Imperfect information in rental sector and housing-induced returns heterogeneity among occupiers are typically estimated with cross-sectional single-equation models. This approach leads to the estimation of conspicuous wedges in insulation investment propensity between tenants vs owner–occupiers ($\ge 20$ percentage points) and low-return vs high-return dwellings households (0.10–0.20pp) in the UK. I analyse 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. 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 a certain degree of selection on research conclusions and offer some convenient tools to integrate in the assessment of the sources of under-retrofitting with cross-sectional data.

租赁部门的不完善信息和居住者之间由住房引起的回报异质性通常使用横截面单方程模型进行估计。这种方法导致对租户与自住业主之间绝缘投资倾向的明显楔形的估计（$\ge 20$百分点）以及英国的低回报与高回报住宅家庭（0.10–0.20pp）。我分析了他们对 à la Oster (2019) 和 Cinelli and Hazlett (2020) 的不可观测假设的敏感性。根据前者的参数化，在可观察和不可观察同等强的情况下，分割激励对阁楼/墙体保温投资的影响最多可降低40%/26%，而住房选择的影响没有改变。后者的策略表明，平等选择方案将至少减少 60% 的分裂激励估计，而非随机住房只会导致估计下降不到三分之一。因此，我对研究结论的选择进行了一定程度的量化，并提供了一些方便的工具，可以将横截面数据整合到对欠改造来源的评估中。