News | Innovative Data Modeling Framework Supports Fertility and Education Decisions
Researchers at the International Institute for Applied Systems Analysis (IIASA) introduced an innovative method for reconstructing incomplete or unreliable fertility and education data in developing countries. The method gives policymakers an important tool for evaluating how women's education affects fertility rates, especially as education expands globally and fertility rates decline.
Data Reconstruction: Addressing Data Challenges in Developing Countries
Accurate, consistent fertility data are often difficult to obtain in developing countries, making it challenging to assess how women's education affects fertility. Fertility is closely linked to economic inequality, healthcare access, educational disparities, environmental and climate change, and political instability. Accurate data are therefore especially important for decision-makers, but gaps by age and education make decisions more complex.
To address this problem, Afua Durowaa-Boateng of the Vienna Institute of Demography worked with IIASA researchers Anne Goujon and Dilek Yildiz to develop a modeling framework that reconstructs existing data. It can help assess education's role in fertility decline and provide historical evidence for future population projections.
"Our reconstructed data help assess the role of education in fertility decline and fill gaps in existing time-series data. The model's estimates and historical evidence can also be used for future population projections," Durowaa-Boateng said.
Findings and Policy Applications
The findings confirmed that women with more education generally have lower fertility rates and tend to give birth at older ages. During the early stages of fertility decline, however, educated women may have higher fertility rates than women with no education. This was especially apparent in sub-Saharan Africa in the 1980s. As education levels rose, fertility differences by education first widened and then narrowed. The trend was particularly clear in Latin America, where fertility transitions began in the 1970s and the gap had narrowed substantially by 2020.
The study found that as more educated women have fewer children, women with less education in the same communities may follow. This spillover effect of education on fertility behavior may be valuable to policymakers and organizations in low-income countries.
"Although our findings are important for policymaking, the main direct users may be academics, who can use these consistent time-series data in their own models. Our research also creates opportunities to reconstruct education-related fertility data in other regions," Yildiz added.
Goujon said the findings could support policymakers and international organizations addressing population challenges in low-income countries. The team also plans to expand its data website with more research on African populations.
News | Innovative Data Modeling Framework Supports Fertility and Education Decisions
News | Innovative Data Modeling Framework Supports Fertility and Education Decisions
Researchers at the International Institute for Applied Systems Analysis (IIASA) introduced an innovative method for reconstructing incomplete or unreliable fertility and education data in developing countries. The method gives policymakers an important tool for evaluating how women's education affects fertility rates, especially as education expands globally and fertility rates decline.
Data Reconstruction: Addressing Data Challenges in Developing Countries
Accurate, consistent fertility data are often difficult to obtain in developing countries, making it challenging to assess how women's education affects fertility. Fertility is closely linked to economic inequality, healthcare access, educational disparities, environmental and climate change, and political instability. Accurate data are therefore especially important for decision-makers, but gaps by age and education make decisions more complex.
To address this problem, Afua Durowaa-Boateng of the Vienna Institute of Demography worked with IIASA researchers Anne Goujon and Dilek Yildiz to develop a modeling framework that reconstructs existing data. It can help assess education's role in fertility decline and provide historical evidence for future population projections.
"Our reconstructed data help assess the role of education in fertility decline and fill gaps in existing time-series data. The model's estimates and historical evidence can also be used for future population projections," Durowaa-Boateng said.
Findings and Policy Applications
The findings confirmed that women with more education generally have lower fertility rates and tend to give birth at older ages. During the early stages of fertility decline, however, educated women may have higher fertility rates than women with no education. This was especially apparent in sub-Saharan Africa in the 1980s. As education levels rose, fertility differences by education first widened and then narrowed. The trend was particularly clear in Latin America, where fertility transitions began in the 1970s and the gap had narrowed substantially by 2020.
The study found that as more educated women have fewer children, women with less education in the same communities may follow. This spillover effect of education on fertility behavior may be valuable to policymakers and organizations in low-income countries.
"Although our findings are important for policymaking, the main direct users may be academics, who can use these consistent time-series data in their own models. Our research also creates opportunities to reconstruct education-related fertility data in other regions," Yildiz added.
Goujon said the findings could support policymakers and international organizations addressing population challenges in low-income countries. The team also plans to expand its data website with more research on African populations.
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