Bibliographic citations
Tristán, A., (2021). Identificación de conglomerados espaciales de acuerdo a niveles de morosidad de empresas en el Perú [Pontificia Universidad Católica del Perú]. http://hdl.handle.net/20.500.12404/20819
Tristán, A., Identificación de conglomerados espaciales de acuerdo a niveles de morosidad de empresas en el Perú []. PE: Pontificia Universidad Católica del Perú; 2021. http://hdl.handle.net/20.500.12404/20819
@mastersthesis{sunedu/3113588,
title = "Identificación de conglomerados espaciales de acuerdo a niveles de morosidad de empresas en el Perú",
author = "Tristán Gómez, Alex Edward",
publisher = "Pontificia Universidad Católica del Perú",
year = "2021"
}
Compliance with the nancial obligations of companies is ensured by proper credit risk management, this avoids liquidity and solvency problems. For this reason, it is important to identify the risk level of default in peruvian companies. The goal of this thesis is to identify clusters of provinces of Per u with regard to the default rate of payments, also known as probability of default. Thus it is proposed a model in two stages. In the rst stage hierarchical agglomerative models select prior candidate clusters, and the nal number of clusters is selected through selection criteria of models. In the second stage it is proposed the Poisson model considering autoregressive conditional prioris, the clusters de ned in the rst stage, and also including covariates. This model ll in the class of Gaussian latent models, therfore its paremeters were estimated using bayesian inference, speci cally through integrated nested Laplace approximation. Finally, as a result, we found clusters in accordance with the default level, allowing to classify provinces into clusters of high, medium and low risk level.
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