11
Assessing the Economic Returns to Investing in Youth in Developing Countries
James C. Knowles and Jere R. Behrman
Youth ages 10 to 24 constitute a large proportion of society and have many pressing health, education, economic, and social needs. Despite the critical value of youth to future well-being, countries may invest inappropriately in their healthy development. There may be gaps between current and socially desired levels of investment in youth such that social rates of returns to investments in youth are higher on the margin than for alternative uses of these resources. If so, the case may be strong for using public resources to close this gap.
Some evidence suggests that youth-focused interventions may be cost-effective in improving health, reducing poverty, and providing overall benefits to society. Compared to investments in child health and development, investments in youth often offer a shorter time lag between costs and benefits, thereby having higher benefit-cost ratios, all else equal, if even a relatively modest discount rate is used. Also, in countries in which there has been underinvestment in children, investments in youth may offer an opportunity to “catch up” in the area of human capital investments. Yet full economic analyses of the benefits and costs of investments in youth in developing countries are rare.
This chapter explores the economic case for investments in youth in developing countries by synthesizing the current knowledge of the economic costs and benefits of those investments, analyzing key gaps in the evidence, and identifying priority research needs.
MAJOR THEMES
The current cohort of youth in developing countries is the largest cohort ever, either in the past or predicted for the future, given the stage of the demographic transition which developing countries have experienced on average, though there are variations across countries and regions. This means that whatever investments are made in youth in developing countries have an important impact on a relatively large share of the population. It also means there may be large resource implications and large intergenerational transfers required to make substantial investments in youth.
Major changes have been occurring in the context for youth in developing countries:
-
The world has become more integrated due to economic, technological, and cultural globalization.
-
Developing countries in which hundreds of millions of youth live—particularly in Asia but also elsewhere—have experienced historically unprecedented economic growth, while smaller but still large numbers of youth, particularly in sub-Saharan Africa, Latin America, the Middle East/North Africa, and Central Asia, live in countries with limited economic growth or stagnation, often with high rates of youth unemployment.
-
Human capital investments in the form of formal schooling and training have expanded rapidly, particularly for females, and have facilitated the exploitation of new technologies and new markets by those in whom such investments have been made.
-
At the same time, severe fiscal constraints faced by most developing countries together with reappraisals of governmental roles have led to a growing share of the investments in youth, particularly in health and schooling, being financed directly by households rather than through governments.
-
The health and nutritional environments have changed radically, with rapid transitions in each of these, so that on average there have been substantial improvements as reflected in increased life expectancies, with a shift from contagious diseases and malnutrition that impinge particularly on infants and children to chronic diseases that affect adults and particularly the aging—while at the same time new health problems, most notably HIV/AIDS, have spread rapidly and in some areas have become major threats.
-
Cultural norms and legal changes, often related to globalization, have shifted to more emphasis on gender equalities, individualism, and materialism.
Therefore, it is necessary to rethink and to reevaluate the range of investments in youth in developing countries, inter alia, schooling, training, reproductive health, and investments in other aspects of health, including behavioral changes related to food consumption, physical activity, and substance use. The large cohort size means that there are pressures on resources that are likely to be squeezed due to the large numbers, therefore strengthening the need for the best evaluations possible for any use of scarce resources for investments in youth. The changed context means that the economic returns to different investments in youth probably have altered substantially.
This reappraisal of the economic returns to investing in youth in developing countries must incorporate certain critical features. These include:
-
The inclusion of an appropriately wide range of such investments, including their costs and benefits, within a lifecycle context.
-
The considerable lag in the effects and ultimate outcomes of many of these investments, implying that the choice of an appropriate discount rate may be of considerable importance.
-
Consideration of these investments within the frameworks of standard policy concerns of efficiency and distribution and trade-offs between efficiency and distribution.
-
Sensitivity to problems in making inferences from behavioral data given endogenous choices (selectivity), important unobserved variables, and other measurement and estimation problems.
-
The likelihood that youth investments in one area impact investments and behavior in other areas. For example, reducing youth unemployment might strengthen the demand for schooling. Improving nutrition might improve school performance and reduce the health risks of a youthful pregnancy.
-
Greater clarity regarding matters such as what are costs and what are transfers. The previous literature, for example, often confuses resource costs with transfers, such as welfare payments.
ORGANIZATION OF CHAPTER
Reassessing the economic benefits of investing in youth in developing countries requires frameworks for analysis to organize the existing fragmented and imperfect information. The next section presents such frameworks, then turns to problems of empirical inferences, and a basic framework for policy evaluation. Building on this foundation, the following sections turn to estimates of the rates of return to different investments, with an effort when possible (which is too infrequent) to distinguish between private and social rates of return and between females and males.
The strategy is to identify the time pattern of costs and benefits (requiring the translation of impacts into economic terms if they are not presented in those terms) over the lifecycle from a range of piecemeal estimates, and then to estimate the ratio of the discounted benefits to the discounted costs. The methodology used to measure costs and benefits is sufficiently flexible to incorporate, in a simple way, a wide range of effects of different investments. The robustness of these estimates is explored by relaxing different assumptions related to critical aspects of costs, benefits, and the discount rate. Such estimates are presented for a number of alternative investments in youth, including formal and nonformal schooling, reproductive health, school-based health interventions, and investments to reduce the consumption of tobacco. The final section presents a synthesis and conclusions, with emphasis on what are the highest return investments in youth, how these compare with other investments, and what are the highest priority research areas.
To implement this strategy, we combine the piecemeal information we have been able to find on the effects and costs of investments in youth in developing countries, together with information that permits translating the effects into benefits measured in monetary terms, in order to estimate benefit/cost ratios and internal rates of return. We start with a lifecycle perspective and consider the estimated costs at the time the investments are made and the subsequent effects over the lifecycle, based on the best estimates we have been able to find. For the benefits, we need the effects of investments in youth in areas such as schooling, unemployment, mortality and morbidity, teen pregnancies, and HIV/AIDS, and a way of associating a monetary value to each effect. We then calculate the present discounted values of the benefits and the costs, conditional on assumptions about the discount rate, and the internal rates of return to these investments. Because of the great uncertainties that underlie many of the estimates that we use, we present some alternative estimates based on alternative assumptions for key variables, such as the discount rate. In light of the considerations discussed below about policy motives, we would like to be able to make separate estimates of total benefits and costs and private benefits and costs in order to identify the extent to which there are efficiency reasons for using public resources to increase certain investments. Unfortunately, in most cases this distinction is difficult to make. However, we try to identify cases where the private and social benefits are likely to diverge.
THREE MAJOR CONCLUSIONS
First, there are large gaps in what we know with confidence about many aspects of rates of return to investments in youth in developing countries. Most studies are not sensitive to major estimation problems in
assessing the determinants or the impacts of such investments. Most studies focus only on the impacts and do not consider the costs (including, possible distortionary costs), which also must be understood to assess the economic returns to such investments. In a number of cases, they further confuse resource costs with transfers. Often the impacts are in terms of some objective, such as improved health and nutrition, but not translated into economic benefits by assessing productivity effects or by using the resource cost of alternative means to attain the same effects. The majority of studies, moreover, do not consider whether the policies examined are likely to be the preferred policies for attaining the policy objective. For such reasons there is a considerable research agenda in order to inform policy makers and other interested parties about the economic returns to various investments in youth in different contexts in developing countries.
Second, nevertheless, the available evidence suggests there are some high-return investments in youth in developing countries and there are efficiency reasons for using public as well as private resources for such investments due to inadequacies in markets such as for capital, insurance, and information. Examples of such high-return investments include both supply-side and demand-side investments in formal schooling, investments in adult basic education and literacy targeted to adolescents, investments in some types of school health services (e.g., micronutrient supplementation), investments designed to reduce the consumption of tobacco, and possibly some types of reproductive health investments.
Third, what are relatively high rates of return for different investments in youth depends importantly on the context of such investments. Rates of return to schooling, for example, are likely to be much higher in dynamic contexts in which there are rapid changes in technologies and markets through greater integration into world markets. Many health and nutrition investments tend to yield higher returns in settings in which health and nutrition conditions are poor. The economic returns to reproductive health investments designed to reduce rates of HIV infection increase substantially with HIV prevalence in the targeted age groups.
FRAMEWORKS FOR ANALYSIS
Why Frameworks for Analysis Are Necessary
Good analysis of impacts of investments in youth has tripartite foundations: data, modeling, and estimation. These three dimensions are critically interrelated. Data, of course, are essential for empirical analysis, limit the extent to which analyses can be undertaken, and shape most of the estimation problems. If there were available data from well-designed and well-
implemented experiments,1 associations between observed investments in youth and observed outcomes would reveal the underlying causality directly. But for numerous reasons, including costs and ethical concerns, such experimental data are rarely available.2
Therefore, although there are likely to be high returns for some aspects of policy analysis to increase experimental data, most analysis will continue to be based on behavioral data. Such behavioral data can “speak for themselves” regarding associations between investments in youth and various outcomes. But they generally cannot “speak for themselves” with regard to what observed determinants—policies or otherwise—cause differences in investments in youth or to what extent observed investments in youth cause different outcomes. The problem is that most data result from a number of behavioral decisions taken by households, individuals, bureaucrats, policy makers, and others in light of a number of factors unobserved by analysts.3 Good analysis of what causes household and individual investments in youth or of what effects such investments have is difficult, and requires a much more systematic approach than simply looking at associations among observed variables.
Analytical frameworks permit exploring systematically investments in youth, point to what data are needed for such explorations, facilitate the interpretation of empirical findings, and help to identify some of the probable estimation issues that should be addressed given the data used. The analytical frameworks provided by models are essential if the empirical estimates are based on behavioral data generated in the presence of unobservables such as innate ability and family connections. The problem, for example, is that youth with greater ability and motivation and better innate health may be more productive directly and may also benefit from higher levels of investments. Therefore, it may be difficult to sort out the effect of investments in youth per se as opposed to the fact that such investments are correlated with unobserved abilities, motivation, and innate health.
For such reasons, empirical effects of investments in youth can be analyzed satisfactorily with nonexperimental data only within frameworks that incorporate well behaviors related to the phenomena of interest. To be interpretable, estimates based on behavioral data require some model of the underlying behaviors, though far too often in the literature the models used are not explicit. Those who are not clear about their framework of analysis may think they are revealing underlying truths unconstrained by such frameworks, but instead they are usually making implicit assumptions that may not be plausible upon examination.
Analytical Frameworks for the Determinants of Investments in Youth
Households and the individuals in them are the proximate sources of demands for many investments in youth (e.g., schooling, health, social capital, behaviors that lead to productive lives), given their predetermined assets (i.e., physical, financial, and human, including endowments4), production functions related to human resources, public and private services related to investments in youth (i.e., schools, health clinics), and current and expected prices for inputs used in investments in youth and for outcomes of the investments. Policies, of course, may enter directly or indirectly into this process through a number of channels, ranging from the accessibility and quality of public and private services to the functioning of capital markets for financing investments in youth to the functioning of markets in which these investments are expected to have returns. Becker’s (1967) Woytinsky Lecture provides a simple framework for investments in human resources that captures many of the critical aspects of investments more broadly in youth and which has been widely appealed to in rationalizing empirical studies of the determinants of investments in youth.
In Becker’s framework, human resource investment demands, under risk neutrality, reflect the equating of expected marginal private benefits and expected marginal private costs (both in present discounted terms) for investments in a given individual. The marginal private benefit curve depends importantly, inter alia, on expected private gains in productivity in all of the ways in which the human resource investment may have impacts. The marginal private benefit curve is downward sloping because of diminishing returns to investments in youth (given genetic and other endowments) and because, to the extent that investments in youth take time (e.g., schooling, training, and most other forms of education and social capital, as well as time and other resources devoted to search for better options in labor and other markets), greater investments imply greater lags in obtaining the returns and
a shorter postinvestment period in which to reap those returns. The marginal private cost may increase with investments in youth because of higher opportunity costs of more time devoted to such investments (especially for schooling and training) and because of increasing marginal private costs of borrowing on financial markets. The equilibrium human resource investment for an individual is where the marginal private benefits and the marginal private costs are equalized. This equilibrium human resource investment is associated with an equilibrium rate of return that equates the present discounted value of expected marginal private benefits with the present discounted value of expected marginal private costs. This simple stylized representation of human resource determinants is based on a dynamic perspective, with both benefits and costs not only in the present but also those that are expected in the future and with current period options conditional on past decisions. Thus it is consistent with placing investments in youth in a lifespan perspective, as has been emphasized from a number of perspectives.
The marginal private benefit and marginal private cost curves are likely to vary across youth because of variations in observed and unobserved individual, family, household, and community characteristics, the latter in part related to policies and to markets. Changes in any of these factors can shift these curves and thus the equilibrium investment levels. This simple framework systematizes six critical points for investigating dimensions of the determinants and the effects of investments in youth—and how these relate to policy choices.
First, the impacts of changes in policies may be hard to predict by policy makers and analysts. If households or other entities face a policy or a market change, they can adjust all of their behaviors in response, with cross-effects on other outcomes, not only on the outcome to which the policy is directed.
Second, aggregation to obtain macro-outcomes will average out random stochastic terms across individuals or households. But such aggregation does not average out systematic behavioral responses at the microlevel. Therefore associations among macro-variables can reveal, conditional on the overall context, what those associations are—but not causal effects of processes occurring at the micro-level.
Third, the marginal benefits and marginal costs of investments in a particular individual differ depending on the point of view from which they are evaluated: (1) There may be externalities or capital/insurance market imperfections so that the social returns differ from the private returns, and (2) there may be a difference between who makes the investment decision (e.g., parents) and in whom the investment is made (e.g., youth). The effectiveness of policies are likely to depend crucially on the perceived private effects by private decision makers, and these may differ from the social effects of interest to policy makers.
Fourth, investments in youth are determined by a number of individual, family, community, (actual or potential) employer, market, and policy characteristics, only a subset of which are observed in available data sets. To identify the impact of the observed characteristics on investments in youth, it is important to control for the correlated unobserved characteristics.5
Fifth, to identify the impact of investments in youth, it also is important to control for individual, family, community, market, and policy characteristics that determine the investments in youth and also have direct effects on outcomes of interest.
Sixth, empirically estimated determinants of, and effects of, investments in youth are relevant only for a given macroeconomic, market, policy, schooling, and regulatory environment in which there may be feedback both at the local level and at a broader level.
Empirical Issues: Measurement
To assess the rates of return to investments in youth, we need to (1) measure what we mean by investments in youth and by various outcomes that might be affected by investments, (2) estimate the impact of investments in youth on the latter measures, (3) assign a monetary value to these effects, and (4) measure the costs of these investments. These are not trivial tasks. This section considers some of the measurement difficulties.
Investments in Youth
In the case of schooling, which is an important example, most empirical studies represent human resource investments empirically by years of schooling or highest grade (level) of schooling completed. Though “years” and “grades” of schooling are often used as synonyms, they need not be the same if there is grade repetition, as is widespread in many parts of the developing countries (e.g., in much of Latin America). One of the major costs of schooling is the opportunity cost of time in school, which is greater if there is more grade repetition for a given schooling grade attainment. Putting aside the question of the time spent in school, there are other limitations of grades (years) of schooling as a measure of human resource investments. Probably most important is the implicit assumption that school quality is constant. But empirical measures indicate that school quality
varies substantially, so it would be desirable in assessment of the impact of human resource investments in youth to represent not only the time (grades, years) that they spend in school, but also the quality of that schooling. If both the quantity and the quality of schooling should be included, but only the quantity is included, the likely result is to overstate the impact of time in school and to miss that there is likely to be an important quality-quantity trade-off.
Besides schooling (or education more broadly defined), there are many other investments in the human resources of youth. Such investments may be directed, for example, at improving health, nutrition, information, social capital, and habitual behaviors that lead to desirable outcomes. Similar problems exist in empirical measurement of these variables, as for education. For example, health is often measured by anthropometric indicators, respondent reports, or clinical reports on disease histories; respondent reports on capabilities for undertaking certain activities or tests for doing so; or respondents’ self-assessment of health. Some of these indicators may be good measures of particular disease conditions, but that does not make them (or their inverse) necessarily good measures of what people mean by good health. For another example, social capital is often measured by participation in group activities, but this is at best an imperfect and endogenous indicator of whether one has social capital in the sense of being able to obtain information or resources at times of need.
Outcome Variables
Unfortunately there are many problems in measuring these outcomes.6 For some outcomes that may be affected importantly by investments in youth, data usually used in the social science literature do not include direct measures—self-esteem and learning capacities are two examples. This may mean that important outcomes are missed when assessing the impact of investments in youth.
For some other outcomes there are, at best, imperfect indicators—representing health by health-related inputs (e.g., nutrients), reported disease conditions, curative health care, and preventative health measures (e.g., vaccinations). Some of these measurement problems may be systematic, moreover, resulting in biases in estimated impacts of investments in youth. If, for example, those who have less schooling report less sickness for the same health conditions than those with more schooling (perhaps because the degree of sickness viewed as normal is less with more schooling), impacts of schooling on actual sickness are likely to be underestimated.
For some other measures of outcomes, conventions are used in the literature that may not be sensible. For example, economic gains from reducing mortality are represented at times by the present discounted value of foregone earnings of an individual (e.g., CGCED, 2002). For young individuals, such gains can be considerable. For measuring the purely economic benefits of survivors, however, this seems an overstatement of the economic costs of mortality because such individuals also would have consumed perhaps most or all of their earnings over their lifetime.7 For another example, the economic gains from improving the earnings capacities of individuals are at times measured by the reduction of their demands on governmental social welfare systems for transfers (e.g., CGCED, 2002). But governmental transfers, though perhaps appropriately viewed as costs from a budgetary perspective, are not resource costs in the sense desirable to evaluate policies. There are likely to be some resource savings if social welfare programs are reduced because some resources are consumed in running and financing such programs. But such possible resource savings should not be confused with the amount of transfers involved (and the latter probably greatly exaggerate the true resource costs). For one last example, the gains from reducing crime are at times equated with the amount of losses that crime victims suffer due to crime. But, again, a significant component of the costs so calculated is the transfer from the victim to the criminal, particularly in thefts. The amount of such transfers, once again, is not likely to reflect well the true resource costs of crime. All three of these examples point to substantial difficulties in evaluating benefits and to questionable practices that have been used in some previous studies.
We intend to deal with these difficult questions by evaluating the benefits in terms of the least cost alternative way of obtaining the same objective, along lines implemented by Summers (1992, 1994) in a well-known study of the economic benefits of female schooling. This procedure gives, for hard-to-evaluate outcomes, what society is willing to pay for alternative ways of attaining the same gain—and thus, if the prices that are used in the evaluation reflect the true social marginal costs of resources, the true resource costs of such gains. Note that this method in principle includes both the direct resource cost gains and the indirect resource cost gains. To illustrate the latter, investments in youth that reduce crime may not only have gains from directly improving the safety of citizens, but from indirectly encouraging international tourism and international investments. This procedure accounts for what resources society would be willing to pay for alternative ways of reducing crime in light of all these gains.
Even for the economic outcomes on which there long has been focus in evaluating the impact—particularly of schooling but also of training, health, and nutrition—there are often serious measurement problems. People with less schooling, for example, may remember income less well, may have more problems in assessing the value of their income because more is in kind or self-produced, and may be subject to greater variations in income because of greater fluctuations in employment. If such factors lead to a tendency to underreport their incomes, then all else equal, the returns to schooling will be overestimated due to these systematic errors.
Costs
There are often problems in measuring the costs of investments in youth. The direct budgetary expenditures for particular investments, for example, may be intermingled with many other expenditures in budgets, and therefore be difficult to identify. They also may be spread among various budgets at various levels of aggregation—for example, if health clinic staff salaries are paid by the Ministry of Health, but other recurrent expenditures are paid by local governments, as in the Philippines. Furthermore, there is frequently the problem that the budgetary expenditures do not reflect the true costs because of distortions in market prices, perhaps created by policies. For example, governments may mandate wage rates for some workers such as teachers that may differ from the true scarcity value of such individuals, and then introduce other distortions such as in benefits or job securities in order to attempt to attract enough qualified individuals to these positions. A major problem with evaluating costs, finally, pertains to the nongovernmental costs. Policy makers often ignore these because they are focused on governmental budgets. But the costs of a program to the private sector may be considerable. For example, many programs require considerable amounts of time from private individuals—time that has opportunity costs in the form of other uses. For another example, raising funds for governmental programs in itself may have large distortionary costs.
Measurement of Policies
Including policies among key variables for which there are measurement problems might seem strange. But there are serious measurement issues related to representing policies in empirical studies. For example, there is considerable emphasis on improved outcomes through policies that improve women’s education. But the empirical foundation for these claims in substantial part relates associations between schooling attainment and desirable outcomes. Schooling attainment is not a policy variable, but be-
havioral outcomes that reflect schooling market interactions between household/individual demands for schooling and various aspects of schooling supply that generally are conditioned by policies.
Empirical Issues: Estimation of Effects of Investments in Youth
This chapter is concerned with assessing what we know about the rates of returns to investments in youth in developing countries. But obtaining good empirical estimates of the effects of investments in youth is not easy, in part because of the measurement problems discussed above and in part for other reasons to which we now turn. We first consider the possibility of empirical estimation through experiments and then through econometric methods using nonexperimental (behavioral) data.
Experimental Evaluation
To assess the impact of a particular change, such as increasing use of health clinics, the ideal approach generally is thought to be a double-blind experiment with random assignment to treatment and control groups for the policies of interest over a long enough time period to assess the effects of interest. Experiments have been conducted to evaluate a relatively small number of policies related to youth in developing countries. One example is the Mexican Programa de Educación, Salud y Alimentación, PROGRESA (Education, Health, and Nutrition Program), which was introduced as part of an effort to break the intergenerational transmission of poverty and which included an evaluation sample in which communities were randomly assigned to immediate versus delayed treatment. This design permitted evaluation of the impact of this program on a number of outcomes by comparing changes in treatment households with changes in control households (see Knowles and Behrman, 2003, Appendix A).8
But the possibilities for using such experiments for policy evaluation are limited. First, most such experiments cannot be double blind, with neither the subjects nor the evaluator knowing who received treatment (though some medical experiments can be if, for example, the placebo appears to human senses to be identical to the treatment). That those who are treated know they are treated may create better performance (i.e., the “Hawthorne effect”). That those who are not treated know they are not treated may create incentives to obtain treatment through migration, po-
litical pressure, market purchases, or other means. Second, the argument often is made that new programs cannot easily be introduced at the same time throughout a country, so it may be effective in terms of evaluation, as was attempted with PROGRESA, to introduce them in a random set of treatment communities and only later in a random set of control communities. But if members of the control group know they will eventually be affected by the program and if they can transfer resources over time, they should immediately adjust their behavior to reflect their changed command over resources due to the expected eventual future direct program impact. If so, the comparison between the program and the treatment groups probably underestimates the program impact.9 Third, many experiments cannot be conducted because they are unethical or too costly. Randomly imposing some human resources, particularly related to health and nutrition, but also to education, for example, is likely to be viewed as unethical. Even if some such possibilities are not viewed as unethical, they may be very costly in terms of resources or political costs. Consider the difficulties with the possibility of randomly assigning schooling among individuals in order to obtain better estimates of the effects of human resource investments in youth, as would be desirable for the present study. Fourth, even for the policies for which good experiments can be conducted at a reasonable (resource, ethical, and political) cost, they reveal only the gross changes induced by the experimental treatment conditional on a particular situation, not what would happen in somewhat different circumstances. That is, experiments basically are “black boxes” that reveal the total impact of some change, but do not reveal anything about the underlying structural relations that could be used to infer what the effects of other changes would be. Fifth, there may be insufficient time to observe effects of interest to policy makers. This is a particular problem for youth investments because many of the desired outcomes are expected to occur much later in life.
For such reasons, though it would be desirable to increase experimental evaluation of policies and to assure that the experiments undertaken are of high quality (e.g., with good baseline data and random assignment of treatment versus control groups), there are severe limits on what policies can be evaluated by experimental means. Nevertheless, the experimental design is an important benchmark against which other means of evaluation should
be compared and judged to aid in understanding what probable biases may arise from nonexperimental evaluation.
Econometric Estimates of Impacts of Investments in Youth
Econometric or statistical methods are used to attempt to circumvent some data limitations. The basic point is that there are a number of reasons—including measurement errors in variables, right-side variables that reflect current or past choices, important variables that are not observed in data sets (e.g., innate ability, preferences), and selected samples (e.g., clinic health test results only from those who go to health clinics and have the tests)—why the stochastic term in relations being estimated often is not likely to be independent of the right-side variables. As a result, estimates are likely to be biased and therefore misleading unless special data and estimation procedures, grounded firmly in the analytical framework used for the analysis, are used to control for these problems.
Implications for Analysis of Endogenous Policies
Policies of all sorts—including those related to investments in youth—are not predetermined, but are made by individuals or groups of individuals with various objectives in mind, including accommodating to pressures from and needs of constituents. This means it may not be possible to evaluate the impact of governmental policies on various outcomes without controlling for the fact that governmental policies themselves are determined, implemented, and monitored as part of a larger set of behavioral decisions.10 The failure to control for the determinants of governmental policies may cause substantial misestimates of their effectiveness. These misestimates, moreover, may either overestimate or underestimate policy effectiveness, depending on the nature of the governmental decision (Rosenzweig and Wolpin, 1986).
The basic intuition is clear from considering the simple example of evaluating the impact on youth health of special health programs from cross-sectional data from a number of communities. If the resources devoted to such special programs tend to be concentrated in communities that have greater political power, wealth, and more healthy youth net of the effects of the special health programs and of characteristics that are observed in the data, the association between youth health and resources devoted to special health programs without control for resource allocation among these special health programs in different communities overstates the effectiveness of the programs. Those communities that receive more
special health program resources would have had better youth health for other reasons that are correlated positively with the allocation of special health program resources (and vice versa). On the other hand, if the resources devoted to such special health programs tend to be concentrated in communities that have poorer health environments, greater poverty and less healthy youth net of the effects of the programs and of characteristics observed in the data, the association between youth health and resources devoted to special health programs without control for resource allocation among those programs in different communities understates the effectiveness of the programs. As a result, even if the programs are effective in improving youth health, the simple cross-sectional association between special health program resources in various communities and youth health may be negative (and, if positive, is an underestimate of the effectiveness of special health program resources). Therefore, it is essential to control for the determinants of program placement and intensity across recipients in order to evaluate the impact of programs with confidence.
Private Versus Social Returns, Efficiency, and Distribution
Often analyses of the impact of investments in youth are undertaken without consideration of the general rationale for policies. It is just presumed that policies that, say, through greater investments in youth increase some outcome such as subsequent health must be good. But such analyses may not provide much in the way of guidelines for choosing among policy alternatives. Therefore, it is useful to ask why policy interventions with respect to investments in youth might be desirable.
At a general level of abstraction, policy should be chosen in order to maximize social welfare. Of course, that begs the critical political economy question of how the social welfare function is determined. Even if that difficult question is put aside, the practical guidance offered by the injunction to maximize social welfare may seem quite limited. For that reason it is often useful to think separately of the two standard economic justifications for governmental policy interventions: (1) to increase efficiency/productivity and (2) to redistribute resources.11 Policy justifications based on efficiency and on distribution are both firmly rooted in micro-dimensions of behaviors. Both of these standard economic motivations for policy are
concerned ultimately with the welfare of individuals as judged by those individuals.
Efficiency/Productivity
Resources are used efficiently in the economic sense if they are used to obtain the maximum product possible given the resources and available production technologies at a point of time, and over time, and if the composition of that product increases the welfare of members of society as much as possible given the resource and technological constraints and preferences, and the distribution of resource ownership. An investment (or expenditure) is efficient if the marginal social benefit of the last unit of that investment just equals its marginal social cost.12 If the marginal social benefit of a particular investment is greater (less) than the marginal social cost, society is not investing enough (is investing too much) and would benefit from increasing (decreasing) the level of investment until the marginal social benefits and costs are equalized.
Although applying the above rule maximizes social gains, private maximizing behavior leads to investments (including those related to youth) at the level at which the marginal private benefit of the investment equals its marginal private cost under the assumption that, given the information available to them and the constraints they face, individuals act in what they perceive to be their best interests. Consider the possibility that private incentives for investments differ from social incentives for such investments, first with respect to the marginal benefits and then with respect to the marginal costs.
Why might marginal social benefits exceed marginal private benefits for investments in youth? The most frequent answers to this question include the following:
-
There are externalities in the form of effects on others that are transferred “external to markets.” Investments in education are thought to have not only private benefits to the person being educated, but, by adding to society’s stock of knowledge, social benefits beyond the private benefits. Other relevant examples of externalities include being exposed to second-
-
hand smoke, controlling contagious diseases such as HIV/AIDS, creating social capital, and developing incentives for legal rather than criminal behaviors.
-
Information used to make schooling, health, and employment decisions may misrepresent the private rates of return to these investments because it is incomplete or incorrect. For example, youth may not know about contraceptives or about risks associated with sexually transmitted infections (STIs). The “public good” nature of information (i.e., that the marginal cost of providing information to another consumer is virtually zero) leads to underproduction of information from a social point of view by private markets because private providers cannot cover their costs if they price information at the social marginal cost as required for efficiency.
-
The combination of uncertainty, risk aversion, and imperfect insurance markets may result in private incentives to underinvest in human, financial, and physical assets because, from a social point of view, the risks are pooled.
-
The social discount rate may be lower than private discount rates because individuals value future outcomes more collectively than they do individually.
-
Prices for outcomes affected by such investments may understate social gains, in part because of distortions due to policies (e.g., policy restrictions on salaries in the health and education sectors).
Why might marginal social costs be less than marginal private costs for investments in youth? Answers include the following:
-
There may be capital market imperfections for some types of investments (e.g., social capital investments and human resource investments, in part because these forms of capital are not accepted as collateral) such that the marginal private costs for such investments exceed their true marginal social costs, which probably is more relevant for individuals from poorer families who cannot easily self-finance such investments.
-
The sectors that provide some types of services (e.g., information, health care, schooling) may produce inefficiently because institutional arrangements do not induce efficient production of an efficient basket of commodities. School teachers and staff, for example, might be oriented toward rewards established by the Ministry of Education or union negotiations, not toward satisfying the demands of clients. Governmental health workers may be more interested in their private practices than in their public work.
-
The sectors that provide services related to investments in youth may produce inefficiently because regulations preclude efficient production of an efficient basket of commodities. For example, regulations that limit
-
hours during which schools are open, limit textbook choices, impose quality standards based on different conditions in other economies, or limit provision of services to public providers, all may result in much greater costs of attaining specific investments than would be possible with fewer regulations.13
What are the implications of differences in the marginal private and social benefits or costs? Simply, if there are such differences, private incentives for investments in youth differ from social incentives. In such circumstances, policies may increase efficiency by reducing the differences between the private and the social incentives or through other means that cause outcomes to be closer to the socially desirable outcomes.
Distribution
Distribution is a major policy motive distinct from efficiency. Distributional concerns, at least officially in pronouncements of governments and of international agencies, often focus on the command over resources of poorer members of society.14 Society might want to assure, for example, that everyone has basic schooling, even at some efficiency cost (van der Gaag and Tan, 1997). Though distributional concerns are often characterized by focus on the distribution of income or other resources among households, there may also be important distributional considerations within households. Household decision makers are not likely to consider equally preferences of all household members in allocating household resources. For example, if women have preferences for using more resources to invest in children than do their husbands, these preferences may not be weighed equally as those of their husbands in decisions made by husbands. Moreover, even if some households as aggregates have sufficient resources to cover what society considers basic needs, certain types of individuals in households may not be allocated what society considers to be sufficient resources for their individual satisfaction of basic needs. A particularly germane example may be child labor. Such labor may contribute importantly to the resources and the welfare of the household decision makers, but may detract from improving the human resources of the child by, for
example, exposing the child to health and other risks and limiting the education of the child. Thus there may be an important intergenerational distribution trade-off.
Policy Choices to Increase Efficiency and to Improve Distribution
If all other markets in the economy are operating efficiently and there are differences between marginal private and social incentives in a given market related to investments in youth, policies that induce investments at the socially efficient levels increase efficiency.15 That still does not indicate what policies would be best to induce investments in youth at the socially desirable levels. There is a large set of possibilities, including governmental fiats, governmental provision of services at subsidized prices, price incentives in markets related to investments in youth, price incentives in other markets, and changing institutional arrangements in various markets. To choose among alternatives based on efficiency alone, there are two important considerations.
First, policies have costs. These costs include direct costs of implementing and monitoring policies and distortionary costs due to policies that may encourage socially inefficient behavior (including rent seeking by both public and private entities). Often policy makers focus only on the direct costs and ignore the distortionary costs because only the direct costs have obvious and visible direct ramifications for governmental budgets. In fact the costs may be sufficiently high that it is not desirable to try to offset some market failures by policies.16 But, if it is desirable to do so, there is a case generally for making policy changes that are directed as specifically as possible to the inefficiency of concern because that tends to lessen the distortionary costs. An efficiency policy hierarchy can be defined in which alternative policies to attain the same improvement in efficiency are ranked according to their social marginal costs, including direct and distortionary
costs. This hierarchy indicates the preferential ordering of policies to deal with particular divergences between private and social incentives.17
Second, there are tremendous information problems regarding exactly what effects policies have, particularly in a rapidly changing world. This is an argument in favor of policies that are as transparent as possible, which generally means higher in the efficiency policy hierarchy with regard at least to distortionary costs because more direct policies are likely to be more transparent.18 Information problems also provide an argument for price policies (taxes or subsidies) because if there are shifts in the underlying demand and supply relations, they are likely to be more visible in a more timely fashion to policy makers if they have impact on governmental budgets than if they only change the distortions faced by private entities, as tends to happen with quantitative policies.19 Finally, information problems in the presence of heterogeneities across communities point to the possible desirability of decentralization and empowerment of users of social services in order to increase the efficacy of the provision of those services. However, such considerations must be balanced off against possible economies of scale, higher quality of staff, and possibly lower levels of corruption at more centralized levels, as well as intercommunity distributional concerns.
Thus, for efficiency/productivity reasons, particularly given that in the real world information is imperfect and changes are frequent, there is an argument generally for choosing policies as high as possible in the efficiency policy hierarchy defined by the extent of marginal direct and distortionary costs—and thereby using interventions that are focused as directly on the problem as possible. Note that this means that, for example, if there is a good efficiency reason for public support for investments in youth, that does not mean the best way to provide that support is through governmental provision of the relevant services. Higher in the efficiency policy hierarchy than direct governmental provision of such services, for example, may be subsidies or taxes that create incentives for the efficient provision of these services, whether
the actual providers are public, private, or some mixture. On the other hand, policies that discriminate against one type of provider—for example, by making the availability of such subsidies dependent on whether the provider is public—are generally likely to be lower in the efficiency policy hierarchy than policies that do not have such conditions.
Now consider distribution. Generally subsidization of specific goods and services (and even less, the direct provision by governments of goods and services at subsidized prices) is not a very efficient way of lessening distributional problems. Because subsidies are designed to lower prices to consumers, they induce inefficient consumption behavior. Instead, it is generally more efficient (and thus less costly in terms of alternative resource uses) to redistribute income to consumers, allowing them to allocate the income in ways that lead to efficient patterns of consumption.20 Nevertheless, there are cases in which subsidization of selected goods and services may be defensible to attain distributional objectives. For example, in cases where it is difficult (and therefore costly) to target the poor households or poor types of individuals within households, subsidizing certain goods and services that are mainly consumed by the poor may be relatively high in the efficiency policy hierarchy.
Rather than being concerned with the general command over resources of its poorer members, as noted above, society may deem it desirable that everyone enjoy basic services, including basic schooling, nutrition, and health care. Such an objective might be obtained through many means. But presumably it is desirable to assure that everyone has these basic options at as little cost in terms of productivity as possible, so, rather than ignoring efficiency considerations, it is desirable to choose policies as high as possible in the efficiency policy hierarchy and still assure that the basic service objectives are met. Thus, to obtain a given distributional objective, it is possible to define a distributional policy hierarchy in which policy alternatives that obtain that objective are ordered from lowest to highest marginal direct and indirect costs. Efficiency goals thus should play an important role in interaction with the pursuit of distributional goals, not as independent considerations.
Implications of Efficiency and Distributional Motives for Evaluating Benefits and Costs of Different Policies
There are important implications of the two policy goals—efficiency and distribution—for how the costs and benefits of policies should be valued:
-
Whether particular policies are warranted or not depends on the social trade-off between efficiency and distribution.
-
Transfers may be an important tool for attaining distributional ends, but they are not costs in the sense that in themselves they use resources. Related to transfers (as well as to other programs), however, generally are real resource costs related to program administration and distortions caused by programs.
-
Just because there are large productivity gains relative to costs does NOT mean that a program warrants subsidies from the point of view of efficiency. From the point of view of efficiency, there is a reason for public policy support only if the social rate of return to a particular use of resources is greater than the private rate of return.
-
With imperfect capital and insurance markets for the poor, there are likely to be some productivity and efficiency gains if the poor are beneficiaries of transfers.
-
Measurement problems are great. These are particularly severe, for example, for the social welfare weights for marginal incomes for different members of society and for differences between social and private rates of returns due to market imperfections for the productivity and efficiency measures. But, despite such difficulties, it is important to attempt to undertake benefit/cost analysis with such considerations in mind—though, all too often, they are ignored.
Methodologies for Economic Evaluation of Investments in Youth
If one has reliable estimates of the effectiveness of a set of alternative investments in youth, how can one best evaluate them against the criteria of efficiency and distribution? Several methodologies are available.
Cost-effectiveness analysis (CEA) consists of ranking a set of related investments according to their cost per unit of effectiveness, where the measure of “effectiveness” is as clearly defined and narrow as practical. CEA has been widely used to evaluate alternative investments within a given sector. For example, cost per life saved or cost per disability-adjusted life year (DALY), are criteria that have been widely used in CEA evaluations of alternative investments in the health sector. However, CEA has several shortcomings in the context of evaluating alternative investments in youth. First, it requires a single effectiveness measure. This is impractical in the case of many youth investments because they involve such a wide range of possible outcomes. Second, CEA does not provide any basis for comparing investments in youth to alternative investments, such as investments in economic infrastructure or investments to improve governance. Third, although CEA addresses aspects of the efficiency motive for policies, it does not do so comprehensively (i.e., it does not address whether the objective
used to measure “effectiveness” itself represents an efficient use of resources).21
Cost-benefit analysis (CBA) is an alternative methodology for evaluating investments that is designed to compare investments that may have several different outcomes. Because CBA values benefits in monetary terms, it obtains results (i.e., benefit/cost ratios or internal rates of return) that readily permit comparisons with alternative investments. If one has reliable estimates of effects, the problem is valuing them in monetary terms. This is often technically challenging and can be politically sensitive as well (e.g., assigning a monetary value to a human life). Although several approaches are used to do this in the literature, we focus on micro-estimates of direct productivity effects that can be measured in monetary terms on the one hand and, for the effects that cannot be easily translated into monetary terms, use the resource cost of the most cost-effective alternative to achieve the same effects on the other hand.22,23 Problems with this approach include that (1) it is partial equilibrium, and therefore market feedbacks, particularly within relatively closed economies, may be missed, and (2) information with which to assess private versus social rates of return, and therefore, the efficiency motive, is relatively rare. Nevertheless, this seems to be the best available methodology, so we adopt it in this chapter. In our estimates of benefits, we try to give appropriate attention to the lag between the investment and the expected effects, because with even a modest discount rate (e.g., 5 percent), the delay between investments and the resulting effects can have an important effect on benefit/cost ratios or internal rates of return. We also try to examine critically the case for public intervention with respect to each type of
investment because most benefit/cost ratios by themselves do not shed any light on this issue.24 Finally, we also try to examine the likely impact of investments on the poor as compared to the nonpoor and on women as compared to men, because distributional concerns are not usually incorporated directly into benefit/cost estimates.25
EFFECTS AND COSTS OF A RANGE OF BASIC INVESTMENTS IN YOUTH
Table 11-1 lists alternative investments in youth that are examined in Knowles and Behrman (2005). An important general point is that many estimates of effects of investments in youth are not persuasive because they are based on behavioral, not experimental, data and do not control for behavioral choices that led to the investments in youth nor for many measurement problems.
In surveying the literature on youth investments, we have found that there are a number of serious gaps in the information base that would support the kind of estimates we would like to present. In developing countries, there is little evaluation of the effectiveness of existing youth programs. Where reliable estimates of effectiveness exist, the measurement is often over too short a period of time to be useful or focused on only one or two effects of an investment (e.g., the productivity effects of investments in formal schooling). Without reliable information about the effectiveness of interventions, it is impossible to obtain reliable estimates of the benefits and thus of the benefit/cost ratios or the internal rates of return of various investments. The absence of reliable estimates of the full range of the hypothesized effects of investments frustrates efforts to obtain separate estimates of private and social benefits. Accordingly, the rationale for government intervention is absent or weak in the case of many of the possible investments in youth.
We summarize below the main findings of our review of the literature regarding the effects, costs, and cost effectiveness of various categories of investments in youth.
TABLE 11-1 Alternative Investments in Youth Reviewed in Knowles and Behrman (2005)
School quality improvements |
Vocational and technical |
Child labor regulations |
Scholarships |
Adult basic education and literacy |
Other employment regulations |
Compulsory attendance laws |
Military |
(e.g., safety, minimum wage, maximum hours) |
Reproductive health (RH) |
School health investments |
Other health investments |
School-based RH education |
School health policies |
Tax on tobacco products |
Social marketing of RH services |
School-based health education |
Ban on advertising tobacco |
Youth-friendly RH services |
School lunch/feeding |
Antialcohol abuse programs |
Linked services |
School micronutrient supplements |
Antidrug abuse programs |
Peer counseling programs |
School deworming programs |
Mass media health programs |
Mass media programs |
School water and sanitization |
Food supplements for pregnant women |
Workplace/community outreach |
School malaria treatment |
Food fortification |
Programs to delay marriage |
School physical examinations |
Road accident prevention |
RH program development |
School health insurance |
Mental health programs |
Community and other investments |
Youth development programs |
Microcredit for youth |
Youth centers |
Sports and recreation programs |
Youth rehabilitation programs |
Formal Schooling
There are reliable estimates for some countries of the cognitive achievement effects of both demand-side investments (scholarships) and supply-side investments (quality improvements) based on randomized experiments. However, there is no developing country evidence of the effects or cost effectiveness of investments to enforce compulsory school attendance laws. The effects of school quality investments and scholarships can differ significantly by income and gender. For example, investments that improve the quality of schooling mainly provide benefits to children already enrolled in school. Accordingly, such investments tend to benefit the better off more than the poor and boys more than girls in areas in which enrollments for boys are higher than for girls, particularly if the investments are made at the secondary level. In contrast, scholarships are often targeted to poor children or to girls in an effort to encourage them to enroll or remain in school. Cost estimates are provided in several studies. However, the cost estimates usually do not include estimates of distortionary and administrative costs, and in some cases they wrongly include transfers (e.g., scholarships) as if they are resource costs. Most of the countries for which reliable estimates of cognitive achievement effects are available are middle-income countries in Latin America (e.g., Mexico, Colombia), though a randomized experiment on evaluating alternative quality improvement investments is currently ongoing in Kenya.
Civilian and Military Training
Estimates are available of the cost of providing vocational/technical and adult basic education and literacy (ABEL) training in many countries. However, the cost estimates do not include distortionary costs, or even administrative costs in some cases. Reliable estimates of effects, in terms of cognitive achievement, are not available in any study that we have been able to locate. Most of the existing estimates do not address the problem of selectivity bias. In countries where female illiteracy rates are considerably higher than those of males, ABEL investments are likely to benefit more females than males. ABEL investments also tend to be effectively targeted to the poor. There are no studies that we have been able to find on the effects or costs of military training.
Work
There are no reliable estimates of the effectiveness of child labor regulations/laws and other employment regulations/laws in developing countries, nor is there any information on the costs of enforcing them. Some types of child labor (but clearly not all types) may enhance labor productiv-
ity, either through the acquisition of skills or through additional work experience. However, there are no reliable estimates of these possible negative productivity effects of child labor regulations/laws.
Reproductive Health
There are reliable estimates of effects of some investments (e.g., reproductive health education provided in schools). In some cases, these are obtained from randomized experiments. However, randomized experiments are rarely used to evaluate reproductive health investments in youth and are often too small to yield reliable results. Small quasi-experimental studies, which yield less reliable results, are much more common in the evaluation of reproductive health investments in youth. Other problems include the short time span over which effects are estimated in most studies and the reliance on intermediate outcome indicators (e.g., delayed sexual activity) rather than measures of health impact (e.g., HIV infections prevented). This is a significant problem because many reproductive health investments in youth are directed to low-risk populations (e.g., in-school adolescents) in which health impacts may be relatively small. Social benefits exceed private benefits for many investments in reproductive health because they involve the prevention or treatment of communicable diseases (e.g., HIV/AIDS prevention, STI diagnosis and treatment).
The biggest information gap in the reproductive health area is the lack of information on investment costs. There are almost no studies of reproductive health investments in youth that present cost estimates. The Honduras HIV prevention study (the results of which are used below) is an exception inasmuch as it provides estimates of both effects and costs. However, many of the “estimates” are based on the consensus views of Honduran and international experts, rather than on the results of carefully designed research. Another problem with the existing studies on reproductive health investments in youth is that they tend to focus on only one effect, such as HIV prevention, but not, for example, on teen pregnancy prevention. There is almost no information on either the cost or effectiveness of reproductive health policy development investments or on investments designed to delay age at marriage. In the case of highly active antiretroviral therapy (HAART) treatment of youth infected with HIV, the literature does not yet provide estimates of the potential health benefits or of the likely impact of HAART treatment on the secondary transmission of HIV.
School-Based Health Investments
There are reliable estimates of the costs and effects of some school-based investments, such as deworming and micronutrient supplements.
The available evidence suggests that both school-based deworming and micronutrient supplementation yield high returns in some settings (although there is apparent inconsistency in some of the findings of what appear to be carefully designed studies). There is somewhat less reliable information available on the costs and effects of school-based health education programs (other than those focused on reproductive health), school lunch and other feeding programs, and school water and sanitation investments. There is almost no information on the cost and effectiveness of investments in school health policy development, presumptive malaria treatment, periodical physical examinations, and school health insurance. An important distributional issue with respect to school-based health investments is that their benefits are mostly limited to children currently enrolled in school (who are predominantly from better off families and males in many countries).
Other Health Investments
There is reliable information on the effectiveness of tobacco taxes and bans on advertising, but there is little information on the cost of the investments required to implement these policies effectively. There is limited cost and effectiveness information for most of the remaining investments in this category (i.e., antidrug and antialcohol abuse programs, mass media interventions, food supplements for pregnant and lactating women, food fortification programs, road accident control programs). However, there is no information on either the cost or effectiveness of investments to improve the mental health of youth.
Community and Other Investments
There is very limited information on the cost and effectiveness of youth centers, but there is no information on the remaining investments in this category (i.e., youth development programs, micro-credit programs targeted to youth, youth rehabilitation programs, sports and recreation programs targeted to youth).
BENEFITS
Our literature review in Knowles and Behrman (2005) indicates that there is a wide range of possible effects from investments in youth. In order to carry out cost-benefit analysis of these investments, it is necessary to assign monetary values to their various possible effects. In some cases, it is possible to develop estimates of benefits directly in monetary terms that permit comparisons with costs and with other impacts that also are mea-
sured directly in monetary terms, such as the monetary value of enhanced labor productivity. We refer to benefits estimated in this way as “directly estimated” benefits, which are preferred, if possible. However, in cases where it is conceptually or practically difficult to value benefits directly in economic terms, we develop estimates based on the least amount of money society currently spends to secure the same effects, as discussed above. We refer to benefits estimated in this way as “indirectly estimated” benefits.26 In using the indirect approach, the following caveats are noted:
-
The effect(s) of the cost-effective alternative investment must be the same as the effect(s) for which a monetary value is sought. For example, if the cost per birth averted in a family planning program is used to value the effect of reduced fertility, it is important to adjust that cost for the other benefits that family planning programs provide, such as reduced maternal mortality and morbidity, reduced child mortality, ability to space births, and information.27
-
It is important not to double count the value of effects that are directly and indirectly valued (van der Gaag and Tan, 1997). For example, if the value of enhanced labor productivity is used to value the benefits of increased education among all children, even those who may voluntarily not participate in the labor force (e.g., persons engaged full-time in housework), it is incorrect to include the value of improved health of children as an additional benefit (because this benefit should be reflected already in the enhanced productivity of more educated persons in housework).
-
What is really needed for indirect estimation is the amount of money society spends on the margin to secure a given effect, that is, the marginal cost-effectiveness ratio rather than the average cost-effectiveness ratio. Unfortunately, there is little information currently available on marginal cost-effectiveness ratios (e.g., the marginal cost per DALY gained in immunization or family planning programs). However, in many programs, marginal cost-effectiveness ratios may differ substantially from average cost-effectiveness ratios.
In cases where a broad effect such as “increased education” is expected to be the primary effect of an investment (e.g., a targeted scholarship program), it is necessary to value each of its components either directly (the preferred approach) or indirectly (the second best approach). For example, in the case of “increased education,” one of its components is enhanced
labor productivity. Because there is a substantial literature on relationships between increased education and enhanced labor productivity and on how to assign a monetary value to enhanced productivity, it is usually possible to value this component directly. However, other components of increased education (e.g., reduced teen pregnancy, reduced crime, reduced fertility) are more difficult to value directly, and an indirect valuation may be more practical.28 Knowles and Behrman (2005) identify the components of such broad effects in order to facilitate such a two-step valuation process. This information is summarized in Annex A.
Knowles and Behrman (2005) also review the extensive literature relevant to valuing the benefits of the various hypothesized effects of investments in youth. It is convenient to group the various effects of investments in youth into the following categories: (1) directly monetizable effects, (2) effects that are difficult to monetize directly but that can be monetized indirectly, and (3) effects that are particularly difficult to monetize even indirectly. In the case of directly monetizable effects, such as “enhanced labor productivity,” the review discusses only direct methods of valuation. In the case of effects that are more difficult to value directly, such as “increased education” or “improved health,” the review discusses both direct approaches to valuing the effects (using the two-step procedure discussed above) and indirect methods based on the cost of cost-effective alternative investments currently used to obtain the same effects (the Summers method discussed above). In the case of effects that are inherently difficult to value in monetary terms, such as “enhanced social capital” or “enhanced self-esteem,” the review provides only conjectures about how they might be valued. The main findings regarding the valuation of the effects of investments in youth are summarized below.
Directly Monetizable Effects of Investments in Youth
Enhanced Labor Productivity
An estimated percentage increase in labor productivity can be valued directly by multiplying it by the average wage.
Reduced Underutilization of Labor
There is often little information on activities of unemployed youth (i.e., the extent to which they may be engaged in housework or studying). This complicates efforts to place a monetary value on the increased labor utiliza-
tion benefits obtained from reducing youth unemployment (a broad effect).29 However, where such information is available, the percentage increase in labor productivity that results from reduced unemployment can be multiplied by the average wage to obtain a direct estimate of this benefit.
Increased/Decreased Work Effort
There is often little information on the effect of investments in demand-side schooling (e.g., scholarships and other transfers) or the enforcement of child labor laws on adult and child work effort. However, when such information is available, this benefit (or cost) can be estimated directly by multiplying the reported change in work effort by the average wage.
Expanded Access to Risk-Pooling Services
Estimates of this benefit can usually be made from knowledge of the characteristics of the risk insured against (e.g., the risk of health care expenditure among youth), usually in combination with some rather strong assumptions.
Reduced Age at Which Children Achieve a Given Level of Schooling
In valuing the effects of a given schooling investment, it can be assumed that earlier completion of a given grade level results in a longer active period in which to recoup the benefits of enhanced productivity. Because this benefit occurs at the beginning of a person’s active period, it is not as heavily discounted as some other education-related benefits.
Reduced Cost of Medical Care
There is some information on the cost of treating persons infected with HIV and other sexually transmitted infections. However, there is little information on the cost of medical care associated with unsafe abortions, or from female genital cutting. There is no problem in assigning a monetary value to the monetary component of this effect, because effects on the cost of medical care are usually expressed in terms of a percentage of an average level of spending on medical care. However, it is more difficult to assign a value to the opportunity cost of time and other indirect costs (e.g., transportation costs) involved in obtaining medical care.
Increased Tax Revenue
This is equivalent to a transfer. Hence, there is generally no benefit associated with the collection of increased tax revenue. However, in some cases (e.g., a tobacco tax), the tax revenue collected may have lower than usual distortionary costs because the tax may be offsetting in part or in whole some distortion, and in such cases this benefit should be valued, if possible.
Some possible approaches for indirectly valuing effects of investments in youth can be found in Table 11-2.
Effects That Are Particularly Difficult to Value Directly or Indirectly
Some examples of effects of investments in youth that are particularly difficult to value, whether directly or indirectly, include increased social capital, averted infertility, averted social exclusion, improved self-esteem, and enhanced national security (an effect of military training). For some of these effects (e.g., increased social capital, averted social exclusion), it is too difficult even to find a suitable measure of the effect. However, the difficulties involved in measuring and valuing these effects do not necessarily imply that they are less important than other effects of investments in youth.
BENEFITS AND COSTS OF INVESTMENTS IN YOUTH
Existing Cost/Benefit Analyses of Investments in Youth
There are only a few existing studies for developing countries in which the benefits and costs of investments in youth are calculated. Some of these studies are reviewed briefly in this section.
Bangladesh Food for Education (FFE) Program
The government-funded FFE program in Bangladesh provides grants of food (and more recently, cash) to households in designated poor localities on the condition that primary school-age children in the household are attending school. The annual FFE program expenditure needed to encourage an additional poor child to attend primary school was estimated to be $66.40, while the estimated annual expenditure for an additional very poor child to attend was estimated to be $95 (Ravallion and Wodon, 2000). Benefits in the form of additional per capita consumption enjoyed both by the child attending school and his/her family when the child reaches adulthood were estimated to be $69.90 for the poor child and $52.60 for the very poor child. After netting out the value of the food grains received
under the program, which are a transfer (but without including any estimate of social or other private benefits or estimates of distortionary costs), the internal rate of return was estimated to be 8.11 for the very poor and 11.50 for the poor. The report concludes that the FFE program is cost-effective as an education program. However, it suggests that a cash stipend program might be more cost-effective because of the likelihood that it would involve lower administrative costs (a recommendation that has been adopted, as indicated above).
Colombia PACES School Voucher Program
The Programa de Ampliación de Cobertura de la Educación Secundaria (PACES) program provides vouchers to poor households that can be used to pay for children to attend private secondary schools. In municipalities in which the number of applicants exceeded the funds available, scholarship recipients were randomly selected through a lottery (Angrist et al., 2002). The total social cost of the program was estimated to be $43 annually per lottery winner, or $195 over a 3-year period (after adjusting for different rates of voucher take-up in each year of the program). This cost, however, does not include any distortionary costs incurred, for example, in raising revenues to finance this program or due to effects of the program on the behaviors of other household members (e.g., changing their labor supplies). The evaluation estimated that the additional 0.12 to 0.16 years of schooling completed by lottery winners would raise their annual incomes by about $36 to $48 per year (based on an estimated rate of return to schooling of 10 percent in Colombia and predicted average annual earnings of $3,000). Additionally, the estimated increase of 0.2 standard deviations in test scores among lottery winners was estimated to be the equivalent of about one full year of schooling (based on the mean test scores by grade of U.S. Hispanic students taking the same test), which if correct, would translate into an additional gain of about $300 in annual earnings. Clearly the estimated gain in earnings would exceed the program’s cost as calculated in the study in any cost/benefit analysis, even if earnings gains are heavily discounted, distortionary costs are included, and social and other private benefits from improved cognitive achievement are ignored.
Increasing the Quality Versus the Quantity of Basic Schooling in Rural Pakistan
Increasing the quantity or quality of schooling an individual receives is likely to raise his or her cognitive skills. Increasing the quantity of schooling—by providing a primary education to children who otherwise would not go to school, or by providing a middle school education to children
TABLE 11-2 Possible Approaches for Indirectly Valuing Effects of Investments in Youth
Indirect Valuation Method |
Cost of public works programs targeted to youth per job created. |
Cost of scholarship programs per hour of reduced child labor. |
Cost of family planning services targeted to youth per averted teen birth. |
Cost of HIV/AIDS preventive programs targeted to high-risk populations. Alternatively, the estimated number of DALYs gained per averted HIV infection, multiplied by an estimate of the monetary benefits per DALY gained. |
Cost per STI averted through cost-effective investments to prevent HIV/AIDS (e.g., cost of preventive interventions directed to high-risk populations). |
Cost per DALY gained of cost-effective investments in health (e.g., immunization). |
Cost per DALY gained of cost-effective investments in health (e.g., immunization). |
Cost per unit of improved nutritional outcome (e.g., height-for-age, goiter rate, hemoglobin level, birthweight) of cost-effective nutrition investments (e.g., micronutrient supplements, food fortification). |
No information available on the cost-effectiveness of alternative interventions designed to improve mental health. A less satisfactory interim solution might be to obtain an estimate of the average number of DALYs lost per case of mental illness and to value each DALY gained on the basis of cost-effective alternative investments in health (e.g., immunization). |
Cost of scholarship programs for girls per year of delayed marriage. |
No information available on the cost effectiveness of alternative interventions designed to avert drug/alcohol abuse. A less satisfactory interim solution might be to obtain an estimate of the average number of DALYs lost per case of drug/alcohol abuse and to value each DALY gained on the basis of alternative cost-effective investments in health (e.g., immunization). |
No information available on the cost-effectiveness of alternative interventions designed to avert physical and/or sexual abuse. A less satisfactory interim solution might be to obtain an estimate of the average number of DALYs lost per case of physical and/or sexual abuse and to value each DALY gained on the basis of alternative cost-effective investments in health (e.g., immunization). |
No information available on the cost-effectiveness of alternative interventions designed to avert crime in developing countries. In this case, direct estimates may need to be prepared. See Knowles and Behrman (2005). |
If an estimate of the average number of DALYs lost per case of female genital cutting can be obtained, it would be possible to value each DALY gained on the basis of alternative cost-effective investments in health (e.g., immunization). |
Cost of family planning services per birth averted (with adjustments for fact that family planning services have other effects, e.g., birth spacing, improved health). |
Cost of family planning services per abortion averted (estimated crudely as the cost per pregnancy averted by family planning services divided by the proportion of pregnancies terminated by abortion). |
Cost of enforcing an increase in the tobacco tax per 1 percentage reduction in tobacco use (can be used for any investment except investments designed to enforce an increase in the tobacco tax). Alternatively, an estimate of the number of DALYs gained, valuing each DALY gained on the basis of alternative cost-effective investments in health (e.g., immunization). |
No reliable information available on the cost-effectiveness of alternative interventions designed to reduce violence and civil conflict. |
Cost of cost-effective interventions (e.g., professionally assisted deliveries) designed to avert maternal deaths (which produce orphans). |
who otherwise would leave school upon the completion of primary school—entails substantial costs. Similarly, improving the quality of schools has costs. However, in the case of quality improvement, there is little or no change in the opportunity cost of student time—a large component of the total cost of schooling.
Behrman, Ross, and Sabot (2005) developed a conceptual framework for evaluating the rates of return to increases in the quantity versus the quality of schooling. They collected most of the necessary data for rural Pakistan, and made estimates with methods that control for the key behavioral choices and for unobserved determinants of education. They found that increasing the quantity and improving the quality of schooling are alternative means of increasing the productivity and earnings of the labor force.30 Their estimates are that the “social” rate of return to enabling the graduate of a low-quality primary school to complete middle school, 2.8 percent, is low compared to improving school quality, 13.0 percent, or providing access to a low-quality primary school, 18.2 percent.31 The relatively high rate of return to improving quality reflects the absence of any additional opportunity cost to the students and the absence of higher capital costs for students already enrolled in school. In this context, it appears that productivity and equity concerns both point toward expanding primary schools, even if they are of lower quality. Additionally, because few boys now lack access to basic schooling, girls will benefit disproportionately.
This study again points to some of the difficulties in undertaking such evaluations. Even with the special data collected for the study, for example, it was not possible to identify with confidence the relative importance of the various components of teacher quality (i.e., the relative importance of factors such as teacher experience, teacher schooling, teacher training). This study also limits the measurement of the effects of changes in schooling to the private value of labor market outcomes, and provides no information on possible efficiency reasons for interventions. Furthermore, as in the other studies reviewed in this section, there is no attention to some possibly important distortionary costs, such as those incurred to raise governmental revenues.
Estimates of the Benefits and Costs of Investments in Youth
In this section, estimates are presented of the benefits and costs of some investments for which a sufficient amount of information is available to permit the preparation of estimates of investment effects, costs, and benefits. These estimates attempt to incorporate the direct and indirect effects of investments, using the method presented in Annex B. Before proceeding, attention is drawn to the fact that the estimates presented are quite specific to a particular country or context. They do not represent generally applicable estimates of the returns to the above investments. Additionally, as will become apparent in the discussion that follows, the estimated benefit/cost ratios (and internal rates of return) are quite sensitive to the particular assumptions used.
Scholarship Program
The effect of the investment on increased education is estimated on the basis of results obtained in the PACES voucher program (Colombia), which awarded scholarships to poor children (some of whom were selected randomly from among applicants via a lottery) to attend private secondary schools (Angrist et al., 2002; also see discussion above). The estimated effect of the scholarships was 0.12 additional grades of schooling completed by each lottery winner (as compared to lottery losers, all of whom had also applied to the program). In addition, each lottery winner performed 0.2 standard deviations higher on standardized achievement tests, a difference that was estimated to be equivalent to having completed approximately one additional grade of schooling.32 There was almost certainly an effect of the investment on the average age at which secondary school was completed, because repetition rates were significantly lower among lottery winners and because 8th grade completion rates among lottery winners were about 10 percentage points higher (with age held constant). But the average age at which a given grade was completed was not reported, possibly because most of the sample children were still in secondary school at the time of the evaluation. There was also some evidence that lottery winners were less likely to be married at the time of the survey (although the effect was less than 1 percent). No information was provided on the possible effect of the scholarships or on the means used to raise revenues for the program on adult work effort. However, lottery winners (school children) worked significantly fewer hours per week (about 1.2 fewer hours).
In calculating the benefits and costs of a scholarship program, the following assumptions were used:
-
The total cost of the investment (i.e., during the three years in which the program operated before its effects were measured) is equal to $227.65 per scholarship recipient (consisting of $9.07 in additional resources consumed to provide education, $185.93 in reduced work effort of children receiving scholarships, and $32.65 for administrative and distortionary costs).33
-
Each scholarship recipient completes 0.12 additional grades of schooling (i.e., the effect of the scholarship on higher test scores is initially assumed to be zero).
-
The cost of the investment is distributed equally during three years (i.e., ages 13, 14, 15).
-
Each additional year of secondary schooling completed results in a 10 percent increase in annual earnings, as compared to expected future average annual earnings of $3,000.
-
Earnings are received continuously from age 16 until age 60.
-
The investment reduces the average age of completing secondary school by 0.2 years per scholarship recipient, which is assumed to provide an additional 0.2 years of earnings at age 15.
-
There is no effect of the investment on age at marriage or on the number of hours worked by adults.
-
The discount rate is 5 percent per annum.
Because increased education is a broad effect, the following additional assumptions were made about the components of increased education:
-
Each additional year of completed secondary schooling results in reduced fertility (i.e., 0.1 fewer births at age 35, averaged over males and females) and improved health (i.e., 1.0 DALY spread out evenly between ages 15 and 70).
-
Each additional year of completed secondary schooling results in 1.2 fewer hours worked per week by scholarship recipients while enrolled in school.
-
There is no effect of increased education on any of the following: crime, violence and civil conflict, social exclusion, youth unemployment, teen pregnancies, HIV infection or STIs, drug/alcohol abuse, physical/sexual abuse, or mental health. Clearly, this assumption (necessitated by the absence of estimates of increased education on these hypothesized effects) renders it impossible to obtain separate estimates of the social and private benefits of this investment.
The benefits from reduced fertility, improved health, and reduced child work are assumed to be as follows:
-
$50 per birth averted (indirectly estimated, based on the cost of 4 couple years of protection using contraceptives).
-
$20 per DALY gained (indirectly estimated, based on the cost of cost-effective health investments targeted to youth).
-
$0 (based on the assumption, for secondary students, that the benefits of any decrease in child labor are offset by the loss in benefits from reduced work experience).
Under these assumptions, the benefits discounted to age 13 are $3,152, while the costs (also discounted to age 13) are $953. The benefit/cost ratio is 3.31, while the internal rate of return is 25.6 percent. However, these estimates are quite sensitive to the discount rate used. For example, if a discount rate of 3 percent is used instead of 5 percent, the benefit/cost ratio increases from 3.31 to 4.41. The estimates are also very sensitive to the assumed productivity effect of an additional year of schooling. For example, if this effect is reduced from 0.10 to 0.08, the benefit/cost ratio decreases from 3.31 to 2.77.
The estimates are not sensitive to the inclusion of other components besides enhanced labor productivity in the broad effect of increased education. For example, if both the assumed fertility and health effects are reduced to zero, the benefit/cost ratio decreases only from 3.31 to 3.30. However, the estimates are sensitive to the assumed effect of the scholarship on the average age at which children complete school. If this effect is reduced to zero, the benefit/cost ratio declines from 3.31 to 2.68.
The preceding estimates assume that the effect of the scholarship on education is limited to the increase in the number of grades completed by scholarship recipients. If the effect is expanded to reflect the improved performance of scholarship recipients on standardized achievement tests (estimated to be the equivalent of an additional grade completed in the Colombia study), the benefit/cost ratio increases dramatically, from 3.31 to 25.63, while the internal rate of return increases from 25.6 percent to 93.9 percent.
Adult Basic Education and Literacy Program
Information on the effectiveness of investments in adult basic education and literacy in creating lasting cognitive achievement is not readily available. It is also unclear how appropriately and accurately costs are measured in the available evaluation literature. Accordingly, cost/benefit estimates are prepared for this type of investment using a wide range of assumptions in terms of cost and effectiveness. Estimates of the cost per trainee successfully completing an ABEL course range from $20.40 to $97.78 for four projects in three countries, Ghana (two projects), Bangladesh, and Senegal (World Bank, 2002b). This implies that a $1,000 investment in ABEL could produce from 10.23 to 49.02 successful trainees. However, these cost estimates apparently do not include the distortionary costs resulting from raising revenues to finance these programs, and thus are probably underestimates of the true costs. There is no information on the level of lasting cognitive achievement that successful trainees would acquire. An upper limit is probably the equivalent of four years of primary schooling. A lower limit is plausibly the equivalent of one year of primary schooling (although the possibility cannot be ruled out that in some mass campaign programs, less is acquired). The range of assumptions about cost and effectiveness creates a wide range of estimates about the cost effectiveness of ABEL, that is, from 10.2 years of primary school equivalency to 196.1 years of primary school equivalency per $1,000 investment (not including distortionary costs).
The cost/benefit estimates are made using the following assumptions:
-
The training is provided to 18-year-olds and is assumed to be the equivalent of only one year of primary schooling completed.
-
The effect of $1,200 invested in ABEL (including distortionary costs of 20 percent) is initially assumed to create only 10.23 years of primary school equivalency.
-
Each additional year of primary school equivalency results in a 10 percent increase in annual earnings, as compared to average annual earnings of $1,400 in Colombia.34
-
Earnings are received continuously from age 19 until age 60.
-
The discount rate is 5 percent per annum.
Because the increased education that is assumed to result from ABEL investments is a broad effect, the following additional assumptions were made about the components of increased education:
-
Each additional year of primary school equivalency results in reduced fertility (i.e., 0.1 fewer births at age 35, averaged over males and females) and improved health (1.0 DALYs spread out evenly between ages 19 and 70).
-
There is no effect of increased education on any of the following: violence and civil conflict, crime, social exclusion, youth unemployment, teen pregnancies, HIV infection or STIs, drug/alcohol abuse, physical/sexual abuse, or mental health. Clearly, this assumption (necessitated by the absence of estimates of increased education on these hypothesized effects) renders it impossible to obtain separate estimates of the social and private benefits of this investment.
The benefits from reduced fertility and improved health are assumed to be as follows:
-
$50 per birth averted (indirectly estimated, based on the cost of 4 couple years of protection using contraceptives).
-
$20 per DALY gained (indirectly estimated, based on the cost of cost-effective health investments targeted to youth).
Under these assumptions, the benefits discounted to age 18 are $23,880, while the costs (including distortionary costs) are $1,200. The benefit/cost ratio is 19.9, while the internal rate of return is 70 percent. However, these estimates are quite sensitive to the discount rate used. For example, if a discount rate of 3 percent is used instead of 5 percent, the benefit/cost ratio increases from 19.9 to 27.6. The estimates are also very sensitive to the assumed productivity effect of an additional year of primary school equivalency. For example, if this effect is reduced from 0.10 to 0.08, the benefit/cost ratio declines to 15.93. If, alternatively, the productivity effect of the ABEL training is assumed to be 0.10 initially but to diminish at 5 percent annually, the benefit/cost ratio declines to 11.55. If it is assumed to decline at 10 percent annually, the benefit/cost ratio falls to 8.14.
If instead of the lower limit of cost effectiveness that is used in preparing the above estimates (i.e., 10.2 successful trainees per $1,000 invested and one year of primary school equivalency per successful trainee), the upper limit is used (i.e., 196.1 trainees per $1,000 invested and four years of primary school equivalency per successful trainee), the benefit/cost ratio rises to an astoundingly high 1,764 (i.e., discounted benefits of $2,116,248
for each $1,200 invested), corresponding to an internal rate of return of 980 percent.
School-Based Reproductive Health Education Program to Prevent HIV/AIDS
Estimates of the effectiveness of this investment are based on estimates developed in the Honduras HIV/AIDS modeling work supported by the World Bank (2002a). It is important to emphasize at the outset that the benefits presented for this investment are limited to the effects of the investment on HIV prevention. No other effects were considered in the Honduras study. It was estimated that a school-based reproductive health education program targeted to adolescents (ages 10 to 19) would reach an estimated 60 percent of the targeted population and, among those reached, would reduce HIV incidence by 38 percent (the baseline annual HIV incidence among adolescents was estimated to be 0.001 in Honduras). Such a program was estimated to cost $10.44 per targeted adolescent (and $12.53, if an additional 20 percent in distortionary costs are included in the unit cost estimate to represent the cost of mobilizing the necessary tax revenue to finance the investment). Under these assumptions, the cost per averted HIV infection is $54,947, or 0.0182 new infections averted per $1,000 invested.
Two alternative estimates of the benefits of this investment are presented. The first estimate (referred to as the “aggregate” estimate) is based on the Commission on Macroeconomics and Health’s (2001) estimate that averting an HIV infection in a developing country involves a gain of 34.6 DALYs 5 to 8 years after the infection is averted and the Commission’s recommendation that each DALY should be valued at one to three times the level of annual earnings. Assuming that annual earnings are $1,000 and that the lower limit of the estimate of benefits is used (i.e., one times annual earnings), the aggregate estimate of benefits per averted HIV infection would be $34,600 (34.6 × $1,000 = $34,600). Such an estimate would include the benefits not only from improved health, but also from the other components of the broad effect of averting an HIV infection (e.g., reduced medical care costs). Under these assumptions, the benefit/cost ratio is 0.493, while the internal rate of return is undefined (because even undiscounted benefits are less than costs).35 If a 3 percent discount rate is used instead of 5 percent, the benefit/cost ratio rises to 0.543. This relative insensitivity with respect to changes in the discount rate reflects the fact that the benefits of the investment are assumed to occur at a relatively young age (23).
An alternative estimate of the benefits from averting one HIV infection (referred to below as the “disaggregated” estimate), which is a broad effect, is based on the following assumptions regarding the benefits of the components:
-
It is assumed that any HIV infection is averted at age 18.
-
In the case of improved health, it is assumed that each HIV infection averted results in a gain of 34.6 DALYs (but valued differently, as explained below) at age 23.
-
Each DALY of improved health gained is valued according to the cost per DALY gained from alternative cost-effective health investments targeted to the same age group. An estimate of $20 per DALY gained is used for this purpose.
-
In the case of secondary HIV infections, it is assumed (consistent with estimates in the Honduras HIV/AIDS modeling) that each infected adolescent infects 0.1 others between the age of infection (18) and the age of death (23).
-
Each secondary infection averted is assumed to provide a benefit of $4,867 (based on the estimated discounted benefits of averting an HIV infection, using the disaggregated method).
-
It is assumed that each averted HIV infection averts the annual medical costs of caring for an AIDS patient, assumed to be equal to 2.7 times the level of annual earnings ($2,700, assuming annual earnings of $1,000) during the last two years of life (i.e., at ages 21 and 22).
-
There is no effect of an averted HIV infection on secondary tuberculosis infections, orphans’ social exclusion, or education. This assumption (necessitated by the absence of estimates of averted HIV infection on these effects) renders it impossible to obtain separate estimates of the social and private benefits of this investment.
Using the disaggregated estimate of benefits, the estimated benefit/cost ratio is only 0.102, while the internal rate of return is again undefined (the estimated benefit/cost ratio increases to 0.109 with a discount rate of 3 percent). The estimated benefit/cost ratio is so low in this case because the estimated benefits of each averted HIV infection are only $4,867 in this case (compared to $34,600 when an averted HIV infection is valued using the aggregate method discussed above).36
The estimated benefit/cost ratios for this investment are directly proportional to the incidence of HIV infection in the targeted adolescent population. For example, if the incidence is 1 percent, instead of 0.1 percent, the benefit/cost ratio increases by a factor of 10, from 0.493 to 4.93 in the case of the benefits estimated using the aggregate method and from 0.102 to 1.02 in the case of benefits estimated using the disaggregated method.37 The benefit/cost ratio would presumably be significantly higher in both cases if some of the other benefits of such an investment (e.g., STIs averted, teenage pregnancies averted) were considered.
In addition to the fact that the Honduras study neglects benefits other than the prevention of HIV infections, it is also conservative in assuming that the benefits of health education do not continue beyond a single year. A more realistic assumption might be that the HIV prevention effectiveness of health education declines at a fixed annual rate over time. However, an offsetting factor is that the incidence of HIV infection is likely to rise with age. In the absence of better information, it is not unreasonable to assume for illustration that these two factors offset one another. In this case, health education received at age 15 would have the same impact, in terms of HIV infections averted per $1,000 investment, at ages 18 to 29. Under these revised assumptions, the estimated benefit/cost ratio would increase to 4.59 in the case of benefits estimated using the aggregate method, and to 1.115 in the case of benefits estimated using the disaggregated method.
Iron Supplementation Administered to Secondary School Children
It has been estimated that iron supplements provided to school children increase their cognitive achievement by 5 to 25 percent (McGuire, 1996). The annual cost of iron supplements per school child has been estimated to be $0.10 (World Bank, 2002c). A conservative estimate of delivery costs per child is $0.05 (i.e., 50 percent of the cost of the supplements).
A direct estimate of the benefits and costs of iron supplements administered to school children is based on the following relatively conservative assumptions:
-
Iron supplements are administered to children ages 13 to 15 for three years.
-
The annual cost of the iron supplements is $0.15 per child ($0.18, including additional distortionary costs of 20 percent).
-
The cost of the investment is spread out equally during three years (i.e., ages 13, 14, 15).
-
The effect of iron supplementation at age 15 is to increase each child’s cognitive achievement by the equivalent of 0.05 years of completed schooling.
-
Each additional year of secondary schooling completed results in a 10 percent increase in annual earnings, as compared to average annual earnings of $200.
-
Earnings are received continuously from age 16 until age 60.
-
The discount rate is 5 percent per annum.
Because increased education is a broad effect, the following additional assumptions were made about the components of increased education:
-
Each additional year of completed secondary schooling results in reduced fertility (i.e., 0.1 fewer births at age 35, averaged over males and females) and improved health (1.0 DALYs spread out evenly between ages 15 and 70).
-
There is no effect of increased education on any of the following: crime, violence and civil conflict, social exclusion, youth unemployment, teen pregnancies, HIV infection or STIs, drug/alcohol abuse, physical/sexual abuse, or mental health. Clearly, this assumption (necessitated by the absence of estimates of increased education on these hypothesized effects) renders it impossible to obtain separate estimates of the social and private benefits of this investment.
The benefits from reduced fertility and improved health are assumed to be as follows:
-
$50 per birth averted (indirectly estimated, based on the cost of 4 couple years of protection using contraceptives).
-
$20 per DALY gained (indirectly estimated, based on the cost of cost-effective health investments targeted to youth).
Under the above assumptions, the benefit/cost ratio is estimated to be 32.1, while the internal rate of return is 88 percent. Using a discount rate of 3 percent, the benefit/cost ratio increases from 32.1 to 45.2. If the productivity effect of an additional year of schooling is assumed to be 8 percent, rather than 10 percent, the benefit/cost ratio declines to 25.8.
Tobacco Tax
Estimates of the cost per DALY gained from a tax on tobacco products (i.e., $5 to $17) are obtained from the World Bank (1999). An aggregate
estimate of benefits per DALY is based on the recommendation of the Commission on Macroeconomics and Health (2001) that a DALY should be valued at one to three times the level of annual earnings.
An aggregate estimate of the benefits from a tobacco tax is based on the following conservative assumptions:
-
An investment of $1,000 ($1,200, including additional distortionary costs of 20 percent) would produce a gain of 58.82 DALYs (i.e., the cost per DALY gained is assumed to be $17).
-
There is a lag of 30 years between the investment and the resulting gain in DALYs.
-
Annual earnings are $1,000.
-
Each DALY gained is valued at one times annual earnings.
Under these assumptions, $1,200 invested in a tobacco tax today would yield discounted future benefits of $13,610. The benefit/cost ratio is therefore 11.34, and the internal rate of return is 13.9 percent. Given the long lag between costs and benefits, the benefit/cost ratio is quite sensitive to changes in the discount rate. For example, using a discount rate of 3 percent instead of 5 percent raises the benefit/cost ratio from 11.34 to 20.20. The estimated benefit/cost ratio is also quite sensitive to the length of the lag between costs and benefits. For example, increasing the lag from 30 to 40 years reduces the benefit from 11.34 to 6.96. Valuing each DALY at twice annual earnings ($2,000) raises the benefit/cost ratio from 11.34 to 22.68. Reducing the cost per DALY gained from $17 to $5 (its lower limit) increases the benefit/cost ratio from 11.34 to 38.56.
SYNTHESIS AND CONCLUSIONS
What Are Highest Return Investments?
Based on the very limited information available on the effects of investments in youth, it would appear that the investments in youth with the highest economic returns include: investments in formal schooling (i.e., supply-side investments in the quality of schooling, demand-side investments in targeted scholarship programs), investments in adult basic education and literacy targeted to adolescents, selected investments in school-based health services (e.g., micronutrient supplements), and investments designed to reduce the use of tobacco products (e.g., an increase in tobacco taxes). School-based reproductive health programs to prevent HIV/AIDS provide comparably high economic returns when annual HIV incidence among targeted youth rises to 1 to 2 percent or more or when their effects are assumed to last over a period longer than one year (although there is
TABLE 11-3 Estimated Benefit/Cost Ratios (BCRs) of Some Investments in Youth in Selected Countries
Investment |
BCR (5% discount rate) |
Plausible Range in BCRs |
Scholarship program (Colombia) |
3.31 |
2.77 to 25.63 |
Adult basic education and literacy program (Colombia) |
19.9 |
8.14 to 1,764 |
School-based reproductive health program to prevent HIV/AIDS (Honduras) |
0.493 |
0.102 to 4.59 |
Iron supplementation administered to secondary school children (low-income country) |
32.1 |
25.8 to 45.2 |
Tobacco tax (middle-income country) |
11.34 |
6.96 to 38.56 |
SOURCE: Estimates in text. |
unfortunately no information in the literature that establishes that the effects of these investments continue for several years). The economic returns to school-based reproductive health programs designed to prevent HIV/AIDS would also be higher if they could be shown to yield other benefits, such as the prevention of adolescent pregnancies and other types of STIs.
Table 11-3 presents estimates of the benefit/cost ratios for selected investments in youth in particular countries or country settings for which there is sufficient information available to support the preparation of such estimates. The data and assumptions used to obtain the estimates reported in Table 11-3 are discussed above. What is most interesting in this table is not the estimates obtained under a single set of assumptions (column 2), but rather the wide range of estimates one obtains by using alternative, and perhaps equally plausible, sets of assumptions (column 3). In fact, for several of the investments, the plausible ranges in the estimates of benefit/cost ratios overlap, making it impossible to develop an unambiguous ranking of their economic returns. The appropriate conclusion to draw from Table 11-3 is that, even in cases where the information base is relatively strong, a high level of uncertainty remains regarding the economic returns to alternative investments in youth.
How Do Investments in Youth Compare with Other Investments?
Of course, one purpose of estimating benefit/cost ratios (and internal rates of return) for alternative investments in youth is to compare their economic returns to those of alternative investments. If the benefit/cost ratios are properly calculated and are greater than one, the investment is worth undertaking in an expected value sense. For investments for which
TABLE 11-4 Benefit/Cost Ratios for Selected Development Bank-Supported Investments
Project (Year) |
Benefit/Cost Ratio |
Hill Forest Development Project, Nepal (1983) |
1.18 |
Irrigation Systems Improvement Project, Philippines (1977) |
1.48 |
Livestock Development Project, Uruguay (1970) |
1.59 |
Livestock and Agricultural Development Project, Paraguay (1979) |
1.62 |
Cotton Processing and Marketing Project, Kenya (1979) |
1.80 |
SOURCE: van der Gaag and Tan (1997). |
they are less than one, they are not worth undertaking. Therefore in an important sense, the estimates summarized in Table 11-3 provide a basis for comparing the economic returns of investments in youth with those of other investments.
Table 11-4 lists the benefit/cost ratios of some development bank-supported investments in other sectors for purposes of comparison. These investments were made in the so-called “hard” sectors. When one compares the estimates in Table 11-4 with those in Table 11-3, the immediate impression is that at least some types of investments in youth are likely to compare quite favorably to investments in other sectors.
What Are Highest Priority Research Areas?
At a general level, the highest priority research areas that emanate from this review are those that are necessary to obtain better empirical estimates of the benefit/cost ratios and internal rates of return to the plethora of possible policies that might improve the development of youth in developing countries. We refer to these as research gaps and discuss them below. In addition, the findings reported in this review raise a number of key questions that are also discussed in this concluding subsection.
Four Critical Research Gaps
First, an important gap is the absence of reliable estimates of many hypothesized effects of investments in youth. In future research, high priority should be given to obtaining reliable estimates of the effects of those investments for which little, if any, information currently exists (e.g., the effects of ABEL, vocational and technical training, military training, reproductive health policy development, investments designed to avert drug and alcohol abuse and to improve mental health, youth centers, youth rehabilitation programs, sports and recreation programs targeted to youth). There
is clearly a need for more, and larger, randomized experiments of longer duration than have been conducted in the past. Such experiments also need to collect data on a wider range of outcomes than in previous studies. One important contribution of this chapter and of the companion papers (Knowles and Behrman, 2003, 2005) may be to guide future researchers in terms of the data needed to make reliable and complete assessments of the effects of investments in youth. Due to the limitations of randomized experiments for some purposes (i.e., measuring effects that occur only after a considerable lapse of time), there is also a parallel need for more careful behavioral research on the effects of investments in youth than has been done in the past. Such research will require better data, that is, more longitudinal data sets, more carefully measured variables, and data on appropriate instruments.
Second, investments in youth are hypothesized to have a wide range of effects, but many of these are difficult to evaluate. It is not the problem of attaching monetary values to these hypothesized effects that currently constrains efforts to obtain estimates of their economic returns. Rather, it is the lack of reliable estimates of the effects of the investments. One solution to this problem that is explored in this review is the valuation of broad effects indirectly on the basis of the cost of least cost alternative investments that obtain the same broad effects. Although this approach to valuing broad effects may enable one to obtain estimates of benefit/cost ratios for many investments in youth, treating broad effects as a package makes it more difficult to distinguish social from private benefits (because the social effects that give rise to a possible divergence between the two may be packaged together with private effects as components of a single broad effect).
Third, partly in the short to medium term, due to the lack of reliable information on many of the hypothesized effects of investments in youth, there is a role for indirect valuation of the effects of investments in youth (particularly of broad effects, such as “increased education” or “improved health,” that are difficult to value directly). We have suggested some possible approaches to developing indirect valuations of many of the hypothesized broad effects of investments in youth in this review and in the companion literature review (Knowles and Behrman, 2005). However, there is a critical need for more research in this area. What is needed are estimates of marginal cost-effectiveness ratios for a number of alternative investments because these best reflect the value that society currently attaches to securing a given outcome.
Fourth, cost estimates are not available for many types of investments in youth (e.g., in the reproductive health area). In addition, the definition of costs (and in some cases, even benefits) used in many studies is incomplete and/or incorrect. Administrative costs and distortionary costs (most often related to the cost of financing investments) frequently have been neglected,
while transfers often have been treated as costs. More effort clearly needs to be devoted to the collection of accurate cost data.
Seven Key Remaining Questions
First, could better information be obtained with which to make estimates for some of the areas that we touch on above for which information is scarce? For example, mental health recently has become more widely recognized as a potentially important area for future health intervention. Estimates suggest that mental health problems account for a rapidly expanding share of poor health in the developing world. However, we have been able to find almost no information with which to compare investments in mental health with other investments. For another example, the rapid nutritional transition means that being overweight and obese rapidly is becoming a widespread problem for many youth in developing countries, but there is almost no information available with which to evaluate possible investments designed to address these problems.
Second, are there important policy areas that we have missed in the discussion above despite our effort at broad coverage? Might there be, for example, important legal changes that we have missed concerning, for example, minimum ages of marriage or property rights of youth?
Third, where are the returns from better quality data likely to be greatest? Across the board, given positive discount rates, the costs and returns early in any investment are particularly important. Although there is a general scarcity of information on the public costs of investments in youth, private costs—such as the opportunity cost of time of private citizens necessary to participate in the benefits of various investments—are often ignored.
Fourth, how can information be collected to assess better investments in light of the efficiency motive for policy? For such assessments, it is important to distinguish between private and social benefits and costs—but there is almost no information with which to assess these differences. Obtaining reliable estimates of both private and social benefits depends critically on the availability of reliable estimates of a full range of the effects of a given investment, not only of the private benefits associated with increased productivity.
Fifth, can evaluations better integrate the efficiency and the distributional motives for policies and the trade-offs between them? Although both are often recognized, the trade-offs are infrequently explored. This is clearly a fertile area for future research.
Sixth, how do such estimates need to be fine tuned for particular countries? Many of the assumptions regarding costs and benefits are likely to vary substantially across countries because of differential prices and institu-
tions. How do they need to be fine tuned for distinctions by gender, race, and ethnicity?
Seventh, in the absence of complete information on the economic returns to alternative investments in youth, are there guidelines that development practitioners can follow in designing youth programs that would prioritize youth investments in specific contexts in the short to medium term? One such guideline might be to focus on interventions that address highly prevalent problems, such as micronutrient supplements in poorly nourished populations or reproductive health interventions targeted to populations at high risk. Thus, examining the country context carefully may provide useful and immediate guidance as to which investments in youth are likely to yield the highest economic returns. In addition, some investments may provide benefits much sooner than others. For example, effective adult basic education and literacy training may raise labor productivity almost immediately. Investments involving a long lag before benefits are experienced will be attractive only in cases where the expected benefits are very large (e.g., reducing tobacco consumption). Lastly, investments in youth differ importantly in their distributional and gender effects. Often these differences are apparent from a careful consideration of the country context. In cases where investments in youth are targeted to specific groups, it may be relatively easy to identify those providing the highest returns.
ANNEX A
THE COMPONENTS OF BROAD EFFECTS OF INVESTMENTS IN YOUTH
Annex Table A11-1 lists the various components of broad effects of investments in youth. Each column in the table refers to a given broad effect. A “+” in a particular column indicates that the broad effect corresponding to that column includes the component corresponding to that row of the table. For example, column 1 refers to the broad effect of “increased education.” The table indicates that the components of this broad effect include “enhanced labor productivity,” “averted youth unemployment,” and “reduced child labor,” among others. Note that some of the components themselves are broad effects (e.g., “averted youth unemployment,” “reduced child labor”).
ANNEX B
METHODOLOGY USED TO CALCULATE THE BENEFIT/COST RATIO AND THE INTERNAL RATE OF RETURN
This annex calculates benefit/cost ratios and internal rates of return for various investments in youth using EXCEL spreadsheets in an extension of
ANNEX TABLE A11-1 The Components of Broad Effects of Investments in Youth
Components |
Units |
Enhanced labor productivity |
% |
Reduced underutilization of labor |
% |
Increased adult work effort |
% |
Increased social capital |
Crime rate |
Expanded access to risk-pooling services |
1 insured person |
Reduced age at which children achieve a given level of schooling |
1 year |
Reduced cost of medical care |
% |
Averted infertility |
1 woman |
Increased tax revenue |
$ |
Increased education |
1 year of schooling completed |
Averted youth unemployment |
1 youth |
Reduced child labor |
1 hour |
Averted teen pregnancy |
1 pregnancy |
Averted HIV infection |
1 infection |
Averted STIs |
1 infection |
Averted TB infections |
1 infection |
Improved health |
1 DALY |
Improved nutritional status (height) |
1 cm |
Improved nutritional status (body mass) |
% change in body mass index |
Improved nutritional status (anemia) |
1 anemic person |
Improved nutritional status (iodine deficiency) |
1 iodine-deficient person |
Improved nutritional status (Vitamin A deficiency) |
1 Vitamin A-deficient person |
Improved nutritional status (birthweight) |
1 kilo |
Reduced obesity |
1 obese person |
Improved mental health |
1 depressed person |
Delayed marriage |
1 year |
Averted drug/alcohol abuse |
1 person |
Averted physical and/or sexual abuse |
1 victim |
Averted crime |
1 criminal |
Improved self-esteem |
1 youth |
Averted female genital cutting |
1 victim |
Reduced fertility |
1 birth |
Averted abortion |
1 abortion |
Reduced tobacco use |
1 tobacco user |
Reduced violence and civil conflict |
1 death |
Averted social exclusion |
1 excluded person |
Averted orphans |
1 orphan |
Broad Effects |
|||||||||
(1) Increased Education |
(2) Averted Youth Unemployment |
(3) Reduced Child Labor |
(4) Averted Teen Pregnancy |
(5) Averted HIV Infection |
(6) Averted STIs |
(7) Improved Health |
(8) Improved Nutritional Status (Height) |
(9) Improved Nutritional Status (Body Mass) |
|
+ |
+ |
|
+ |
+ |
+ |
||||
|
+ |
|
|||||||
|
+ |
|
+ |
+ |
|
||||
|
+ |
|
|||||||
|
+ |
+ |
+ |
|
|||||
+ |
|
||||||||
+ |
|||||||||
+ |
+ |
|
|||||||
+ |
|
+ |
|
|
+ |
|
|||
+ |
+ |
|
|||||||
|
+ |
|
|||||||
+ |
|
+ |
+ |
+ |
+ |
|
+ |
|
|
|
+ |
+ |
|||||||
+ |
|
+ |
|
||||||
+ |
+ |
|
|||||||
+ |
|
+ |
|
||||||
|
+ |
|
|||||||
|
+ |
|
|||||||
+ |
|
+ |
|
+ |
+ |
|
|||
|
+ |
|
|||||||
+ |
|
||||||||
+ |
|
+ |
+ |
|
|||||
|
+ |
Components |
Units |
Enhanced labor productivity |
% |
Reduced underutilization of labor |
% |
Increased adult work effort |
% |
Increased social capital |
Crime rate |
Expanded access to risk-pooling services |
1 insured person |
Reduced age at which children achieve a given level of schooling |
1 year |
Reduced cost of medical care |
% |
Averted infertility |
1 woman |
Increased tax revenue |
$ |
Increased education |
1 year of schooling completed |
Averted youth unemployment |
1 youth |
Reduced child labor |
1 hour |
Averted teen pregnancy |
1 pregnancy |
Averted HIV infection |
1 infection |
Averted STIs |
1 infection |
Averted TB infections |
1 infection |
Improved health |
1 DALY |
Improved nutritional status (height) |
1 cm |
Improved nutritional status (body mass) |
% change in body mass index |
Improved nutritional status (anemia) |
1 anemic person |
Improved nutritional status (iodine deficiency) |
1 iodine-deficient person |
Improved nutritional status (Vitamin A deficiency) |
1 Vitamin A-deficient person |
Improved nutritional status (birthweight) |
1 kilo |
Reduced obesity |
1 obese person |
Improved mental health |
1 depressed person |
Delayed marriage |
1 year |
Averted drug/alcohol abuse |
1 person |
Averted physical and/or sexual abuse |
1 victim |
Averted crime |
1 criminal |
Improved self-esteem |
1 youth |
Averted female genital cutting |
1 victim |
Reduced fertility |
1 birth |
Averted abortion |
1 abortion |
Reduced tobacco use |
1 tobacco user |
Reduced violence and civil conflict |
1 death |
Averted social exclusion |
1 excluded person |
Averted orphans |
1 orphan |
Broad Effects |
|||||||||
(10) Improved Nutritional Status (Anemia) |
(11) Improved Nutritional Status (Iodine Deficiency) |
(12) Improved Nutritional Status (Vitamin A Deficiency) |
(13) Improved Nutritional Status (Birthweight) |
(14) Reduced Obesity |
(15) Improved Mental Health |
(16) Delayed Marriage |
(17) Averted Drug/Alcohol Abuse |
(18) Averted Physical and/or Sexual Abuse |
(19) Averted Crime |
+ |
+ |
+ |
|
|
+ |
|
+ |
|
+ |
+ |
+ |
+ |
+ |
+ |
+ |
|
|||
+ |
+ |
|
+ |
|
|||||
|
+ |
|
+ |
|
|||||
+ |
+ |
+ |
|||||||
+ |
+ |
+ |
|||||||
+ |
+ |
+ |
+ |
+ |
+ |
|
+ |
|
+ |
|
+ |
|
|||||||
+ |
|
||||||||
|
+ |
|
|||||||
|
+ |
|
|
+ |
|
|
+ |
|
|
|
+ |
+ |
|
|
|||||
|
+ |
|
+ |
+ |
|
||||
|
+ |
|
|||||||
+ |
+ |
+ |
+ |
|
|
+ |
|
Components |
Units |
Enhanced labor productivity |
% |
Reduced underutilization of labor |
% |
Increased adult work effort |
% |
Increased social capital |
Crime rate |
Expanded access to risk-pooling services |
1 insured person |
Reduced age at which children achieve a given level of schooling |
1 year |
Reduced cost of medical care |
% |
Averted infertility |
1 woman |
Increased tax revenue |
$ |
Increased education |
1 year of schooling completed |
Averted youth unemployment |
1 youth |
Reduced child labor |
1 hour |
Averted teen pregnancy |
1 pregnancy |
Averted HIV infection |
1 infection |
Averted STIs |
1 infection |
Averted TB infections |
1 infection |
Improved health |
1 DALY |
Improved nutritional status (height) |
1 cm |
Improved nutritional status (body mass) |
% change in body mass index |
Improved nutritional status (anemia) |
1 anemic person |
Improved nutritional status (iodine deficiency) |
1 iodine-deficient person |
Improved nutritional status (Vitamin A deficiency) |
1 Vitamin A-deficient person |
Improved nutritional status (birthweight) |
1 kilo |
Reduced obesity |
1 obese person |
Improved mental health |
1 depressed person |
Delayed marriage |
1 year |
Averted drug/alcohol abuse |
1 person |
Averted physical and/or sexual abuse |
1 victim |
Averted crime |
1 criminal |
Improved self-esteem |
1 youth |
Averted female genital cutting |
1 victim |
Reduced fertility |
1 birth |
Averted abortion |
1 abortion |
Reduced tobacco use |
1 tobacco user |
Reduced violence and civil conflict |
1 death |
Averted social exclusion |
1 excluded person |
Averted orphans |
1 orphan |
SOURCE: Knowles and Behrman (2005). |
Broad Effects |
|||||||
(20) Improved Self-Esteem |
(21) Averted Female Genital Cutting |
(22) Reduced Fertility |
(23) Averted Abortion |
(24) Reduced Tobacco Use |
(25) Reduced Violence and Civil Conflict |
(26) Averted Social Exclusion |
(27) Averted Orphans |
|
|
+ |
|
|
|
+ |
|
|
+ |
|
|
||||
|
+ |
+ |
+ |
|
|
||
+ |
|
||||||
|
|
+ |
|
|
+ |
+ |
+ |
+ |
|
||||||
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
|
+ |
||||||
+ |
|||||||
+ |
|||||||
+ |
|||||||
+ |
|||||||
|
+ |
|
|||||
|
+ |
|
+ |
|
|
||
+ |
|
||||||
|
+ |
|
|
||||
+ |
|
+ |
|
|
|||
+ |
|
||||||
|
+ |
a procedure previously used, for example, by Summers (1992, 1994). This procedure simplifies the process of doing the simulation experiments referred to above. The next section develops the methodology using matrix algebra notation so that interested readers can understand the details of the procedures. Some readers may wish to skim this section and proceed directly to the following section, which presents an illustration.
Methodology for Cost/Benefit Analysis
The objective is to estimate an s × 1 vector of discounted benefits (B) corresponding to an s × 1 vector of alternative investments38 in youth (H), expressed in thousands of US$ (for concreteness). Then this vector can be used together with an s × 1 vector (C) of the discounted costs, again corresponding to the s × 1 vector of alternative investments in youth (H), in order to calculate an s × 1 vector of cost/benefit ratios or an s × 1 vector of internal rates of return, once again with one element for each of the corresponding alternative investments in youth (H).
The procedure we use begins with a matrix (spreadsheet) of discounted effects (E) with m + n rows and s columns.39 The first m rows refer to directly monetizable effects of a $1,000 investment in youth. The last n rows refer to the broad effects of the investment (i.e., effects that cannot be directly monetized). The s columns refer to s alternative investments that is, H1, H2, H3,…, Hs. We partition the matrix of effects (E) into submatrices E1, containing the first m rows of E, and E2, containing the last n rows of E.40
We next define the broad effects translation matrix (T) with m + n rows and n columns, each (m + n) × 1 column of which lists first the m directly monetizable components of one of the n broad effects and then the n remaining components of one of the n broad effects. The elements in each column of matrix (T), that is, the components of each broad effect, are in fact discounted effects, while the last n rows of each column in matrix (T) are themselves discounted broad effects. We next partition the matrix (T)
conformably into submatrices T1, containing the first m rows of (T) (corresponding to directly monetizable effects), and T2, containing the last n rows of (T) (corresponding to broad effects). The matrix (T) embodies an important simplifying assumption, that is, that the components of each broad effect do not vary by intervention. Otherwise, the matrix (T) would be much larger (i.e., (m + n) × n × s instead of only (m + n) × n).
Lastly, we define an (m + n) × 1 vector of benefits (Z) corresponding to one unit of each of the m + n directly monetizable and broad effects.41 We partition Z into Z1, containing the first m elements of Z, and Z2, containing the last n elements of Z. The first m elements of vector Z (Z1)—the benefits associated with directly monetizable effects—are estimated directly. The last n elements of vector Z (Z2)—the benefits associated with the broad effects—are calculated by transposing the rows and columns of the two submatrices in matrix T to obtain the n × m submatrix T1' and the n × n submatrix T2', and then postmultiplying T1' by the m × 1 vector Z1 and adding it to the expression obtained by postmultiplying T2' by the n × 1 vector Z2:
![](/openbook/0309096804/xhtml/images/p2000df43g483001.jpg)
Which implies:
![](/openbook/0309096804/xhtml/images/p2000df43g483002.jpg)
Where I is the n × n identity matrix (i.e., matrix with 1s on the diagonal and zeroes elsewhere). In some cases, we may want to use indirect estimates of the benefits of broad effects rather than estimating them directly (i.e., use indirect estimates for some elements of Z2, rather than basing them on estimates of the corresponding elements of (I − T2')−1T1' Z1).
Under these assumptions, the s × 1 vector of discounted benefits (B) corresponding to s alternative investments in youth (H) is given by:
![](/openbook/0309096804/xhtml/images/p2000df43g483003.jpg)
The vector of discounted benefits (B) is compared to the vector of discounted costs (C), both of which are discounted to the same age (e.g., age 18, or the age at which a given investment is assumed to occur). The benefit/cost ratio (BCR) for a given investment s is defined as:
![](/openbook/0309096804/xhtml/images/p2000df43g483004.jpg)
Where bs refers to element s of B and cs refers to element s of C.
The internal rate of return (IRR) for a given investment s (IRRs) is calculated as the discount rate that makes bs = cs.
A separate set of matrices (spreadsheets) in principle should be used for different categories of countries (e.g., grouped according to their per capita income), for different genders, and for other groups (e.g., ethnic minorities) for which disaggregated analysis is needed. The limited availability of the necessary disaggregated estimates, however, limits the extent to which such disaggregation currently is possible.
A Hypothetical Illustration of the Methodology
We illustrate the methodology with a (relatively) simple, purely hypothetical example. For our example, we take the case of an investment (e.g., a scholarship program for girls) designed to increase the amount of schooling a girl has by one year. We assume that the target group of girls would have quit school at age 13 after completing six grades, in the absence of the investment, and that with an investment of $1,000, we are able to keep 10 girls age 13 in school until they complete seven years of schooling, at which point they will be age 14. The $1,000 investment consists of the following costs: $250 in distortionary costs to raise the revenues to finance this investment, $100 for the program’s administrative costs, $300 in costs to accommodate the additional 10 girls in school (i.e., $30 per enrolled pupil), $250 of household investments, largely in the form of foregone earnings of the girls, and a discounted cost of $100 for the girls’ children to continue their schooling beyond the grade at which they otherwise would have left school.
We assume that the effect of the hypothetical investment is to increase schooling among the 10 girls by a total of 10 school years (one completed school year per scholarship beneficiary) and that this increase in years of schooling completed results in a proportionate increase in education (as measured by cognitive achievement). However, increased education is a broad effect assumed to have the following components:
-
Each girl’s labor productivity increases by 10 percent from age 16 until retirement (assumed to occur at age 60).
-
Completed fertility is reduced by one child (i.e., the average woman decides not to have a fifth child at age 36).
-
Each girl’s health improves by 0.05 DALYs per year, beginning at age 14 and continuing throughout her lifetime (which is assumed to be 70 years).
-
The health of each of the girls’ four children is assumed to improve by 0.05 DALYs beginning at her age 36 and continuing for the 18 years that her children are assumed to spend with her.
-
Each of the girls’ four children completes 0.5 years more schooling than they otherwise would have completed by the time each girl (woman) reaches age 40.
-
The probability that the girls will be infected by HIV decreases by 0.01 from age 15 to 24.
Most of the above components of increased education are directly monetizable effects. However, the increased education that the girls’ children are assumed to receive is a broad effect assumed to have the same components as the girls’ own increased education (but with substantially longer lags). But, in the case of the girls’ children, it is assumed that there is no effect of the investment on their own children’s schooling or on their children’s risk of contracting HIV. In addition, each HIV infection averted is assumed to be a broad effect with the following components (reflecting the additional assumptions that a girl, if infected with HIV, would be infected on average at age 20, that the infection would turn into AIDS at age 25, and that she would die as soon as she turns 27):
-
The additional medical care necessary to treat a person with AIDS is averted at ages 25 and 26 (i.e., during the last two years of life).
-
There is an improvement in health equivalent to 34.6 DALYs at age 27.
Annex Table B11-1 presents the assumed effects (including the components of broad effects) of this hypothetical investment over each girl’s lifecycle.
There is only one effect in Annex Table B11-2, the broad effect of 10 girls receiving one additional year of schooling at age 14. Because the benefits are discounted to age 18, the effect of the investment is shifted forward to age 18, using the discount rate. The last three effects (i.e., the last three rows of the table) are broad (i.e., not directly monetizable) effects.
Annex Table B11-3 presents the broad effects translation matrix (T) for this hypothetical example. The numbers presented in this table are the cumulative sums of the annual effects presented in Annex Table B11-1 discounted to age 18.
The unit benefits associated with each of the assumed effects are assumed to be as follows:
Enhanced labor productivity. Each woman’s full earnings are assumed to be $100 annually.
Reduced fertility. The value to society of averting each woman’s fifth birth at age 36 is assumed to be $50 (based on the least cost alternative means of reducing fertility by one birth).
Improved health. The value to society of each DALY gained is assumed to be $10 (based on the assumed cost per DALY gained from the least cost alternative investment to improve health).
ANNEX TABLE B11-1 Assumed Timing of Lifecycle Effects for One Girl in Hypothetical Girls’ Scholarship Example
Age |
Increased Education |
Enhanced Labor Productivity |
Reduced Fertility |
Improved Health |
Improved Health of Children |
Discounted (to age 18) cumulative sum of effect |
1.2155 |
2.0576 |
0.4155 |
1.1972 |
1.0200 |
Age 13 |
0 |
0 |
0 |
0 |
0 |
14 |
1 |
0 |
0 |
0.05 |
0 |
15 |
0 |
0 |
0 |
0.05 |
0 |
16 |
0 |
0.1 |
0 |
0.05 |
0 |
17 |
0 |
0.1 |
0 |
0.05 |
0 |
18 |
0 |
0.1 |
0 |
0.05 |
0 |
19 |
0 |
0.1 |
0 |
0.05 |
0 |
20 |
0 |
0.1 |
0 |
0.05 |
0 |
21 |
0 |
0.1 |
0 |
0.05 |
0 |
22 |
0 |
0.1 |
0 |
0.05 |
0 |
23 |
0 |
0.1 |
0 |
0.05 |
0 |
24 |
0 |
0.1 |
0 |
0.05 |
0 |
25 |
0 |
0.1 |
0 |
0.05 |
0 |
26 |
0 |
0.1 |
0 |
0.05 |
0 |
27 |
0 |
0.1 |
0 |
0.05 |
0 |
28-35 |
0 |
0.1 |
0 |
0.05 |
0 |
36 |
0 |
0.1 |
1 |
0.05 |
0.2 |
37 |
0 |
0.1 |
0 |
0.05 |
0.2 |
38 |
0 |
0.1 |
0 |
0.05 |
0.2 |
39 |
0 |
0.1 |
0 |
0.05 |
0.2 |
40 |
0 |
0.1 |
0 |
0.05 |
0.2 |
41-53 |
0 |
0.1 |
0 |
0.05 |
0.2 |
54-60 |
0 |
0.1 |
0 |
0.05 |
0 |
61-69 |
0 |
0 |
0 |
0.05 |
0 |
70 |
0 |
0 |
0 |
0.05 |
0 |
Increased Education of Children |
Reduced Risk of HIV Infection |
Improved Health (HIV) |
Decreased Medical Care (HIV) |
Discount Factor |
0.6837 |
0.0939 |
22.3035 |
1.3875 |
|
0 |
0 |
0 |
0 |
1.2763 |
0 |
0 |
0 |
0 |
1.2155 |
0 |
0.01 |
0 |
0 |
1.1576 |
0 |
0.01 |
0 |
0 |
1.1025 |
0 |
0.01 |
0 |
0 |
1.0500 |
0 |
0.01 |
0 |
0 |
1.0000 |
0 |
0.01 |
0 |
0 |
0.9524 |
0 |
0.01 |
0 |
0 |
0.9070 |
0 |
0.01 |
0 |
0 |
0.8638 |
0 |
0.01 |
0 |
0 |
0.8227 |
0 |
0.01 |
0 |
0 |
0.7835 |
0 |
0.01 |
0 |
0 |
0.7462 |
0 |
0 |
0 |
1.0 |
0.7107 |
0 |
0 |
0 |
1.0 |
0.6768 |
0 |
0 |
34.6 |
0 |
0.6446 |
0 |
0 |
0 |
0 |
— |
0 |
0 |
0 |
0 |
0.4155 |
0 |
0 |
0 |
0 |
0.3957 |
0 |
0 |
0 |
0 |
0.3769 |
0 |
0 |
0 |
0 |
0.3589 |
2 |
0 |
0 |
0 |
0.3418 |
0 |
0 |
0 |
0 |
— |
0 |
0 |
0 |
0 |
— |
0 |
0 |
0 |
0 |
— |
0 |
0 |
0 |
0 |
0.0791 |
ANNEX TABLE B11-2 Effects Matrix (E) for Hypothetical Scholarship Program for 10 Girls
Effects of Hypothetical Investment |
Scholarship Program |
Enhanced productivity |
0.0000 |
Reduced fertility |
0.0000 |
Improved health |
0.0000 |
Improved health of children |
0.0000 |
Decreased medical care expenditure |
0.0000 |
Increased education |
12.1551 |
Increased education of children |
0.0000 |
Averted HIV infections |
0.0000 |
SOURCE: See text. |
ANNEX TABLE B11-3 Broad Effects Translation Matrix (T) of Hypothetical Scholarship Program for Girls
Components of Broad Effects |
Broad Effects Increased Schooling |
Increased Schooling of Children |
Averted HIV Infections |
Enhanced productivity |
2.0576 |
2.0576 |
0 |
Reduced fertility |
0.4155 |
0.4155 |
0 |
Improved health |
1.1972 |
1.1972 |
22.3035 |
Improved health of children |
1.0200 |
1.0200 |
0 |
Decreased medical care expenditure |
0 |
0 |
1.3875 |
Increased schooling |
0 |
0 |
0 |
Increased schooling of children |
0.6837 |
0 |
0 |
Averted HIV infections |
0.0939 |
0 |
0 |
SOURCE: See text. |
Decreased medical care expenditure. The medical care expenditure for HIV-infected persons is assumed to be $270 annually during their last two years of life.
The full unit benefit vector (Z) for this hypothetical example is presented in Annex Table B11-4.
ANNEX TABLE B11-4 Benefit Vector (Z) for Hypothetical Example of Scholarship Program for Girls
Benefits |
Elements of Vector Z |
Enhanced productivity |
100 |
Reduced fertility |
50 |
Improved health |
10 |
Improved health of children |
10 |
Decreased medical care expenditure |
270 |
Increased schoolinga |
475 |
Increased schooling of childrena |
249 |
Averted HIV infectionsa |
597 |
aElements obtained by solving the equation above for Z2, i.e., Z2 = (I − T2')−1 T1' Z1. SOURCE: See text. |
REFERENCES
Alderman, H., Behrman, J.R., Ross, D., and Sabot, R. (1996). The returns to endogenous human capital in Pakistan’s rural wage labor market. Oxford Bulletin of Economics and Statistics, 58(1), 29-55.
Angrist, J.D., Bettinger, E., Bloom, E., King, E., and Kremer, M. (2002). Vouchers for private schooling in Colombia: Evidence from a randomized natural experiment. American Economic Review, 92(5), 1535-1559.
Ballard, C., Shoven, J., and Whalley, J. (1985). General equilibrium computations of the marginal welfare costs of taxes in the United States. American Economic Review, 75(1), 128-138.
Becker, G.S. (1967). Human capital and the personal distribution of income: An analytical approach (Woytinsky Lecture). Ann Arbor, MI: University of Michigan. (Republished in Human capital [2nd ed.] pp. 97-117) 1975, New York: National Bureau of Economic Research.
Behrman, J.R., and Knowles, J.C. (1998a). The distributional implications of government family planning and reproductive health services in Vietnam. (Prepared for the Rockefeller Foundation). Philadelphia: University of Pennsylvania.
Behrman, J.R., and Knowles, J.C. (1998b). Population and reproductive health: An economic framework for policy evaluation. Population and Development Review, 24(4), 697-738.
Behrman, J.R., and Knowles, J.C. (1999). Household income and child schooling in Vietnam. World Bank Economic Review, 13(2), 211-256.
Behrman, J.R., Ross, D., and Sabot, R. (2005). Improving the quality versus increasing the quantity of schooling: Evidence from rural Pakistan. Pennsylvania Institute for Economic Research. (PIER Working Paper 02-022.) Available: http://www.econ.upenn.edu/Centers/pier/Archive/02-022.pdf [accessed September 2005].
Caribbean Group for Cooperation in Economic Development (CGCED). (2002, June). Youth development in the Carribbean. (Draft Report No. 24163-LAC.) Washington, DC: The World Bank.
Commission on Macroeconomics and Health. (2001). Macroeconomics and health: Investing in health for economic development. Geneva, Switzerland: World Health Organization.
Devarajan, S., Squire, L., and Suthiwart-Narueput, S. (1997). Beyond rate of return: Reorienting project appraisal. World Bank Research Observer, 12(1), 35-46.
Feldstein, M. (1995). Tax avoidance and the deadweight loss of the income tax. (NBER Working Paper No. 5055.) Cambridge, MA: National Bureau of Economic Research.
Harberger, A.C. (1997). New frontiers in project evaluation? A comment on Devarajan, Squire, and Suthiwart-Narueput. World Bank Research Observer, 12(1), 73-79.
Knowles, J.C., and Behrman, J.R. (2003). Assessing the economic returns to investing in youth in developing countries . (For World Bank Human Development Network.) Bangkok, Thailand/Philadelphia: University of Pennsylvania.
Knowles, J.C., and Behrman, J.R. (2005). The economic returns to investing in youth in developing countries: A review of the literature. (World Bank Human Development Network; Health, Nutrition and Population Discussion Paper.) Available: www.worldbank.org/hnp>publications>Discussion Papers [accessed June 2005].
McGuire, J.S. (1996). The payoff from improving nutrition. Unpublished manuscript, World Bank, Washington, DC.
Miguel, E., and Kremer, M. (2002). Why don’t people take their medicine: Experimental evidence from Kenya. Unpublished manuscript, Harvard University and University of California, Berkeley.
Miguel, E., and Kremer, M. (2004). Worms: Identifying impacts on education and health in the presence of treatment externalities. Econometrica, 72(1), 159-217.
Psacharopoulos, G. (1994). Returns to investment in education: A global update. World Development, 22(9), 1325-1344.
Ravallion, M., and Wodon, Q. (2000). Does child labor displace schooling? Evidence from behavioral responses to an enrollment subsidy. Economic Journal, 110(462), 158-175.
Rosenzweig, M.R., and Wolpin, K.J. (1986). Evaluating the effects of optimally distributed public programs. American Economic Review, 76(3), 470-487.
Summers, L.H. (1992). Investing in all the people. Pakistan Development Review, 31(4), 367-406.
Summers, L.H. (1994). Investing in all the people: Educating women in developing countries. (Economic Development Institute Seminar Paper No. 45.) Washington, DC: World Bank.
van der Gaag, J., and Tan, J.P. (1997). The benefits of early child development programs: An economic analysis. Washington, DC: Author.
World Bank. (1999). Curbing the epidemic: Governments and the economics of tobacco control. Washington, DC: Author.
World Bank. (2002a). Optimizing the allocation of resources among HIV prevention interventions in Honduras. Washington, DC: Author.
World Bank. (2002b). Review of World Bank supported projects in adult basic education and literacy, 1997-2002. Washington, DC: Author.
World Bank. (2002c). School health toolkit. Washington, DC: Author.