WPS5719


 Policy Research Working Paper                    5719




Population, Poverty, and Sustainable Development
                       A Review of the Evidence

                              Monica Das Gupta
                               John Bongaarts
                                John Cleland




 The World Bank
 Development Research Group
 Human Development and Public Services Team
 June 2011
Policy Research Working Paper 5719


  Abstract
  There is a very large but scattered literature debating                           better health and greater labor-force participation for
  the economic implications of high fertility. This paper                           women. They also indicate that rapid population growth
  reviews the literature on three themes: (a) Does high                             can constrain economic growth, especially in low-income
  fertility affect low-income countries’ prospects for                              countries with poor policy environments.
  economic growth and poverty reduction? (b) Does                                      Population growth also exacerbates pressure on
  population growth exacerbate pressure on natural                                  environmental common property resources. Studies
  resources? and (c) Are family planning programs effective                         highlight the deep challenges to aligning divergent
  at lowering fertility, and should they be publicly funded?                        interests for managing these resources. However, part
     The literature shows broad consensus that while policy                         of the pressure on these resources can be mitigated by
  and institutional settings are key in shaping the prospects                       reducing the rate of population growth.
  of economic growth and poverty reduction, the rate                                   Although family planning programs are only one policy
  of population growth also matters. Recent studies find                            lever to help reduce fertility, studies find them effective.
  that low dependency ratios (as fertility declines) create                         Such programs might help especially in the Sub-Saharan
  an opportunity for increasing productivity, savings and                           African region, where high fertility and institutional
  investment in future growth. They find that lower fertility                       constraints on economic growth combine to slow rises in
  is associated with better child health and schooling, and                         living standards.



  This paper is a product of the Human Development and Public Services Team, Development Research Group. It is part
  of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy
  discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org.
  The author may be contacted at mdasgupta@worldbank.org, or mdasgupta@gmail.com.




         The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development
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         names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those
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         its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.


                                                       Produced by the Research Support Team
       Population, Poverty, and Sustainable Development:
                    a review of the evidence1

                        Monica Das Gupta2, John Bongaarts3, and John Cleland4




JEL codes: Demography, Poverty, Economic Growth, Environment & Development, Public Policy




1
    Acknowledgements: We thank the Hewlett Foundation for grant support through Trust Fund TF070424 given to
    the World Bank. We are also very grateful for inputs from Shareen Joshi, and for valuable feedback from Martha
    Ainsworth, Jere Behrman, Ed Bos, Partha Dasgupta, Shanta Devarajan, Andrew Foster, Manny Jimenez,
    Elizabeth King, David Lam, Peter Miovic, Vijayendra Rao, T. Paul Schultz and Adam Wagstaff, as well as
    feedback received from participants in the Population and Poverty Conference held by the Hewlett Foundation,
    Marseille January 2011, the Population Association of America annual meeting April 2011, and a seminar at the
    World Bank April 2011.
    These are the authors‘ personal views and should not be attributed to the World Bank or any affiliated
    organization or member country.
2
    Development Research Group, The World Bank, Washington DC, USA. Email: mdasgupta@worldbank.org,
    mdasgupta@gmail.com (Corresponding author)
3
    The Population Council, New York, USA. Email: jbongaarts@popcouncil.org
4
    London School of Hygiene & Tropical Medicine, London, UK. Email: John.Cleland@lshtm.ac.uk
1 Introduction
In recent decades, there has been little policy attention to the potential benefits of reducing high fertility in
low-income countries. These have not been seen as compelling, despite many careful studies
documenting them. This is partly because the studies are scattered across different subjects, such as
family health, economic growth, and environmental change. It is also partly because an earlier literature
argued that lowering fertility was largely irrelevant (or even counter-productive) to developing countries‘
prospects for economic growth and poverty reduction.

This paper seeks to bring together the evidence on these issues, by reviewing the literature on three
themes: (a) Does high fertility affect low-income countries‘ prospects of economic growth and poverty
reduction? (b) Does population growth exacerbate pressure on natural resources? and (c) Are family
planning programs effective at lowering fertility, and should they be publicly funded?

Section 2 reviews the literature on the relationship between population, economic growth, and poverty
reduction. Opinions have swung back and forth on these relationships. Yet there has been a broad
consensus that while policy and institutional settings are key in shaping the prospects of economic
growth, population dynamics also play a role. At the household level, lower fertility has also been found
associated with better health and schooling outcomes, and lower poverty.

Section 3 reviews the literature on whether population growth exacerbates pressures on natural resources.
Some have argued that human innovation can overcome any resource constraint, and studies confirm this
for some types of resources, which are more fully priced. Others find that there are serious challenges to
sustainably managing the use of resources that are underpriced or free, such as global common property
resources, whose depreciation will affect the sustainability of production possibilities. Pressures on these
resources are exacerbated by increased consumption per capita and by population growth.

Section 4 turns to the implications of continuing high fertility for Sub-Saharan Africa. This region has
the highest population growth rates in the world today as mortality decline has far outpaced fertility
decline. It also experiences institutional and other constraints to economic growth that make it more
difficult to accommodate larger populations. We review some of the pressures building up in this region,
and suggest that accelerating the demographic transition may help mitigate them.

What then are the best policy levers to encourage lower fertility? Many factors are associated with
smaller families. Educating populations is widely perceived to create many positive externalities
associated with lower fertility, such as increased wages (Duflo 2001, Schultz 2002), improved child
health and schooling, increased female labor force participation, and lower fertility (Schultz 2002)
especially by raising the age at first birth.1 However, these benefits are well-recognized, and much effort
has been made to enhance education quality, reduce barriers to access, and incentivize parents to send
their children to school with subsidies, school meals, and conditional transfer programs. Improved child
survival can also help reduce fertility, but much programmatic effort is also underway on this.

By contrast, there is little consensus on the potential gains from helping lower fertility through family
planning programs, and even the effectiveness of these programs has been challenged.2 Section 5 reviews
the evidence on this, which indicates that well-executed family planning programs are effective at
lowering fertility. Section 6 concludes.




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2 Does High Fertility Affect Low-income Countries’ Prospects for
  Economic Growth and Poverty Reduction? The Debates

Since the 1960s, economists have taken very different positions on the implications of population
dynamics for economic growth. Many of these differences, as discussed below, have been driven by
different analytical approaches. For example, some studies have focused on the projected trajectory of a
single country while others have done cross-country regressions where it is difficult to control for
differences in the policy and governance settings. And over the decades analytical techniques have
evolved, yielding different results.

At bottom, there is little fundamental disagreement on the issue. There is broad consensus that policy
settings that support growth are the key drivers of economic growth, while population size and structure
play an important secondary role in facilitating or hindering economic growth.

2.1 Malthus’ original idea

Malthus argued that population and resources maintain a homeostatic balance: if living conditions permit,
the population will grow until it is restrained either by the ―preventive check‖ of controlling reproduction
or by resource shortages resulting in ―positive checks‖ (famine, disease, war). This was based on the
assumption that the supply of key factors of production such as land was largely fixed.

While this may sound like an extreme position today, it was not at the time Malthus wrote. Many studies
by economic historians and historical demographers show that GDP growth and real wages were indeed
stagnant or grew very slowly over centuries and even millennia. They also show that fertility control was
exerted through methods such as postponing marriage, never-marrying, infanticide, and abstinence.3
Galor and Weil (2000: 807) summarize the findings of several studies covering a wide geographical and
historical range:
    ―…Angus Maddison (1982) estimates that the growth rate of GDP per capita in Europe between 500 and
    1500 was zero. Furthermore, Ronald D. Lee (1980) reports that the real wage in England was roughly the
    same in 1800 as it had been in 1300. According to Kang Chao's (1986) analysis, real wages in China were
    lower at the end of the eighteenth century than they had been at the beginning of the first century…..
    Edward A. Wrigley and Roger S. Schofield (1981) find that there was a strong positive correlation
    between real wages and marriage rates in England over the period 1551-1801. Negative shocks to
    population, such as the Black Death, were reflected in higher real wages and faster population growth
    (Livi-Bacci, 1997)….Finally, the prediction of the Malthusian model that differences in technology
    should be reflected in population density but not in standards of living is also borne out. As argued by
    Richard Easterlin (1981), Pritchett (1997), and Lucas (1999), prior to 1800 differences in standards of
    living among countries were quite small by today's standards; yet there did exist wide differences in
    technology. China's sophisticated agricultural technologies, for example, allowed high per-acre yields, but
    failed to raise the standard of living above subsistence. Similarly in Ireland a new productive
    technology—the potato—allowed a large increase in population over the century prior to the Great
    Famine without any improvement in standards of living (Livi-Bacci, 1997).

Galor and Weil (2000:826) conclude that ―In early stages of development—the Malthusian Regime—the
economy remains in the proximity of a Malthusian trap, where output per capita is nearly stationary and
episodes of technological change bring about proportional increases in output and population‖.

Since Malthus‘ time, things have changed dramatically (Demeny 2011). The functioning of the
―preventive checks‖ has been altered by technological advances which are available even in low-income
settings. Advances in agricultural and industrial technologies can transform a society‘s productive
capacity and allow it to sustain growing populations.

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2.2 Models indicating that rapid population growth constrains economic growth

Mid-twentieth century models of economic growth indicated that increases in population growth constrain
growth in income per-capita. The Harrod-Domar model (Harrod 1939, Domar 1948), showed that in the
absence of diminishing returns to capital, growth in income-per-capita is affected negatively by
population growth and positively by savings as well by increases in the output-capital ratio. Solow (1956,
1957) assumed that both capital and labor had diminishing returns, and illustrated that an exogenous
increase in the population growth rate would translate into a growth of labor supply that would outpace
the growth of capital formation and ultimately lower per-capita income.

Coale and Hoover (1958) modeled the relationship between population growth and economic
development for one low-income country ─ India in the 1950s ─ characterized at the time by low GDP
growth, low industrialization, and heavy reliance on subsistence agriculture. They concluded that
population growth might adversely affect the prospects for economic development because of the
population‘s (1) increasing size, as well as (2) its structure, with high and rising child dependency ratios.
They argued that the combined effect of these two factors divert national resources away from investment
in expanding production and increasing the capital/labor ratio ― to meet the growing needs for schools,
health, housing, and other infrastructure needed to avoid compromising the future population‘s wellbeing
and productivity. Similarly at the household level, they divert resources away from saving for productive
investment, to meet current consumption needs.

These models were deeply influential, developing a consensus in development policy circles on the need
to reduce the high rates of population growth rates in developing countries.

2.3 Early empirical challenges to these models

The first challenge to the Coale and Hoover model was the lack of any significant correlation between
rates of population growth and per-capita output across a sample of developing countries (Kuznets, 1967,
reprinted in Kuznets, 1973:43). A spate of studies followed with similar conclusions (Lee 1983).

What seems to have attracted little attention was the fact that Kuznets very explicitly and carefully
qualified the conclusions he drew from his work. He was careful to specify that technological
improvements can increase production and help avoid the Malthusian ―positive checks‖. He added that
the technologically feasible may not be actualized, that there could be serious social and political
problems involved in making the needed adjustments (Kuznets 1973:7, 45). He clarified that lower rates
of population growth could enable more rapid growth in per capita output (Kuznets 1973:90).

Moreover, Kuznets did not know at the time of his writing that world population was growing much
faster than indicated by the UN medium projections he used, which were published in 1966. These
projected a doubling of the population in the less-developed areas of the world between 1965 and 2000
(Kuznets 1973:7). In fact, this projection tallies with recent UN estimates4― but only because from the
mid 1960s onwards the most populous developing countries undertook energetic and successful efforts to
reduce fertility. This hindsight adds yet another qualification to Kuznets‘ careful qualifications of his
conclusions, that:
     ―…purely technological and economic factors allow sufficient margins, in most underdeveloped
     countries, to permit substantial and sustained economic growth, even with a significant rise in population
     ― at least for the proximate future of two to three decades.‖ (Kuznets 1973:41)

Those building on Kuznets‘ work sometimes seem to think that he did not believe that population growth
can hinder economic growth. Easterlin5 summarizes Kuznets‘ position more accurately : ―Kuznets saw

                                                                                                                  4
the basic obstacles to economic growth as arising from delays in adjusting social and political institutions,
and viewed population growth, though an impediment, as of secondary importance‖.

A second challenge to the Coale-Hoover model came from studies exploring their prediction that higher
dependency ratios would divert resources towards meeting growing needs for outlays in areas such as
education. Schultz (1987) tested for this investment-diversion effect. He found that over the period 1969-
1980, enrolment rates and number of years of schooling completed rose significantly in low-income
countries, and that the relative size of the school-age cohort exerted no independent influence on the share
of GNP allocated to education. Costs per pupil dropped, with rising class sizes per teacher, and decline in
teachers‘ salaries. This suggests that the quantity of schooling can rise without diverting resources from
other forms of investment despite growth in the school-age population. However, Schultz pointed out
that reduced expenditures per pupil may have reduced the quality of schooling.

A third challenge to the Coale-Hoover model came from empirical studies that failed to confirm that high
youth dependency ratios have a negative impact on savings and thereby on economic growth (National
Research Council 1986:44-45, Kelley 1988:1707). However, Kelley (1988:1707) cautioned that these
studies have serious methodological limitations, deriving not only from the limitations of cross-country
analysis, but also from problems with specifying several key variables.

Kelley (1988:1700) cites a large number of studies that found weak or non-existent empirical support for
the thesis that population growth hinders economic growth, based on cross-country correlations.
However, he points out that this analytical approach does not reveal causation, and that ―institutional
variations among countries may mask the relationships‖.

The methodological problems with these early studies were carefully acknowledged by Johnson and Lee
(1987:xi) in their editorial preface to the studies carried out on behalf of the National Research Council‘s
Working Group on Population Growth and Economic Development:
     ―The working group concluded that slower population growth would, on balance, benefit most
     developing countries and that the positive effects of slower population growth on economic development
     would be clearest in the poorest and most densely populated countries. But the working group also
     reported that drawing firm conclusions about the overall impact of slower population growth is difficult
     because the research base is inadequate. Studies completed to date are frequently based on limited
     samples and data of poor quality, as well as on only partial and occasionally inappropriate conceptual
     models and statistical techniques. Simply put, the scientific literature contains few adequate studies of the
     effects of slower population growth in developing countries.‖

Their conclusion that slower population growth would benefit most developing countries, especially the
poorest and most resource-stressed, was much less clearly stated in the NRC‘s summary report on policy
questions (NRC 1986:93). This influential report was widely interpreted as not supporting the view that
family planning programs could do much to enhance the prospects for economic growth.

2.4 Recent empirical studies re-affirming the Coale-Hoover model

A spate of recent studies have re-affirmed different aspects of Coale and Hoover‘s thesis. These use a
wide range of analytical methods (macro and micro), including updated approaches to cross-country
regressions. 6 Coale and Hoover‘s youth dependency hypothesis has received the most attention. This is
that if a population has a high proportion of children to working-age adults ― typical of populations with
high fertility ― the prospects for economic growth are diminished.

Higgins and Williamson (1997) find that high youth dependency ratios are associated with lower savings
and investment. They found that ―much of the impressive rise in Asian savings rates since the 1960s can

                                                                                                                     5
be explained by the equally impressive decline in youth dependency burdens. Wherever the youth
dependency burden has fallen dramatically, Asian countries have relinquished their reliance on foreign
capital.‖ They found this effect to be stronger in East Asia than in South Asia, where the fertility
transition has been less rapid.

Bloom and Williamson (1998) argued that rapid fertility decline in East Asia facilitated the rapid
economic growth in this region by reducing the dependency ratio, ―thereby expanding the per capita
productive capacity of East Asian economies‖. They noted that this is a temporary window of
opportunity, because continuing fertility and mortality decline will result in high proportions of old
people relative to working-age adults. They also pointed out that the East Asia region was able to
capitalize heavily on this opportunity because they had built the policy and institutional settings needed to
realize the growth potential created by this demographic dividend.

The gains from this demographic window of opportunity may be made permanent if they are invested in
physical capital and human capital (Lee 2009). With good planning, this demographic dividend can be
used to transform economies such that their growth potential remains high after the window has closed.

Moving to global macro-studies, Kelley and Schmidt (2005) conclude that higher dependency ratios
(including both youth and old-age dependency ratios) have a significant impact on growth. They find that
―Worldwide, the combined impacts of demographic change have accounted for approximately 20% of per
capita output growth impacts, with larger shares in Asia and Europe.‖ Earlier, they had found that
dependency ratios impact on savings, from an examination of 65 less developed countries and 23
developed countries over time and cross-sectionally since 1960 (Kelley and Schmidt 1996).

Turning to the question of whether rapid population growth reduces growth in income per capita,
Acemoglu and Johnson (2007) examine the data from 47 developed and developing countries over the
period 1940-2000 and conclude that
     ―Overall, the increases in life expectancy (and the associated increases in population) appear to have
     reduced income per capita.‖ (Acemoglu and Johnson 2007: 975).
As Galor and Weil (2000: abstract) put it, the relationship between population growth and income growth
changes as economies mature:
     ―The economy evolves from a Malthusian regime, where technological progress is slow and population
     growth prevents any sustained rise in income per capita, into a Post-Malthusian regime, where
     technological progress rises and population growth absorbs only part of output growth. Ultimately…the
     economy enters a Modem Growth regime with reduced population growth and sustained income growth‖.

2.5 What of poverty reduction?

Although the debates summarized here have focused more on the potential impact of population dynamics
on economic growth rather than explicitly on poverty reduction, it is apparent that they view economic
growth as a means to raise living standards and reduce poverty. GDP growth ― whether derived from
growth in the agricultural, manufacturing, or service sectors ― typically raises living standards among
substantial sections of the population, with ripple effects for others. A possible exception is growth that
derives from exploitation of mineral resources (such as oil), where small elites can potentially capture
much of the proceeds.

Some micro-studies have focused on fertility and children‘s wellbeing. They support Coale and Hoover‘s
thesis that at the household level, high fertility reduces investments in children. Some studies use twin
births to minimize the potential confounding effect of endogeneity: namely, that parents who have larger
numbers of children have different characteristics from those who have few children. Using this method,
Rosenzweig and Wolpin (1980:239) found that in India: ―exogenous increases in fertility decrease child
quality and suggest that a decrease in family size brought about, say, by exogenous improvements in birth

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control technology, would increase schooling levels of Indian children‖. Rosenzweig and Zhang (2009)
use the same approach to estimate the net effect of an extra child at parities one and two in China, and
find that the extra child ―significantly decreases the schooling progress, the expected college enrolment,
grades in school and the assessed health of all children in the family‖.

Other micro-studies find that fertility decline is associated with broader indices of household wellbeing
and poverty reduction. In Matlab, Bangladesh, fertility decline was found associated with improvements
in women‘s health, household earnings and assets, use of preventive health inputs, and children‘s health
and schooling (Joshi and Schultz 2007). In Colombia, the family planning program was found to bring
substantial socio-economic gains to women, especially if they had access to the program when young.
Such women obtained more schooling, and were more likely to work in the formal sector. The study
concluded that ―(c)omparisons with other well-regarded development interventions suggest that these
estimates may place family planning among the most effective (and cost-effective) interventions to foster
human capital accumulation‖ (Miller 2010:711).



3. Does Population Growth Exacerbate Pressure on Natural Resources?
Some economists have argued that more rapid population growth may help drive economic growth, by
spurring technological innovation that can potentially stretch resources indefinitely. However, there is
reason to believe that human ingenuity may have its limits.

3.1 Can human innovation stretch resources indefinitely?

The first to argue that population growth may have a positive effect on technological innovation was
Kuznets (1960), who speculated on a priori grounds that if the proportion of geniuses in a population is
constant, the larger the population the large the number of geniuses. He acknowledged that this was
based on the assumption that the necessary resources would be available for education, training, and other
capital investment, to maintain or increase per capita productivity ― and that therefore this argument did
not hold for the developing world. Even for the developed world, he warned that there could be severe
problems in adjusting to the implications of larger population size.
    ―First, few if any of the points made are relevant to the underdeveloped countries. By definition, the latter
    suffer from an acute shortage of capital, not only for material investment but also for adequate raising and
    education of their younger generations….Second, even in the advanced and developed economies,
    population increase means further pressure upon limited natural resources, upon the supply of material
    capital, and above all, upon the capacity of the social and economic structure to adapt itself to it. All the
    factors cited in the current (and past) literature that make for the increased burden of larger populations—
    if higher per capita product is to be attained—are relevant here.‖ (Kuznets (1960: 337-8)

Despite Kuznets‘ very cautious treatment of his thesis, subsequent studies underplayed his cautions and
built on the possibilities he had raised to suggest that population growth was a positive force for economic
development.

Boserup (1965) argued that rising population tends to induce agricultural innovation and lead to
agricultural intensification, allowing greater productivity per unit of land to feed the larger population.
This process of agricultural intensification has been widely observed, but it is less clear how much this
raised per capita consumption before the Industrial Revolution brought radical new agricultural
technologies. Yet as Galor and Weil (2000) note, many studies indicate that output per capita was nearly
stationary for millennia preceding the Industrial Revolution.


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Kremer (1993) argued that over the long sweep of history, ―larger initial populations have had faster
technological change and population growth‖. Klasen and Nestman (2006: 14-15) argue that SubSaharan
Africa‘s low population density hampered technological change, but that this may change now with rapid
population growth. They add, though, that modern technology can be diffused even without high
population densities, but that technological uptake is still slow in the region.

Simon (1981, 1996) built on Kuznets‘ thesis to argue that human innovation assures that population
growth has long-term benefits for living standards, in both developing and developed countries. Contrary
to the evidence from the wide range of studies summarized by Galor and Weil (2000), Simon (1996: 580)
asserts that the ―standard of living has risen along with the size of the world‘s population since the
beginning of recorded time…‖.

Simon argued that people and markets innovate in response to potential resource shortages, and therefore
the resource base is effectively infinite. ―There is no physical or economic reason why human
resourcefulness and enterprise cannot forever continue to respond to impending shortages and existing
problems with new expedients that, after an adjustment period, leave us better off than before the problem
arose‖ (Simon 1996:580). He argued further that human activity was not responsible for environmental
damage, and that ―the trends toward greater cleanliness and less pollution of our air and water are even
sharper than before‖ (Simon 1996:578).

For Simon, population growth helps resolve ― not cause ― resource scarcities and environmental
problems. Simon and Boserup both argued that higher population densities can increase the economies of
scale in providing productivity-enhancing infrastructure and services such as transport and extension
services (Glover and Simon 1975; Boserup 1981).

Simon‘s arguments were supported by studies of the costs of some industrial resources. Potter and Christy
(1962) for example, showed that mineral prices in the US actually fell by approximately 40 percent
between 1870 and 1957, a period during which there was rapid growth in both population and industrial
output. Barnett and Morse (1963) showed that the labor and capital inputs needed to produce scarce
natural resources that included fuels, metals and non-metal minerals had more than halved over the same
time-frame. For such clearly-priced resources, there are strong private incentives to find innovative ways
of managing their use to keep prices down.

Certainly the Industrial Revolution and subsequent technological innovation enabled a huge jump in
productive capacity, enabling rising levels of per capita GDP and consumption. The manufacturing sector
also allows much more scope than the agrarian for absorbing a growing labor force. However, policy and
institutional settings shape the scope for benefiting from the new technical possibilities. Much of the
developing world lagged behind the developed world in putting policies in place to encourage economic
growth, but this has changed in recent decades and their pace of growth has picked up.

The long view taken by some who argue that population growth can be accommodated by technological
change discounts the deprivation faced by generations before the benefits of change manifest themselves
― even under the most conducive of circumstances. China is a good example, since its political system
permits far more radical innovation that most others. From the end of the 1970s, a series of economic
reforms were instituted − GDP per capita (in US$ Purchasing Power Parity terms) rose nearly 20-fold
between 1980 and 2007 (IMF 2010a), and poverty levels fell sharply. This was helped by rapid fertility
decline since 1970, when targets were set for implementation by local authorities.7 Yet after decades of
blistering economic growth and fertility decline, there are still significant levels of poverty in China.
Almost a third of the rural population was consumption poor in at least one year between 2001 and 2004,
using the dollar-a-day estimate in 1993 PPP dollars which is a low threshold by international standards
(World Bank 2009: vi, 18). Using more average thresholds increases the estimated poor population
substantially (Chen and Ravallion 2008).

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3.2 Limits to innovation – managing environmental common property resources

The concerns raised by early studies8 forecasting population pressure on resources receded quickly as
technological innovation rapidly raised agricultural productivity and kept the prices of some commodities
down. More recently, widespread concern over environmental common property resources has again
raised issues of sustainable development.

A relentless demand for continuing adaptation and innovation is generated by the world‘s growing
consumption needs, with increases in per capita consumption levels and population growth.
Technological progress has certainly increased production, but this has not been without negative
ramifications. Common property resources are under pressure from activity to meet rising consumption
requirements. For example, fertilizer runoff has increased with agricultural intensification, creating low-
oxygen ―dead zones‖ in coastal oceans (Map 1).

While market forces and ingenuity can find ways to better manage the use of non-renewable resources
that are clearly priced, it is proving more difficult to conserve resources that are unpriced or underpriced,
such as oceans and the atmosphere. Even to understand the intricacies of environmental change is a
challenging task for scientists ― and organizing collective action to avert negative consequences is a
challenging task for political leaders even at local levels, let alone national and global levels.

These factors combine to create a daunting list of needed adaptations and innovations, which are complex
to develop as well as to implement. The World Development Report 2010 summarizes some of the
measures needed just for sustainable food production (World Bank 2010a). To manage land and water
resources to feed 9 billion people and protect natural systems, they point to the need for politically
daunting measures, such as:
             building flexible international agreements
             pricing carbon, food and energy
             redirecting agricultural subsidies
             strengthening the policy environment for natural resource management.

As the World Bank (2010a) points out, food demand is rising with growth in incomes as well as in
population size. Climate change will make it harder to meet that food demand. A huge increase in
productivity will be needed at the same time as huge increase in regulation to protect natural systems.
However, the report takes as given the projected rate of population growth, perhaps because it was outside
its already enormous scope to discuss policies that might alter its trajectory.

Yet population size is amenable to policy, as we discuss below, and makes a big difference to the size of
adjustments required on other fronts. Models vary, but the World Bank (2010a) estimates that to meet the
growing demand for food between 2005 and 2055, agricultural productivity will need to rise by 64
percent under the assumptions of the ―business as usual‖ scenario and by a further 80 percent under the
assumptions of projected stresses arising from climate change (Figure 1). Yet the model indicates that if
population remained constant at the 2005 level, agricultural productivity would need to rise only 25%
under the ―business as usual‖ scenario ─ i.e., more of the required productivity increase under the
―business as usual‖ scenario is necessitated by population growth, than by increases in per capita
consumption.

Conventional estimates of GDP growth are misleading on the sustainability of production possibilities,
because they ignore the depreciation of natural capital (Arrow et al 2004, Dasgupta 2010).
     ―Since GDP is the total value of the final goods and services an economy produces, it does not deduct the
     depreciation of capital that accompanies production—in particular, it does not deduct the depreciation of
     natural capital. In the quantitative models that appear in leading economics journals and textbooks, nature


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     is taken to be a fixed, indestructible factor of production. The problem with the assumption is that it is
     wrong: nature consists of degradable resources. Agricultural land, forests, watersheds, fisheries, fresh
     water sources, river estuaries and the atmosphere are capital assets that are self-regenerative, but suffer
     from depletion or deterioration when they are over-used. (I am excluding oil and natural gas, which are at
     the limiting end of self-regenerative resources.) To assume away the physical depreciation of capital
     assets is to draw a wrong picture of future production and consumption possibilities that are open to a
     society.‖ (Dasgupta 2010:6)
Moreover, ―property rights to natural capital are frequently unprotected or ill-specified....(which) typically
leads to their overexploitation, and so to waste and inequity‖ (Dasgupta 2010: 6).

Arrow et al (2004: Table 2) estimate how much ―genuine wealth per capita‖ (including natural capital,
human capital, and manufactured capital) changed during 1970-2000. The estimates are necessarily
approximate, but they have been made carefully and the results are instructive. They find that while GDP
per capita grew quite rapidly in all regions except in Sub-Saharan Africa, rates of growth in ―genuine
wealth per capita‖ were far lower. They declined sharply in Sub-Saharan Africa and in the Middle East
and North Africa (by -2.6 and -3.8 percent per year respectively). They grew very slowly (well below 1
percent per year) in South Asia and the United States. They grew rapidly only in China, due to its low
population growth and heavy investment in productivity. Revising the method to include more
information on growth in human capital and institutional change, Dasgupta (2010: 9-10) derives far lower
estimates of growth in genuine wealth per capita for China 1970-2000, and for South Asia he estimates a
decline of between -0.4 percent per year (India) and -1.4 percent (Pakistan).

Rates of internal and international labor migration will rise with the pressures of environmental
degradation and climate change (Laczko and Aghazarm 2009, World Bank 2010a: ch2). Even current
rates of migration have proved difficult to manage politically in many countries, as local residents resent
encroachment on their resources. It is likely to prove very daunting to accommodate accelerated in-
migration, especially when receiving areas are under greater pressure themselves. This is just one of the
challenges that increasing rates of population growth pose to societies‘ capacity to adapt their social,
political, and economic institutions to respond to the new needs (Kuznets 1973:91, McNicoll 1984).

Human ingenuity has faced an uphill task at devising ways of managing common property resources ─
given the institutional and political challenges posed in aligning divergent interests. Markets are very poor
at incentivizing people not to overuse resources that are un-priced or under-priced relative to social cost
(Arrow 1969, Dasgupta 2001, Stern 2006), especially in the case of transnational common resources
(Dasgupta et al 1997). The consequent negative externalities need to be addressed through collective
action, but in the absence of strong mechanisms for mutual coercion it is very difficult to align the
interests of different stakeholders to this end. Ostrom (1990) has argued that common property can be
successfully managed by user associations in small communities if eight ―design principles‖ are met,
including the ability to effectively exclude unentitled parties. Such conditions clearly do not apply to
global common resources. As Lee (1990:317) points out ―each birth inflicts costs on all others by
reducing the value of their environmental birthright‖.

The juxtaposition of all these daunting scientific, executive, and political challenges suggest that even
countries which have so far adapted to growing needs may find it difficult to respond to these new kinds
of demands (Demeny 2011). They place high demands on national and global institutional capacity, as
evidenced by the slow progress made in decades of efforts to regulate carbon emissions.

Reducing the number of births may be one of the simplest ways of reducing pressure on common
property resources. For instance, it is estimated that the effect of a 40% reduction in CO2 emissions per
head in developed countries between 2000 and 2050 would be entirely offset by the increase in emissions
attributable to expected population growth in poorer countries over this period, even assuming no change
in emissions per head in these countries (Dyson 2005). Moreover, CO2 emissions per head have risen in

                                                                                                                   10
countries such as China, India and Brazil in line with rapid economic growth. O‘Neill et al (2010)
estimate that slowing population growth could reduce carbon emissions significantly. Indeed it has been
argued that the prevention of unwanted births today is likely to be one of the most cost-effective ways to
preserve the planet‘s environment in the longer term (Birdsall 1994).



4. Implications for Sub-Saharan Africa
Sub-Saharan Africa is now the developing region closest to the scenario described by many as that in
which rapid population growth is most difficult to accommodate because of slow productivity growth. As
Weil and Wilde (2009:259) conclude from their study:
    ―The Malthusian channel by which a high level of population reduces income per capita is still relevant in
    poor developing countries that have large rural populations dependent on agriculture, as well as in
    countries that are heavily reliant on mineral or energy exports.‖

Fertility rates remain high in much of Sub-Saharan Africa, with a regional average of 5.1 children per
woman in 2008 ― matched outside the region only by 4 small war-torn countries9 (World Bank 2010b:
Table 2.19). Although fertility has declined in many countries in this region,10 only a few have a TFR
below 4.11 High fertility also helps keep maternal mortality high (section 5.1) ― Sub-Saharan Africa has
an estimated 1:31 lifetime risk of maternal death, which is four times higher than that of developing
regions as a whole (WHO et al 2010: Table 2).

Between 1970 and 2005, the population aged below 15 years grew by 150 percent in Sub-Saharan Africa
as a whole, and by over 200 percent in the high-fertility country of Niger ― compared with 30 percent for
Asia, and 36 percent for Latin America (Figure 2). As a result, Sub-Saharan Africa has as yet benefited
far less than other regions from the impact of reduced dependency ratios on per capita output growth
(Kelley and Schmidt 2005, Eastwood and Lipton 2011).

This region is estimated to have depleted ―genuine wealth per capita‖ quite rapidly during 1970-2000
(Arrow et al 2004, Dasgupta 2010):
    ―Population growth implies significant differences between the initially estimated growth rate of genuine
    wealth… and the growth rate on a per capita basis…. At an annual rate of decline of 2.6 percent in
    genuine wealth per annum, the average person in the sub-Saharan Africa region becomes poorer by a
    factor of two about every 25 years.‖ (Arrow et al 2004: 164-5)

Although it has an enormous wealth of resources, including land and minerals, policy environments in
many countries have not been conducive to rapid growth in average living standards. Growth in real GDP
per capita during 1960-2004 was only 24% in the Sub-Saharan African region, compared with 108% on
average in low-income countries, and 685% in the East Asian region (Figure 3). The region as a whole
showed low growth despite rapid growth in some countries, including Botswana and Mauritius. This is
because several populous countries show low growth: population growth rates from 1960-2004 were
higher for countries with large- and medium-sized populations than for those with small ones (World
Bank 2007a:33-35). More recently the annual percentage growth in GDP has risen (at constant prices) to
around 5.6% per year during 2004-07 (IMF 2010a), and similar rates are projected for the region for
2011-12 (IMF 2011: Box 1). Some countries are growing much faster. However, the regional GDP
growth is nearly halved on a per capita basis by population growth.

Agricultural production per capita was stagnant during 1960-2005, whether measured in overall food
production per capita (Figure 4) or cereal yields per hectare (World Bank 2007b:Fig 2.1) ― in sharp
contrast to rapid growth in these indices in Asia and Latin America. Agricultural stagnation is an especial


                                                                                                                 11
problem because a large proportion of the people depend on it for a livelihood: agriculture in Sub-Saharan
Africa employs 65 percent of the labor force and generates 32 percent of GDP growth.12

Productivity growth in agriculture has been hampered by policies discouraging innovation by
smallholders. In a seminal study, Bates (1981) showed how in many countries, policies have depressed
the prices smallholders can obtain for their output, and limited their access to subsidies for agricultural
inputs and credit. This reduces smallholders‘ incentives to invest in their land, and to grow more than they
need for subsistence. By contrast, elite farmers with political connections are given access to highly
beneficial terms.13 Djurfeldt et al (2006:10) note that ―The result was a dual structure comprising, on the
one hand a small group of ‗modern‘ often well-connected and sometimes absent, commercial farmers and
estate owners and, on the other hand, a vast majority of low-productivity, semi-subsistence oriented
smallholders growing traditional varieties using only small amounts of fertilizers and improved seeds.‖
Added to this are investment disincentives in areas with insecure tenure arising from traditional patterns
of communal landownership (Besley 1995, Otsuka and Place 2001).

Rates of technological uptake have been low (World Bank 2007b:52-55). The use of modern inputs such
as fertilizers, improved varieties of cereals, and irrigation are far lower in Sub-Saharan Africa than in
other developing regions. Soil degradation is widespread. This contrasts with the policies that helped
most Asian countries to increase agricultural production by providing credit, support prices, and input
subsidies to farmers, as well as by investing in research and development and in infrastructure such as
roads and irrigation. The good news is that policies are improving. Djurfeldt et al (2006:10, 62) note
policy shifts that will improve incentives for smallholders to invest in their land and enhance productivity.
Agricultural taxation has fallen in several countries (World Bank 2007b:100).14 In recent years,
agricultural output has increased in several countries (Badiane 2008). And a study in Machakos, Kenya
finds that with improved agricultural policies it is possible to raise productivity and reverse soil
degradation (Tiffen et al 1994).

Meanwhile, population pressures are growing on the land. Jayne et al. (2003) found that almost a quarter
of rural households in Ethiopia, Kenya, Rwanda, Mozambique and Zambia were virtually landless and
had little non-farm income to supplement their livelihood. Aggregate availability of cropland per
agricultural person fell by 40 percent between 1960 and 2003 (World Bank 2007b:63). Land quality is
another issue ─ although cropland availability was still double that of Asia in 2003, population densities
on the land are similar to those of Asia when adjustment is made for land quality (World Bank
2007b:55,63). The land-quality-adjusted population density in Kenya was estimated in the 1980s to be
higher than that in Bangladesh (Binswanger and Pingali 1988, cited in World Bank 2007b:55). In
response to population pressure, people are degrading land through over-cropping and over-grazing, and
expanding into more fragile lands (World Bank 2007b:55). The FAO (2003) estimates that the demand
for food will increase by 2.9% per year, heavily fuelled by population growth of 2.4%.

Other pressures are also building up. Africa is one of the regions projected to be most severely affected
by drought and temperature rises due to global warming. Water availability will shrink significantly,
especially in the South, West, and North of the continent (World Bank 2010a:137). Land degradation and
drought have already caused much movement of people seeking livelihoods elsewhere, and the Sahel is
especially at risk.

Demographic, economic and political pressures ─ population growth, land degradation, government
crises ─ generate conflict, which in turn can create further economic and political pressures. Conflicts
over land and livelihoods are intensifying in many countries (Peters 2004, Green 2010). Mamdani (2001:
ch 6,7) points out that rapid population growth was one of the factors underlying the Rwanda genocide,
generating resentment among locals who experienced heavy in-migration of people seeking areas with
richer land. Large flows of refugees and other migrants create pressures for the receiving areas: Hatton

                                                                                                          12
and Williamson (2003:474) estimate that for every two refugees, one local is pushed out of the home
labor market.

These pressures generate much migration in the region (Hatton and Williamson 2003). Most of this
migration is within the region, within-country and between-country. People migrate to other rural areas
where sometimes competition for land generates conflict, and to cities where slow growth in
infrastructure and jobs make urban poverty a serious issue. And the pressures for international out-
migration are projected to continue to mount (Hatton and Williamson 2003).

Yet things could really change. As the case of Botswana shows, with good management the region‘s
enormous mineral wealth and other natural resources can be tapped to create social and physical
infrastructure and generate employment for the large cohorts of young people. Some of the wealth could
be invested in expanding the manufacturing sector, which can absorb large amounts of labor. Such
measures could offset demographic pressures and enhance living standards. In many settings though, this
wealth has been viewed as having been turned into a ―resource curse‖, facilitating elite capture and
reducing the need for the political leadership to maintain their legitimacy by building institutions for a
developmental state (Collier and Goderis 2007, Unsworth and Moore 2010).

Despite many successes, most countries in this region face challenges to growth arising from institutional
constraints of various kinds. Tackling these constraints to growth is urgently required. In addition, most
countries would benefit from strengthening family planning programs, to ease the currently high
momentum of population growth that further constrains the prospects for improving standards of living.



5. Do Family Planning Programs Help Lower Fertility?
Family planning programs seek to expand the availability of contraceptives and reduce barriers to their
use.15 They are especially important for the poor, who typically have higher numbers of unwanted
children than the rich except in settings with very effective programs, such as Indonesia (Figure 5).
Family planning programs also typically disseminate information on contraception, and on how lower
fertility can help parents invest in their children and avail new opportunities for raising living standards.16
Parents – especially poorer parents – have imperfect information on these issues. Households also appear
to face difficulties in making optimal choices that involve long-term planning horizons (see for example
Cronqvist and Thaler 2004 on pension decisions). Offering simple information on contraception ― or
more complex messages through media such as soap operas that portray the lives of people with small
families and how they access new opportunities ― helps reduce imperfect information. Many studies
using cross-sectional survey data have found access to media significantly associated with increased
contraceptive use and reduced fertility.17 The few quasi-randomized evaluations of media effect have
found it effective at altering fertility and contraceptive use in Tanzania (Rogers et al 1999) and reducing
fertility in Brazil and India (La Ferrara et al 2008; Jensen and Oster 2009).18

In a highly influential paper, Pritchett (1994a) argued that family planning programs have little impact on
fertility:
     ―Ninety percent of the differences across countries in total fertility rates are accounted for solely by
     differences in women's reported desired fertility…. The results contradict theories that assert a large
     causal role for expansion of contraceptive use in the reductions of fertility.‖ Pritchett (1994: abstract)

Many have taken Pritchett‘s study as indicating that effort on family planning programs is ill-spent, but he
later concludes that his estimates imply that strengthening a family planning program substantially (by 50
points out of a scale of 0-100) would reduce fertility by one birth (Pritchett 1994b: 626). Bongaarts

                                                                                                                  13
(1997) estimates the corresponding fertility reduction at 1.4 births, but even Pritchett‘s lower estimate
amounts to a very large difference in population momentum and size ― if one birth less per woman was
sustained in Sub-Saharan Africa over the projection period 2010-2050, the UN (2009) estimates that there
would be half a billion fewer people in that region (Figure 6).19

The crucial gap in Pritchett‘s argument is that he assumes that family planning programs work only on the
supply side, and overlooks their important role in reducing desired family size. He conducts cross-
country regressions of the Total Fertility Rate against contraceptive prevalence and against family
planning effort, but in both cases he controls for desired fertility (Pritchett 1994: Table 3). As he says
(1994:41-42), he does not focus on the determinants of desired fertility, and concludes that reducing
fertility has little to do with manipulating contraceptive supply. This is missing much of the point, as
mass media outreach to reduce desired family size is a major component of family planning programs.
Studies have shown that the mass media is very effective at increasing contraceptive use and reducing
fertility (see above).

Evaluating the impact of family-planning programs is challenging, because they are rarely randomly
placed and uniformly executed. However, many studies indicate that family planning programs affect
fertility. Schultz (2009: 4) notes that several careful evaluations of family planning programs (including
in Taiwan, Colombia, and Indonesia) find a negative association between ―the regional intensity of
program treatment and the regional level of fertility‖ in a country.20 While some studies are simple cross-
sectional analyses, others have gone further to analyze panel data and include fixed effects for regions and
time. However, the estimated program impact may be biased by nonrandom placement ─ for example it
could be over-estimated if program effort is directed more towards areas with greatest demand, and
under-estimated if effort is directed more towards areas with the greatest need.21 In Indonesia, the
program was found to have helped reduce fertility, and this effect was if anything under-estimated
because the authors found that ―the government targets resources to areas of low contraceptive use and
dynamically updates those allocations on the basis of program performance‖ (Molyneaux and Gertler
2000:82-83).

Rigorous randomized experiments of family planning programs are not available. The Matlab program in
Bangladesh approximates a randomized trial, since half the villages studied for the period 1974-96
received more intensive family planning and maternal and child health program inputs, while the other
half received regular government program inputs. Note that the country was poor and largely illiterate for
much of the study period. The first set of villages showed more rapid fertility decline after the program
began, and maintained 15 percent lower fertility 1982-96 (Joshi and Schultz 2007:30). This difference is
especially striking given that fertility was falling rapidly across the country. Similar results emerge from
an evaluation of Colombia‘s family planning program, which exploits differences in timing of the
introduction of the family planning program to estimate the impact of contraceptive availability on
fertility (Miller 2010:717).22 The program is found to have lowered fertility by about 10 percent ─ again,
despite the fact that fertility was declining rapidly across the country. As described above, households
with lower fertility also showed improvements in schooling, health, and earnings.

These evaluations may tend to under-estimate the impact of family planning programs, insofar as their
measures of program effort are more likely to pick up variation on the supply side. Mass communication
efforts to reduce desired family size are likely to reach people regardless of whether they live in areas
with higher or lower supply-side program effort. However, as mentioned above, without randomized
trials it is difficult to assess whether on balance evaluations tend to over-estimate or under-estimate
program effect.




                                                                                                         14
Fertility and maternal mortality

Reducing fertility also helps lower maternal mortality (NRC 1989). Abortions following unplanned
pregnancies are a significant cause of maternal death. Secondly, the risk of maternal death varies widely
with maternal age and birth order ─ it is high for younger teenage mothers, and rises sharply again at
higher birth orders and higher ages. Avoiding teen childbearing and having smaller families reduces
maternal mortality risks, as does longer spacing between births. And women‘s mortality risk remains
elevated for long after childbirth: a study in Bangladesh found that it is nearly twice as high as normal for
up to two years after childbirth (Menken et al 2003).

That fertility reduction can help improve women‘s health is suggested by Figure 7, which shows how
much female adult mortality improved (relative to male) in India concomitant with fertility decline. The
comparison with men provides a rough control for overall health improvements. In the early 1970s,
female mortality plummeted relative to males in the early childbearing years, picking up gradually over
the lifecycle. By 1990, adult women‘s mortality relative to men‘s had improved sharply, not only in the
childbearing years but also up to age 50, suggestive of reductions not only in maternal mortality but also
in lagged mortality arising from maternal depletion and maternal morbidity from repeated childbearing.
Improved maternal health care is another major factor in maternal mortality decline. Note, however, that
these data predate the big donor thrust from the mid-1990s, aimed at improving reducing maternal
mortality.



6. Conclusions
The argument that has raged for half a century over the relationship between population and economic
development has distracted people from recognizing that there is in fact little disagreement over the
bottom line. There is wide consensus that appropriate policy environments and technological advances
are key to improving standards of living ─ and that population dynamics play an important secondary role
in this process.23 A combination of policies is in order, as the World Bank put it:
     In short, policies to reduce population growth can make an important contribution to development
     (especially in the long run), but their beneficial effects will be greatly diminished if they are not
     supported by the right macroeconomic and sectoral policies. At the same time, failure to address the
     population problem will itself reduce the set of macroeconomic and sectoral policies that are possible,
     and permanently foreclose some long-run development options. (World Bank 1984:105)

Recent studies conclude that reducing fertility facilitates economic growth in low-income countries. Low
dependency ratios (resulting from fertility decline) create a window of opportunity for savings, increased
productivity, and investment ― which if properly managed can transform living standards permanently.
The more rapid the fertility decline in a region, the wider the window of opportunity, though its duration
will be shorter because the population will age more rapidly. They also indicate that rapid population
growth can be a constraint on economic growth, especially in poor countries with policies that do not
encourage rapid rise in productivity. Micro-studies also find that lower fertility is also associated with
better child health and schooling, reduced maternal mortality and morbidity, increased women‘s labor
force participation, and higher household earnings. This is quite aside from the intrinsic human right of
being able to control one‘s own fertility.

Hopefully these recent studies will put this debate to rest. Meanwhile, the debate has helped discourage
donors from investing in family planning programs. While these are by no means the only policy lever to
help reduce fertility, they are an effective but neglected lever with a clear rationale for public funding.
This has been a missed opportunity, especially for the Sub-Saharan African region, where fertility

                                                                                                               15
remains high and pressures on resources have been increasing. Much of the growth achieved by countries
in this region is diluted by population growth. Through careful effort, Tanzania has achieved 6-7 percent
real GDP growth over the past decade, but the effect of this on a per capita basis is almost halved by
population growth (IMF 2010b:5).

Family planning programs are intrinsic to anti-poverty efforts by facilitating increases in living standards.
They also form part of a package of measures addressing basic government failures that help sustain
poverty and high fertility ― including efforts to improve health and schooling, and to expand income-
earning opportunities. Family planning programs help by increasing access to contraception, and by
providing informational outreach to enhance perception of the benefits of shifting to a more secure
equilibrium in which people have fewer children and are able to invest more in them.

The developing world offers sharply contrasting models. At one end of the spectrum is the East Asian
region, where policies highly conducive to rapid economic growth were boosted by low dependency
ratios resulting from rapid fertility decline. These countries are using these favorable conditions to build
up human and physical assets, thus transforming their economies and locking in high growth potential
even after the demographic ―window of opportunity‖ closes and the population starts aging. At the other
end of the spectrum is Sub-Saharan Africa, characterized by high fertility and low growth in income per
capita. The fact that many countries in this region have shown some fertility decline suggests a decline in
desired family size, and family planning programs can build on this and accelerate fertility decline.

Rapid population growth exacerbates an even less tractable problem ─ environmental change and the
management of global common property resources, whose depreciation will affect the sustainability of
production possibilities. While changing consumption patterns with rising incomes is a strong driver of
pressure on these resources, population growth is also key (Figure 1). Managing global common property
resources has proven to be politically very challenging and ridden with difficulties. Family planning
programs are far simpler to design and implement. The most feasible way to reduce mankind‘s ecological
footprint may be to further reduce the number of feet being born.




                                                                                                          16
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                                                                                                               21
                       Figure 1: Required growth in agricultural productivity
                 under different assumptions of climate change and population growth


          Population growth and climate change mean that increases in agricultural productivity
                   must accelerate to meet the growing food demands as incomes rise

             250



             200                                                                  Climate change



             150                                                                  Population growth

                                                                                  Change in per
                                                                                  capita consumption
             100



               50
                 1965      1975     1985    1995    2005     2025     2045

                ••••   The scenario with climate change
                ― The "business as usual" scenario without climate change
                --- The "business as usual" scenario without climate change
                       AND NO POPULATION GROWTH AFTER 2005



Source: World Bank (2010a) World Development Report 2010: Figure 3.5 (derived from Lotze-Campen
et al 2009). We thank Dr Lotze-Campen for disaggregating the ―business as usual‖ scenario into two
estimates: (1) with population held constant at the 2005 level, and (2) the WDR 2010‘s ―business as
usual‖ scenario, which includes anticipated population increase to 9 billion by 2055.

Explanatory note from the original figure in the WDR 2010:
―The figure shows the required growth24 in an agricultural productivity index under two scenarios. In this index, 100
indicates productivity in 2005. The projections include all major food and feed crops. The green line represents a
scenario without climate change of global population increasing to 9 billion in 2055; total calorie consumption per
capita and the dietary share of animal calories increasing in proportion to rising per capita income from economic
growth; further trade liberalization (doubling the share of agricultural trade in total production over the next 50
years); cropland continuing to grow at historical rates of 0.8 percent a year; and no climate change impacts. The
orange line represents a scenario of climate change impacts and associated societal responses (IPCC SRES A2): no
CO2 fertilization, and agricultural trade reduced to 1995 levels (about 7 percent of total production) on the
assumption that climate change-related price volatility triggers protectionism and that mitigation policy curbs the
expansion of cropland (because of forest conservation activities) and increases demand for bioenergy (reaching 100
       18
EJ [10 joules] globally in 2055).‖



                                                                                                                  22
                                                                             Figure 2
                                                           % increase in population aged 0-14, 1970-2005
                                                                                                                                    (207)
               200
               180
               160
               140
               120
               100
                80
                60
                40
                20
                 0
                                                          Asia                        LAC                    SSA                   Niger


Source: Population Division of the Department of Economic and Social Affairs of the United Nations Secretariat,
World Population Prospects: The 2008 Revision, http://esa.un.org/unpp, Tuesday, August 24, 2010; 4:37:08 PM.




                                                           Figure 3 Growth in GDP per capita, 1960-2004

                                                   900
                  GDP per capita index, 1960=100




                                                   800                         East Asia & Pacific                                          785
                                                   700                         Low income
                                                   600                         Sub-Saharan Africa
                                                   500
                                                   400
                                                   300
                                                   200                                                                                      208
                                                   100                                                                                      124
                                                     0
                                                         1960
                                                                 1964
                                                                        1968
                                                                               1972
                                                                                        1976
                                                                                               1980
                                                                                                      1984
                                                                                                             1988
                                                                                                                    1992
                                                                                                                           1996
                                                                                                                                  2000




Source: World Bank 2007b: Figure 2.5, derived from the World Bank World Development Indicators database.
Note: GDP per capita index 1960=100.




                                                                                                                                                  23
                                              Figure 4: Changes in per capita food production, 1961-2005




                                                      Source: The Royal Society 2009: Figure 1.4




                                                Figure 5: Unwanted fertility is higher among the poor,
                                              and effective family planning programs can reduce this gap
                  Unwanted births per woman




                                                2                 Philippines




                                                                                                   Average 41
                                                1                                                  countries



                                                             Indonesia
                                                0
                                                        1            2            3            4           5
                                                       Poorest wealth quintile ..............................Richest


Source: Gillespie et al (2007): Table 1




                                                                                                                       24
                      Figure 6: Population projections for sub-Saharan Africa
     Maintaining one less birth per woman reduces projected population size in 2050 by half a billion


                    2


                                                                                        }
                                                                                           Difference is one
                                                                                           birth per woman
                                                                High                       throughout the
                                                                variant                    projection period

                                                                              Low
                                                                              variant
              Billions




                    1




                    0
                         1950       1970       1990        2010        2030        2050
                  Source: UN 2009
Note: The UN creates the high and low variants by keeping the TFR 0.5 births higher or lower than the median
variant throughout the projection period. Hence the total difference between the high and low variants is 1 birth per
woman
                                                                Figure 7
 Fertility Decline Helps Improve Women’s Health: adult women’s mortality fell faster than men’s
                                Trends in the Ratio of Male to Female Mortality, India, 1970-1990
            Male / female
            ratio in mortality                         Reproductive age group (15-44)
                  1.6

                  1.5                                                                          male/female mortality
                                                                                               ratio1988-92
                  1.4

                  1.3

                  1.2

                  1.1

                         1

                  0.9

                  0.8
                                                                                               male/female mortality
                                                                                               ratio 1970-75
                  0.7

                  0.6
                                0    1     5    10    15   20     25   30     35   40     45    50    55    60    65   70
                                                                   Age
                   Source: Government of India, Sample Registration Bulletin 16(1), June 1982, and SRS Based
                   Abridged Life Tables 1988-92, New Delhi: Registrar-General of India.
                                                                                                                            25
 Map 1: Intensive agriculture in the developed world has contributed to the proliferation of dead
                                             zones




Source: World Bank (2010a) World Development Report 2010: Map 3.4 (derived from Diaz and Rosenberg 2008).
Explanatory note from the original figure in the WDR 2010: ―In the developed world intensive agriculture has often
come at high environmental cost, including runoff of excess fertilizers leading to dead zones in coastal areas. Dead
zones are defined as extreme hypoxic zones, that is, areas where oxygen concentrations are lower than 0.5 milliliters
of oxygen per liter of water. These conditions normally lead to mass mortality of sea organisms, although in some of
these zones organisms have been found that can survive at oxygen levels of 0.1 milliliter per liter of water.‖




                                                                                                                  26
Endnotes
1
  It is associated with later entry into union and higher age at first birth in settings as varied as Guatemala, Indonesia,
   and Nigeria (Behrman et al 2006; Breierova and Duflo 2004; Osili and Long 2008).
2
  For example, expanding access to family planning services was introduced into the Millenium Development Goals
   many years after these goals were initially adopted.
3
  This is indicated by many studies across Europe, Asia, and Africa. See for example Scrimshaw (1984), Das Gupta
    (1995), and the papers in Page and Lesthaeghe (eds) 1981 and Tsuya et al (eds) 2010.
4
  Source: Population Division of the Department of Economic and Social Affairs of the United Nations Secretariat,
    World Population Prospects: The 2008 Revision, http://esa.un.org/unpp, Tuesday, August 24, 2010; 4:37:08 PM
5
    http://www-bcf.usc.edu/~easterl/papers/SimonKuznets.pdf
6
   In ongoing research, Ashraf, Weil and Wilde (2010) simulate the effect on Nigeria‘s per capita output, if its Total
    Fertility Rate were to decline by 1.0 immediately and exogenously. Their model ―allows for effects that run
    through schooling, the size and age structure of the population, capital accumulation, parental time input into
    child-rearing, and crowding of fixed natural resources‖. They estimate that this fertility decline (of one child per
    woman) would raise output per capita ―by approximately 13.2% at a horizon of 20 years, and by 25.4% at a
    horizon of 50 years‖, and that the dependency effect is the dominant channel whereby this impact takes place.
   Eastwood and Lipton (1999) did cross-national regressions that found that ―higher fertility increases poverty both
    by retarding economic growth and by skewing distribution against the poor‖.
7
  Contraceptive and abortion services were extended to the rural areas. ―At local level, collective incomes and
  allocation of funds—for health care, welfare, and schools, for example—made it possible for couples to
  understand the effect of their personal family choices on the community. They also made it possible for the
  community to exercise pressure on those who wished to have children outside the agreed plans.‖ (Kane and Choi
  1999:992). The Total Fertility Rate fell from 6.4 1968 to 2.7 in 1978, and 2.0 by 1992 (CPDRC 2009: Table 3-3).
8
  See for example Ehrlich 1968, Meadows et al 1972
9
  These are Afghanistan, Timor-Leste, West Bank & Gaza, and Yemen.
10
    The decline began in the late 1960s and 1970s in urban areas, and about 10 years later in rural areas (Garenne and
   Joseph 2002). Some cities are at or below replacement levels (Garenne 2008). However, the fertility decline
   stalled in many countries, even in Ghana and Kenya which had shown significant decline (Garenne 2008:26).
11
     McNicoll (2011) argues that the slow pace of fertility decline in Nigeria (and perhaps also other countries in the
   region), as compared with Indonesia, is partly attributable to differences in institutional legacies from the past.
12
    WDR 2008 press release
    (http://web.worldbank.org/WBSITE/EXTERNAL/NEWS/0,,contentMDK:21517663~pagePK:64257043~piPK:4
    37376~theSitePK:4607,00.html)
13
    Bates (1981:59):"Using political connections to secure land, publicly subsidized credit and forgiveness of debts,
    publicly subsidized and allocated fertilizer, and highly favorable terms for the importation and financing of
    capital equipment, influential members of the urban elite with close ties to the managers of the public
    bureaucracies have thus entered into food production in the northern savannah areas. . . . A major consequence of
    government efforts to promote food production in this area has been the development of disparities of wealth,
    social status, and political power within the savannah region. When similar policies have been adopted elsewhere
    in Africa, the consequences have been much the same."
14
    There may be a small uptick in GDP per agricultural person (World Bank 2007b:54), though this is barely
    detectable when the overall population is included --- so it may be partly an artifact of rural out-migration.
15
     Studies of the adoption of cost-effective new technologies show substantial evidence of learning spillovers—once
     one household accesses a successful technology others are quick to follow (see for example Foster and
     Rosenzweig 1995 on agricultural technologies). Because individual households do not appear to fully capture the
     benefits to their neighbors of their experimentation with these new technologies, spillovers create a classic case
     for public subsidy of experimentation with possibly beneficial technologies.
16
     Seeking to alter childbearing decisions may seem paternalistic. Yet it is largely accepted that the public sector has
     a responsibility to influence the set of opportunities and constraints faced by households when this affects the
     wellbeing of the collectivity. Subsidies and financial incentives are offered, for example, to encourage parents to


                                                                                                                        27
   send their children to school and use health services. These measures are generally justified in terms of the social
   benefits of schooling. Safety net transfers are offered to those facing poverty, not only on humanitarian grounds
   but also because deep social inequalities can be socially corrosive. In other cases action is mandated for the
   public good, for example immunization or elementary schooling in many countries, and contributing to pension
   schemes to provide for old age. Mandating lower fertility is clearly unethical, but that is a long way from seeking
   to alter fertility desires and lowering barriers to contraceptive use.
17
   See for example Bhat (1996).
18
   DellaVigna and Kaplan (2007) show that mass media shape voter behavior. They examined the effect of Fox
   News, which was introduced between 1996-2000 in about 20 percent of US towns. It was found to significantly
   increase the Republican share of the vote in these towns between the 1996 and 2000 Presidential elections.
19
   This is the difference between the high and the low variant of the UN population projections.
20
   These include Schultz, 1973, 1992; Rosenzweig and Schultz, 1982; and Molyneaux and Gertler, 1994.
21
   Government programs may prioritize high-demand areas if their primary objective is to meet voter preferences.
    They may prioritize low-demand areas if their primary objective is to reduce population growth.
22
   Miller (2010:711-5) argues that program placement did not prioritize areas with either higher or lower demand.
    Schultz (personal communication) observed that the program prioritized high demand populations, and that
    therefore Miller may have over-estimated the impact of the program. In an earlier study, Rosenzweig and Schultz
    (1982) found evidence of the Colombian program‘s effectiveness in a cross sectional association between the
    regional intensity of program treatment and the regional level of fertility in Colombia (cited in Schultz 2009:4).
23
    Of course, countries with fertility levels far below replacement have the opposite problem of a shrinking
    laborforce, and shrinking tax base to support the aged.
24
   The original explanatory note said it was the required annual growth, Dr Lotze-Campen corrected this by deleting
   the word ―annual‖.




                                                                                                                    28