【摘要】This paper investigates spatio-temporal variations in ex-post credit risk in the United States, as a function of real estate prices, loan purchases made by government sponsored enterprises, and a set of local characteristics during the recent housing boom and bust.We model bank's non-performing loans as a first-order dynamic panel data regression model with group-specific effects and spatial autoregressive errors. To estimate this model, we develop an ad-hoc generalized method of moments procedure which consists of augmenting moments proposed by the panel literature to estimate short T, pure dynamic panels, with a set of quadratic conditions in the disturbances. Results on estimation of the empirical model point at the negative impact of real estate prices on non-performing loans. Further, our results show that a rise in the number of real estate mortgages backed by government-sponsored enterprises increases non-performing loans, thus deteriorating the quality of banks' loan portfolio.

【关键词】Non-performing loans; House prices; Dynamic panels; Spatial dependence; GMM estimator

【文献来源】Francesco Moscone; Elisa Tosetti; Alessandra Canepa.Regional Science and Urban Economics.2014（11）