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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


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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

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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

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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

................................................................................


Agricultural Growth and Rural Incomes: Rural Performance Indicators and Consumption Patterns