The Demographic Dividend: A Potential Surplus Generated by a Demographic Transition

Turbat, Vincent

doi:10.1007/978-3-319-46889-1_12

Vincent Turbat³

1209 Accesses
10 Citations

Abstract

The Demographic Dividend (DD) is currently one of the most scrutinized issues in the field of development studies. The key question is whether sub-Saharan Africa is going to experience a DD in the near future. Some forecast an imminent DD and focus on what should be done by the sub-Saharan African countries to reap its maximum benefits. Others are less optimistic, and focus on what should be done to ensure that a DD could effectively happen. However, in both cases, most authors do not take time to explain what the DD is. And when they do, they define the DD by its formative process, but fail to explain what the DD is made of. In this chapter, we first attempt to provide a detailed and exhaustive definition of the DD, knowing that this “phenomenon” is economic by nature but generated by a demographic process, i.e., a demographic transition. In the second part, we discuss the probability that a DD will occur in sub-Saharan Africa in the near future. Our findings show that the window of opportunity is not ready to open up in two of the three sub-Saharan regions of this study. Unless these regions implement several drastic changes in the near future, the sub-Saharan African DD will never have the size, and therefore the impact, of its East Asian equivalent.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Chapter: USD 29.95; Price excludes VAT (USA)

eBook: USD 99.00; Price excludes VAT (USA)

Softcover Book: USD 129.99; Price excludes VAT (USA)

Hardcover Book: USD 179.99; Price excludes VAT (USA)

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

1.
The dependents should include the youth that are under-age (to legally work), the pensioners, but also the unemployed. Some authors do not take into account the unemployed population. This, in our opinion, is incorrect. In fact, whether indirectly, through taxes and a social security system, or directly (within the family or the ethnic group), the unemployed portion of the population is supported, as are the dependents, by the working population.
2.
Centre de recherches en économie et finance appliquées de Thiès, Senegal.
3.
See The System of National Accounts (SNA) of the United Nations: unstats.un.org/unsd/nationalaccount/sna.asp, accessed on June 9, 2016.
4.
See among others: (Moreland et al. 2014; Ashraf et al. 2013: 97–130; Drummond et al. 2014).
5.
Lee, M. “National Transfer Accounts Project”; see: http://www.ntaccounts.org, accessed on June 9, 2016.
6.
Calculated with U19 and Over 65.
7.
See Piero Sraffa, Production of Commodities by Means of Commodities: Prelude to a Critique of Economic Theory, Cambridge: Cambridge University Press, 1960.
8.
Both Western and Central Africa regions have few countries; therefore, the two regions were combined in this analysis.
9.
Calculated by Ms. Samantha Roecker, Georgetown University Research Assistant, based on World Bank and UN data.
10.
CREFAT : Country Profiles for Burkina Faso , Chad, Côte d’Ivoire , Mali, Mauritania and Niger, 2016.
11.
Population Reference Bureau data.
12.
Author’s calculations from World Bank data.
13.
See World Bank, Doing Business 2016: Measuring Regulatory Quality and Efficiency. Washington, DC: The World Bank Group, 2015.

References

Ashraf, Q. H., Weil, D. N., & Wilde, J. (2013). The effect of fertility reduction on economic growth. Population and Development Review, 39(1), 97–130.
Article Google Scholar
Basu, A. M., & Basu, K. (2014). The prospects for an imminent demographic dividend in Africa: The case for cautious optimism. United Nations University (UNU-WIDER): Helsinki.
Book Google Scholar
Bloom, D., Canning, D., & Sevilla, J. (2003). The demographic dividend: A new perspective on the economic consequences of population change. Santa Monica: Rand Corporation.
Google Scholar
Canning, D., Raja, S., & Yazbeck, A. S. (2014). People powered growth: The demographic dividend and the future African lions. Version 3. Washington, DC: The World Bank Group.
Google Scholar
Collier, P. (2007). The bottom billion: Why the poorest countries are falling and what can be done about it. Oxford: Oxford University Press.
Google Scholar
Drummond, P., Thakoor, V., & Yu, S. (2014). Africa rising: Harnessing the demographic dividend, IMF Working Paper, WP/14/143. Washington, DC: International Monetary Fund.
Google Scholar
Lee, R., & Mason, A. (2006). What is the demographic dividend? Finance & Development, 43(3), 16–17.
Google Scholar
Lee, R., & Mason, A. (2015, April 30–May 2). Demographic dividend, human capital, and saving: Take it now or enjoy it later? Paper prepared for the Annual Conference of the Population Association of America, San Diego.
Google Scholar
May, J. F. (2012). World population policies: Their origin, evolution, and impact. Dordrecht: Springer.
Book Google Scholar
Moreland, S., Leahy Madsen, E., Kuang, B., Hamilton, M., Jurczynska, K., & Brodish, P. (2014). Modeling the demographic dividend: Technical guide to the DemDiv model. Washington, DC: Futures Group, Health Policy Project.
Google Scholar
Rostow, W. W. (1960). The stages of economic growth: A non-communist Manifesto. Cambridge: Cambridge University Press.
Google Scholar
Sanderson, W. C., & Scherbov, S. (2015). Are we overly dependent on conventional dependency ratios? Population and Development Review, 41(4), 687–708.
Google Scholar

Download references

Author information

Authors and Affiliations

Georgetown University, Washington, DC, USA
Vincent Turbat

Authors

Vincent Turbat
View author publications
You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Vincent Turbat .

Editor information

Editors and Affiliations

World Demographic & Ageing Forum (WDA Forum), St. Gallen, Switzerland
Hans Groth
Population Reference Bureau (PRB), Washington, DC, USA
John F. May

Appendices

Annex 1

Dependency ratio (0–14 + 65 and over/15–64) in East Asia

	1960 (%)	1970 (%)	1980 (%)	1990 (%)	2000 (%)	2005 (%)	2010 (%)
Cambodia	93.41	92.78	77.53	90.19	80.57	67.93	58.40
China	77.48	79.28	68.00	54.03	48.07	39.24	36.04
Indonesia	74.78	87.05	79.48	67.28	54.62	53.54	53.47
Japan	55.97	45.25	48.38	43.40	46.64	50.72	56.85
Laos	80.96	82.65	91.91	91.34	89.05	78.96	68.09
Myanmar	78.16	85.42	81.70	72.05	54.96	49.29	45.27
Philippines	100.40	95.90	86.30	78.82	71.65	66.89	63.93
Singapore	82.77	72.83	46.57	37.09	40.43	37.70	35.80
South Korea	80.66	83.31	60.72	44.11	39.46	39.63	37.59
Thailand	86.05	90.87	75.82	53.18	44.40	42.95	39.28
Vietnam	81.66	97.09	86.01	75.80	61.28	50.80	42.92
Hong-Kong	77.70	69.43	45.52	43.24	39.40	35.77	33.40

Source: Author’s calculations from World Bank and UN data

Annex 2

U15 + 65 Plus/15–64 dependency ratios in sub-Saharan African countries

	1960 (%)	1970 (%)	1980 (%)	1990 (%)	2000 (%)	2005 (%)	2010 (%)
Benin	77.13	88.22	95.48	97.36	93.57	89.86	86.21
Cameroon	77.34	84.70	93.63	99.24	94.81	90.94	87.47
Chad	81.01	86.54	94.44	102.86	107.53	107.93	105.52
Ghana	87.70	92.67	94.24	87.20	80.01	77.23	73.92
Guinea	72.57	79.11	81.54	89.70	90.34	88.21	85.22
Côte d’Ivoire	78.76	87.21	92.23	89.52	81.80	82.72	81.56
Mali	72.91	78.77	88.05	101.31	98.26	97.47	98.81
Niger	93.79	97.72	98.23	100.57	101.87	106.32	110.11
Nigeria	79.98	83.14	87.80	91.37	86.24	86.20	87.80
Senegal	85.31	88.89	97.52	100.35	93.41	89.62	87.72
Western Africa Region Average	80.65	86.70	92.32	95.95	92.78	91.65	90.43
CAR	74.07	80.91	86.55	89.90	86.14	84.58	80.31
DR Congo	86.21	87.67	90.46	93.92	97.15	96.25	93.41
Eritrea	90.64	88.36	91.89	92.87	95.48	83.38	82.25
Ethiopia	85.53	87.56	93.35	97.81	98.65	97.30	91.33
Kenya	100.47	110.55	112.76	106.94	88.68	83.45	82.42
Rwanda	102.98	102.32	101.45	108.29	98.11	87.81	88.60
Somalia	83.68	86.82	88.69	95.54	100.43	102.51	102.10
Sudan	92.73	96.49	99.64	93.81	87.65	86.02	82.47
Tanzania	92.99	95.03	96.68	94.97	91.07	90.93	92.14
Uganda	94.22	97.86	100.18	102.56	108.07	107.68	105.36
Central & Eastern Africa Region Average	90.35	93.36	96.16	97.66	95.14	91.99	90.04
Angola	86.62	95.00	96.75	100.25	100.42	100.92	100.91
Botswana	98.48	104.42	96.26	90.37	70.22	63.84	60.69
Lesotho	89.96	93.08	93.78	93.00	84.31	79.50	72.15
Madagascar	85.01	95.69	98.84	92.95	94.07	91.34	86.06
Malawi	94.16	94.54	98.69	94.04	95.58	96.71	96.94
Mozambique	81.94	86.47	88.13	99.19	88.56	92.19	94.47
Namibia	82.98	87.74	100.20	88.80	77.88	75.80	69.84
South Africa	81.19	83.52	80.67	72.80	57.25	54.31	53.70
Zambia	90.54	96.21	100.58	94.91	94.06	97.76	98.27
Zimbabwe	94.61	105.40	107.90	96.36	83.61	82.35	82.54
Southern Africa Region Average	88.55	94.21	96.18	92.27	84.60	83.47	81.56

Source: Author’s calculations from UN data

Rights and permissions

Reprints and permissions

Copyright information

About this chapter

Cite this chapter

Turbat, V. (2017). The Demographic Dividend: A Potential Surplus Generated by a Demographic Transition. In: Groth, H., May, J. (eds) Africa's Population: In Search of a Demographic Dividend. Springer, Cham. https://doi.org/10.1007/978-3-319-46889-1_12

Download citation

DOI: https://doi.org/10.1007/978-3-319-46889-1_12
Published: 24 May 2017
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-46887-7
Online ISBN: 978-3-319-46889-1
eBook Packages: Social SciencesSocial Sciences (R0)

Publish with us

Policies and ethics