Tony Hawkins investigates how to make economic growth benefit the poor in Zimbabwe. Presented at 'Moving Forward with Pro-poor Reconstruction in Zimbabwe' International Conference, Harare, Zimbabwe, (25 and 26 August 2009)

1. Tony Hawkins

2. After a decade of economic decline
2009 will be the first year of positive
growth in Zimbabwe since 1998.
Output (GDP) fell 45% (1998-2008)
while per capita incomes dropped 43%.
Unemployment and poverty increased

3. As also did income inequality, with
the Gini coefficient increasing to 0.64
(2003) from 0.50 in the mid-1990s.
UNDP data (2005) suggests this is
the second most inequitable income
distribution pattern in the world after
Namibia (0.74).

4. 2400
2200
2000
1800
1600
1400
1200
1000
Z$ (1990)

5. 0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
1975 1980 1985 1990 1995 2000 2005

6. 1400
1300
1200
1100
1000
900
800
Employment (000)

7. 8000
7000
6000
5000
4000
3000
2000
1000
0
Z$ (1990)

8. The official figures assume a population
of 12.1 million in 2008, which is almost
certainly overstated, with the actual
figure between 10 and 11 million.
Assuming a population of 10.5 million,
income per head in 2009 is estimated at
around $330 meaning that the “average”
Zimbabwean is living in “extreme
poverty” (World Bank) on less than
$1.25 a day (annual per capita income of
$456).

9. The most recent poverty headcount for
Zimbabwe (2003) suggested that 63% of
the population were living in poverty.
MDG target is 12.9% by 2015.
CSO figures suggest the poverty
headcount rose 21% between 1995 and
2003 while per capita incomes fell by
slightly less (19%).

10. Extrapolating these figures, the 30%
fall in GDP per head since 2003
implies a poverty headcount of some
9.5 million people.
Depending on the population
estimate poverty is then somewhere
between 80% and 90% of the
population.

11. UNIDO estimates (2004) put the
poverty elasticity of income growth in
Zimbabwe at -0.7, meaning that for
every 1% increase in per capita
income, the headcount falls 0.7%.
The IMF’s medium-term projection for
GDP growth in Zimbabwe is 5.85% a
year.

12. Assuming population growth of 1.5%
annually this suggests per capita
income rising at just over 4%
annually.
If the UNIDO poverty elasticity is
broadly right then, the poverty head
count falls 2.8% a year.

13. Starting from a population of 11
million it would then take 47 years
from 2010 to reach the MDG target of
a poverty headcount of 12.9% of the
population.
Not as horrific as it might sound
Unido’s 2004 estimate was that it
would take until 2108 for Zimbabwe
to halve poverty.

14. My projection is far more optimistic
primarily because of the assumption
of 4%-plus growth in per capita
income.
UNIDO’s projection was based on
average growth in the 1990s, when
per capita incomes actually fell in
Zimbabwe.

16. Poverty reduction occurs:
Because average incomes rise,
assumed to be income-distribution-neutral,
and/or
Because income is redistributed from
the more prosperous to the poor – so-called
pro-poor growth.

17. In countries with very high levels of
income inequality – Botswana, South
Africa, Zimbabwe – poverty reduction
can be accelerated by simultaneously
increasing average incomes, AND
Reducing income inequality by dint of
redistributive public spending
programmes.

18. Given the lop-sided nature of Zimbabwe’s
economic decline – the eradication of the
middle class – in a post-crisis economy
there is virtually certain to be some
reduction in income inequality as the middle
class re-emerges.
At the same time, donor support will focus
on poverty alleviation that will improve the
pattern of income distribution

19. Furthermore, while Zimbabwe will
get debt forgiveness, because it is not
currently servicing foreign (or
domestic) debt this will not translate
into new money for social spending
as is normally the case.
Accordingly, the main impetus for
poverty reduction must come from
faster GDP growth.

20. The scope for redistributive policies will
be limited by :
The narrow, already highly regressive,
tax-base heavily reliant on consumption
taxes, and
The imperative of increasing public
investment in infrastructure rather than
recurrent social spending.

21. Unfortunately, Chinese experience tells
us that exceptionally rapid income
growth in China has worsened income
distribution – the Gini has gone up.
This may be an inevitable consequence
of growth because productivity rises
faster in rapidly-expanding sectors –
manufacturing and services – than in
agriculture and especially small-scale
farming.

22. For any given rate of GDP growth, the
speed of poverty reduction depends
on a range of factors:
1.The pattern of growth - because
poverty elasticities are greater in
manufacturing (0.22) and services
(0.26) than agriculture (0.16) industry
growth makes a greater contribution to
poverty reduction than agricultural
expansion.

23. 2. The capital-intensity of growth –
the greater this is, (oil, mining,
heavy industry), the fewer jobs are
created and the smaller the impact
on poverty reduction.
3. Physical infrastructure – where this
is poor the weaker the spillover
effect of industrial (urban)
development on the rural economy.

24. 4. Policy – where conditions for Doing
Business are difficult because of
bureaucratic red-tape, SME growth –
normally labour-intensive – tends to
be stifled and driven into informality.
5. There are feedback effects between
growth, poverty and informality – the
larger the informal sector the more
sluggish the rate of economic growth.

25. In part this is because informal sector
participants are low-technology, low-productivity
players
But also because they escape the tax
net, thereby limiting government
revenue and public spending
programmes targeting poverty
reduction.

26. This is important because it is often
claimed that informal sector
“development” is desirable because it
does create job and income-generating
opportunities.
That is so, but they are second-class
jobs and global evidence shows
informality and low productivity go
together, which by extension means
slower growth in per capita incomes.

28. In focusing on the MDGs policymakers
and especially donors and NGOs, risk
losing sight of the big picture.
No point in telling – forcing –
governments to increase poverty-reduction
spending, funded to varying
degrees by donors, and then when aid is
withdrawn leaving the country with
unsustainable social programmes.

29. Instead, governments must create the
fiscal space to fund future spending
programmes
This in turns means rapid economic
growth to increase the tax revenue
base
A focus on infrastructure investment,
as well as on training and skills
development

30. In Zimbabwe two difficult policy trade-offs
stand out:
1.Increased social spending targeting
poverty reduction, versus higher
investment spending to facilitate strong
growth, and
2.Rural development and small-scale
agricultural development, versus growth
of agribusiness, mining, manufacturing
and services.

31. The ten-year crisis has radically
changed this country’s economic
landscape.
Commercial agriculture which, along
with manufacturing, with which it is was
closely integrated, can no longer fulfill
the locomotive role.
Neither can manufacturing because of
the loss of commercial farming as the
bastion of its competitiveness.

32. 6000
5000
4000
3000
2000
1000
0
Agriculture
Manufacturing
1985 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007 2008

33. Mining – highly capital intensive,
accounting for under 4% of formal
employment – and
Services such as tourism and, eventually,
finance (both labour intensive)
Along with heavy infrastructural investment
– labour intensive construction –
Are likely to be the lead sectors driving
recovery.

34. Pro-poor growth implies targeting rural
communities where most of the poor
live, along with the informal sector and
low-paid workers in industry and
commerce.
Shortly after Independence in 1980 the
government set a target of reducing the
population of the communal areas to
325 000 families by 1990.

35. In fact, by that year, the number of
families had grown to over a million
which explains why the government
embarked on its land resettlement
policy.
That failed so that the problem of
rural overcrowding and poverty is still
there, but much more so than it was.

36. There is no quick fix
The government talks vaguely of land
audits and land commissions to
rationalize land ownership
But even if this were feasible – and
there are a number of political and
logistical road-blocks in the way
It would not solve the problem.

37. As economies develop so:
Agriculture’s share of GDP declines
as also does its share of formal
employment.
Other sectors must expand to take up
the slack both in terms of output (and
exports) and employment.

38. This means that rural depopulation
can work only when:
a)Jobs are created elsewhere in the
economy – industry and services – to
absorb those who leave the
communal areas, and
b)Where it is accompanied by rising
productivity in agriculture nationally to
provide the required food and cash-crop
exports.

39. Although donors, NGOs and
lenders like the World Bank
prioritize smallholder agriculture as
the road to poverty reduction, they
often overlook some unpalatable
truths.

40. Yes – the poor performance of
African agriculture is attributable to
natural resource and infrastructure
constraints but also to often
overlooked institutional
bottlenecks.
Effective property rights are crucial.
Yet few if any African countries
have a modern system of land
tenure in traditional areas.

41. Although there is plentiful land
available, farm productivity is poor
due to soil degradation, tropical
climatic factors and disease.
Only about a quarter of Africa’s
irrigation potential is actually under
irrigation.
Over the past 20 years, productivity in
African agriculture has declined some
7.5%

42. Because smallholder yields are low
and productivity poor, it is very difficult
to bring traditional agriculture into the
commercial world.
Yet increasingly agriculture needs to
be viewed not as an industry in its
own right, but as part of industry –
agribusiness or agro-industry.

43. Comparative figures help. The table
compares the share of agriculture in
African GDP (about a third) with much
smaller shares in Brazil and Thailand.
But in those two countries the share of
agribusiness in GDP is much higher,
so that in a small country – Thailand –
agribusiness is bigger than in Africa.

44. REGION SUB
SAHARAN
AFRICA
THAILAND BRAZIL
Agriculture’s
share of GDP
32% 11% 8%
Agribusiness
share of GDP
21% 43% 30%
Agribusiness
GDP
$67 billion $68 billion $236
billion

45. Today food products are as globally
sourced as are industrial products and it is
vital for firms, producers and countries to
become part of the supply chain.
A typical value chain consists of
independent producers, service providers
(transport, storage, banks, input suppliers)
exporters, importers, retailers, wholesalers
and buyers or consumers.

46. Agricultural supply chains today are
dominated by large supermarket
groups.
Worldwide 30 supermarket chains
control one third of grocery sales.
In Zimbabwe, where once there was a
good deal of participation in such chains
by commercial farms, this is much more
difficult to achieve with smallholders.

47. There is a whole host of problems:
Low productivity and poor, or variable,
qualities
Poor infrastructure
Inadequate and uncertain financing
Communications and information gaps
Contract enforcement difficulties – see
the example in the cotton sector in
Zimbabwe

48. State marketing bodies
Overvalued exchange rates
High inflation rates
Inadequate investment in agricultural
research
Strong government opposition to
genetically modified foods

49. Accordingly, the viability of a pro-poor
smallholder agriculture strategy is
problematic
Instead, governments need to promote
larger farms, bigger units, corporate
agriculture while also seeking to foster non-farm
rural activities
Experience in Zambia and Tanzania shows
how agricultural potential is held back by
traditional subsistence farming by small units

50. These comments apply also to
manufacturing where business
models have changed out of all
recognition in the last 30 years.
Very few African manufacturers today
can match the cost competitiveness
of Chinese and other Asian exporters.

51. The entry (in our case, re-entry) point
for low income countries is not for
labour-intensive clothing or footwear
manufacture so much as for task-manufacturing,
offshoring and, as in
agriculture, participation in
regional/global value chains.

52. My point is that these “new” models
may not be optimal from a narrow
poverty reduction viewpoint.
But if they are the only – or the best –
option, and
If they deliver growth in average
incomes, which will reduce poverty
than that will be the way to go.