Linking biopsychosocial indicators with financial risk tolerance and satisfaction through macroeconomic literacy: A structural equation modeling approach

Figures & data

Table

Authors	Topic	Method	Results
(Topa, Moriano, & Moreno, 2012)	Psychosocial determinants of financial planning for retirement among immigrants in Europe	SEM	Quality of life and life satisfaction has negative impact while all other variables have a positive impact.
(Ali, Rahman, & Bakar, 2015)	Financial Satisfaction and the Influence of Financial Literacy in Malaysia	SEM	The positive impact was found.
(Dinç Aydemir & Aren, 2017)	Do the effects of individual factors on financial risk-taking behavior diversify with financial literacy?	Structural equation modeling and Multigroup structural equation modeling	A positive relationship existed among study variables.
(Rai, Dua, & Yadav, 2019)	Association of Financial Attitude, Financial Behavior and Financial Knowledge Towards Financial Literacy: A Structural Equation Modeling Approach	SEM	Financial knowledge has insignificant impact while other has positive and significant impact.
(Sivaramakrishnan, Srivastava, & Rastogi, 2017)	Attitudinal factors, financial literacy, and stock market participation	SEM	Positive relationship was found.
(Lusardi, Mitchell, & Curto, 2010)	Financial literacy among the young: Evidence and implications for consumer policy	Multivariate Analysis	Positive relationship was found.
(Muda, 2017)	User Impact of Literacy on Treatment Outcomes Quality Regional Financial Information System	Structural equation modeling	Positive relationship was found among study variables.
(Morgeson, Sharma, & Hult, 2015)	Cross-National Differences in Consumer Satisfaction: Mobile Services in Emerging and Developed Markets	SEM	Positive relationship was found.

Table

Reasons for selecting purposive sampling technique
“The purpose of the current study was to assess the individual factors of investors that determine their FRT and financial satisfaction”
“The researcher wants to access a particular subset of people, as all participants of a study are selected because they fit a particular profile”
“The researcher has the prior knowledge about the purpose of his study and he can properly choose and approach eligible participants”
“The researcher will rely on his own judgment when choosing members of the population to participate in his study”

Table 1. Descriptive Statistics

	N	Minimum	Maximum	Mean	Std. Deviation	Skewness
	Statistic	Statistic	Statistic	Statistic	Statistic	Statistic	Std. Error
Personality	1134	1.00	5.00	3.5710	1.07046	−0.849	0.140
Sensation Seeking	1134	1.00	5.00	3.5439	1.13120	−0.745	0.140
Self-esteem	1134	1.00	4.90	3.5799	1.07698	−0.858	0.140
Macroeconomic Literacy	1134	1.00	5.00	3.4576	1.12890	−0.558	0.140
FRT	1134	1.00	5.00	3.5881	1.08664	−0.837	0.140
Financial satisfaction	1134	1.00	7.50	3.4010	1.13279	−0.136	0.140

Table 2. KMO and Bartlett’s Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy.		.947
Bartlett’s Test of Sphericity	Approx. Chi-Square	11714.992
	Df	561
	Sig.	0.000

Table 3. Convergent Validity and Discriminant Validity

	CR	AVE	MSV	ML	FRT	FS	Personality	SE	SS
ML	0.911	0.804	0.486	0.896
FRT	0.943	0.768	0.379	0.437	0.877
FS	0.799	0.665	0.486	0.697	0.472	0.816
Personality	0.943	0.737	0.293	0.425	0.444	0.510	0.859
SE	0.928	0.751	0.364	0.498	0.527	0.603	0.541	0.867
SS	0.951	0.797	0.379	0.378	0.616	0.400	0.541	0.584	0.893

Table 4. CFA

Indicators	Threshold range	Current values
CMIN/DF	Less or equal than 3	2.362
GFI	Equal or greater than 0.80	0.810
CFI	Equal or greater than 0.90	0.941
IFI	Equal or greater than 0.90	0.940
RMSEA	Less or equal than 0.08	0.067

Figure 1. Macroeconomic literacy

Figure 2. CFA

Table 5. SEM Results

Total Effect	SE	SS	Personality	ML
Total Effect
ML	0.328***	0.033	0.260***	0.000
FS	0.406***	−0.028	0.256***	0.438***
FRT	0.196**	0.388***	0.158**	0.158**
Direct effect
ML	0.328***	0.033	0.260	0.000
FS	0.262***	−0.042	0.143**	0.438***
FRT	0.144**	0.382***	0.116**	0.158**
Indirect effect
ML	0.000	0.000	0.000	0.000
FS	0.144**	0.014	0.114**	0.000
FRT	0.052*	0.005	0.041*	0.000

Note: *** indicates p-value <0.001, ** indicates p-value <0.01, * indicates p-value <0.05.

Figure 3. SEM

Topa, G., Moriano, J. A., & Moreno, A. (2012). Psychosocial determinants of financial planning for retirement among immigrants in Europe. Journal Of Economic Psychology, 33(3), 527–537. doi:10.1016/j.joep.2012.01.003

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Ali, A., Rahman, M. S. A., & Bakar, A. (2015). Financial satisfaction and the influence of financial literacy in Malaysia. Social Indicators Research, 120(1), 137–156. doi:10.1007/s11205-014-0583-0

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Dinç Aydemir, S., & Aren, S. (2017). Do the effects of individual factors on financial risk-taking behavior diversify with financial literacy? Kybernetes, 46(10), 1706–1734. doi:10.1108/K-10-2016-0281

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Rai, K., Dua, S., & Yadav, M. (2019). Association of financial attitude, financial behaviour and financial knowledge towards financial literacy: A structural equation modeling approach. FIIB Business Review, 8(1), 51–60. doi:10.1177/2319714519826651

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Sivaramakrishnan, S., Srivastava, M., & Rastogi, A. (2017). Attitudinal factors, financial literacy, and stock market participation. International Journal of Bank Marketing, 35(5), 818–841. doi:10.1108/IJBM-01-2016-0012

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Lusardi, A., Mitchell, O. S., & Curto, V. (2010). Financial literacy among the young. Journal of Consumer Affairs, 44(2), 358–380. doi:10.1111/j.1745-6606.2010.01173.x

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Muda, I. (2017). User impact of literacy on treatment outcomes quality regional financial information system. Management Dynamics in the Knowledge Economy, 5(2), 307–326. doi:10.25019/MDKE

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Morgeson, F. V., III, Sharma, P. N., & Hult, G. T. M. (2015). Cross-national differences in consumer satisfaction: Mobile services in emerging and developed markets. Journal of International Marketing, 23(2), 1–24. doi:10.1509/jim.14.0127

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