An Empirical Illustration of Positive Stigma towards Child Labor

This empirical note complements the qualitative and theoretical research on positive household stigma towards child labor. We use data from Guatemala and two instruments for measuring stigma: a child's indigenous background and household head's childhood work experience. We then adopt binomial probit regression methods to illustrate that positive stigma has a large effect on child labor practices, and a modest effect on school enrollment.child labor, education, indigenous, stigma, Guatemala

Technology, computers, and wages : evidence from a developing economy

Increasing returns to schooling and rising inequality are well documented for industrial countries and for some developing countries. The growing demand for skills is associated with recent technological developments. The authors argue that computers in the workplace represent one manifestation of these changes. Research in the United States and industrial countries documents a premium for computer use. But there is recent evidence suggesting that computer skills by themselves do not command a wage premium. The authors review the literature and use data from a survey of higher education graduates in Vietnam. The results support the unobserved heterogeneity explanation for computer wage premiums. They suggest that computers may make the productive workers even more productive. However, given the scarcity of computers in low-income countries, an operational strategy of increasing computer availability and skills would seem to offer considerable hope for increasing the incomes of the poor.Information Technology,General Technology,Educational Technology and Distance Education,ICT Policy and Strategies,Teaching and Learning,ICT Policy and Strategies,General Technology,Educational Technology and Distance Education,Teaching and Learning,Primary Education

Measuring human capital using global learning data

Human capital—that is, resources associated with the knowledge and skills of individuals—is a critical component of economic development1,2. Learning metrics that are comparable for countries globally are necessary to understand and track the formation of human capital. The increasing use of international achievement tests is an important step in this direction3. However, such tests are administered primarily in developed countries4, limiting our ability to analyse learning patterns in developing countries that may have the most to gain from the formation of human capital. Here we bridge this gap by constructing a globally comparable database of 164 countries from 2000 to 2017. The data represent 98% of the global population and developing economies comprise two-thirds of the included countries. Using this dataset, we show that global progress in learning—a priority Sustainable Development Goal—has been limited, despite increasing enrolment in primary and secondary education. Using an accounting exercise that includes a direct measure of schooling quality, we estimate that the role of human capital in explaining income differences across countries ranges from a fifth to half; this result has an intermediate position in the wide range of estimates provided in earlier papers in the literature5–13. Moreover, we show that average estimates mask considerable heterogeneity associated with income grouping across countries and regions. This heterogeneity highlights the importance of including countries at various stages of economic development when analysing the role of human capital in economic development. Finally, we show that our database provides a measure of human capital that is more closely associated with economic growth than current measures that are included in the Penn world tables version 9.014 and the human development index of the United Nations15

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

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