N°24-55: Proxy-Identification of a Structural MGARCH Model for Asset Returns

We study the impact of armed conflict on loan officers and their lending decisions. Our empirical results show that following repeated mortar shelling, loan rates set by loan officers surpass those in comparable border areas, with a stronger effect when decisions are made closer to recent incidents. Estimating a structural model of credit demand, default, and supply suggests that this increase is driven by heightened risk perception among loan officers. Our findings reveal substantial hidden costs for borrowers, driven by pessimistic beliefs in credit markets during armed conflict.