Pricing and momentum of syndicated credit in Europe

We investigate the determinants of syndicated loan prices for European borrowers, spanning the entire period of credit expansion and crisis. We construct a large data base consisting of 2102 rated syndicated loan deals from 1990 to 2008 in twenty three countries and ten economic sectors. We investigate the effects on the spread paid over the risk free rate of three major groups of factors: loan characteristics, borrower characteristics and characteristics of country of the borrower, using both qualitative and quantitative variables in a hedonic regression. The results show that all three groups are significant joint determinants of prices of syndicated credit. Our results confirm the existing literature but also provide for first time results stemming form the risk characteristics of the borrower and the country of the borrower. It is shown that distance-to-default as well as aggregate risk associated with country of the borrower are of great concern to the lenders and hence significantly affect the pricing of syndicated loans. Furthermore, we report that financial institutions and public utilities are able to negotiate for cheaper loans, but this result is reversed when financing is for acquisition purposes. Overall, risk, liquidity, solvency and sustainable performance by both the borrower and its domicile country are key determinants of syndicated loan prices.     

Critical social work and competency practice: a proposal to bridge theory and practice in the classroom

Social work education in North America is increasingly focused on competency criteria and micro skills training for future practitioners. Market forces are transforming the nature of social work practice in Canada, and social work regulators are concerned about the lack of evidence-based competencies in social work education. Since the Controlled Act of Psychotherapy was proclaimed in 2017, social work practitioners are in a position to offer psychotherapy services; as a result, universities are under greater pressure to shift to competency-based learning that meets the requirements of a regulated profession. This has raised concerns about the narrowing focus on critical social work theory in preparing students for practice. The divergence between anti-oppressive and direct practice schools is widening with the result that many students have difficulty bridging the gap between critical theory and competency-based practice. This paper attempts to integrate both traditions by offering students a course that directly links critical analysis of structural barriers and client centered interventions. The course is part of a developing critical competency curriculum that focuses on methods of facilitating empowerment and change in the helping process by articulating key relational components between service user and practitioner from a critical-competency perspective.     

“Super-covariates”: Using predicted control group outcome as a covariate in randomized clinical trials

The power of randomized controlled clinical trials to demonstrate the efficacy of a drug compared with a control group depends not just on how efficacious the drug is, but also on the variation in patients' outcomes. Adjusting for prognostic covariates during trial analysis can reduce this variation. For this reason, the primary statistical analysis of a clinical trial is often based on regression models that besides terms for treatment and some further terms (e.g., stratification factors used in the randomization scheme of the trial) also includes a baseline (pre-treatment) assessment of the primary outcome. We suggest to include a “super-covariate”—that is, a patient-specific prediction of the control group outcome—as a further covariate (but not as an offset). We train a prognostic model or ensembles of such models on the individual patient (or aggregate) data of other studies in similar patients, but not the new trial under analysis. This has the potential to use historical data to increase the power of clinical trials and avoids the concern of type I error inflation with Bayesian approaches, but in contrast to them has a greater benefit for larger sample sizes. It is important for prognostic models behind “super-covariates” to generalize well across different patient populations in order to similarly reduce unexplained variability whether the trial(s) to develop the model are identical to the new trial or not. In an example in neovascular age-related macular degeneration we saw efficiency gains from the use of a “super-covariate”.