This predictive analytic model prioritizes high-cost individuals for whom the solution of housing costs less than the problem of homelessness. Cost offsets from reduced service use after high-cost individuals are stably housed can be stretched across a larger pool of homeless people whose...

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,...

We investigate the accuracy of ex ante assessments of vulnerability to income poverty using cross-sectional data and panel data. We use long-term panel data from Germany and apply different regression models, based on household covariates and previous-year equivalence income, to classify a...

We investigate the accuracy of ex ante assessments of vulnerability to income poverty using cross-sectional data and panel data. We use long-term panel data from Germany and apply different regression models, based on household covariates and previous-year equivalence income, to classify a...

The belief that home ownership makes people happy is probably one of the most widespread intuitive theories of happiness. However, whether it is accurate is an open question. Based on individual panel data, we explore whether home buyers systematically overestimate the life satisfaction...

The belief that home ownership makes people happy is probably one of the most widespread intuitive theories of happiness. However, whether it is accurate is an open question. Based on individual panel data, we explore whether home buyers systematically overestimate the life satisfaction...