Tony Hawkins

� 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

� 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).

1000

1200

1400

1600

1800

2000

2200

2400Z$ (1990)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

1975 1980 1985 1990 1995 2000 2005

800

900

1000

1100

1200

1300

1400

Employment (000)

0

1000

2000

3000

4000

5000

6000

7000

8000Z$ (1990)

� 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).

� 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%).

� 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.

� 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.

� 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.

� 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.

� 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.

� 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.

� 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.

� 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

� 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.

� 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.

� 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.

� 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.

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.

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.

� 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.

� 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.

� 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.

� 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

� 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.

� 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.

0

1000

2000

3000

4000

5000

6000

1985 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007 2008

Agriculture

Manufacturing

� 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.

� 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.

� 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.

� 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.

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.

� 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.

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

� 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.

� 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%

� 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.

� 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.

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

� 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.

� 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.

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

� State marketing bodies� Overvalued exchange rates� High inflation rates� Inadequate investment in agricultural

research� Strong government opposition to

genetically modified foods

� 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

� 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.

� 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.

� 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.