Discussion: Does Demographic Change Set the Pace of Development? (with Jane O’Sullivan, U. Queensland)

Original Essay: Does Demographic Change Set the Pace of Development? 

Comment:  Jane O’Sullivan, U. Queensland.

A good title but a disappointing treatment. In the context of the fertility transition, age structure and population growth rate are confounded. There is little evidence that age structure per se delivers these benefits – it is the slowing of population growth that affects “demand side”. Of course, age structure affects specifically which areas of demand are first affected, but that’s not what matters. The problem is that the “demographic dividend” discourse is used as a means to not have to talk about population growth, but in doing this, it undermines the motivation to get fertility down below replacement-level, which is the urgent need. Indeed, by fuelling the “aging crisis” myth, the DD message actively discourages efforts to complete the transition to low fertility. Also, the role of family planning programs is missing from the flow diagram. Education, income and child survival don’t have strong effects on fertility without explicit behaviour-change programs.    [Note: see Dr. O’Sullivan’s research on population impacts, demographic ageing, food security, and climate change issues]


Reply:  Richard Cincotta, Woodrow Wilson Center/Stimson Center

Thank you for your interesting comments, Dr. O’Sullivan. And, welcome to the growing ranks of the disappointed.

The curves featured in this essay were developed as part of the (U.S.) National Intelligence Council’s (NIC) long-range effort (the Global Trends series of publications) solely for the purpose of forecasting changes in political, social, and economic indicators from 2 to 20 years into the future.

For forecasting, the method has worked surprisingly well (you can read some of its forecasts in my other NSB posts). Analysts have used the method’s “eight rules of political demography” (also on NSB) to successfully forecast the rise of a liberal democracy in North Africa two years before the Arab Spring, to identify the remaining clusters of countries most at risk of intra-state conflicts, and to predict declines from liberal democracy among youthful countries.

Along the way, however, its findings have disappointed (or even angered) diplomats, advocates, and political scientists who have deeply-held views of how the world works.

One source of disappointment has to do with population growth. While states with a population under 5 million (particularly small island states) do, indeed, appear to develop politically and socioeconomically more quickly than expected, we have found no additional statistical evidence suggesting that larger population sizes or densities are—so far, at least—a “net impediment” to political and socio-economic development.

For example, population size and density may depress economic productivity by limiting per-capita freshwater supplies, exacerbating pollution, and forcing agriculture into marginally productive land. At the same time, however, population growth drives urbanization, which positively affects per-capita income and speeds other development transitions (including fertility decline).

My own experience with assessing population’s influence leads me to conclude that, in general, increasing human density disrupts and alters natural ecosystem processes (i.e., nature). Unfavorable age structures disrupt development processes (i.e., the state). States are, indeed, affected by ecosystem disruption, but our species has become very good at making and remaking its own highly productive ecosystems—most of which create additional long-term disruption (e.g., climate change, species loss, high nitrogen loading in soils, etc.–a point that you know well from your own research).

As for your critique of Fig. 3: I have indicated (in the diagram) that income and child survival’s effects on fertility are (as you suggest) weak or highly variable. However, I believe that most development analysts would disagree with your assessment of education’s impact on fertility—particularly the impact of women’s educational attainment, which in the past has been statistically strong. Nonetheless (consistent with your assertion), the effect of women’s educational attainment on fertility in tropical sub-Saharan African countries seems, so far, to be weaker than expected (when compared to the Asian and Latin American fertility transitions).

While you insist that getting fertility “down below replacement-level” is an urgent need, our analysis differs somewhat. To achieve a median age of 26 years—the beginning of the demographic window—fertility must decline below 2.8 children per woman. However, continued progress toward a median age of 30 years has generally led to additional fertility decline to near-replacement (close to TFR 2.1) or below-replacement levels.

On population aging: A myth? Perhaps you are referring to the mistaken beliefs/rhetoric of some political leaders of tropical African states who fear an aging population—seemingly unaware that the current UN Medium Fertility Variant scenario projects that such large proportions of elderly, for most tropical African states, will likely show up on the far side of 2100 (probably a century into the future). I believe that, to achieve a median age of 26 years, the leadership of those states must be prepared to dismantle the traditional and religious constraints on women’s lives (much like Habib Bourguiba did shortly following Tunisia’s independence), in addition to supporting quality family planning programs, girls’ education, and elevating women into positions of political power.

However, for the group of very low fertility European and East Asian countries that are rapidly advancing into the post-mature phase of the transition (median age 46+ years), the challenges of population aging are hardly mythical. Does population aging qualify as a crisis for economic and political liberalism? No one knows. However, the most credible research foresees substantial fiscal strains on retirement and healthcare systems (see Lee & Mason’s National Transfer Accounts review), and the admixture of population aging and immigration seems (to me, at least) to be yielding some unfavorable political byproducts.

Thanks again for your comments, Dr. O’Sullivan. // Richard Cincotta

Bangladesh & Pakistan: Demographic Twins Grow Apart

UN figures indicate that Bangladesh, a state once identified with natural catastrophes and rock-concert relief, is on the cusp of its demographic window (reflected in its age structure, shown in Figure 1, below)—a period of favorable age structures that researchers associate with an increased pace of development and a more stable political future. Bangladesh is already a solid member of the World Bank’s lower middle-income class. According to a set of statistical models that we have developed, by 2030 Bangladesh appears to have an even chance of reaching the Bank’s upper middle-income class (roughly US$4,000 to $12,000 per capita annually). For a country that Henry Kissinger famously dubbed “a basket case” at independence in 1971, that prospect is impressive.

Comparison of age structures, 1970 & 2015, following Bangladesh’s secession in 1971: East Pakistan Provincial Wing becomes Bangladesh; West Pakistan Provincial Wing becomes Pakistan.



This remarkable turnaround is not a big surprise to international health specialists. In 1975, the government in Dhaka began collaborating with the International Centre for Diarrheal Disease Research, Bangladesh (ICDDR/B) to initiate a program of community-based contraceptive distribution in Matlab subdistrict, a long-term health and demographic surveillance site.


Click here to read the rest of … “Bangladesh & Pakistan: Demographic Twins Grow Apart” on the New Security Beat, or download the .pdf here.

The 4 Dividends: PRB’s Pace Project

See the Population Reference Bureau’s excellent video explaining the “Four Dividends” that countries generally attain following fertility decline as they pass through the demographic window. These four dividends are: (1) child survival, (2) educational attainment, (3) per-capita income, and (4) political stability (measured by 10-year risk of intra-state conflict).

Here are links to obtain the IUSSP Conference paper (authored by Elizabeth Madsen and me) that describes the timing of these changes, in terms of the movement of countries through the age-structural transition. A background paper on the Age-structural Theory of State Behavior is published in the Oxford Research Encyclopedia of Politics.  Some of this information is published in a short essay on the “Eight Rules of Political Demography“, on the New Security Beat.



Sub-Saharan Africa: Looking Toward the Demographic Window

Over the past 25 years, economic and political demographers have focused on documenting the improvements in state capacity and political stability that have been realized in the wake of fertility declines in much of East Asia, Latin America, and most recently in the Maghreb of North Africa (Tunisia, Morocco, Algeria). Nonetheless, foreign affairs, defense and intelligence analysts still seem confused over when and where this demographic dividend should occur—and whether the youthful, low-income states of Sub-Saharan Africa are due to experience the dividend’s economically favorable age structures anytime soon. Because two very different development narratives vie for these analysts’ attention, their confusion is not that surprising.

     In this essay, I discuss the concept of “the demographic window” and compare economists’ perspectives on sub-Saharan Africa to that of political demographers.  I also identify 4 groups of countries in sub-Saharan Africa that have very different schedules for reaching the demographic window (and thus reaching the World Bank’s upper middle income category and other development milestones). For the entire essay, posted in the Woodrow Wilson Center’s New Security Beatsee this page.

Download this New Security Beat essay on Sub-Saharan Africa’s Demographic Window .

Article: Oxford Research Encyclopedia of Politics

The Age-structural Theory of State Behavior

Richard Cincotta

ABSTRACT: Over the past three decades, economic and political demographers, using various measures, have discerned that increased age-structural maturity makes significant statistical contributions to levels of per capita income, to educational attainment, to declines in the frequency of onsets of intrastate conflict, and to the likelihood of achieving and maintaining liberal democracy. Some of the stronger statistical relationships have been used in forecasts. For example, using the United Nations Population Division (UNPD) demographic projections, political demographers have relied on the strong statistical association between age structure and stable liberal democracy to forecast the rise of democracy in North Africa more than two years in advance (in 2008)—at a time when regional experts believed that forecast to be absurd.

Whereas critics remain skeptical of the murky causal connections of age-structural theory, its proponents counter that causality in the development of state capacity is complex and is less important than the theory’s positive qualities (namely, that it is forward-looking, its statistical findings are easily repeated, its forecasts have out-competed regional experts, and its predictive products can be readily adapted to the needs of intelligence foresight, defense planning, and foreign policy analysis). Perhaps most important, the age-structural theory of state behavior has yielded a surprising number of “novel facts”—new knowledge concerning the observed pace and timing of state political, social, and economic behaviors.

Full article is published in: 

Cincotta, R. (2017) “The Age-structural Theory of State Behavior.” In William Thompson (Ed.), Oxford Research Encyclopedia: Politics, Oxford Univ. Press. DOI: 10.1093/acrefore/9780190228637 .013.327;

The full article is downloadable here or request article from author (click here).

And it is available as a web article at the Oxford Research Encyclopedia site, at Oxford University Press.