We present the methodology for developing a predictive model for identifying homeless persons likely to have high future costs for public services. It was developed by linking administrative records from 2007 through 2012 for seven Santa Clara County agencies and identifying 38 demographic,...

To their credit, empirical legal scholars try to live up to the highest methodological standards from the social sciences. But these standards do not always match the legal research question. This paper focuses on normative legal argument based on empirical evidence. Whether there is a normative...

The WHO defines vaccine hesitancy as one of the ten biggest threats to global health nowadays. To contribute to finding a solution for vaccine hesitancy, this study aims at gaining new insights on the influence of the default effect, anticipated regret, and decision roles on vaccination...

Human decision-making differs due to variation in both incentives and available information. This generates substantial challenges for the evaluation of whether and how machine learning predictions can improve decision outcomes. We propose a framework that incorporates machine learning on...

This paper proposes a new set of public health and long-term care expenditure projections till 2060, following up on the previous set of projections published in 2006. It disentangles health from longterm care expenditure as well as the demographic from the non-demographic drivers, and refines...

Concerns about health expenditure growth and its long-term sustainability have stimulated the development of health expenditure forecasting models in many OECD countries. This comparative analysis reviewed 25 models that were developed by, or used for, policy analysis by OECD member countries...