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Labor Market Returns to Higher Education  

Ghazala Azmat and Jack Britton

The persistent high wage premium associated with college education, despite increasing participation rates, continues to generate a great deal of academic and policy interest. While it is widely agreed that the financial benefits associated with college completion outweigh the costs, modeling and empirically estimating the returns are complicated. A simple theoretical framework on educational investment illustrates the decision-making processes and key factors, such as expected returns, that guide the choice of an individual to engage in higher education and to achieve an optimal level of educational investment. Broadening the investment model, however, is instrumental to account for potential heterogeneous returns to higher education—the variation in returns by institution, field of study, and students’ background characteristics, among others—and to recognize the wider societal benefits of higher education, beyond private returns. The challenges involved in estimating the returns to higher education and the heterogeneity in returns are central in the discussion. Interpreting a naive correlation between education and wages is complicated by the nonrandom selection of individuals into higher education, such that individuals who are most likely to benefit from higher education are also those most likely to attend. Advancements in data collection, the ability to track individuals from compulsory education to the labor market, and improvements in econometric methodologies have enabled researchers to causally estimate the impact of higher education on earnings and allow for an improved insight into the disparities in returns to higher education. Recognizing the links between students’ characteristics (or backgrounds) and associated constraints helps to understand differences in higher education choices. Similarly, identifying differences in labor market returns associated with attending certain colleges or pursuing particular academic disciplines is as important in shedding light on the complex nature of human capital disparities and the signaling effect of higher education. As the costs of higher education provision constitute an increasingly large share of government spending all over the world, the high returns to college raise questions associated with who should pay for attending college and the role of the state. Internalizing the social returns to education and their broader implications on the growth and the persistence of inequality complicates this discussion. Higher education funding is one potential policy instrument to influence college attendance and returns. It is not, however, the only one. Better information on returns to education or access to policies that target members of certain social groups might be other potential tools to overcome constraints.


Unintended Fertility: Trends, Causes, Consequences  

Christine Piette Durrance and Melanie Guldi

Unintended fertility occurs when an individual, who did not intend to, becomes pregnant or gives birth. Most measures of unintended fertility account for whether the pregnancy (birth) was wanted and whether it occurred at a desired time. Economic models of fertility provide a framework for understanding an individual’s desire to have children (or not), the number of children to have alongside the quality of each child, and the timing of childbirth. To study fertility intendedness, researchers often classify pregnancies or births as unintended using self-reported retrospective (or prospective) survey responses. However, since survey information on the intendedness of pregnancies and births is not always available, the research on unintended fertility using survey data is necessarily limited to the population surveyed. Consequently, to broaden the population studied, researchers also often rely on reported births, abortions, and miscarriages (fetal deaths) to estimate intendedness. However, other factors (such as laws restricting access or financial hurdles to overcome) may restrict access to the methods used to control reproduction, and these restrictions in turn may influence realized (observed) pregnancies, births, and abortions. Furthermore, abortion and miscarriages are not consistently reported and, when reported, they exhibit more measurement error than births. Despite these research challenges, the available data have allowed researchers to glean information on trends in unintendedness and to study the relationship between fertility-related policies and unintendedness. Over the last 2 decades, unintended fertility has declined in many countries and fewer births are happening “too soon.” There are multiple factors underlying these changes, but changes in access to and quality of reproductive technologies, changes in macroeconomic conditions, and socioeconomic characteristics of fertility-aged individuals appear to be crucial drivers of these changes.


COVID-19 and Mental Health: Natural Experiments of the Costs of Lockdowns  

Climent Quintana-Domeque and Jingya Zeng

The global impact of the COVID-19 pandemic has been profound, leaving a significant imprint on physical health, the economy, and mental well-being. Researchers have undertaken empirical investigations across different countries, with a primary focus on understanding the association between lockdown measures—an essential public health intervention—and mental health. These studies aim to discern the causal effect of lockdowns on mental well-being. Three notable studies have adopted natural experiments to explore the causal effect of lockdowns on mental health in diverse countries. Despite variations in their research methodologies, these studies collectively support the conclusion that lockdowns have had detrimental consequences on mental health. Furthermore, they reveal that the intensity of these negative effects varies among distinct population groups. Certain segments of the population, such as women, have borne a more profound burden of the mental health costs associated with lockdown measures. In light of these findings, it becomes imperative to consider the implications for mental health when implementing public health interventions, especially during crises like the COVID-19 pandemic. While rigorous measures like lockdowns are essential for safeguarding public health, striking a balance with robust mental health support policies becomes crucial to mitigating the adverse impacts on mental well-being.


Happiness and Productivity in the Workplace  

Mahnaz Nazneen and Daniel Sgroi

Happiness has become an important concept in economics as a target for government policy at the national level. This is mirrored in an increasing understanding of the microeconomic effects of increased happiness. While correlational studies have for many years documented a relationship between individual-level happiness and productivity, more recent work provides causal evidence that a positive shock to happiness can boost productivity significantly. These studies include three strands of research. The first provides a number of longitudinal surveys that have generated evidence linking happiness to productivity but run the risk of confounding happiness with other related variables that may be driving the relationship. The second includes laboratory experiments that simulate a workplace under tightly controlled conditions, and this strand has established a clear relationship between positive happiness shocks and rises in productivity. The third involves examining experimental field data, which sacrifices the control of laboratory experiments but offers greater realism. However, there is still work to be done generalizing these findings to more complex work environments, especially those that involve cooperative and team-based tasks where increases in happiness may have other consequences.


What Drives HIV in Africa? Addressing Economic Gender Inequalities to Close the HIV Gender Gap  

Aurélia Lépine, Henry Cust, and Carole Treibich

Ending HIV as a public health threat by 2030 presents challenges significantly different to those of the past 40 years. Initially perceived as a disease affecting gay men, today, HIV disproportionately affects adolescents and young women in Africa. Current strategies to prevent HIV mostly rely on using biomedical interventions to reduce the risk of infection during risky sex and to address that biologically; women are more vulnerable to HIV infection than men. Ongoing policies and strategies to end the AIDS epidemic in Africa are likely to fail if implemented alone, given they fail to address why vulnerable young women engage in risky sexual behaviors. Evidence strongly suggests economic vulnerability, rather than income level, is a primary driver of women's decision to engage in commercial and transactional sex. By viewing HIV through the lens of structural gender inequality, poverty, and use of risky sexual behaviors to cope with economic shocks, a new explanation for the HIV gender gap emerges. New and promising approaches to reduce HIV acquisition and transmission by protecting women from economic shocks and increasing their ability to participate in the economy have proven effective. Such interventions are vital to break the pattern of unequal HIV transmission against women and if HIV is to be beaten.


The Implications of Pupil Rank for Achievement  

Richard Murphy and Felix Weinhardt

The significance of social interaction has become an increasingly important part of economic thought and models through the work on peer effects, social norms, and networks. Within this literature, a novel focus of ranking within groups has emerged. The rank of an individual is usually defined as the ordinal position within a specific group. This could be the work environment or a classroom, and much of this literature focuses on rank effects in education settings. The literature studies rank effects for various age groups. There is evidence that a rank position even during early life phases, such as in elementary education, has lasting effects on education outcomes such as test scores or subject specializations, choices during college, and wages. A first-order challenge in the study of rank effects is to separate them from other highly correlated effects. For example, individuals with a high rank academic rank in a group will likely have high academic ability in absolute terms. Papers in this field directly account for measured ability, and so rely on the variation in rank that exists across groups for any given ability measure, that is, a score of 80 in one group would rank the student top, while near the bottom in another. The comparability of achievement measures across settings is key; one commonly employed solution is to account for level differences across settings. While the literature has now established the importance of rank, there are several—potentially non-competing—ideas for the precise behavioral mechanisms of why rank matters so much. Future work will most likely focus on integrating rank effects into the literature on social interactions to discuss implications for optimal group formation.


Peer Effects in Education  

Andrés Barrios-Fernandez

The identification of peer effects is challenging. There are many factors not related to social influences that could explain correlations among peers. Peers have been shown to affect many important outcomes, including academic performance and educational trajectories. Confirming the existence of peer effects is important from a policy perspective. Both the cost-benefit analysis and the design of policies are likely to be affected by the existence of social spillovers. However, making general policy recommendations from the current evidence is not easy. The size of the peer effects documented in the literature varies substantially across settings and depends on how peers are defined and characterized. Understanding what is behind this heterogeneity is thus key to extract more general policy lessons. Access to better data and the ability to map social networks will likely facilitate investigating which peers and which characteristics matter the most in different contexts. Conducting more research on the mechanisms behind peer effects is also important. Understanding these drivers is key to take advantage of social spillovers in the design of new educational programs, to identify competing policies, and to gain a deeper understanding of the nature and relevance of different forms of social interactions for the youth.


The Economic Benefits of Education for the Reduction of Crime  

Joel Carr, Olivier Marie, and Sunčica Vujić

Historically, social observers have repeatedly noted a correlation between education and crime, observing that individuals with lower levels of education are more likely to commit crime. However, the relationship between education and crime is complex, and it is important to clearly establish causality to determine if investing in education can effectively reduce crime. Merely observing persistent educational-attainment inequalities between offenders and non-offenders is not sufficient to make any causal claims about the underlying relationship between education and crime. Many other factors can influence an individual’s decision to stay in school or commit a crime, and these factors need to be accounted for when estimating the relationship between education and crime. Economists theoretically predicted in the late 1960s that education, via its positive effect on future earnings, would reduce the probability of criminal participation. Empirical studies have since used various econometric methods to establish that, on average, education has a strong causal crime-reducing effect. One strand of this literature has established in various contexts that individuals from cohorts forced by law to stay longer in school were much less likely to end up in court or prison. There is, however, still much to be discovered about the effect of education on crime, such as the underlying mechanisms related to income or non-cognitive effects, and heterogeneities by context, education level and quality, and individual characteristics. Overall, economists widely agree that investing in education is an efficient public-spending strategy to effectively reduce crime.


Explaining the Mathematics Gender Gap: The Role of Stereotypes  

Pilar Cuevas Ruiz, Ismael Sanz, and Almudena Sevilla

Descriptive stereotypes such as “girls are not good at mathematics” or prescriptive stereotypes, that is, fixed views about women’s societal roles, can explain the persistent gender gap in mathematics. Stereotypes lower girls’ beliefs, expectations, and incentives to put forth effort, and can constrain girls’ choices in male-dominated high-paying careers that are math-intensive and that require strong math skills. This gap slows progress toward gender equality in the labor market and hinders productivity and economic growth. Policy interventions to alleviate the negative impacts of descriptive stereotypes aim to prevent girls from internalizing socially constructed behaviors aligned with prevalent gender stereotypes regarding the innate mathematical abilities of boys and girls. Boosting girls’ confidence in their math skills includes introducing them to female role models, such as women math teachers, using gender-neutral language, and providing textbooks and other teaching materials that challenge gender stereotypes. A different set of policies focuses on altering the environment in which girls learn, rather than modifying their beliefs. By adjusting the testing methods (such as reducing the level of competition) or adapting the instructional approach to better align with the learning style of girls, it is possible to create an environment that enables more girls to achieve their maximum potential and to accurately assess their math abilities and interests, rather than simply their test-taking or classroom performance. However, interventions that aim to modify the beliefs and attitudes of girls and women ex post, as well as those that seek to alter the environment, may not work in the long term because they reinforce preexisting stereotypes and operate within the constraints of those stereotypes. For instance, while modifying the testing environment may result in higher grades for girls, it may not necessarily alter the perception that girls are incapable of excelling in math. In some cases, these interventions may even have negative consequences. Encouraging girls to “lean in” and behave like boys, for example, can lead to unequal, unjust, and inefficient outcomes because the benefits (economic returns) of doing so are lower or even negative for girls in light of existing gender stereotypes. One popular and affordable approach to combating gender stereotypes involves addressing (unconscious) biases among teachers, parents, and peers through initiatives such as unconscious bias training and self-reflection on biases. The underlying premise is that by increasing awareness of their own (unconscious) biases, individuals will engage their more conscious, non-gender-stereotypical thinking processes. However, such behavioral interventions can sometimes have unintended consequences and result in backlash, and their effectiveness may vary significantly depending on the context, so that their external validity is often called into question. The recognition of the adaptable nature of both conscious and unconscious stereotypes has led to progress in economics, with the development of social learning and information-based theories. Interventions resulting from these models can effectively counteract prescriptive stereotypes that limit girls’ education to certain fields based on societal expectations of gender roles. However, prescriptive gender stereotypes are often based on biased beliefs about the innate abilities of girls and women. Overcoming deeply ingrained descriptive stereotypes about innate abilities of boys and girls is a fruitful avenue for future economics research and can help close the gender performance gap in mathematics.


An Analysis of COVID-19 Student Learning Loss  

Harry Patrinos, Emiliana Vegas, and Rohan Carter-Rau

The coronavirus disease 2019 (COVID-19) pandemic led to school closures around the world, affecting almost 1.6 billion students. This caused significant disruption to the global education system. Even short interruptions in a child’s schooling have significant negative effects on their learning and can be long lasting. The capacities of education systems to respond to the crisis by delivering remote learning and support to children and families have been diverse and uneven. In response to this disruption, education researchers are beginning to analyze the impact of these school closures on student learning loss. The term learning loss is commonly used in the literature to describe declines in student knowledge and skills. Early reviews of the first wave of lockdowns and school closures suggested significant learning loss in a few countries. A more recent and thorough analysis of recorded learning loss evidence documented since the beginning of the school closures between March 2020 and March 2022 found even more evidence of learning loss. In 36 identified robust studies, the majority identified learning losses that amount to, on average, 0.17 of a standard deviation (SD), equivalent to roughly a one-half school year’s worth of learning. This confirms that learning loss is real and significant and has continued to grow after the first year of the COVID-19 pandemic. Most studies observed increases in inequality where certain demographics of students experienced more significant learning losses than others. The longer the schools remained closed, the greater were the learning losses. For the 19 countries for which there are robust learning loss data, average school closures were 15 weeks, leading to average learning losses of 0.18 SD. Put another way, for every week that schools were closed, learning declined by an average of 0.01 SD. However, there are also outliers—countries that managed to limit the amount of loss. In Nara City, Japan, for example, the initial closures had brought down test scores, but responsive policies largely overcame this decline. In addition, a decreased summer vacation helped. In Denmark, children received good home support and their reading behavior improved significantly. In Sweden, where primary schools did not close during the pandemic, there were no reported learning losses. Further work is needed to increase the quantity of studies produced, particularly in low- and middle-income countries, and to ascertain the reasons for learning loss. Finally, the few cases where learning loss was mitigated should be further investigated to inform continued and future pandemic responses.