1997-98 fellows program in population policy communication€¦ · web viewtamil nadu and andhra...
TRANSCRIPT
Women's Education in Andhra Pradesh:
Killing Two Birds with One Stone
A Case Study of Differences in State Performance in Fertility Reduction in India
Sanjeev SabhlokPopulation Research Laboratory,University of Southern California,Los Angeles
3/10/981. BACKGROUND
Each year India adds more people to the world's population than any other
country. Toward the middle of the next century, India will overtake China as the most
populous nation in the world.1 The estimated total number of children that an average
Indian woman has over her lifetime (also called the Total Fertility Rate, or TFR) has
been on the decline since from about 6 in the 1960s to about 3.6 in 1991 (compared with
about 2.0 for developed countries). This decline has been rather slow, and the large
population in the reproductive age group is generating an enormous momentum for
continued population growth. In fact, even “if all young Indians decide to have no more
than two children each, the population would continue to grow for the next 60-70
years.”2
India was “a pioneer in the international movement to control population growth
by lowering birth rates. The government first officially promoted family planning in
1952 - 19 years before China launched its ambitious policy to slow population growth.”3
But the results of India's early efforts clearly left much to be desired. In fact, its own
target of lowering the crude birth rate to 25 by 1973, had not been achieved even by 1993
except in some parts of the country.
A wide variation in fertility is observed among the states of India. Differences in
implementation of family planning programs no doubt play a role in explaining some of
these differences in fertility. On the other hand, the family planning movement has been
almost entirely funded by the central government in India, and there has been a uniform
emphasis, throughout India, toward enhancing the supply of contraception and target-
1 See details at the PRB web site: http://www.prb.org/prb/media/tipquick.htm2 Visaria, 1995:43.3 Visaria, 1995: 4
1
oriented sterilization. It would appear, therefore, that differences in supply of
contraception do not fully explain these differences in fertility.
The search for reasons explaining state differences in fertility would perhaps
more fruitfully be carried out among the underlying factors influencing the demand for
children. Educational attainment – particularly among women, and their status in
comparison with that of men, the level of income in the family, the infant mortality rates,
and local cultural beliefs, are considered to be important determinants of this demand. In
fact, the importance of these factors seems to be now recognized at the national level
where there has been a recent shift in emphasis toward promotion of women’s rights and
health.4 This study is designed to examine the relevance of these factors and to test the
need for a shift in policy in Andhra Pradesh.
2. STUDY OBJECTIVE
Tamil Nadu and Andhra Pradesh are two large states of India in the southern
peninsula. Tamil Nadu has had consistently lower fertility from 1951 to 1990 compared
with Andhra Pradesh (Figure 1). In this study we examine plausible factors that might
explain higher fertility in Andhra Pradesh. The study is interesting because what is
known generally as a key determinant of the demand for children - infant mortality rate,
has seen a virtually similar decline across these two states for 40 years (Figure 2).
Another factor determining demand for children, the cultural factor, seems to be not
quite crucial.5 Therefore there must be other reasons for Andhra Pradesh’s higher
fertility. The study is based on a long series of data, extending for 40 years. This is
4 Visaria (1995).5 The language, religion, food habits, and many cultural practices in these two states are relatively similar when compared to say, the practices in Andhra Pradesh and Uttar Pradesh.
2
arguably a superior method of analysis compared with basing one’s conclusion on
detailed surveys carried out over a short time period.6 Using longer time periods helps
avoid paying excessive emphasis to a particular year where chance phenomena may have
played a role in determining the data. By using coarse and aggregated long-term data,
one does lose out, though, in the feel of the “pulse” of the people. Recent change, if
significant, is also masked.
3. METHODOLOGY AND DATA
Trends in the data were fitted using what are called multiple regression models. I
used the standard “synthesis” theory of Easterlin7 to frame plausible models. Numerous
subtleties were excluded, though, due to the coarseness of data. For example, in the ideal
world I would have liked to get household-level indicators on the status of women in the
state. But such information has neither been measured earlier nor is available in a format
that is comparable over time. Therefore I had to construct a broad indicator to proxy the
status of women with respect to that of men.
A questionnaire (see Appendix) was sent out to the Chief Secretaries of the two
states, and colleagues in the civil service in these states were contacted. Due to their
apathetic response, much of the data was obtained through other, more reliable, sources.
Many statistical sources were consulted. The primary focus was on the publications of
the Registrar General and Census Commissioner of India, publications of the Ministry of
Information and Broadcasting such as the annually published India, and the Gazetteer of
India. A very useful source was the Year Book 1990-91 on the Family Welfare
Programme in India, published by the Department of Family Welfare. Statistical
6 Retherford, Robert D., and B.M. Ramesh (1996).7 Easterlin (1996) discusses this model which was first proposed in the late 1970s.
3
handbooks of the states were consulted wherever possible. The Hindustan Year Book,
Manorama Year Book, Statesman Year Book, etc., which are privately published annual
statistical reports, were consulted. Books containing relevant data were also consulted,
such as Mamoria (1961), Bhattacharjee (1976), Andhra Pradesh (1995), Srinivasan
(1995), etc.
Despite extensive search, some data could not be obtained.
a) Data on the total fertility rate (TFR) were available only for a few years; therefore
the crude birth rate (CBR) had to be made use of.
b) In other cases, data had to be extrapolated, using appropriate smoothing
techniques. In the case of urbanization, for example, data is always available only for
every tenth year. The long-term non-linear trend at the national level was therefore used
as a guide in the process of extrapolating annual data on urbanization, so as not to lose
the essential character of this change.
c) On some aspects such as family planning expenditures and state level health
facilities, as well as on women’s work force participation, data was not only scanty, but
contradictory in terms of definitions, and hence had to be dropped completely. Not
including this information might have some potentially unpredictable effects on the
results. At the same time, what are believed to be the major potential factors have been
adequately captured.
4. ANDHRA PRADESH AND TAMIL NADU
With an area of 275,068 square kilometers and a population of 66.5 million in
1991, Andhra Pradesh (AP) is the fifth largest state in India both in terms of area and
population. The people of the state are predominantly Hindu (89 per cent), with 9 per
4
cent professing Islam and 2 per cent other religions. The majority of the people speak
Telugu (85 per cent), 8 per cent speak Urdu, and 7 per cent speak other languages. In
1991 the TFR was estimated to be 3.0 compared with the national average of 3.6. A little
less than half of all couples in the reproductive age group (45.3 per cent) were using
some method of contraception, compared with 43.5 percent for India. A vast majority of
the couples used sterilization (mostly of the females, but male sterilization was also
popular). The pill, IUD and condoms are other popular methods. Despite having a lower
level of fertility than the average level in India, the increase in population in AP between
1981-91 was 24.2 per cent, higher than the national average of 23.4 per cent. This higher
than national increase can be explained by the fact that AP had a lower than average
death rate.
Tamil Nadu (TN), with an area of 130,058 square kilometers, is the 11th largest
state in India in terms of area, but its population of 55.9 million in 1991 (6.6 per cent of
the national population8) places it in the 7th position, implying a high density. Hindus
constitute the majority religion of the state, with Muslims and Christians forming the
other major groups. In 1971, 84.5% of the population spoke Tamil, 8.7% spoke Telugu,
2.5% spoke Kannada and 1.8% spoke Urdu.9 After Kerala, TN has the lowest fertility in
India. The Total Fertility Rate (TFR, as described earlier) estimated in 1991 was 2.2, and
implies a rather low demand for children. The couple protection rate was 57 per cent. As
in the case of Andhra Pradesh, the most popular method was sterilization, followed by
the IUD, condom and the pill. The increase in population in TN in between 1981-91 was
15.4 per cent, much lower than the national average.
8 India 1994: 12.9 The Population of India (1974:72)
5
As far as social attitudes are concerned, while the two states are generally similar
in nature, including in religious characteristics, there is a major difference in the mean
age at marriage of females. In Tamil Nadu, social reformers like ‘Periyar’ Ramaswamy,
and later, Anna Dorai, in the earlier decades of this century, started what is known as the
“self-respect” movement, advocating an increase in the age of marriage and acceptance
of the small family norm.10 This seems to have contributed at least to some extent to the
higher mean age of marriage of females in TN (Mamoria, 1981:257) of 20.22 years in
1981. While this difference has been incorporated in the index of female status in this
study, there are arguments against reading too much into this difference. For example, in
Andhra Pradesh, the mean age of marriage was 17.25 in 1981,11 while it was 17.77 in
Uttar Pradesh (UP) where fertility is enormously higher than AP.
5. RESULTS OF THE STUDY
It is hypothesized that crude birth rate (CBR) is impacted upon by a host of
“demand-side” factors such as
* the Infant Mortality Rate (IMR) in a state,
* the percentage of population living in urban areas, or urbanization (URB),
* the per capita income in the state (PCI),
* female literacy (FLIT), and
* female status - measured through an index called FSTAT, which attempts
to capture the relative status of women in society compared with men.12
10 Srinivasan, 1995:250.11 Family Welfare Programme in India: Year Book 1990-91, p.159.12 Components of FSTAT include the sex ratio (i.e., the number of females to every 1000 males), the ratio of female age at marriage to 18, where 18 is the legal age for marriage of women, and the ratio of female literacy to male literacy.
6
Table 1 represents the findings. Factors that are found significant are shown by a
+ or a - sign, depending on the direction of their effect on the crude birth rate. For
example, a negative sign associated with PCI indicates that as income increases, the
demand for children decreases. Insignificant factors in a particular model are shown by *.
It would not make sense to include FLIT and FSTAT in the same model. Also, it
can be argued by some that PCI and URB possibly measure the same effects. Therefore a
choice of five models was considered. In model 1, as applied to both the states, only PCI,
FSTAT and URB were considered. In model 2, IMR, PCI, and FLI T were included. The
most “sensible” model, as far as theory goes, is Model 3 where the effects of IMR, PCI,
FSTAT and URB are considered. If asked to choose a single “best” model, one would go
by its results.
We see from Table 1 that the effect of increasing incomes and female literacy is
always to decrease birth rates. Increasing female status also decreases birth rates
unequivocally. There is a bit of a question with infant mortality, which in one case
(model 2) and in one state (AP) shows a non-intuitive sign. There is a possible issue here,
of a lag of time between the effects of drop in infant mortality the consequent reduction
in fertility. In most models, though, reducing IMR in a state would reduce birth rates.
The real question is about the behavior of the URB factor. Its sign is non-intuitive in
most cases. It is clear here that is another factor, positively related with URB, that has not
been captured in the models. The spread and extent of family planning services seems to
be this factor.
Table 1: ResultsImpact of different factors on the demand for children
and hence on the crude birth rate in the states of AP and TN.MODEL IMR PCI FLIT FSTAT URB
7
1 AP - - +
TN - * -
2 AP - * -
TN + - -
3 AP + - - +
TN + - * *
4 AP * - - +
TN + - - *
5 AP + - +
TN + - *
Technical note: Statistical significance at 5% is the only thing considered since R-squared is very high for all models, which is normal for time series models.
On considering the numerical size of the impact of various significant factors,13 it
is seen that female literacy and female status play the most powerful role in changing
fertility.
6. SIGNIFICANCE OF THE RESULTS
Many studies carried out in other contexts and circumstances have shown that
increasing female education, raising the status of women in society, reducing infant
mortality, economic development, and making available a reasonably priced basket of
contraceptives, increases the acceptance of voluntary fertility control. While we were not
13 Numerical magnitudes of the effects of the factors were excluded from Table 1 for the sake of simplicity.
8
able to examine the role of the supply of contraceptives, the importance of the rest of the
factors was mostly confirmed by this study.
Using data from the National Family and Health Survey of 1992-3, Retherford
and Ramesh (1996) have found that the provision of antenatal care (i.e., care during
pregnancy) to women is the most powerful predictor of demand for contraception. In our
study, the rapid declines in infant mortality in Andhra Pradesh are a strong proxy for the
quality of health care, and therefore this result of Retherford can be supported.
However, while they find primary education of girls to be important in other
states of India, they believe that “Andhra Pradesh is an outlier … inasmuch as this state
has somehow managed achieved to achieve quite low fertility despite low levels of
female education and literacy. This is an interesting result, suggesting that high levels of
literacy and education are not a necessary condition for achieving replacement–level
fertility.”
This interpretation of the Retherford et al., I believe, is quite misleading. It
appears to originate in the shortcomings of their study. They use the single year fertility
(observed in 1992-3) to base their results on. This fertility level, it would appear, was far
lower than what trend rates of the past 40 years would indicate. 14 Our study is superior
in this regard that the long-term trend in fertility is considered. The use of extensive
periods of time clearly demonstrates the well-known significance of female education as
the critical variable in supporting lower birth rates.
14 Of course, our study did not quite measure fertility correctly since we had to use the crude birth rate. However, the crude birth rates of Andhra Pradesh have always been significantly higher than those of Tamil Nadu. It is implausible that the TFRs in Andhra would be equal to Tamil Nadu during this period.
9
7. POLICY RECOMMENDATION
In Andhra Pradesh, nearly 67.3% of the women were illiterate in 1991. The gains
from making this huge share of the population literate would be enormous. Investment of
resources into women’s education would appear to be the most efficient use of scarce
resources at this stage. There are two arguments supporting this claim.
(i) Educated women demand lesser children and invest more effort in building up
human capital in these fewer children. The physical health of these children and
of the population is also enhanced, reducing pressure on the health infrastructure.
(ii) Educated women, by virtue of their higher level of skills, are more productive
than uneducated women. This increase in productivity has the effect of increasing
their incomes which in turn further increases the quality of life of the population
and simultaneously reinforces the lower demand for children.
That is why it can be said that by focusing on women’s education in Andhra
Pradesh, the government can “kill two birds with one stone.”
10
REFERENCES
Andhra Pradesh: National Family Health Survey (MCH and Family Planning) 1992 (1995). Visakhapatnam: Population Research Centre, Andhra University, and Bombay: International Institute for Population Sciences.
Bhattacharjee, P.J., and G.N. Shastri (1976). Population in India: A Study of Inter-Sate Variations. New Delhi: Vikas Publishing House Pvt. Ltd.
Easterlin, R.A. (1996). Growth Triumphant: The 21st Century in Historical Perspective. Ann Arbor : University of Michigan Press
Family Welfare Programme in India: Year Book 1990-91. Delhi: Department of Family Welfare, Government of India.
Hartmann, Betsy (1995). “Questioning the population consensus,” in Earth Island Journal, v10n2 (Spring 1995): 34.
India 1994 (1994). New Delhi: Ministry of Information and Broadcasting, Government of India.
Mamoria, C.B. (1961). India’s Population Problem. Allahabad: Kitab Mahal.
Panandiker, V.A. and P.K.Umashankar (1994). “Fertility Control and Politics in India,” in Finkle, J.L. and C.A.McIntosh (1994) (eds). The New Politics of Population: Conflict and Consensus in Family Planning. New York: Oxford University Press.
Piel, Gerard (1995). “Worldwide development or population explosion: Our choice,” in Challenge, v38n4 (Jul 1995): 13-22 1995
Retherford, Robert D., and B.M. Ramesh (1996). “Fertility and Contraceptive use in Tamil Nadu, Andhra Pradesh, and Uttar Pradesh,” a National Family Health Survey Bulletin. No. 3, April, 1996. International Institute for Population Sciences, Bombay.
Srinivasan, K. (1995). Regulating Reproduction in India’s Population: Efforts, Results, and Recommendations. New Delhi: Sage Publications.
The Population of India (1974). (CICRED series, 1974 World Population Year). Delhi: Ministry of Home Affairs, Office of the Registrar General and Census Commissioner.
Visaria, Leela and Pravin Visaria (1995). India's Population in Transition. Population Bulletin. Vol. 50. No. 3. Washington: Population Reference Bureau.
11
12
Appendix: SAMPLE OF THE QUESTIONNAIRE SENT OUT TO THE STATES
1950Demographics
1 Total Population (In lakhs)
2 Sex ratio
3 Crude Birth Rate
4 Crude Death Rate
5 Total fertility rate (estimated)
Health and Family Welfare1 Infant Mortality Rate (out of 1000)
2 Couple Protection Rate (family planning coverage)
3 Female age at marriage
4 Number of Primary Health Centres and Sub-Centers
5 Expenditure on Family Planning in lakhs of Rupees
Economic Status1 Per capita income (in current Rupees)
Work force participation1 % of women who work in gainful employment
2 % of men who work in gainful employment
Educational status1 Total literacy rate
2 Female literacy rate
3 Male literacy rate
4 Primary school enrollment of those eligible (total)
5 Primary school enrollment of those eligible (girl child)
6 Primary school enrollment of those eligible (male child)
Urbanization1 Percentage of population living in urban areas
13