Mathematics in Education, Research and Applications (MERAA), 2017(3), 2
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Published online 2017-12-31
DOI:http://dx.doi.org/10.15414/meraa.2017.03.02.49-56
Application of the logistic regression analysis to assess credibility of the farm
Jozef Palkovič, Martina Šoporová
Slovak university of Agriculture in Nitra, Nitra, Slovak Republic
Article Fulltext (PDF), pp. 49–56
- Logistic regression is useful tool of statistical analysis used in various field of research, especially to classify units according their
parameters, or to estimate chance of event occurrence. On the economic field this method is usually used to estimate bankruptcy and credit models, or to
predict consumers’ behavior. Objective of the proposed paper is to present application of the logistic regression analysis to assess credit of the farm. This
paper can be used also as guide through the process of modelling, model verification and interpretation of its results. Data used to estimate logistic
regression were individual farm data cover large farms from the database of the Ministry of Agriculture and Rural Development in Slovakia for the period
2009 to 2013. 4000 observations were used to estimate final model, and 427 observations were used as the sample for the model verification. Then, logistic
regression model was estimated and verified. From the initial set of 13 variables were selected 7 significant variables to final model. Factor which increased
probability of getting loan the most significantly was proportion of loans, on the other hand, factor which decreased this probability the most was the
proportion of crop production. Quality and prediction ability of the final model according to standard indicators was fair, however there could be suggested
including additional variables to improve model prediction ability, and its further testing by its application on more testing samples. Paper offers better
insight into process of logistic regression application, and suggests ways of current topic further developing.
- Keywords: logistic regression, credit model, chance model, logit
- JEL Classification: C01, C10, C18, B23, B26