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Whose Poverty? Making Poverty Mapping and Poverty Monitoring Participatory

Li XiaoyunCollege of Humanities and Development, China Agricultural University

Introduction

In its report Poverty Trends and Voices of the Poor, the World Bank 2001 defines poverty as a multidimensional phenomenon, encompassing inability to satisfy basic needs, lack of control over resources, lack of education and skills, poor health, malnutrition, lack of shelter, poor access to water and sanitation, vulnerability to shocks, violence and crime, lack of political freedom and voice’ (p3). When confronted with such an omnibus definition, the potential heuristic power relating to the concept of poverty is locked behind intuitive processes. The effort needed to bridge the gap that remains between the concept as reflected in ‘the way that development agencies measure poverty’ and the reality of ‘how poor people experience and understand their poverty’, is not trivial. This paper is a contribution to this task.

Early in 2001, the Beijing office of the Asian Development Bank, in partnership with China State Council’s Leading Group Office for Poverty (LGOP), set about identifying a means by which the reality of poverty at the grass-roots, especially chronic hard-core poverty in village China, could be measured, monitored and addressed (3). This initiative, that has been dubbed CPAP, for County-administered Poverty Alleviation Planning (see Asian Development Bank project TA3610), involved a research process that not only identified a theoretical basis for a more participatory approach to poverty reduction planning in China, but also incorporated some fundamental village-level research to test a range of poverty indicators that could be used for poverty mapping, poverty reduction priority setting, and participatory monitoring of changes in the incidence of poverty (4). This paper reports on the results of these efforts in the belief that the findings are of general interest and readily replicable, cross-cultural and institutional differences between poor communities notwithstanding. The strategies involved are participatory, yet they are also objective and quantitative, leading to the design and calculation of a participatory poverty index. Moreover, the indicators of poverty, which have been identified by the poor, are also of a sort that facilitates an understanding of poverty in ways that are practical, relatively unequivocal in meaning, comparable across individuals, households, or communities, and easily monitored at the local level.

Background Trends in the Incidence of Poverty in Rural China

Whether one uses official Chinese statistics or World Bank measures, the decline in the incidence of poverty in China since 1980 is one of the great achievements in modern development. At the dawn of the opening of China to the harsh winds of global trade and international competition in 1978, the head-count index of persons below the poverty line showed that at least 250 million of China’s citizens were living below the local income-poverty line of just 60 cents per person per day. By the start of the new millennium in 2000, this number had been reduced to less than 50 million. If one applies the World Bank standard of $1 per person per day, the number of rural poor rises to around100 million, but even this figure records a substantial fall in both the relative and the absolute number of poor people in China (5).


Substantial gains in poverty reduction notwithstanding, official data on poverty trends in China since the mid 1990s also show that progress in reducing village poverty has not kept pace with growth in the rest of the economy, with the chronic rural poor failing to benefit from continued stellar growth rates in the macro-economy. The data strongly supports the conclusion that the poorest households in rural China are being increasingly marginalised. Progress in reducing the incidence of poverty in rural China appears to have stalled, possibly even reversed, since just before the turn of the century. In the latter years of the 1990s, for example, gross domestic product (GDP) increased at twice the pace of household income. This means that it is groups other than households that are garnering the lion’s share of the benefits of recent economic growth. Similarly in the rural sector, while agriculture’s contribution to GDP declined from 23% to 12% in the fifteen years since 1985, at the start of 2000, seventy percent of the rural labour force still found its primary employment in agriculture. The failure of the rural sector to realise more vital growth is reflected in the fact that during the same period, rural off-farm employment grew by less than five percent while the numbers employed in agriculture fell by ten percent. As rural unemployment increased, so did the pressures and incentives for rural people to migrate to urban areas in search of work and more secure livelihoods, making the challenge of labour mobility a key improved livelihood strategy for poor households (6).

The reasons for the slowing in the rate of rural poverty reduction in China since the late 1990s can be debated, but the consensus (7) appears to be that three main factors are responsible:(i) ineffective poverty targeting, reflected in the rising proportion of public sector sourced poverty reduction resources that do not reach the poor; (ii) perverse fiscal policies that have led to taxation systems in which the poorest 20% of rural households are paying 50% of taxes collected in rural areas; and (iii) income inequality in the rural areas that has been estimated by the World Bank to have increased by 23% in the seven years to 1995. The CPAP research project done to test participatory approaches to poverty reduction planning in rural China, does not contradict these findings. The research did, however, add insights into how participatory strategies in poverty reduction planning can help redress the forces that threaten to accelerate the slide of poor villages in China into chronic hard-core poverty (8). The pilot studies done to test components of CPAP appear to show that the top-down nature of extant poverty mapping and poverty reduction planning does contributed significantly to the neglect of interventions that are directly relevant to poverty alleviation at village level. The top down approach has also aided the leakage of resources meant to have benefited poor villages. CPAP addresses these problems by significantly improving poverty targeting on the one hand; and enabling poverty interventions to be designed in ways that are of immediate benefit to poor households in poor villages.

A Participatory Approach to Poverty Mapping, Measurement and Monitoring

The CPAP approach to participatory poverty analysis and poverty reduction planning required the design and testing of a village-friendly set of poverty indicators. However, before one can test the general relevance and meaningfulness of alternative indicators to the poor in villages across China, one has first to allow poor villagers the opportunity to offer their insights.

Based on their daily familiarity with poverty, the poor in China’s chronically poor rural areas are the true experts on what it means to be poor. More importantly, however, the rural poor are well versed on the constraints that prevent them from escaping from their poverty and the opportunities that they would like to take up as investments in their own betterment if they had the opportunity. Consequently, they are also the best source of information on key


areas of assistance they would like to have to help them escape poverty, be this assistance from the public sector, non-government organisations or the private sector. However, in approaching the poor to ask them their views on how best to measure or observe and monitor their poverty, the CPAP field trials showed that it is useful to illustrate what it is that is being asked. To this end, the CPAP research program reviewed the poverty literature to select-out poverty indicators reported there for the purposes of village poverty mapping, poor village rank ordering, and characteristics of poverty as manifest at household level. The process followed, which is unlikely to be comprehensive, identified 91 separate indicators, summarised in Table 1. For the purposes of this paper, these 91 indicators have been classified into nine distinct types of poverty, linked to the measure relevant to each indicator and the primary source of the data on each indicator.

Table 1: Potential Poverty Indicators Drawn from the Literature on Poverty in China

Type of Poverty Indicator Measure Main Source1. Environmental Natural disasters Frequency Village officials

Type Village officialsNumber of people affected Village officials

Vulnerability to misadventure IsolationVillagersPollution Air pollution Village officials

Water quality Village officialsSoil contamination Village officials

Isolation Time to access assistance VillagersSafety and security Incidence of petty crime Village officials

Feelings of uncertainty Villagers2. Gender Women leaders % Female heads of households Villagers

% of officials who are female Village officialsDiscrimination Female wages as % male wages Village women

Girl in school as % males in school Village teacher

Women’s work constraints Village women3. Human Skills base % primary school graduates Village teacher Resource Primary school participation rate Village teachers

Secondary school participation rate Village teachers

School participation rate Village teachers% households unable to pay fees Villagers

Unemployment Days seeking work/month VillagersWage labour Number of days worked/month VillagersHealth status % children immunised Health workers

% household that is able-bodied VillagersWomen’s morbidity rate VillagersChildren’s morbidity rate VillagersNumber of disabled Health workersNutritional status of females Health workersNutritional status of males Health workersInfant mortality Health workersMorbidity rates Health workers% of cash flow spent on health Villagers% of household that is HIV+ve Health workers

4. Infrastructure Market access Time to nearest market Village officials


Availability of all-weather road VillagersEnergy availability Rural electrification VillagersInformation availability Information sources Villagers

Newspapers VillagersTelephones Village officialsRadio VillagersTV Villagers

Community facilities Access to a health/birthing centre Health workersCommunity library VillagersCommunity sports-ground Villagers

Access to potable water Time/distance to source VillagersAccess to sanitation Number of latrines Villagers

5. Institutional Education Distance to School VillagersLiteracy rate VillagersSchool attendance Villagers

Health facility Number of days available Health workerFinance Sources of finance Villagers

Savings facilities VillagersPoverty transfers per household Village officialsPoverty loans per household Villagers

6. Livelihood Subsistence production Number of months of deprivation VillagersNumber of crops per year VillagersCrop yield per hectare VillagersAverage grain output/person/year

VillagersArea of arable land per household Villagers

Market activity Cash-needs/Cash-flow availability VillagersAverage cash receipts/person/year

Villagers% of production marketed VillagersValue of remittances received Villagers

Self-employment Number of functioning enterprises VillagersNumber of employees VillagersValue of household production VillagersValue of paid employment Villagers

Consumption standards % income spent on food VillagersCapacity to save Villagers

Wealth creation Quality of housing VillagersTotal household debt VillagersDebt owed to government VillagersDebt owed to family and friends VillagersCommercial debt outstanding VillagersHousehold assets VillagersNumber of functioning enterprises VillagersArea of land owned VillagersArea of land rented Villagers

7. Natural Type of resource % area that is arable Village officials Resource % of area that is hilly Village officials

Area lost to soil erosion annually Village officialsMonths of water stress Village officialsEmployment in resource mining Village officialsValue of resource sales Village officials

8. Political Participation Village governance structure Villagers


Sources of local government funds Village officials

Human rights Accountability perceptions VillagersIncidence of local corruption Villagers

Discrimination % of ethnic minority households VillagersLegal constraints to mobility Village officialsRegistration requirements Village officials

9. Social Capital Community Networks Number of active community groups Village officials

Number of volunteer activities VillagersSources of emergency assistance Village officials

Due process Number of legal procedures begun Village officials

The indicators shown in Table 1 provided the CPAP team with a wealth of examples of different indicators that researchers have used to measure and monitor the incidence of poverty. Only eight of these indicators, however, proved really meaningful to the poor villagers engaged in the CPAP trials. These eight indicators, hereafter referred to as the participatory poverty indicators because they are the results of extensive consultations with poor villagers, are highlighted in bold script in Table 1. It is important to note that the eight participatory poverty indicators that villagers consistently chose to describe their poverty cover only three of the nine types of poverty shown in Table 1. For convenience, the eight participatory poverty indicators and the three types of poverty they refer to are summarised in Table 2.

Table 2: Eight Participatory Poverty Indicators Covering Three Types of Poverty

Type of Poverty Participatory Poverty Indicator Key sourceI. Human Resource Poverty

Skills base 1. School participation rate Villagers & teachersHealth status 2. Women’s morbidity rate Villagers & health workers

II. Infrastructure PovertyMarket access 3. Availability of all-weather road VillagersEnergy availability 4. Rural electrification VillagersPotable water availability 5. Time/distance to source Villagers

III. Livelihood PovertySubsistence production 6. Average grain output/person/year VillagersMarket activity 7. Average cash receipts/person/year VillagersWealth creation 8. Quality of housing Villagers

The significance of these three types of poverty and eight associated indicators, is that it is this combination of indicators that hundreds of poor villagers consistently chose to best describe how poverty is experienced by poor households in village China, when asked to identify how poverty is manifest in their daily lives. This is not to say that villagers consulted as part of the CPAP field tests and trials did not identify other indicators; they did. However, there is very real significance to the fact that it is these three types of poverty and these eight indicators of these three types of poverty that have been constants in responses received from poor villagers, officials from poor villages, and county officials responsible for the administration of publicly funded poverty reduction policies in poor villages. It is this subset of participatory poverty indictors that forms the basis of CPAP poverty analysis and the construction of a participatory poverty index (PPI).


When the first trials of CPAP were undertaken in Fengning County, Hebei Province, a series of 11 group meetings were held during which poor villagers, plus village, township and county officials were consulted on their views on how best to measure and monitor poverty, and how best to address the problems that give rise to their poverty. Fengning County was chosen as the key site for the CPAP trials because this county was judged by the LGOP as not only poor by national standards, but also subject to environmental fragility. It had recently been visited by members of the State Council as a key poor working county severely effect by drought for the past several years. All nine of the group meetings were held in separate villages reputation for being among the poorest in the county.

In each of the nine villages, open meetings were held with all villagers invited. The smallest of these meetings has 20 villagers in attendance, not including officials. At times the meetings resembled a social gathering as individuals shared anecdotes and animatedly discussed and argued the point they were trying to make. A single meeting could easily extend through the whole morning or the afternoon, which for some participants meant it was a moveable feast as they came and went in response to the needs of their children or other duties. Village participants, representing a cross-section of the livelihood types of household in the village, were joined by the village leader, the village accountant, the village teacher, the village health worker, and the village women's group leader. Typically each village meeting was held in the village primary school or health centre. Two further township meetings were also held, involving almost 200 county and township representatives from the 26 villages with the reputation as the poorest among Fengning County's 309 villages.

The purposes of the meetings held at village and township levels was to explore with participants their views on the best means by which to measure poverty and monitor changes in the incidence of poverty. The results of these consultations are summarized in Table 3.

Table 3: Poverty Indicators Selected by 180 Poor Villagers and 252 Village and County Officials, Fengning County, Hebei Province, China

Priority Accorded By:122 Fengning 78 Township 180 Poor

Poverty Indicator County and Villagersin Officials 52 Village fromRank Order Officials 9 Villages1. Cash receipts per person per year 2 1 12. Grain production per person per year 1 2 23. Access to an all-weather access road 5 3 34. Easy access to quality drinking water 4 6 45. House quality (roof and exterior walls) 3 5 76. Access to reliable electricity supply 6 4 87. Days lost due to women’s ill health 7 7 58. Children’s access to education 8 8 69. Average arable land per person 4 10 910. Frequency of natural disasters 0 9 1111. Availability of irrigation 9 12 012. Degraded local ecology 0 0 1013. Access to poverty loans 0 11 0


The rank order of poverty indicators shown in Table 3 was arrived at after lengthy consultations with each respondent group. It is significant that respondents chose to ignore the great majority of the indicators in Table 1 above. It is even more significant that there is a complete overlap in the top eight indicators selected by each group, differences in ranking notwithstanding. This outcome has been crucial for the design and further development of CPAP as a practical and meaningful approach to the use of participatory strategies in the design, implementation and impact monitoring of village poverty reduction policies in China.

The differences in the indicator rankings shown in Table 3 are worth highlighting. First, the very much higher priority given by poor villagers to the existence of an all-weather access road is indicative of the influence that such an asset has on those who suffer most when access to nearby markets, emergency assistance, off-farm job opportunities, etc., is restricted because of transport and communications constraints. In like manner, the higher priority given by poor villagers to the importance of the health of the able bodied women in their households can be directly linked to the critical role that poor villagers recognize is played by women in household livelihood, household asset creation and household resource management activities. Villagers and village officials place a higher ranking on the importance of access to cash flow at household level than do township officials. The difference between them is not great, but this difference is likely to be an hangover from the days when village livelihoods were largely subsistence based and the use of cash to facilitate economic transactions in rural China was minimal.

It is the similarities in the rankings in Table 3, however, that are most striking. In contrast to the typical official approach to poverty monitoring and mapping, (according to the level of subsistence production or value of per capita income attributable to each household member), poor villagers and village officials consistently ranked access to cash receipts from earnings or other sources above non-cash components of household income as a measure of poverty. This is consistent with the observation that even among the most deeply subsistence-based households, the chains of poverty are rarely loosened if there is no added access to cash-flow, surplus subsistence production notwithstanding. The implication for the designers of poverty alleviation programs would seem to be clear: consider first the impact of public sector assistance on the flow of cash into poor households. Chronic village poverty may well be one case where ‘throwing money at the problem’ is not only the right thing to do but also the most effective thing to do

The first eight poverty indicators in Table 3 describe three key types of poverty; livelihood, infrastructure and human resource poverty. It is this subset of indicators that the CPAP field trials have focused upon as the core data needed for effective participatory poverty reduction planning at village level. Table 4 presents these eight indicators according to the form in which the data on each indicator has been collected in field trials.

Table 4: Eight Key Indicators for Three Core Types of Poverty

Poverty Indicators in Rank Order Measure1. Livelihood Poverty

a. Cash receipts per person per year Yuanb. Grain production per person per year Kgc. House quality (roof and exterior walls) % brick

2. Infrastructure Povertya. Access to an all-weather access road Days without accessb. Access to reliable electricity supply Days with interrupted supplyc. Easy access to quality drinking water Hours spent collecting water

3. Human Resource Poverty


a. Women’s morbidity Days lost to illness, females >12 years b. Children’s education % of eligible children in school

The eight indicators shown in Table 4 give us a unique insight into poverty as it is experienced and understood by poor villagers. The immediate livelihood components draw attention to the importance of grain production as a major source of nutritional security. There is nothing surprising about this finding. However, the higher priority given to financial liquidity as an indictor of poverty underscores the fact that money matters when you are poor. Poor farmers are very aware that their farm and household productivity improvements are not only a function of increased staple grain and other agricultural production. Poor villagers will easily and quickly tell you how important food security is to them, especially if they are subject to regular periods of food shortages. Equally, however, poor villagers draw on their personal experiences to explain that sustained improvements in household productivity are also a function of the things that increase the value of their earnings, whether from the sale of surplus production, earnings from off-farm employment, or public sector financial transfers. The housing indicator, on the other hand, is typically not a reflection on the awareness by poor villagers of the close statistical relationship that can be observed between poverty and the quality of the house one lives in. The housing indicator is important to poor farmers and poor villagers generally because housing is important to the quality of their lives. When poverty grinds and limits the range of choices that can be taken, investment in home improvements and renovations come a long second behind more immediate livelihood demands on the budget. However, when things are on the improve, one of the first things that poor farmers do is buy building materials or pay for home improvements. Officials from poor villages, townships and the county interpret this behaviour as a sign that villagers place a very high importance to home improvement. Poor villagers, on the other hand, rank the housing index below the cash income and production indicators. This is consistent with a perspective that reflects poor villager awareness that the capacity to invest in home improvements is dependent on the success of the production and wealth creation activities of household members.

It does not take very many encounters with poor villagers before one is struck by the awareness they have of how important good health is to their poverty status and future prospects of escape from poverty. Poor farmers are very familiar with the way in which ill health can sap their savings, sometimes forcing the liquidation of key family assets, such as draught animals or implements, without which future productivity will decline. However, it came as a significant surprise to learn of the importance given by poor villagers to the consequences of illness among the adult female members of their family. The faminisation of agriculture in China will further add to the importance of this indicator as a guide to emerging pockets of chronic poverty. Hence, the female morbidity rate is an indicator of first rank according to the experience of poor villagers. The housing indicator, in contrast, is also an important way in which poverty manifests itself in the quality of daily life, but as a measure of poverty it is, from the perspective of poor villagers, a dependent variable, and so less important than female morbidity, which is a key cause of poverty.

Constraints to escape from poverty can be legion, but the reality is that many constraints are directly linked to the level of investment that has been made in the accumulation of local infrastructure assets with public-goods dimensions. For example, the availability of an all-weather access road is has livelihood implications that are both personal and public. An all weather road is a public-good in that no matter how many individuals use the road, there is no loss of relief that the road brings to villagers from the isolation and poverty of information and market opportunities that existed before the all weather road was built. The all weather road is also a private asset to the extent that it enables village people to gain access to information and market opportunities that lead to improved income generation opportunities


and potential employers. Similarly, public sector investment in the provision of quality potable water systems can not only boost the availability of labour for household production, but also lead to significant savings as health costs associated with water born illnesses are slashed. However, access to a reliable supply of electricity is an indicator of a totally different order. This indicator has little to do with the consumption of a public good. Rather, it reflects on the extent to which poor villagers are able to plan and realize their entrepreneurial production activities.

A Participatory Poverty Index (PPI)

CPAP field trials not only consulted with poor villagers on how best to map poverty, but it also engaged poor villagers in the process of quantifying each indicator and attaching to each indicator relative weights, including a weight for each of the three key types of poverty. As a result, the CPAP process allowed for the construction of a composite participatory poverty index (PPI), that allows direct comparisons of the depth of poverty across villages or larger communities. Uniquely, because the PPI is participatory, it allows for poverty mappings that reflect poverty from the perspective of the poor themselves, as contrasted to poverty assessment methods that are imposed from the point of view of the researcher or the policy maker (9).

The PPI goes beyond good intentions and the comfort zones defined by what policy makers think constitutes priorities in the choice of poverty reduction strategies or project level initiatives. This is so because a close examination of the data associated with each of the eight poverty indicators provides us with a practical, productivity, market and people oriented view of what needs to change if the incidence of poverty is to fall and people in village China are to genuinely feel less poor. Consider the following examples.

Among the three indicators of livelihood poverty, first importance is given to household cash flow. This is as it should be, because there is no truer feature of poverty than that it is a condition where the poor have no money. The policy implication is clear. Poor people want policy makers and poverty reduction planners to give greater priority to increasing the access that they have to cash receipts or cash earning opportunities. Cash for work is unequivocally preferred over food for work. Similarly, the poor recognise that food insecurity, the second livelihood indicator, is not just about the inability of poor households to produce enough food for their own household use, but also the absence of cash resources to be able to buy-in the shortfall. That the third livelihood indicator should focus on the quality of housing is not surprising. Poverty analysts and microfinance specialists have often found that the quality of housing is an excellent proxy for household poverty. Lack of access to potable water is also recognised as important for sustainable poverty reduction not only because time spent fetching water is ‘dead-time’, restricting the available labour power for household or farm production, but it also bears on the level of household morbidity and capacity to save. Illness of household members from water born diseases is a drain on household savings, household cash reserves and an increase in the household dependency rate. All three compound the difficulty of escaping the mire of poverty unassisted.

The PPI incorporates the views of poor householders on what they believe are the critical causes and impacts of their poverty on the quality of their lives. CPAP field trials have confirmed that poor villagers are able to quantify each of the eight indicators as these apply to their households and their village. Moreover, they are also able to rank the eight poverty indicators according to which are most and least important to the ways in which they experience poverty. These rankings, which are not imposed by the researchers, but reflect the revealed priorities of poor villagers, are recorded using a scale of 1 (most important) to 5


(least important), which poor villagers are asked to attach as weights to each indicator and each type of poverty.

We can use the relative weights attached to each indicator and each type of poverty, one to another, to construct a weighted participatory incidence of poverty indicator. By so doing, the CPAP methodology integrates the poor themselves into the process of poverty mapping, allowing villagers, particularly poor women, to inform the process of relative poverty mapping and key indicators in monitoring progress in poverty reduction, with first-hand knowledge of poverty. Exactly how is this done? The process relies crucially not only on allowing poor villagers to quantify each indicator based on their own experience, but also the active involvement of poor villagers in specifying the poverty range for each indicator. On the basis of this range, each indicator can be converted to a common base, from a low of five to a maximum of one. The upper limit of 1 in the poverty range defines not only an indicator-specific poverty line, but also the top of a scale down to the situation of the poorest of the poor, defined as level 5, at the bottom of the poverty pyramid (10). Algebraically, if the bottom of the range is x1 and the top of the range is x2, then any number in-between x1 and x2, defined as xi, is given a number, yi, within the limits of 1 and 5 using the following formula:

yi = 5[x2 - (x2-xi) / x1]where i = a marker for any number in the poverty range for each indicator

Given the relative nature of poverty, poor householders in each village in the county are asked to define a what they regard as a poverty range for use with each indicator. Relative poverty is influenced by local knowledge of factors such as the importance of subsistence production to local survival strategies, the relevance of population density in the village’s unique geographic context, and the role that distance of village households from townships, for example, plays in determining local income generation opportunities. Poor villagers are well aware of these influences on the quality of their lives. As a result, it is poor villagers who are best able to determine the poverty range of, for example, the cash receipts indicator of livelihood poverty. The poverty range for the cash receipts indicator is an artefact of local knowledge of how much in total cash receipts is needed to keep a person or a household out of poverty. The poverty range is independent of the official income based poverty line, that sets a monetary (¥) limit to per capita income, including both cash receipts and non-cash income. The poverty range may overlap with the official poverty line, but it can also be either above or below the official estimate.

Data collected from villagers and village officials on each of the eight key poverty indicators can then be converted to a scale based on each unique poverty range, and the results directly compared across indicators, weighted according to the weights given to each indicator by villagers. The weights attached to the eight poverty indicators provide additional information to poverty reduction planners and policy decision-makers as to the poverty reduction interventions that poor householders want addressed in priority order. They also provide an insight into key constraints that poor villagers believe is the on-going cause of their poverty.

Table 5 summarises the results of a poverty range definition exercise undertaken in Fengning County, Hebei Province.

Table 5: Poverty Indicator Range Setting for Eight Key Poverty Indicators, Fengning County, Hebei Province

Poverty Indicator Unit Poverty Range:5 4 3 2 1


Cash receipts/person/year ¥ <100 100-250 251-400 401-550>550

Grain production/person/year kg <200 200-250 251-300 301-350>350

Quality of house % clay >80 79-60 59-40 39-20 <20All weather road access % with <20 21-40 41-60 61-80 >80Reliable electricity supply % with <10 10-20 21-30 31-40 >40Potable water access % with <20 21-40 41-60 61-80 >80Women’s morbidity rate % ill >40 30-40 20-29 10-19 <10Children’s school attendance % attending <60 40-60 61-80 81-90 >90

It is important to note that the research team was at pains during the field trials of CPAP to ensure that village groups understood what was being asked of them. The village groups confirmed that they understood that each indicator could take a value from 1 to 5, where 5 represented the worst case and 1 a level of poverty just below what would be 'acceptable' on a sustainable basis. Villagers understood that at 5, the indicator is judged as having hit rock bottom; things could not get worse. At a value of 1, the indicator is judged as showing a standard that is just below what would be acceptable to them for a happy and sustainable livelihood. Without exception, the research team did not proceed until it was clear that villagers understood these distinctions and were readily able to associate a point in the poverty range for each of the eight indicators relevant to their particular situation.

In like manner, when the villagers were asked by the meeting moderator to assign weights to each indicator and each type of poverty, it was explained to the villagers, at length, that the weights they assign must sum to 1, and that what they are doing is revealing the importance they attach to each of the different characteristics of poverty experienced in their village. It did not come as a surprise, therefore, that villages where access to potable water is an especially big problem, villagers assigned a higher weight to this indicator than villages where food security is the primary worry. While each villager was encouraged to add his or her personal estimates to each indicator estimate and associated rankings (weights), it was the task of the village meeting moderator and assistants to collate the numbers, average them and then to present the results to the meeting for confirmation or revision until a consensus is achieved. Once confirmed, villagers are reminded that it is their responses that will be used to calculate the PPI for their village.

One might speculate if the participatory nature of the CPAP process might undermine the veracity of the poverty mapping results, because the process may present villagers with the opportunity to exaggerate their poverty so as to maximize the chances that their village will be selected for public sector assistance. In an effort to avoid this possibility, CPAP includes a peer review step, which is designed to allow village representatives to review and comment on the baseline data collected from all villages in their area. During these peer review sessions villagers and village officials are able to challenge the veracity of individual indicators relative to what is shown for their own village. These challenges should continue until there is a consensus that the relative position of one village compared to another, for each of the eight indicators, is a true and fair description of the incidence of poverty in the county.

CPAP field trials show that villagers are pragmatic and realistic. Despite significant opportunities to succumb to the temptation to exaggerate, not a single example of exaggeration was encountered in the many meetings held across Hebei Province. Rather, poor villagers took the opportunity to participate in CPAP as occasions to draw attention to their needs and the key problems that must be overcome for poverty in their village to be reduced if not abolished. The participatory nature of CPAP appeared to create realistic


expectations, and not to cause villagers to revise their understanding of the important role that county, township and province considerations will play in the choice of local development priorities. The participatory process does, therefore, insert a welcome element of 'robustness' into poverty reduction planning, in particular to the PPI based poverty mapping, which is defined for each village on the basis of the data collected and subject to peer review (11).

Calculating the PPI

The arithmetic needed to calculate a PPI for each village is neither trivial nor overly complex. This is important as it is village, county and township officials especially for whom the PPI ought to be an important new tool in the fight to abolish hard-core village poverty. As already noted, the data needed to calculate the PPI are taken from a sequence of village participatory rapid assessment exercises. Each indicator is associated with weights identified by villagers, which is used to convert the raw data from a poverty range, also defined by villagers, restricted to values between 1 and 5, to best reflect how poor villagers feel that poverty is typically manifest in their village. These calculated weighted values are then further weighted by the weights that villagers also attach to each of the three priority types of poverty that prior CPAP research identified as most important in village China. The sum of these numbers is a value between 1 and 5, that is then adjusted to a base of 100 for easy comparison of the incidence of poverty across villages. The closer the PPI is to 100, the more severe and deeper the incidence of poverty.

The formula for the PPI can be expressed algebraically as follows:

PPI = [(Ii*wit)*Wt]*20

where:

Wt=1-3 = poverty weights for each component of: Livelihood (W1), Infrastructure (W2) and Human Resource (W3) poverty.

Wt = 1

Ii=1-8 = eight poverty indicators converted to within a poverty range of 5-1.

wit = poverty weights for each poverty indicator relevant to each type of povertywhere t=1-3 and i=1-8

and

wit = 1

In expanded form the PPI can also be written as:

PPI = [W1(I1.w11+ I2.w12+ I3.w13)+ W2 (I4.w21+ I5.w22+ I6.w23)+ W3 (I7.w31+ I8.w32)].20

The calculation of the PPI is essentially a simple arithmetic exercise, as shown in Table 6, where data for three villages from Fengning County, Hebei Province, PRC are presented. The data shown in Table 6 was gathered as part of the field trials of CPAP.


Table 6: Calculating the Participatory Poverty Index for Three Villages in Fengning County, Hebei Province

Poverty Poverty Range Poverty Type Weights Poverty IndicatorWeights

Ii Wt wit

------------------------Village---------------------------------1 2 3 1 2 3 1 2 3

Livelihood Poverty .35 .38 .34Grain production (I 1) 4 5 5 .37 .41 .35Cash receipts (I 2) 4.5 3 4 .39 .38 .40Quality of housing (I 3) 3 5 5 .24 .21 .25Infrastructure Poverty .33 .31 .34Access to potable water (I 4) 4.5 2 1 .41 .41 .40Access to reliable electricity (I 5) 2.5 1 1 .24 .28 .20Access to all weather road (I 6) 3.5 5 5 .35 .31 .40Human Resource Poverty .32 .31 .32Women's health (I 7) 5 4 3 .5 .47 .53School attendance (I 8) 3 5 2 .5 .53 .47

Participatory Poverty Index (PPI) 77 76 64

Table 6 contrasts three villages with a PPI ranging from 64 to 77. These numbers can be interpreted as showing that poverty is significant in all three villages, but least severe in village 3 and most severe in village 1. Moreover, the components of the index tell us that all three villages have a significant food security problem, but village 1 gives higher priority to overcoming its problem with women’s health and access to quality drinking water than villages 2 and 3. Villages 2 and 3, however, attribute their poverty in great part to their isolation, which investment in a good all-weather access road would, in the opinion of villagers significantly address.

The CPAP field trials have been extensive enough to allow for the calculation of PPI estimates for all 309 villages in Fengning County, Hebei Province, PRC. If one takes a PPI of 50 as a cut-off for villages with urgent need for poverty reduction assistance, the results, which are presented in Table 7, confirm Fengning to be a poor County. More than 80 percent of villages in Fengning County have been found to have a PPI greater than 50!. However, the real significance of data such as is reported in Table 7 will remain elusive so long as a more general application of CPAP and calculation of PPIs for villages in other poor counties remains undone.

Table 7: Ranked PPI Estimates for 309 Villages in Fengning County, Hebei Province, PRC

Town Village PPI Town Village PPI Town Village PPI Town Village PPI Town Village PPI Town Village PPINanguan 86.2 6 67.4 6 61.1 Datan 58.3 2 64.9 13 48.5

1 92.6 Tucheng 73.1 7 54.3 1 67.9 3 63.1 14 48.5 2 92.6 1 92.1 8 50.6 2 67.8 4 61.3 15 47.8 3 92.6 2 92.1 Caoyuan 62.9 3 66.1 5 61.3 16 31.0 4 92.6 3 78.8 1 63.5 4 65.8 6 61.3 Yuershan 50.2 5 92.6 4 78.7 2 63.5 5 65.8 7 59.1 1 57.7 6 90.8 5 77.4 3 63.5 6 65.8 8 57.6 2 53.3 7 89.1 6 75.9 4 60.9 7 63.2 9 56.3 3 52.9 8 89.0 7 75.4 Beitou 62.3 8 63.1 10 52.6 4 48.6 9 87.2 8 74.1 1 73.4 9 63.1 11 50.1 5 48.610 85.0 9 73.0 2 71.5 10 61.3 12 50.1 6 48.611 81.3 10 70.2 3 63.9 11 61.0 13 46.3 7 48.612 78.0 11 66.7 4 61.4 12 61.0 14 44.5 8 46.813 77.6 12 49.8 5 59.6 13 57.8 Sichakou 56.7 9 46.8


14 65.2 13 46.0 6 54.3 14 57.6 1 62.7 Huangqi 49.2Fenshan 79.0 Kulongsan 71.6 7 51.8 15 56.3 2 60.2 1 62.4

1 92.0 1 80.1 Wudan 62.2 16 56.2 3 60.2 2 62.4 2 92.0 2 74.8 1 84.5 17 54.0 4 58.0 3 62.4 3 85.5 3 74.5 2 83.0 18 50.1 5 55.4 4 62.3 4 85.5 4 72.4 3 76.1 19 50.0 6 53.2 5 59.7 5 85.5 5 69.7 4 73.1 20 44.9 7 52.7 6 57.5 6 85.5 6 69.5 5 63.2 21 44.9 8 50.9 7 55.3 7 85.5 7 60.5 6 45.6 22 38.6 Tianqiao 53.6 8 55.3 8 85.5 Tanghe 71.0 7 39.1 Xiguan 58.1 1 67.7 9 54.9 9 85.5 1 83.3 8 32.8 1 73.5 2 65.1 10 52.210 85.5 2 78.1 Waigou 59.9 2 62.0 3 65.1 11 47.811 85.5 3 76.4 1 64.7 3 60.2 4 52.7 12 44.012 85.5 4 73.7 2 61.7 4 57.9 5 52.7 13 44.013 85.5 5 73.4 3 60.2 5 57.0 6 51.6 14 44.014 85.5 6 73.3 4 58.9 6 55.3 7 46.8 15 40.315 85.5 7 72.9 5 57.5 7 55.3 8 40.3 16 30.116 82.9 8 71.1 6 56.2 8 55.3 9 40.3 17 25.617 82.9 9 70.8 Sujiadian 59.1 9 53.4 Xueyin 53.6 18 25.618 82.9 10 70.7 1 68.4 10 50.9 1 62.9 Dage 41.719 79.1 11 66.0 2 60.2Heishan 57.3 2 62.7 1 70.720 79.1 12 63.3 3 58.3 1 70.6 3 60.9 2 63.721 78.9 13 62.8 4 57.6 2 66.6 4 60.9 3 60.122 76.7 14 57.7 5 55.7 3 65.9 5 59.7 4 55.623 76.7 Boluonuo 68.8 6 54.6 4 64.1 6 53.3 5 48.624 76.7 1 94.0 Wanyong 59.1 5 64.1 7 50.6 6 45.825 76.2 2 94.0 1 66.1 6 62.9 8 43.1 7 44.726 76.2 3 91.2 2 59.2 7 59.6 9 42.9 8 42.127 76.2 4 79.9 3 58.7 8 59.1 10 38.6 9 41.828 76.2 5 74.2 4 52.4 9 56.9 Humayin 53.3 10 39.329 72.7 6 70.6 Yangmu 58.5 10 56.6 1 72.3 11 39.330 60.3 7 61.6 1 79.3 11 54.5 2 68.7 12 35.631 60.3 8 53.4 2 65.2 12 53.5 3 60.2 13 35.6

32 60.3 9 48.0 3 62.4 13 52.9 4 60.2 14 34.933 60.3 10 46.0 4 59.1 14 52.9 5 57.5 15 34.934 54.7 11 43.6 5 58.2 15 52.3 6 53.1 16 34.9

Xiaobazi 76.2 Wangyin 65.2 6 56.4 16 50.5 7 53.1 17 34.9 1 80.1 1 79.3 7 55.5 17 50.5 8 52.7 18 34.9 2 79.6 2 76.7 8 52.9 18 47.5 9 50.5 19 29.2 3 78.4 3 74.5 9 52.9 19 47.5 10 50.3 20 27.3 4 76.8 4 64.3 10 51.3Sirengou 56.7 11 50.3 21 22.7 5 74.9 5 61.1 11 50.2 1 65.7 12 48.6

PPI and Wealth Rankings Compared

If the PPI is to stand the test of validity, it ought to bear a close relation with village wealth rankings, whereby the poorest villages are also the least wealthy villages. In order to test this relationship, wealth rankings were also conducted in 9 villages in Fengning County. The results are presented in Table 8

Table 8: Comparison of Wealth Ranking and PPIs for 9 villages, Fengning County, Hebei Province, PRC

Village Wealth ranking1(Wealthiest)-9(Poorest)

PPI(% incidence of poverty)

Tucheng 1 50Dongshang 2 46Qianfoshi 3 67Sijianfang 4 70Sanjianfang 5 75


Liutiaogou 6 74Zhangying 7 79Mawopu 8 92Liquan 9 92

The parallel between the wealth rankings reported in Table 8 and the corresponding PPIs taken from Table 7, is striking. The wealth rankings, however, unlike the PPIs, are not pregnant with information and policy guidelines on why these levels of poverty exist and how the poor in villages can best be assisted to raise the quality of their lives.

Villages in Fengning County are shown to have a PPI between a high of 92.6 for the poorest villages and a low of 22.7 for the least poor. These differences can be interpreted as an indicator not only that one village is relatively poorer than another, but also an indicator of the 'depth' of the incidence of poverty in each village. It is legitimate to say that a PPI of 90 indicates a depth of poverty that is 70 percentage points more intense than a PPI of 20. In this sense, the PPI goes beyond simple head-counting. It incorporates allowances for how poverty manifests itself at the village level and in poor households. Its component parts provide planners with insights into the priority problems as perceived by villagers. This is important new information, responses to which can be expected to mobilize community support for CPAP.

One might ask the question, at what level of the PPI does a village 'stop' being poor and eligible for inclusion in public sector funding for poverty reduction? The answer to this rhetorical but valid question is not straightforward. In one sense, the answer is academic and trite, because only villages identified as key counties by China’s State Council are eligible for public sector support. However, it does not follow that the PPI and CPAP in general is irrelevant to other counties in China. Poverty exists in all counties in China, and the CPAP strategy is relevant to the resources allocation decisions needed to ensure that the PPI ranking for poor villages will decline.. The PPI presents policy makers and development workers with a unique, participation based approach to poverty mapping and progress in poverty reduction that is practical, socio-culturally relevant to target communities, and a basis for comparing performance across a range of well defined key indicators.

The importance of the PPI for village poverty reduction planning has three foundations: First, the PPI is a powerful tool with which to determine which villages would be eligible for priority attention if the poorest counties are to be targeted as a matter of policy priority. Second, the PPI is a basis on which planners at county level can assess the incidence of poverty across the county and use this information to ensure that poor villages are not by-passed in the county development plan. Third, knowledge on the geographic distribution of poor villages allows development planners to search for 'strategic patterns' in the distribution of poor villages. This information can then be taken into account in the preparation of regional development plans in ways that offer a basis for poverty reduction focused development planning.

Endnotes(1). Dean, College of Humanities and Development, China Agricultural University. (2). Director, International and Community Development, Faculty of Arts, Deakin University. (3). The final Technical Assistance report, coded TA 3610, can be found at www.adb.org/prcm. The full citation is: Li, Xiaoyun (Team Leader), Zhou Li, Yanli Liu, Yonggong Liu, Joe Remenyi, Sibin Wang, and Chungtai Zhang, 2002, CPAP, A Methodology for Participatory Development Planning for Poverty Reduction in China, Asian Development Bank, Beijing. .

http://www.adb.org/prcm


(4). For details see Li, Wang, Remenyi and Thomas 2003, and Remenyi and Li 2004. (5). Poverty trends in China are reviewed in: China State Council, White Paper 2001, Fan 2002, LGOP 2002, 2000, LGOP, UNDP and World Bank 2000, Solveig Buhl, Qian Wei, and Wang Xuexiong 2004, UNDP and ILO 2000, UNDP 1999, World Bank 2001(6). These data are reported in Fan 2002, World Bank 2001 and LGOP 2002, 2000(7). LGOP, World Bank and UNDP 2000(8). The grossly neglected concept of ‘chronic’ poverty is addressed by David Hulme and others in the March 2003 special issue of World Development. (9). The participatory character of the CPAP strategy and the PPI is in marked contrast to the typical poverty assessment strategy currently employed by development assistance agencies. See for example, the results of the USAID-sponsored Developing Poverty Assessment Tools Project, (USAID 2004), available via email at Poverty Assessment Tools <[email protected]>, or via the internet at http://www.povertytools.org. See also the IFPRI-CGAP approach in Henry, et.al. 2003. (10). A separate exercise that is part of CPAP involves the description of each village according to the main groups of livelihood survival strategies into which each household or individual can be placed. This process describes a village poverty pyramid, ranking the population according to the productivity of each livelihood group, with the most productive at the top and the least productive at the bottom. The poverty pyramid method of describing and monitoring trends in the structure of poverty at village level is described in Remenyi, 1991, 1994a, b, and 2004. (11). This conclusion is not inconsistent with the experiences of many other development professionals who regularly incorporate participatory methods into their development work. See especially, Brock and McGee 2002.

Bibliography

ADB 2000, A Study on Ways to Support Poverty Reduction Projects, Final Report, TA3150-PRC, ADB, Beijing.

Brock, Karen and Rosemary McGee, eds., 2002, Knowing Poverty, Earthscan, London.

China State Council, White Paper 2001, The Development-oriented Poverty Reduction Program for Rural China, Information Office China State Council, Beijing, October 15

Fan, S 2002, Public Investment, Growth and Poverty Reduction in Rural China and India, Figure 1: Rural Poverty Incidence, World Bank, Washington, DC, http://poverty.worldbank.org/files/12402_SFan-Presentation.pdf

Henry, Carla, Manohar Sharma, Cecile Lapenu and Manfred Zeller 2003, Microfinance Poverty Assessment Tool, International Food Policy Research Institute, Technical Tools Series No. 5, CGAP, Washington, DC

Hulme, David and Andrew Shepherd, eds., 2003, Chronic Poverty and Development Policy, World Development, Vol. 31, No. 3, March.

IFAD and WFP 2000, Formulation Report, West Guangxi Poverty Alleviation Project, Vol. 1, Main Report, WFP Country Office, Beijing, April.

IFAD and WFP 1999, Appraisal Report, Qinling Mountain Area Poverty Alleviation Project: Vol. 2, Working Papers, WFP Country Office, Beijing, September.

http://poverty.worldbank.org/files/12402_SFan-Presentation.pdf

http://www.povertytools.org/


IMF et. al. 2002, G8 Okinawa Summit, ‘Global Poverty Report’, and ‘A Better World for All”, July; Full texts and discussions of progress in achieving the IDGs is available at www.paris21.org/betterworld.

LGOP 2000, Key Poverty Reduction Documents of the Chinese Government, PRC, paper prepared for the International Conference on China's Poverty Reduction Strategy in Early 21st Century, Beijing, May.

LGOP, UNDP and World Bank 2000, China, Overcoming Rural Poverty, Report No. 21105-CHA, Rural Development and Natural Resources Unit, East Asia and Pacific Region, World Bank, Washington DC, October.

LGOP 2002, Guidelines for Rural Poverty Alleviation and Development in China 2001-2010, China State Council, Beijing.

LGOP 2000, Key Poverty Reduction Documents of the Chinese Government, PRC, paper prepared for the International Conference on China's Poverty Reduction Strategy in Early 21st Century, Beijing, May.

LGOP, UNDP and World Bank 2000, China, Overcoming Rural Poverty, Report No. 21105-CHA, Rural Development and Natural Resources Unit, East Asia and Pacific Region, World Bank, Washington DC, October.

Li, Xiaoyun, Wang Goliang, Joe Remenyi and Pam Thomas 2003, Training Manual for Poverty Analysis and Participatory Planning for Poverty Reduction, China International Books, Beijing (in Chinese).

Li, Xiaoyun, Zhou Li, Yanli Liu, Yonggong Liu, Joe Remenyi, Sibin Wang, and Chungtai Zhang 2002, CPAP, A Methodology for Participatory Development Planning for Poverty Reduction in China, Asian Development Bank, Beijing. Full text of the report has been published by the ADB at www.adb.org/prcm

Ravallion, Martin 2002, India: higher growth in the 1990s, but how much impact on poverty?, paper presented at the Fostering Country Ownership of Poverty Analysis, World Bank India Poverty Workshop, January, http://www.worldbank.org/poverty/wbactivities/pa/index.htm

Remenyi, Joe 2004, The Poverty of Development, chapter 7 in Kingsbury, Damien, Joe Remenyi, John McKay and Janet Hunt, 2004, Issues in Development, Palgrave-Macmillan, London

Remenyi, Joe, and Xiaoyun Li 2004, ‘Towards Sustainable Village Poverty Reduction? The Development of the CPAP Approach’, in Taylor, John and Jannelle Plummer, eds., 2004 forthcoming, Capacity Building in China, DFID, London.

Remenyi, Joe 1994a, Poverty Targeting, chapter 8 in Geddes, Bill, Jenny Hughes & Joe Remenyi 1994, Anthropology and Third World Development, p. 261-293, Deakin UP, Geelong.

Remenyi, Joe 1994b, The role of credit in the Qinghai Community Development Project, Pingan, Haidong County, Qinghai, PRC, Consulting report to CARE Australia, Hassall & Associates and the Australian International Development Assistance Bureau, Canberra.

Remenyi, J V 1991, Where Credit is Due: A Study of Credit Based Income Generation Programmes for the Poor in Developing Countries, Intermediate Technology Publications, London.

http://www.adb.org/prcm

http://www.paris21.org/betterworld


Solveig Buhl, Qian Wei, Wang Xuexiong 2004, Towards Comprehensive and Participatory Poverty Monitoring and Impact Evaluation in Jiangxi Province, PR China, paper prepared by Sino-German Poverty Monitoring Project, Nanchang, Jiangxi Province, for the Asian Development Bank Regional Meeting on Poverty Monitoring, Manila, March, www.rcpm.net

UNDP and ILO 2000, Policies for Poverty Reduction in China, Supplement to the Joint Government – World Bank – UNDP China Poverty Study, prepared for the International Conference on China's Poverty Reduction Strategy in Early 21st Century, Beijing, May.

UNDP 1999, Project Document: Comprehensive Approach to Poverty Reduction in China, Project Number: CPR/01/201/A/99.

USAID 2004, Developing Poverty Assessment Tools Project, Poverty Assessment Tools <[email protected]>, or via the internet at http://www.povertytools.org.

World Bank 2001, China: Overcoming Rural Poverty, World Bank, Washington, DC

World Bank, 2001, Poverty Trends and Voices of the Poor, Washington DC

http://www.povertytools.org/

http://www.rcpm.net/