The application of classification and regression trees in the analysis of saving and credit decisions made by households
The application of classification and regression trees in the analysis of saving and credit decisions made by households

Summary/Abstract: The study analyses the behaviour presented by natural persons in situations which require making decisions about savings or taking loans. The objective of the article is to identify the factors determining the choice of a given option and to indicate both the advantages and disadvantages resulting from a particular attitude. The following research tools were applied: the CART method (Classification and Regression Trees) and the descriptive method. The empirical data originate from surveys carried out by the CAWI method (Computer Assisted Web Interview) performed on a sample of 1000 Poles. The obtained results indicate that debt aversion, holding credits and the level of income earned, represent the main factors determining an individual tendency to make decisions regarding saving. In the case of credit decisions, the most important factors are the level of debt aversion, monthly net income level of a household and being in possession of savings.

• Details
• Contents