimates
the head
percent
rural
poverty FPA
the
and
enterprises
the
mild
the
period
pricing
against
of
count
with
shifting
urban
criteria
head
41
of villages.
was
areas.
a relatively
with
to
the
based
response
this
both
biased
incomes
is consistent
during
by agricultural
in poverty, 1988
This
medium-scale
In contrast,
decrease
percent
FIES
to
the
show
52 percent.
considerable 48
1988
and
provided
poor.
be
insignificant,
agricultural
below,
to
weakening
of
was
inequality
nonfarmsmall
estimates
percent
1988
elaborated
FIES from
comes
As
stimulus
poverty
rural
income
to the
The
the
tended
to 1971
growth
rising
policies
particularly
1965
rapid
benefit
1993).
infrastructure
from
relatively
finding
(Balisacan
rural
change
significantly
the
from
the
to
population
50 percent
in
13
1991.
In contrast,
FPA was
virtually
Table
interesting
1978
1965 not
have
and
expected
change
to note
In the
significantly
other
by
and
insignificant,
the danger As
which
might to
while
be
standards.
events.
where
indices that
was
only
GDP
from
1977
other
highly
rural period by
rural
East
incomes
a combination
was
in many over
a
1990).
on the
head
statistically
is sensitive This
to
illustrates
in measuringpoverty. significantly
beginning
of
of unfavorable
by about
growth
(Oshima
increased the
not
rose
was
is
did
and
to 1978
poverty
contracted
estimates
based
index
marked
for
Asia
significant.
count
estimates
poverty
which
the
1977
poverty
index
These
for
LFS
conslderably
in rural
period.
While
agricultural In
fell
the head
This
of
on
comparable,
FIES
agricultural
in the
expected,
1983.
1970swhen
change
precipitated
global
the
1980.
estimates
bias that
same
strictly
as the
upward
based
LFS data."
to
Roverty
suggests
poverty
of poverty
difflculties and
gap
the
1977 not
magnitude
1970s,
the
of using
1981
same
rural
poverty
severity
LFS
during
Interestingly, count
that
the
on the
from above,
the
share
-- during
as noted
countries
period,
population
based
falling
international
developing
sustained
from
the
to be large,
impressive
the
are,
almost
1971.
estimates
poverty
data
rural
-- 64 percent
poverty
rural
and the LFS
it is and
show
estimated
the same
3 shows
estimates FIES
the
10 percent
economic domestic
in 1984
and
1985. It changes _/_/26
is
well
in poverty .._r_De
1993
known may
that be
conclusions
influenced
concerning
by.the
choice
intertemporal of poverty
line
14
and
poverty
slmilar are
index.
income
real.
(aonsumption)
There
standards.
Differences
may
Thus,
errors
can
comparisons?
We
results
on
dominance
ordering
of
poverty
measures
of
rural
that
above-stated
the
rural the
poverty
early
assumed the
income
lines
the
poverty
measures
account
the
standards
poverty
all
plausible
2.4
poverty
Rural
Agricultural The
PInd/_nb/26
1981
lines.
Response
that
to
early
the only
and
to
the
is
lower
Finally,
in
with to
are sensitive
to
in
poverty
is
However,
if
which
head 1977
poverty
of
respect
1980s.
the
than
absence
with
distribution
excluding
suggest
coinciding
change
those
partial
well-behaved
virtual
is robust
measures
a
analysis
a period
The
(i.e.,
in previous
is
take of
count and
into living
index), 1978
for
unambiguously
years.
to Rapid
Growth
agricultural
,Tun,e 194P_
and
the
poor.
poverty
poor
any
the
of
theoretical
of
of
on living results
terms
to 1971,
restricted
of
1980
than
1970s
the
least
Revolution,
the
data
at
concerning
to poverty
of
are
the
in
in 1988
Weak
and
are
of
measurable,
well-known
results
1965
easily
obtain
in
The
Green
late
depth
among
then
lower
from
shortfalls from
6
households
available
robust
to
conclusion
of the
poverty
ambiguous
poverty.
not
employed
distributions
reduction
stage
how
have
between
though in the
ask:
poverty
stochastic
needs
levels,
be also one
in
sector
(comprising
crops,
livestock
and
15
poultry,
fishery,
remarkably
well
and forestry) during
Revolution.
The
substantially
higher
Asian
countries
countries
the
(4.6
growth,
was
the
of
and
and
below
the
performed
of the a
favorably (4.3
averages
for
these
was
Monsoon
developing
well
with
percent).
Green
year
developing
middle-income
Indonesia
the
height percent
for
the
and compared
economy
the
4.6
averages
percent)
percent)
period,
growth
than
(2.3
way
1965-80
sector's
(3.6 percent),
Thailand
of the Philippine
_
those
However,
for the
countries
in
the
as
above,
19808. The
rapid
translate
agricultural
into and
distribution
in
substantial
Unemployment
1971 urban
(Balisacan areas)
The decline rapid
yield
seed
work
workers
for
indicative oshima
areas
1993).
also
(HYVs) and
for
supplementary of
reduction
of
also
1970s
and
in in
the
fuelled
by
and
irrigation
by
small
farmers
incomes,
sector
where of
also
deteriorating
economic
and supply
considerations
in
1986).
relatively
high-yielding
depend
decline
to
as
(Lal
investments.
who
the
1965
(as well
1980s
diffusion
Income
from
areas
early
in the rice
poverty.
to swell.
egalitarian
rural
the
shown
rural
continued
less
wages
pronounced was
not,
became
Real
in the
did
in
For
on off-farm
real
well-being
the
wages
(Papanek
is
1989,
1990). Both
demand
of agricultural by
rural
growth
varieties
landless
underemployment
fell was
growth
agricultural
growth. income
On the growth
demand on
constrained
side,
domestic
the
the
stimulus
nonfarm
linkages provided
activities
was
16
weak
owing
arose the
to the
partly
from
highly
less
export
continuing
actual
the
distribution greater
the
more
of
with
income
(as well
as urban) the
strong
Trade
the
in the policy
restrictions
agrarian
likely urban)
were
1980
Gini
ratio 1991). on
the was
and fertilizer
for
the
consumption
to those the
setting
multiplier
much
increases
content, in
been
structure
geared
side, the
unfavorable
goods
and
linkages
of
in
effects
rural
agricultural
nonfarm
against
and
highly
and
sector
income
import-substituting bias
fiscal
motion
on the
from
manufacturing
agriculture overvalued
capital-intensive
activities
and,
penalized
labor-intensive
activities
and
PZrt_a/a_l)/26
1993
and
responding
High
the
exchange
sector
induced
rural
sector.
in the process, backward
effective
rate
a
rural
macroeconomic
growth.
promoted
Jt_ne
has
(Balisacan
Because
weak
income
there
on credit
is most (or
and plantation).
productivity
1986).
and
prevented to
this
and
large-scale
landholding
to
This
economy.
supply
environment
the
(David
growth
of employment
reform,
from
and
banana
1960
gains
import
sequence
protection
on land
based.
of landholding
farming
(e.g.,
of subsidies
farmers
high
agricultural
vigorously
sector
of
farmers
large
not broadly
distribution
Thus,
income
availability
of
services
crop
0.5--from
the
was
plantation
influence
affluent
On
skewed
implementation."
Accentuating
the
growth
legislation
high--about
pattern
the
the highly
in the
remained
a
that
capital-intensive
processing Despite
fact
unduly severely
integration."
17
Generous development
fiscal
of export-oriented
export-processlng EPZs,
which,
intensive, had
little
Stewart
the
exception
of_Cebu
located
and
impact
a
economy.
on
rural
favor
of
The
privileges
use
to
of
some
and
to
important
close
to
to
large
(Ranis
role
of
as
dispense ruling
and
in
the
market
well
as
of
the
sectors
the
labor,
capital-
especially the
and
by and
parastatals
functions
group
led
of
agriculture"
by in
governmental
through
garments
which
to diminish
the
of these
sources
interventions,
structure
select
from
or
regulations
monopolistic
(exporting
operations,
tended
for
the development
investments,
industry
also
window
establishments
distance
Government
1980s,
in
promoted
a
MNC-dominated
98).
early
mechanism
at
infrastructural
1993:
1970s
However,
uneconomic,
a
manufacturing
(EPZs).
were
heavy
provided
zones
with
electronics), "required
incentives
economic elite
was
concentrated
in
rampant. Investments highly
in
urbanized
Eclja).
Metro
centers
Manila
total
infrastructural
(ILO
1974).
rapidly 1960s
to the
sector.
an early
This
inequality.
PzDe/amb/a6
While
-- by
O'ume
and
infrastructure
and
Central
Central
average
of
1980s, of
late
percent
occurred
government
importantly,
almost
the
in
a year mainly
spending
neglect
and
one
1960s
expenditures
13.2
this
(Pampanga
had
in the
government
were
Luzon
Luzon
investments
pattern
More
3.993
physical
half
Nueva of the
and early
1970s
agriculture
grew
-- from
the
late
favored
rice
in the
promoted
of most
rural
regional areas
in
18
the
Philippines
response
considerably
to the
Public
stimulus
1970s to
and
less
early
to
in
health
population,
as health
Undoubtedly,
Demand
information
into
and
estimation
technological Such
demand
of
welfare
in identifying
relatively
impressive Deaton to
and
is helpful
was
household
mostly
the
how
they
in
Likewise,
for
to
the
limited
the
rural
in Metro
is an extremely
alternatively,
growth
(AIDS)
the
and
(or,
agricultural
system
patterns change
of
employs
concentrated
contributed
incomes
change
information
study
was
1976).
point
In
Manila.
weak
rural
Patterns
about
as prices the
education
Bank
sore
were
areas.
and
response.
Consumer
change
biases
a
health
population,
(World
supply
growth.
rural
elementary
was
facilities
these
entrepreneurial
3.
services
the
primary
Manila
sector's
agricultural
against
of total
Metro
rural
capital--mainly
high-quality
10 percent
the
by
human
biased
1980s,
schools
access
in
likewise
than
private
provided
investment
education--was
weakened
in
consumption.
by
and
extract
the
international
Muellbauer's this
The estimation
important
economic
which,
as
standards.
from
results
almost
of
policies). linkages
shown
above,
The
present
ideal
demand
Philippine include
to
input
impact
the consumption
(1980)
information
llkely
distributional of
Philippines
are
data
on
information
19
about
various
income
3.1
consumer
Model
theory,
degree
by
zero
the
a
following
system
in prices
elasticities
equal
definiteness
of
from
function
automatically
are,
and
unrealistic)
of
Deaton
to price
called
minimization
of easily
the existence
out
J%u_
and to be
1993
terms.
maximization
satisfy
these
of
to
handle
and
conditions
in
to deriving This
between
demands
and the
specified
very
the
approach
and,
cost
be
1975;
systems utility
Such
systems
be
imposition
quite (often
utility
functions
system
is the so-
a demand
problem
Lau,
negative
1980).
cost
never
and
may
the
of
of income
specified
estimation
be
some
Demand
a
without
to
homogeneity
restrictions.
their
approach
a
symmetry
cross-price
of corresponding
need
dorgenson,
and
approach."
a correctly
function
unity,
Muellbauer
"duality
relatively
to
(c)
expected
(a)
(b) share-weighted
separability
An alternative
equations:
income,
clumsy
and
are
and
restrictive;
complicated
restrictions
demand
constrained
however,
(see
of
compensated
derived
PI_/_/R6
responses
Structure
satisfied
turns
differential
changes.
In
given
groups'
preferences,
Deaton,
useful
therefore,
function,
explicitly 1986).
in applied
involves
cost
only
allows
the
moving
function.
Moreover,
the approach
guarantees
even
though
evaluated This work.
the utility
(Christensen,
"flexible"
property
20
The class
basic
of
form
of
flexible
generality
of
functional
advantages
over
it are
first-order
from
utility-maximizing exactly,
functional
form
consumption
of
model
the
allows
through
linear
is
While
consumer
demand of
these on
in the AIDS
theory
be
axioms and
has
household
Slutsky
easily
restrictions
fixed
model
and
can
the
available
homogeneity
derived
consumers,
with
has
derived
system
satisfies
over
consistent
restrictions
(expenditure)
model
one the
but
functions
to any demand The
is
preserves
models,
demand
perfectly
the
testing
Preferences cost
approximations
which
_estrictions
The
model
model
translog
both.
behavior.
AIDS
The
and
aggregates
data.
Muellbauer's
forms.
Rotterdam
from
choice
and
both
considerable
of
Deaton
symmetry
imposed,
against
the
the data
parameters.
are represented
bythe
following
function:
+ U,o jp j Where 7z_
p_ and are
are
commodity
parameters.
substituting inverting
p_
Applying
for (7)
prices,
to
u into give
Shephard's
the u as
u is
resulting a function
wl = a i + _yijlogpj where
w, is
expenditures,
the and
budget P is
share a price
of
utility,
lemma system of
p
and to
this
of
equations
and
x),
+ _log(m/P) commodity
index
defined
i,
u_, function
we
by
and and
(after
find
, m
8_,
(8) is
total
nominal
21
In
many
collinear,
practical
Stone's
situations,
(1953)
price
logP" provides
index
given
=_wklogp
a reasonable
approximation
theoretical
restrictions
The
where
to on
prices
are
highly
by
k
(10)
(9). (8)
apply
directly
to
the
parameters:
=o
(12)
Yij = Yj_ Equations
(ii)
and
(12)
restrictions,
respectively,
maximization.
Equation
bears
noting
and
(13)
the adding-up of
testing
the
which
adding-up are
provides
thattheunrestricted
automatically opportunity
are
(13 )
the
implied symmetry
estimation
restriction.
and
of
and
symmetry
measure
change
by
utility
condition.
(8) only
The model
homogeneity
homogeneity
thus
by
It
satisfies offers
imposing
the (12)
(13). The
following
71j parameters
a 1 proportional
B, parameters,
PX'l_Iia_b126 _
IS_3
on
the
other
the
change hand,
in the
in p_ with indicate
ith
(m/P) whether
budget
share
constant.
The
the
goods
are
22
luxuries
or
co_mmodity
necessities.
i is a luxury;
Apart affected of
modelled
use
with
economic
in
a scaling
1986;
w, increases
commodity
and
social
manner
as in the
demand Gould,
function
models
COx,
of the
pattern
is
Perali
e.g.,
that
are
study,
the
recognized
and
of demographic Pollak
1991).
so
patterns
this
incorporation (see,
and
In
m
a necessity.
demand
factors.
consumption
with
i is
incomes,
on
familiar
Deaton
B_<0,
and
urbanization same
B_>0,
prices
demographic
in the
scaling 1981;
from by
effect
With
and
Wales
In particular,
form:
) = where
rl is
variable.
estimated Viewed
P] = Pj_I = Pj e'_a â&#x20AC;˘
LA/AIDS
model
(14)
coefficient,
and
this
the
way,
Incorporating
this
R
is
urbanization
scaled
scaling
prices
function
dummy become
into
the
yields
w_ = =l where
we
P'=_jlnP;.
It
is
7/jlog#_ easy
to
+ _ilog (m/P I),
check
that
(15)
(15) can
be
rewritten
as
wl = _i + _yijlogPj J where
Pzl_ll/amb/.1)6
D = -_,S_.
J_
J.993
+ _log(m/P)
+ u_R,
(15")
23
In almost
the
universally
Symmetry
structure
of demand
provides
little clear
whether
the
rejection. impose
that
what
additional
and
expression
uses
the
price
other
hand,
known
that,
well
maintain
that
is
model,
theory Thus,
the
assumption
the
underlying
forms. is
is
1989).
Unfortunately,
rejected
of the AIDS
symmetry
theory
or
causing
we have
the
chosen
defined
elasticity by
(9)
in
the
AIDS
the
if the
Stone's
"linear
price
formula
given
to take
account
approximate"
index
by
(16) for
defined is not
the
the
Stone's
price
index.
the
LA/AIDS
model
as
role We
to
model
is
Hi = I+81/_ However,
it
restrictions.
expenditure
index
on the
functional
being
Barboza,
the correct
systems.
maintained
for
and
must
represents
actual
is
estimation
homogeneity
The
as to
whether
In our
the researcher
of demand
guidance
Strauss,
restriction
It is, of course,
he employs
relationship
homogeneity
on homogeneity),
data.
theory,
of the model
behaviorial
not
by the
the
(Thomas,
conditional
rejected
in any test
literature,
rejected
(at least
is seldom
is
empirical
by
(16)
AIDS
(10) is employed,
appropriate.
The
of expenditure write
(LA/AIDS)
the
model the
correct
shares
expenditure
that
uses
elasticity formula
as variables elasticity
has in for
24
_, = i + (8,/w,)[1
Notice interest
(17)
in terms
matrix can
that
form,
of
the
expresses
itself
as
to
(see
the
and all
solution
be expressed
-_wjlogP_(_j-
the
Green
of the
N
vector is
an
with
an
and
is
n-vector
elements
identity
C"
is an
The model
of
m_ = _-i,
matrix, n-vector
B with
uncompensated
is also
is
price
a function
el]
where
in
Kronecker
matrix
simultaneous
vector
with
M of
is
length
elements
E
matrix
3.2.
is
with
Data
PI_/amb/26
n
x
typical
and
Jumm 199s
n,
I
c_ = wjlogPl.
relevant
delta
of
demand
price
in the
LA/AIDS
elasticities,
(6_j = 1 for
notation,
equations
an
n-
b_ = B_/wl,
the
i=j;
solution
to
6 = 0 for this
i.e.,
n
i_j).
system
of
is
E = [I + BC] -_ [A + I]-I, where
an
wl
6_j is the
Again,
(18)
elasticities,
elasticity
of all
equations
+ L,
n-vector
elements
In
1991)
_ is a unit
an
of
elasticities.
of simultaneous
Alstgn
expenditure
elasticity
other
N = M + _ = (I + BC)-_B where
(17)
expenditure
system
and
i)]
matrix
elements
Estimation
with a_
elements = 6_
PKQcedure
+
[y_
(20) n_
and
A
- B_w_]/w_.
is
an
n x
n
25
Data
on household
the Family The
FIES
out
by
is
the
survey and
Income
a national National
is deemed
expenditure
were
excluding or
urban).
For
expenditure
shares
expected,
cereals
in total
However,
of
the
the
areas
about
share
on 30
cereals;
1985
of
the
of income
(Table
4).
requirements
of
for the analysis
of technological
both
urban
by
and
declines is
of
change
areas
corresponding
housing,
is substantially
and FIES,
the greater
by
Manila,
area
these 5
but
(whether
make
shows
up
50
average
area. rural
areas,
the
as per
capita
income
for
rural
quintile. spend
expenditure
Metro
Table
higher
of income
rural
1988
group.
for
cereals
average
(including
and
quintile
In
designed
Region)
each
the
carried
frame
groups
the parameter
region
for
in
1988.
country.
7 commodity
effects
commodity
irrespective
percent.
(23 percent)
both
of
of the
model
and
estimates
classification,
expenditures
population
incomes
into
Autonomous
each
sampling
from
reforms.
for each
Cordillera
for
urban
policy
The
reliable
account
7-commodity
observations
As
regularly
distributional
estimated
the
survey
region
equilibrium
as economic
shares
rural
and
the
budget
each
general
With
for 1985
levels
into
mainly
(FIES)
to provide
takes
derived
Survey
sufficient for
been
Office.
are classified
efficiency
as well
household
Statistics
The classification a computable
have
and Expenditures
Expenditures
the
expenditures
The bottom
about figure
average than
areas
40
share that
urban for
of
rises.
than
for
20 percent
percent
for
share
of
areas
urban
for rural
their is
areas
areas
(13
26
percent).
As
expenditures the
also
rises
consumption
expected,
with
per
patterns
the
capita
of
share income.
various
implication
on the distributive
policies,
especially
on
price
FIES
does
not
indices
for
each
commodity
groups
indices,
however,
areas.
Consumer
expected the
to be
expenditure
location
of
including
of
variable
does
of the
LA/AIDS
Because the
error
terms
the
system.
p_/anbl_6
in
are _t_3
urban
NSO.
price
be
We
have
(see
affect
equation
the
in
(15')).
the
The
and
areas,
and
so the
model
by
independent
inclusion
symmetry
are
with
LA/AIDS
capture
homogeneity
and urban
related the
price
cereals)
rural
"augmented" to
rural
(e.g.,
systematically
variable
regional
between
than
Consumer
disaggregated
The
commodities
areas
may
dummy
fact
that
the budget
equations
ordinary
unbiased,
models.
_e
in
Using and
equations
for
across
consistent
LA/AIDS
the
some
of the
appropriate
an
of
this
restrictions
model.
correlated.
demand
from
prices.
sufficiently
prices
location not
for
a distinction
URBAN
in
have
of commodity
about
do not make
households.
influence
and
obtained
shares
an
impact
total
differences
of households
information
region
higher
in
food. contain
are
housing
These
groups
important
The
of
but
The
Since
linearly
least
the
the
demand
squares
inefficient,
iterative
obtaining
must
of
shares
Zellner
efficient budget
independent
system
(OLS)
would
are give
parameter
estimates
of
estimation
procedure
is
parameter shares
add up to one,
add
estimates up
and one equation
to
one,
must
of
the
only
n-1
bedropped
27
for
estimation
which
purposes.
budget
satisfies
share
the
(The
is
Zellner
deleted.)
adding-up
estimation
The
restriction
process
of
is invariant
thus
consumer
to
automatically
demand
theory.
3.3 Table
6 presents
the parameter
The
coefficients
of total
for
CEREALS
MEAT,
and
necessities. that
they
FUEL
are
significant. CEREAL
half
the
own-price
although
The
dummy
URBAN
are negative
that
have
luxuries,
terms,
these
positive only
model.
and significant
commodity
groups
coefficients,
the
variable
evaluated
however,
at
demand
inelastic,
The
are
latter
are
suggesting
is statistically
is significant
variation
sample
means,
has
own-price
J.-_-
the _gg3
the
Table
MEAT,
and
HOUSE
lowest
only
for the
BEVE,
system.
from
have
for
one
of
the
Most might
be due
to
set. (Marshallian) These
these
of
the
estimates
CLOTH,
price
elasticities
means
are income income
significant
This
7. i.e.,
elasticities
coefficients
demand
data
In general,
CEREAL,
are
uncompensated
the
FUEL
the
in the
and
levels.
terms
insignificant.
in
while
of
of
shown
for
CEREAL
price
are
and price
groups,
the
expenditure
elasticities
shares
of
parameters
price
The
PX_I/amb/_
and HOUSE
price
limited
most
indicating
coefficients
of
the
expenditures
of the LA/AIDS
equation. The
the
estimates
and
expenditure suggest
MISC
elastic.
are
are
Among
that income
the food
elasticity. the
which
negative they
are
signs, based
although on
are
28
statistically
not
elasticities, are
significant.
the
subsitutes
signs
The
of which
indicate
or complements,
substitutability
between
of CEREAL,
for
example,
demand
for
FUEL
BEVE,
CLOTH,
and
and
a significantly
suggest
foodgroups has
HOUSE
MISC.
whether
that
and
nonfood
The
impact
of
on the
groups.
effect
BEVE,
goods
The
effect
on the
on the
demand
paired
is a significant
positive
a negative
price
cross-price
the
there
a significantly and
negative
uncompensated
for
price on the
demand
for
hand,
has
FUEL
and
response
by
other CEREAL,
HOUSE. There various 8).
For both
while
for that
of
areas, have
change
in
their
nutritional
consumption
J_mQ
of
1_93
of
MISC
important
In
whom status
CEREAL.
are
lower
for
urban
as
a
in
result
the
a
income
of
rural of
the
areas,
to
CEREAL,
the
areas
than These
analysis
policies),
example,
the
income,
quintiles.
for
of
invariant
of
For
located
is almost
pricing
increases
household
income
(Table
elasticity
case
implication
distribution.
incomes
the
high
(or of economic
that
with
CLOTH
is considerably
demand
expenditure
falls
and
for
the
household
the
income.
agriculture
majority
in
areas,
FUEL,
especially
income
in
changes
and
BEVE,
change
large
l?Z_dl/omb/26
HOUSE,
an
and
to
urban
household
technological poverty
and
elasticity
rural
results
rural
for MARINE,
level
differences
groups
CEREAL,
expenditure for
substantial
population
demand
the
are
of
nutrition,
technological the
poor,
may
increase
the
improve in
their
29
There
is
population that
the
groups data
on prices The
little
locational
within
4.
in this
study
does
not
a region
or
activity
to
the
to
rural
areas
in 1988
-The
is remarkably PII_I/Imb126
jUiWl
%_3
the
population
share
implication
was
based
-- during of this
important.
the
in relative
of
prices
not
and
became
shifting
a
1990s.
for
areas
of
in 1991. on fixed the
rural
adjustment
economic
problem and
in 1990
for
1970s,
number when
areas.
of they This
from
rural
rural
areas
from
the
estimated
In contrast,
same
Estimates
FIES
and/or
1960s
"urban"
be
initially
A large
to net migration share
to
of
serious
in the
urban
criteria
tend
expands
poverty
1980s
in 1980
to 50 percent
64 percent
this
the
in addition the
population
same
in
to
population
of rural
case
reclassification,
percent
or r_al)]
performance
owing
as
While
satisfy
reduced
rural
areas
comparison
rural
found
areas,
of downward
urban
intertemporal
initially
from
area.
biased
not
arising
(urban
differences
information
circumstances.
prices
an_area
inter-household
increases.
was
region
in
across
considering
contain
economic
differences
[i.e.,
indicators
areas
unexpected not
of different
captures
elasticities
Remarks
systematically
were
used
but
Usual
this
is not
only
Concluding
rural
This
differences
households,
price
shown).
by households
regression
in
(not
set
faced
variation
areas
to urban
was virtually
62
the
period. on rural
based
on
povertyestimates
fixed
physical
rural
3O
areas
show
a
1991.
Head
percent
in
substantial count
1988
reduction
poverty
and
41
fell
percent
distribution-sensitive
indices
procedure,
on the other
hand,
from
FIES
rural
reduction,
with
1985
to
50 percent
from
reveal
and
the
from
percent
a
in
gap
pattern. poverty
much
less
slightly
from
to
to
48
and
The
rural
only
1985
1985
poverty
same
falling
then
poverty
The
show_
poverty
in 1988
56
in 1991.
counts
count
rural
of calculating
population head
of
the
usual
directly
significant
rising
59 percent
in
to 52 percent
in 1991. The 1960s
little
and
growth
in the
was
suggest
rural 1970s
fairly
that
is surprising
Sustained
an institution
of interrelated
enhancing
intersectoral
income
growth,
building
the
increasing human
It appears considerably stimulus to
bank
provided on
Counterfactual capture
a
analysis
the economic
size distribution
of
reduction
of
the
the
rural
This
to
get
poverty
of
factor
may
rural
demands aimed
at
agricultural
productivity,
of assets
of rural
growth.
and
understanding
using
economywidemodels
is little of
this
areas
to
research issue.
that realistically
of the Philippine endowments,
and incomes
(and urban)
There
deeper
of factor/asset
agricultural
programs
linkages
of the
poor.
response
structure
enough
reformsand
distribution
byagricultural
for
is not
and total
the initial
influences
that
half
standards.
growth
policy
labor
second
considering
employment
capital
that
in the
by international
agricultural
moving.
the
reduction
impressive
rapid
development
poverty
economy,
are needed
including if further
31
insights
are
estimating
to
the
be
parameters
The
exercise
the
information
gap
for
analyzlng
the
pursued
technological The also
supply
estimating
better
of
on the
3 of this
demand
efficiency as well
models
understanding
in of
response
effort
of
agriculture. dynamics
has
of
rural
of
policy
reforms.
supply
response,
move
include
capital Only
designed
effects
to
and
data.
to bridge
models
agricultural
functions
dynamics
the
economic
as certain.economic
The
change
is meant
distributional
work.
the
paper
actually
Philippine
and
further
of
using
of
on
supply
requires
side
especially
static
analysis
these
side,
characterization technological
The
in section
change
requires
gained.
beyond
as well
accumulation
then
can
one
development.
a
and have
a
32
NOTES
I.
For
a description
various 2.
FIES,
see
Quarterly
ISH data are
for of
3.
The
newly
line
is
an
rural
adaptation
and monthly
menus
by
on
incomes
the
nonfood),
total 1985
to
methodology
obtain
the
food
for these uses
the
meet
of
FIES
points the
can
not
above
calories)
and
and
below
is
divided
by
whose food
(food
plus
average
of
food
In contrast, pattern
are
the
the
proportion
consumption
needs
families
line
families.
low-cost the
poverty
sample
1965).
of
total
as the
used.
the poverty
nonfood
sample
data
be
adequacy
(2,000
No
significant
(Orshansky
of
defined
average
the
100%
Estimates
1977.
by costing
for energy
threshold
(APC),
method
obtained
which
pattern
to
of the
income
of establishing
are
i0 percentage
consume
data
nutrients.
is,
expenditures,
sample 4.
within
1988-1990
(RDA)
to
third-quarter Given
Orshansky
Allowance
prior
1990.
procedure
thresholds
other
That
propensity
the
the
consumption
fall
threshold. basic
for
limitations
collected
and
urban-rural,
Dietary
adequacy
of
food
region,
Recommended
based
TWG's
not
and only
1989,
incomes,
revised
Daily
were
for 1987,
1988,
and
(1993).
data
are available
seasonality
comparability
Balisacan
income
available
80%
of the
for
all
to
TWG's FIES
families. The
P. for u=2
to its appealing (1986)
and
has been
properties.
Ravailion
and
van
popular See,
in recent for example,
de Walle
(1991).
empirical Greer
work
owing
and Thorbecke
33
5.
AS
in
FIES
is
not
problem
classification the
1970
frames 6.
The
7.
Based
8.
The
America.
For
structure,
see
Indeed,
students Power Krugman
of and
that
numerous
the
Philippines
a
comprehensive
this
is
a
Sicat
et al.
de
bases
theme
The
markedly
for
LFS
Report
peasant
sampling
of
the
(1984),
1992).
and
large
of
Latin
that
Philippine
Adriano in
(1990,
farms
resembled
development.
Dios
of
set.
(1987).
account
economic
(1971), (1992).
small
and
vary
areas"
3.
somewhat
common
Philippine
the
Development
Quisumbing,
data
not
of Atkin_on
of
physical
this
does
in Table
World
Hayami,
in
censuses,
Bank's
coexistence
"shifting
issue
included
follows
the
(villages)
population
on World
in
1988,
important
years
analysis
to
barangays
1980
the
plantations
9.
an
of
and
for
prior
agrarian
(1990). writing See,
Bautista
of for
serious example,
(1989),
and
34
References
Atkinson, Anthony B. (1991), "Comparing Poverty Rates Internationally: Lessons from Recent Studies in Developed Countries," World Bank Economics. Review 5, 3-21. Balisacan, Arsenio M. (1992), Incidence, Determinants Review i0, 125-163.
"Rural Poverty and Policies,"
in the Asian
Philippines: Development
Balisacan, Arsenio M. (1993a), "Agricultural Growth, Landlessness, Off-Farm Employment and Rural Poverty in the Philippines," Economic Development and Cultural Change 41, 533-562. Balisacan, Arsenio M. (1993b), "Urban Poverty in the Philippines: Incidence, Determinants and Policies", paper presented at the Finalization Meeting on Critical Issues and Policy Measures to Address Urban Poverty, Asian Development Bank, Manila. Bautista, Romeo M. (1987), Production Incentives in Philippine Agriculture: Effects of Trade and Exchange Rate Policies, Research Report 59, Washington, D.C.: International Food Policy Research Institute. Bautista, Romeo M. (1991), "Dynamics of Rural Development: Analytical Issues and Policy Perspectives," Working Paper Series No. 91-07, Philippine Institute for Development Studies. Christensen, L.R., "Transcendental Economic Review
D.W. Jorgenson, and L.J. Lau Logarithmic Utility Functions," 65, 367-83.
David,
Cristina C. (1986), "The Philippines," Cristina C. David et al., Food Trade and ASEAN and Australia (Kuala Lumpur and Australia Joint Research Project).
Deaton, Angus (1986), "Demand Analysis," Intriligator (eds.), Handbook of Elsevier Publishers BV. Deaton, Angus System," de
and John American
(1975), American
in Anne Boc.th, Food Security in Canberra: ASEAN-
in Z. Griliches and Econometrics, Vol.
Muellbauer (1980), "An Almost Economic Review 73, 312-326.
Ideal
M.D. III,
Demand
Dios, Emmanuel S. (ed.) (1984), An Analysis of the Philippine Economic Crisis: A Workshop Report, Quezon city: University of the Philippines Press.
Foster,
James
E.,
Joel
Greer,
and
Erik
Thorbecke
(1984),
"A Class
35
of Decomposable
Poverty
Measures,"
Econometrica
52
761-766.
Gould,
Brian W., Thomas L. Cox, and Federico Perali (1991), "Demand for Food Fats and Oils: The Role of Demographic Variables and Government Donations," American Journal of Agricultural Economics 73, 212-221. _.
Green, Richard and Julian M. Alston (1991), Models: A Clarification and Extension," Agricultural Economics 73, 874-875. Greet,
J. and E. Thorbecke Food Poverty Applied Economics 24 59-74.
Hayami, Yujiro, Toward an Perspective
"Elasticities in AIDS American Journal of
(1986), "A Methodology to Kenya," Journal
for Measuring of Development
Agnes Quisumbing, and Lourdes Adriano (1990), Alternative Land Reform Paradigm: A Philippine (Quezon City: Ateneo de Manila University Press,
1990). ILO
James,
[International Labour Development: A Programme the Philippines (Geneva:
Organization] of Employment, ILO).
(1974), Equity
Sharing and Growth
in in
William and James Roumasset (1992), "How to Facilitate Stifle Economic Development: The Role of Agriculture Indonesia and the Philippines," Southeast Asian Journal Agricultural Economics 1, 125-156.
or in of
Krugman, Paul, J. Alm, S.M. Collins, and E.M. Remolona (1992), Transforming the Philippine Economy, Makati: NEDA/UNDP. Lal,
Deepak (1986), Real Wages and 1978," Journal
"Stolper-Samuelson-Rybczynski in the Pacific: Real Exchange Rates in the Philippines, 1956of Development Economics 21, 181-204.
Mills,
Edwin S. (1993), "Urban Poverty in Selected Asian Countries," paper presented at the Finalization Meeting on Critical Issues and Policy Measures to Address Urban Poverty, Asian Development Bank, Manila.
Nijkamp, Peter (1993), "Urban Environmental Quality Improvement in Developing Countries: Socio-Economic Possibilities and Limits," paper presented at the Finalization Meeting on Critical Issues and Policy Measuresto Address Urban Poverty, Asian Development Bank, Manila. Oshima, Harry solution
T. (1990), to poverty,"
Pollak,
and
R.A.
T.J.
"Employment generation: Asian Development Review
Wales
(1981),
"Demographic
the long-term 8, 44-70. Variables
in
36
Demand
Analysis,"
Econometrica
Power, John H. and Gerardo Industrialization and University Press).
49,
1535-51.
P. Sicat (1971), Trade Policies
The Philippines: (London: Oxford
Papanek, Gustav F., "Growth, poverty, and real wages in labor abundant countries," Background paper for the World Bank's World Development Report 1990 (Washington, D.C.: World Bank, 1989). Power,
John H. and Gerardo Industrialization and University Press, 1971.
P. sicat (1971), Trade Policies,
The Philippines: London: Oxford
Ranis,
Gustav and Frances Stewart (1993), "Rural Nonagricultural Activities in Development: Theory and Application," Journal of Development Economics 40, 75-101.
Ravallion, Martin, Gaurav Dart, and Dominique van de Walle (1991), "Quantifying Absolute Poverty in the Developing World," Review of Income and Wealth 37, 345-361. Ravallion, Martin and Dominique van de Walle (1991), "The Impact on Poverty of Food Pricing Reforms: A Welfare Analysis for Indonesia," Journal of Policy Modelling 13, 281-299. Thomas, Dunoan, John Strauss, and Mariza M,T.L. Barbosa (1989), "Estimating the Impact of Income and Price changes on Consumption in Brazil," Economic Growth Center Discussion Paper No. 589, Yale University, Connecticut, USA. World
Bank (1976), The Philippines: Development (Washington, D.C.:
Priorities World Bank,
and Prospects 1976).
for
37
Table l Rural Areas and Urbanization ...............................................
;L ........................
1960
1970
[980
1990
[. Total Populatiou (in ltillit, n) g Change
27.09 _
36.68 3.01-
48.10 2.7i
60,69 2,33
2, ProportiollWhichis Rural Census Report Fixed Rural Areas a/
70,20 68,55
68,17 68,17
62,49 66,35
51,16 64,16
3.Proportion |hich IsOrt)atl CensusReport Fixed Rural Areas
29.80 3i.45
3t,83 31,83
37,51 33,65
_8.84 35.84
4, Rural PopulationGrowth Ceusus Rept>rt FixedRural Areas
_
2,74 2,98
1,84 2,_4
0.32 t.99
S. Tempoof Urbanizatiotl b/ CensusReport FixedRuralAreas
_
0,9S 0,80
2,$l 0.82
4,64 0.97
a/ Basedon 1970urhau-rural classificatiot_ ,f villag,:_. h/Orhau-rural growth dif(ereo_:e, Sources: htional Statistics Office, [lttcgratcd various years.
(;ellStlS
Of tile Population,
39
Table 3 Rural Poverty, LFSData, 1977-83 (in I except for t-rati.s)
Head Count
Poverty Gap
FGT (a:2)
.........................................................
28,08
t4,04
t977
56.17
1978
55.67 (-0,65)
28,39 (0,80)
14,_3 (2,51)
1980
48.58 (-I0,90)
24.29 (-i2,40)
12,14 (-{4,23)
1981
49,41 (1,62)
24.70 (1,60)
1982
57.08 (15,08)
28,54 (15,I0)
4,27 (i5,09)
1983
60.6] (7,06)
](I._2 (7,08)
15,16 (7,08)
2,35 (1,64)
.........................................................
Notes:Nodataavailable for1979: Figures inparenllleses aret-ratios furpc, retry differences between theyearindicated andtile preceding year.ThetestisbasedonKaktani's (1990) methodolo U. Critical t-value at5_ significance ievc[is 1,96. Sources
HasteData: Nati,,nal Statistics Office, Faiily inc,_e and Expenditures Survey, Integrated 5{,rvcy ,,f 1[ouseholds Bulletin, LaborF.rce, varioils years, Of
'
40.
Table 4 Aggregatiunof Commodities
Variable Name
Components
.........................................................
2 ...............................................
CEREAL
Cereals and cereal preparation, fruits and vegetables
IEAT
Neat and dairy products, eggs, fish
BEVE
Beverages, tobacco, misceliaaeutts foods
FUEL
Fuei_lightandrater, transportation andcommunicalion
HOUSE
Housing andrepairs, household furnishing andequipment, hous_ht_Id operations
CLOTH
Clothing
list
Personal careandeffects; medical, recreational, educational, personal, andotherservices; medica[ andpharmaceutical sl{pplies; schuol supplies; othermiscellaneous items
43_
Table5 _?ercentage Distributionof Per_pita Expenditures byQuintiie
Quintile
CSR'_L I_T
B_E
_EL
HOUSECLOTIt MISC
TOTAL
ROI_L
26.79
18.24
14,47
8,89
13.31
4,45
I3.84 100.00
First Second '_,ird Fourth Fifth
42.45 36.81 3t.88 27,3i 18.22
17.99 18.50 48,9g 19.26 [7.39
11,82 13.45 iS,06 15,54 14,53
8,61 8,63 9,05 8.78 9.03
8,69 9.45 10,44 12.50 17.0[
3.32 4,23 4,46 4,59 4.68
7.[2 8.92 10,14 12.03 19.t5
_B_
15,83
16,96
14.37 10,86 22,95
3.98
45.06 100.00
First Second Third Fourth Fifth
31,51 24.29 19.74 15.96 10.28
19.59 18,48 49.85 18,72 14,45
I5.21 9,05 17.48 9,49 16.72 9.89 15,68 !t,98 12,15 12,17
3.84 4,[5 4,t7 4,33 3,72
8.43 10.89 I2.08 14.41 18,26
12,37 15.22 17,55 20,93 28,97
tO0,O0 lO0,OO 100,00 lO0,O0 I00.00
100.00 [O0,O0 100,_0 [O0.OO 100,00
42 Table6 Constrained Parameter Estimatesof the LA/AIDS Model a/ .............................................................................................................................
Price Total Equation Constant.................................................................... ExpendituresUrban CHRHAL M_T _H FUEL HOUSE CLOTH MISC
CrtHAL
0,5508 -0.0231
0,0287 -0.04[0
0.0537
0.0968 -0,0516 -0.0636
-0.(132
-0.0343
(t6,56) (-0,77) (t.37) (-2,S4) (4.06)(3.83) (-3.24) (-L37) (-9.07) (-4.75) iIBAT
0.2551 0.02B)-0.0082-0.0077-0.00450.0106 0.0280-0.0470 -0.0270 0.0023 (8.64) ([,373(-0,30)(-0.52){-0.39)('0.46)(2,00)(-1,82) (m2.403 (0.)5)
BIjVH
0.144SmO.04lO--0,00770.0506--0.0262 --0.06220,0235 0,0631 --0.0009--0.0012 (5.67)(--2.$4) (--0.52)(2.06}(--2,78) (--2'36)(2.46) (2,91} (--0,09)(--0.20)
FUHL
0,07S9 0.0S37--0.004S --0,0262 _0,013S"0,0252--0.01480.0204 (3,2S} (4.06)(--0.39) (--2,78) (--1.23) (--i,653 (--2.39)(1,80)
0.00% 0,0070 (I,II) {1,46)
HOUSE
--0.06850,0968 0.0106--0,0622 --0.0252 --0.0176 --0.01840.0160 {--1.46){3'82) (0,46)(--3,36) (--1.65) (--0,43) (--1,303(0,45)
0,0881 0.0136 (4.96) (1.36)
cLOTH
0.0447--0.0S160.0280 0,0225--0.0148 --0,0[840,0119 0.0213 -0,0012 0.0004 (2.87)(-3.24)(2.00) (2.46)(-2.39)(-I.30) (0,55) (I,553 (-0.20) (O.l[)
LikelihoodRatiotest statistic : 51,12. Critical chi-squareat 18d.f. (alpha:O.05) = 28,87. a/Homogeneity andsyuetry restrictions imposed, Note:Fi@ures inpareutheses areasylptotic t-ratios. Prices andexpeoditx)res areinnatiiral logarithm.
43
Table 7 Expenditure anti Bncompensated Price Elasticities .................................................
_ ...........................................
WithRespect to the Price of Equation ....................................................................... CEREAL IEAT BEVE FUEL ROUSE .......................................................
CEREAL IEAT BEVE
CLOTH
Total _ISCExpendit_lres
_ .....................................
-0,703
0,404
-0.313
0,161
0,431
-0,267
-0,095
0,382
0.282 -0.%4
-0.089
-0,047
0.069
0,136
-0,203
0.805
-0,294 -0.054 -0,629 -0.191 -0,453
0.175
0.457
0.990
FHEL
0.487 -0.118 -0.245 -l.l_5 -0,274 -0,148
0.293
1,141
HOUSE
0.[46 -0.27t -0.222 -0,084 -t.tSl -0.052 -O,lO?
1,741
CLOTH
-1,269
0,710
_[SC
-0.690 -0,505
0.588 -0.376 -0,445 -0.705 0,532
0.967
0.516
0,205
0,251
..............................................................................................
0,083
0,177 -0,038
44
Table 8 ExpenditureElasticities .............................................
Quintile
by Quintile _'_ .................................
CEREAL
WEAT
BEVE
FUEL
HOUSE CLOTH
MISC
0.648 0,594 0,531 0.452 0.179
0.801 0.807 (1.817 0.814 0,795
0.989 0.990 0.991 0.991 0,991
I.[54 1,153 l,ld6 1.151 1,147
2.341 2.323 2.116 1.932 1,685
0,960 0,969 0.970 0,97{ 0,972
1.818 1,654 1.573 1,483 {,304
0.816 0.806 0.819 0.808 0,751
0.991 0.992 0.992 0.991 0.989
l.{a7 1.140 i,134 {.133 i,I09
1,947 1.769 1,667 1,559 1.404
0,965 0.968 0,968 (1.969 0.964
1.695 {.538 1.485 1,406 1,32l
RURAL First Second Third Fourth Fifth URBAN First Second Third Fourth Fifth
0.523 0.381 0,238 0.058 -0,463
................................................................................