The Hardest Interview 2 May 2026

where (\lambda) is unknown to the families but fixed. Families stop early if they a negative marginal utility from another child, but they have only noisy public information about the global ratio.

If (\lambda = 0.1), threshold (p=0.2). If estimated (p < 0.2), they stop early. Families observe historical stops and national ratio changes. Using Bayesian learning, after several days they form a posterior on (\lambda). This influences future stopping. the hardest interview 2

Set (\Delta U = 0) → threshold (p_\textthresh = 2\lambda). where (\lambda) is unknown to the families but fixed

where (k > 0) is a sensitivity parameter (here, (k=2)). threshold (p=0.2). If estimated (p &lt

This creates negative feedback: If boys exceed girls nationally, (p_n < 0.5), and vice versa. At each step, before having another child, the family estimates current national ratio (\hatR) using: