Page 73 - IJPS-7-2

International Journal of
Population Studies Age-adjusted measures for fertility transition

schedules of the ASMFRs from the two surveys. The 3.4. Differences between CEB and ASMFR in
RDHS2005 clearly had higher ASMFRs for the peak multivariable analysis
childbearing age groups of 20 – 24, 25 – 29, as well as the 30 We executed the OB decomposition using education and
– 34 and 35 – 39 compared to the RDHS2000. These clear age group as the independent variables to explain the
differences were absent when comparing the two surveys’ change in the marital fertility levels as measured by CEB
age patterns of average CEB. There were no differences
between RDHS2000 and RDHS2005 in terms of CEB and ASMFR. This analysis determined how the difference
across all the age groups, which, further, strengthens the between CEB and ASMFR affects the nature of the
conditional contributions from a decomposition analysis
argument that the CEB measure is not robust to capture
changes in fertility rates. of change in the level of fertility. The analysis focused on
two inter-survey periods from Zimbabwe, the 1988 – 1994
Zimbabwe displayed the most defined contradictions which was a period of rapid marital fertility transition
between ASMFRs and average CEB. The ASMFRs of the and the 2010 – 2015 which was characterized by stalled
first three ZDHS surveys were consistent with the rapid marital fertility transition. We used Zimbabwe as a case
decrease in TMFRs from 1988 to 1999, something which in this study because it had the most defined differences
CEB also suggested especially for the age groups 30 – 34, in the trends of its unadjusted and adjusted measures of
35 – 39, and 40 – 44. However, after 1999, TMFRs for fertility. The aggregate results from decomposition analysis
Zimbabwe stalled and started to increase. These increases were that in the 1988 – 1994 period, the mean ASMFR
were more defined during the 2005 – 2010 and 2010 – 2015 decreased by 16%-points, while the mean CEB declined by
inter-survey periods, where TMFRs notably increased. The 8% points, showing an underestimation of the decline by
ASMFRs reflect these stalls as shown by the schedules of the the latter (Figure 5). In the 2010 – 2015 period, ASMFR
ZDHS2020 and ZDHS2015 which had higher rates than showed a rebound of marital fertility rates equivalent to 6%
the preceding the ZDHS2005 and ZDHS2010, respectively. points, while the mean CEB was found to increase by 3%
While the ASMFRs proved effective at capturing marital points. As was the case in the 1988 – 1994 period, the CEB
fertility stalls in Zimbabwe, the cumulative CEB measure underestimated the rebound of marital fertility by 50%
was unable to do so. For all the surveys post 1988, the compared to the mean ASMFR.
CEB 45-49 was higher than that of the preceding survey.
This was also the case for most of the age groups from In interpreting the results of the decomposition, where
25 – 29 to 40 – 44. The results for Zimbabwe thus further the difference in the mean estimate of CEB/ASMFR
confirm that CEB is not an effective measure for capturing between the ZDHS1988 and ZDHS1994 is negative and
trends in fertility rates, especially where these trends are the changes in characteristics and coefficients supported
characterized by episodes of stalls and rebounds. the decrease (denoted by negative sign), the percentage

Figure 5. Differences in fertility change determinants based on type of fertility measure
*Constants for CEB are -1.413 and -0.698 for 1988-1994 and 2010-2015 respectively. For ASMFR, the constants are -0.006 and -0.005 for 1988-1994 and
2010-2015 respectively.

Volume 7 Issue 2 (2021) 67 https://doi.org/10.36922/ijps.v7i2.354