Logical differencing in dyadic network formation models with nontransferable utilities
针对非转移效用下的二元网络形成问题，提出一种称为逻辑差分法的新方法，通过构造基于多元单调性的互斥事件来消除未观测异质性，并给出了一致估计量，应用于Nyakatoke风险分担网络。
This paper considers a semiparametric model of dyadic network formation under\nnontransferable utilities (NTU). NTU arises frequently in real-world social\ninteractions that require bilateral consent, but by its nature induces additive\nnon-separability. We show how unobserved individual heterogeneity in our model\ncan be canceled out without additive separability, using a novel method we call\nlogical differencing. The key idea is to construct events involving the\nintersection of two mutually exclusive restrictions on the unobserved\nheterogeneity, based on multivariate monotonicity. We provide a consistent\nestimator and analyze its performance via simulation, and apply our method to\nthe Nyakatoke risk-sharing networks.\n