Small Area Estimation of Age-Specific and Total Fertility Rates in Bangladesh
Bangladesh has experienced a rapid national decline in fertility in recent decades, however, fertility rates vary considerably at the sub-national level (i.e., division). These variations are expected to be more pronounced at lower levels of geography (e.g., district level). However, routinely condu...
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description | Bangladesh has experienced a rapid national decline in fertility in recent decades, however, fertility rates vary considerably at the sub-national level (i.e., division). These variations are expected to be more pronounced at lower levels of geography (e.g., district level). However, routinely conducted demographic health surveys are designed for national estimates and do not have adequate samples to produce reliable estimate of fertility rates at lower levels of administrative units, particular when considering district level age-specific fertility rates. Data extracted from the Bangladesh Demographic Health Survey 2014 are used to derive direct estimates of age-specific fertility rates and associated smoothed standard errors. These are used as inputs for developing a small area model, which is expressed in a hierarchical Bayesian framework and fitted by Markov Chain Monte Carlo simulation. The model accounts for variation at different levels—women age-group, division, and district. The modeling results show large reductions in the estimated standards errors and provide consistent estimates of fertility at the detailed district age-specific level. There are significant differences in the fertility levels within and between districts and at the division level. Fertility rates are observed to be higher for Sylhet division and for women aged 20–24 years. We use geo-spatial maps of the fertility rates to visualize the variations over districts, and identify hot and cold-spots to have better targeted local level planning and policy decision making for further reductions in fertility rates in Bangladesh. |
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These variations are expected to be more pronounced at lower levels of geography (e.g., district level). However, routinely conducted demographic health surveys are designed for national estimates and do not have adequate samples to produce reliable estimate of fertility rates at lower levels of administrative units, particular when considering district level age-specific fertility rates. Data extracted from the Bangladesh Demographic Health Survey 2014 are used to derive direct estimates of age-specific fertility rates and associated smoothed standard errors. These are used as inputs for developing a small area model, which is expressed in a hierarchical Bayesian framework and fitted by Markov Chain Monte Carlo simulation. The model accounts for variation at different levels—women age-group, division, and district. The modeling results show large reductions in the estimated standards errors and provide consistent estimates of fertility at the detailed district age-specific level. There are significant differences in the fertility levels within and between districts and at the division level. Fertility rates are observed to be higher for Sylhet division and for women aged 20–24 years. We use geo-spatial maps of the fertility rates to visualize the variations over districts, and identify hot and cold-spots to have better targeted local level planning and policy decision making for further reductions in fertility rates in Bangladesh.</description><identifier>ISSN: 2364-2289</identifier><identifier>EISSN: 2164-7070</identifier><identifier>DOI: 10.1007/s40980-022-00113-1</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Age ; Age determination ; Bayesian analysis ; Decision making ; Demographics ; Demography ; Errors ; Estimates ; Fertility ; Geographical Information Systems/Cartography ; Geography ; Humanities ; Law ; Markov chains ; Monte Carlo simulation ; Policy and planning ; Regional/Spatial Science ; Social Sciences ; Statistics for Social Sciences ; Surveys ; Variation</subject><ispartof>Spatial demography, 2023-04, Vol.11 (1), Article 2</ispartof><rights>The Author(s) 2023</rights><rights>The Author(s) 2023. 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These variations are expected to be more pronounced at lower levels of geography (e.g., district level). However, routinely conducted demographic health surveys are designed for national estimates and do not have adequate samples to produce reliable estimate of fertility rates at lower levels of administrative units, particular when considering district level age-specific fertility rates. Data extracted from the Bangladesh Demographic Health Survey 2014 are used to derive direct estimates of age-specific fertility rates and associated smoothed standard errors. These are used as inputs for developing a small area model, which is expressed in a hierarchical Bayesian framework and fitted by Markov Chain Monte Carlo simulation. The model accounts for variation at different levels—women age-group, division, and district. The modeling results show large reductions in the estimated standards errors and provide consistent estimates of fertility at the detailed district age-specific level. There are significant differences in the fertility levels within and between districts and at the division level. Fertility rates are observed to be higher for Sylhet division and for women aged 20–24 years. 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These variations are expected to be more pronounced at lower levels of geography (e.g., district level). However, routinely conducted demographic health surveys are designed for national estimates and do not have adequate samples to produce reliable estimate of fertility rates at lower levels of administrative units, particular when considering district level age-specific fertility rates. Data extracted from the Bangladesh Demographic Health Survey 2014 are used to derive direct estimates of age-specific fertility rates and associated smoothed standard errors. These are used as inputs for developing a small area model, which is expressed in a hierarchical Bayesian framework and fitted by Markov Chain Monte Carlo simulation. The model accounts for variation at different levels—women age-group, division, and district. The modeling results show large reductions in the estimated standards errors and provide consistent estimates of fertility at the detailed district age-specific level. 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subjects | Age Age determination Bayesian analysis Decision making Demographics Demography Errors Estimates Fertility Geographical Information Systems/Cartography Geography Humanities Law Markov chains Monte Carlo simulation Policy and planning Regional/Spatial Science Social Sciences Statistics for Social Sciences Surveys Variation |
title | Small Area Estimation of Age-Specific and Total Fertility Rates in Bangladesh |
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