Ch.apter III

TRENDS IN THE

FERTILITY

DYNAMICS OF

IN INDIA

Chapter I I I

TRENDS IN THE DYNAMICS Of FERTILITY IN INDIA

Chapter II has revealed that rural and urban areas in

India have varied population growth rates. As a rule, urban

population is growing faster tt'.an rural and resul tantl y there

is a continuous increase in the level of urbanisation in the

country. This urban population growth is the collective

outcome of the functions of four demographic: components~

namely, natural increase, net rural-urban migration, emergence

of new towns and areal expansion of urban places. However, as

discussed In Chapter II, natural increase has been the single

most. dominant factor in determining the overall urban growth

rate in the country. Similarly, in rural areas also it is

natural increase which is plaYing a positive role while

migratiof) and other· fac.tors have a negative role on the growth

rate of rural pop,-,lation. This phenomenon maJ~·es f.ert11ity and

mortality the two most significant demographic components of

IndiaPs pOpulB~ion. Therefore, considering the role of these

components 1n shaping the country>s population both in rural

and urban areas, the present Chapter analyses the trends in the

dynamics of fertility while the following Chapter deals with

the trends in the dynamics of mortality in India during the

period under study. Tt-,is Chapter, besides summary, consists

60

three sections.

trends of rural

The first section discusses the levels and

and urban fertility. The second section

attempts to analyse the role of intermediate variables in

affecting rural-urban fertility trends. The third section is

on the socio-~conomic determinants of rural and urban fertility

in India.

Ctcapter.

The last section presents the summary of the

Levels and TJ~ends ot- Rural and UJ-ban Fertlll ty

Fertility in India, lil~e many othEitr developing

with the countries, has been very high. Even now when along

growing population on increasing number of live births are

occuring in the country, birth rates also continue to maintain

a high ·level. As a result, in an already large population size

there is a massive .aggregate annual addition of above 20

million people due to births. This characteristic

differentiates India from any other country~s fertility

behaviour having comparable socio-economic development and

explains the existenc~ of a number of social and institutional

factors in the ~ountry which control fertility trends in

traditional ·cultures. A custom of large families, partilcularly

in rural areas (Askhem, 1975, 1), a general desire for having

sons, nCR"! popul ari ty .of birth control measures (Cassen, 1978,

61

51} and high mortality of children (~andalbaum, 1974, I8)

ac.companied by ignorance, indecision and 'self interest

Nevertheless, associated with the role played by

moderni2ing elements which cause the transformation from high

to low fertility, there has been a traditional existence of

rural-urban dimens~on pertaining to fertility trends In all the

soci~ties (United Nations, 1984, 88). On the similar lines in

India also this dimension provides that fertility in the

country's rural areas is higher than urban ~nd hence there 150 a

rural-urban fertility differetial (Premi, 1983, 88; Ramu, 1988,

37}. The assumption behind this differential is the fact that

urb;::m dwslle-rs tend to have fewer chi 1 dren than rural dwell ers

<Census of India 1981, 1988b, 37) • Viewed ·from a broad

perspective,it is'the function of demand factor for prefering

certain number of children that makes the actual difference

between the ferti~. i ty rates of theSe? two areas. In the case of

India, the existence of this differential was recognised in the

early 19605 by Robinson (1961, 218-234) and later on by Davis

(1968, 70). BeSides, various rounds of National S.ample Survey

62

(NSS) ~Dnduct~d betweEn 1958 and 1967 have also confirmed the

e~i~t~nce of rural-urban fertility differentials.t all India

leyel. T",ble 3.1 shows the crude t>irth r,ate (CBR) for rural and

urban areas in the country estimated by NSS during this period.

Table 3.1 Crude Birth Rate ~ India~ 1958-67

Peri,ad Rural Urban

July 1958 June 1959 38.3 U

July 1959 June 1960 38.9 U

July 1960 August 1961 U 33.0

September 1,961 - August 1962 36.0 34.0

February 1963 - J",nuary 1964 37.0 31.5

July 1964 June 1965 37.1 31.9

July 1965 JUOIi!o 1966 36.3 30.3

JU,l Y 1966 :,,-tne 1967 36.3 30.0

Note . U - Unavailable . . Source: Premi ( 1982, 40) •

However, it was only with the ,inception of a more

reliable S.mple Registration System (SRS) in 1964 that the

spatio-temporal trends of this differ-ential came out with a

greater degree of reliability. Although the NSS conducted

fertility surveys even after 1967, the dual record system of

63

SRS ilii consider~d to be a superior method for Eliit1mating

f&r:-tility than time recall system of the NSS. With thlii

introduction of SRS~ a whole range of fertility measures have

become available which reflect that ~ertility in urban India is

lower compared to rural areas. Table 3.2 ~hows that the standard

measures of fertilit·y, like crude birth rate {CBR) , general

fertility rate (GFR), total fertility rate (TFR> , and gross

reproduction rate (GRR) indicate this differential in

rural-urban fertility for the period 1971-88.

Table 3.2 Crude, General, Total and Gross Reproduction Rates:

India, Rural/Urban, 1970-88

'(ear Rural Urban·

CBR GFR TFR GRR CBR GFR TFR GRR

19.70 39.~ 173.4 ~.6 2.7 30.1 133.2 4.1 1.9

1975 36.7 158.6 5.2 ,., c:-", • ..s 28.2 118.6 3.7 1.8

1981 3~.6 149.4 4.8 2.3 27.0 107.2 3.3 1.6

1984 35.4 153.1 4.8 ,., .,.. 4.";' 29.4 120.2 3 .. 5 1.7

1988 33.1 139.8 4 ? • ...> 2.0 26.3 103.9 3.1 1.5

Source .. Sam.ple ReerLstratLon System. • .1975, 1981, 1984, 1988. .

Table 3.2 indicates that different rates of fertility

have been continuously d&clining over' time despite the fact

that along with growing popultion in the country, increasing

number of women are entering the reproductive age group and the

64

aggregate numbliir of live births is continuously increasing.

whereas the CBR, which forms the basis of state l~v&l f&rtility

analysis 1n the n~xt section, has. continuous.ly, though slowly

declined, the GFR trends show that fertility measured in terms

of the number of children bor-n ir. a year to 1000 women in

reproductive age group has also gone down. How&ver, the sharp

difference between r-ural and urban GFR testifies that besides

alteration it, marital customs, mainly higher mean age at

marriage in urban areas, more urban women are practicing family

;:ilanning than rural women. The e)ctent of difference between

rural and urban GFR is, to a certain e>~~ent, a reflection of a

fertility trend effected by bjrth control measures. As

Bongaarts has described, if all marr"ied women throughout" their

reproductive span used no contraception, had no induced

abortion and experienced no lactation infecundity, thti'y would

achieve their m .. t>:imum fertility level, which he refers as

"natural fertilit~· CBo~gaart, 1978, 105-129}. Given the Indian

circumstances these observations are more closer to reality for

rural women and this is one strc"srI(J reason why rural GFR is

higher than urban.

The rate of average nu~ber of children born to a women

as she passes through her child bearing span, studied

TFR data, shows a slower declining trend in both the

65

through

areas. A

comparison of TFR with those giver.. in Table 3.7 on age sp.ecific

fertility rates would indicate that even after a period of

nearly 20 years owing to early marriage and high fertility

women continu~ to begin childbearing early and finish late.

Therefore, fertility has been quite high in the age group 20-24

and 35-39 and resultantly, reproductive span continue to be

around 25 years.

Taking into consideration the declining GRR it is

clear that over time fewer live births of females· per women are

taking place in the country and urban GRR is lower than rural·.

This effect, however, seems to have been conpensated by the·

fact that the reduced mortality is ensuring the entry ·of a

larger proportion of women in the reproductive age group and

consequently a reproductive women is now being replaced by more

women than a few decades back.

Thus, the different measures of human fertility based

on varied standards of reproduction whereas emphasises its

declining trend over time it also bring home the point that

there has been a clear differential 1n rural and urban

fertility, the former having higher birth rates than the

latt . .=:r.

66

I I I

R-liral-Urban Fert L l i t:y Tren.ds Si nee 197 J

A State Level Anal:ysis

Since 1971 the SRS data on fertility are available·

sepa .... etely for ru .... al and urban areas. These data at the state

level indicate the .varying fertility trends and their

rural-urban differentials among different states. Taking CBR as

a suitable indicater of fertility trends, Table 3.3 shows that

in many states in the country this rate has been quite high. In

fact, there has been a very strong positive· relationship

between rural and urban CBR, the correlation coefficient being

0.60 in 1981. This implies that the states having high or low

urban CBRs are also having high 01'" low rural CBR. Therfore,

whereas in low CBR states urban-rural continuum is helping in

minimizing these fertility rates in both the areas in hi9h CBR

states it seems that the dominant presence of values attributed

to high rural CBR on the one hand and lack of industrial and

occupational structure as well as exposure to many aspects of

modernization and development conducive to reduce urban

fertiiity~ have contributed in keeping the CBRs in both . the

areas at relatively higher levels.

Thus, in the north Indian, states of Haryana, Uttar

Pradesh, Bihar, Rajasthan and Madhya Pradesh, the CBR in both

the a .... eas is among the highest in the cpuntry. In Mahar,ashtra,

67

Table ~ "":W' ...) . .....,)

Trenqs ;in Crude Birth Rate by Rura.l/Urban Residence : India/States, 1971-1990

India/States 1971 * ~981' 1990

Rural Urban Rural

India 38.9 30.1 "':'P~ t -.)..J • ..J

AndhFa Pradesh 34.3 33.1 32.1 Arunachal Pradesh 35.8 + 34.7 Assam 36.8 28.7 34.8 Bihar 33.7 27.5 38.4 Goa 27.0 21.0 20.1 Gujarat 40.1 34.2 35.6 Haryana 42.5 32.0 38.~

Himachal Pradesh 36.8 23.5 33.1 Jammu & Kashmir 34.9 22.6 33.7 Karn",taka 32.3 26.4 29.4 Kerala 30.7 29.2 25.8 Madhya PF",desh 39.6 33.4 39.6 Maharashtra 32.0 29.1 31.0 Manipur 31. 7 24.1 NA Meghalaya ..... .,.. ~

""",,'t:.J. ~ 18.2 33.6 Na9aland 21.3 + NA Orissa 34.8 32.5 33.8 Punjab 31.1 30.4 30.8 Rajasthan 42.4 34.3 39.7 Sikkim NA t4A ..,..~ a:"

-.)..,) • ..J

Tamil Nadu 33.4 26.2 29.3 Tripura 35.0 22.5 25.7 Ut ::ar Pradesh 44.6 34.0 40.1 West Bengal 31.4 24.0 36.6

Notes: * Average of thre~ years, respectively.

NA Not Applicable.

Urban RUFal Urban

27.6 31.5 24.4

28.0 25.9 24.4 + 30.6 20.9

23.9 28.1 . 20.7 32.8 33.8 24.7 17.9 15 .. 4 15.9 30.9 30.6 28.2 29.8 33.3 27.5 20.8 27.6 19.2 23.1 33.3 24.1 25.8 28.8 24.0 24.5 19.0 19.3 31.9 38.7 29.1 25.9 29.5 23.6

NA 22.2 17.3 19.6 35.4 15.5

NA 16.7' 14.0 30.3 30.6 23.6 28.7 28.4 25.6 32.9 34.3 27.6 27.7 28.1 18.4 24.9 23.2 20.9 16.6 ..,- ....

.. ...J.~ 17.4 32.3 . 37.2 29.3 .20.4 30.7 18.3

1971-73 and 1981-83

+ There was no urban sample in Nagaland and Arunachal Pradesh up.to 1981. Data fOF 1990 is provisional. For Mizor'am, data is not available.

Source : (i) Sample Registration S-ystem, Sample Rel!{isl.ral. ion Bulletin, XXIII, 2, 1989.

(i1) Sampl~ Registration System,' Estimated Annual Birth and Death Rates (Provisional} 1990.

68

Punjab and South Indian states af Tamil Nadu, Karnataka and

Kerala, these rates have been relatively lower. In hilly

northern and north-eastern states,the CBR is among the lowest

in the countr~ chiefly because of high literacy, a superior

status of women and their greater partiCipation in the work

force as well as a high female age at mar.ri age.

Therefore, the areal differences in CBR reflect the

social and economic characteristics of local population. These

differences are themselves a function of diffrent social

classes and cultural characteristics of the concerned areas or

their industrial structure, of the nature and accessibility, of

the dwelling stocks and also of certain traditions associated

with different area~ which are more difficult to quantify.

However, despite u-,e prevailing CBR differentials between rural

and urban areas as \o\Iel1 as their inter-state variations, there

have beennoti~eable trends in CBR decline during the last 20

years~ As Table 3.3 indicates, this decline has been observed

by all the states, though its deg'ree varied. It may be seen

from the same Table that in 1971 the maximum and minimum CBR in

rural areas was 44.6 (uttar Pradesh) and 21.3

respectively, with a difference of 23.3/1000. In 1990, the

maximum rural CBR was 38.7 (Madhya Prade~h) while the minimum

was 15.4 (Goa). This caused Exactly the same difference

69

.-.'. '~If"\ .-''\.. '-. :- I

". :- --. ( =-- --.• ~ -- -. ! ".......... : .

•

..... "' .. , __ • '~'--n

-- - ..... : ~ '. -:- ~ --: . ~~ J \ •

• •

l "".J ---~_

I

Fig 3.1 69-A

INDIA CRUDE BIRTH RATE

RURAL~.

.~-.J'

1971

1981

1990

- . ~., -

J

between these two CBRs as it was in 1971. Similarly, the

maximum urban CBR in 1971 was 34.3 (Rajasthan) while the·

minimum was 1;:;'.2 CMeghalaya), making a difference of 16.1/1000.

If. 1990 the maximum ul>-ban CBR was 29.3

minimum was 14.0 (Nagaland).

(Uttar Pradesh) and

This caused a difference of 1~.3/1000. Thus, as a

whole the declining fertility trend in the country caused only

a slight tendency. of reducing the difference between the

maximum and minimum CBRs.

In fact, the declining fertility trends in various

states have encouraged among them the inconsistency and

disparity in C.c..iR and over time values of this rate have shown

growing Variations both in rural and urban areas of the states.

As the values of the coefficient of variation (C.V.) of rural

and urban CBR for 1971 and 1990 shows, in 1971 the urban CBR·s

C.V. was myc~ higher (17.89) than rural .(12.33). It implies

that urban CBR had a greater variation and ,inconsistency.

However, in 1990, although both the areas had shown increased

C.V., being 19.41 in the rural areas and 20.34 in the urban

ar:eas, it is cl·ear that increase in ttle variation was more

marked in rural areas.. It appears that the socia-economic

attributes which regulate the fertility trenosand determines

70

• Fi 9 3-2 70-A

INDIA CRUDE BIRTH RATE ,

URBAN

1971

t------t . 19 81

1990

•

its lEvel, I, ,ve obser· ..... ed increasing regional

Although in urban areas an already very high C.V.

disparity.

emphasises

and thE traditional existence of this disparity, the increasing

trend associated with socio-economic development among various

states during t~e last 20 years is particularly seen in the

sharply increased C.V. of rural CBR. On a single index this

characteristic is also reflected 1n terms of growing disparity

in per capita income among various states (Mohan and Pant,

1985,1580) . These emerging features clarify that the elements

of modernization and pro~ess of socia-economic d~velopment in

the country which ·are responsible for not only to cause

fertility decl~ne but to reduce its regional variations are

sti 11 confined 1n their spatic:d influence cimd hence regional

fertility differentials are increasing.

Ne ..... ertheless, .it ougt".t to be

determi nati on of I eVE~ sand tY-ends of

clear

urban

that in

fertility,

urbanization seems to have played a less significant role in

influenCing urban CBR in various states. A correlation

coefficient between the level of urbanization and urban CBRfer

the year 1981 and 1990 shows a highly insignificant

interrelationship as R-square values ciH-e -0.08<1981> and 0.11

(1990) • The empirical evidence may be seen in Table 3.3 where

lowest urban CBR has been recorded in those states where level

71

of urba~ization is relatively low. With the simultaneous

interplay af se0eral socia-economic and demographic as well ~s

behavioural factors relating to modern outlook, the level of

urbanization does not show any direct bea~ing in regulating

ur~an fertility. E)Cperiences around the world indicate that

for having any Significant influence on fertility urbanization

requires a substantial high level, which India lacks.

Moreover, as· seen in the previous Chapter, urbanization in

India t-.dS not been ac:c:ompanied by industrialization to the same

extent. Chi ef.i. 'yo due to above menti oned two reasons the rol e of

the urbanization affecting fertility 1s still inconsistent.

The most typical c:ase in this regard is from Kerala where

despite a low level of urbanization, urban CBR is also very

low. P~tcliffe (1978, 217) has attributed this feature to

soc:ial justice theory whi~h provides that the demographic:

trends and levels reflec:t the degree to which existi.ng

political and economic: institutions promulgate stic:1al justic:e.

This in turn, implies a more suc:c:essful implementation of land

tenure system than the rest of the states (Ratc:liffe, 1978,

217). Besides, higher wage rates for the landless labourers as

a result of unlonization and more labour intensive industrial

and servic:e sec:tors have caused a reduction in income

inequality although the average inc:ome remains low. Nag

(1984,33) has redic:uled the soc:ial justic:e theory by suggesting

72

that the lower fertility in Kerala is associated more with

greater eq~ity 1n education and health facilities than with

gr~ater equl t·y in income and assets. However~ irrespective of

these differences in arguments the fact remains that the state

government" 5 efforts an varioLIs SOCia-economic fronts have

largely helped Kerala having one of the lowest fertility rates

in the country.

Role o.f Inlel"mediale Variabls-s in A.f.fecling Rural-Urban Fert.ilily TJ"ends"

Davis and Blak~ C1956,211-2~5} have argued that there

are certain intermediate variables which directly affect the

hum~n fertility and function between social organization and

social norms on the one hand and fer·til i ty on the other. Under

this scheme they have identified elever-j variables integrated

within a definite framework. These are as follows:

I Variables Affecting Exposure to intercourse

A. ThG .. e governing the formation and dissolution of

unions in the reproductive period.

1. Age of entry into sexual unions.

2. Proportion of women never entering unions.

'3. Amount of reproducti ve period spent after or

bet~~een uni ons.

73

a. when unions are broken by divorce, separation or

desertion.

b. When unions are broken by death of husband.

B~ Those governing exposure to intercourse within unions.

1. Voluntary abstinence.

2. Involuntary abstinence.

3. Coital frequency.

II. Variables affecting exposure to conception.

A Fecundity or infecundity as aff&cted by involuntary

cause.

B. Use or non-use of contraception.

1. By mechanical and chemical means

2. By other means

C. Fecundity or infecundity as affected by voluntary causes.

III. Variables affecting gestation successful purtur1tion

A. Fetal mortality from voluntary causes.

B. Fetal mortality, involuntary.

Howe·;er, this framework has proved hard to

operationalize, mainly because of the absence of suitable data

on . the intermediate fertility determinants (Hobcraft and

Little, 1984,21). Therefore, this analysis ex~mines the role

of only those important intermediate variables which are

74

exposed to intercourse and contraception. Based on availability

of data, the·following variable have been selected for further

analysis~

1. Female age at marriage.

2. Proport1on of women aged 35-49 never married.

3. Amount of reproductive period spent between unions

when the same are broken by divorce, separation, that

is, the proportion of divorced or separated women in

the age group 10-49 and the proportion of widowed in

the age groups 10-49.

4~ Pattern of contraception prevalence.

Female Hean. Ae?·f? at J1arriage CFHAH:>

Female age at marriage is an important determinant of

fertility as it is directly related to the duration of

likelihood of conceiving and carrying pregnancy. Therefore, a

lower female age at marriage besides having high fertility

potential, also lengthens the span of marital union. In

contrast, a relatively higher female ag. at marriage causes a

shortening of reproduct.ive span which

like higher female 'liter~cy and

accompanied by factors

ultimately contributes towards

this regard falls into the

work

lowering

the former

75

force participation

fertility. India in

group_ A host of

socia-Economic (D,Souza,1974,46) and demographic factors in th~

Indian society<Wringley, 1978, 143) encourage a low f9male age at

marriage. As TCibie 3.4 reveals, in most of th~ stat~s the

existing female mean age at marriage (FM,AM) is below 18 years

and 0"11'"1ng 1971-81 theintercensal change was very slow. Since

a question on the age'at marriage of currently married women

was for the first ·timeincluded in the 1971 Census, the data

of FMAM are not available for 1961. However, in any casii!, the

then FMAM would not be higher than the existing one. Despite the

,fact that the urban FMAM has remained higher than, rural,the

difference is not significant enough to make it a major

explanatory factor in a higher rural and a law&r urban

fertility trends.

Although studies suggest thk prevalence of

infEcundity' '(Hobcraft,1985, 71> at the existing level of

rural and urban FMAM in the country, the age specific fertility

rate (ASFR) indicate that fer'tillty is rislng in the age group

20-24 compared to 1~-19. (Table 3.5). Thl$ observation

E!0tabllshesthe impression that later married women reportedly

make conscious effort to catch up their delayed cammen,cement

through rapid child bearing.

76

Table 3.4 Female Mean Age at Marriage . India/Major States, 1971-1981 .

Indi, a/Stat.es 1971 1981 Rural Urban Rural Urban

India 15.4 16.8 16.5 17.6

Andhra Pradesh 14.5 15.5 15.8 16.6

Bihar 14.5 15.6 15.9 16.1

Gujarat 16.9 17.5 18.2 18.5

Haryana 15.2 16.7 16.5 17.8

Himachal Pradesh 16.0 17.5 19.6 18.4

Jammu & Kashmir 16.5 16.7 17.3 17.6

Karnataka 15.7 16.8 16.6 17.6

Kerala 18.6 18.9 19.0 19.5

Madhya Pradesh 13.7 15.5 15.3 16.5

Maharasht.ra 15.2 17.2 16.3 17.9

. Orissa 17.0 16.5 17.2 17.3

Punjab 17.6 17.9 18.8 18.9

Rajasthan 14.2 15. 1 15.5 16.2

Tamil Nadu 18.2 18.0 18.3 18.4

Uttar PraDesh 14.6 16.6 16.0 17.4

West Bengal 15.2 16.7 16.0 17.4

Source: Cer,sus of India. 1981, Female Atf9 at Harria8e 1981 data analysis, -:teeasional P~per No. 7, 1988.

77

T .... ble ..,. C" "'> • ..J

~ge Specific Fertility Rate - Ind! a, 1970-88

ye .... r T/R/U 15-19 20-24 25-29 30-34 35-39 40-44 45-49

1971 R 112.8 262.7 282.6 217.0 139.9 70.6 19.1 U 74.7 230.0 217.2 163.5 93.4 37~3 14.122

197~ R 104.4 261.3 261.8 21222.4 130.2 58.9. 24.5 U 64.3 206.7 207.6 136.8 76.8 33.2 10.9

1982 R ':;6.4 258.2 245.5 180.122 ·112.4 53.9 25.8 U 62.7 207.6 193.122 117.9 62.3 26.3 12.0

1985 I R 97.0 267.2 232.1 163.0 .92.0 45.3 19.8 U 62.5 231.2 182.2 107.3 48.2 ·20.1 8.3

1988 R 97.1 26122.1 220.7 143.4 84.8 39.1 14.4 U 57.2 211.9 173.122 89.3 45.2 18.7 4.8

Source: Sample Re8istration System. 1970-75, 1982, 1985, 1988.

·However, over time the trend Of ASFR 1n thQ country

shows that with increasing FMAM it is continuously declining

which attributes that for the increase in FMAM, among

socio-economic measures as determinants of fertility decline,

are education {Cochran, 1979, 8>' Vocational training,

employment (Goldstein, 1972, 419) and other expanding social

and economic opportunities for women. To the extent that FMAM

is raised in this way it may at the same time reinforce other

soci.al c.hanges which tend to reduce fertility such as the

transformation of the extended family pattern into nuclear one

and the aC<7ep.tance of greater responsibility by the parents for

bringing up their own ci.ildren. Since the role of foregoing

78

discussed socia-economic components are more effec:tive 1n urban

areas, the low urban fertility trends may be ass.ociated with a

higher urban FMAM.

Therefore, an increasing FMAM ih India whereas

indicates the improving status of women 1n the country and

growing consciousness for their betterment,it is also working

as a medium to channelize the impact of various socio-economic

determinants 'of fertility decline. Therefore, a relatively

lower CBR in the states observing high FMAM is not the result

if any direct I.~gative impact of the former over the latter but

du~ to certain other socio-economic factors which are

attributed to lowering fertility. For example in Kerala, a low

fertility rate can not be conSidered as a direct outcome of one

of the highest FMAM, because, as mentioned earlier, a

favourable government policy and certain other social factors

like very high lit~racy have also motivating the people for

following the norm of small family. However, a note of caution

may be added that the degree of influence of socia-economic on

fertility rates through FMAM are always not the same in all the

states.

Proport ion of Women A8ed 35--49 Neuer Married

Traditionally, besides having low age at marriage

79

Ind1a also has almost a un1versal female marriag.e. Resultantly,

there is a very low accurrance of permanent celibacy among

. women which ·seems to have left very nominal or no negative

influence on fertility in the country. Table 3.6 indicates that

the proportion of never married women falling in the age group

35-49 was barely half percent in rural areas in 1961 which

fur·ther declined by 1981. Although a gr'eater opportunity of

self dependence, more exposure to the outside world and the

values attached to self identity appear to have caused a higher

proportion of never married women in the s~me age group in

urban areas, yet here too this proportion has observed a

declining trend during.1961-81.

Table 3.6 Pru~ortion of Never ~1arried Women in the Female Population Aged

35-49 : . India, 1961-1981 (1n p&rcentage)

. Year Rural Urban

1961 0.52 1.20

198~ 1.12

. Source: Census of India 1961 and 1981, Social and Cul.tt.tral Tables, India, Part-II- C <i) and IV-A respect! vel y.

This trend is contrary to that in the developed

countries where remaining single 01"" cohabit1ng without marriage

has been dominantly emergi ng on the demographi'c scene (Kiernan,

1989, 31) and like late. female age at marriage, it also has a

80

mor'e potent impact on fertility decline. In fact, in pr&sently

developed countries the proportion of remaining never married

women duri'ng'the later part of the 19th and the early 20th

century was almost 10 per cent. This proportion of females

never marrying may be much higher now.

In this regard, the basic difference between d&veloped

world and India lies in terms of difference 1n the for-ms of

social organization and prevailing religious belief which

permit or prohibit the women to lead a single life with

respectability. Whereas in the former society, the high levels

of urbanization, employment of womer, in non-family wage' labour

and permission by Catholicism to live Single, have encouraged

permanent celibacy among women, in India the value based

kinship system accompained by the lack of skill, freedom and

job opportunities among females, discourage them to remain

permanently unmarried. Hinduism and ,Islam, the two major

religions of more than 90 per cent population in the country,

are opposed to individualism (Kapadia;1l'd/1~'Far'ma1an, 1978, 217) •

As a consequence, there are very few women who never had a

partner by the ,time they reach in theirfourties. This mar,ginal

prpcirtion of never married women is also obvious because there

will always be a minority of women who do not marry because of

illness or physic~l deformity. Thus" although compared to

81

rural areas, the pr.oportion of single women in urban areas is

high, the general trend of the proportion of never married

women in the countr'}/' does not show any high plus ferti 1 1 ty

.value.

Proportion oj women Divorced. Separated and Widowed A6ed 10-49

. Any negative influence of the iilmount of reproductive

period on f er't il i t Y is Qoverned by two marital . functi ons -. a) When unions are broken by divorce or separ ati on.

b) WhQn unions are 'broken by death of husband.

_ As a rule, the more these functions are stable, the

less fertility will be effected adversely. In India, like ,the

proportion of permanently single women, the proportion of

divorced or separated females has also remained very low and

declining_ The same socio-religious factors wh1c~ prohibit

permanent celibacy, are also discouraging the divorce or

separa.tion- of couples. Along with the pressure of social

structure and emotional rela.tionship, an economic insecurity,

particularly among females, helps couple intact together.

Consdering the observed heavy correlation between marriage

dissolution and informal unlons,the'latters disapproval in the

Indian society ma'{es divorce or separation further difficult.

However, data ,~i\len in Table 3.7 show that the percentage of

82

females divorced, separated and widowed if, the reproductive age

group has been higher in rural areas compared to urban and both

these groups of women have observed a declining their

proportion between 1961 and 1981, although the percentage of

,widowed pas ,been very high compared to the former category of

women.

Table 3.7 Proportion of Females Divorced, Separated or Widowed of the

Female'Population in Age Group 10-49 :India, 196i-19'&

Year Rural/Urban divorced or separated Widowed

1961 Rural. 0.,80 6.47

Urban 0.62 5.63

1981 Rural 0.65 3.30

U!'-'ban 0.42 2.91

SOGrce : See Table 3.6.

Therefore, the declining proportion of divorced or

separated women and widow in urban as well 1n rural areas. is

also contributing towards hampering the fertility decline 1n

the country. Although a grleater e~po!iure to death and mor~

impact.of certain chronic diseases' cause· more possibility of

male deaths 1n c~rtain age groups, 1n contrast to many

developed countries, in IQdia male life expectancy has been

higher than females and it has increased over time~ This

83

phE;-,o'flenon accompanied by a trend of widow-remarriage has been

contributing in declining proportion of widow in the country.

In fact, the effect of increase in the age at marriage or

decrease in the proportion of married female!D at

on fertility decl:ne are offset by ·the contrary

younger ages

impact of

'de~lining proportion of divorced or separated and widowed.

Role of V~'iables Affecting Exposure to Conception

Th~se variables under the schema of Davis and Blake

basically refer to

mettlods. Whereas

the

the

use and non Use of previously di~cus!Ded

contraceptive

intermediate

variables affect fertil.ty through ob!Dtinence, the effici9ncy

of these instrumental fertility control measures depends on the

e~tant of use. In India, although the tradition to control

human fertility consciously and intentionally has an old

history (Agarwala, 1962, ~4), in modern times three main

fertility ~ontrol means have been in practice for this purpose.

These are contraceptives, sterlization and induced ab~rtion.

The_a means 1n the country are largely chennelized through

national family welfare programme. However, despite th9. first

government sponsored family planning programme in the world,

the initial ten to fifteen years were devoted to different

strdtegies and approaches without any marked achievement and

services proposed under this programme developed only slowly.

84

How~ver available data show that the programme made a h~adway

_1nc~ th~ late 1960s and although sterlization ·r~m_1n~d th~

most prominent form the use of IUD, pill. .nd l~galisQd

abortions w~r~ also added in it sub6~quently. As data in Table

3.8 on coupl~ protection rate at all Indi. 1&v&1 reveal. that

wher.eas in 1970-71 only eight percent of the eliQibls couples

were protected due to sterlization, in 1986-87 this b&came 28

percent. S~milarly, CPR due to IUD, though remained v~ry low it

moved from 1.4 percent ... n 1970-71 to 4.8 percent .in 1986-87 for

effectively eligib1Q couples.

Table 3.8 Couple Protection Rate: India, 1970-71 to 1986-87

Year

1970-71

1975-76

1980-81

1985-86

198(.,-87

Percentage of eligible Couples due to sterlization

8. III

14.2

20.1

26.5

27.9

Percentage of eligible couple. due to IUD currently

1.4

1.1

1.1

3.9

4.8

Source: Government of India, Family Welfare Yearboo~, 1987

Inspite of wide gap between the couples protected due

t, sterlization and IUD there has been tremendous increase in

the couple protection rate due to these measures. However, the

85

growing use of these two measures along with ctindoms indicate

thatfamily welfare programme in India has developed markedly,

from the point of view of present study it is important to

gauge the role of this programme in relation to fertility

decline in India. According to criterion of the population

Council, New York, 5Watson, 1977,~), to assess whether national

famil"y planning statements are supported by pr"ogramme activ1ty,

"real programetic support" is considered to exist 1n a country

if the number of family planning acceptors is equivalent to one

per cent of the number of women aged 15-49. Although family

planning in India attracted a number of acceptors equal to one

per cent of the number of women aged 15-49 (Table 3.9), it is

still not considered strong enough as it has failed to meet a

more reasoriable and harsher criterion to define a vigorous

programme by not being able to attract five per cent accepters

of the number of women aged 15-49.

Table 3.9 Pe"rcentage of IUD and sterl ization accepters to females 15-49

years in rural and urban areas.

year IUD sterlizat10n ------------------- ----------------------

Rural Urban Rural Urban

1970-71 0.32 0.71 1.48 3.05

1981-82 0.35 0.69 1.36 1.96

Source: See Table 3.6 and Table 3.8.

86

Moreove~, other birth control measu~es like, induced

abo~tion, the principal cause of bi~th cont~ol in European

countries and Japan along with contraceptive (Ewell, 1971, 60),

was legalized in India in 1972 on a very low level of

application. Officially called Medical Termination of

P~e9nancy, its impact on fe~tility decline has been considered

negligible (Jain di,d Adla~{ha,

mode~n tempo~i<.ry methods like

1982, 595). Likewise other

pills .have also been made

a\'rll.lable only recently and their- use is still very limited.

Tietze and Bongaarts (1975, 114-120) have demonstrated that

historically the levels· of fertility near replacement were

rarely, if ever obtained, without substantial reliance on

abG: tlon,. and on the basis of computer simulations of modern

c:ontracepting populations, he concluded that barring a major

br-·eakthrough in contracepti ve· technology and major

modifications 1n t-,uIHan sexual behaviour, levels of fertility

required for pC'. Ltlation stabilization can not

obtained without induced abo~tion. Taking these

be easily

issues into

conside~ation,. it is clear that at the existing level althougt.

the pe~formance of family welfare prog~amme has been proving

contributory in fertility decline a more rigorous effort is

till desired to make it much mor-e effective. Partlcula~ly

non-conventional methods of birth control and induced abortion

deserve special attention.

87

Thus, the analysis of the role bf selected important

intermediate variables on fertility trends in the country

indjcates that female mean age at marriage is probably the most

effective one which bears the status of women as well as their

socio-economic importance. This is followed by variables

exposed to conception. The remaining variables like never

married women in the age group 35-49 proportion of widowhood

and divorced 1-1.-;5 not been significant in causing fertility

decline. Obviously in a developing society like India~s it

might well be the case that the traditional value orientations

following religious believes and social systems would better

account for variation in fertility behaviour than modern

orientations dealing with divorce,sepeation or remaining

unmarried.

Socio-Econoinic Det.erminant.s of' Fert.ili t.y Trends

Although in determining the levels and trends of

fertility intermediate variables play their role, being a

complex component of population change fertility is largely

trends are influenced by a set of· socia-economic and cultural

factol'"s (Bongaarts, 1978, 11225-129) • However, in India, in many

instances the role of these factors have remained unclear

('Jorapur, 1'968, a~-83; Dandekar, 1959, 72. Dandekar and

88

Dandekar, 1953. 60-66; Pethe, 1964, 68}·. The issue becomes

fu· ther complicated since a majority of people in the country

are staying 'in rural areas who tend to have higher fertility

compared to urban areas~ Therefore, owing to differences in

fertility behaviaur between these two populations, the de~ree

of J.iTlpact'of fertility determinant may also vary between rural

and urban population. In view of these factors, this;, section

attempts to analyse the role of socia-economic factorg. by using

multivariate tectmique based on step-wise multiple regression.

For this purpose eight explanatory variables have been selected

which according to Serelson and Mauldin (1978, 84-148) have

most effective, influence on human fertility. since these

independent explanatory variables are related to demand factor

which produce motivation for family limitation or account for

fertility decline, total fertility rate (TFR) seems to be a

more ideal dependent variable. Following is the list of

independent variables u~ed In this study ~

Xl = Primary and middle school enrollment as a percentage of the 5-19 age group.

X2.= Percentage of urban population

X3 = Percentage of literates (age 10 and over)

X4 = percentage of male workers 1n non-agricultural sector

X5 = Per capita income

X6 = Female mean age at marriage

89

X7 = Infant mortality rate

X8 = Crude death rate

In the present analysis in order to show how far these

factors have affected TFR on rural and urban areas in 1975 and

1985, the previously mentioned variables have been taken for

the years 1971 and 1981 separately for rural and urban areas,

except X2 and X5 which is commo~ for both. Since TFR. values

obtained from SRS are limited to major states, this exercise

has been conducted by using the data of 14 major states.

Determina.nts of Rura.l ]FR in t975 and 1985

A stud"y of the inter-correlation matrix 91 ven 1n

Tables 3.10 and Table 3.11 showing the interrelationship among

the eight explanatory variables affectirlg rural TFR in the

country in 1975 and 1985 reveals that largely .these variables

have shown ver"" strong correlation with TFR .. Naturally, most

of these var,'iables bear a negative corralation except the

Variables' of crude death rate and infant mortality rate which

have a positive correlation with TFR. This interrelationship

justifies the observation that more deaths encourage more

bit":hs. It is particularly due to ·this kind of relation~hip

that India continues to have high births and high deaths

simultaneously for a considerably long period. To keep the

90

.family ~ize within accepted family limit high d~ath rates have

always encouraged high birth rates. This feature al~o indicates

that in spite of marked mortality decline infant mortality

still poses a major danger 1n the minds of the people reQarding

the survival of their off-springs.

Table 3.10

Correlation Matrix Among Variables: India, Rural 1975

y Xi X:z X3 X. X!s x.s X? Xs

Y 1.000 -.684**-.201 -.656 * -.591* -.002 -.625 * .586* .500

x· 1.000 .124 .722 .629* .250 .~48* -.408 -.452

X2 1.000 .298 -.079 .443 .188 .003 -.155

X3 '1.000 .688** .061 .714** -.295 -.371

X. 1.000 .142 .632 * -.713**~.696**

X!s 1 ~000 .216 -.154 -.454

Xes 1.000 ' -.422 -.478

X';' 1.000 .923**

Xa 1.000

Note . * Signiilcant at 5T- level. . ** Significant at 1'Y. level.

The 1~lost important change in the correlation between

TFR and other explanatory variables in 1985 in relation to 1975

has been in the case of the correlation of urban population

percentage. This explanatory variable had shown a rather weak

negative correlation with TFR in 1975. But the value of

91

Table 3.11 Correlation Matrix Among Variables: India, Rural 1985

y Xa

y 1.000 -.890**-.821**-.204 ** -.700 -.220 -.778** .702** .752**

Xs 1.000 .90S** .024 .845** .272 .697**-.742**-.753**

X2 1.000 .003 .826** .157 .757**-.605* -.669**

X3 1.000 -.151 .407 .190 -.081 -.160

X. 1.000 .169 .638* -.805**-.766**

X5 1.000 .393 -.273 -.435

Xes 1.000 -.494 -.653 * X7 1.000 .911**

Xa 1.000

Note . * Signifi"cant at 5r. level. . ** Significant at IX level.

correlation sigr .... fy a. marked increase in 1985 from its

previously held posit.ion in 1975 which indicates t.hat with

growing urbanization the rural-urban l1nkages are also

contributing in declining TFR in rural areas.

The results of st.ep-wise regression platted 1n Tables

3.12 and 3.13 indicat.e t.hat. in 1975 in t.he country~s rural

areas the most dominant, factor affecting TFR was the percentagE!

of children enrolled in primary and midcle education falling in

the ayE! group 5-19. Thi s ",as followed by infant mortal i ty rate,

92

percentage of literates above age 10 years, crude birth rate,

non-agricultural male workers and per capita income. The most

dominant determinant e):plained 46~ 7 percent of the' total

variation and in each subsequent step the explanatory

determinant have raised the explanatory power by 11.3 percent,

5.5 percent, 6.8 percent, 3.9 percent and 3.5 percent, thus,

explaining as much'as 77.7 percent of the Variation in TFR. In

this analysis only six steps had been retained because after

that the value of R had started declining. Furthermore, a

smaller contribution of other determinants compared to the

first one is also due to the fact that a part of their

contribution has already been e)~plained by the first dominant

var., Cible.,

The results of step-Wise regression for the year 1985

indicate that the p~rcentage of children enrolled in

and middle educdtion continue to be the, most

explanatory determinant of TFR explaining 77.6 percent

primary

important

of the

total variation. This percentage of variation has been 30.9

percentage point higher than the 1975 percentage of variation.

This was fallowed by three other' explanatory determinants of

female mean age at marriage, percentage of literates 10 years

and above age group and per capita income. At each subsequent

step e):planatory variables have raised tt-.E E>:planatory power by

93

4.8 per-cent, 1.8 percent and 2.3 percent which together-

explained as much as of 88.2 percent variation in TFR.

Table 3.12 Results of Step-wise Regression Analysis: India, Rural, 1975

Step 1 y.: 6.a8~2121 (,596) R2= .467

Step 2 '( 5.14~26

(1. 152)

.1219332 Xl (.029) R = .423 F = 10.529

• 07283X 1 + .01112 (.029) ( .01216)

X7

R2= 0.580 R = .504 F = 7.607

Step 3 '( = 5.12962 - .03946 Xl + .01111 X"" ..:. -(1.126) ( .039) ( . (063) R2= 0.635 R = 0.526

Step ~ Y = 6.1301212 - .04165 Xl + .02996 X7 ( 1. 279) (. (38) (. 014 ) R2= .703 R = .571

• 02082X3 (,017)

F = 5.810

.12124487 X3 (,016)

.20119 xa (.140)

F = 5.325

Step 5 Y = 4.72fll66-.fll4478Xl+.fll3775X7-.03718X3-.21349X8+.05886X4 (1.805) (,037> (.016) (,019) ('140) (,054) R2~ .742 R = .580 F = 4.594

Step 6 Y = 7. 19057-. 1212553 X 1+. 06323X7-.05125X3-.47972X8+.07055X4-.00241X5 (2.954) (.041> ('029) (,024) <'289) <.055) (,002) R2 = • r,. 7 R = . 586 F = 4. 063

Note : Figures in Parentheses are standard Error

It is clear with the results of step-wise regression

analysis that the education of children in primary and middle

classes has been a dominant determinant of rural TFR. That is

educating child~en in these classes play an important role in

motivating the parents to have fewer member of children.

Therefore, whereas, the educational attainment of parents and

94

other socia-economic factors related to fertility control are

well recognized, the education of children is also becoming

significant determinant of fertility~ particularly in rural

areas where the literacy rate is still very low.

Table 3.13 Results of Step-wise Regression Analysis! India, Rural, 1985

Xl Step 1 Y -= 6.85706 (.368) R2= .793

X6 Step 2 Y - 10.68552 <2. 129) .

,-2 f'~ = .841

X3 Step .... Y -= 10.50810 ..... (2.110) R2= .859

X6 Step 4 '( = 10.90898

.01673 Xl (.017>

R= .776 F = 45.911

- .08624 Xl - .25843 X6 (.021 ) (.142)

R = .812 F = 29.048

.08993 X1- .21925 X6 (.214) (.145)

R = .816 F

- .09154 Xl - .26127 X6

- .01805 X3 (.016) = 20.24

.02634 X3 + • 0007X5 (2.053) ( • 021 ) ~ . 143) (.016) (.0005) R2= .882 R = .829 F -= 16.826

Note: Figures in parenthesis are standard error.

Determ.inants ol Urban TFR in 1975 and 1985

Like in the CAse of rural TFR determinants, a study of

the inter-correlation matrix for urban areas. given in Tables

3.14 and 3.15 showing the interrelationship among the given

Variables indicated that whereas mortality variables of infant

95

mortality rate and crude death rate have obviously been having

a positivE ~elationship with TFR, two other determinants ·of the

proportion of workers in the non-agricultural sector and per

capita income have shown a very insignificant positive

relationship with TFR in 1975. Howeve~, by 1985 all the

variables except .those of mortality have shown negative

relationship with TFR.

Table 3.14 Correlation Matrix A~ong Variables: India, Urban 1975

y X1 X:z Y.3 X" . X!; XCi X7 Xa

Y 1.000 -.533 *-.074 -.323 .216 .035 -.458 • 797 *" .• 831 * ..

X.t 1.000 .242 .828**-.140 .268 .737** -.489 -.569 *

X2 1.000 .101 .148 .443 .252 .139 .003

X3 1.000 -.009 .265 .673** -.203 -.282

X4 1.000 .448 -.2133 .475 .177

X5 1.000 .. 359 .002 -.196

X6 1.000 -.265 -.361

X7 1.000 .891**

Xa 1.000

Note , * - Significant at 51. 1 evel. .

** Significant at 11. level.

The results of stepwise regression analysis given in

Tables 3.16 and 3.17 show t~at in1975 crude death rate emerged

96

as tt. most dominant determinant of TFR explaining as high as

69.0 percent of the tbtal variations. This was followed by

other determinants of per capita income~ female mean age at

marriage and perce~tage of urban population. In each subsequent

step these determinants have raised the e):planatory power by

.4.1 percent, 6.1 percent and 2.2 percent which together

explained as high as 81.4 percent of the variation 1n TFR.

Table 3.15 Correlation Matrix Among Variables India, Urban 1985

y X1 X2 X3 X" x~ X6 X7 Xs

'( 1.000 ** ~ T'""=** 19 J -.208 _ 7"7"7"** .5.83* .629* -.777 -.0,:,9 -. _'-* -. 0 • ~.j

X1 1.000 .033 .868** .007 .107 .652* 1::"8-* -.,.J ~, -.461

X2 1.000 .003 .391 .4. ! .153 -.141 .274

X3 1.000 .251 .158 .690** -. 3~-.4 -.289

X4 1.000 =6'7* • .J "- .187 .076 - •. 037

X~ 1.000 .483 -.166 -.052

Xes 1.000 -.293 -.222

x? 1.000 .805**

Xs 1.000

Nate . '* -: Significant at 5'Y. level .. . ** Significant at 1'Y. level.

The result of step-wise regression analysis for 1985

indi~ate that percentage of children in primary and middle

97

cl~ ises falling in the age group 5-19 emerged as the most

important determinant of TFR explaining 69 per cent of the

total variation. The other dominant determinants were crude

death rate an~ female mean age at marri~ge. At each subsequent

'=> ,-ep these determi nants have rai sed the E):pl anatory power by

9.2 percent and 10.5 percent which explained 80.1 percent of

the variation in TFR. It is clear with the analysis of

explanatory variables that level of urbanization have not shown

significant impact on the fertility in urban ~reas of the

country and like in the case of rural areas, in urban also the

enrolment of children in primary and secondary classes has

emerged a forceful determinant of urban fertility.

Table 3.16 Results of Step-wise Regression AnalysiS

Step 1 Y = .72969 + .30804 X8 ( • 573) ( • 059 )

R2= .690 R = .665 F 26.78

Step 2 Y= .03607 + .32299 X8 + .00(£18 X5 ( • 775) ( . (59) ( • 00064 ) R2= .731 R = .682 F = 14.96

Step 3 Y = 3.42012 + .29184 X8 + .000117 X5

India, Urban, 197~

.19571 X6 (2.113) ~.(57) (. 00(63) (. 115)

Step 4 Y = R2= .792 R = .729

3.14387 (2.116) R2:: .814

+ .30(£185 X8 (. (57)

R =

F :: 12.66

.00146 X5 (. (0068) .732

.177 X6 ~ .016 X2 (. 1156) (. (15)

F = 9.89 ---;...-------:----------_._--_._--_ •. _-------------------Note : Figu~es in parentheSiS are standard errors.

98

Tabl e 3. 17 Results of Step-wise Regression Analysis: India, Urban, 1985

Step 1 Y = 5.62~45 - .06728 Xi (.513) (.016) R2= .604 ~ = .571 F = 18.31

Step 2 Y = 4.13689 - .~5359 Xi + .13942 xa (,935) (.016) (.076)

R2= .696 R =.641 F = 12.64

St&P 3 Y = 8.46132 -.?2770 Xl + . 15685 X8 .2973 X6 (2.05) (. 017> (.065) ( . 129)

R2= .801 R = .741 F = . 13.42

Note . Figures in parenthe-si s are standard errors • .

Stmunary

The analysis of this Chapter has revealed that

fer(llity in India, desp~te its declining trend, is still Very

high. In fact, over time there has been very slow change in

different fertility rates in the country. The spatial·

variations anu rural-urban attributes in this regard are quite

markable. As a rule, urban fertility rates have been lower

than rural. In the South Indian states CBR in both the areas

is not only relatively low but their decline has also been

faster. Compared to this in the north Indian states of Uttar

Pradesh, Bihar, Madhya Pradesh and Rajasthan fertility rate is

still quite high. Therefore, a sustainable fertility decline

99

of a significant magnitude 1s yet to begin in some of these

north India s·ates. These characteristics have been common to

r0ral and urban areas. That is, states with a high rural CBR

also have a high urban CBR. Contrary to this, in low rural CBR

states, urban CBR is also relatively low. In this connection it

is noteworthy that in spite of a low urban fertility rates,

urban CaR urbanization have not shown any strong correlation.

It appears that the low. level of urbanization in the country

has riot been effective in making its influence on fertility.

However, with the declining urban as well as rural CBR, the

inconSistency in CBR prevalent among various states has

ihcreased in both the areas during 1990. Although in urban

areas this :nconsistency, analysed through coefficient of

variation, has been higher than rural, the rural areas have

ob~erved a more marked increase in the values of coefficient of

variation between 1971 and 1990. Obviously, these features

emphasis&! the gro"'~ing economic disparity among states in the

country which have probably, been more rapid in rural areas.

In view of the fact that human fertility 1s affected

by certain factors, referred as intermediate variables· in

demographic literature (Davis and Blake~ 1956, 211-235). It has

been found that the data of all the· proposed ·11 intermediate

variables are not available. Therefore, the selected such

100

variables which function b~tweEn social organisation and social

norms on the one hand and fertility an~ the other, indicate

that female mena a~e at marriage and family planning measures

appear to have bFen effective in fertility decline in the

country. However, whereas female age at marria~e in the

country is still very low and family planning programtT,es are

yet to attain popularity among the masses, it is clear that a

desirable fertility decline ih the country needs more

concentrated effort towards making these two variables more

effective. Since female age at marriage reflects the status of

women and. their educational and economic progress, any attempt

to increase their age at marriage implif 5 the provision of more

socia-economic opportunities for women in the country.

The socio-ecDnomic determinants of fertility in the

country have indicated wide variations between rural and urban

areas and these determinants have changed durin~ 1975 and 1985.

However, in rural areas the percentage of children enrolled in

primary a~d middle classes to the total number of children in

the age-gr6up 5-19 has been the most effective determinant for

TFR. In urban areas, although in 1975 crude death rate was the ,

most important de1;-erminant of TFR, by 1985 in urban areas also

the percentage of enrolled children in primary and middle

school became a dominant factor. Thus, it is clear that the

101

education of children 1n primary and middle school is proving

helpful in motivating the parents for having lesser number ·of

. children. Their growing cost of education and other problems

related to .the children~s future prospects, are compelling the

parents to have lesser children.

TFR negatively.

This, in .turn is affecting

Hit'