From Death to Birth Mortality Decline and Reproductive Change (1998) / Chapter Skim
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10 Micro and Macro Effects of Child Mortality on Fertility: The Case of India
10 Micro and Macro Effects of Child Mortality on Fertility: The Case of India
Pages 339-383
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From page 339... ...
Perhaps because of the increasing availability of survey data on individual couples, much of the recent analyses of the relationship between infant mortality and fertility has focused on the estimation of the replacement rate and on refining techniques to measure it. As the estimated replacement rates are generally significantly below unity, an increasing body of literature has concluded that declines in child mortality tend to accelerate population growth both in the shortand the long-run.
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From page 340... ...
Child deaths are represented on the horizontal axis and are assumed to reflect only the changes in child mortality (q) and not of live births.
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From page 341... ...
341 ;^ o 4= ca ;^ so 4= ~ so .O ~ o ca ,4 · ~ 4..
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From page 342... ...
An extreme example of this is the decline in child mortality until point A in the graph which will not elicit any fertility response. Note that at extremely high mortality levels a price effect may be operating to suppress fertility levels (Schultz, 1976~.
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From page 343... ...
As mortality declines from point A in the RH curve, unwanted fertility (given by the vertical distance between the RH curve and the line B`3) begins to accumulate since desired family size falls, but substitution of replacement for hoarding does not occur at the desired speed.
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From page 344... ...
Fortunately, because mortality levels at different intervals are strongly correlated, it should be sufficient to employ an age range that includes the majority of child deaths. I have used the under-5 mortality rate (q5)
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From page 345... ...
Because fertility levels are influenced by family size desires in addition to child mortality, it is essential to control for changes in the former so as to obtain an unbiased estimator of the effect of the latter on fertility. A question arises as to whether factors influencing unwanted fertility should also be used as covariates in the regression.
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From page 346... ...
it is obvious that unwanted fertility is a direct consequence of r end p being different from 1. When the two parameters are less than 1, child deaths and desired family size are inversely related to unwanted fertility.
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From page 347... ...
Cd .~ LL 5 a'45 cat 4 3.5 347 - 250 '\ 1 1 1970 1975 1 1 1980 1985 1990 Year a) - 200 ~ .~ o ~1 - 150 _ - 100 FIGURE 10-2 Trends in the total fertility rate and the under-5 mortality rate, 3-year moving averages, all India, 1971-1991.
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From page 348... ...
(5) When the model is estimated in this form, the coefficient of lagged fertility provides an estimate of the parameter X, from which the implied mean lag of fertility response to child mortality can be computed as \/~1 - hi.
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From page 349... ...
349 o EM a' 3 · _4 o .~ a' a' o a' o be ~ o o a' ~ ^ be ~ ·~ ~ o o Cq ~ a, Cq · ~ a' cq a' o ~ o sol ~ ¢ a' ~ .= Cq ~ a' VO Cq ~ ~ o O ~ a' .
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From page 350... ...
Annual estimates of the total fertility rate and of child mortality are available for 15 major states of India from the SRS from 1970 onward. Furthermore, cohort data are available from two national surveys conducted in 1970 and 1992-1993.
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From page 351... ...
MARI BHAT 7 4~ ~5 4J ,, . ~ I, - A 4 ~4 LL ~3 4~ o 2 ~351 ~ 1971 0 1991 + lgS1 + ~ ~+ ~ ooo a +0 o + o °0 ^0 + ++ + 0 + + a 0 +0 + + + 1 1 it 1 ' ''- ~ ~1 -- 1' 0 50 100 150 200250 300 Lagged Under-5 Mortality Rate FIGURE 10-3 Relationship between the total fertility rate and lagged under-5 mortality rate for major states of India, 1971, 1981, and 1991.
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From page 352... ...
352 _' o ,, o a' ~ ~ o ·s a' o Em ~ o ° be o 1 - C')
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From page 353... ...
However, the continuity of a rising trend in the mortality rate coefficient over the 1980s (though this is statistically insignificant) and the absence of a clear trend in the coefficient on female literacy, argue strongly in favor of a structural change in the mortalityfertility relationship.
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From page 354... ...
354 o Cq a' VO o I' a' a' o EM o be o o Cq ho Cq a' be a' o a' VO Cq Cq s° cq cot .= VO a, ·0 ~ Em o ~ oo o, Cq Do Cq ~ ~ Car o o ~ .
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From page 355... ...
First, with cohort data, there is no need to worry about lags in the mortality-fertility relationship because the cohort measures reflect the cumulative fertility response to child mortality experience by the end of the reproductive period. Second, a cohort analysis allows us to control explicitly for variation in desired family size, circumventing the need to use proxies such as female literacy, which may also partly capture some portion of unwanted fertility.
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From page 356... ...
However, this increase could be the result of excessive reliance on sterization as a method of fertility control, the low cost of unwanted fertility, and unanticipated declines in child mortality while pursuing an insurance strategy. From the data presented in Table 10-6, a quick estimate of the RH rate can be made by assuming that changes in child deaths and desired family size elicit identical fertility responses.
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From page 359... ...
Given prolonged breastfeeding in India, one can expect a biological replacement of about 30 percent of child deaths to occur virtually automatically (Preston, 1978~. If I assume that a child death would elicit a response rate of 0.3 over and above the response to changes in desired family size, the above data imply an RH rate of 0.97.
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From page 360... ...
360 o o a' a' o o o · C a' ~ C o ~ o a' ~ VO bC 1 ~ Cq ·0 Cq Cq s°- ~ o a' .= a' VO a' · E~ ~ a' o o o Cq ~ Cq ¢ ~ o o ~ ¢ E~ ~o ca ~ o == c ~ o ~ V ca 4= C)
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From page 361... ...
The implied difference in the effects of child death and desired family size is substantially larger than 0.3, indicating that additional forces must be inflating the size of the fertility response. Statistically, however, the difference between the two coefficients is significant only in the random-effects model, perhaps due to the fact that the results are based on only 20 observations.
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From page 362... ...
At the same time, it is not at all clear how much of the variation in desired family size the covariates used in the district regressions captured and how much unwanted fertility they
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From page 363... ...
bInformation was available only at the state level. CLagged by 10 years; used in logarithmic form in Specification 2.
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From page 364... ...
The data have been analyzed for cohorts at the end of their reproductive lives, as well as for all women of reproductive age. The cohort analysis employed data on children ever born, children dead, and desired family size, whereas the analysis of all married women examined data on contraceptive practice with child loss as one of the key determinants.
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From page 366... ...
When desired family size is directly controlled in the regression, as in the state-level analysis, a problem arises. As many as 20 percent of women gave nonnumeric responses to the question on desired family size.
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From page 367... ...
The estimated coefficient on this variable suggests that women who gave nonnumeric responses to the question on desired family size have an average desired family size of 4.6 in Karnataka and 4.9 in Uttar Pradesh. This was computed by dividing the coefficient on the dummy variable GOD by the coefficient on the desired family size variable.
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From page 368... ...
and interacting it with the desired family size variable. This dummy variable equals 1 for all women fortunate enough to have their desired sex composition of chil
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From page 369... ...
dren when they attain their desired family size and 0 otherwise. Only about 60 percent of the women in Karnataka and 50 percent of women in Uttar Pradesh had attained their desired sex composition when they reached their desired family size.
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From page 370... ...
Interestingly, my estimates suggest that the experience of own-child mortality and desired family size have fertility effects of roughly the same order of magnitude, even though there is an additional biological component to the former. The effect of the latter could be overstated by a rationalization in the reports of family size desires, but this is partly offset by the desire to have children of a particular sex.
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From page 371... ...
The data analyzed here pertain to 3,585 married women of Karnataka aged 13-49 in 1992-1993 with at least one living child. The National Family Health Survey, from which these data are derived, did not collect information on complete contraceptive history and cannot be subjected to an event-history analysis.
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From page 372... ...
The results of this analysis show that the effect of child loss experience is quite large and negative at parities below 5. The coefficient on male child death is strongly significant at parities 3 and 4 whereas that of female child loss is significant only at parity 3.
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From page 373... ...
. In addition, if a biological component of 0.3 is associated with prolonged breastfeeding, the implied total replacement rate would be 0.54, almost identical to the estimate derived from the cohort analysis using desired family size as a control (0.56~.
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From page 376... ...
The district-level child mortality variable is significant at most parities, but its effect is nearly three times larger at parity four than at any other parity (see Table 10-12~. Because the average desired family size in Karnataka is about three children, many have a fourth child primarily for insurance.
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From page 377... ...
In short, the analysis of contraceptive acceptance patterns shows that the prevalence rates for sterilization, a method used by a overwhelming majority of couples in India to control their fertility, is lower because of their experience of child loss and their concerns about the survival of their living children. The estimated reduction in sterilization prevalence because of child loss implies a volitional response of about 0.25 for a child death in Karnataka.
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From page 378... ...
However, at initial stages of the transition, the substitution Of replacement for hoarding occurs at a sluggish pace because of lags in individual perception of community-wide mortality declines, the low cost of unwanted fertility, and the lack of access to family planning services. Consequently, the relationship between fertility and child mortality is generally weak at this stage.
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From page 379... ...
P.N. MARI BHAT APPENDIX Appendix tables begin on following page.
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From page 380... ...
380 a' a' Cq Cq a' .~ o x o Cq ·_4 VO a' a' ~ a' · _4 ·0 o ~ ·~ ·0 ~ ~ o ~ o ~ a' VO ~ ^ a c., .= ·= ~4 o Cq ·Cq ¢ ¢ X C Cq a' bC a' ¢ ~ · ~ o X ~ + -- 1 + 1 +1 + + -- 1 o oo o o ~CM ~C .
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From page 382... ...
Heer, D.M., and D.O. Smith 1968 Mortality level, desired family size and population increase.
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From page 383... ...
Olsen 1983 Evaluation of the Olsen technique for estimating the fertility response to child mortality. Demography 20(3)
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