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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'