Journal of Economic Perspectives—Volume 7, Number 1—Winter 1993—Pages 133–150

Human Developmentin Poor Countries:On the Role of Private Incomesand Public Services

Sudhir Anand and Martin Ravallion

Development is often taken to mean rising incomes. A still common viewequates development with growth in average income, though therehas been a shift in emphasis since the 1970s to a focus on the

distribution of incomes. Discussions of the "goals of development" now oftenemphasize the reduction of poverty, rather than raising average incomesper se (for example, see World Bank, 1990, 1991). The role of socialservices—particularly basic health and education—has also received greateremphasis in the 1980s, although these services have been viewed mainly asinstruments for raising the incomes of the poor (for example, see World Bank,1980). In all these approaches, income growth of one sort or another is whatdevelopment is all about.

A rather different view of the meaning of development has recently foundexpression in the 1990 Human Development Report (HDR) produced by theUnited Nations Development Programme (UNDP).1 A conceptual underpin-ning for this approach can be found in the work of Amartya Sen (1977b, 1984,1985a,b, 1987a,b), which has clearly influenced HDR. The essence of this viewis that human development—what people can actually do and be—is the

1This approach relates to earlier works on basic needs (for example, Pigou, 1952; InternationalLabour Office, 1976; Streeten et al., 1981) and on the quality of life (for example, Sen, 1973;Adelman, 1975; Grant, 1978; Morris, 1979), though the focus is more integrated and less ad hoc inthe concept of "human development."

• Sudhir Anand is Fellow of St. Catherine's College, and Research Associate of theInstitute of Economics and Statistics, both in Oxford, England. Martin Ravallion isPrincipal Economist, Poverty and Human Resources Division, Country EconomicsDepartment, World Bank, Washington, D.C.

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overriding purpose of economic development. Underdevelopment is viewed asthe lack of certain basic capabilities, rather than lack of income per se.

We do not aim here to advocate one of these approaches over the other,but rather to explore their implications for development policy. For theincome-based approach, those implications have been explored at some length(for example, see World Bank, 1990). The policy implications of the humandevelopment approach—and whether they are appreciably different fromthose of the traditional approach—seem to be less well understood. What doesit imply about the role of economic growth and, in particular, about reducingincome poverty? Should development priorities shift toward the provision ofpublic services in poor countries, even if such a shift is at the expense of incomegrowth?

Ends and Means

It is common to equate a person's "well-being" with his or her commandover commodities. The precise measure used in practice can vary; it may simplybe money income, or it may be "money metric utility," whereby money incomeis adjusted for differences in the prices faced in a way which is consistent withan ordinal representation of individual preferences over alternative commoditybundles.2 The common element is that command over commodities is whatmatters in assessing well-being.

This approach has come under attack from Sen (1977b, 1984, 1985a,1987a,b). Sen is critical of the use of both "opulence" (income, wealth orcommodity possession) and "utility" (whether interpreted as happiness, desirefulfillment, or simply choice) as measures of well-being, arguing that theyconstitute the wrong space in which to make such assessments.3 Instead, heargues that "well-being" has to do with being well, which in the most elemen-tary terms is about being able to live long, being well-nourished, being healthy,being literate, and so on. As Sen (1987a, p. 25) puts it, the "value of the livingstandard lies in the living, and not in the possessing of commodities, which has

2 Preferences over commodities can generally be represented directly (or over income and pricesindirectly) by means of a scalar-valued function. But such functions are ordinal, and have nocardinal significance, reflecting simply the underlying binary preference ordering. There is obvi-ously something of a leap involved in using the term "utility"—which is normally associated withconcepts like "happiness" or "satisfaction"—for such a scalar-valued function. But to the extentthat a higher level of the function indicates a preferred commodity bundle, one can think of"utility" as arising from the fulfillment of an individual's desires.3The basis of the problem is discussed in the early writings of Sen (1970, 1977a,b). For example,Sen (1970) points out the conflict between traditional welfarism in its weakest form—the Paretoprinciple—and ensuring a minimum degree of liberty for individuals. The informational bases ofboth "utility" and "real income" in social choice theory are shown to be deficient in dealing withachievements, freedoms, and capabilities (which involve non-utility or non-income information).Hence the need to go beyond traditional welfare economics in making assessments of the livingstandard.

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derivative and varying relevance."4 What is valued intrinsically are people'sachievements—their "beings" and "doings"—or their "capabilities" to func-tion. Opulence can have importance as an instrument for expanding capabili-ties,5 while utility can provide evidence of achievement. But Sen's argument isthat the space in which well-being should be evaluated has to be more directlylinked to what matters most—not its instrumental antecedents nor its evidentialcorrelates.

Capabilities cannot, in general, be assessed by looking solely at people'sachievements, except perhaps in the case of certain basic capabilities such asthose related to avoiding mortality, morbidity and hunger. People will tend togive priority to such elementary functionings and will value them in a similarway. In assessing the well-being of people in developing countries, the humandevelopment approach thus leads one to ask: Do they live long? Do they escapepreventable morbidity? Do they avoid mortality during infancy and childhood?Do they avoid illiteracy? Are they free from hunger and undernourishment?Do they enjoy personal liberty and freedom?

The contrast between the mainstream, income-centered approach to devel-opment policy and the capabilities approach may be illustrated most sharply byconsidering their respective treatments of ends and means. The income-centered approach assesses investment in "human capital"—including health,nutrition, and education—entirely in terms of the extra income or output theinvestment generates, judging it to be worthwhile if the rate-of-return exceedsthe capital cost.6 By contrast, proponents of the capabilities approach wouldargue that the enhancement of people's ability to read and write, or to bewell-nourished and healthy, should be considered ends in themselves, even ifthe conventionally measured economic return to investment in literacy, orimproved food intake and health care, is zero.

The human development approach should also be contrasted with theso-called "basic needs" approach, which was advocated by the InternationalLabour Office in the 1970s. Although both approaches move away from valuingincome per se, the basic needs approach is still firmly centered on commoditypossession (minimum requirements of food, and the like) rather than on

4The need for commodities to achieve any specified living conditions can, in fact, vary greatly withvarious physiological, social, cultural, and other contingent features. For example, "To reach thesame level of nutrition as another, one needs a larger command over food if one has a highermetabolic rate (or a larger body frame), or if one is pregnant (or breast-feeding), or if one has adisease that makes absorption more difficult, or if one lives in a colder climate, or if one has to toil alot, or if food has other uses (such as for entertainment, ceremonies or festivals)" (Sen, 1987a,p. 16).5As noted by Sen (1987b, p. 3) and UNDP (1990, p. 9) this was recognized at least as far back asAristotle. In his Nicomachean Ethics, Aristotle clearly distinguished the means from the ends: "Thelife of money-making is one undertaken under compulsion, and wealth is evidently not the good weare seeking; for it is merely useful and for the sake of something else" (Barnes, 1984, p. 1732).6There is a large literature on this topic; for recent surveys, see Schultz (1988), Psacharopoulos(1988) and Behrman (1990).

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functioning achievements.7 The human development approach focuses on thestate of existence of people—the lives they lead—not the detached objects theyhappen to possess.

From Theory to Policy

The way one conceptualizes the objectives of public action can greatlyinfluence the nature of that action. The capabilities approach offers a newperspective on a range of policy issues (for example, Sen, 1985a,b, 1987a;Drèze and Sen, 1989). We cannot go into all these issues here; for example, wewill not discuss what public action can do to promote people's capability toenjoy personal liberty and freedom, or to "take part in the life of the commu-nity." Rather, we want to focus here on the relative importance of privateincomes and public services in attaining some very basic human capabilities,ones which are still woefully lacking in most poor countries.

The proposition that incomes matter is not disputed in the literaturediscussed above; nor is it particularly contentious that other things matterbesides incomes. However, there is considerable room for debate over theextent to which private incomes matter relative to public services, and aboutthe reasons why incomes matter.

Advocates of the human development approach tend to attach a higherweight to supplying public services relative to expanding private incomes—asinstruments of public action—than do proponents of an incomes-centered viewof the objectives of development. A comparison of the 1990 Human DevelopmentReport (HDR) (UNDP, 1990) and the 1990 World Development Report (WDR)(World Bank, 1990) is instructive on this difference. The WDR views thereduction of poverty—in terms of incomes, though not solely in those terms—asthe fundamental objective of development. A high weight is attached by theWDR to economic growth as the instrument for reducing poverty, though animportant role is also seen for certain public services. The HDR takes a ratherdifferent view of what development is about, broadly consistent with the"capabilities" approach advocated by Sen.8 This leads the HDR to view thepublic provisioning of social services as a leading instrument for human devel-opment, and relatively less emphasis is given to economic growth tout court.

7Although the focus on the possession of vitally important commodities is a move in the rightdirection in understanding the living standard, there is need for clarity in foundational justification.Are basic needs important because their fulfillment contributes to utility—as argued by Pigou(1952, p. 759)—or are they best seen in terms of requirements for minimal levels of basiccapabilities? On various aspects of this issue, see Streeten (1984) and Stewart (1985).8There are, of course, differences in emphasis between HDR and Sen's capabilities approach. Forexample, there is greater concern with issues of personal liberty and with the general perspective offreedoms in Sen (1970, 1977b, 1987a,b). Also in general, the fit between theory and application isnot quite so easy in this complex field. For example, the HDR's specific measurement of humandevelopment is not consistent in every respect with capability-based reasoning. Thus HDR com-bines three indicators in its construction of the human development index: life expectancy, adultliteracy, and "command over resources needed for a decent living." However, the last indicator

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While neither approach denies that both private incomes and publicservices matter (that would surely be hard to do), their difference in emphasiscould entail different development policies for an economy. However, theempirical support for these differences in policy emphasis is not always clearfrom the writings of these two schools.9 A number of issues remain unresolvedconcerning the implications for development policy.

The proper balance between public and private provisioning is a long-standing and difficult issue in all of economics. If only a weak link existedbetween "income poverty" and "capabilities," relative to other factors, then thehuman development approach would clearly imply less emphasis on privateincomes, except insofar as growth facilitates the financing of public support. Onthe other hand, if private incomes are a powerful instrument for expandingcapabilities, then a focus on income poverty may be justified from eitherperspective.10 That empirical question needs to be addressed fully before anassessment can be made of the policy implications of the human developmentapproach.

However, the existing evidence is inconclusive. Over the last 10 years, anumber of studies have used household or individual level data to look at thedeterminants of health and educational outcomes in developing countries.11

Methodologies and data have differed greatly amongst these studies, and theusual estimation problems in micro-econometric work cloud inferences. Whilesome studies predict (say) a positive effect of rising incomes on health, othersindicate little or no effect; the same is true of the availability of public services.12

For the present purpose, one problem in drawing lessons from thisliterature is that much of the micro-econometric evidence has not focused onthe capabilities concept, but rather on consumption of one sort or another. Forexample, one important strand of the empirical literature has looked at the

blurs the distinction between ends and means: it continues to be based on income even thoughvarious adjustments are made to it (such as purchasing-power-adjusted real GDP per capita, and alogarithmic transform applied to reflect diminishing returns in converting income into a decentliving standard). Hence it is not directly an indicator of any achievement or functioning, but ameasure of what can be done with income. For further discussion of the human developmentindex, see Anand (1991).9For example, see Ravallion's (1992) assessment of the arguments made by Drèze and Sen (1989).

Indeed, it may be useful to view both income poverty reduction and direct public support asroutes to "entitlement" creation—and through that to capability expansion or protection (Sen,1981a; Ravallion, 1987). The balance between the two instruments will depend on the capabilityand circumstances in question. Thus, for example, Drèze and Sen (1989) emphasize incomegeneration through workfare programs—rather than public support involving the direct provision-ing of food—in dealing with the capability to avoid starvation in famine situations.11 For a good recent survey of this literature, see Behrman (1990).12Compare, for example, the results on the impacts of local public health services on child mortalityobtained by Rosenzweig and Schultz (1982) for urban Colombia with those of Wolfe and Behrman(1988) for Nicaragua. Conflicting results are not uncommon even for the same data set; forexample, compare the estimates of the income effects on nutrient intakes obtained by Behrman andDeolalikar (1987) for a sample of households in rural India with those of Bhargava (1991) for thesame sample.

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question of how responsive nutrient intakes (particularly food energy intakes)are to income changes. Some past estimates had found that individual intakesrose quickly with private income, but more recent econometric estimates (usinghousehold level data) have suggested that intakes are relatively unresponsive toincome changes, even for the poor.13

However, this evidence does not imply that aggregate undernutrition is alsounresponsive to income changes. This connection will depend on how changesin intakes are reflected in nutritional attainments, which will depend on thedistribution of nutrient shortfalls relative to needs, as well as other factors.14

Empirically, these factors can easily interact in a way that strengthens theconnection between income and undernutrition. For example, in Indonesiareasonable measures of aggregate undernutrition (which depend on the num-ber of individuals with intake below their requirement and the severity of theirshortfalls) have been found to respond quite strongly to income gains, eventhough intakes at the individual level show relatively small responses(Ravallion, 1990). In this case, a "capabilities" perspective suggests that incomesmay matter more in reducing undernutrition than was otherwise thought, notless.

The rest of this paper will look more closely at the relative importance ofprivate incomes and public services within the human development approach,using some aggregate data both across countries, and for one country overtime. We offer only a few observations of a limited nature, and hope that otherswill take these issues further.

Human Development and Aggregate Affluence

The higher the average income of a country, the more likely it is that itspopulation will be healthy and able to enjoy a full and long life. People in richcountries are also more likely to avoid hunger and illiteracy. In short, theirbasic capabilities tend to be greater than those of people living in poorcountries. The same correlations also appear when one confines attention todeveloping countries. Figure 1 illustrates the pattern observed for 86 develop-ing countries, by plotting life expectancy at birth against consumption percapita (from national accounts with currencies adjusted to give purchasingpower parity using the results of Summers and Heston, 1988).15, 16

This empirical observation may lead one to think that economic growth isthe key to human development. Of course, some countries seem to deviate

I3See, for example, Behrman and Deolalikar's (1987) results for rural south India. For furtherdiscussion and references see Behrman (1990, 1991) and Bouis and Haddad (1992).14For further discussion, see Lipton (1983), Ravallion (1990), and Anand and Harris (1992).1 5There is a fairly large literature on this empirical relationship; see inter alia Preston (1975),Rodgers (1979), Williamson (1984), Goldstein (1985), Caldwell (1986), and Anand (1991).

1 6The fitted values in Figure 1 refer to a regression between life expectancy and private consump-tion per capita which uses the same functional form as the first regression equation reported innote 22.

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Figure 1Life Expectancy at Birth and Private Consumption per Capitafor 86 Developing Countries in 1985

from the pattern in the figure, and we will discuss one such exception ingreater detail below. Here, we want to inquire as to whether the fact that richercountries tend to have better social indicators implies that economic growthshould be at center stage in discussions of how to promote human developmentin poor countries. The answer has great bearing on the policy choices thatcountries face in trying to expand the capabilities of their people.

One problem with interpreting Figure 1 as evidence that income growthpromotes human development is that other variables which may matter a greatdeal are correlated with average incomes. One can think of three distinctexplanations for the observed correlation between human development andaggregate affluence.17

Explanation 1: Capability Expansion through Economic Growth. In this view,economic growth expands capabilities directly. As average incomes increase,this view argues, the population has greater command over the relevant goodsand services—food, health care, medical services, basic education, and soon—which in turn leads to improved health and nutrition, and (hence) lowerrates of mortality and higher life expectancy. All capabilities expand witheconomic growth, thus promoting human development.

Explanation 2: Capability Expansion through Poverty Reduction. This view, acousin of the first, starts from the premise that the relationship between

17Our list is not exhaustive; for example, relative prices may also have an important role. On thelink between infant mortality and relative prices of food staples, see Horton, Kerr and Diakosavvas(1988).

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individual capabilities and income is steepest at low incomes, and quite flatbeyond some point (like the concave cross-country relationship fitted in Figure1). Thus, social outcomes can only be improved appreciably if income poverty isreduced; it is not growth in aggregate incomes that matters, but a reduction inpoverty. On this view, the correlation evident in Figure 1 reflects atendency—although only a tendency—for growth to lead to lower absolutepoverty.

Explanation 3: Capability Expansion through Social Services. This explanationis quite different. By this view, the public provision of essential goods andservices—clean drinking water, sanitation, health care, epidemiological protec-tion, elementary education, and so on—leads to improved social outcomes.Growth only matters if it is used to finance suitable public services. On thisview, the correlation in Figure 1 reflects a tendency for economic growth tolead to better provision of social services.

All three explanations accept that social outcomes like life expectancy orother health achievements are aggregates of individual capabilities, but theydiffer in how they view the link between individual capabilities and income.18

While these three explanations are abstract, they do deliver some empiricallytestable propositions. Both the "poverty reduction" and "social services" argu-ments claim, in effect, that the relationship depicted in Figure 1 is, to someextent, a spurious correlation. If one controlled either for the incidence ofabsolute poverty, or for the public provisioning of social services, depending onwhich argument one is advancing, then the relationship between humandevelopment and aggregate income should vanish.19

Controlling for poverty is not easy. For an empirical test, what is needed isan internationally comparable indicator of differences in the extent of absolute

18The difference between these three theories can be elaborated further using a simple model. Themodel postulates that the capabilities ct of an individual i depend on that individual's commandover privately provided goods, yi, and publicly provided ones, gi; we write this as ci = ci(yi, gi), inwhich the function ci is assumed to be non-decreasing in its arguments. It is possible to derive thisrelationship from prior assumptions about (inter alia) health determinants at the individual level(Ravallion, 1987). The first theory starts with the assumption that ci depends on yi, and adds to thisanother assumption, namely that all incomes will increase with economic growth. The secondassumes more about the relationship between individual capabilities and individual income, namelythat the relationship is steep amongst the poor, and flat above some level of income. Thus it is onlyif growth is sufficiently "pro-poor" (in the appropriate sense) that it will promote human develop-ment. The third and final theory points to the second argument (gi) in the right-hand side of theequation as the important factor, and the link with growth then rests largely on what this entails forsocial provisioning.

One might also ask how well each of these theories can explain another feature of the relationshipbetween social indicators and average income, namely the curvature that is typically evident, andappears in Figure 1. The second theory (Capability Expansion through Poverty Reduction)postulates such a curvature, but at the level of the individual; under certain conditions on thedistribution of income, this will translate into a similar relationship between social outcomes andaverage income. However, the other two explanations offer no particular rationale for the curva-ture. But this may not be a very interesting line of inquiry, since these social indicators areintrinsically bounded variables; life expectancy is bounded above, as well as below, and the same istrue of other social indicators. Once one establishes the direction of the relationship, the curvatureis unavoidable beyond some point.

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poverty. While estimates of poverty measures are available for many developingcountries, the data and estimation methods (including the poverty lines used)differ widely, and their comparability is doubtful. However, research done forthe 1990 World Development Report on poverty (World Bank, 1990) involvedsetting up reasonably comparable statistics on the distribution of consumptionfor 22 developing countries, and estimating the proportion of the population ineach consuming less than $1 per day in 1985 at purchasing power parityexchange rates.20

By further analysis using the results of that study, we have found thataverage incomes are correlated with the incidence of absolute poverty (nega-tively), and with public spending on social services (positively), even whenfocussing solely on developing countries.21 Across these 22 countries, the simplecorrelation coefficient between the log of the head-count index of poverty andlog GNP per capita is – 0.65, while the simple correlation between the log ofpublic health spending per capita and log GNP per capita is 0.91. (Bothcorrelations are significant at the 1 percent level.) These correlations suggestthat these other variables may well explain at least some of the empiricalrelationship between social indicators and average income.

Furthermore, once we control for these two variables, we find that there isno significant partial correlation between life expectancy and average incomeacross these 22 countries; the significantly positive relationship between lifeexpectancy and income vanishes entirely in a regression of life expectancyagainst poverty incidence, public health spending, and average income.22

20The estimates are based on distributions of household consumption or income around the year1985; see Ravallion et al. (1991) on the methodology. The countries are: Indonesia, Malaysia,Philippines, Thailand, China, Bangladesh, India, Pakistan, Sri Lanka, Brazil, Colombia, Costa Rica,Guatemala, Jamaica, Peru, Venezuela, Botswana, Côte d'Ivoire, Ghana, Morocco, Poland, andYugoslavia. The poverty line was adjusted to local currencies using the Summers and Heston(1988) purchasing power parity exchange rates. This is less than ideal for this purpose, but appearsto be the best available option.21Hereafter, we use GNP per capita at purchasing power parity exchange rates as our measure ofaggregate affluence across countries. Alternatively one can use private consumption per capita(similarly adjusted), as in Figure 1. None of our results is materially affected by that choice.22Regressing a suitable nonlinear transformation of life expectancy (LE)—to measure the propor-tionate reduction in shortfall of LE from 80 years (UNDP, 1990, pp. 13–14)—against the log of meannational income across these 22 countries we obtained (with absolute t-ratios in parentheses):

–log(80 – LE) = –6.15 + 0.45 log(GNP per person) R2 = 0.45.(2.07) (4.00)

On adding the poverty index and public health spending per person to this regression, weobtained:

–log(80 – LE) = – 1.08 – 0.28 log(GNP per person)(2.34) (1.34)

– 0.21 log (Proportion of the population consuming(2.36) less than PPP $1 per day in 1985)

+ 0.30 log(Public health spending per person)(3.02)

R2 = 0.71.

With the addition of these two variables, the coefficient on log (GNP per person), in fact, reversessign though it ceases to be significantly different from zero.

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Of course, this does not imply that economic growth is unimportant in expand-ing life expectancy; rather it says that the importance of growth lies in the waythat its benefits are distributed between people, and the extent to which growthsupports public health services.23

The cross-country evidence can also throw some light on the relativeimportance of these two channels connecting aggregate affluence with socialoutcomes. Regression analysis can be used to decompose the elasticity of thesocial indicator with respect to mean income into two components: (i) thatoperating through the reduction in income poverty associated with higheraverage income; and (ii) that operating through the increase in social spendingassociated with higher average income. For life expectancy, our results suggestthat roughly one-third is due to the first factor, and two-thirds is due to thesecond.24

A number of caveats should be noted about these results.1. They are based solely on the patterns observed in this sample of 22

countries. The relative importance of these two channels—poverty reductionversus public health services—is likely to differ greatly from country to country,and over time for the same country. For example, the pattern of growth thathas been observed in Indonesia during the 1980s (in which rising averageincome has been associated with relatively low, and generally falling, inequality)implies an elasticity of the poverty rate with respect to average income which isroughly three times the cross-sectional elasticity we find across this set ofcountries.25

23In Drèze and Sen (1989) a distinction is made between "support-led" and "growth-mediated"strategies of capability expansion, with examples of each given from actual country experiences.Examples of "growth-mediated" security include such countries as South Korea, Hong Kong andSingapore (Ch. 10); each case exhibits powerful evidence of wide distribution of the fruits ofgrowth, and of the use of resources generated by growth in expanding public health services andeducation. Examples of "support-led" security include such countries as China, Jamaica, Costa Ricaand Sri Lanka.24Following note 22, we can safely delete log(GNP per person) from the regression. On doing so,one also finds that the coefficients on the poverty measure and public health spending add up to anumber which is not significantly different from zero (t = 0.08). On imposing this parameterrestriction, we obtain the more parsimonious model giving LE as the following nonlinear functionof public health spending per person below the poverty line:

–log(80 – LE) = –2.88 + 0.19 log(Public health spending per person(24.48) (6.56) consuming less than PPP $ 1 per day)R2 = 0.68.

Thus the relative importance of these two channels linking life expectancy to average incomedepends solely on the relative sizes of the elasticities of the poverty rate and public spending withrespect to average income. Across the same 22 countries, our (OLS) estimates of those elasticitiesare –0.84 (t = 3.80) for the poverty rate and 1.86 (t = 9.59) for public spending. It follows thatclose to one-third of the elasticity of (80 – LE) with respect to GNP per person can be attributed tothe response of the poverty measure to GNP per person, while two-thirds can be attributed to theresponse of public health spending. The same will be true of the income elasticity of LE, at everyvalue of LE.25From the results of Ravallion and Huppi (1991), the elasticity implied by the evolution in thehead-count index of poverty in Indonesia (at a poverty line equivalent to $1 per day) between 1984and 1987 is –2.7 (as compared to –0.8 across countries; see note 24).

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2. The result may not generalize to other indicators of human develop-ment. We did a similar test for the infant mortality rate and under-fivemortality, with very similar results. The basic "health" indicators do seem tobehave this way. But when we did the test for literacy, the positive correlationbetween the social indicator and average income persisted even after con-trolling for poverty and social spending: adding the latter two variables, in fact,had little impact on a regression of literacy against average income.26 The lackof any significant correlation between literacy and public spending on educa-tion could well reflect the fact that a large share of public spending oneducation in developing countries goes to secondary and tertiary levels ofschooling (World Bank, 1990, Ch. 5), whereas the literacy impact should belargely confined to spending on primary level schooling. The lack of anysignificant correlation with poverty may reflect the fact that most people indeveloping countries (particularly poor people) attend publicly-provided freeprimary schools.

3. Treating "social spending" as a single aggregate in the regressions isclearly unsatisfactory; the allocation of that spending across subsectors (preven-tive health care vs. curative, primary education vs. higher levels) undoubtedlymatters a great deal to the impact on social outcomes. Similarly, the povertyrate is only a crude indicator of the relevant aspects of income distributionwhich are likely to matter to how average income translates into social out-comes. The regressions may also suffer from various biases; for example, higherpublic spending on health may be due in part to higher life expectancy, as wellas higher life expectancy being due in part to higher spending on health.

These questions surely merit further research. However, we believe thatthis cross-country evidence does offer some provisional support for the viewthat, at least for basic health, the main channels by which growth promoteshuman development in a typical developing country are through its impact onincome poverty and the public provisioning of health services. Average income

26On regressing a suitable nonlinear transformation of literacy—to measure the proportionatereduction in shortfall of the literacy rate from 100%—against log mean national income acrossthese 22 countries, we obtained:

–log(100 – Literacy) = – 10.21 + 0.95 log(GNP per person) R2 = 0.51.(3.56) (4.55)

On adding the poverty index and public spending on education per person to this regression, weobtained:

–log(100 – Literacy) = –9.51 + 1.12 log(GNP per person)(1.86) (2.56)

–0.27 log(Proportion of the population consuming(1.24) less than PPP $1 per day in 1985)

+ 0.33 log(Public spending on education per person)(1.02)

R2 = 0.56.

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matters, but only insofar as it reduces poverty and finances key social services.This conclusion has an important policy implication: if social expenditures

and the reduction in income poverty are the main forces driving humandevelopment, rather than economic growth per se, then policy intervention canplay a role in promoting human development independently of the promotionof aggregate affluence. Some countries have followed this route, and achievedimpressive social outcomes for their income level. To explore how they havedone this, we now turn to one much-researched "outlier" in the typicalrelationship between social indicators and average income: Sri Lanka.

The Case of Sri Lanka

In academic and policy discussions on the role of government intervention,Sri Lanka has become a test case. The country has exceptionally high achieve-ments in health and education: the life expectancy at birth of a Sri Lankan is 71years; the infant mortality rate is 19 per 1000 live births; and the literacy rate is88 percent. This record owes much to government intervention in the areas ofhealth, education, food subsidies, and other social welfare. In most areas,intervention predates independence in 1948; in some areas it even predates thegranting of universal adult franchise in 1931. The first Health Unit in SriLanka was established in 1926, providing primary health care and control ofinfectious diseases. (Similar interventions did not start in some other develop-ing countries for as much as 50 years later!) Government intervention ineducation effectively began in 1920, with Education Ordinance No. 1.

Annual data for infant mortality, public health spending, and averageincome over the period 1952–81 are plotted in Figure 2 (the estimates aretaken from Anand and Kanbur, 1991, and cover the longest period for which aconsistent time series was available). Real public health spending per capitaincreased rapidly over the first 10 years or so of this period, during which timeaverage income (real GDP per capita) grew little. The infant mortality rate(IMR) fell sharply. However, in the later period real public health spendingshows no clear trend, while incomes grew more rapidly than before, and infantmortality continued its downward trend. In general, the evidence seems broadlyconsistent with the belief that infant mortality trends downward, and that bothincome growth and public spending matter in hastening that trend.

The effects of government intervention in the health and education sectorsin Sri Lanka have been disputed by Bhalla and Glewwe (1986) and by Bhalla(1988a,b). They have challenged the claim by Isenman (1980) and Sen (1981b)that Sri Lanka's achievements have been exceptional relative to its income,especially during the period 1960–78, and they have gone on to question theeffectiveness of government welfare programs in general. These claims havestimulated much debate.27

27For comments on various aspects of the Bhalla and Glewwe arguments, see Ravallion (1986),Pyatt (1987), Anand and Harris (1987), Sen (1988), and Anand and Kanbur (1991).

Human Development in Poor Countries 145

Figure 2Infant Mortality Rate, Real GDP per Capita, and Real Public Health Spendingper Capita, Sri Lanka, 1952-1981

We calculated regressions, using the time-series data from Anand andKanbur (1991), to test the relative effects of income growth and health expendi-ture, much as was done in the previous section for the cross-country regres-sions. However, the only living standard variable for which we have annualdata for Sri Lanka is the infant mortality rate, and we do not have a time seriesof distributional data as needed for estimating the poverty index (Anand andHarris, 1985). So for the time period 1952–81, we used real GDP per capitaand real health subsidy expenditure per capita to attempt to predict infantmortality.28

28Regressing a suitable nonlinear transformation of the infant mortality rate (IMR)—to reflect thelowest IMR of 5 per 1000 live births attained by any country so far—over the full period 1952–81,we obtained the following result:

log(IMR – 5)t = 8.30 - 0.79 log(GDP per capita)t

(3.63) (3.66)

–0.33 log(Public health spending per capita)t

(2.37)

+ 0.41 log(IMR – 5)t–1 R2 = 0.94.(2.37)

To allow the possibility that these variables may have lagged effects we included the lagged value ofthe dependent variable; thus, the regressions assume that the lagged effects can be exponentiallysmoothed. Adding lagged values of income and health spending had little effect on the results. Norwas a time trend significant, and, moreover, all other variables remained significant with the samesigns when the time trend was added. A full set of diagnostic tests on the residuals is available fromthe authors; the regression performed satisfactorily in all tests.

146 Journal of Economic Perspectives

In our calculations, both real average income and public health expendi-ture have significant effects.29 The results are consistent with the cross-sectionresults reported earlier, in that they suggest that public assistance did promotehuman development, independently of what was happening to incomes. How-ever, there are two notable differences with the cross-sectional analysis of theprevious section. First, since we do not have annual time-series data for SriLanka on poverty, we cannot say whether the significance of average income isreally reflecting its negative correlation with absolute poverty, or is an indepen-dent effect. Secondly, it does not appear that growth promoted human devel-opment in Sri Lanka through any indirect effect on public provisioning; indeedthere is no sign in the Sri Lankan time-series data of a positive income elasticityof public health spending.30 The latter observation probably reflects the SriLankan government's quite deliberate policy of supporting a high level ofpublic health spending throughout the period.

This sort of analysis can also shed some light on the role of directintervention versus an incomes-based strategy in reducing the infant mortalityrate. Our estimates show a significant income effect, but this effect seems smallrelative to the effect of public health expenditure. The regression coefficientsimply that (at the mean points) an increase of one Sri Lankan rupee in publichealth spending per capita would reduce infant mortality by 1.1 deaths perthousand; this is 22 times more than the impact on infant mortality from thesame increase in average income.31

29Anand and Kanbur (1991) adopted the Bhalla and Glewwe (1986) specification of the livingstandards relationship (which excludes the lagged dependent variable from the right-hand side) inorder to test for the impact of income and social welfare expenditures in Sri Lanka during theperiods 1960–78 and 1952–81. They found that for the Bhalla-Glewwe period 1960–78, publichealth spending per person had a significant effect in reducing infant mortality, but income had aninsignificant effect; for the full period 1952–81, both variables were significant. For the latterregression, an increase of one Sri Lankan rupee in public health spending per person wasequivalent in terms of its impact on infant mortality to an increase of 33 Sri Lankan rupees inaverage income (GDP) per person.30Regressing public health spending per capita on GDP per capita, and allowing for the serialdependence of public spending, one finds that:

log (Public health spending per capita)t

= 0.58 + 0.78 log(Public health spending per capita)t–1(0.98) (6.68)+ 0.003 log(GDP per capita)t R2 = 0.70.

(0.026)

Nor could we find any sign of higher-order lagged effects of GDP on public health spending.31At mean GDP per capita, the marginal effect on log(IMR – 5) of an increase of one Sri Lankanrupee in health spending per capita is – 0.024; that for the same increase in GDP per capita is– 0.0011. The mean infant mortality rate is 52.8, mean health spending per capita is 13.87 SriLankan rupees, while mean GDP per capita is 746.28 Sri Lankan rupees, the latter two expressedin 1959 prices.

Sudhir Anand and Martin Ravallion 147

Conclusion

The capabilities approach does not deny the instrumental importance ofincome growth, but it does deny its relevance as an end in itself; it sees the basicgoal of development as the enhancement of the capability to live a long,healthy, and active life. Our purpose here has not been to debate the pros andcons of this conceptualization of the objectives of development, but to probesome of its implications for development policy.

We have made a tentative attempt to identify and quantify the relativeimportance of the main channels through which aggregate economic growthmight promote human development. The cross-country evidence assembledhere suggests that, at least for basic health, average affluence matters to theextent that it delivers lower income poverty and better public services. Indeed,the commonly observed positive correlation across countries between life ex-pectancy and affluence vanishes once one controls for incidence of poverty andpublic spending on health. (The same is true for other health indicators.)Though both these variables matter, it is notable that the quantitative signifi-cance of public health spending appears to be sizable. We attribute roughlytwo-thirds of the elasticity of life expectancy with respect to average income tothe positive effect of income on public health spending; the rest is attributed tothe decrease in income poverty that typically accompanies higher averageincomes. Sri Lanka's impressive record of progress in human developmentdespite being a poor country also illustrates what the right sort of public actioncan achieve, independently of income growth.

We have pointed out a number of caveats to these conclusions; for exam-ple, basic health capabilities may well be more responsive to this type of publicaction than other capabilities, such as those related to education. Nonetheless,our analysis does lend qualified support for the view that certain components ofpublic spending can matter greatly in enhancing human development in poorcountries, and that they matter quite independently of what they do or don'tdeliver in terms of reduced income poverty. It is the latter claim that lies at theheart of the difference in policy implications between the human developmentapproach and more traditional income-centered approaches to development.

• For their very detailed and helpful comments on this paper, we are grateful to CarlShapiro, Joe Stiglitz, and Timothy Taylor. We have also had useful discussions with, orcomments from, Ritu Anand, Pranab Bardhan, Robert Cassen, Jean Drèze, PaulGlewwe, Jeff Hammer, Barbara Harriss, Heather Milne, Helena Ribe, Amartya Sen,Lyn Squire, Nick Stern, Frances Stewart, Dominique van de Walle, and Etienne van deWalle. The views expressed are those of the authors, and should not (in the case ofRavallion) be attributed to the World Bank.

148 Journal of Economic Perspectives

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