Page 267 - Contributed Paper Session (CPS) - Volume 6

CPS1925 Marek K.
centuries. In order to obtain a homogeneous sample with relatively consistent
experiences, all respondents aged 25-45 were required to have higher
education. In total, 902 respondents participated in the study.
The analysis of such a defined data set was carried out in two stages. In
the first step, data related to various aspects of saving and borrowing
(separately for each area) were subjected to exploratory factor analysis (EFA),
with principal component analysis and varimax rotation. The extracted factors
were supposed to have eigenvalues higher than one. Additionally, the
resulting set of factors had to explain a minimum of 75% of the variance of
the original set of variables (factors explaining less than 10% of the total
variance were not taken into account). The primary purpose of factor analysis
was to identify latent constructs and assessment of dimensionality in the set
of analyzed questions. In both analyzed areas – saving and borrowing – the
number of concealed dimensions obtained was 3. The dimensions identified
in this way meet the conditions set by Briggs and Cheek (1986) – they are both
conceptually meaningful and empirically useful. In the second step, the
emergent constructs were utilized in the regression analysis as independent
variables what allowed to indicate key determinants of the aspects of saving
and borrowing identified in this way.
The basic variable whose impact on saving and borrowing was verified is
the respondent's economic resourcefulness, for which the structural equation
model (MIMIC) proposed in Kośny and Piotrowska 2018 (one-generational
model) was used. The theoretical values of the hidden variable – economic
resourcefulness – were estimated on the basis of the estimates given there.
Then the imputed values obtained in this way were used as an explanatory
variable in the regression models estimated for particular aspects of saving
and borrowing.
All analyzes and calculations presented in this article were carried out in
IBM SPSS Statistics 24.

3. Result
The starting point for the analysis is the exploratory factor analysis (EFA),
the results of which are presented in Table 1. For the principal component
analysis, answers to 7 questions were used, which in the study concerned the
issue of saving. Taking into account the content of the questions on the basis
of which the analysis was carried out, emerging factors can be described in
the following way.
Factor 1 can be characterized as the Ability to accumulate savings, because
it shows the specific effects of the saving process, which is the savings
accumulated – both pension savings, as well as those which, in the
respondent's opinion, are not intended for this purpose. This distinction is
significant because the question left the respondent free to define the nature

256 | I S I W S C 2 0 1 9