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

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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.

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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.

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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

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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)

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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.

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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

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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.

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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.

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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.”

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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.

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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

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