UiS Working Papers in Economics and Finance,
University of Stavanger

Abstract: This paper addresses the issue of credit risk in the salmon industry. During the period 2000-2002 the Norwegian salmon industry witnessed a period of low prices leading to a wave of defaults and bankruptcies. The consequences were large monetary losses for both investors and banks, highlighting the importance of early detection of failing firms. Using financial ratios measuring the firms' financial status prior to this event, two credit risk models are developed; one using logit regression and the other Classification and Regression trees. The performance of the two models developed is compared to a cross-industry benchmark model developed by the Norwegian Central Bank. The models estimated on industry data is better at separating between companies with high and low credit risk in the salmon industry compared to the benchmark model.

Keywords: Atlantic salmon production; credit risk; default probability models; logit; Classification and regression trees.

JEL-codes: G17; M49; Q22

41 pages, December 18, 2015

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