C25 - Single Equation Models; Single Variables: Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; ProbabilitiesReturn

The aim of the paper is to estimate models for household classification from the point of view of their financial situation. The models are constructed on the basis of data from the Living Conditions 2010 survey. The target indicators are the possibility of a household to afford a week-long vacancy outside home, the possibility of a household to afford paying an unplanned expenditure in a certain amount, and an evaluation of how a household is economical with its income. The explanatory indicators are the gender of the head of the household (HOH), the education level of the HOH, the marital status of the HOH, the age of the HOH, and the household type according to the OECD classification. For this purpose, classification trees and logistic regression were applied. The models obtained were evaluated according to the total success rate and the F-measure. The education level of the head of the household was found to be the most important indicator for the prediction.

Panel data are specific data where cases are observed at two or more time periods. This approach brings many advantages: larger dataset, decreasing collinearity between exogenous variables and using advanced econometric models. The panel data models were applied to data from the Household Budget Surveys 2000-2004 carried out by the Czech Statistical Office in order to analyze choice behavior of households. The data on households included demographic characteristics of individuals, housing, household amenities, net income, and opinions of households about their own socioeconomic situation. We analyzed the role of income as a determinant of PC ownership and its development through the observed period by using three static econometric models with panel data.