Model-Based Estimation of Sovereign Default
SSRN, ISSN: 1556-5068
2017
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
We estimate a canonical sovereign default model from Arellano (2008) for Argentina via maximum simulated likelihood estimation to understand how well it performs in terms of predicting default events. The estimated model accounts for the overall default patterns of Argentina and closely matches the default data. Out-of-sample forecasting shows that the model performs better than a logit model in predicting the onset of default events. In terms of the business cycle statistics, the findings of the model are consistent with the data and Arellano (2008), with some caveats.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85116645063&origin=inward; http://dx.doi.org/10.2139/ssrn.3056539; https://www.ssrn.com/abstract=3056539; https://dx.doi.org/10.2139/ssrn.3056539; https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3056539; https://ssrn.com/abstract=3056539
Elsevier BV
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