scholarly journals Demographic and Human Capital Heterogeneity in Selected Provinces of Turkey: A Scenario Analysis Using Multi-dimensional Population Projection Model

2015 ◽  
Vol 8 (3) ◽  
pp. 215-244
Author(s):  
Mustafa Murat Yüceşahin ◽  
Samir KC
2014 ◽  
Vol 41 (1-2) ◽  
pp. 144 ◽  
Author(s):  
Martin Spielauer

The relation between education and labour force participation of Aboriginal peoples: A simulation analysis using the Demosim population projection model


1991 ◽  
Vol 23 (12) ◽  
pp. 1797-1810 ◽  
Author(s):  
J Shen

The multiregional demography approach is used in an analysis of the urban—rural population dynamics of China. Multiregional population-accounts and methods of estimation of demographic rates are developed on the basis of the multiregional population-accounts concept. An accounts-based urban—rural population projection model is established and used to project the population of China from 1988 to 2087.


2008 ◽  
Vol 72 (7) ◽  
pp. 1605 ◽  
Author(s):  
William R. Clark ◽  
Todd R. Bogenschutz ◽  
Dale H. Tessin

2018 ◽  
Vol 115 (33) ◽  
pp. 8328-8333 ◽  
Author(s):  
Samir KC ◽  
Marcus Wurzer ◽  
Markus Speringer ◽  
Wolfgang Lutz

Within the next decade India is expected to surpass China as the world’s most populous country due to still higher fertility and a younger population. Around 2025 each country will be home to around 1.5 billion people. India is demographically very heterogeneous with some rural illiterate populations still having more than four children on average while educated urban women have fewer than 1.5 children and with great differences between states. We show that the population outlook greatly depends on the degree to which this heterogeneity is explicitly incorporated into the population projection model used. The conventional projection model, considering only the age and sex structures of the population at the national level, results in a lower projected population than the same model applied at the level of states because over time the high-fertility states gain more weight, thus applying the higher rates to more people. The opposite outcome results from an explicit consideration of education differentials because over time the proportion of more educated women with lower fertility increases, thus leading to lower predicted growth than in the conventional model. To comprehensively address this issue, we develop a five-dimensional model of India’s population by state, rural/urban place of residence, age, sex, and level of education and show the impacts of different degrees of aggregation. We also provide human capital scenarios for all Indian states that suggest that India will rapidly catch up with other more developed countries in Asia if the recent pace of education expansion is maintained.


2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Leiwen Jiang ◽  
Karen Hardee

Is education the best contraceptive? Using the multistate human capital projection model, our analysis shows that the projected changes in India population vary depending on investments in education and helping women reduce unwanted fertility rates, that investments in both education and helping women in each education category—but particularly less educated women—meet their wanted fertility will have the largest impacts on India’s population projections, and that the impact from investment in reducing unwanted fertility will be much more immediate and significant than only investments in education. Our analysis also reveals that an increasing education transition rate in India will not only help to achieve a population age structure that is favorable for economic growth, but also result in a larger share of skilled labor force that help to achieve higher economic growth rate. More importantly, investment in girls’ education and achieving gender equality in education will be the most effective measure to increase India’s population education level and improve its overall values of human capital.


1974 ◽  
Vol 6 (5) ◽  
pp. 509-546 ◽  
Author(s):  
J R King

A simple population-projection model is presented which is used to predict the future numbers of Commonwealth immigrants in Leeds CB. The assumptions concerning survival and immigration used in the model are stated fully. The rates of fertility of immigrant groups in Leeds are investigated along with the trends in these rates in the historical period. These trends are used to calculate future fertility rates for the immigrant groups in Leeds CB. The results of the projection model are presented for each census date up to 1986 and conclusions are drawn from this information.


2018 ◽  
Author(s):  
Jonathan P. Rose ◽  
Julia S. M. Ersan ◽  
Glenn D. Wylie ◽  
Michael L. Casazza ◽  
Brian J. Halstead

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