IDS 40th Anniversary: Electronic Round Table between the former DPhil students of Professor Michael Lipton

Final ReportOctober 11th 2006.

The former doctoral students held an electronic Round Table (e-RT) between May-August 2006 as one of the Round Tables held between alumni and friends to mark the 40th Anniversary of the IDS, University of Sussex. The e-RT was organised by Richard Longhurst (DP81) and moderated by Professor Lipton (hereafter ML). Twenty two former students were contacted (see list attached) with nineteen responding and eleven taking an active role.

The e-RT progressed through three rounds. The participants were first asked to take the IDS ‘generic’ RT questions 1 as a starting point with an emphasis on poverty reduction. As a result of this initial discussion, the second round produced six questions for discussion which were derived as follows: two proposed by participants, two proposed by ML, and two drawn from some areas most popularly discussed in other RTs. A seventh ‘any others’ question was also considered. This report summarises the discussion by each question.

First, what measures are needed to persuade able officials, scholars and other professionals to remain in SSA and to keep working on its poverty problems?

What are the most effective incentives for professionals to stay in place?

A better understanding is needed of what the developing country health professional wants, and whether this is affordable in terms of the initial training investment in relation to realized return, given four ‘types’ of personnel flight. These include i) flight from rural to urban stations; ii) the public to private sector often with an inefficiency-inducing ‘straddling’ within the health sector or into non-health sectors; iii) from poor to less poor or rich countries; and iv) from the health sector into other more profitable sectors. Research seems to have focused on ‘what doctors want’, yet the demands of other cadres might be even more significant for the resource shift.

The interaction of health professionals with decision-making politicians/civil servants may be a key issue. Are these people themselves fairly old? And (not quite the same issue) do they experience, in their families, the health burdens of the rich and elderly rather than those of the poor and young? Does this bias their decisions in allocating health resources?

1 What are the key issues that must be confronted in moving towards more sustainable patterns of human development towards 2015 and beyond? What are the likely shocks and events that may occur in the next 10-20 years? How can the likelihood of the event be anticipated? How can resilience be improved? What decisions should be taken now in anticipation of the events?How does development research re-invent itself to offer significantly greater support to those seeking just and sustainable development?

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These issues tie in with the question on retention of officials, scholars and other professionals remaining in SSA. Where scholars are concerned, there are at least two pre-conditions that could deter migration, a more amenable research environment and adequate research funding. It is not just salaries as SSA professional salaries are usually well above the Asian equivalents in PPP. Yet professional brain drain is far faster from SSA. It is essential to create a reasonably stable research environment, with funds for other things than professional salaries, if researchers are to produce useful results near home2. For both research freedom and funding, collaboration with foreign institutions is a likely help for local scholars. As for the other professionals, there will be instances in which professional as well as social and political freedom are factors, besides the lure of better terms and conditions of employment outside the country. Also, stability of funding matters: the curse of agricultural research in African national systems is that it’s ‘easy’ to cut during fiscal stress. Then the result of years of work is often lost.

One participant returned to the issue of financial incentives for professionals and the role of top up salaries paid by development organizations requiring both high caliber people and meet ‘diversity’ criteria. Others argued there was a problem with this approach, creating a two-tier system, with those public servants not on enhanced salaries under performing and compelling governments to spread the practice more widely creating a hugely increased fiscal burden, worsening inequality and resentment, and making it less attractive to work in the private sector. In Afghanistan, levels of remuneration of public servants is a huge issue. With salaries of public servants there is a clear discrimination between the two-tiers (returning Afghans get up to US $5,000 per month; those who stayed back get on average US $50 per month) which leads to reduced motivation and resentment. The returnees are younger and fluent in English, but still the difference in capacities between the two categories is not 10 times as reflected in average salaries. This is not fiscally sustainable and there are concerns about "human resource flight" once the funds run out. Returning Afghans not compelled to give up their foreign passports - only Ministers have to. Donors haven't helped, especially those like USAID which work through private contractors. These and other factors contribute to the 'Dutch disease' and so there is an overvalued exchange rate and a high-cost/low productivity economy, probably typical of a post-conflict country. Linking personnel flight to poverty reduction

There was a discussion as to whether personnel flight is in and of itself a hindrance to sustainable development and poverty reduction. Yet, even if it is, this can only be within particular sectors and/or countries rather than a universal phenomenon. But, if higher proportions of professionals, in all sectors and all developing countries, move from poor to rich countries, surely that hampers poverty reduction? In Kenya,

2 One participant recounted his experience trying to get what appeared to be relatively routine data (on the distribution of specializations in post-graduate medicine in order to assess correlation with national health care needs) in making a point that the research environment had not liberalized, only to be told it was “sensitive information”. Funding also proved difficult for this research.

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for instance, unemployment and underemployment of professionals is disturbing, underlying concerns about efficiency of training investment.

Professional structures and poverty reduction

There was another strand of the discussions on professionals: what was a poverty specialist: people are not sure what this means. Specific poverty focused programs are still second class citizens compared to programmes such as infrastructure, and even if infrastructure investments are often justified because they "alleviate poverty". If someone is serious about poverty alleviation research s/he does not get the attention or the support that is required, and this is one reason why serious poverty researchers in SSA are usually instrumentalized for justifying investment projects that serve a political agenda and then get frustrated and leave. Incentives are needed to have funding allocated to independent poverty research for "poverty specialists' and not just as an addendum.

However, the role of ‘poverty specialists’ is different from that of the role of ‘specific poverty-focused programs’. A programme aimed at more and better national agricultural research on main staples, or at getting family planning to rural areas, as examples, might in most circumstances cut poverty more than many programmes labeled “for the poor” - especially badly-targeted subsidized credit which has loomed very large in claimed ‘poverty programmes’. But that is a major reason why poverty specialists are needed: to compare the poverty-reducing effects, in a specific environment, of alternative policies, or ways of spending public money.

Second, what difference is made to poverty and development policy by medium term changes in the structure of the population? Big falls in the ‘dependency ratio’ – the ratio of (over 65s plus under-15s) to people working and saving age – are underway in much of Africa and poorer rural areas of Asia. This process is almost complete in advanced areas of developing Asia, where ageing means – now or soon – a rising dependency ratio.

The value of using the dependency ratio

It is not clear that the standard definition of the dependency ratio (DR) has ever done justice to the extent of the burden, with the likelihood that (analysis of) the impact of demographic structures on poverty and development policy may be compromised. For example, the extended African family system has always meant that anyone with an income cares for more than just the under 15 and 65-plus categories. Linked to this, public sector retrenchment has often happened abruptly (with deadline ahead of the next Bretton Woods mission), laying off more than 200,000 workers in the last 15 years, with people often totally unprepared for self-employment and too excited by the massive ‘golden handshake’ to think clearly of how to substitute it for the regular monthly salary. At best, such people fuel the downward spiral of real informal sector earnings. At worst, they join the rural peasantry after the money disappears through injudicious business and social investments. Most such people turn to the extended family, increasing the ‘effective’ dependency burden.

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But not all of age15-64 work and not all outside these age-groups depend. But a falling DR normally means a rise in the proportion of people supplied to the workforce and an offsetting fall in the proportion of people relying on others for income. This has to be an opportunity for mass poverty reduction, provided that demand for labour expands at least as fast as supply.

Linked to this is that changes to population are taking place along changes in the extended family structure. While aging increases the DR, migration lowers it. In Mali for example, rural household size varies from 10 to 30. But when young people migrate to towns, although they do send some money back, their life pattern changes and they become responsible for a smaller family size and therefore less dependency.  These two countervailing forces need to be considered in dependency analysis. Demographic transition and hence the falling DR normally (i) arrive later in rural areas, and for the poor in any area, (ii) are offset in rural areas by out-migration of young men (less so women, except in parts of Latin America). Timed effects on DRs by income-group, and hence on poverty, in different cases needs working out, using household surveys. We all know this in principle. But in practice this effect – and over, say, a 10-year horizon it can be huge – is largely ignored.

The effects of ageing

The effect of ageing on the physical capacities of a population (labour supply, morbidity patterns) is well recognized, but also amenable to policy, and to policy-induced behavioural change, e.g. in lifestyle. Another effect may be on ‘intelligence’. Medical literature shows the mature human brain functions differently from that at younger ages. Therefore ageing will alter the intellectual basis of a population. Changes can occur differently in the various dimensions of ‘intelligence’ and so it is not a simple story of a secular decline in functioning. It is also conditional partly on biological changes to the brain and partly on how the brain was used at working ages (some life course studies show this). Therefore the impact on intelligence in an ageing “well-fed knowledge economy” may be different to that in an ageing “undernourished labouring economy”. Longitudinal studies could test this – see question 3.

Similarly, emotional functioning may be altered in an ageing population. In a world of uncertainty, a population of 70 year olds may choose very differently to one of 20 years olds. A well known age-related difference is risk-taking (a big factor in higher mortality of young males), but broader economic judgement may be altered. Motivations for age-specific savings – and hence the pattern of incentives required to increase private saving – are another important issue as age-structure changes. The hard point to get over to politicians (and some economists) is that these changes are often big and can’t be ignored in policymaking.

However, we need to be specific to the ageing pattern at the stage of transition in which a country finds itself. Some developing countries (China) have reached, and some will reach in 5-15 years, a situation where the DR actually rises again as the proportion of over-65s grows. The purely arithmetical effects of these changes matter a lot for policy. In India (and probably other countries), the ageing workforce means that the proportion of workers who will not benefit from ‘school improvements more than 20 years ago’ is rising. This means the importance of adult education in maintaining workforce quality, relative to the importance of school education, is also

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rising, in some States of India quite dramatically. Education policy pays almost no attention to this change.

The other side of the matter is that child labour and peasant livelihoods mean that the under 15 and 65-plus are not all dependent. In SSA, for example, the HIV/AIDS scourge has generated child-headed households while grandparents also care for AIDS orphans. These realities suggest a need for a more nuanced definition – or at least interpretation – of the dependency ratio. Some of this can be achieved by looking at age-specific participation rates – their past levels and trends, and the factors likely to affect them.

Population structure and social protection

This is the century of social protection, linked to the changing demographics. Most programmes in operation were designed quite some time ago to tackle contingency risks and not systemic changes (economic crises, environmental shocks, HIV/AIDs pandemic) which are increasingly influencing people’s well-being, and which imply systemic insecurity of a type that is hard to cover by existing insurance structures. Therefore the protection scenario has deteriorated; less people have access to social services; in most poverty work social protection is missing and needs to be addressed. New ways of providing protection are needed, with new partnerships with whole range of organisations or else there will be social crises. There are links to demographic patterns, there is a fat bottom of the pyramid with no stabilisation until 2040. With inequality between DCs (older) and LDCs (younger), how to provide for LDCs populations. In Pakistan over 40% of the population is below 15 years of age, and they will soon enter the labour marker. SP has a role to play. SP programmes from the World Bank are largely excellent but do not much engage with the impact of changing age-structures on private and public provision - or even on changing the balance of demand among forms of SP.

Third, what differences can be made by time series data in general and panel studies in particular to qualitative and quantitative research and policy making for development and policy reduction, for example as regards understanding inter-generational transmission of poverty, or as regards combining quantitative and qualitative approaches to measuring poverty and the impact of policy on it? Are household panel studies an unmixed blessing for understanding poverty and development – or has their use perhaps been overdone and or over hyped?

Poverty reduction and panel studies

Panel studies for poverty would be a tremendous help as we need long term, consistent, independent research to really understand who is poor and what role do various programs play in poverty levels. Given the huge sums of money spent on so many other items, there should not be any cut in poverty research whatever its form (including panel data). The question is: how much should be spent on panel surveys, given funds available for (i) poverty research, and (ii) household surveys. For decades, panel surveys of households received a very small proportion of (i) or (ii). Since 1990, these proportions have gone up a lot: 100% is too much, and 0% too little, but the huge rise in the share of panels has costs. There is a lot that we need to

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know about causes, and cost-effective reducers of poverty that we will not find out from panels.

There is another worry. The panel selected initially is usually supposed to be a random (or a stratified random) sample of initial population. The longer the time during which the panel continues, the less typical does the panel become. For example, at all times later than t (0), a panel necessarily has heads-of-household that are older than the population at the time of the survey round. It is in principle possible to constantly add new households to the panel, so as to ‘correct’ for the various under-representations of growing segments of the population that develop over time. But this is expensive and is not often done. If it isn’t, the knowledge gained from panel data about what causes given households to move into or out of poverty is directly at the cost of reduced knowledge about what’s happening to (a random sample of) the currently poor. Worse, this is often overlooked, so that it is common to discuss trends in ‘uncorrected’ panel data as if they were trends in a sample population.

Panel data: measurement error and integration with other forms of data

There are two further points to make: i) measurement error is much more of a concern than with cross-section data and can be the main driver of results re. poverty transitions; and ii) the relative merits of panel vs. ‘pseudo-panel’ data using cross-sectional data3. On integrating qual/quant data in the context of use of panel surveys, there are a number of further points here. Putting aside definitional issues about what these terms mean, the following need to be taken into account on integration: i) comparability issues: are we talking about the same things – basket, cut-off, time-period (such as seasonality) and units of measure (need for conversion factors)?; ii) validity issues: there can be perceptual biases associated with self-reports (in life histories or household surveys) due to adaptation, memory issues, changes in expectations, mood/ affect etc. This can make the results less policy relevant; iii) representative ness: are we talking about different populations with different characteristics? iv) reliability issues: is the investigator the main driver of results? Less structure in the dialogue of life histories means this is more likely to be a serious problem4. For policy purposes this may need to be addressed – more standardisation, multiple coders?

Long term poverty research and ‘genetic endowment’

There is a view that poverty is mostly due to faulty genes, and drives a lot of racism, stereotyping and social exclusion of the poor. If so, then all poverty research is overdone and over-hyped. But even if one (wrongly) believes that poverty is mainly due to genetic endowment, it need not drive one towards a racist, stereotyping or exclusivist outcome, and can well do just the reverse. First 5, genetic origin of a phenomenon is neither necessary nor sufficient for it to be non-corrigible by policy: short-sightedness is 100% genetic, but can be corrected with appropriate reading glasses; many diseases are 100% (or almost) non-genetic but are incurable. Second,

3 See Deaton vs. Dercon on this4 There was an interesting seminar in Feb 2006, hosted by the Chronic Poverty Research Centre and ODI that dealt with integrating panel and life histories which addressed many of the above issues. It is on the CPRC and q-squared websites (www.q-squared.ca) .5 as Jay Gould pointed out

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one might believe that people with “unlucky” genetic endowments ought to be compensated (e.g. by receiving more education than others) – either because this is in some cases a more cost-effective or even GDP-efficient use of resources than is concentrating them on the already well-endowed, or because one has a moral imperative towards helping the needy or even towards equalizing potential where possible.

One might think panel-based intergenerational studies can estimate what part of poverty is genetic and what part is structural, but they have not done this because nearly all studies span only two generations. Also panel studies suffer the big weakness that they rarely include in the dataset variables that can be changed through public policy, and so studies are largely descriptive of the longitudinal transformations that occur in the tracked households6. However panels will improve in the same way that cross-sectional household datasets improved since LSMS. If we are to explain why some people advance and others don’t, better longitudinal data is needed. Leaving out the temporal dimension means leaving out the sense of the term “development” (which is intrinsically a progression through time).

However, that said, one can in principle “explain why some people advance and others don’t” from a one-shot random sample, plus careful, in-depth questions into the past history of households (or household heads). This is expensive and not 100% accurate, but it is not worse, in either respect, than a panel in all circumstances7.

Fourth, given the proposals for much larger aid flows to SSA (and given that SSA already gets most of the aid, while most of the poverty, and arguably the best prospects for curing it, are still in Asia) are we at risk of too much aid for SSA?

The quality of aid for it to be effective

The problem is not "too much" or "too little" but the quality of aid and its fit to the local realities. The lion's share of aid is from multilateral agencies in many white elephant projects (e.g. of many of IFAD's disappointing projects in East and West Africa). Some of the most disappointing projects are very tiny micro-elephants… white mice? IFAD’s efforts with on-farm micro-irrigation look splendid but spread very slowly at high cost, and therefore low ERR or per-dollar poverty impact.

Disbursement was also rated as a key issue, specifically: (i) how much of it comes through the government budget (in Afghanistan this is 30% approx.); and (ii) how can the government improve disbursement rate (40% last year) which is largely because of low government capacity. Donors not keen to give more aid if disbursements are low; and not keen to channel more aid through the treasury because

6 Although that is less expensive to remedy than is the non-typicality of the panel after t (0), and it also applies to many non-panel studies.7 Observation: uncorrected, the history approach yields a sample representative now, but less and less so as we go back in recorded memory; uncorrected, the panel approach yields a sample representative now, but less and less so as the panel moves forward in time. A bit like Laspeyres and Paasche. Or something.

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of limited capacity and weak fiduciary systems in place.

One view was to disagree that the problem is too much aid to Africa. We go to SSA with a lot of theory and expectations but we don’t try to match the theory with the realities from the ground. Research quality is often poor and very short term. We end up with a long list of negatives and a long shopping list. Projects fail and it is all blamed on "corruption" and local culture. Although culture is a huge factor, we don’t really understand why. Linked to this is to disagree with Sen's dismissal of the cultural factors. Aid should be reprioritized by a much greater focus on studies of poverty, culture and also history. We have lost sight of the fundamental role of historical research in explaining persistent poverty patterns.

On the other hand, while aid is never enough, SSA’s current share of it is too high, and Asia’s too low, to maximise the impact of aid in reducing poverty (not, of course, the only proper target of aid, let alone the improper targets of donors). But if we suppose i) SSA now gets the share of world aid that is optimal for reducing poverty, and ii) now double or triple aid to SSA by 2015, front-end-loading so the increase is even faster at first, as is proposed by the Africa Commission. Is 2006-2016 enough time to acquire the necessary knowledge to spend this extra cash properly? Is there enough simultaneous investment in information – e.g. basic farm data, which are dreadful – let alone in deeper understanding of socio-economic processes and cultures in these numerous countries? There has to be a serious worry about disasters in 2006-26 that will discredit aid, and SSA development, for decades. Yet NEPAD and some individual countries have gone far to identify poverty-reducing priorities and to put in place finance and overview mechanisms that could make a big difference.

Aid and disaster risk reduction

In our development agenda and development research, there has not been adequate focus on disaster risk reduction. Natural disasters, such as flood, cyclone and earthquake have tremendous impact on the life and livelihood of poor people. They are more vulnerable to such disasters. On the other hand, disasters also adversely affect development efforts and even increase the incidence of poverty. It is necessary to ensure that disaster risk reduction measures are integrated with development agenda. For example, houses for the poor - and of course, for others – should be built in a way they are resistant to various hazards in disaster prone areas. Livelihood generation projects should also focus on reducing vulnerability and the risk of disaster.

We also need to consider the demand side. One tends to assume that poor people are more likely than the well-off to choose (or to have no choice but to accept) houses – and occupations – with greater exposure to natural disasters. Yet most economic evidence suggests that the poor are more risk-averse than the well-off. Perhaps it is different for different sorts of risk of disaster. If the risk is disruption or loss of assets, rather than death or injury, might it be more cost-effective (a) to insure (maybe with subsidy) and compensate, rather than (b) to directly invest in reducing disaster risk or increasing resilience or (c) to finance overall rebuilding afterwards? Just as with crop insurance, so with some sorts of disaster in some sorts of polity: a “publicly subsidised insurance” option might raise GDP by encouraging private behaviour that accepted risk in order to raise expected return. One cannot apply this if

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the risk is death or serious injury: so probably some mixture of insurance-subsidy and precaution is best. It varies with quality of administration – what works in Gujarat does not work in New Orleans or Chad.

But is aid part of the problem?

When it comes to developing SSA, (aid) money is part of the problem, not the solution. States in many SSA countries are already big relative to the rest of the economies with little to show in terms of social service provision, but much in terms of graft, corruption and fights over distribution of riches. Rather than more money, SSA needs indigenous leadership to produce home-grown development agendas, and public sector reforms to increase government effectiveness. This comes back to incentives (see question 1).

But the problem here may be that not states doing too much (too much agricultural research, primary education and health care, roads, surely not), but states doing the wrong things, due to political-economy pressures in and on them. This is as much of a problem in Nepal, and in Bihar (an Indian province with over 90 million people), as in most countries of SSA. Indigenous leadership is important, and even more mass demand for and expectations of it, that drives. But it is not likely that much less aid, especially suddenly, fosters the necessary qualities. And this can perhaps be done in and with (not ‘for’) several SSA and other countries by more aid, carefully managed and not front-end-loaded on a set of fashionable nostrums. A nostrum is far worse and more fungible than most of the much-maligned projects.

Issues in Implementation of ODA

An additional point concerning significantly increasing ODA for activities undertaken primarily by the public sector is assuming that funds are allotted to the ‘right’ sectors, and a key issue relates to the operational capacity of the public sector to undertake vastly expanded activities. There are financial issues which concern putting in place mechanisms to monitor (increased) flows (audits, expenditure tracking, etc.). There are also more generic issues concerning the activities which public authorities are better (worse) able to do (it is likely to be easier to expand a vaccination program than an integrated rural development schemes (where successful interventions are more contextual and require more administrative discretion). In Afghanistan too much aid seems to go for governance, human rights, capacity building etc. and far less for hard-core, tangible things like infrastructure, irrigation, agriculture, etc. This is a reality which is recognised by a large number of Afghans and seems be a cause for disenchantment and frustration with the slow pace of development. An oft-repeated question is: "where has all the aid money gone?"

This was agreed. If the SSA aid explosion (or some of it) will happen, we soon need a much more rigorous re-run of the old “absorptive capacity” debates. Radelet et al. claim to have shown that, even in SSA countries that score badly on “governance” indicators, quick-disbursing aid for key sectors can have very high GDP and poverty-reducing returns, especially in post-conflict situations. This work influenced the Africa Commission report - perhaps too much so. It’s just one paper, peer-reviewed

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but not yet publicly discussed, very surprising and contrary to previous work (because it implies redirecting aid to poor performers), and – perhaps inevitably - based on econometrics with a big package of assumptions.

This was further emphasised by some experiences from Bangladesh. Is it lack of policy or implementation (some times impeded by people like us professionals as the example of Indian doctors in Question 1 has shown) which is the real culprit in poverty eradication? While weights cannot be assigned, probably bad or lack of implementation is more to be blamed. This may be called governance or something similar. There are many policies in Bangladesh which sound good to read but are very badly implemented or not at all.

Three examples can be cited. First, everybody understands the importance of energy in development. There is a Power Sector Master Plan approved by the Government. Yet, during the last 5 years there had been little or no addition to generation capacity meaning in effect that a substantial part of the country remains under darkness every day. Farmers have been deprived of power and as a result there had been near revolutionary situation in some parts of the country this summer. Why has this happened? Consider that Bangladesh has for the first time crossed the 10 billion dollars export earnings (was only $300 million in 1971/72). Could not the policy makers apportion some money out of it for power generation, however small, from this money? There are allegations that the disagreement regarding kickbacks had been the root of the problem. It may be true or not. But the country and its growth prospects suffer. Second, there is the PRSP. It has a clean bill from World Bank. But there is little indication of its implementation in the sense that the strategies have to be transformed into programmes for intervention (investment, policies, facilitation) which are lacking. Third, the Telecom Regulatory Authority has long ago recommended that VOIP (Voice over Internet Protocol) be made legal which would immediately lower telephone and internet charges. But it has not been done. Again some people (high and mighty) are making money by doing illegal VOIP but the government gets no revenue.

Corruption may indeed be a contributory cause. (It certainly is for another clear cause of poverty in South Asia, irrigation misuse and under-performance.)  But power and VOIP raise two other issues: First, can one come up with evidence that poverty reduction would be faster, if Government shifted spending to power or VOIP via lower spending for (or higher taxes on) those activities/groups most likely to be squeezed?8 Second, why is there not enough public "voice" - parliament, media, NGOs etc - to improve power provision, to spread VOIP gains to the poor, and especially to hold the Government to implementing PRSP?

There are many such examples. Not all of them directly affect poverty, but they affect growth which ultimately affects poverty. Of course a section of people gets richer this way. So, we are back to the old "political economy" issue of whose interest is served by such lack of implementation or bad implementation.

8 When asked to support more and better computers and software in Soweto, Bill Gates replied (in effect): "What these children need, first, are proper schools, teachers, textbooks, clinics."

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Fifth, with the Comprehensive African Agricultural Development Programme (CAADP) now up and running, how can the role of irrigation in reducing poverty be got right?

West African experience on irrigation projects (Guinea and Mali) is that they exacerbated poverty and made the rich richer. First, the main irrigated crop (rice) was not very economical to produce. Second, the bulk of poverty is in the areas with subsistence rain fed food production and not in areas with irrigated rice9. It is agreed that the risk of using irrigation to reduce poverty is terrible. But hardly any country or region has achieved, say, 5% growth of staples output per year for 7-10 years without substantial irrigation. With half or more of the population dependent on income from staples production, it is hard to see how anything anywhere near the MDGs for poverty can be achieved by 2030, let alone 2015, without breakthroughs in agriculture that are led by appropriate water control.

The problem it is that, having largely neglected this for fifty years – barely 4% of SSA is irrigated, below 1% if we exclude ‘not really SSA’ (S Africa, Sudan and Madagascar) – SSA and its donors are now attempting “fifty years’ development in five” with little knowledge, great hopes, and huge risks of waste or worse. The problem for pro-poor development thinkers is how do we get irrigation and aid in SSA done better, being absolutely honest about the risks and preconditions, but also not pretending one can get rapid poverty reduction without a big expansion?

A crucial issue is how SSA can learn from Asia failures, as well as Asia successes, for example in irrigation design, incentives, overview and management; Asia has lots of examples of both success and failure. SSA under NEPAD/CAADP is just starting to finance an (overdue) expansion of irrigation. Probably this is necessary for most SSA countries to achieve rapid farm growth, which in turn is necessary for widespread, rapid poverty reduction.

Sixth, what is the implication of the rising economic power of the BRIC nations (Brazil, Russia, China, India) for development in African countries ?

BRIC and social protection

Generally, BRIC countries have huge transfer incomes that can be used/are being used for social protection10. Brazil has the largest budgets for transferring incomes in the flavvelas; in China, Ministry of Civil Affairs is providing top up income for 22m residents and although this is a small proportion of the urban poor – it is still 22m.! The SP group at the World Bank has data for standardised SP expenditure as share of public expenditure and of GDP by country. India’s is very low even when State (province) expenditures are brought in11. Russia, despite collapsed health systems, is not all that low. China’s is quite low – e.g. health provision in rural areas is now cost-recovery, though Premier Wen is committed to restoring free or 9 Currently a $100 million project is being planned for Office du Niger in Mali (MCC) when the expected number of the direct beneficiaries are less than 10,000. Again, this is a very political project which will most likely fail and add to the long list of failed irrigated projects.10 although to qualify that statement, the share of social protection by Central and State governments in Indian GDP remains very low. In Russia health care systems have collapsed in some places, transfer incomes are true in Brazil.11 The national employment guarantee will raise these sums, but not all that much

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near-free provision. Have to set up all the administrative structures, ‘tagging’ etc. In India, transfers are low, but there is the scaling up of the Maharashtra Employment Scheme to national level, still will be an interesting cushion to put in workfare at a national level. The question to ask is: fiscally, is it do-able?

Globally, the BRIC (Brazil, Russia, India, China) countries will have a negative impact on LDCs as they will draw any resources and make them too aid dependent, some may benefit, others may not. This can be beneficial if there is economic integration (e.g. SAARC, ASEAN). On the other hand BRIC can be a huge positive factor if they see it in their national interests to provide technical support to low-income countries especially in SSA. The financial costs should be largely or wholly borne by rich developed countries, in view of remaining mass poverty within BRIC. But one or other members of BRIC have substantial surpluses of competent persons in areas that, at the BRIC stages of development, are actually contracting but that are seriously understaffed and/or mis-staffed/misdirected/starved in many low-income countries, especially SSA. Examples are: research into primary food staples; collection, processing and policy use of reliable smallholder food production statistics; irrigation management. It’s a much more cost-effective use of UK aid to ‘buy’ an Indian or Chinese specialist in any of these disciplines, adaptively retrain, and pay her for work in SSA, than to send expensive UK personnel or even more expensive UNDP/World Bank staff.

India

In Maharashtra there is a drought at the moment. There are high fiscal pressures in India, but look to India for a social protection model based on productive employment, generation of infrastructure. Maharashtra’s Employment Guarantee Scheme started as a model, with strong poverty impact estimated by Dev, Ravallion and others. But most of the experts think it got into a dreadful mess, and ceased to provide much SP, about ten years ago. Supreme Court imposed a minimum wage, cash ran out, and the guarantee ceased to be a guarantee.

In recent times, a significant number of farmers have committed suicide in some parts of India, particularly, Maharashtra and Andhra Pradesh. This phenomenon seems to be due to their inability to repay debt on account of failure of crops. This issue needs study and research in the context of our development agenda, because it could be an early warning for acute distress in the agriculture sector.

There is also direct experience of this tragic situation in Andhra. It may not be new, or worse than before, but it is certainly noticed more. It is often wrongly blamed on technical change12. Why does farm or debt failure cause many suicides in some places, but few or none in others? Weaker initial position (or heavier obligations) among farmers? Less (or less reliable/effective) “social capital”? Less access to emergency loans? Less chance to defer payment after illness or harvest failure? Less social insurance or safety-nets of various sorts (are there farmer suicides in Kerala)? Greater social stigma attaching to debt-default? Fewer ways to save one’s land, or fewer alternatives when the land is lost? Or just greater risk? Are suicides an early

12 E.g. a British anti-transgenics NGO stigmatised transgenic cotton in Andhra as “seeds of suicide”, yet the widespread reports of suicides preceded transgenic cotton: it was conventional cotton varieties that had failed.

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warning, or whether they indicate that distress has long started and that one or more of the above factors needs attending to.

Most funds go into development expenditures but little into recurrent expenditures. For example there is a huge social action programme in Pakistan with $8b. allocated over 5 years for areas such as education, health, water and sanitation, but this allocation proved a millstone as there was a problem of recurrent expenditure – contractors were happy, but it was a bricks and mortar only approach.

China

China is perhaps a little better e.g. where there is married development and recurrent expenditure, good policy coherence (if raise productivity, there is less employment). They have backed TVE – Townships and Village Enterprises – combined agriculture with absorbing excess labour. But China has 150m surplus labour and given the numbers it is a major example of policy coherence. China needs to generate 24m new jobs a year but is only generating 10m, therefore needs to concentrate on economic development as no democratic safety valve (unlike India).13

TVEs (now rolled up into other programmes) initially, in the 1980s, were pro-poor. But increasingly policy has been concentrated on enterprises to support trade and on drawing in private foreign investment, with the decision taken to do this by giving advantages such as EPZs (Special economic Zones) to the better-off coastal provinces. This has done absolute, not just relative, harm to some of the interior areas and there is a ‘crescent’ of NW-Centre-SW provinces with much higher poverty rates than elsewhere, slower poverty decline (though still good by most standards) due to both slower growth and weaker conversion from growth to poverty reduction. Moreover these States heavily over-represent non-Han ethnic and linguistic minorities and low-education groups, so their migration rates are lower than elsewhere. The hukou system (which the Centre wants to phase out) means that there are at least 100 million urban workers and families who have rural registration and are thus not able to access health and education, or any social services, in the towns and also have far less job security.

Russia

Russia is an outlier, the state has abdicated from social protection. Look and learn from the other three countries in terms of reaching the vulnerable with large scale programmes.

BRIC and AfricaAfrica needs a much better network of contacts with BRIC. The post colonial

patterns of trade with Europe should and will change. This process needs to be pushed along by donors who may well be constrained by their constituencies. OECD aid can be very cost-effectively used to pay for surplus Asian agro-experts (for example), of

13 ML just back from a first-ever visit to China, and like everyone else bowled over with their very fine, long-run overall growth and anti-poverty performance. But the latter has slowed down (while growth has if anything speeded up), and I don’t think most local economists would give high marks for policy coherence, at least as regards reducing the huge inequalities that have emerged, especially among regions.

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many sorts, to be retrained (if necessary) and provide hands-on advice for SSA countries that want and need it.

Finally a key issue raised was where it will be in the geo-political interests of the BRIC countries to forge closer economic ties with SSA which go beyond primarily resource extraction. This goes beyond technical support to FDI, trade, etc.

Seventh, any other questions (and answers) you would like to propose?

A plea for better macro economic policy

There needs to be better macro economic policy, better policy coherence at the policy level, and better integration between meso and the micro. There is some common ground between the old Washington Consensus on “better macroeconomic policy” and a common sense pro-poor agenda. Big deficits are bad in large part because they accelerate inflation, and that hurts the poor most. Heavy protection and forex undervaluation keeps consumption expensive and it’s the poor who lose most, because they have the highest propensity to consume. State subsidies and indirect taxes are generally skewed to supporting the rich groups who control and interlock with the State. The fallacy is to think that sharply correcting this – eliminating deficits, subsidies, forex under-valuations etc – will necessarily be pro-poor. Given the balance of power, the powerful can retain their share of benefits by other means.

Policy sequencing is what people get wrong. Africa is forced to listen to Washington directives plus the other actors involved. Need a broader based macro policy, not a fait accompli, an evenly balanced policy, not so coercive. The hard bitter pills of the past have not delivered the right sort of situation, has skewed distributions to dysfunctional levels. The oddity is that liberalisation, in a labour-surplus and capital-scarce economy, ought on standard Heckscher-Ohlin grounds to be good for income distribution. That has not been the case usually, but why?14, this cannot drive investment policy properly. For example if the policy decreases wages then there is no aggregate demand, there is the inefficiency of inequality, poverty, indecent work, economically dysfunctional for the macro economy. On the other hand this may be the case up to a point. Kerala is the only State in India that enforces above-market minimum wages and makes it very hard to dismiss workers. Kerala also has three times the time-rate of unemployment of the rest of India (these NSS data are rather good). The two facts are related.

WC policies have led to wages, jobs and incomes all falling, domestic market is driven out. In Africa aggregate demand is very low. One of the big mistakes in many SSA countries is excess concentration on a tiny export sector, and neglect of what the State needs to do positively – much more enabling than stopping – to make internal trade and exchange simpler. Facing this are big fluctuations in prices e.g. copper, so badly need balanced macro economic policy. We need to invent a new theory for macro economic policy (e.g. the Goldilocks story, one that is not too hot and not too cold). There is a big disparate set of opinions at the World Bank and we need much more heterodox macro policy, ideology to be driven out, need to allow for all issues of aggregate demand, and a better understanding of multiple equilibria. We need more ‘horses for courses’

14 Adrian Wood’s work gives part of the answer but far from all

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Developing countries do not espouse the most appropriate health system

There is a concern on the failure of developing country health systems to espouse the more cost-effective, primary health care approach to delivery (and financing, implicitly), instead of the prevalent curative/hospital/urban system. Considered widely, this concern ties in with questions 1 (personnel flight) and 4 (optimal ODA) above. This failure to shift resources has persisted since Alma Ata (1978), or more recently, the World Bank’s Investing in Health (1993) and Better Health in Africa (1994), as well as various individual country commitments to doing so. A common explanation is the lack of political will. However, could a lack of professional will – among health care professionals – be an even greater impediment?

It is agreed this is an issue well known in India. Doctors’ organizations agitate for larger shares of public health spending on teaching hospitals and high-quality medicine. They also impede and oppose the use of para-medical staff, including for giving contraceptive advice or devices – especially but not only IUD insertions.We should put ourselves in the doctors’ place, if we want to change their behaviour. Some are protecting their privileges. However, some genuinely fear side-effects if para-medicals, or even local clinics with doctors, try to substitute for activities best done by referrals and/or higher-tech medicine. Even a few validated reports of such side-effects can drive people away from modern medicine, to quacks.

Use of estimates of the effect, on life expectancy and DALYs, of alternative allocations of health resources can change attitudes, towards primary and preventive care and parameds, of doctors and professional organizations with genuine concerns. This is especially true if affordable precautions are taken to reduce risks of error when parameds/clinics undertake work. That will isolate and expose doctors who act only to protect privileges, and make it easier for governments – if they want to do so – to get medical resources to the neediest.

There is a separate issue of managing the health transition. Successful developing countries (i.e. those really developing) experience a shift of health burdens from diseases of poverty and childhood to diseases of lifestyle and old age. This happens even in stagnant economies, in the late stages of demographic transition, with a ‘double burden’ of health requirements. Voices for expanding the treatment of lifestyle diseases, such as CHD and diabetes, are usually powerful and concentrated; voices for treating dysentery and malaria, as ever, are weak and scattered.

Assets are ignored in favour of income when assessing poverty

Poverty or rather chronic poverty is essentially a situation of lack of assets and not just lack of incomes. Michael Sherraden’s contribution in this regard in his book Assets and the Poor (1990) is seminal. Unfortunately focusing on income leads to the dead-end of income support and income generation projects whereas a focus on assets pushes towards asset-building for the poor which is more important.15 The reason that most income generation projects fail has a lot to do with this conceptual error. Neoclassical economics is seriously at fault since assets are just an integral away from

15 Accountants would be amazed to find out that in development projects we just look at the income statement but there is no balance sheet!

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income. Reality is quite different. It is difficult to accumulate enough income to turn it into an asset. The other way around is also not always easy, i.e. moving assets to income – it depends on markets etc. Some assets of the poor are often hard to turn into income, e.g. remotely located land or land without title. Also De Sothos’s mystery of capital is very relevant here and Sen’s capability framework is very much about asset building and not just changes in income/utilities.

This is agreed. Assets affect poverty, partly because they can prevent it (or can stop transient poverty from becoming chronic) by being liquidated, partly because of their expected yield. The value of an asset is not simply equal to the expected value/present value of future income streams. The value depends also on the reliability or predictability of that yield, the liquidity of the asset, and whether the asset is readily transferable or heritable among persons. Assets comprising so-called social capital score very badly on all these, and even "human capital" assets are not heritable and often not transferable. Even for standard physical assets, including land, the poor can lose out either because they suffer market disadvantages compared to the non-poor, or because they have a less "satisfactory" asset-mix.

But consumption per equivalised adult remains the best single measure (if one wants a single measure) in terms of which to set a poverty line, or assess the depth or severity of poverty. Assetless people can be consumption-rich and possessors of substantial but illiquid assets can be consumption-poor. Asset size and structure, though, give lots of information about poverty risk and security. Also, more - or better structured - assets can, in some circumstances, achieve more reduction of consumption poverty (at a given cost) than more income from employment.

Importance of level of inequality and their spatial dimension

One issue on poverty reduction in SSA relates to the very high levels of inequality in the continent (which are either the same or slightly higher than Latin America) and the spatial dimension of inequality. Are there success stories of inequality reduction, growth promotion and poverty reduction to replicate?

In response to this, first, part of the problem is that rural-urban inequality, and the political economy underlying urban bias, remain - as they were in the 1970s – much more extreme in most of SSA than in other developing areas. Reduced price bias against agriculture has been offset by increased public-expenditure bias against rural people. Second, some parts of Eastern and Southern Africa have land Ginis, and income-per-head Ginis, reminiscent of Latin America. However, Western and Central African land and income-per-head Ginis, while scarcer and less reliable, are closer to South Asian levels than to Latin America. De Janvry has shown that extreme land inequality in Latin America – as a cause of overall high income-per-person Ginis - persists long after the share of workforce in agriculture falls below 30%. This is true everywhere, partly for reasons in Barrington Moore’s book. South Africa in particular will not substantially reduce inequality – higher now, though less racial, than at the end of the apartheid era! – without genuine land reform; the mass of the poor are rural, and land policy has been diverted towards creating middle/big African farmers.

October 11th 2006.

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Students supervised by Professor Michael Lipton(Date corresponds to award of degree)

Information as of 17 August 2006

Year Family name First name Email contact1970 KAMARAS Ioannis1975 STARK Oded ostark@uni-bonn.de1976 AFFAN Khalid affank2000@yahoo.com1977 GREELEY Martin m.greeley@ids.ac.uk1980 AHMAD Ehtisham-Uddin eahmad@imf.org1980 ASADUZZAMAN Mohammed asad@sdnbd.org1981 LONGHURST Richard r.longhurst@ids.ac.uk1982 KHAN Azfar khan@ilo.org1982 MOORE Mick m.p.moore@ids.ac.uk1986 JAZAYERI Ahmad Ahmad.jazayeri@fsa-

international.com1988 MAHMOOD Moazam mahmood@ilo.org1990 DEMPSEY Gerard1990 TAAL Housainou Housainou.taal@wfp.org1994 MISHRA Pramod pkmgsdma@yahoo.com

Pkmishra1@rediffmail.com1997 EVANS Alison a.evans@odi.org.uk1997 BARTSCH Ulrich ubartsch@imf.org1998 ZAMAN Hassan hzaman@worldbank.org1999 SINHA Saurabh Saurabhsinha04@yahoo.com1999 SHAFFER Paul P.Shaffer@utoronto.ca2001 MECHARLA Prasada Rao mecharlapr@yahoo.com2004 YAQUB Shaheen Shahin.yaqub@undp.org2005 CRAVIOLATTI Paolo Pcrv2005@yahoo.co.uk2005 NGO Thi Minh tngo@wisc.edu 2006 NYANJOM Eric Othieno_n@yahoo.co.uk

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