Europeans' willingness to pay for ending homelessness: A contingent valuation study.

The purpose of this study is to assess the utility value European citizens put on an innovative social program aimed at reducing homelessness. The Housing First (HF) model involves access to regular, scattered, independent and integrated housing in the community with the support of a multidisciplinary team. Currently, HF is not implemented by most European countries or funded by healthcare or social plans, but randomised controlled trials have stressed significant results for improved housing stability, recovery and healthcare services use. The broader implementation of HF across Europe would benefit from a better understanding of citizens' preferences and "willingness to pay" (WTP) for medico-social interventions like HF. We conducted a representative telephone survey between March and December 2017 in eight European countries (France, Ireland, Italy, the Netherlands, Poland, Portugal, Spain, and Sweden). Respondent's WTP for HF (N = 5631) was assessed through a contingent valuation method with a bidding algorithm. 42.3% of respondents were willing to pay more taxes to reduce homelessness through the HF model, and significant differences were found between countries (p < 0.001); 30.4% of respondents who did not value the HF model were protest zeros (either contested the payment vehicle-taxes- or the survey instrument). Respondents were willing to pay €28.2 (±11) through annual taxation for the HF model. Respondents with higher educational attainment, who paid national taxes, reported positive attitudes about homelessness, or reported practices to reduce homelessness (donations, volunteering) were more likely to value the HF model, with some countries' differences also related to factors at the environmental level. These findings inform key stakeholders that European citizens are aware of the issue of homelessness in their countries and that scaling up the HF model across Europe is both feasible and likely to have public support.