The height production function from birth to maturity

Starting in the 1970s, anthropometric measures have increasingly been used in the social sciences as indicators of social well-being. Since then, adult height has been considered an indicator of the general health status in life, of the relative risk of survival, and labor productivity (Fogel, 1986). In particular, Case and Paxson (2008) explain the positive correlation between adult height and labor productivity by showing that height is positively associated with cognitive ability. They show that both cognition and height are driven by early childhood investments and therefore cognitive achievements are correlated with height, and wages are affected by cognitive skills. Poor health can explain both low height and low labor productivity. This is more evident in developing countries where living conditions are poor. However, adult height is just the final result of a process of growth that involves many different mechanisms and variables, and most of the common evidence looks at adult height (Steckel, 2009). It is therefore necessary to investigate the factors driving height, since understanding the determinants of height is important in order to understand health (Deaton, 2007). The determinants of height can be divided into non-genetic factors, genetic factors and the age when height is measured. The principal non- genetic factor is net nutrition which is the difference between food intake and the losses to activities and to diseases (Eveleth and Tanner, 1991).

To study the determinants of height from birth to maturity I use in my last CSAE working paper the Cebu Longitudinal Health and Nutrition Survey (CLHNS), which is a rich longitudinal survey of a cohort of Filipino children followed from conception, in 1983-84, to 2005. The distribution of height by age and sex is shown in Figure 1.

Figure 1: Height distribution by age and gender of the child. The dots correspond to the raw height measurements, while the lines correspond to spline interpolation of the mean height per gender and age of the child.

I build and estimate a height production function which depends on age, previous investments in the child, biological endowment and a shock. To study empirically the height production function, I assume (A) that the child’s biological endowment is determined at conception and is constant over time, and (B) that the height production function is linear in the inputs and in the unobserved endowment, and that the effects of the inputs depend on the child’s age. I can then specify a model where the current height is regressed on a function of age (linear and a quadratic age), current and past inputs (nutrition and diseases), a child’s fixed effect and a shock.

The nutrition inputs considered are the caloric intake and breast feeding. I distinguish between diseases experienced during infancy, pre-puberty and puberty because they are age-dependent and might have a different impact on a person’s growth, and moreover the data contain different measures of morbidity that differ between waves. In particular, I consider diarrhea episodes experienced during infancy, length of stay in the hospital during pre-puberty, and hospitalization during puberty (dummy if the child has been hospitalized).

In order to estimate this model, I consider a within-child fixed effects specification (FE) where I estimate the change in height between two consecutive measurements, remaining only with the contemporaneous inputs. However, contemporaneous inputs could respond to previous shocks causing endogeneity because correlated to unobserved parental preferences regarding their children’s nutrition and preventative care. I address endogeneity of both nutrition and diseases by using variation in village-level food prices, village and household characteristics, and climatic shocks as instrumental variables (IV) to estimate the production parameters via IVFE.

The IVFE results show that the diarrhea episodes experienced during infancy, and in particular in the second year of life, have the largest and negative effects on height. If experienced in the first year of life, an increase by one of the diarrhea episodes decreases the height of a boy by 1.376 cm, and the height of a girl by 2.113 cm. Experiencing an extra episode of diarrhea in the second year of life, reduces the height of a boy by 2.214 cm, and the height of a girl by 3.171 cm. Diseases experienced later in life and measured with time spent in the hospital or number of hospitalizations do not seem to affect height. Pre-puberty (age 8 and 11) is dominated by the effects of nutrition. The IVFE estimates show that if caloric intake increases by 100 kcal then height increases in 8 year old boys by 0.199 cm, in 11 year old boys by 0.246 cm, and in 11 year old girls by 0.200 cm. It might be that the pre-puberty years prepare the body for the final phase of growth, and that might explain the relevance of nutrition inputs at age 11 and also age 8 for boys.

Overall, these results show that growth in infancy and in the pre-puberty years turn out to be critical stages in the process of height formation. This is in line with the increasing literature on the long term effects of early life conditions (Almond and Currie, 2011) and with new studies that reveal the importance of later critical periods (van den Berg et al., 2014). Most importantly the paper shows that some critical periods are important because diseases experienced during infancy play a major role compared to nutritional intake. This might be important to design policy interventions that target individuals in these critical periods to improve their health and potentially their socio-economic outcomes later in life.


Elisabetta De Cao – Centre for Health Service Economics & Organisation, University of Oxford

New Radcliffe House (2nd floor), Walton Street, Oxford, United Kingdom (e-mail:;


Almond, G. and J. Currie, 2011. Human capital development before age five. In O. Ashenfelter, R. Layard, and D. Card, editors, Handbook of Labor Economics, volume 4B, chapter 15, pages 1315–1486. Amsterdam, The Netherlands: North- Holland.

Case, A. and C. Paxson, 2008. Stature and status: Height, ability, and labor market outcomes. Journal of Political Economy, 116(3):499–532.

Deaton, A., 2007. Height, health, and development. Proceedings of the National Academy of Sciences, 104(33):13232–13237.

Eveleth, P. and J. M. Tanner, 1991. World-Wide Variation in Human Growth. Cambridge. Cambridge University Press, second edition.

Fogel, R., 1986. Physical growth as a measure of the economic well-being of popula- tions: The eighteenth and nineteenth centuries. In F. Falkner and J. M. Tanner, editors, Human Growth: A Comprehensive Treatise, volume 3, pages 263–281. New York: Plenum Press.

Steckel, R. H., 2009. Heights and human welfare: Recent developments and new directions. Explorations in Economic History, 46(1):1–23.

van den Berg, G. J., P. Lundborg, P. Nystedt, and D. O. Rooth, 2014. Critical periods during childhood and adolescence. Journal of the European Economic Association, 12(6):1521–1557.



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Community-Based Development initiatives: Who in the village hears about them and who doesn’t? And how?

Community-based development programmes, known for placing greater control of resources and decision-making in local hands, have long been an important part of development policy. But these programmes are also behest with their own challenges and limitations. One of these is the spread of information: those who might stand to benefit the most from these programmes (such as the elderly and disabled) might be the least likely to hear about them. It is hard to benefit from something you’re unaware of. Community-based development initiatives often rely heavily on village meetings and media campaigns (e.g. radio, television and newspapers) to sensitise communities and to encourage participation. But vulnerable groups such as the elderly and disabled may not have (easy) access to such direct sources of information because of physical or socio-economic constraints.

Village meeting

We tend to learn information from our peers, so it is possible that interactions within a person’s social network might compensate for a lacklustre information campaign. One of my recent CSAE working papers sets off to investigate the extent to which neighbours may influence the awareness of elderly and disabled groups in rural Tanzania. My paper examines this in the context of Tanzania Social Action Fund II (TASAF II), one of Tanzania’s flagship community-based development projects, funded by the World Bank. Launched in May 2005 as an important component within the national framework of the Tanzanian National Strategy for Growth and Reduction of Poverty (popularly known as MKUKUTA), TASAF II followed its predecessor TASAF I (2000–2005) in the aim of empowering local communities to participate in development initiatives. Among the communities explicitly targeted by TASAF II are vulnerable groups comprising orphans, disabled, elderly, widows/widowers and those infected by HIV/AIDS. These vulnerable groups could collectively apply for funding to start up income generating group activities.

Most of the activities implemented by TASAF during the first two years of implementation (2005–2007) were aimed at creating programme awareness, by means of national and regional radio programmes, newspapers, newsletters, television shows, technical launch workshops, village meetings and the distribution of brochures, posters, t-shirts and caps. And yet, as has recently been shown by Baird et al. (2013), in 2008 less than half of TASAF’s eligible non-beneficiary households reported to have ever heard about the program, and that was after the funds had already been allocated.

Baird et al. (2013) identify a household’s direct access to information (such as education and village meeting attendance rate) and their immediate access to local politicians and other decision makers (e.g. being blood related to the village elite) as the dominant determinants of being informed about TASAF. I contribute to this evidence base by considering whether social interactions with neighbours played a role in the information reaching more widely and, if so, whether different households benefitted differently from information in their neighbourhood.

To answer this empirical question I used household data from a listing exercise organised by the World Bank in April–November 2008 collected in the context of an impact evaluation of TASAF II. This unique dataset captures the details of 30,339 households, including all elderly and disabled people (19,916 households), in 100 villages from 5 regions in rural Tanzania. The dataset includes, among other things, global positioning system (GPS) coordinates of each of these households in the dataset and information about their knowledge of TASAF.


Using a two-stage least squares estimation strategy derived from Bramoulle et al. (2009) and De Giorgi et al. (2010), I find that, on average, for each additional informed neighbour in a set of 10 nearest neighbours, the respondent of a household with disabled or elderly members was approximately 8 percentage points more likely to be informed about TASAF. To put this into context, compare this estimated peer effect with the impact of attending village meetings (i.e. the sensitisation medium most heavily relied on by TASAF): having two informed neighbours among one’s ten nearest neighbours had, on average, a similar impact on the probability of being informed as had attending a village meeting (15% and 14%, respectively).

My paper also looks at which types of elderly and disabled households were most and least receptive to information in the neighbourhood, and which households (vulnerable and non-vulnerable) were most effective in transmitting information to others. The results suggest that households with members holding political positions were relatively more effective in the transmission of information to others. Moreover, the economically worse-off households benefitted most from the presence of well-informed neighbours. This is not surprising, as better off households are likely to have better access to primary sources of information, such as radio and newsletters and, therefore, are less therefore likely to rely on peers for information.

Importantly, the following groups turned out to be least sensitive to information in the neighbourhood: the oldest of the elderly members, female-headed households living in a male-dominated neighbourhood, those who do not have blood relatives living in the village, those who are uneducated and/or unemployed and/or those who do not belong to the main religion of the village.

Although we should be careful in generalising these results to other demographic groups and other geographic contexts, this new piece of evidence points out that there are people who are not only restricted in their access to direct sources of information (e.g. village meetings, radios, television, etc.) but who also lack indirect access to information through social networks. If the aim is to maximise inclusion in  community-based development programmes, especially those targeted at the most vulnerable people, it may be desirable to target some demographic groups separately with complementary – specifically designed – sensitisation strategies which take these constraints into account (e.g. through targeted home visits).

Bet Caeyers – Institute for Fiscal Studies (

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Gender equity in schools in Muslim countries: it can be done

Muslim countries worldwide have problems with gender equality. They dominate the bottom ten countries in the Global Gender Gap Report and none of the ten most successful countries offering equal opportunities for men and women is Muslim.

Girls lag behind boys in school attendance, making up 54% of the out-of-school child population in the Arab states, a figure that has not changed since 2000. Of the ten countries that fare the worst for child school attendance rates, seven are Muslim. These are Nigeria, Pakistan, Ethiopia, Cote d’Ivoire, Burkina Faso, Niger and Yemen: countries that are often considered hotspots for acts of violence against women and school girls.

The near-fatal attack on Malala Yousafzai by a Taliban gunman in Pakistan two years ago reminds us of the challenging circumstances in which girls attend school in many Muslim countries. Her subsequent fight for education for girls and children worldwide won her this year’s Nobel Peace Prize.

Earlier this year, as many as 276 school girls were abducted for similar reasons in the Borno state of Nigeria. Their captors from the extremist Boko Haram group consider secular education a grave threat to Islam. Frequent attacks on schools in Nigeria have forced many parents to withdraw girls from education. In some states schools have even closed down for fear of insurgent attacks. More recently a Boko Haram-style armed group warned schools in Pakistan against co-education. It’s little wonder Nigeria and Pakistan together account for a quarter of the world’s out-of-school children.

Many Muslim nations fare poorly for gender equity, but there are steps they can take and examples they can follow to make sure girls are properly educated. Flickr/Nevil Zaveri, CC BY-SA

Why this inequity in Muslim nations?

In many Muslim countries women are subjected to patriarchal norms and varying degrees of restriction on economic participation. This reduces the value of girls’ education in society.

Some scholars blame culture and religion for this problem. Others say the economic structure of some Muslim countries is not conducive to women’s development. They argue patriarchal norms persist because oil‐rich economies limit the role of women in the paid workforce and restrict women’s participation in politics.

Not all Muslim nations suffer gender inequity in education

Within the Middle East, a region widely considered to lack progress in girls’ education, Turkey is very close to eliminating the gender gap in schooling. In Quwait, UAE, Bahrain and Libya, more girls are in secondary school than boys and there is gender parity in primary enrolment.

Much clearer success stories are emerging outside the Arab world. In Indonesia, the world’s most populous Muslim country, equal numbers of girls and boys are in school. In neighbouring Malaysia, boys even lag behind girls at almost all levels of education.

Muslim nations in South-East Asia have a better record of educating girls. Flickr/Andy Maluche, CC BY

In the Borno state of Nigeria, half of ten-year-old girls remain out of school, a situation Malaysia overcame nearly three decades ago. A similar pattern is visible in Bangladesh where girls outnumber boys in primary as well as secondary school. Neither religious orthodoxy nor income poverty could keep girls away from schools in this Muslim majority nation.

What explains these contrasts within the Muslim world?

The answer lies partly in different policy choices. Even though public spending on education hasn’t increased significantly, the Bangladesh government prioritised women’s development through gender-responsive budgeting and partnered with non-state providers to make up for gaps in public investment.

The government introduced nation-wide scholarship schemes for school-aged girls. NGOs were also encouraged to run development programs targeting girls and women in rural communities. The coordinated push for greater educational opportunities for girls was matched by large-scale deployment of rural women as providers of social services as well as micro-entrepreneurs.

This helped to quickly shift the cultural norm in girls’ social participation. The absence of such a “big push” in Pakistan probably explains why it has fallen behind Bangladesh in terms of girls’ education. The Global Gender Gap index ranks Bangladesh (75) much higher than other Muslim majority countries such as Saudi Arabia (127), Iran (130) and Pakistan (135).

Neither poverty nor patriarchy stands in the way of women’s development in some Muslim countries. Flickr/Guy Nesher, CC BY

Malaysia’s approach to girls’ education was more conventional. Inspired by the success of high-performing East Asian economies such as South Korea, Malaysia prioritised education for all. Long before experiencing double-digit growth rates, Malaysian education spending was much higher than that of other developing countries. According to the World Bank’s World Development Indicators, by 1970 gross female primary school enrolment in Malaysia was nearly three times higher than that of Nigeria.

In Malaysia, democracy, development and equitable growth in early years reduced the demand for extreme views. This may explain why female schooling has never been undermined in Malaysia by religious extremism or violence caused by “Islamic” radical groups like Boko Haram.

What is happening in Nigeria is a reflection of long-term deprivation of basic health and education services. Despite plentiful natural resources, human development was never a priority. The country’s oil rent was not used productively to build schools and boost literacy rates.

The absence of a functional democracy, poor governance and widespread corruption may have fuelled demand for a puritanical Islamic regime and allowed extremists groups like Boko Haram to thrive. Boko Haram has emerged in the poorest part of Nigeria where nearly three-quarters of the population live in abject poverty. Nigeria remains one of the few developing countries where more than 20% of primary school-aged children will remain out of school by 2015.

The success stories of Indonesia and Malaysia highlight the importance of sustained public investment. And Bangladesh proves that if gender equity is prioritised, rapid progress is possible despite limited economic capacity. These three countries show that neither poverty nor patriarchy can stand in the way of women’s development in Muslim societies.

The lesson for the rest of the Muslim world is that schooling gender gaps can be narrowed, as long as there is a political consensus on achieving education for all. A lack of consensus can encourage religious extremism and opposition to inclusive development. This will further limit the prospect of women’s empowerment through education.

* Niaz Asadullah is Professor of Development Economics and Deputy Director of the Centre for Poverty and Development Studies (CPDS) at the University of Malaya. He is a Research Affiliate of the CSAE.

The article was first published on The Conversation.


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The Future in Mind: Aspirations and Forward-Looking Behaviour in Rural Ethiopia

A person’s aspirations, or goals and targets for their future, can be a driving force in their life, providing motivation and guiding their choices. In forming aspirations, all people dismiss some options for their future lives, and fail to even imagine other options or opportunities. Once formed, aspirations can limit the possible futures we consider by focusing our attention on some future options and filtering out others.

Poor people who have faced the ongoing struggles of living in poverty may struggle to believe that a better life is possible. Their aspirations may reflect beliefs that their future opportunities are limited, that there is limited potential for a change in their circumstances, or that they have limited capabilities to change their lives. As a result, they may be unwilling to invest in certain opportunities.

Role models could help change all that. A new paper, co-authored by Tanguy Bernard (IFPRI/University of Bordeaux), Stefan Dercon (University of Oxford), Kate Orkin (University of Cambridge) and Alemayehu Seyoum Taffesse (IFPRI), suggests that when people see inspiring examples of other people changing their lives, they may revise their aspirations and alter their choices regarding investments, savings, and even education for their children.

In a randomized field experiment conducted in 64 rural Ethiopian villages in 2010 and 2011, poor participants were shown short documentaries in which people of similar socio-economic backgrounds tell personal stories about how they were able to change their circumstances and better their lives. Importantly, the documentaries emphasize hard work, goal-setting, and careful decision-making – none of the people interviewed in the documentaries became extremely successful, but all moved out of poverty without the help of government programs or NGOs. The documentaries and an example of a placebo are available here.

The experiment found that these documentaries had increased participants’ aspirations six months after viewing the one-hour documentary. Participants who were invited to a documentary screening were compared to both a control and a “placebo” group shown short comedy sketches. Here we focus on comparisons between the treatment and control group.

The treatment group increased their total saving (by 97 birr compared to the control group mean of 182 birr) and total amount taken in credit (by 21 birr compared to the control group mean of 101 birr). Exposure to the documentaries also increased parents’ immediate investments in their children’s education. The number of children between 6 and 15 who are enrolled increases by 0.21, a 21 per cent increase from the baseline average of 1.02 children enrolled in school across all groups and 17 per cent larger than the control group average of 1.23 at the time of the endline survey. Treated households spend 33 ETB (17 per cent more) more on school expenses than the control group average of 197 birr in the same period.

The bars on the graph below show the effect on outcomes of being invited to the documentary, compared to the control group. The black lines are 90 per cent confidence intervals for the effect. If the ends of the black lines are always above zero, we conclude that there is a statistically significant difference between the control group and the group who saw the documentary.

treatment v control ed spending credit

Varying the number of individuals exposed to documentaries across villages, the authors also find evidence of peer effects, with the  number of a person’s friends invited to the documentary further contributing to his/her decision to further invest in children education.

The authors also show that the documentaries altered psychological measures of people’s perception of whether they are able to shape their lives and future. The intervention increased the extent to which people think their life’s outcome depends on their own actions and choices and decreases the extent to which they see poverty as a condition determined by fate. Psychologists have shown that these measures are correlated with individuals setting higher aspirations, so these results provide further support for the aspirations results in the paper. The authors also show that the documentaries did not alter people’s preferences in relation to risk, nor the extent to which they discount the future, ruling out some of the other possible explanations for the change.

All the results were measured six months after the one-hour documentary screenings occurred. The randomized experimental design ensures that any changes in behavior could only be due to the intervention, not to any other changes. The nature and extent of responses in the treatment group are surprising and make a strong case for further research on the psychological effects of poverty and on the role interventions to reduce these effects may play in reducing poverty.


The research paper is available here.
The paper has also been discussed on the Development Impact blog, here.
Documentaries and one of the placebo videos used in the RCT are here.

This research was funded by the United Kingdom Department for International Development (DFID) as part of the Institutions for Pro- Poor Growth Consortium (iiG), a research programme to study how to improve institutions for pro-poor growth in Africa and South-Asia. Production of the documentaries used in the randomized controlled trial was funded by SEVEN (Social Equity Venture Fund) through the Open Enterprise Solutions to Poverty competition. Bernard and Taffesse acknowledge the support of the International Food Policy Research Institute (IFPRI) Development Strategy and Governance and Markets, Trade and Institutions divisions. The views expressed are not necessarily those of the funders.

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Subjective Well-being and Social Evaluation in a Poor Country

China’s remarkable rate of economic growth since the start of economic reform is generally assumed to have raised the economic welfare of the Chinese people dramatically. This is regarded as self-evident from the facts that, in less than three decades, average real income per capita rose more than six times and that more than 300 million people were lifted out of ‘dollar a day’ poverty (Ravallion and Chen, 2007). Moreover, within a quarter of a century China’s ‘human development index’ rose from 0.37 to 0.68 (UNDP, 2010: table 2). For us to question whether economic growth has raised happiness in China appears either absurd or disingenuous.

Nevertheless, starting from the pioneering work of Easterlin (1974), economists have increasingly asked this question of advanced economies. It has been shown that, in several economies income per capita rose consistently over one or more decades and yet the mean subjective well-being score remained roughly constant. Very few studies have apparently been made for developing countries, probably owing to a lack of relevant time series data on subjective well-being.

Are these  findings for the advanced economies true also for China? Easterlin and Sawangfa (2010) provide evidence of the trend in reported life satisfaction or happiness in China from three sources: the Gallup survey, the Asiabarometer survey, and the World Values survey (table 1). In each case the average life satisfaction score fell over time.


In our recent CSAE working paper , we present time series evidence confirming this observation. First, we find that current income has a positive and significant effect on happiness in all three Chinese subsamples considered – the rural, the urban, and the migrant. However, in none of these sub-samples is the coefficient on current income substantively large. Clearly, there are other, more important, determinants of individual subjective well-being.

Second, we find the higher the incomes to which people aspire, the lower is their subjective well-being. Aspirations are influenced by peoples’ reference groups and reference times. For rural people, the reference group is generally their fellow-villagers, for urban people it is their fellow-citizens within the city, and for rural-urban migrants, it is also other people living in the city, urban as well as rural hukou holders. It is not the income of ‘any old Zhou’ that produces feelings of relative deprivation but the income of the ‘Zhous you know’ – those who fall into a person’s reference group. China’s national Gini coefficient of household income per capita rose from 0.39 in 1988 to 0.47 in 2002 (Gustafsson et al., 2008: 19). It is likely that this rising income inequality reduced happiness, but the relationship is complicated by the importance of local reference groups and the possibility of demonstration effects as well as relative deprivation effects.

Third, aspirations for income are much influenced by reference time income, and this is governed mainly by the present. It is current income – both absolute and relative – that mainly determines aspirations for income. However, there appears also to be a ‘ratchet effect’: previous income can also influence aspirations, so that experience of a past fall in income reduces happiness, other things being equal. In general terms, the analysis highlights the important role that aspirations play in peoples’ perceptions of their own well-being.

Fourth, expectations of future income are important for current happiness. This suggests that a gloomier view of the economy’s prospects could be serious for well-being, and maybe even for political stability.

Using this framework of empirical findings, we can see that the changes in the economy and in the society that stem from, or go along with, economic growth are likely to have influenced overall happiness in China. They help to explain why the chapter of Easterlin et al. appearing in the same volume as this paper found that life satisfaction in China was no higher in 2010 than it had been in 1990. The effects of income growth itself are limited because of the resultant growth in aspirations, this being a function of both own and relative income. The importance of relative income for subjective well-being in all three sub-samples, together with rising income inequality over time, helps to explain the failure of happiness scores to rise with income levels. The new urban insecurities and uncertainties generated by economic reform and marketization have a negative impact on the subjective well-being of the growing number of urban residents. In particular, rural-urban migrants – rapidly expanding in number – suffer both from their second-class status in the cities and from the widening of their reference groups to include the more affluent urban-hukou population. By extending the reference groups of rural-dwellers beyond the village, migration can also have the effect of reducing rural happiness.

Our analysis of the relationship between economic growth and happiness in China is only a beginning. Progress – in China as in many other countries – awaits a ‘second generation’ of household panels which contain modules on subjective well-being designed with research questions in mind. A start could have been made in the CHIP household survey of 2007, which was the first year of an annual panel. However, their political sensitivity required that questions on happiness be excluded from the surveys of rural and of urban resident households – the implementation of which required the cooperation of the National Bureau of Statistics.

Our analysis raises, and also illuminates, some basic normative and policy issues. To what extent should subjective well-being enter into the social welfare function, and be accepted as one of the criteria for policy making? There is no right answer: ultimately, a value judgement is required. Our discussion was an attempt to set out the case for and against making this, and alternative, value judgements.

There is a case, grounded in economic theory but not incontestably so, for using subjective well-being as one of the criteria. The case has been criticised in several ways: that subjective well-being is misleadingly tainted by aspirations and adaptation, that happiness is not the only objective which guides people’s actions, that reports of subjective well-being are unreliable because they biased by use of different happiness scales. However, each of these arguments is in turn open to debate. Even if the case for including subjective well-being in the social welfare function is accepted, it remains possible that other criteria should be included as well.

The alternative capabilities approach to social evaluation discards the use of subjective well-being on account of the adaptation of the deprived to their deprivation. Instead it includes in the social welfare function the achievement of certain capabilities to function, that is, to be and to do things of intrinsic worth. However, this approach is also open to criticism, requiring as it does an externally imposed valuation of the various capabilities, not based on clear criteria for selection or aggregation.

We made an attempt to present subjective well-being as an encompassing concept by including income, physical functionings and social functionings as inputs in the happiness equation. The estimated coefficients of the equation can be viewed as the weights that people attach to the contributions that these inputs make to their welfare, averaged over society as a whole. This approach is also open to criticism: the subjective values that people on average attach to the variables in the equation may not be an acceptable reflection of their social values, either because aspirations and adaptation are not tethered or because the social value is not well measured by the effect on happiness.

Powerful and plausible regularities were observed in the positive analysis. Thus, in making the necessary value judgement, it is difficult simply to dismiss as irrelevant peoples’ reported perceptions of their own welfare. Our own position is that, provided it is guided by knowledge of the determinants of subjective well-being, there can be a case for including subjective well-being in the social welfare function, but also for including other criteria as well, such as concern for individual freedoms and social fairness. Subjective well-being can be appropriate not only for judging social progress but also for making policy choices.

It is government which effectively makes the value judgements about the implicit social welfare function that guides policy. There are some difficult policy trade-offs between the gains from economic growth in China, and the losses from the socioeconomic changes accompanying growth, and these have not always been sufficiently recognised. For over a quarter of a century China’s reformist policy-makers gave the highest priority to the achievement of rapid economic growth. In the last few years, however, the balance of policy objectives has moved somewhat in the direction of creating a ‘Harmonious Society’, for instance, showing greater concern for reducing income inequality and for improving social security. That move can be seen as a response to the issues that underlie this paper. Whether it is because of their threat to social stability and thus to continued Communist Party rule or for other reasons, the forces that influence subjective well-being appear to have entered the government’s social welfare function.

John Knight* and Ramani Gunatilaka**

 *   Department of Economics, University of Oxford, Manor Road Building, Oxford OX1 3UQ

** School of Graduate Studies, University of Colombo, Sri Lanka

[1] The paper will appear in a chapter of Andrew Clark and Claudia Senik (eds), Happiness and Economics. Lessons from Developing Countries, OUP (in press)


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The Global Cost of Violence

CNN interviewed Anke Hoeffler on the global cost of violence. The news feature was based on a new report by James Fearon and Anke Hoeffler that estimates the annual costs of violence at around $9.5 trillion, which is about 11 per cent of World GDP.  In their study they consider the costs resulting from civil wars, homicides, assaults and violence against women and children (figure 1).

Slide1Figure 1 – The global cost of violence

While civil wars receive a lot of attention, they are relatively rare events. People are more at risk from other forms of violence. Approximate prevalence rates are:

  • 1 in 100,000 people die in civil conflicts
  • 9 in 100,000 people are victims of homicides
  • 16,000 in 100,000 children are subjected to severe physical punishment
  • 12,000 in 100,000 women are assaulted by their intimate partner

The high prevalence rates of violence against women and children make it the most costly type of violence; about 85 per cent of our total cost estimate is due to violence against women and children.

The authors argue that the post-2015 MDGs should include targets on violence reduction. While a world free of violence may be an unrealistic target, the world is now more peaceful than at the end of the Cold War and some countries (such as the US and the UK) have seen a reduction in some forms of violence (homicide rates, intimate partner violence) over the past 20 years.  Ambitious targets and programs for public health problems, such as the eradication of small pox, Rinderpest, Guinea worm, polio and measles have been very successful over the past six decades. As advances in medical science have resulted in a decline in deaths from communicable diseases, social causes of death, such as violence, have become relatively more important.

The report also highlights that almost no development aid is spent on the prevention of violent crime (only about 0.27 per cent of total aid spending). The little aid that is spent on the improvement of judicial systems and police performance is mainly spent in post-conflict countries.

Setting violence reduction targets would acknowledge that the global agenda is evolving and would promote research in finding ways to reduce violence in low and middle income countries. The authors argue for moving beyond a near-exclusive focus on civil war violence – concern with which has increased in the development community and is admirable and important – to recognizing that the costs of interpersonal violence are probably much larger but are almost wholly neglected in current development programming.

The report is part of the Copenhagen Consensus Project

The link to the interview is:

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From rebellion to electoral violence

Promoting democratisation and elections has been at the core of peace-building missions in post-conflict societies since the end of the Cold War. Recent examples are Afghanistan, the Democratic Republic of Congo, Iraq and Libya, just to name a few. Democratisation has been considered as a key factor for supporting the governments’ accountability and legitimacy, which ultimately fosters social trust and make violence relapse less likely. Nonetheless, elections failed to be implemented properly in a vast majority of post-conflict countries in Africa. A recent study by Bishop and Hoeffler (2014) reveals that during the 1975-2011 period, 80% of African polls were spoiled by violence, bribery, intimidation or inequitable government interference (Figure 1).

figure1Figure 1 – Electoral Malpractices in Africa from 1975 to 2011

Understanding the causes of electoral misconducts is all the more important to prevent its adverse economic consequences, the destruction of social capital, a weakening of the State’s capacity and its devastating effects on the living conditions of civilians.

In a new working paper, Olivia D’Aoust, Olivier Sterck and Andrea Colombo discuss the origins of the electoral violence that spoiled the 2010 elections in Burundi. Burundi is a small landlocked country located in the Great Lakes region in sub-Saharan Africa and it is ranked 178th out of 187 countries according to the Human Development Index. Its GDP per capita was USD 267 in 2013 (The World Bank).

The history of Burundi has been characterised by deeply anchored cleavages between its two major ethnic groups, the Hutu and the Tutsi. Ethnic rivalries constituted the ground for tensions and ethnic massacres that culminated in the 1993 civil war between the Tutsi-led army and Hutu rebel groups. After the Arusha peace agreement was signed in 2000, two rebels groups remained active on the ground: the CNDD-FDD and the Palipehutu-FNL. In 2004, the CNDD-FDD laid down its weapons. One year later, its leader, Pierre Nkurunziza, won the elections. Burundi then became the battleground for the two rival Hutu rebel groups. During four years, the new Hutu government fought against the Palipehutu-FNL, which finally demobilised in 2009, putting an official end to the civil war. The first post-civil war elections were organised a few months later in May 2010.

The pre-electoral climate was spoiled by numerous violent episodes, claims of intimidation and suspicions of fraud. The aim of our study is to understand whether the ex-combatants played a role in triggering electoral violence. We also assess whether electoral violence had any socio-economic, ethnic or political grounds.

We show that episodes of electoral violence in 2010 were channelled through enmities between Hutu rebels, eventually bursting during the electoral competition. The local distribution of Hutu demobilised soldiers, based on their affiliation during the civil war, was indeed a prominent determinant of violence: the more a municipality was polarised (through the presence of two opposing groups of ex-combatants), the more likely electoral violence occurred. Figure 2 displays the number of events predicted by the distribution of ex-soldiers as a function of the number of groups of similar size in each municipality. It predicts a five-fold increase in electoral violence between the lowest- and highest-polarised municipalities.


Figure 2. Predicted number of events as a function of projected number of groups of the same size

 We also show that municipalities that had been heavily exposed during the 1993-2009 civil war were more prone to violence in 2010. On the contrary, the Hutu-Tutsi rivalry was not a good predictor of electoral malpractices. As a matter of fact, the demobilised soldiers’ polarisation effect was stronger in municipalities where the Hutu were the majority. Political competition did not matter either when tensions between ex-rebel groups were accounted for. The key for tackling electoral malpractices in Burundi may then reside in the role played by demobilised soldiers within the political arena during the campaigning process.

Policy-wise, our research urges for a democratisation process to be tailor-made on the basis of a country’s specific political and historical contexts. Elections, even if combined with demobilisation programmes, are not sufficient for establishing sustainable peace in post-conflict societies like Burundi. Policies facilitating the transition from rebellion to political competition, within a sounder institutional framework, should be enhanced.

Burundi’s 2015 elections are fast approaching and the incumbent president does not seem to be willing to conform to the constitutional requirement of ceding the term of office (BBC news). Burundi’s internal stability will thus be challenged, once again.




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How useful is education in Africa?

Travelling around any poor country in sub-Saharan Africa (SSA) the visitor is struck by how far schools outnumber factories. The large number of schools is due partly to the success of one of the MDGs which is that primary education should be available to all children. According to World Bank data the primary completion rate for boys in SSA increased from 58 to 73 percent between 1999 and 2012 and for girls from 48 to 66 per cent. But why all these schools and no factories? Isn’t the idea that education should enable the newly educated young to have better jobs and aren’t those better jobs likely to be in factories?

That this schooling is useful is virtually unquestioned in discussions of development policy. True there will be concern at the quality of the education, at the fact that much of this education is not free and that girls do not have equal access to the education. But surely its usefulness is self-evident?

In this blog I want to argue that its value in enabling the newly educated to earn more is far from self-evident. The inference, rather obviously, is not that the young should not be educated. The inference is that we need to understand what does make education useful for increasing earnings. (I am not arguing that this is the only, or indeed the most important, function of primary education, it is just the one I wish to focus on). While, rather out of character, all economists would agree that education and earnings are highly correlated beyond that they revert to normal and agree on very little. The question we need an answer to, and it turns out to be a very hard question to answer, is how does education at different levels affect earning opportunities?

Figure 1 below shows why we care a lot about the earnings gain at different levels of education in SSA. The extent of the investment in primary education has dramatically changed the skill composition of Africa’s population. In 1960 some 90 per cent of Africa’s adult population had no education meaning that they had failed to complete primary level. By 2010 this proportion had roughly halved and similar proportions, 40 per cent, had no education as had primary. The implication is rather stark – the vast majority of the increase in education that has been achieved has been at the primary level. Unless education at this level increases earnings then the very large increases in education that have been achieved will not have increased earnings.

 Figure 1: Percentages of Skilled and Unskilled Labour sub-Saharan Africa


So how does primary education affect earnings? There is no agreement as to the answer to that question. There is a long history in this area of arguing that primary education is the most valuable aspect of education in the sense that the earnings increase at that level is highest. That is the argument advanced by George Psacharopoulos and his collaborators. Where this view has been confronted with actual earnings, usually wages, the result has been rather different. Figure 2 shows the pattern across four sub-Saharan African countries where it appears low levels of education have negligible returns. The figure does not show that education at the primary level did not raise earnings. It may be the case that it did but something else, we do not know what, reduced it so the net effect was zero. While such charts do not tell us about causes they do tell us about outcomes and for the primary educated the outcomes appears a rather unhappy one.

In a recent working paper drawing on the DPhil work of Rulof Burger (WPS/2014-10) a different approach is taken to this question. This uses industrial sectoral data for South Africa to link education, not to earnings, but to labour productivity. The findings here are radically different from the shape showing how earnings and education are linked. In this study low levels of education have by far the highest returns. This result is of interest partly because it is, as far as I know, the first to find such an effect and partly because the data enables a range of tests which suggest the result is fairly robust. Why then the difference between this result and the convex function shown in Figure 2?

Figure 2: Earnings in Manufacturing Firms in Africa


We do not know but I would like to suggest one possibility. This is that the data is from South Africa which differs from the rest of SSA in that most employment is wage employment in firms. It is true that there are not nearly enough such jobs in South Africa but that is a different issue. The employment structure is very different from the rest of SSA. Is it the case that education to be useful in increasing earnings needs to be linked to the kind of jobs and if those jobs are there then education is indeed far more valuable? Such an interpretation is speculative. When earnings are regressed on education the shape of the function for South Africa is very similar to that shown in Figure 2. Why such different patterns emerge as to how education impacts on earnings from how it impacts on productivity is a puzzle.

If the high return to primary education found in South Africa’s sectoral data is due to its industrial structure then the picture with which we began of many schools and very few factories is indeed a problem. Without the factories the dramatic increase in the primary educated work force will indeed see little economic gain from their education. The recent increases in the demand for education beyond the primary level certainly suggests that both students, and their parents, are aware that low levels of education have little value in the job market place. Focusing on meeting that demand rather than focusing on why that demand has arisen may well be to miss the critical problem facing educational policy in Africa.



Figure 1 is based on the data provided by:  Barro, R.J., Lee, J-W. (2010) “A new data set of educational attainment in the world, 1950-2010”, Journal of Development Economics, Volume 104, September 2013, Pages 184–198.

The sources for the data used in Figure 2 can be found at: A statement of Geoge Psacharopoulos’ arguments can be found at: Psacharopoulos, G. and Patrinos, H. A. (2004) Returns to investment in education: a further update”, Education Economics, Vol. 12, No. 2, August.

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Agricultural Technology and Structural Change

Developing countries employ a relatively large share of their workers in agriculture, and the labor productivity of those agricultural workers is only a fraction of that found in the developed world. Together, these two facts account for a significant portion of the gap in aggregate output per worker between the developing and developed world. Low productivity in the agricultural sector keeps most workers employed there despite low productivity because of the “food problem”, as T.W. Schultz termed it. To provide enough food to meet subsistence, most workers have to remain in the agricultural sector. This implies that increasing agricultural productivity would free up workers to shift into non-agricultural sectors like manufacturing and services, increasing output per worker and expanding the variety of goods that people can consume.

While agricultural productivity improvements can drive development, we argue in our paper that agricultural technology determines how effective those improvements are. By technology we mean the elasticity of agricultural output with respect to labor. This makes technology different from productivity. Productivity determines how big the marginal product of a worker is (high in rich countries, low in poor countries), but technology determines how fast that marginal product changes in response to a change in the labor supply.

We do two things in our recent CSAE working paper (co-authored by Markus Eberhardt and Dietrich Vollrath). First, we use recent advances in panel time-series econometrics to estimate agricultural production functions on a country-by-country basis. We are able to let both productivity and technology vary across countries. Once we have technology estimates for each country, we look at how that those estimates vary by climate group. We find that countries that are predominantly in cold and/or temperate climate zones have very low elasticities of agricultural output with respect to labor, about 0.15, meaning that the marginal product of labor doesn’t change much as we move labor into or out of agriculture. In contrast, countries in equatorial zones or highland zones tend to have high elasticities, 0.35–0.55, meaning that the marginal product of labor is very sensitive to the amount of labor in agriculture.

The second thing we do in the paper is calibrate a simple model of structural change and development to see how important those differences in technology are for things like the labor share in agriculture or output per worker. What we find is that the low labor elasticities in temperate zones allow economies to respond very rapidly to improvements in agricultural productivity. Given a productivity shock, temperate economies are able to move a lot of workers out of agriculture, because the marginal product of those that stay remains relatively large. Thus the structural transformation occurs very quickly in these economies, and this shows up as more non-agricultural output and higher output per worker. In response to the same shock to productivity, equatorial and highland economies move fewer workers out of agriculture, because the marginal product of remaining workers falls very quickly, and thus their structural transformation is slower and does not provide as big of a boost to output per worker. They certainly benefit from productivity increases, but not to the same degree as in temperate economies.

One easy way to see the implications of agricultural technology is to look at the following figure. This shows, in our model, how much agricultural total factor productivity (TFP) would have to rise in order to push the agricultural labor share down to 3\%, similar to levels seen in rich countries today. The poorest temperate zone countries, like Malawi (MWI), would need TFP to rise by a factor of 10. But an equatorial country like Tanzania (TZA) or a highland one like Ethiopia (ETH) would need TFP to rise by a factor of 20 or 40, respectively. It is easier for temperate economies to transform their economies from agriculture to industry, because their agricultural technology has a low elasticity of output with respect to labor.

If we look across countries, then one reason that some countries are relatively poor may be their agricultural technology has not allowed them to take advantage of productivity increases as rapidly as temperate zone countries. We use our model to calculate several counter-factual situations, and find that roughly 20\% of the variance in cross-country output per worker could be attributable to differences in agricultural technology. Another way of saying this is that the ratio of the 90th percentile to the 10th percentile country in terms of output per worker is roughly 22/1 now. This ratio would be only about 15/1 if all countries had an agricultural technology with a labor elasticity of only 0.15.

figureFigure 1 – Relative Agricultural TFP Increase

While our research indicates that equatorial and highland zone countries are at a disadvantage in making a structural transformation, we should be clear that our results do not indicate some kind of “geographic determinism”. That is, there is nothing in our research that says those countries are doomed to be poor. You can see in the figure 1 that there are relatively rich highland and equatorial countries. But at any given level of output per worker, equatorial and highland countries will require larger productivity increases to reach higher levels of development than their temperate zone peers.

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How to increase your GDP without anyone noticing

African GDP statistics have been in the news recently. Both Ghana and Nigeria in West Africa have seen revisions to their GDP which, in the case of Ghana, has made it a middle income country with per capita GDP, in purchasing power parity US$ dollars, of over 3,000 US$ and in the case of Nigeria has made it the largest economy in Africa.

These statistical innovations clearly do not change the incomes of individuals in those economies but they do suggest that rather dramatic gains have been made recently within Africa. While GDP data is clearly problematic in very poor countries the picture the GDP figures suggest of major improvements in the level of activity in those countries is borne out by a range of data sources. If these figures are correct they suggest a puzzle. Why if progress is being made is there such concern for the lack of employment opportunities, particularly for the young, and why are Nigerians not celebrating more?

My recent working paper for the CSAE looks at these issues, not from the point of view of macro data, but from the perspective of employment creation in Nigeria and the incomes those jobs create. The paper documents three rather remarkable “facts” about job creation in Nigeria over the period from 1999 to 2006. The first is that the number of jobs has increased in line with population. The second is that the number of wage jobs has actually declined in absolute terms. The third is that most job creation has been within the rural sector. In summary, small scale self-employment activities have become increasingly important over a time a relatively rapid GDP growth. As with most data on Africa these “facts” are open to dispute but I argue in the working paper that the evidence from household surveys strongly points towards their broad accuracy.

If correct, this pattern of job creation can help explain the disconnect between the GDP numbers and the working experience of most Nigerians particularly the young. They are told, probably correctly, that their nation’s income is increasing rapidly but they see no access to those increased incomes for themselves. The lack of connect is due to the lack of higher income jobs. The fact that jobs have increased in line with population does not mean that there are plenty of jobs Nigerians want. Some 25 per cent of those aged from 15 to 64, who are not in full time education, are defined as out of the labour force. That means that applying standard definitions they are not seeking work and are therefore presumed not to want employment. It is extremely likely these would take jobs if there were more better paid ones. The problem is not jobs it is the incomes from those jobs and the data we have for 2004 suggest median private sector urban earnings of about US$80 per month. Is it little wonder, seeing the plutocratic lifestyles of those with access to the oil rents, that faced with such job opportunities Nigerians are angry and bitter?

Figure 1


It is important to be clear the problem is incomes from jobs not the provision of more wage jobs. While private wage jobs do, on average, produce more income than those in self-employment a critical issue is the extent of the distribution of incomes within occupational categories and the overlaps across these sectors. For the urban sector the extent of the overlap between private wage and self-employment activities is shown in figure 1. It is the very low incomes we observe in Nigeria at the bottom of the distribution, for both wage and the self-employed, that accentuate the disconnect between increasing prosperity for Nigeria as a country and the lot of most of its population. For the young this disconnect can appear grotesque. In 2006, for those aged 15 to 25, less than 5 per cent had access to any wage job (that excludes those in full time education) and only 15 per cent had an urban self-employment income. Nearly 50 per cent were classified as either out of the labour force or unemployed. Failing so dramatically to supply income sources for so many, and the young in particular, does seem an excellent way of increasing your GDP and ensuring most do not notice.

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