If governments, NGOs and international development agencies are to monitor how their development policies affect the nature and extent of poverty, they need to know more about their target populations. For example, knowing how the poor derive and spend their incomes will guide policy-makers to assess how changes in the relative prices of various goods and services will impact on real incomes. In Pacific Island countries, what do we know about the characteristics of the poor? I would suggest that the subject has received less than adequate attention in this part of the world⁴.

Poverty, as measured by low income, and often according to the social indicators, is its worst in rural areas. Problems of malnutrition, lack of education, low life expectancy and sub-standard housing are very often more severe in the country side. Variation within rural areas can also be wide. Where are the poorest people in countries of the Pacific located? We simply do not know because we do not yet have the requisite information. In many other countries, urban poverty is much greater because of overcrowded slums and squatter settlements, bad sanitation and contaminated drinking water. In the Pacific countries, however, urbanisation is relatively low, although increasing, and poverty may not be so easily associated with capital cities and large towns.

What are the demographic characteristics of the poor? Households with the lowest incomes per capita are often large, containing many children and other dependents. The lack of a male or a healthy working male, often leads the household directly into its poverty status. Yet, the decision to have many children may be a rational response to poverty. Infant mortality is higher in destitute families, and in order to ensure that some children survive to support parents in old age, it is necessary to produce a large number of births. Indeed, parents often 'over-replace' dead children. Yet, survey data suggest that many poor mothers wish to bear no more children and that the last born child was not wanted. These are the couples who lack access to family planning services and should be the prime focus of UNFPA's efforts at IEC and awareness raising, as well as initiatives to improve the accessibility to, and the quality of, service and distribution outlets.

However, in poor, rural underdeveloped countries the value of many children is realised through their contribution to household income via their participation in labour market activities. This contribution negates the future benefits of attending school (especially for girls), ensuring that the net flow of resources is from children to parents and inducing large family sizes. In contrast, in developed countries, the future benefits of education are large and outweigh any possible income derived from child labour force activities, and the net flow of resources is clearly from parents to children. The outcome is that parents prefer few 'quality' children over 'quantity', particularly where the need to anticipate that a large proportion of births will die, is negligible.

Are women poorer than men? Available social indicators on health, nutrition, education, labour force participation and income often show that sex differentials are large and women are severely disadvantaged. They face all manner of cultural, social, legal and economic obstacles that men do not. Female-headed households have often been shown to be amongst the poorest, in the sense of having the smallest plots of land, greater food insecurity, lower farm output (partly because they are less likely to get access to fertilizer) and lower incomes. What is the condition of female-headed households in the Pacific countries? Again, prevailing data and knowledge gaps are prevalent and indicate the urgent need for well-designed household surveys to gather the requisite information.

Apart from being deficient in their access to land, the poor invariably lack other assets, including education and other marketable skills. Without much land and little human capital the poor are restricted to irregular, low-skilled wage employment. With rapid population growth and high population densities on land, as in some Pacific Island countries, we would expect the absolute and relative size of this group of poor to grow in the future. The implications for development policies are that, without an increase in assets, broadly defined, that are owned by the poor, especially education, labour market skills, health and access to land, the plight of this already vulnerable group - the group that needs development the most - will deteriorate further.

Other characteristics of the poor in less developed countries include an over reliance on agriculture as a source of income, either as subsistence farmers or as seasonal wage labourers. In towns they tend to be concentrated in low-paid informal sector jobs. Their incomes tend to fluctuate significantly over the agricultural season, particularly due to the seasonality in the availability of wage labour opportunities, yet capital markets are grossly underdeveloped to allow them to borrow when the crops are in the ground and to repay the loans when the harvest is sold. In any case, they often lack any form of collateral against which to borrow. The result is that the potentially 'hungry' season - when food stocks are low and food prices high - coincides with the busy season, which entails heavy agricultural work and when under-nutrition and illnesses are more common, particularly amongst the more vulnerable women and children.

One very well documented behavioural relationship of the poor is contained in the so-called Engel curve; the poor typically spend 60% or more of their low incomes on food and the rest on other basic essentials. As incomes rise, however, this proportion drops, allowing larger absolute and relative amounts to be spent on such human capital enhancing investments as education, health and labour market skills.

This portrait of the poorest members of the population in countries which are themselves classified as underdeveloped and poor indicates the direction in which they must move. To attain the status of being developed they need to expand the production of food by raising the productivity of land and labour in the farm sector. As farm incomes rise, the supply price of labour to the non-farm economy rises and demands are created for other essential goods and services to satisfy basic needs as well as for products considered to be not so essential.

As new lines of production are created - often in rural, non-farm activities - and a wider spectrum of job opportunities are created necessitating a better trained and more flexible labour force, the demand for education is raised. New types of manufacturing and service jobs are created, the relative importance of agriculture declines, and labour productivity grows as capital accumulation occurs in these more dynamic sectors. An expanding wage labour force, often more urban-based, receives higher wages and income inequality declines. As a result, the incidence of poverty, unemployment and underemployment are all likely to become less widespread as the economy attains the elusive 'developed' status. Its social indicators - literacy, the rates of primary and secondary school enrolment, nutritional status, infant mortality, life expectancy, morbidity, access to health facilities, safe water, sanitation etc. - should all improve. All kinds of new choices - education, occupation, residence, life - style - are made available to a much larger proportion of the population as a result. In addition, wider demographic choices are likely to be made resulting in a lower level of desired and achieved fertility. The development criterion mentioned earlier - the realisation of the human potential embodied in each individual has a much greater likelihood of coming to fruition.

C. Developed and Less Developed Countries: How they differ

In order to substantiate some of these hypotheses it is worthwhile to examine some relevant data recently collated by the World Bank and the UNDP and presented in Table 2. The data compare the affluent developed countries with the poorest in Africa. I have also presented data from four Pacific Island countries, Papua New Guinea, Fiji, Solomon Islands and Vanuatu, which were incorporated in the most recent Human Development Report of the UNDP.

The table shows that the rich OECD countries have very significantly higher levels of incomes than the poor, sub-Saharan African countries. The economies of the former are much more diversified, with much less reliance on agriculture and greater emphasis on the industrial and service sectors where productivity and incomes are higher. They save and invest more of their much larger incomes so assuring their future growth. Yet, countries in Africa have much higher fertility and population growth so that their slowly growing GDPs need to be shared amongst much larger numbers, allowing for little advance in per capita income. In addition, African investment in human resources, as reflected in primary and secondary school enrolment rates are relatively low. Using the pupil-teacher ratio as an index of education quality, there are over three times as many pupils for each primary teacher in Africa than in Belgium.

Health and demographic indicators are also very low in Africa. Each physician has 50 times more patients on average to cater for, the IMR is 13 times greater and the maternal mortality rate is 16 times greater than in western countries.

In general, the four Pacific Island countries lie somewhere between the extremes of these development indicators. However, there is considerable differentiation between these four countries, with Fiji invariably performing better from the viewpoint of human development. Yet all four exhibit some of the characteristics of least developed countries in having high fertility and rapid population growth, relatively high mortality, low domestic saving and a heavy reliance on agriculture to generate employment and income.

Table 2 - Indicators of Development in Developed and Less Developed Regins

Note : Where data for sub-Saharan Africa or the OECD countries are not available, individual country level data have been reported:
PNG=Papua New Guinea
S.I.= Solomon Islands
Van. = Vanuatu
Source : World Bank (1990), World Bank Report 1990, Washington, D.C. and UNDP 1992, Human Development Report 1992, New York

Many would argue that the principal contributing cause of these discrepancies is found in differences in population growth. Fertility has remained very high in Africa and some of the Melanesian countries included in table 2. Mortality has declined so that population is growing at an unprecedented 3% per annum, or more, in Africa and over 2% per annum in most of Melanesia, so that population will double in 25-30 years. This situation is reflected in the large proportion of the population that is under 14 years of age - 47% in Africa but only 20% in the rich western counties. These dependents impose a heavy burden on the working population aged 15 to 64 years. On the other hand, it might be argued that the line of causation is reversed i.e. the state of underdevelopment induces high fertility and rapid population growth because individual households perceive their own large family size to be in their own interest. No doubt, both lines of causation are at work and contribute to poor income growth and rapid population growth.

Although they are not nearly so poor, most of the countries in the Pacific experience very high natural rates of population growth which are only partly mitigated by international out-migration. The result is a retardation in the potential to undergo economic development.

An alternative approach has recently been created by UNDP with their Human Development Index (HDI) focussed on measures of health, life expectancy, education and access to resources. Human development is defined as:

"The process of enlarging the range of people's choices-increasing their opportunities for education, health care, income and employment, and covering the full range of human choices from a sound physical environment to economic and political freedoms. Human development is concerned both with developing human capabilities and with using them productively. The former requires investments in people, the latter that people contribute to GNP growth and employment. Both sides of the equation are essential" (UNDP, 1992,p.2).

For each of 160 countries the index combines purchasing power, life expectancy and literacy. Table 3 sets out the numbers. Sri Lankans have an official GNP of about $400 per head, but purchasing power of more than $2,000 per head because goods are cheap; their life expectancy is 71 years, 88% of them are literate. That gives them an HDI - rank of 76. Brazilians (GNP per head of about $2,000) have purchasing power of $4,900,can expect to live 66 years, and 81% of them are literate. They attain an HDI-rank of 59. Saudi Arabia (GNP per head of over $6,000) scores purchasing power of $10,330, life expectancy of 65 years and 62% literacy, for an HDI rank of 67. That order reverses the conventional ranking by GNP per head.

The strength of the HDI is in reminding us that there is more to life than GNP. Its big weakness, inevitably, is that it is subjective. The implicit weighting of purchasing power, life expectancy and literacy is arbitrary. Because the index is intended to ensure the absence of deprivation, it gives little credit for income growth beyond an 'adequate' income level of just under $5,000. This helps to explain some peculiar results.

How many would agree, for instance, that Singapore (line 40) deserves to be ranked five places lower than Bulgaria, or Italy no fewer than 20 places lower than top-placed Canada (and three lower than Israel)? Oddities become absurdities in the case of and newly ex-communist countries, whose underlying GNP figures are worthless. Hands up everybody who thinks that the former USSR (33) has reached a higher place of development than Malta or Argentina, or Yugoslavia (37) than Portugal (39).

Still, students of development will study promotion and relegation in the HDI league with interest. Among the more surprising promotions is that of India (121). By raw GNP per head, only 22 countries are poorer. On the HDI, India moves in front of another 17.

Most Arab nations, with high incomes but also high death rates and low literacy, are relegated en bloc by the HDI. Several social-democratic countries in and around Latin America - such as Costa Rica (42), Argentina (43) and Jamaica (63) - win promotion; so do some 'progressive' Asian countries such as Sri Lanka (76), China (79) and Thailand (69). Bravely the UNDP opines that this may have something to do with freedom, even with democracy. Unfortunately, one of the best of all Latin America performers has been Chile (36) - not exactly free or democratic in recent years!

It is of interest to review the situation of the five Pacific Island countries included in table 3. Fiji, Samoa, Solomon Islands and Vanuatu are all promoted in terms of their HDI index compared with their relative position in GNP per capita. Their performances in life expectancy are very respectable although there is a wide variation between these countries in educational attainments, with adult literacy ranging from 92% in Samoa to 24% in Solomon Islands, and in Real GDP per capita (PPP$), ranging from $4192 in Fiji to $1981 in Samoa. Papua New Guinea provides a stark contrast because it is the only PIC of the five which is relegated according to the HDI, despite its already poor showing in terms of real GDP per capita of $1,834. The result is a reflection of its poor social indicators, whereby its levels of life expectancy, literacy and mean years of schooling are comparable to those in some of the least developed sub-Saharan countries. The result is that Fiji ranks at 64 in the Human Development Index, followed by Samoa (84), Vanuatu (93), Solomon Islands (105) and Papua New Guinea (116).

Wishful thinking aside, the UNDP report has little to say about why some countries have been so much better than others at translating growth in GNP into "development'': more guidance on policy is promised by UNDP in the future. Not long ago, the UNDP might have argued that growth hardly matters, but attitudes have changed. Growth is good, it now affirms. What is needed is more of the right sort of public spending, especially on primary education and health and less of the wrong sort - e.g. on armies.

The UNDP adds to the literature on military waste with figures on soldiers in relation to teachers. In the rich world, Japan's armed forces enlist 25 people for every 1000 employed in teaching. In the United States there are almost as many soldiers as teachers; France has more soldiers than teachers. In other big West European countries with conscription, the armed forces are often slightly larger than the teaching profession. Britain, with no conscription, has 62 soldiers per 100 teachers.

Table 3 - Human Development Index - All Countries

a. A positive figure shows that the HDI rank is higher than the GNP rank, a negative the opposite.
Note : Figures in italics are UNDP estimates.
Source : UNDP (1992)

Construction of the human development index (HDI)

The HDI includes three key components: longevity, knowledge and income, which are combined in a three step process to arrive at an average deprivation index (for a full technical description, see Human Development Report 1991, technical note 1, pp. 88-89). Longevity is measured by life expectancy at birth as the sole unadjusted indicator. Knowledge is measured by two educational stock variables; adult literacy and mean years of schooling:

E = a₁ LITERACY + a ₂ YEARS OF SCHOOLING
a₁ = ²/₃ and a₂ = ¹/₃

For income, the HDI is based on the premise of diminishing returns from income for human development using an explicit formulation for the diminishing return. A well known and frequently used form is the Atkinson formulation for the utility of income :

W(y) = ^{1/_1-Î X y1-Î}

Here, W(y) is the utility or well-being derived from income, and the parameter measures the extent of diminishing returns. It is the elasticity of the marginal utility of income with respect to income. If x=0 there are no diminishing returns. As approaches 1, the equation becomes :

W(y) = log y

The value of Î rises slowly in the HDI as income rises. For this purpose, the full range of income is divided into multiples of the poverty line y*. Thus, most countries between 0 and y*, some between y* and 2y*, even fewer between 2y* and 3y* and so on. For all countries for which y < y* - that is, poor countries - Î is set = 0. There are no diminishing returns here. For income between y* and 2y*, Î is set equal to ¹/₂. For income between 2y* and 3y*, Î is set at ²/₃. In general if a y* £ y £ (a+1)y*, then Î = a/(a+1). This gives:

So, the higher the income relative to the poverty level, the more sharply the diminishing returns affect the contribution of income to human development. Income above the poverty line thus has a marginal effect, but not a full dollar-for-dollar effect. This marginal effect is enough, however, to differentiate significantly among industrial countries. This method does not take Î = 1, but allows it to vary between 0 and 1.

For example, Singapore has a real GDP per capita of $15,108. With the poverty line set at $4,829, there are four terms in the equation to determine the well-being of Singapore :

W(y) = y + (2y*) ^1/2 + 3(y - 2y*)^1/3 + 4(y - 3y*)^1/4

= 4,829 + 2 (4,829) ^1/2 + 3 (4,829) ^1/3 + 4 (15,108 - 14,487) ^1/4

= 4,829 + 139 + 51 + 20 = $5,039

In calculating the HDI of Singapore using the improved variables and applying the methods described here, the following steps are taken :

Maximum country life expectancy = 78.6
Minimum country life expectancy = 42.0
Maximum country educational attainment = 3.00
Minimum country educational attainment = 0.00
Maximum country adjusted real GDP per capita = 5,079
Minimum country adjusted real GDP per capita = 380
Singapore life expectancy = 74.0
Singapore educational attainment = 2.04
Singapore adjusted real GDP per capita = 5.039
Singapore life expectancy deprivation = (78.6 - 74.0) / (78.6 - 42.0) = 0.126
Singapore educational attainment deprivation = (3.00 - 2.04) / (3.00 - 0.00) = 0.320
Singapore GDP deprivation = (5,079 - 5,039) / (5,079 - 380) = 0.009
Singapore average deprivation = (0.126 + 0.320 + 0.009) / 3 = 0.152
Singapore human development index = 1 - 0.152 = 0.848

3. Population and Development: A Conceptual Framework

It is widely recognized that population and development are closely interrelated: population-related factors influence development variables and are also influenced by them. Furthermore, population goals and policies must be considered to be integral parts of social, economic and cultural development, aiming at improving the quality of life of people.

In order to ensure that population variables are fully integrated into the development planning process, many governments, with ILO and UNFPA assistance, have established a population unit in their planning ministries to be responsible for integrating population policies and programmes with related social and economic development policies and programmes. Because of the small size of most Pacific Island countries the 'Population Focal Point' or 'Unit' might consist of only one or two professionals. However, it is very important that such a contact point is established, to play an advocacy role for the importance of population-related variables in the various sectoral ministries engaged in the development effort, as well as to serve as a source of information about population-related matters. Where the country is attempting to implement an explicit population policy, the Population Unit should be the overall co-ordinator of programmes and be earmarked to monitor and evaluate their implementation via the chairing of an inter-sectoral National Population Co-ordinating Committee.

Socio-economic and demographic interrelationships must be fully considered, or integrated, in the formulation of development policies and programmes in order to achieve a country's development goals and objectives. These may be expressed in its Development Plan in terms of sustained economic growth, human resources development, including such concerns as employment promotion, education and health expansion, and adequate nutrition, etc and a more equitable distribution of the fruits of development among individuals, social groups, geographic areas, etc. These objectives may be ultimately specified in terms of both socio-economic and demographic outcomes during the plan period e.g. a target growth rate of the economy of 5% p.a., a reduction in the IMR from 50 to 30, a reduction in the TFR from 5.6 to 3.6, and a decline in the rate of population growth from, say 2.4% p.a. to 1.8% p.a.; and a reduction in the annual rate of urbanisation from 6% to 3%. The role of development planning is then to formulate policies and programmes to achieve these goals and objectives. A more explicit statement about demographic-related goals, targets and programmes might be incorporated in a formal Population Policy.

The formulation of policies and programmes must be based on a comprehensive understanding of the real world in the form of a conceptual framework which takes account of various socio-economic and demographic interrelationships. Figure 1 illustrates the concept of integration at the macro level and incorporates three constituent elements:

• The Development Objective
• The Behavioural Model
• The Development Policies and Programmes

As stated above, development objectives in the Development Plan will be specified in concrete, quantitative targets, as socio-economic and demographic outcomes. For example, a principal objective may be to raise the overall level of employment (the demand for labour) as well as to increase the activity rates of women (the supply of labour), in addition to diversifying the occupational or sectoral distribution of women's employment. Educated youth unemployment may be another problem area such that a development objective may be to raise the growth of employment of teenagers, particularly those found outside of the main urban centres. Clearly, the success of such targeted employment goals to raise the activity rates of vulnerable social and demographic groups will enhance the goal of increased equality in the overall distribution of income in the economy.

^{Figure 1:
Framework for viewing the integration of population and development planning at the macro level}

Development Policies	Behavioural model	Development Objectives
Economic Policies (X)     Demographic Policies (Y)		Desired socio- economic- demographic outcomes

DO = Demographic outcomes             EP = Socio-economic processes
DP = Demographic processes             EO = Socio-economic outcomes
^{Source: Herrin, Parkdoko, Tan Boon Ann and Hongladorom (1986)}

^{The next or second stage of integrating population factors in development planning is the behavioural model which serves as a framework for viewing such socio-economic and demographic interrelationships at the broad general or macro level. This framework is described in figure 2.}

<sup>Source: Herrin, Pardoko, Tan Boon Ann and Hongladorom (1986)

Sectoral Planning</sup>

 
^{Source: Herrin, Pardoko, Tan Boon Ann and Hongladorom (1986)}

^{Figure 4: Simplified framework for analysing the impact of population and development activities on household behaviour}

^{Source: Herrin, Pardoko, Tan Boon Ann and Hongladorom (1986)}

^{Figure 5: A simple framework for analysing the impact of development programmes on fertility behaviour}