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The effect of natural disaster on fertility, birth spacing, and child sex ratio: evidence from a major earthquake in India

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Abstract

Natural disasters can lead to significant changes in health, economic, and demographic outcomes. However, the demographic effects of earthquakes have been studied only to a limited degree. This paper examines the effect of the 2001 Gujarat earthquake on reproductive outcomes. This earthquake killed more than 20,000 people; injured 167,000; and caused massive losses to property and civic assets. Using data from two large-scale District-Level Household Surveys (2002–2004 and 2007–2008), we employ difference-in-difference and fixed-effect regression models to compare the outcomes across earthquake-affected districts and their neighboring districts during 5 years before and after the earthquake. We find that the earthquake led to significant rises in childbirth rates. It also reduced birth spacing among uneducated, tribal, and Muslim women, and the incidence of male births among rural women. We find considerable variation in the demographic effects of the earthquake across location, household socioeconomic status, and parental age and education.

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Notes

  1. The moment magnitude scale (Mw) is the current standard scale for measuring earthquake strength, replacing the better-known Richter scale (USGS 2002).

  2. The estimated loss was 144 billion Indian Rupees (INR). We assume US$1 = INR 50.

  3. DLHS-3 did not cover the state of Nagaland.

  4. NFHS-3 collected migration data separately for adult men and women. A survey question asked the number of years an individual had lived in the current residence. Using this information with the year of interview, we are able to accurately determine the year of in-migration from another place. Migration rates of women are higher as compared with men likely due to the practice of patrilocal marriages.

  5. In order to preserve sample size, we impose no restriction on the year of birth. It is possible that even in the post-earthquake period (in DLHS-2 data), the older of the two most recent born children was born before the earthquake. Our objective is to examine if the space between the two births was affected by the earthquake, irrespective of year of birth of the older child.

  6. The probit regression of annual incidence of childbirth is of the following form:

    $$ \mathrm{Birt}{\mathrm{h}}_{\mathrm{idt}}=f\left({\uptheta}_0+{\uptheta}_1\mathrm{Quak}{\mathrm{e}}_d+{\uptheta}_2\mathrm{Yea}{\mathrm{r}}_t+{\uptheta}_3\mathrm{Quak}{\mathrm{e}}_d\times \mathrm{Yea}{\mathrm{r}}_t+{\uptheta}_5{X}_{\mathrm{idt}}+{\upmu}_{\mathrm{idt}}\right) $$

    where Yeart indicates dummy variables for the year. The vector X includes location, household size, indicators of caste and religion, age and sex of the household head, age and the number of previous births of the woman, schooling levels of the woman and her husband, household wealth index quintiles, and time between the interview and the beginning of the reporting period.

  7. The linear probit regression of whether a newborn child is male is of the following form:

    $$ {\mathrm{Boy}}_{\mathrm{jdt}}=f\left({\uppi}_0+{\uppi}_1\mathrm{Quak}{\mathrm{e}}_d+{\uppi}_2\mathrm{Yea}{\mathrm{r}}_t+{\uppi}_3\mathrm{Orde}{\mathrm{r}}_{\mathrm{jdt}}+{\uppi}_4\mathrm{Quak}{e}_d\times \mathrm{Yea}{\mathrm{r}}_t+{\uppi}_5\mathrm{Quak}{e}_d\times \mathrm{Orde}{\mathrm{r}}_{\mathrm{jdt}}+{\uppi}_6{X}_{\mathrm{jdt}}+{\nu}_{\mathrm{jdt}}\right) $$

    where Year t indicates dummy variables for the year. The vector X includes location, household size, indicators of caste and religion, age and sex of the household head, age and number of previous births of the woman, schooling levels of the woman and her husband, household wealth index quintiles, and time between the interview and the beginning of the reporting period.

  8. In 2002, there were inter-communal riots in some parts of Gujarat. However, we do not find significant differences in the effects of the earthquake among Hindu and Muslim women. Therefore, it is unlikely that riots biased our estimates.

  9. This analysis can only be done using the 2002–2004 birth data in DLHS-2. Births before 2004 were not captured in DLHS-3. We use a regression model that includes the covariate X from Eq. (1) and an indicator of child death in 2001. The coefficient of the child death indicator was not statistically significant.

  10. DLHS collected data on age at death for all children who had died. Information on vaccination was also collected for the two most recently born children of each mother. For DLHS-3, these data are available only for children born since January 1, 2004. For neonatal mortality, we consider death within the first month of life; infant mortality is defined as death within the first year of life. We considered a child to be immunized if all of the following vaccines were given: polio, measles, diphtheria-pertussis-tetanus (DPT), and Bacillus Calmette–Guérin (BCG).

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Acknowledgments

We thank the two anonymous reviewers for their very helpful comments.

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Correspondence to Arindam Nandi.

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This study uses publicly available household survey data. No separate ethics clearance was necessary

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Responsible editor: Junsen Zhang

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Nandi, A., Mazumdar, S. & Behrman, J.R. The effect of natural disaster on fertility, birth spacing, and child sex ratio: evidence from a major earthquake in India. J Popul Econ 31, 267–293 (2018). https://doi.org/10.1007/s00148-017-0659-7

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