On making causal claims: A review and recommendations

Social scientists often estimate models from correlational data, where the independent variable has not been exogenously manipulated; they also make implicit or explicit causal claims based on these models. When can these claims be made? We answer this question by first discussing design and estimation conditions under which model estimates can be interpreted, using the randomized experiment as the gold standard. We show how endogeneity – which includes omitted variables, omitted selection, simultaneity, common-method variance, and measurement error – renders estimates causally uninterpretable. Second, we present methods that allow researchers to test causal claims in situations where randomization is not possible or when causal interpretation could be confounded; these methods include fixed-effects panel, sample selection, instrumental variable, regression discontinuity, and difference-in-differences models. Third, we take stock of the methodological rigor with which causal claims are being made in a social sciences discipline by reviewing a representative sample of 110 articles on leadership published in the previous 10 years in top-tier journals. Our key finding is that researchers fail to address at least 66% and up to 90% of design and estimation conditions that make causal claims invalid. We conclude by offering 10 suggestions on how to improve non-experimental research.     

Moment estimators of defect pattern frequencies,allowing for inspection error

Unbiased estimators of the number of individuals in a lot possessing various patterns of types of defects are constructed. Explicit formulas are given for cases of two and three types of defect. Application of the formulas requires knowledge of the probabilities of various kinds of errors in the inspection process.     

Combining Univariate Tests for Multivariate Location Problem

In this article, three methods of combining dependent univariate tests are studied. The Bahadur approximate efficiencies are derived under the asymptotic normal assumption. These procedures are applied to the multivariate location problem and compared with two Hotelling-type tests. A Monte Carlo study indicates that in certain cases the powers of the combination methods are much better than Hotelling's T ² and other multivariate nonparametric tests.     

Labour and international accounting standards: A question of social justice

As the international guardian of social justice, the ILO is witnessing a global revolution in accounting, which has culminated in international accounting standards (IAS-IFRS). Previously, accounting measured the economy in relation to the capacities and responsibilities of workers and their employers. Today, the exact opposite is the case: the IAS-IFRS no longer measure work and enterprises, referring instead to the abstract concept of a cybernetic entity capable of constant restructuring, at the cost of unprecedented inequality. The author points to the incoherence of this system and to the need to restore the full carrying value of labour.     

Travail et normes comptables internationales: une question de justice sociale

En tant que garante internationale de la justice sociale, l'OIT se trouve confrontée à une révolution comptable mondiale, parachevée par les normes comptables internationales (IAS-IFRS). La comptabilité mesurait autrefois l'économie en rapport avec les capacités et les responsabilités des travailleurs et de ceux qui en disposent. C'est aujourd'hui l'exact opposé: les normes IAS-IFRS ont perdu le sens de la mesure du travail et de l'entreprise en se référant au concept abstrait d'une entité cybernétique capable d'incessantes réorganisations, au prix d'inégalités sans limites. L'auteur en dénonce les incohérences et démontre la nécessité de redonner au travail toute sa valeur comptable.     

T. Brandsen,S. Cattacin,A. Evers,A. Zimmer (Eds.): Social Innovations in the Urban Context

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations -     

Prosocial Behavior: Long‐term Trajectories and Psychosocial Outcomes

This study investigated developmental trajectories for prosocial behavior for a sample followed from the age of 10–18 and examined possible adjustment outcomes associated with membership in different trajectory groups. Participants were 136 boys and 148 girls, their teachers, and their parents (19.4 percent African‐American, 2.4 percent Asian, 51.9 percent Caucasian, 19.5 percent Hispanic, and 5.8 percent other). Teachers rated children's prosocial behavior yearly in grades 4–12. At the end of the 12th grade year, teachers, parents, and participants reported externalizing behaviors and participants reported internalizing symptoms, narcissism, and features of borderline personality disorder. Results suggested that prosocial behavior remained stable from middle childhood through late adolescence. Group‐based mixture modeling revealed three prosocial trajectory groups: low (18.7 percent), medium (52.8 percent), and high (29.6 percent). Membership in the high prosocial trajectory group predicted lower levels of externalizing behavior as compared with the low prosocial trajectory group, and for girls, lower levels of internalizing symptoms. Membership in the medium prosocial trajectory group also predicted being lower on externalizing behaviors. Membership in the high prosocial trajectory group predicted lower levels of borderline personality features for girls only.