Jochen SchweikertEpidemiologische Ausbreitung von Kreditausfällen auf dem Hypothekenmarkt

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This dissertation introduces a mathematical model to capture the spreading of mortgage defaults within the United States. The dependence between several default events that occur far away from each other are included and explicitly modelled. Therefore epidemiological models, which usually measure the spreading of diseases are used. There are similar characteristics between the spread of an infection between humans (such as cholera) and the spatial influence of mortgage defaults on the default probabilities of mortgages that are located nearby (inside the same US-county). Using this comparison, the state of the infected and potential subsequent death, represent the steps of payment delinquency and default. Furthermore, a large number of studies show that unemployment rates run a similar course in areas whose economies are similarly specialised. The proposed model also uses some highly significant drivers of mortgage defaults, e.g. unemployment rates. The work of Bertuzzo et al. (2010) that captures the spread of cholera is adapted to the mortgage market to model the ’infected’ mortgages. The G statistic from Feser et al. (2005) is applied to the industry clustering algorithm first proposed by Delgado et al. (2016) to connect areas that are far apart but economically similar. As a result, dependencies of the mortgage market between several areas can be measured. The estimation of key parameter is based on a large sample of loan-level data. 14602073 mortgages originating between 2000 and 2014 are used to estimate the model’s parameter by using the iterated filtering algorithm proposed by Ionides et al. (2015).

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