Correlations between attitude to money and demographic variables on a sample of university students

DOI:

Nowadays research on the people’s attitude to money was followed by greater attention. With globalisation gaining ground, the rapid changes in the labour market and the appearance of the economic crisis studying and understanding people’s attitude to money has become inevitable not only in Western but also in other cultures, too. The first researches were centred on the attempt to develop psychometric instruments in order to measure people’s attitude to money. Yamauchi and Templer [28] worked out Money Attitude Scale (MAS), Furnham [7] developed the Money Beliefs and Behaviour Scale (MBBS); Tang et al created Money Ethical Scale (MES) [21; 22; 23]. Afterwards, Lim and Teo [13] adapted the three abovementioned measures to gain data on general attitude to money. The studies published afterwards basically used and developed the existing list of items and examined the individual differences in people’s attitude to money and their impact. These papers typically analysed the correlations between financial attitudes and different demographic variables [18], personality variables and work and life experiences. The validity of MAS, however, was checked in several countries such as patterns in China, the United States, England and Mexico [7; 8; 18; 22; 28].

Our present study explains and supplements the Hungarian literature on financial attitude by examining the financial attitudes of the Hungarian students. It is significant to concentrate on the Hungarian students for two reasons. On the one hand, it is because in our country the altered market circumstances (socialist system versus market economy) and the accompanying value system changes cater for a dramatically new system of financial habits. On the other hand, we focus on

Hungarian students as it is obvious that their education, social standing etc. also influence our financial attitude but it is not clear how they are exactly interrelated. By taking the measures of the above-mentioned into consideration we decided that in this paper our attention is directed at gender differences (1), age (2), income relations (3), education (4) and their position in employment (5).

• II.    Literature review: measures and correlations

Several attempts have been made so far to measure and assess financial attitude and explore the correlations. In the following part a short summary is written about the most important results.

• II.1.    Development of measures.

Wernimount and Fritzpatrick [26] were trying to understand our relationship with money by identifying different factors. In their examination adjective pairs had to be assessed on a seven-grade scale and then dimensions were created in connection with opinion on money by means of factor analysis. Such dimensions are ‘ shameful failure ’ (the lack of money means failure or shame); ‘ neglecting it ’ (money is not important at all, it does not give pleasure and does not impress the environment); ‘ evil spirit ’... etc ... According to the results the work experience, gender and social-economic situation of the respondents affect the cognitive representation of money, i.e. how they perceive and regard money. The groups that had jobs positively assessed money and thought it was a desirable, important and useful thing while the unemployed had a negative image about money full of tension.

‘MAS’ (Money Attitude Scale) developed by Yamauchi and Templer [28] is the most frequently used measure in international literature to assess financial attitude. (The alpha value for the total MAS: 0.77; alpha values for the single factors (I–IV – see later: 0.80, 079, 0.73 and 0.69, respectively. The reliability of the test (5 weeks after the original data collection) was 0.88, 0.95, 0.92, 0.87, and 0.88 for the total MAS). Regarding the fact that one of its modified versions is also used in our examination, the other characteristics of MAS are also presented in details. The research of Yamauchi and Templer [28] is based primarily on the principles of Freud and neo-Freudian theories, which supposed three basic parts in the nature of financial attitude. They are Security, retention and power prestige. The authors made 62 such statements that reflect these 3 ranges and afterwards the items were assessed with the help of 300 volunteers by using a seven-grade Likert scale. Of the 62 statements finally a list of 29 items was selected by means of factor analysis. As a result, the following four items of the five categories below were isolated. The fifth factor was added later by Roberts and Sepulveda in their research [18].

Power – Prestige: according to the statements concerned money can be interpreted as a measure of power and success. The individuals who reach a high number of points in this factor regard money as an instrument of influencing/affecting others.

Retention-Time: items belonging here are primarily focused on financial planning and taking good care of money. Those with a high number of points plan their future and continuously control their current financial situation.

Mistrust: who reached a lot of points in this factor are insecure, suspicious and have doubts about themselves concerning money-related situations and the world of money.

Anxiety: who have high scores of this factor regard money as a source of anxiety/nervousness or something that can protect against anxiety.

Quality: the statements belonging here focus on buying good quality products/services. The individuals who scored high here can be characterised by the saying: ‘You get what you pay for’.

The scale of the authors was used by several researches in its original or modified form [10; 13; 16; 18]. Gresham and Fontenot unified the factor of mistrust and anxiety based on their examinations just as Andersen et al. [2] did so the power-prestige, quality and retention-time factors were retained only the anxiety and mistrust factors were merged. Anderson et al. also created the so-called ‘action-conscious/obsessed’ factor that was also used by Roberts and Shepulveda [18] in their research and we also applied it in our own. (The researchers disregarded several of the original 62 items and our research uses 28 items, too).

Furnham [7] developed such a list of items called ‘MBBS’ – Money Beliefs and Behaviour Scale (of 60 items, Likert-based) – that primarily assesses individual opinions on the correlation between efforts and financial well-being. The list of items was worked out on the basis of the results of Yamauchi and Templer [28], Goldberg and Lewis [9] and also Rubinstein [19]. The objective of Furnham by working out the scale was the following. (1–3): (1) Creating such a versatile, multi-purpose measure that can assess attitude to money and patterns of behaviour in Great Britain.

• (2)    Examining what kind of correlations there are between the different demographic and social/ employment characteristics and the people’s financial attitude and patterns of behaviour. (3) Examining what the consequences of people’s attitude and behaviour to money are. According to his results the following six clearly visible factors are seen in financial attitude: (1) Notoriety; (2) Power/Spending; (3) Retention; (4) Security/Caution; (5) Inaptitude; (6) Effort/ Ability. The empirical results reflect that the lack or presence of age, education and protestant labour ethics ¹ are the factors that differentiate attitude to money. In the analysed sample of Furnham the elderly were more concerned about their future in its financial sense and scored higher in the Retention factor. The young, however, tended to interpret money as a source of power and did not aim Security. Men were more obsessed by money and women showed a more ‘safety-oriented’ attitude. Those with a lower level of education and qualification were rather obsessed by money. The individuals with a secondary school education were more concerned with Security than those with very high or very low level of education.

Gresham and Fontenot [10] examined the differences between genders concerning the management of money. By justifying MAS they also identified four factors: Power/Prestige, MistrustAnxiety, Retention-Time and Quality . The differences by gender were prevalent while examining all the factors, especially in the Retention/Time factor. The results show that women are more worried about money than their male counterparts and also they are more interested in the quality of the purchased goods or services. Medina et al. [15] in their cross-cultural study compared the attitudes to money of the Mexican-Americans and the Anglo-Americans. The same four factors could be identified as Gresham and Fontenot [10], which also justifies the validity of MAS. The

Mexican-Americans reached lower values in ‘Retention-Time’ and ‘Quality’ categories. Baker and Hagedorn [5] examined the attitude to money on an adult sample by using MAS and MBBS ( n = 200). The internal and predictive validity of both tests were examined. The results stress that the four factors of MAS, i.e. power/prestige, mistrust, anxiety and retention-time are the most important statistically proven dimensions of financial attitude. (The factors of MBBS were not justified.) The authors created such a list of items from MAS and MBBS (which slightly differs from MAS) where all the items can be classified to any of the four factors mentioned above.

Tang and Gilbert [23] invented MES – Money Ethic Scale. Due to the triple nature of the attitude the authors think that attitude to money has an emotional component (good, evil), a cognitive component (how it can be related to results, respect and freedom) and also a behavioural component. Such a 30-item list of simple statements was created that could be centred on 5 factors. This scale proved to be very reliable. The authors proved that the income of parents, education/qualification, their social standing, beliefs and financial habits do have an impact on the financial attitudes of their children. Lim and Teo [13] invented such a scale with the help of which the gender differences could be identified. The scale consists of 34 items that can be classified into eight different dimensions. 1. Obsession, 2. Power, 3. Budget, 4. Performance, 5. Assessment, 6. Anxiety, 7. Retention (saving), 8. Frugality. The only detectably significant difference between the two genders was in the ‘Assessment’ factor, i.e. men would rather use money to compare their financial situations with the others’.

• II.2.    Correlations between financial attitude and demographic variables.

The following part presents such results that reflect the correlations between the demographic variables and financial attitude on the basis of MA. Moreover, other research results are also described that were based on other measures.

Gender and financial attitude . Gresham and Fontenot [10] researched the prominent gender difference in using money while relying on MAS. While analysing all the factors differences were outlined, especially in the ‘Retention-Time’ factor. The researchers concluded that men assign more importance to money than women (a similar result was gained earlier by Wernimont and Fitzpatrick in 1972 and Lynn in 1991). According to Furnham the explanation lies in the fact that men are more competitive. Men regard money as an instrument of influencing or pressurising others [2; 4; 10; 13; 17; 20;

23; 27]. Women are more conservative and manage money more carefully. They are less money conscious in financial planning (retention-time factor) but would rather bargain or ‘hunt’ for special opportunities [7]. The results of Gresham and Fontenot [10] show that women are more concerned about money and are more interested in the quality of the purchased goods or services. The empiric research of Yablonsky [27] corresponds with it, i.e. men would rather show confidence in financial matters than women but at the same time, women more frequently prepare financial plans [22] and it is them who most bargain hunt and look for good opportunities [17].

Age and financial attitude. According to the research of Furnham et al. [7] the young use (or would like to use) money to influence others (powerprestige factor) and less thrifty (retention-time factor). The research results of Tang [23] state that the older we get, the more likely we make financial plans for the future and we tend to regard money as a symbol of success (power-.prestige factor), which partly contradicts Furnham’s results. The examinations of Tang and Gilbert [23] justified that managing money properly correlates with age and gender. The elderly usually manage money more carefully and it is usually them who have lower level of income, higher selfesteem and lower stress level in connection with money. The individuals who have a strong positive attitude to money assign a great economic and political, but not religious value to money – stated Tang and Gilbert. Furthermore, people with a high level of income tend to think that money reflects success and it is not ‘evil’ while the young would rather have a negative attitude to money. As there is only a slight difference in age in our small sample of students it is expected that there will be significant differences in the financial attitudes of undergraduate full-time students (Year 1, too young) and elder (primarily correspondent) student as growing older also means taking greater financial responsibilities.

Education and financial attitude . According to the results of Furnham [7] and Lynn [14] those with lower level of education are afraid of money and would rather see it as an instrument of influencing (power-prestige factor). The better educated ones would rather seek special offers and good financial opportunities [8]. Differences in the students’ sample are expected in line with the results above depending on whether the students have a certificate of secondary education or a previous degree.

Work experience and financial attitude. According to the results of Wernimont and Fritzpatrick [26] those with a job have a positive image about money while those unemployed are more stressful and unhappy when thinking about money. This corresponds with the results of Bailey and Gustafson [4] as well as Bailey and Lowm who found that the unemployed and the students living in a student hostel would rather go through ‘dissatisfaction’ when it comes to money. The results of Tang and Gilbert [23] prove that the intellectual workers tend to believe that money is naturally good. An interesting issue for us was to what extent the direction of studies (study programmes, majors) influences attitude to money. It is natural as we grow older that we also have more work experience so on grounds of more time spent at work and not because of age correspondent students are expected to appreciate money (they save more) more than the students who take the others’ support for granted.

By considering the research results presented, our personaly experience and the possible outcomes our empirical research is based on the following hypotheses (Table 1).

• III.    Presenting the sample and methodology

  • III.1.    The sample.

Our analysis relies on the questionnaires filled in by 305 students studying at the Faculty of Economics of Szent István University (Table 2–6). The questionnaire was anonymous and its printed or paper-based form could be filled in voluntarily. The participants were not given any incentives or bonuses.

Regarding the gender ratio of the population the sample was not representative but taking the proportion of the gender of the university students, and especially the students of Arts, into account it was a bit closer to the proportion of Hungarian students. Three-quarters (73.4 %) of the respondents were female and males (26.6 %) made up one-quarter of the sample. (In 2011 43.43 % males and 56.57 % females applied for higher education [6]. Care was also taken that students of business (165) and non-business (140) trainings should be proportionally represented (50 %–50 %) and also the sample should be evenly distributed in terms of age.

Table 1

Research hypotheses

Hypothesis 1	In the students’ sample men are more power-and prestige-oriented than women
Hypothesis 2	As we grow older, the ‘saving-self-supporting’ attitude is also getting stronger
Hypothesis 3	Higher levels of education go together with higher ‘saving-self-supporting’ attitude
Hypothesis 4	The amount of income/salary/money given by the parents correlates with attitude to money
Hypothesis 5	The students’ work experience or lack of it is decisive on financial attitude
Hypothesis 6	The selected study programme/profession and knowledge of the students correlate with financial attitude

Table 2

Breakdown of the sample by form of training

Age	Full-time	Correspondent	Total
21 or younger	126 (61.5 %)	3 (3.0 %)	129 (42.4 %)
22–26	76 (37.1 %)	26 (26.3 %)	102 (33.6 %)
27–34	2 (1.0 %)	46 (46.5 %)	48 (15.8 %)
35 or older	1 (0.5 %)	24 (24.2 %)	25 (8.2 %)
	205 (100.1)	99 (100.0)	304 * (100.0)

Note. * One student in his ’20s did not indicate it.

Table 3

Breakdown of the sample by study programme

Study programme	Person	%
Human resource management (bus)	64	21.0
Economics and management (bus)	56	18.4
Finance and accountancy (bus)	35	11.5
Commerce and marketing (bus)	10	3.3
Communication and Media (non bus)	29	9.5
Tourism and catering (non bus)	33	10.8
Management and business administration (bus)	32	10.5
Other (not from FESS)	16	5.2
Ddi not indicate it	30	9.8
Total: 165 business + 140 non-business students	305	100.0

Note. (bus) stands for students of business faculties.

Table 4

Breakdown of respondents by marital status

Marital status	Person	%
Single	29	9.5
Common household with parents	148	48.5
In relationship with common household	64	21.0
In relationship with separate household	29	9.5
In lodgings or student hostels with many others	31	10.2
Other	4	1.3
Total	305	100.0

Table 5

The sources of income of the respondents by marital status

Indicators	Dependent on parents	Dependent on parents and work	Have casual and/or permanent work	Live on bene-fit/contribution /student grant	Total
Single	3 (10.3 %)	1 (3.4 %)	24 (82.8 %)	1 (3.4 %)	29 (100.0 %)
Common household with parents	73 (49.3 %)	27 (18.2 %)	43 (29.1 %)	5 (3.4 %)	148 (100.0 %)
In relationship with common household	1 (1.6 %)	3 (4.7 %)	51 (79.7 %)	9 (14.1 %)	64 (100.0 %)
In relationship with separate household	5 (17.2 %)	1 (3.4 %)	20 (69.0 %)	3 (10.3 %)	29 (100.0 %)
In lodgings or student hostel	13 (41.9 %)	12 (38.7 %)	6 (19.4 %)	0	31 (100.0 %)
Other	0	1 (25.0 %)	3 (75.0 %)	0	4 (100.0 %)
Total	95 (31.1 %)	45 (14.8 %)	147 (48.2 %)	18 (5.9 %)	305 (100,0 %)

Table 6

The sources of income of the respondents by form of training *

Indicators	Full-time	Correspondent	Total
Dependent on parents	92 (45 %)	3 (3 %)	95 (31 %)
Dependent on parents and work	45 (22 %)	0	45 (15 %)
Have casual and / or permanent work	58 (28 %)	88 (89 %)	146 (48 %)
Live on benefit / contribution/student grant	10 (5 %)	8 (8 %)	18 (6 %)
Total	205 (100 %)	99 (100 %)	304 (100,0)

Note. * 12 of the full-time students have their own business while 6 of the correspondent students also own an enterprise.

It can be seen that almost half of the sample (49 %) live with their parents in a common household so they are free from the burden of taking care of themselves and their families financially.

Data show that almost one-third of the respondents manages money not earned by them and entirely depend on the parents. There are a lot of them (15 %) who work in addition to receiving money from the parents and approximately half of the sample are totally self-catering and have independent activities from where they earn money. It can be seen that a significant part of those living on their own or in relationship are obviously self-supporting. From the breakdown by study programme (Table 6) it can also be concluded that although nearly half (45 %) of the full-time students are exclusively supported by their parents, the others can contribute by working on their own or they are entirely self-supporting while a great part of the correspondent students (89 %) are obviously characterised by self-support.

• III.2.    Methods.

Our instrument applied in the research was a questionnaire that covers several topics. However, we only concentrate on the results on the correlations outlined. The questionnaire used one of the types of ‘MAS’ (Appendix 1), which, as mentioned beforehand, proved to be a suitable measure. It was also important for the students to analyse and understand the certain statements which should be adequate and life-like. That is why we also modified the original list of items. Our basis was the item list of Roberts and Shepulveda [18] mentioned. We kept Factor 1, 2, 3 and 4 but the ‘quality’ factor was renamed ‘bargain hunter/money conscious’ that describes the content better in our mind. (We also regarded it was important to make a difference between budget conscious and money consciousness Under the first term we mean keeping to the budget at all times while the latter one refers to the constant willingness of reducing costs. In our opinion the presence of both of them results in ‘financial consciousness’). The second half of item 12 was deleted so that it should not contain dubious statements and also item 16 was removed due to its general content and one more item was created in the last factor: ‘I usually bargain-hunt’.

As the Hungarian word-for-word translation of the names of MAS factors by Roberts and Shepulveda [18] did not express the original meaning at three points, they were partly modified / supplemented to be understandable. Parts that require content similarity, several translators were working on the same text and the results gained were harmonised. Three specialists worked on translation (from English into Hungarian and from Hungarian into English). In the case of the 28 items agreement or disagreement could be expressed by a 7-grade scale where 1 = not at all agree, 7 = entirely agree. Filling in the questionnaire and the item list took approximately 15 minutes.

• IV.    Presenting the results

Our most important analyses comprise two areas: 1. the factor analysis of MAS items; 2. comparing the averages of demographic variables (gender, age, education, work experience, study programme) and the MAS factors, i.e. in which cases the impact of single demographic values can be regarded significant regarding different factors by means of variance analysis. The significance values gained are presented in the last line.

As our factor analysis produced similar results to the authors mentioned before their system served as the basis for analysis when classifying the items. (The following part outlines our term in the evaluation and as a result of our factor analysis).

MAS I: Power-Prestige-oriented.

MAS II: Retention/Time → MAS II: Thrifty/ Self supporting.

MAS III: Mistrust → MAS III: Insecurity/Mistrust.

MAS IV: Anxiety → MAS IV: Anxious, worried.

MAS V: Obsession → MAS V: Bargain hunter, money conscious.

• IV.1. The factor analysis of MAS scale.

The objective of the factor analysis was to find out whether a similar factor structure could be identified on the basis of the responses, i.e. whether the same, common latent structures stand in the background of the 28 variables on financial attitude as described by Roberts and Shepulveda [18]. Factor analysis was carried out by PASW Statistics 18 (SPSS) software. All the 28 variables in the analysis were proved to be suitable for factor analysis based both on KMO indicators and the Bartlett test as they showed enough correlation. The nil hypothesis of the Bartlett test is that the examined variables do not correlate. It can be seen that this nil hypothesis can be rejected based on the gained level of significance. When examining the Correlation matrix and Anti-Image matrix, 96 % of the correlation values between the variables at a 0.05 significance level can be regarded as significant. The values of the diagonal parts (MSA) of the AntiImage correlation matrix were between 0.749 and 0.925. There were not so less correlated variables whose omission could have been justified. The Maximum Likelihood extraction method and Varimax rotation were applied to determine the factors. Pairwise method was used to manage the missing data.

In the model consisting of all the variables first of all a model of 6 factors were created but isolating and interpreting factors were not proper either on the basis of the fitting of the model or factor weight. The scree plot of eigenvalues shows a four-factor model when counting the points above the breakage. This is in contrast with the eigenvalue indicator, which is not a problem if we take both of them into consideration simultaneously; the 5-factor structure is adequate.

Afterwards, this 5-factor model was refined but to gain proper fitting, some parts had to be cancelled from the procedure. The basic foundations were given by examining the communality of the variables (the information content of a variable that is not included in the other variables) and their correlations. It is the communality values that show which variables to blame for bad fitting. If the communality of a variable is low (<0.25), it does not make any sense to include it in the factor analysis. A further possibility is leaving the variables connected to many factors, i.e. badly interpretable ones from the analysis. According to general rule, a variable is regarded to be part of a factor if 1) its factor weight exceeds 0.025 in the case of only one factor; 2) its factor weight is greater on one factor than twice the factor weight of any other factors. By following these principles the result is a 5-factor model based on 20 variables whose fitting was acceptable and its explanatory power is 49 % and the factors gained are proportionate based on their eigenvalues (Table 7).

Table 7

Goodness’s fitting test

1Chi-Square	df	Sig.
142.355	100	0.003

Of the 28 items 20 were included in the model and all the 20 variables could obviously be explained and the classification of the single variables into factors corresponds with literature. The factor weight matrix of the model is as follows (Table 8).

Table 8

	Factor
	I	II	III	IV	V
MAS 1 I ofte n b u y so m eth in g ju s t to im p res s o th e rs .	,693	-,006	,051	,032	,057
MAS 2 P eop l e s a y I ove re m p h a size m o ne y.	,553	,042	,145	,194	,1 1 4
MAS3 I g uess m oney is the s ign of s u ccess	,549	-,003	,078	,222	,080
MAS 4 I h ave n i ce/e xp e n s ive th i ng s to in fl u e n ce th e o th e rs	,796	-,023	-,005	-,005	,038
MAS 5 Alth o ug h peo p le s h ou ld b e ju d g ed by actio ns , I a m m ore inte res te d i n h ow m u ch m o n ey th e y h ave	,591	-,025	-,008	,041	,008
MAS 7 S o m eti m e s I b o a s t ho w m uch m o n ey I m ad e .	,482	,116	,074	-,032	-,020
MAS 8 S o m eti m e s I n oti ce I s h o w m o re re s p e ct fo r p e op l e w h o have m o re m o n ey tha n m e .	,520	,057	,058	,172	,1 1 6
MAS 1 0 I p u t as i d e for fu tu re exp e ns e s .	,009	,754	,047	-,003	,092
MAS 1 1 I h a ve fin a n cia l p l an s fo r th e fu ture .	,046	,604	,022	-,00 1	,037
MAS 1 2 I h a ve m o n ey ava il ab l e i n the ca s e o f a n oth e r wo rld cris is .	,159	,736	-,076	-,1 03	,020
MAS 1 3 I m a ke s a vi n g s fo r m y o ld ag e/th e u ne xp e cte d .	-,069	,745	,031	-,002	-,008
MAS 1 7 W h e n I b ou g h t so m e th ing , it dis tu rb s m e afte rw a rd s how m uch it cost.	,135	,023	,728	,152	,1 68
MAS 1 8 I h e sitate to s p e n d e ve n w h e n it co m es to b as i c necess ities .	,005	,087	,61 8	,227	,1 60
MAS 1 9 Afte r b u yi n g s o m e th i ng I w on d e r wh e re I co u ld ha ve bought it cheaper.	,160	-,077	,663	,195	,242
MAS 21 I a m overwh e lm ed by proble m s w h e n it co m es to m oney.	,127	-,126	,260	,642	,065
MAS 22 I a m typ i cal ly n e rvo u s if I d o n ot h a ve e n o u g h m o n e y.	,220	,036	,212	,714	,1 02
MAS 23 I a m co n ce re n e d a b o u t m y fi n a ncia l in s e cu ri ty.	,095	-,035	,131	,796	,1 4 1
MAS 25 I a m a n g ry if I m is s a b a rga in .	,194	,032	,170	,116	,557
MAS 27 It d i s tu rb s m e w h en I d is co ve r I co u ld ha ve b o ug h t som eth ing chea pe r els ewhere .	,020	-,01 8	,261	,195	,638
MAS 28 I ba rga in hunt regu la rly.	,046	,132	,1 1 5	,004	,787

Factor weight matrix

An index per each respondent was generated to measure the strength of the MAS factors from the averages of the variables of the single factors (MAS I – MAS V values) and these values were used for summarising from different demographic points of view.

• IV.2. Correlations between the MAS factors and demographic variables.

Variance analysis (ANOVA) was used to examine the correlations between the demographic variables and MAS factors. As the demographic variables are primarily nominal variables and only the indexes calculated on MAS I – MAS V factors represent a higher level of measuring, ANOVA (F-trial) is the primary method applicable to examine the significance of their correlations [3]. In addition, Eta association indicator was also applied to measure the strength of the relationship, which indicates the strength of the stochastic relationship between two variables. In the case of each factor we considered important to present the results even if the F-trial between two variables did not show significant correlation. On the one hand, as the lack of correlation can also have important information and on the other hand, it frequently occurs that although in general there is no significant relation between two variables, distinctive differences can lie in the single values of the independent variable. It means that if the significant impact of a demographic variable on the single factor cannot be assessed, the consequence is not necessarily that there would be a substantial difference between the indices of any two attributes and by comparing them, further important statements could be made.

Our results justified the first hypothesis (Table 9). The variance analysis in the case of three factors (MAS I, MAS IV, MAS V) shows that gender has an influence on the single factors and in the case of MAS II and MAS III factors there is a slight difference between the responses of the two genders. According to our results for men money rather means source of power and prestige and it is typical of them, although the difference is slight, that they make more savings/keep money than women. Women are more money-conscious ‘bargain hunters’ and they are more anxious about money and also, even to a slight extent, it is more typical of them to be uncertain and not sure in financial matters.

Based on the results of the F-trial in the case of MAS II and MAS III variables the age categories significantly differ (at 97 % significance level and 95 % significance treshold, respectively). In the case of the other factors it cannot be experienced that the changing effect of age would have a significant effect. This can be due to the relative age homogenity of the sample but despite of it, even in this case there are interpretable correlations between the age of the respondents and the money attitude factors.

The younger students (under 35) attach money to the idea of power and prestige (MAS I) , they are more mistrustful and insecure as thy do not feel themselves at home in the world of money (MAS III). This is the strongest especially for the youngest generation (under 22). At the same time, they are more money-conscious and look for discount sales (MAS V) although they are less anxious than the elderly. However, the values are in most cases 4, i.e. a neutral value or below, which means that the average of reponses are in the neutral or not typical range. In contrast, the old tend to save more for their future problems (MAS II). It is most typical for those aged between 27 and 34 but the average of responses in all age groups is in a typical range, i.e. the respondents are likely to be savers and self supporters.

Table 9

The average values of MAS factors by gender

Report

Gender (M ale/Fem ale)		M AS-I power-pre stige	MAS II thrifty, self supporting	MAS III m istrustfu l, insecure	M AS IV anxious	MAS V m oney conscious bargain hu nte r
Fem ale	Mean	2,50	4,40	3,79	4,14	3,73
N=224	Std . D eviatio n	0,99	1 ,49	1 ,39	1,58	1,43
Male	Mean	2,86	4,65	3,57	3,81	3,12
N=81	Std . D eviatio n	1,08	1 ,20	1 ,1 4	1,32	1,26
Total	Mean	2,59	4,46	3,73	4,05	3,57
N=305	Std . D eviatio n	1,03	1 ,42	1 ,33	1,52	1,41
ANOVA	Sig.	0,01	0,18	0,21	0,10	0,00

The results show that people above 35 worry more than the younger generations (MAS IV) and rarely show bargain hunter and meony conscious behavioural patterns although the scattered responses refer to significant individual differences in both cases while uncertainty and insecurity show a gradually decreasing tendency as growing old (Mistrust is less typical. i.e. the mistrustful financial and consumer attitude will be shifted to conscience.) All this justifies the results of the previously mentioned researches on adult samples.

The correlations above are of weak significance on Hungarian students. In terms of the very proximate average values the youngest, also in our sample assessed the questions of the power-prestige factors

(with only 0.09 dfference from the average) but they proved to be the least willing to save and self-support (the difference from the average is 0.16 only). However, thre anxiety over money matters is 0.29 points stronger than the average in the case of the over 35 group (nealry 10 % of the sample). The willingness to make savings was the strongest for those aged between 27 and 34.

The table below (Table 10) presents the average values of MAS factors by age and gender. It shows that the older men are, the less interest they take in special offers while in the case of women such tendency could not be experienced. Men do not want to curb on spending by rationalising consumption, rather, they would make

Table 10

Report

age	g e n d e r (m a le /fe m a le )		M AS-I pow e r-prestige	M AS II thrifty, selfsupporting	MAS III m istrustful, insecure	MAS IV anxious	MAS V m oneyconscious, bargain h unte r
under 22	fe m a le (N = 1 0 0 )	Mean	2,57	4,23	3,90	4,03	3,66
		Std . D e via tio n	1,00	1,37	1 ,43	1,56	1,41
	male(N=29)	Mean	3,07	4,53	4,14	4,01	3,58
		Std . D e via tio n	0,90	1,26	1 ,07	1,22	1,18
22-26	fe m a le (N = 6 9 )	Mean	2,40	4,36	3,77	4,13	3,79
		Std . D e via tio n	0,86	1,60	1,37	1,55	1,41
	male (N=34)	Mean	2,87	4,54	3,41	3,76	3,15
		Std . D e via tio n	1 ,1 7	1 ,1 5	1 ,1 6	1,32	1,23
27-34	fe m a le (N = 3 7 )	Mean	2,59	4,92	3,66	4,18	3,82
		Std . D e via tio n	1 ,1 2	1,40	1,25	1,61	1,36
	male (N=1 1 )	Mean	2,82	5,27	3,00	3,61	2,68
		Std . D e via tio n	1,35	1 ,1 6	0,73	1,38	1,19
o ver 3 5	fe m a le (N = 1 8 )	Mean	2,27	4,40	3,50	4,65	3,75
		Std . D e via tio n	1 ,1 6	1,72	1 ,58	1,83	1,81
	male (N=7)	Mean	2,03	4,64	2,89	3,54	1,75
		Std . D e via tio n	0,57	1,21	0,92	1,77	0,58
Total	fe m a le (N =2 24 )	Mean	2,50	4,40	3,79	4,14	3,73
		Std . D e via tio n	0,99	1,49	1 ,39	1,58	1,43
	male (N=81 )	Mean	2,86	4,65	3,57	3,81	3,12
		Std . D e via tio n	1,08	1,20	1 ,1 4	1,32	1,26

how much money they live on		MAS I powerprestige	MAS II thrifty, selfsupporting	MAS III mistrustful, insecure	MAS IV anxious	MAS V money conscious bargain hunter
less than 5000Ft	mean,	2.57	4.17	3.86	3.99	3.62
N=152	deviation	0.94	1.41	1.37	1.49	1.38
5000-10000Ft	mean,	2.72	4.59	3.87	4.34	3.73
N=64	deviation	1.12	1.26	1.29	1.43	1.37
100000-200000Ft	mean,	2.63	4.83	3.55	3.99	3.52
N=51	deviation	1.08	1.54	1.29	1.61	1.51
more than 200000Ft	mean,	2.44	4.97	3.30	3.89	3.21
N=37	deviation	1.16	1.30	1.20	1.70	1.39
Total	mean,	2.60	4.46	3.74	4.05	3.58
N=304	deviation	1.03	1.42	1.33	1.53	1.41
ANOVA	Sig.	0.614	0.001	0.076	0.393	0.313
	Eta	0.077	0.224	0.150	0.100	0.109
	Eta Sq.	0.006	0.050	0.023	0.010	0.012

The average factor values of MAS by age and gender

savings, support themselves and at all ages they are more characterised by thriftiness than women. While growing older, both men and women are becoming more self-confident but in the case of men the tendency is stronger and the differences are greater. In the case of men a similar decrease of anxiety although to a smaller extent could be experienced while women tend to be more anxious when growing older.

The third hypothesis was accepted. The basis of our hypothesis was that gaining knoweldge goes together with more consciousness so it also affects a thrifty and self-supporting attitude (MAS II). As it can be seen from Table 11 it is obvious that a higher level of education results in a significant rise in making savings and self support and also the deviation of the respondents is slighter. The mean of responses falls into the rather typical category even in the case of those with a general certificate from secondary school, i.e. willingness to save is prevalent but the greater deviation indicates a greater difference among the responses. The variance analysis shows a significant correlation between the categories of qualification and MAS II factor.

By raising the level of qualification only the values of Factor II show a continuous increase while the values of Factor V go to the opposite direction. The latter one suggests that special offers and sales mainly affect the less educated.

The statistical acceptance of the fourth hypothesis shows interesting results. The following was asked about the amount of income: ‘How much do you live on per month?’ (Just to remind the reader, although 67 % of the sample was full-time students, 45 % of them work temporarily or regularly. Three percent of the correspondent students making up 33 % of the sample rely exclusively on family support.) When evaluating the responses four categories were created (Table 12). By increasing the amount from which students can make a living a continuous and simultaneous increase

Table 11

Mean of MAS factor values by qualification

Education (qualification)		MAS I powerprestige	MAS II thrifty, selfsupporting	MAS III mistrustful, insecure	MAS IV anxious	MAS V money conscious bargain hunter
General certificate from	mean,	2.59	4.37	3.84	4.06	3.63
secondary school N = 251	deviation	1.00	1.44	1.34	1.48	1.40
College/BA/Bsc	mean,	2.52	4.73	3.10	3.87	3.31
N = 42	deviation	1.10	1.28	1.14	1.66	1.36
University/MA/Msc	mean,	2.90	5.46	3.73	4.38	3.35
N = 51	deviation	1.39	1.05	1.15	1.86	1.75
Total	mean,	2.59	4.46	3.73	4.05	3.57
N = 305	deviation	1.03	1.42	1.33	1.52	1.41
ANOVA	Sig.	0.614	0.001	0.00	0.56	0.35

Table 12

Mean of MAS factor values by source of income

How much money they live on		MAS I powerprestige	MAS II thrifty, selfsupporting	MAS III mistrustful, insecure	MAS IV anxious	MAS V money conscious bargain hunter
Less than 5000Ft	mean,	2.57	4.17	3.86	3.99	3.62
N = 152	deviation	0.94	1.41	1.37	1.49	1.38
5000-10000Ft	mean,	2.72	4.59	3.87	4.34	3.73
N = 64	deviation	1.12	1.26	1.29	1.43	1.37
100000-200000Ft	mean,	2.63	4.83	3.55	3.99	3.52
N = 51	deviation	1.08	1.54	1.29	1.61	1.51
More than 200000Ft	mean,	2.44	4.97	3.30	3.89	3.21
N = 37	deviation	1.16	1.30	1.20	1.70	1.39
Total	mean,	2.60	4.46	3.74	4.05	3.58
N = 304	deviation	1.03	1.42	1.33	1.53	1.41
ANOVA	Sig.	0.614	0.001	0.076	0.393	0.313
	Eta	0.077	0.224	0.150	0.100	0.109
	Eta Squared	0.006	0.050	0.023	0.010	0.012

(of 0.8!) could only be experienced in the values of MAS II factor. The more money they have, the greater willingness for making savings and selfsupport is shown and their feeling of mistrust and insecurity reduces. The result of the T-trial shows that in the case of MAS II and MAS II factors the single income categories significantly differ (if we accept the 92 % significance level for MAS II) while other factors do not, so the income category has a significant impact both on MAS I and MAS II factors.

The values of the indicator of explanatory power (Eta) are not too high even in significant cases when there is a slight stochastic correlation between the two variables (categories of incoe and MAS II and MAS III factors). In the case of MAS II belonging to a certain income category explains 5 % of the mean deviation of factors while it is 3 % in the case of MAS III. However, we must not forget that the smaller or bigger amount of money do not necessarily signal the standard of the respondent’s living. The amount does not only refer to income by working but also include the pocket money given by the parents in additon to salaries. Nevertheless, we can suppose that those who are self supporting and work hard for money also ‘appreciate’ money more and try to use it cleverly with a greater willingness to make savings. At the same time, however, we have to note that in many cases being a full-time student does not mean carefree student life as it used to be because approximately half of the students pay a tuition fee and this proportion is expected to increase in the forthcoming years. Only 31 percent of the entire sample stated that they

‘depend on their parents’, which held true only 45 % of the full-time students.

Our fifth hypothesis is centred around the statement according to which ‘ the students’ work experience or lack of it is decisive on their financial attitude ’(Table 13). The varience analysis (ANOVA) does not show significant correlations between anxiety and bargain hunting as well as the work experience of the respondents not even from the aspect of power-authority and trust-. The results show that the respondents who work regularly or temporarily are more anxious than those in other categories and the respondents who are entirely or partly dependent on their parents can be described by a lower anxiety level, obviously. However, the mean of MAS II factor shows a significant correlation with the source of income and also with the existing or lacking work experience. Each grade of the scale starting from the status of dependent ranging to selfsupport (and financing studies) have a higher score value in the thrifty-self supporting factor. A growth of 0.78 can be experienced between the two extreme values of MAS II. However, the correlation here is still weakowever, the correelation is still wekaHowe: Eta=0.25 and Eta Squared=0.06, i.e. belonging to the categories above explains 6 % of factor mean spread. To sum up, it can be stated that the source of income has a greater explanatory power than the amount of income.

The MAS factors, as mentioned before, indicate a state of mind and psychological attitude and not level of knowledge. That is why it is interesting to

Table 13

Mean of MAS factor values by work experience

Report

s ource of income (livin g) M AS-I powe r-pre stige M AS II thrifty, self su po prting MAS III m istrustful, in sec ure MAS IV anxious MAS V money co nsc io us ba rgain hunter Szü lők ta rtjá k el N=95 Mean Std . D eviation 2 ,6 2 1 ,0 1 4 ,0 2 1 ,4 2 3,79 1,36 3,88 1,49 3,63 1,36 b e n efit, a l ow a n c e , s tu d e n t grant, cred it N=18 Mean Std . D eviation 2 ,4 0 0 ,6 0 4 ,1 9 1 ,5 6 3,61 1,46 4,04 1,67 3,15 1,23 dep en den t o n paren ts and also work     N=45 Mean Std . D eviation 2 ,6 3 1 ,0 2 4 ,4 0 1 ,2 7 3,78 1,33 3,87 1,41 3,76 1,47 w o rk te m p o ra rily/re g u l a rly N=1 47 Mean Std . D eviation 2 ,5 9 1 ,0 9 4 ,8 0 1 ,3 7 3,69 1,31 4,21 1,55 3,53 1,45 Tota l N=305 Mean Std . D eviation 2 ,5 9 1 ,0 3 4 ,4 6 1 ,4 2 3,73 1,33 4,05 1,52 3,57 1,41 ANOVA Sig. 0,856 0,000 0,915 0,331 0,438 make comparisons between the factors of students from different study programmes. Our sixth hypothesis was drafted as follows: ‘The selected study programme/profession and knowledge of the students correlate with financial attitude’. Of course, we were most interested in the average score of the students of Finance and accounting and Economics and management, i.e. what special features they have in comparison with the students of other disciplines. The data of Table 13 show that those who are ‘mistrustful’ and ‘anxious’ apply mostly for Finance and accounting and Economics and management (or, at least, they become like that while studying there). The average is the highest in these two factors relative to the others. The students of Finance following those of Commerce and marketing lead the ‘prestige-hunter’ group (2.72 and 3.08) respectively, and they are the first in the category of the ‘anxious’ with the students of Economics and management (4.15). In the saving-self-supporting factor which is the most interesting for us the students of both study programmes show median values, and the students of finance even show lower values than the average. They are overtaken by the students of Management and leadership (5.00) and also by the Human resource managers (4.72) (Table 14).

It seems that finance orientation and special knowledge do not assist the everyday, ‘conscious use of money’ (in the MAS II factor the students of Finance ranked the fifth and the students of Economics and management are the fourth). It can be concluded that the attitude to money is not primarily shaped by professional knowledge, rather, a kind of mental attitude is decisive. The students of Management and leadership and Human resources are thriftier and seem to worry less than the students of Finance or Economics and management. Regarding thrift and self-support the master students of Management and leadership are prominent but at the same time, they are less power and prestige-oriented. It can be explained by the fact that they are older being master students. The impact of the study programmes on MAS factors can only be experienced in MAS II by variance analysis (at a level of significance of 98 %).

Our final analysis examines the impact of some further variables in addition to the demographic ones on MAS factors that are also relevant for money matters. We considered how many value keeping or value forming forms the respondents keep their savings and how it is correlated with MAS factors. We thought that the diversity of savings forms signals the consciousness level of using money. We wondered if the respondents strive to possess other money (profit) accumulating forms (shares, stocks, investments etc.) in addition to making use of the

Mean values of MAS factors by study programme

Table 14

Report

s tu dy p r og ra m m e MAS-I powe r-p restige M AS II t hr ifty,s e lf-s up po rting MAS III m istru stful, insecure MAS IV a nx ious MAS V moeny conscious, bargain hunter Hu m an resources       N=64 Mean 2,53 4 ,7 2 3,77 3,98 3,30 Std . Deviation 1,04 1 ,38 1 ,20 1,37 1,26 Econ om ics and managem ent Mean 2,61 4 ,5 3 4,04 4,15 3,93 N=56 Std . Deviation 0,92 1 ,36 1 ,14 1,49 1,36 Fina nce a nd a ccou nta ncy Mean 2,72 4 ,4 6 3,89 4,15 3,67 N=35 Std . Deviation 1,09 1 ,40 1 ,74 1,71 1,71 C o m m u n ica tio n a n d m e d ia Mean 2,48 3 ,82 3,85 3,99 3,41 N=29 Std . Deviation 0,90 1 ,76 1 ,54 1,52 1,65 Tourism a nd catering Mean 2,45 4 ,3 1 3,65 3,95 3,51 N=33 Std . Deviation 0,92 1 ,34 1 ,44 1,63 1,20 Managem ent a nd leadership Mean 2,28 5 ,0 0 3,31 3,95 3,43 MsC N=32 Std . Deviation 1,02 1 ,25 1 ,17 1,66 1,40 Co m m erce an d m a rketing Mean 3,08 3 ,67 3,42 3,93 3,78 N=10 Std . Deviation 0,97 1 ,2 1 0,87 1,18 1,00 othe r (n ot FES S)            N = 1 6 Mean 2,68 4 ,54 3,31 4,06 3,22 Std . Deviation 1,32 1 ,03 1 ,50 1,52 1,32 To ta l Mean 2,55 4 ,49 3,74 4,03 3,54 N=275 Std . Deviation 1,01 1 ,4 1 1 ,35 1,51 1,40 ANOVA Sig 0,427 0,019 0,242 0,997 0 ,3 15 value saving function of money (real estate, fixed-rate savings account etc.). The results are presented by Table 15.

In the MAS II factor the difference between the two extreme values is significant (3.46). While obviously the mean of the responses of those without savings is below level 4 of indifference (showing towards disagreement with savings), in all the cases of those with savings the average is above 4, which means their approval of making savings. The increasing number of savings forms results in higher MAS II values and the deviation of the responses is slighter. There is significant correlation between the number of savings forms and MAS II factor and this relationship is of medium strength. Savings forms explain 10 % of MAS II means. An opposite tendency (although not a significant correlation) can be experienced in terms of anxiety (MAS IV),as the higher the number of savings forms is, the lower the anxiety level (only the two types of savings are the odd-one out). For those who do not make savings or only have one type anxiety is neutral and shows values above 4 (rather anxious) while in the case of the others the values under 4 indicates the attitude of those who would rather not worry.

This result of ours convinced us that our MAS II factor, which has been regarded the most important one so far, illustrates not only mental attitude but also reality and our behaviour in practice and actions well. The savings diversity termed as the levels of savings and investments, or ‘depositors’ career’ in financial professional jargon went together with thrifty, selfsupporting mentality.

• V.    Discussion

Our results show similar correlations between the demographic characteristics of the respondents and their attitude to money like the results in international literature. It seems that the young are more likely to regard money as an instrument of power and influence. The same attitude intensifies among men while in the case of women anxiety and saving (money-conscious bargain hunter) are prevalent at a very young age. Furthermore, in contrast with international findings our study shows that the more money students have, the more willing they are to save and self-support and also their feeling of mistrust and insecurity is reduced. This was concluded on the basis of a relatively low level of ANOVA analysis. In addition to finding out the simple correlations between the single variables the proportionate weighing of their explanatory power would be the real result, which could be measured by regression analyses. Unfortunately, the method of recording our data does not make it possible, so it will be the task of further research. By using the question types as well as nominal and ordinal variables we could rely on cross-table comparisons and variance analysis (ANOVA) in our research. The following part summarises its findings.

Table 15

MAS factor values by the breakdown of the number of money managing/savings forms

Report

m ula ting m o ney-how m any	MAS-I powerprestige	MAS II thrifty, self su pporting	MAS III m istru stful, insecure	MAS IV anxious	MAS V m oney conscious bargain hu nter
0 (N=12)     Mean	2,43	2,93	3,97	4,71	3,25
Std . D evia tio n	0,81	1 ,41	1,61	1,53	1,82
1 (N=211)    Mean	2,55	4,37	3,79	4,11	3,57
Std . D evia tio n	1,01	1,36	1,36	1,48	1,41
2 (N=55)     Mean	2,57	4,65	3,34	3,74	3,55
Std . D evia tio n	1,07	1,37	1,28	1,63	1,42
3-4 (N=24)   Mean	3,12	5,41	4,07	3,97	3,82
Std . D evia tio n	1 ,13	1,22	0,93	1,63	1,24
5 or m ore     Mean	2,44	6,39	2,80	3,75	2,92
(N =3 )            Std . D evia tio n	0,80	0,51	0,53	1,39	0,80
Tota l           Me a n	2,59	4,46	3,73	4,05	3,57
Std . D evia tio n	1,03	1 ,42	1,33	1,52	1,41
ANOVA      Sig.	0,133	0,000	0,073	0,291	0,731
Eta	0,152	0,325	0,168	0,1 28	0,082
Eta Squa red	0,023	0,106	0,028	0,016	0,007

Age and gender. The young attribute a greater power-prestige role to the possession of money than their older counterparts but they also feel more insecure in the world of money. However, they believe that by looking for special offers and sales they can take advantage. Regarding gender, our expectations did not come true and our research did not justify the international results.

Education/qualification: Education does not only mean gaining professional knowledge but also improving the ability of obtaining information and orienteering. It seems that the relatively strong segmenting power of qualification in the money-attitude factor can be attributed to this. Those with a higher level of education (even in our relatively homogeneous sample) are thriftier and more willing to self-support although they do not believe in the advantageous nature of seasonal sales too much. (The differences of qualification do not result in such consequent changes in any other factor than in the ‘thrifty-self-supporting’ MAS II factor).

Labour market (dependent-money maker) status: Those who work appreciate money more than those who can rely on the support of the others. However, the more conscious and thriftier attitude of workers also goes together with more anxiety when thinking about their future. This may be typical of the Hungarian sample. The changes in the scores of the two factors are related to ‘work experience’ categories and in the case of MAS II this correlation is significant.

Income: The bigger amount of money students have, the more willing they are to show thrift and self-support and insecurity as well as mistrust are reduced. The income categories have significant effects on MAS II and MAS III factors. With the increase of the amount that ensures the living of students only the values of MAS II factor showed a simultaneous and continuous rise.

Professional studies: Interestingly, based on the responses the students of Finance and accounting and the students of Economics and management are more uncertain in financial matters (MAS III) and more anxious (MAS IV) than the students of other study programmes. In the thrifty-self-supporting factor (MAS II) they are in mid-position. The question is why their interest in finance deriving from their choice of the study programme and professional knowledge gained do not assist in managing everyday financial matters and the financial side of their lives. In making savings the students of management and leadership are prominent and also it is them who are the least power-prestige oriented, which can be due to the fact that hey are older. On the one hand, our results prove that the MAS indicator frequently used in international literature can also be applied in the Hungarian research and indicates the different attitudes of different groups properly (Table 16).

Of all the MAS factors MAS II is of great importance that refers to willingness to save as well as planning and monitoring costs (Table 15). Its importance is also indicated by the significance levels of different variables on the one hand, and also it refers to basic attitudes that can draw the attention of financial institutions the most and which most trainings are centred on, on the other hand.

MAS questions serve as a good indicator to assess the attitudes to money and examine money and culture in Hungary. As the simultaneous but distinguished impact system of the interrelated factors is only worth assessing by the multi-variate analysis of indicators that ensure a high level of measure, the creation of such indicators (assessors like the ratio scale) is targeted when compiling the questionnaire. An important task of further data recording and analyses is to define attitudes to money more properly and carry out the cluster analytical separation and moderation of items that belong here as well as test the forecasting power of different financial attitudes, i.e. examine how different attitudes affect customer behaviour and financial decisions.

Table 16

The value changes of MAS II scores by the categories of the examined demographic indicators

Indicators	A. Sign. (ANOVA)	B. lowest value	C. highest value	Difference (C – B)
Gender	0.176	4.40	4.65	0.25
Age	0.032	4.30	5.00	0.70
Qualification	0.014	4.37	5.46	1.09
Work experience	0.000	4.02	4.80	0.78
Financial situation	0.001	4.17	4.97	0.80

• VI.    Conclusion

Those who work and make their own living (resources and tuition fees) are more conscious in using money and thriftier in managing money. Are they happier? There is no obvious answer. It is certain that according to the high scores of the ‘anxiety’ factor their satisfaction is not total. However, the people who cover their life expenses from work manage their money more with a higher level of conscience and foresight and this ‘money-culture’ is that must be improved by both the financial institutions and the state.

We know that the pedagogical warning of ‘it is not a must to take on credit’ is losing its timeliness. The number of such investments is growing that can only be financed by asking for loans except some people in exceptional financial situation. A few of them are buying a flat/house or a car or establishing a company as well as running companies and studying itself to a greater and greater extent. Our examination proved that the consciuos use of money correlates with the variety of different forms of savings available. Those who take care of their present and future are diversified and their thriftier attitude to money matters goes without saying. They are less characterised by anxiety over money matters. All this shows that MAS II factor values are distinguishably manifested, and the behavoiur forecasting power of MAS II factor can also be concluded.

FOOTNOTES

• ¹    One of the exemplifications of protestant labour ethics emphasising the curbing consumption and success measured in money is the writing of Benjamain Franklin (one of the drafters of the Declaration of Independence): ‘If one wastes a penny a day, it amounts to six pounds a year, which is the interest for borrowing 100 pounds. Remember, time is money. He that can earn ten shillings a day by his labour, and goes abroad, or sits idle, one half of that day, though he spends but sixpence during his diversion or idleness, ought not to reckon that the only expense; he has really spent, or rather thrown away, five shillings besides’(Franklin, In: [25, p. 46]).

APPENDIX

The ‘MAS’ version part of the questionnaire

The following part contains some statements. Please, indicate the extent of your agreement with them by using a 7-grade scale. Circle the number that expresses your opinion the best.

not at all agree

I do not agree mostly

I do not agree to a small extent

It does not make any difference

I slightly agree

I mostly agree

I entirely agree

1. I often buy something just to impress others.	1 2 3 4 5 6 7
2. People say I overemphasize money.	1 2 3 4 5 6 7
3. I guess money is the sign of success	1 2 3 4 5 6 7
4. I have nice/expensive things to influence the others	1 2 3 4 5 6 7
5. Although people should be judged by actions, I am more interested in how much money they have	1 2 3 4 5 6 7
6. I use money to influence others- I try to make them do things for me for money.	1 2 3 4 5 6 7
7. Sometimes I boast how much money I made.	1 2 3 4 5 6 7
8. Sometimes I notice I show more respect for people who have more money than me.	1 2 3 4 5 6 7
9. I often try to guess why some people can make more money than me.	1 2 3 4 5 6 7
10. I put aside for future expenses.	1 2 3 4 5 6 7
11. I have financial plans for the future.	1 2 3 4 5 6 7
12. I have money available in the case of another world crisis.	1 2 3 4 5 6 7
13. I make savings for my old age/the unexpected.	1 2 3 4 5 6 7
14. I track my financial situation/budget carefully.	1 2 3 4 5 6 7
15. I am very cautious in money matters.	1 2 3 4 5 6 7
16. I often argue or complain about expenses.	1 2 3 4 5 6 7
17. When I bought something, it disturbs me afterwards how much it cost.	1 2 3 4 5 6 7
18. I hesitate to spend even when it comes to basic necessities.	1 2 3 4 5 6 7
19. After buying something I wonder where I could have bought it cheaper.	1 2 3 4 5 6 7
20. When going on a shopping spree, I feel I have benefitted.	1 2 3 4 5 6 7
21. I am overwhelmed by problems when it comes to money.	1 2 3 4 5 6 7
22. I am typically nervous if I do not have enough money.	1 2 3 4 5 6 7
23. I am concerned about my financial insecurity.	1 2 3 4 5 6 7
24. Often I automatically say to myself that I cannot afford it even if I can.	1 2 3 4 5 6 7
25. I am angry if I miss a bargain.	1 2 3 4 5 6 7
26. It is possible to act not accordingly with my budget.	1 2 3 4 5 6 7
27. It disturbs me when I discover I could have bought something cheaper elsewhere.	1 2 3 4 5 6 7
28. I bargain hunt regularly *.	1 2 3 4 5 6 7

* An extra item created by us. The item left out of the final version: ‘I take account of my money’ (Roberts, Sepulveda, 1999) [18].