Non – parametric estimation of conditional and unconditional loan portfolio loss distributions with public credit registry data

Employing a resampling-based Monte Carlo simulation developed in Carey (2000, 1998) and Majnoni, Miller and Powell (2004), in this paper we estimate conditional and unconditional loss distributions for loan portfolios of argentine banks in the period 1999-2004, controlling by type of borrower and type of bank. The exercise, performed with data contained in the public credit registry of the Central Bank of Argentina, yields economic estimates of expected and unexpected losses useful in bank supervision and in the prudential regulation of credit risk, for example to measure if Basel II’s IRB approach is appropriately calibrated to the local economy.