Examining Statistical Methods in Forecasting Financial Energy of Households in Poland and Taiwan

Abstract

This paper examines the usefulness of statistical methods in forecasting the financial energy of households. The study’s objective is to create the innovative ratios that combine both financial and demographic information of households and implement them in the forecasting models. To conduct this objective, six forecasting models are developed using three different methods—discriminant analysis, logit analysis, and decision trees separately for households in Poland and Taiwan. Such a research approach will answer the question whether the implementation of constructed ratios can increase effectiveness of the forecasting model and its’ versatility between different economic regions. The research relies on four samples of households—two learning samples and two testing samples (one for each country) consisting of 2400 households from both countries. This study is one of the first attempts in the literature globally to develop forecasting models based on ratios constructed with a combination of two different types of variables—one financial with one demographic variable. Findings confirm the high usability of the proposed innovative approach for forecasting the financial energy of households by taking into account a wide spectrum of diagnostic variables representing the financial strength of consumers.