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Consistent with the extant literature, the present article identifies that the legal framework and system of taxation enacted within a polity are pertinent to predicting rating migration. However, extending upon traditional estimation techniques the study identifies that a number of different model calibrations achieve greater predictive accuracy than traditional parametric regression. Notably, the method is able to achieve superior goodness of fit and predictive accuracy in determining credit rating migration than models employed within the extant literature.<\/jats:p>","DOI":"10.4018\/ijsds.2018100105","type":"journal-article","created":{"date-parts":[[2018,9,28]],"date-time":"2018-09-28T14:18:13Z","timestamp":1538144293000},"page":"70-85","source":"Crossref","is-referenced-by-count":2,"title":["Predicting Credit Rating Migration Employing Neural Network Models"],"prefix":"10.4018","volume":"9","author":[{"given":"Michael","family":"D'Rosario","sequence":"first","affiliation":[{"name":"Deakin University, Burwood, Australia"}]},{"given":"Calvin","family":"Hsieh","sequence":"additional","affiliation":[{"name":"Deakin University, Burwood, Australia"}]}],"member":"2432","reference":[{"key":"IJSDS.2018100105-0","doi-asserted-by":"publisher","DOI":"10.1017\/9781316761380"},{"key":"IJSDS.2018100105-1","article-title":"Interdisciplinary Due Diligence: The Case for Common Sense in the Search for the Swing Justice.","author":"L. 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