Attenuation bias vs selection bias: a multi-outcome three-stage model
提出一个贝叶斯推断框架，用于处理多结果内生三阶段模型中的偶然截断、参与选择和访问限制问题，发现忽略访问限制会引入测量误差，并在信贷和公用事业需求数据中验证了模型。
.We propose a Bayesian inferential framework for a multi-outcome endogenous three-stage model that accounts for incidental truncation in outcomes (intensive margin), selection into participation (extensive margin), and access restrictions. Simulation exercises assessing finite-sample properties under various misspecification settings suggest that incorporating access restrictions and unobserved correlations is crucial. In particular, access restrictions play a critical role, as failing to account for them may introduce measurement error when correcting for selection bias. This suggests a potential tension between attenuation and selection biases. We apply our framework to two novel datasets on credit and utility demand. We extend our parametric specification to a semi-parametric one in the latter application, modeling stochastic errors using a Dirichlet process mixture. The credit demand application suggests that better socioeconomic conditions increase the probability of using credit cards but decrease the likelihood of taking bank loans. In addition, women are more likely to use credit than men, but men tend to borrow larger amounts. The utility application highlights the importance of urban areas in increasing the probability of access to piped utilities, water and gas are inelastic goods, whereas electricity is elastic.