Stefano Cellini

Researchers have tested for imperfect information in rental sector and housing-induced returns heterogeneity among occupiers by estimating cross-sectional single-equation models. This approach leads to the estimation of conspicuous wedges in insulation investment propensity between tenants vs owner-occupiers (≥ 20 percentage points) and low-return vs high-return dwellings households (0.10-0.20pp) in the UK. I complement these findings by analysing their sensitivity to assumptions on unobservables à la Oster (2019) and Cinelli and Hazlett (2020). According to the former’s parametrization, under equally strong observables and unobservables, the effect of split incentives on loft/wall insulation investment can be up to 40%/26% lower, while the effect of housing choices is unaltered. Instead, the latter’s strategy suggests that an equal selection scenario would reduce by at least 60% the split incentives estimates, whereas non-random housing would just cause the estimates to drop by less than one third. Hence, I quantify how easily research conclusions may be severely affected by a certain degree of selection and offer some convenient tools to integrate in the assessment of the sources of under-retrofitting with cross-sectional data.