Why more educated individuals are not always healthier

Caleb Hia (Economics ’18) wrote the following article on health economics from his research for his undergraduate dissertation at the University of Edinburgh.

BGSE Voice

Caleb Hia ’18 wrote the following article on health economics from his research for his undergraduate dissertation at the University of Edinburgh.


From 2006 to 2007, almost half of the UK’s National Health Service’s (NHS) costs were attributed to behavioural risk factors: diet-related sickness, sedentary lifestyles, smoking, alcohol and obesity cost more than £15 billion (Scarborough et al., 2011). This mammoth sum, deemed an economic burden on public resources, attracted the government’s attention. In the recent Budget, the Chancellor introduced a tax on the sugar content of soft drinks from 2018 to tackle childhood obesity aimed at compelling individuals to consider external costs associated with its consumption which they do not bear such as the publicly-funded health costs of treating diet-related diseases. The effectiveness of this or any further government intervention in an attempt to correct this “externality” will influence the way the NHS allocates its limited resources in healthcare provision.

Beyond this political issue runs an underlying discussion of the social determinants of health which have long been studied (Wilkinson and Marmot, 2003; Adams et al., 2003). In particular, the effects of education on health has been of interest since the inception of Grossman’s (1972) health model. Grossman’s model suggests health can be maintained by health investments, depending on goods and activity consumption, which affect health although health depreciates as individuals age. As better health gives an individual more time to work and enjoy consumption, more educated individuals are expected to demand more health and invest more in their health. This implies more educated individuals are also more efficient health producers.

A possible causal link between education and health exists possibly because higher productivity from more education directly translates to a higher level of health production through allocative efficiency (Kenkel, 1991; Rosenzweig, 1995) and productive efficiency (Grossman, 1972). For example, low literacy is associated with a poor understanding of hospitals’ discharge instructions (Spandorfer et al., 1995) while higher educated individuals are more likely to follow medical treatments (Goldman and Smith, 2002). Relatedly, higher educated people spend more time on health-related activities because they are better at allocating inputs (Grossman, 1972). Additionally, higher educated individuals use their higher earnings to purchase healthier lifestyles (Glied and Lleras-Muney, 2003) which entail more expensive medical treatments, healthier food consumption and living in healthier areas.

I use a natural experiment in England, the increase in compulsory schooling laws from fifteen to sixteen years old following the Raising of School Leaving Age Order in 1972, and an instrumental variable (IV) regression model to examine the relationship between education and health in greater detail. My sample incorporates additional years of data from Health Survey England between 1991 and 1993 which were not analysed before. I measure various health-related measures and behaviours including Body Mass Index (BMI) which has not been considered before. I run Ordinary Least Squares (OLS) and two-stage least squares (2SLS) regressions in a sample containing all individuals and a discontinuity sample comprising individuals born only in January and February using February-born individuals as my instrument. I show education has no causal effect on various health-related measures and behaviours.

A possible explanation for this lies in time inconsistent preferences supported by behavioural economics. Quasi-hyperbolic discounting (Phelps and Pollak, 1968; Laibson, 1997) induces dynamically inconsistent preferences contrary to geometric discounting. The following payoff matrices models a hypothetical situation where an individual fails to quit smoking due to quasi-hyperbolic discounting:

Under geometric discounting where ∝ ≈ 1 and β ≈ 0.8,

he makes time consistent choices regardless of when benefits to those choices are delayed. Since he gets more utility from quitting in both periods, he quits immediately.

However, under Quasi-hyperbolic discounting where ∝ ≈ 1 and β ≈ 0.8,

he changes his choices based on his distance in the future. Unlike geometric discounting, he gets more utility from quitting only in future and not at present and hence do not quit.

The empirical evidence from Gruber and Köszegi’s (2001) addictive behaviour model which incorporates time-inconsistent preferences to the standard “rational addiction” model (Becker et al., 1994) suggests smokers exhibit forward-looking behaviour with time inconsistent preferences concerning smoking. Thus, individuals start smoking often as adolescents when they are most present biased (Hammond, 2005) and do not anticipate the difficulty of quitting.

Therefore, lifestyle habits may not be correlated with education. In the case of smoking, individuals who quit smoking successfully may have used commitment devices (Ashraf et al., 2006; Kaur et al., 2010; Beshears et al., 2011) like quitting with friends to constrain their own future choices by deciding ahead of time to make future deviations costly. Increasing the education budget may be a sound way to promote public health but understanding behaviours and exploring policies to incentivise individuals to adopt healthy habits may be more effective in the long-run.

Download the full paper:

The causal relationship between education and health-related measures and behaviours: Evidence from England

Aspirations and Academic Achievement: The Spillover Effects of Beca 18 on Educational Outcomes of Younger Students

Elena Costarelli, Rosamaría Dasso Arana, and Bárbara Sparrow Alcázar analyze the effect of being near a Beca 18 beneficiary -a new scholarship program for high school students- on the academic achievement of second grade children.

Beca 18 Peru

Editor’s note: This post is part of a series showcasing Barcelona GSE master projects by students in the Class of 2016. The project is a required component of every master program. Photo: PRONABEC


Authors:
Elena CostarelliRosamaría Dasso Arana, Bárbara Sparrow Alcázar

Master’s Program:
Economics

Abstract:

Using administrative data from the Ministry of Education in Peru, we analyze the effect of being near a Beca 18 beneficiary -a new scholarship program for high school students- on the academic achievement of second grade children. Previous literature suggests that information about the potential returns to education plays an important role on students’ achievement. Our hypothesis is that having a fellow nearby might change the perception of younger children and of their parents about returns to education, thus leading them to invest more on it. We use a difference in difference approach to test this hypothesis in a school panel data setting. As we are interested in the effect of information transmission, we use GPS location data to identify which schools are near a Beca 18 beneficiary. We test for several distance specifications with consistent results. Our findings suggest a positive spillover effect of the program on younger children in both reading and math performance.

Introduction:

Access to tertiary education is a well-known motivation for students to perform better at school. Good students are usually the ones that are able to attend better universities which in turn allows them to improve their living conditions. This is true in most developed countries, where access to good quality higher education is a possibility for most students. However, in the case of many developing countries, market failures and government limitations do not allow students to consider this possibility.

When facing the decision of educating their children, many families may consider it to be an unprofitable investment. Little information about the benefits of education in terms of higher future income and the lack of success stories among people close to them may all contribute to this perception. In this regard, the impact of a program that makes access to tertiary education may possibly affect the way people value education in a significant way. If parents and children are aware that been a good student may have a tangible future reward, their investment decisions may change.

Access to tertiary education is greatly limited to children from poor families in Peru. To address this issue, the Peruvian government recently created the Beca 18 program. Beca 18 is a merit/need based scholarship program that targets students applying to higher education institutions such as universities and technical institutes. The program gives selected students the opportunity of attending the best tertiary schools in the country. Before the program existed, even access to public universities was very limited. Beca 18 can be considered as one of the first real opportunities for children of low resources in Peru to access high quality tertiary education.

Current literature suggests that there is a positive relationship between policies that increase the perceived returns of education and educational outcomes among children. There is also evidence that supports that future access to scholarships and merit based programs may encourage better school performance. In this paper, we will analyze the impact of Beca 18 on the school performance of second grade children. To do this, we use test score data from the Ministry of Education and administrative records from the Beca 18 program. Using a difference in difference approach, we were able to identify a positive impact of being near a program beneficiary on both math and reading proficiency outcomes. 

Conclusions:

Our results suggest that the Beca 18 program has relevant spillover effects on the educational outcomes of younger children. Guided by our conceptual framework, we would expect this result to be a consequence of the fact that children and parents exposed to Beca 18 beneficiaries update their information about perceived returns to education, leading them to invest more time and resources in obtaining better educational results.

We also find that effects on math test scores are stronger and more robust to several specifications than effects on reading test scores. This result is consistent with findings of other studies suggesting that math scores are more quickly affected by changes in study behavior. We also find that the effect of being near a beneficiary decreases as the distance to the school of the beneficiary increases. This result is consistent with our hypothesis that the improvements in educational outcomes are a result of information transmission.

Another result worth discussing is that we found that the effect of the program is larger when the number of beneficiaries nearby increases. This suggests that investment decisions are affected by how likely it is to get the scholarship. It may also suggest that the investment decision may vary if there are more people acting as role models.

Overall, our results are relevant from a policy perspective. We present evidence that the program has relevant spillover effects that should be considered when evaluating its benefits. As public programs in Peru are under continuous scrutiny, further evidence that supports the program’s effectiveness is of greatly useful to ensure its continuity. Also, as our results suggest that the number of beneficiaries matter for investment decisions, the expansion of the program could lead to even greater spillover effects.

It is still important to note that the effects found here are not the main intended effects of Beca 18: the scholarship program was designed as a supply side policy intervention. Our findings support the idea that this program can have important demand side effects worth considering. We would also expect for these effects to increase over time: the success stories of current beneficiaries in the labor market could lead to an even greater increase of the expected returns of education.

 

Defining data for decision-making

authorBy Benjamin Anderson ’15 (Master’s in Economics of Public Policy).

Ben is a Data Strategist for Made in Durham, a non-profit organization in North Carolina (United States) that works to improve education and career outcomes for local youths.

This article originally appeared on Made in Durham’s website.


In the past few weeks, there have been a barrage of media reports about educational achievement and, more generally, life outcomes for the youth of Durham.

The positive news is that these issues are receiving attention, but the downside is that the reports may be more harmful than helpful. At its best, data optimizes decision-making, but at its worst data can be deceptive and divisive.

Specialized knowledge is required to leverage data for decision-making, whereas selectively reporting figures requires some effort but no expertise. In the latter scenario, the ambiguity of statistical assumptions predisposes the audience to personal, as well as, framing bias. Those who go through the effort to produce data often have an agenda, and therefore, have incentives to make claims which imply causes and solutions. Data is dangerous when misused. It can create tension, undermine trust and unity, and result in costly adverse decision-making.

One key characteristic of amateur statistics, aside from lacking an experimental design, is that they do not account for the fact that outcomes are a function of many different variables. For example, schools clearly play a crucial role in influencing academic attainment, but a report drawing relative comparisons between attainment outcomes within or across cities usually implicates unidentified failures of one school district versus another while all but ignoring the effects of transportation, affordable housing, food, healthcare, and social support accessibility, as well as people’s different lived experiences, including traumatic exposure of various kinds.

Reactivity to outcomes is strongly linked to bias and emotion. Making decisions about problems and solutions based exclusively on outcomes is the logical equivalent to going with your gut.

Descriptive statistics alone have a tendency to reinforce what we already think we know rather than helping us to gain an objective understanding of the issues because we often overestimate our understanding of the context. Shards of truth may be buried in our presumptions or between the different storylines, but other times the truth isn’t within sight.

If one wanted to know what public schools are doing right and what positive changes could be made, the reported outcomes would not meaningfully increase understanding. This would be like a college basketball coach using the Ratings Percentage Index (RPI) to make game plans. The RPI is simply a function of outcome variables that are influenced by other, more influential variables over a team’s success, such as shot selection, rebounding, ball control and many others.

Similarly, objective inference about the determinants of academic achievement are impossible when we simply have some measure of the output, like grade level proficiency, graduation rates or achievement gaps. Summarized outcomes do not even begin to untangle the multifaceted causal factors of student achievement, or even point to which factors are within the schools’ control and which are shaped by other institutions that govern infrastructure, real estate development, credit markets and criminal justice.

Good intentions often lead to unintended consequences. Calculating outcomes or deriving slightly new definitions of them does not enhance the cultural or intellectual competence of our community, its citizens or the institutions within it.

This is troubling because the extent of harm done with every report that subjectively frames and selectively reports data will never be known. A symptomatic obsession can enable data to have a negative social impact, leading to the proliferation of economic and racial segregation, adverse selection of people and funds from public schools, victim blaming and the marginalization of objectivity. The focus needs to shift from symptoms to solutions.

Data should be collected and analyzed in a way that enables us to separately identify effects on outcomes, including those determinants within the school’s control and those outside, so that all can be addressed in order of impact and feasibility. Robust evaluations should yield insight, pointing out specific causal factors that affect outcomes that the schools, nonprofits policy and citizens can address.

Applying a scientific lens to social issues transforms data from punitive to instructive. Careful investigation using valid quantitative methods can help us gain an understanding of the inferences that the data will and will not permit. Through empirical analysis, we have the opportunity to disentangle the effects that different factors have on certain outcomes. This is powerful because it enables us to create informed strategies.

Subsequently, when we know how our potential actions will affect an outcome, a cost-benefit analysis can help decide which evidence should be brought to action. Operating in the public and nonprofit sectors, the cost-benefit analysis goes beyond fiscal considerations to examine social returns. Combining these empirical tools puts us in a position to optimize social welfare. Data or analysis vacant of these characteristics will result in suboptimal decision-making.

An empirical basis for decision-making that respects the complexity of determinants on outcomes and the tradeoffs between various actions or lack of action should be utilized at all levels – from the systemic to the programmatic. A symptomatic focus and a preoccupation with a single area will not result in systemic improvement. As institutions, organizations and programs, our goal should be to improve, which can only be achieved through learning.

Durham has great potential to grow while enhancing the well-being of all, including the most marginalized. Continuous improvement requires the commitment of people in the public, private, and social sectors to work together.

Part of analytical integrity is the acknowledgement that sometimes our data tells us nothing at all. If we truly care about addressing systemic issues, lack of information is a strong argument for why we should build more robust datasets that incorporate variables across institutions and the socio-economic environment. This requires a willingness to coordinate and to learn. Importantly, these actions imply the willingness to change.

The Made in Durham partnership exists to address issues of the highest importance. It is the job of data is to increase the role of evidence in the partnership’s decision-making, and because of the gravity of these decisions, I also feel an ethical accountability to this work.

If we aren’t asking the right questions, data can lead to costly decisions that undermine improvement. As members of the community, we should all be able to ask the right questions to hold decision-makers accountable to analytical standards that drive improvement.

Regardless of what the outcomes show now, or anytime in the future, what we should be asking is: what are the causes of these outcomes, what are their magnitudes, and thus, what can we do to improve.

The Effect of a Supply-Side Educational Program on Schooling in Indonesia: A Failed Policy for Girls?

By Aurelia Schülen  and Nicolas Volkhausen


Motivation and Background

While the outcomes of most public investments schemes are not completely foreseeable, the benefits of investing in education to both children and broader society could not be more clear: education is strongly correlated with improvements in health and nutrition, it is one of the best protections against poverty, and it fosters civic participation and democratization.

Although the importance of education to individuals and society is apparent, access to education differs substantially between and within countries. In particular in developing countries the access to education is extremely restricted. Looking at within country disparities, these barriers to education often disproportionately affect girls. In the 1970s the Indonesia’s central government launched the Sekolah Dasar INPRES program (henceforth SD INPRES), one of the largest primary school construction programs in history in order to counteract this trend of stagnating primary school enrollment rates. This large-scale construction program led many economists to study the numerous impacts on the Indonesian population by taking advantage of its form as a natural experiment.

Previous literature on the impact of SD INPRES suggests that until recently only little attention has been paid to the effects of the primary school construction program on girls. This is not very surprising since Indonesia constantly performed poorly among international gender equality measurements such as the Gender Inequality Index by the United Nations or the Global Gender Gap Report by the World Economic Forum. Work by Hertz and Jayasundera (2007), Pettersson (2012), and Ashraf et al. (2014), take differing approaches in studying the effects of the SD INPRES program in women. The novelty in our approach lies in the fact that with our data set, containing more cohorts than previous analyses, we are able to check for persistency of the resulting effects of the school construction program on later cohorts by extending the time range used in Duflo’s pioneering analysis. We also investigate whether the effect of the program on women might not be reflected on the intensive margin, i.e. the actual duration of education, but rather on the extensive margin, in other words the likelihood of completing primary school education.

Identification Strategy

A key element of our identification strategy to identify causality of the school construction program on educational outcomes relies on variations of an individual’s exposure to the program based on date and region of birth. For the purpose of our analysis, we only treat the combination of these two variations as exogenous. By its nature, the SD INPRES program was designed to allocate more schools to regions where primary enrollment was particularly low, inducing heterogeneity in the number of average schools built per district. A second source of variation is reflected in the age of the students. A child of 12 years of age or older in 1974 when the SD INPRES schools started to operate, could not benefit from the program. On the other hand, a child aged 6 or younger in 1974 was young enough to fully benefit from the newly constructed schools. Similarly, children between 6 and 12 years of age in 1974 only enjoyed partial exposure to the program. If the program had an effect on an individual’s years of education, we would expect the program to have the largest effects for fully exposed cohorts, a somewhat mediocre effect on the partially exposed individuals, and no effect on children that were too old in 1974 to benefit from the program. The large, exogenous shock of the SD INPRES program enables us to differentiate between treatment and comparison groups, in the manner of a quasi-experiment using a difference-in-differences approach.

Findings

In line with previous literature, we find that the SD INPRES program had significant effects on schooling outcomes of Indonesia’s children. However, children did not benefit from the primary school construction program equally. In fact, we find substantial heterogeneity of the program’s effect between genders, mostly favoring boys over girls. On average, one more school per 1,000 children in the district of birth increased schooling duration by 0.12 to 0.21 years for boys. However, this effect is less clear-cut for women: depending on the sample specification and type of analysis, we were able to obtain significant results for women albeit substantially smaller in magnitude. In particular when breaking down the analysis on each birth year cohort, our estimates suggest that only the youngest cohorts hitherto benefited from the program, with effects ranging from 0.1 to 0.17 additional years of schooling for an additional school built in the district of birth. Such suggestive late onset of the program’s effectiveness on women motivated us to perform a persistency analysis on later female cohorts. Including eight additional birth year cohorts, we find increasing and significant effects of on average 0.2 additional years of schooling. These findings suggest that a potential effect on women’s schooling might have set in later. Our mixed evidence thus far gives rise to doubts whether the SD INPRES program worked on the extensive margin of schooling attainment. Due to possible selection disadvantages at the transition between primary and secondary school, the effect of the program for girls might not be reflected in the in years schooling but merely in their likelihood of primary school completion. We find significant but negligible effects on women’s likelihood to graduate from primary school.

Conclusion

Ideally, a policy trying to increase education should be targeted at disadvantaged groups of society in order to decrease inequality and break the vicious cycle of poverty. Our findings suggest that women in Indonesia are particularly disadvantaged when analyzing educational outcomes. Further research should hence try to identify other possible heterogeneities when stratifying the sample interest. During our analysis, we made first attempts by looking at different specifications such as the difference in effects between individuals living in rural versus urban areas, or looking at potential heterogeneity varying by ethnicity. Such deviations of our analysis might unmask further heterogeneity, which will be essential to identify when assessing and improving Indonesia’s education policy. It will therefore be necessary to devote further research and policy attention towards the long-term impacts of the program by analyzing the educational and labor market outcomes of later cohorts, captured in the SUPAS 2005 and 2015 polls. On the basis of these results it will be necessary to identify and study potential policy remedies to overcome the tremendous challenges Indonesia’s education system faces.

Does Extended Time Improve Students’ Performance?

Editor’s note: This post is part of a series showcasing Barcelona GSE master projects by students in the Class of 2014. The project is a required component of every master program.


Does Extended Time Improve Students’ Performance? Evidence from Catalonia

Authors:

Ana María Costa Ramón, Laia Navarro-Sola, Patricia de Cea Sarabia

Master Program:

Economics

Project Summary:

Education is one of the main priorities of developed societies, and countries are investing huge amounts of resources in this area. However, little is known about the effectiveness of the inputs used in the education production function, leaving the final decision of investment to ideological or political reasons. In this context, there is an increasing support of extending class time among politicians and policy-makers as a way of improving education. Our paper is an investigation of the effect of an increase in the number of hours per day of class on the performance of the students.

As identification strategy, we exploit the exogenous variation generated by a policy change in Catalonia (a region of Spain), known as the “sixth hour policy”. This reform introduced one extra hour per day, representing an increase of 20% of the total number of hours per year. It involved an important investment for Catalonia and thus, knowing the effects of the policy is needed in order to assess whether it was effective or if there exists other alternatives. The specific characteristics of the policy implementation provide three different sources of variation: variation between cohorts, generated by the sudden implementation, variation between types of schools, since the policy was only addressed to public schools (leaving private schools timetable unchanged) and in last term, variation across regions, as the reform only affected public schools in Catalonia. These features allow us to take the policy implementation as a natural experiment and thus, to investigate more deeply the effects of extending school time.

Using the PISA database and the econometric specification of differences-in-differences, we find that there is no conclusive evidence of the causal relationship between extending school time and performance improvement. This difficulty comes from the implementation of the policy itself which was done simultaneously with other major educational changes, and thus it is hard to identify the channel through which this effect could be operating.

However, we face this lack of evidence on this causality introducing an innovative methodology in the study of extending time at school. To solve specific concerns about the suitability of the control group we construct a “synthetic control” group (an artificial control group), which is a weighted combination of other Spanish regions chosen to resemble education characteristics of Catalonia before the introduction of the “sixth hour policy” as much as possible. However, the particularities of the region of the study make it very hard to predict its behavior.

All in all, we believe that the use of the synthetic control approach can help to shed light on these issues in different case studies or with more detailed data. The analysis of time as an input in the education production function still requires a lot of research but as we have seen with our case study, natural experiments by themselves could be an imperfect tool. Maybe it is time to use more innovative approaches to this old topic.

Read the full paper or view slides below:

Why Do Labels Work? – Barcelona GSE Master Projects 2014

Editor’s note: This post is part of a series showcasing Barcelona GSE master projects by students in the Class of 2014. The project is a required component of every master program.


Why Do Labels Work? A Theoretical Analysis and Proposed Test Design of Mechanisms Underlying Labeled Cash Transfers

Authors:

Angela Bouzanis, Victoria Gonsior, Rozália Kepes, and Eva Werli

Master Program:

Economics

Paper Abstract:

Labeled Cash Transfers (LCTs) are Unconditional Cash Transfers (UCTs) with a specific label attached stating the purpose of the cash transfer in order to guide recipients in allocating funds. Recent economic research has provided evidence for the efficiency of LCTs, but the literature is still missing theoretical foundations. In this paper, we propose four mechanisms based on behavioral economics that have the potential to explain why LCTs work. We construct a theoretical framework for designing labels based on (1) mental accounting, (2) lying aversion, (3) social norms, and (4) informational updates. Additionally, we put forward a randomized controlled trial (RCT) with four treatments according to these four theories in order to test which of these mechanisms have a significant effect on educational outcomes. While at this stage we cannot analyze results, we present our identification strategy and address some general issues and specific concerns regarding our experiment.

Read the full paper or view slides below: