Journal Issue

Is there a tradeoff between growth and basic needs?: Evidence from 83 developing countries indicates that policies to meet basic needs can aid growth

International Monetary Fund. External Relations Dept.
Published Date:
June 1980
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Norman L. Hicks

While the developing countries have had substantial increases in output during the past 25 years, it has been widely recognized that this growth has often failed to reduce the level of poverty in their countries. Various alternatives have been proposed to redress this problem—including strategies aimed at increasing employment, at developing rural areas, at redistributing the benefits of growth in favor of low income groups, and at meeting the basic needs of the poor. An approach that concentrates on meeting basic needs emphasizes improvements in health, nutrition, and basic education—especially through improved and redirected public services, such as rural water supplies, sanitation facilities, and primary schools. It has been argued that the direct provision of such goods and services affects poverty more immediately than those approaches that rely on raising the incomes and the productivity of the poor (see Paul Stree ten’s article, “From growth to basic needs,” in the September 1979 issue of Finance & Development).

The critical question for the individual country is: will the provision of basic goods and services slow down a country’s growth rate? In other words, is there a tradeoff between growth and basic needs? From a theoretical standpoint there may be no necessary reason for such a tradeoff; but the evidence is not conclusive. Countries which have emphasized basic needs, such as Burma, Cuba, Sri Lanka, and Tanzania, may be seen to have done so at the cost of lower growth rates of output. On the other hand, one can point to countries such as Taiwan, Korea, and Singapore, which have both grown relatively rapidly and made commendable progress in providing social services, reducing poverty, and improving the distribution of income. The issue is complicated by the many factors which affect growth other than the elements emphasized in theory: that is, the allocations of national resources between savings and consumption or between social services and other “productive” sectors. The true impact of an investment program oriented toward basic needs thus becomes very difficult to evaluate.

The debate

Proponents of a basic needs approach argue that the direct provision of essential goods and services is a more efficient and more rapid way of eliminating poverty than an approach based on hopes that the benefits of increased national growth will eventually reach the poor. While supporting efforts to raise productivity and income, they emphasize that these alone may be neither sufficient nor efficient. Their case rests on their experience that:

  • the poor tend not to spend incremental income wisely or efficiently, since they may not be good managers or are not sufficiently knowledgeable about health and nutrition;
  • there is serious maldistribution of incomes within households which cannot be overcome by raising family incomes but which can be corrected by the direct provision of goods and services to the neglected members;
  • some basic needs—such as water supplies and sanitation—can only be met efficiently through public services; and
  • it is difficult to formulate policies or investment strategies to increase the productivity of all of the poor in a uniform way.

The argument against directly providing for basic needs is based on two main contentions. First, transfers of essential goods and services result in increasing the consumption level of the poor at the cost of eventually reducing the net level of investment and saving in the economy and therefore the welfare of everybody. Second, the poor would be better provided for in the long run through the higher incomes realized by greater overall investment under a more conventional, growth-oriented development strategy. Meeting basic needs is seen as a strategy providing for a temporary consumption transfer to the poor, and not as a transfer of capital resources that would result in a permanent improvement in their condition.

The concept that basic needs can be better met in the long run through increased output appears faulty for two important reasons. First, the basic needs of the poor can be met in ways that have little or no direct effect on national levels of investment and growth—by reducing the consumption expenditures on nonessentials of the poor and the rich or by redirecting the expenditures of the public sector from nonbasic to basic needs activities. Second, it seems quite likely that expenditures on basic needs improve the productivity of human resources, and can therefore be considered a form of long-term investment in human capital. The question then becomes one of identifying the degree to which expenditures on basic needs actually result in permanent improvements in human capital, and whether economic returns to this form of human investment are higher than those from other kinds of investments available to developing countries.

Conflicting evidence

There is a considerable body of literature which attempts to identify the economic returns from improvements in human capital. In developed countries, considerable attention has been given to the concept of “growth accounting.” In this approach, the growth of total output (measured by gross national product (GNP)) is broken down into components relating to the growth of factor inputs (land, labor, and capital) and an unexplained “residual” which captures productivity changes of an unidentified origin. While the earliest efforts in growth accounting can be traced back to George Stigler (1947), the definitive work remains that of Edward Denison (1967, 1974, 1979).

Denison’s latest estimates show that less than 60 per cent of the growth in GNP in the United States can be attributed to the increase in traditional factor inputs—labor and capital primarily—while the remainder is the result of economies of scale, improvements in resource allocation, and a large residual attributed to human capital, which is labeled “advances in knowledge.” Education is considered by Denison to be a factor input which alone accounts for 14 per cent of the growth of GNP between 1929 and 1976. If education is combined with the residual advances in knowledge, then the contribution of human capital to growth would be about 38 per cent. Attempts to apply the same technique to developing countries (Krueger, 1968) tend to show similar results.

There is some question, however, whether the residual can be attributed to improvements in the stock of human capital. It could represent errors in the calculations of other variables, the omission of other important factors, or simply a faulty assumption about the nature of the underlying production function. While growth accounting attributes an important role to human capital in explaining growth, it does not necessarily prove that human capital is important. Thus it is not a completely reliable way to measure the contribution of human capital to the growth process.

An alternative way of assessing the impact of improvements in human capital is to measure the rate of return from education. This can be done by estimating the lifetime earnings of people with various levels of education, compared to the private and social costs of education, which include earnings forgone while at school. In general, these kinds of studies have found high rates of return from investment in education particularly from primary education in developing countries. A survey of 17 developing countries by Psacharopoulos (1973) found an average return of 25 per cent for primary education. These returns range, however, from a low of 6.6 per cent (Singapore, 1966) to a high of 82 per cent (Venezuela, 1957).

There are considerable conceptual difficulties in measuring such rates of return on investments in human capital. The returns may be overstated because they capture the “screening” effect of higher education, which means that more highly educated people receive better paying jobs regardless of any true differentials in productivity. The high unemployment rate often found among highly educated people in some developing countries suggests that investments in education may not always raise productivity, particularly in those countries already possessing a large supply of educated persons. Several studies have questioned the utility of education investments in development. For instance, Correa (1970) found in a study of a group of Latin American countries that while health and nutrition were very important factors in GNP, improvements in education appeared to have no impact at all. Nadiri (1972) concluded from a survey of the published literature that education was not very useful in explaining differences in growth rates between developing countries, although it did seem to explain variations in productivity within countries over time. Thus, the evidence on the role of human capital, particularly education, in affecting the growth of output in developing countries is not definitive or measurable. Furthermore, the concept of human capital improvements covers areas (higher education is an example), which are not considered to be as relevant to a basic needs approach, and vice versa.

Another way of measuring the importance of human capital is to look at the statistical correlations between the provision of basic needs and the growth rates in a large number of countries. The problem with simple correlations is that they cannot identify the links between basic needs that have been met and growth. Better provision of basic goods and services is just as likely to be a result of higher incomes, as its cause. At the same time, growth in income is clearly going to be affected by factors other than those related to the provision of basic needs. Thus, one has to isolate the meeting of basic needs from other factors which can be considered important determinants of growth, in order to avoid giving too much weight to the basic needs variables.

Measurement problems

We have no easy measure, however, of progress in meeting basic needs. A variety of social indicators can be used, but using them often presents conceptual problems. Some indicators reflect results, while others—such as population per doctor and school enrollments—measure inputs. Some indicators measure the average level of social progress for the whole society, while others are based on a “have, have-not” principle. Thus, the percentage of households with access to clean water can accurately capture the numbers without such service. By contrast, an average of the calories consumed per capita as per cent of requirements is quite misleading, since it combines the overconsumption of the rich and the underconsumption of the poor. Likewise, figures on average life expectancy, or average infant mortality, do not give us any idea of the range between the rich and the poor. Two countries with identical average statistics for infant mortality, for instance, could have quite different infant mortality rates for their least favored groups. It would be more useful if social indicators provided data separately for different income groups within a population. There is no reason why we could not construct distribution statistics for social indicators similar to our measures of income distribution.

Until better indicators are produced, however, we are forced to use what we have readily available. It seems appropriate to use life expectancy at birth as one crude measure of the effectiveness of a country’s success in providing for basic needs. This single measure can encompass the combined effects on mortality of health care, clean water, nutrition, and sanitation improvements, although it is admittedly an average of country experience with no feel for how well these have been provided for different groups within the population. Progress in meeting needs for primary education can be measured by adult literacy—a better indicator than primary school enrollment, since it is oriented toward effects rather than efforts. These two indicators—life expectancy and adult literacy—give crude but fairly useful measures of progress in meeting basic needs. Both indicators are generally available for most developing countries on a fairly reliable basis, which is not true for some alternative measures, such as infant mortality.

But even if we use these selected social indicators to measure progress in meeting basic needs, the problem of identifying causality remains. Is the progress in meeting basic needs shown by these indicators a result of growth in output, or is it one of the causes? One way to overcome this problem is to look at the data for growth rates of different countries compared to the levels of basic needs at the beginning of a particular period. If past achievements in meeting basic needs now require high levels of consumption expenditures, the data then should show that good basic needs performance has been associated with low growth. On the other hand, if provision of basic needs leads to an improvement in people’s productivity, the indicators should show that basic needs are related to higher growth.

Comparative evidence

The simplest way of identifying the relationship between the provision of basic needs and growth is to examine the record of countries that have grown very rapidly in the past and to compare their basic needs performance—measured by life expectancy and adult literacy—-with that of the average country. Table 1 presents data for the 12 fastest growing countries between 1960 and 1977 (excluding the oil exporting countries and those with populations of under one million). The average per capita growth rate of these countries—5.7 per cent per annum—was substantially higher than the average of all 83 countries in our sample. Further, the populations of this group of countries clearly had above-average life expectancy at the beginning of this period: 61 years, compared with an overall average of 48 years in all 83 countries.

Table 1Economic growth, life expectancy, and literacy for selected countries

rate 1960-771
Life expectancy

Deviation from

expected levels

of life

Adult literacy

Deviation from

expected levels

of literacy, 19603
(In per cent)(In years)(In per cent)
Hong Kong6.365.06.570.06.4
Average top 12 countries5.761.05.664.712.0
Average—all countries42.448.0-.037.6.0
Source: World Bank, World Development Indicators, 1979.

Growth rate of real per capita GNP.

Deviations from estimated values derived from an equation where life expectancy in 1960 (LE) is related to per capita income in 1960 (Y) in the following way: LE = 34.29 + .07679 Y .000043 Y2 (R2 = .66).

Deviations from estimated values derived from an equation where literacy in 1960 (LIT) is related to per capita income in 1967 (Y) in the following way: LIT = 9.23 + .1595 Y - .0000658 Y2 (R2 = .44).

Data for average growth rates and life expectancy refer to a sample of 83 countries, while that for literacy covers 63 countries.

Source: World Bank, World Development Indicators, 1979.

Growth rate of real per capita GNP.

Deviations from estimated values derived from an equation where life expectancy in 1960 (LE) is related to per capita income in 1960 (Y) in the following way: LE = 34.29 + .07679 Y .000043 Y2 (R2 = .66).

Deviations from estimated values derived from an equation where literacy in 1960 (LIT) is related to per capita income in 1967 (Y) in the following way: LIT = 9.23 + .1595 Y - .0000658 Y2 (R2 = .44).

Data for average growth rates and life expectancy refer to a sample of 83 countries, while that for literacy covers 63 countries.

This would seem to demonstrate that improving the provision of basic needs can augment the rate of growth. While this may be true, the data in the table contain a considerable bias. The countries that grew the fastest in the 1960-77 period were also countries which already had above-average levels of income. Since levels of income and life expectancy tend to be closely (but not perfectly) correlated, it is not surprising to find that the statistics for our 12 countries show above-average life expectancy.

To overcome this bias, an equation was established to relate life expectancy to income and to establish the “expected” level of life expectancy for every country. Better than normal performance on life expectancy could then be measured by the deviation between the actual and the expected levels. In a sense, this formula adjusts the level of life expectancy for the level of income. These deviations are shown in the third column of Table 1. The 12 countries in the sample have life expectancies that are, on average, 5.6 years higher than what normally would have been expected on the basis of their relative income level. Consequently, there does seem to be a positive association between life expectancy and growth, even when allowing for the fact that some of the more rapidly growing countries are also those at more advanced stages of development.

Adult literacy is another useful measure of a basic needs performance. Table 1 shows that in the rapidly growing countries, about 65 per cent of adults were literate in 1960, compared with about 38 per cent for the sample of 63 countries. Even when adjusted for income differences, literacy levels in the rapidly growing countries were about 12 percentage points higher than in the other countries at the beginning of the period.

The preceding analysis suggests that meeting basic needs may contribute significantly to growth, but it does not prove that the approach is a sufficient condition for high growth. In Table 2, we turn the question around and look at the 12 countries that have the highest deviation from expected levels of life expectancy. Many of the same countries shown in Table 1 appear here, namely, Taiwan, Korea, Thailand, Hong Kong, and Greece. In addition, there are a number of other countries which have done well in terms of life expectancy but have not had exceptionally high growth rates during the period, such as Sri Lanka, Paraguay, the Philippines, Burma, and Kenya. Nevertheless, the average growth rate for this second group of 12 countries—4.0 per cent per annum—is still considerably higher than the average for the larger group.

Table 2Growth and life expectancy, selected countries
CountryDeviation from

expected level

of life


(In years)
Growth rate.


(In per cent)
Sri Lanka22.51.9
Hong Kong6.56.3
Average, 12 countries9.14.0
Average, all countries02.4
Source: World Bank, World Development Indicators, 1979.Note: For explanation of variables, see Table 1.
Source: World Bank, World Development Indicators, 1979.Note: For explanation of variables, see Table 1.

One might argue, however, that the simple statistical analysis presented here is inadequate for drawing firm conclusions. The growth performance of countries is dependent on a variety of factors, such as the level of investment, export earnings and capital flows, and the general nature of development policies pursued.

The influence of these factors, as well as the emphasis on basic needs, can be combined and analyzed using multiple regression techniques on the cross-country data. This has been done for the period 1960-73 (see Hicks, 1979), regressing the growth rate of per capita GNP on the investment rate, the growth rate of imports, and the levels of either literacy or life expectancy in 1960. (The growth rate of imports combines the effects of export growth and capital flows.) This analysis concluded that the basic needs variables were significantly related to the growth rate, even after allowing for the influence of the other variables. It was found that countries which had life expectancies ten years higher than expected tended to have per capita growth rates 0.7 to 0.9 percentage points higher. Thus the more sophisticated techniques confirm the simpler ones shown here, which already concluded that those countries which do well in providing for basic needs tend to have better than average performance in terms of economic growth. This would also seem to suggest that a basic needs emphasis in development, far from reducing the rate of growth, can be instrumental in increasing it.

It would appear that economists who formerly focused on human capital may have concentrated too narrowly on one aspect of human capital, namely education. It seems possible that other aspects of a basic needs approach to development, which aim to improve the health and living conditions of the poor, should also be considered as building up a country’s human capital. Exactly how health and related basic needs improvements help increase productivity and growth in the economy is difficult to pinpoint. The most obvious relationship is that healthy workers can produce more, work harder and longer, and so on. In addition, healthy students are apt to learn more. Improved health conditions reduce the waste of human and physical resources which results from the bearing and raising children who die before they reach productive ages. The prospect of a short life expectancy reduces the potential gain from long years of schooling. These kinds of gains in productivity from investments in health and education are now being recognized as important as the returns from investments in the more standard forms of physical capital. In other words, investing in people may be a good way to both eliminate the worst aspects of poverty and to increase the growth rate of output.

Related reading

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    E. F.DenisonWry Growth Rates Differ: Postwar Experience in Nine Western Countries (Washington, D.C.: The Brookings Institution1967). Accounting for United States Economic Growth 1929-1969 (Washington, D.C.: Brookings Institution1974). Accounting for Slower Growth (Washington, D.C.: Brookings Institution1979).

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    NormanHicksGrowth vs. Basic Needs: Is There a Trade-Off?World Development Vol. 7 (November/December1979) pp. 98594.

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    DavidMorawetzTwenty Five Years of Economic Development (Washington, D.C.: The World Bank1977).

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    F.Stewart and PaulStreetenNew Strategies for Development: Poverty, Income Distribution and GrowthOxford Economic Papers 28 (1976).

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    G. J.StiglerTrends in Output and Employment (New YorkNational Bureau for Economic Research1947).

    PaulStreetenBasic Needs: Premises and Promisesjournal of Policy Modeling 1 (1979) pp. 13646.

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