Risk Analysis: Celebrating the Accomplishments and Embracing Ongoing Challenges

As part of the celebration of the 40th anniversary of the Society for Risk Analysis and Risk Analysis: An International Journal, this essay reviews the 10 most important accomplishments of risk analysis from 1980 to 2010, outlines major accomplishments in three major categories from 2011 to 2019, discusses how editors circulate authors’ accomplishments, and proposes 10 major risk-related challenges for 2020–2030. Authors conclude that the next decade will severely test the field of risk analysis.     

Estimation of generalized linear latent variable models

Summary.  Generalized linear latent variable models (GLLVMs), as defined by Bartholomew and Knott, enable modelling of relationships between manifest and latent variables. They extend structural equation modelling techniques, which are powerful tools in the social sciences. However, because of the complexity of the log-likelihood function of a GLLVM, an approximation such as numerical integration must be used for inference. This can limit drastically the number of variables in the model and can lead to biased estimators. We propose a new estimator for the parameters of a GLLVM, based on a Laplace approximation to the likelihood function and which can be computed even for models with a large number of variables. The new estimator can be viewed as an M -estimator, leading to readily available asymptotic properties and correct inference. A simulation study shows its excellent finite sample properties, in particular when compared with a well-established approach such as LISREL. A real data example on the measurement of wealth for the computation of multidimensional inequality is analysed to highlight the importance of the methodology.     

Local dependence estimation using semiparametric archimedean copulas

The authors define a new semiparametric Archimedean copula family which has a flexible dependence structure. The generator of the family is a local interpolation of existing generators. It has locally‐defined dependence parameters. The authors present a penalized constrained least‐squares method to estimate and smooth these parameters. They illustrate the flexibility of their dependence model in a bi‐variate survival example.     

Ethnic Institutions Reconsidered: The Case of Flemish Workers in 19th Century France1

Abstract Traditional perspectives on ethnic institutions tend to consider mainly their role in the preservation of the cultural and social fabric of ethnic communities. Increasing evidence indicates that ethno‐institutional effects are often more varied and complex. France's first industrial‐era immigrants, massively crossing the border from Belgian Flanders during the second half of the 19^th century, are a case in point. Immigrant Flemish workers introduced a new type of institution to the French working class: socialist cooperatives. These would have a long‐term impact not only on the immigrant Flemish community itself, but also on the larger labour movement, on the region, and on the country as a whole. Three elements were important in this process of institutional cross‐fertilization: Belgian workers’ rich institutional repertoire; the coincidence of their settlement with the rise of the French labour movement; and the fact that their institutional innovation was easily transferable.