Graphics for the Minimal Sufficient Cause Model

Graphical representations of causation have been usedfor at least seventy years, and the modern developmentof directed acyclic graphs to portray causal systemscontinues the trend. It is sometimes difficult tounderstand, however, what it is about these diagramsthat is `causal'. The approach to causal graphicsthat is taken here is to base the development ofgraphics on the concepts of an underlying causaltheory, the minimal sufficient cause model. Thisleads to defining a Boolean `and' for arrows thatrepresent causal pathways, and a Boolean `or' forcollections of pathways. Complementation is a morecomplex operation in the minimal sufficient causetheory than simply inverting the sense of a causalrelationship, and this also is represented in thegraphics. By using diagrams that are more faithful tounderlying causal systems, and using a coherent causaltheory, both the perception of causation and itsanalysis might be enhanced.     

Industrial segmentation,the ethnic economy,and job mobility: the case of Cuban exiles in Florida

We examine mobility between core, periphery, and the ethnic economy in a sample of Cuban exiles. We analyze, first, hypotheses involving the relative magnitude of exit rates from given origins, and, second, hypotheses positing effects of independent variables on exit rates. Regarding the first type of hypotheses, we argue that the presence of an ethnic economy requires modification of predictions in the segmented economy perspective. Data support our argument. Concerning the second type of predictions, regression analysis shows that movement into the periphery is negatively associated with number of relatives in the U.S., movement into ethnic economy employment is positively related to number of relatives living in same city as respondent, and movement into self-employment is positively related to education, intention to return to Cuba if communism were overthrown, and taking a university-level course, and negatively associated with living in a Cuban neighborhood. As a whole, regression results indicate that, with the exception of movement into the periphery, individuals with more resources are more prone to mobility.     

Millsian causation

The Directed Acyclic Graph (DAG) theory of causation is based on the assumption that randomly sampling the variables of a causal system will yield a joint probability distribution that satisfies the Markovian condition. It is shown here that this condition can be split into two parts, one of which is named the Millsian condition. It is further shown that the Millsian condition alone implies that causally unrelated sets of variables are conditionally independent given their common causes, very likely a key requirement stated by John Stuart Mill 150 years ago. In Millsian causation, unlike Markovian causation, it is possible for an indirect cause to be associated with its effect even when controlling for the intermediate direct causes. This phenomenon is explained by taking into account the existence of potential causal modulation.