This paper studies the causal effect of improved housing conditions on people's risk and time preferences and cognitive function. Understanding the effects of improved housing quality is important for evaluating public housing policies as well as for understanding the impact of bad housing conditions on the choices of poor people and their ability to improve their economic situation. The data will be collected from adult participants of a unique randomized controlled trial “Rapid Re-Housing” that is currently running in Brno in the Czech Republic. In this trial, a randomly selected group of 50 homeless families were moved to municipal flats, while the 100 control families were not helped by the city and, in the majority of cases, remained in bad housing conditions.

The question about the relationship between wealth or income and risk or time preferences has been studied by many authors (e.g. Guiso and Paiella, JEEA, 2008; Tanaka et al, AER, 2010) and surveyed by Haushofer and Fehr (Science, 2014). The effect of wealth or income on cognitive abilities has been studied e.g. by Mani et al. (Science, 2013). In comparison to these studies, our treatment increases only consumption of housing services while keeping wealth or income constant. Therefore, the design of the RCT allows us to isolate the effect of one channel, better housing, through which higher wealth or income can influence preferences or cognitive abilities.

We conducted a lab-in-the-field experiment with adult members of the treatment and control group (roughly 160 subjects) in 2018. Risk and time preferences and cognitive function were measured using standard incentivized questionnaires. For measuring risk and time preferences we used standard multiple price lists adapted from Sutter et al. (AER, 2013). For measuring cognitive function, we selected the D2 test of attention.

We do not find any differences between the control and treatment groups in risk and time preferences and in their cognitive abilities. This result goes against the above-cited literature on the impact of poverty on preferences and cognitive abilities. There are several possible explanations of the zero result. First of all, our treatment changes the stream of consumption from housing services, but it does not affect the monetary wealth of our participants. The null results would be expected if the differences in preferences and abilities were due to differences in financial wealth. Second, the change in housing condition might not be large enough to drive the expected effects. In order to address this issue, we used questionnaire data about their wellbeing, which is significantly higher in the treatment group. This data is used to estimate the financial impact of the treatment. The third option is that our sample size does not provide enough power to identify the results. This issue is addressed in a power analysis.