CORRELATION BETWEEN FINANCIAL LITERACY VARIABLES AND HOUSEHOLD SAVINGS BEHAVIOUR IN TWO SELECTED MUNICIPALITIES IN SOUTH AFRICA

Authors

  • Dr Ifeanyi Mbukanma Postdoctoral Research Fellow (Economics Sciences), Faculty of Economic and Management Sciences, North-West University, Republic of South Africa. Author
  • Prof Ravinder Rena Professor of Economics, NWU Business School, Faculty of Economic and Management Sciences, North-West University, Republic of South Africa. Author

DOI:

https://doi.org/10.61841/djzbb919

Keywords:

Financial literacy variables, Household savings behaviour, Structural Equation Model, South Africa

Abstract

 This study was conducted to ascertain financial literacy variables that have a statistically

significant impact on household savings behaviour. Thus, to achieve this objective, financial

literacy micro-variables were used to obtain quantitative data from the employees of the City

of Tshwane and Mahikeng Municipality in South Africa. Correlation statistical analysis and

factor analysis were performed to identify financial literacy micro-variables that have a

significant impact on household savings behaviour as well as a confirmatory factor analysis

through structural equation modelling. Hence, the findings of this study reveal that financial

literacy variables under the domain of financial control, planning and knowledge have a

positive correlation with determinant variables of South African household savings behaviour

and recommend that stakeholders in charge of financial literacy and savings campaigns in

South Africa should adopt the study's contribution which identifies financial and savings

literacy as core variables that can improve savings behaviour of South African households 

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References

Allais, S. (2017). Towards measuring the economic value of higher education: Lessons from

South Africa. Comparative Education, 53(1), 147-163.

Andereck, K. L. (2017). Inferential analysis of data. Research methods for leisure, recreation

and tourism (Ed. 2), 269-283.

Asparouhov, T., Muthén, B., & Morin, A. J. (2015). Bayesian structural equation modelling

with cross-loadings and residual covariances: Comments on Stromeyer et al.

Atkinson, A., & Messy, F. (2012). Measuring financial Literacy: Results of the

OECD/International Network on Financial Education (INFE) Pilot Study. OECD Working Papers on Finance, Insurance and Private Pensions, No. 15, OECD

Publishing.

Beckmann, E. (2013). Financial literacy and household savings in Romania. Numeracy, 6(2),

9.

Bernheim, B. D., Forni, L., Gokhale, J., & Kotlikoff, L. J. (2000). How much should

Americans be saving for retirement? American Economic Review 90(2), 288–292.

Boisclair, D., Lusardi, A., & Michaud, P. C. (2017). Financial literacy and retirement

planning in Canada. Journal of Pension Economics & Finance, 16(3), 277-296.

Clark, R., Lusardi, A., & Mitchell, O. S. (2017). Employee financial literacy and retirement

plan behaviour: A case study. Economic Inquiry, 55(1), 248-259.

Cole, S., Iverson, B., & Tufano, P. (2017). Can gambling increase savings? Empirical

evidence on prize-linked savings accounts.

Cranmer, S. J., Leifeld, P., McClurg, S. D., & Rolfe, M. (2017). Navigating the range of

statistical tools for inferential network analysis. American Journal of Political

Science, 61(1), 237-251.

Cronqvist, H., & Siegel, S. (2015). The origins of savings behaviour. Journal of Political

Economy, 123(1), 123-169.

Crowley, S. L., & Fan, X. (1997). Structural equation modelling: Basic concepts and

applications in personality assessment research. Journal of Personality Assessment,

68(3), 508-31.

Darley, W. (2011). Measures to improve household savings in South Africa (Doctoral

dissertation, University of KwaZulu-Natal).

De Vos, A. S., Strydom, H., Fouché, C. B., & Delport, C. S. L. (2005). Research at

grassroots for the social sciences and human service professions. Pretoria: Van

Schaik.

Demirgüç-Kunt, A., & Klapper, L. 2013. Measuring financial inclusion: Explaining variation

in the use of financial services across and within countries. Brookings Papers on

Economic Activity, 1, 279-340.

Fatoki, O. (2014). The financial literacy of micro-entrepreneurs in South Africa. Journal of

Social Sciences, 40(2), 151-158.

Friedman, M. (1957). A theory of the consumption function. Princeton, N.J. Princeton

University Press.

Ge, S., Yang, D. T., & Zhang, J. (2018). Population policies, demographic structural changes,

and the Chinese household saving puzzle. European Economic Review, 101, 181-209.

Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant

validity in variance-based structural equation modelling. Journal of the academy of

marketing science, 43(1), 115-135.

Howard, J. L., Gagné, M., Morin, A. J., & Forest, J. (2018). Using bifactor exploratory

structural equation modelling to test for a continuum structure of motivation. Journal

of Management, 44(7), 2638-2664.

Jonubi, A., & Abad, S. (2013). The impact of financial literacy on individual saving: An

exploratory study in the Malaysian context. Transformations in Business &

Economics, 12(1), 28.

Kenny, D. A., Kaniskan, B., & McCoach, D. B. (2015). The performance of RMSEA in

models with small degrees of freedom. Sociological Methods & Research, 44(3), 486-

507.

Klapper, L., Lusardi, A., & Van Oudheusden, P. (2015). Financial literacy around the world.

Standard & Poor’s Ratings Services Global Financial Literacy Survey. http://media.

mhfi. com/documents/2015-Finlit_paper_17_F3_SINGLES. pdf.

Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities.

Educational and Psychological Measurement, 30(3), 607-610.

Lusardi, A., & Mitchell, O. S. (2014). The economic importance of financial literacy: Theory

and evidence. Journal of Economic Literature, 52(1), 5-44.

Lusardi, A. (2008). Household saving behaviour: The role of financial literacy, information,

and financial education programs: National Bureau of Economic Research. Working

Paper No. 13824

Lusardi, A., Michaud, P. C., & Mitchell, O. S. (2017). Optimal financial knowledge and

wealth inequality. Journal of Political Economy, 125(2), 431-477.

Mahlo, N. (2011). Determinants of household savings in South Africa. (Doctoral dissertation,

University of Johannesburg).

Modigliani, F., & Brumberg, R. (1954). Utility analysis and the consumption function: An

interpretation of cross-section data. Franco Modigliani, 1.

Mongale, I. P., Mukuddem-Petersen, J., Petersen, M. A., & Meniago, C. (2013). Household

savings in South Africa: An econometric analysis. Mediterranean Journal of Social

Sciences, 4(13), 519-530.

Nishina, K., Kawamura, H., Okamoto, K., & Takahashi, T. (2018). Monitoring and diagnosis

of causal relationships among variables. Frontiers in Statistical Quality Control, 12,

175-184. Springer, Cham.

Perry, J. L., Nicholls, A. R., Clough, P. J., & Crust, L. (2015). Assessing model fit: Caveats

and recommendations for confirmatory factor analysis and exploratory structural

equation modelling. Measurement in Physical Education and Exercise Science, 19(1),

12-21.

Petrie, J., Jones, R., & Murrell, A. (2018, March). Measuring impact while making a

difference: A financial literacy service learning project as participatory action

research. In Developments in Business Simulation and Experiential Learning:

Proceedings of the Annual ABSEL Conference (Vol. 45).

Precious, C., & Asrat, T. (2014). Determinants of household savings in South Africa: An

econometric approach (1990-2011). Mediterranean Journal of Social Sciences, 5(15),

183-190.

Refera, M. K., Dhaliwal, N. K., & Kaur, J. (2016). Financial literacy for developing countries

in Africa: A review of concept, significance and research opportunities. Journal of

African Studies and Development, 8(1), 1-12.

Roberts, B., Struwig, J., & Gordon, S. (2014). Financial literacy in South Africa: Results

from the 2013 South African Social Attitudes Survey round. A report prepared by the

Human Sciences Research Council on behalf of the Financial Services Board.

Pretoria: Financial Services Board.

Şahin, R., & Liu, P. (2017). Correlation coefficient of single-valued neutrosophic hesitant

fuzzy sets and its applications in decision-making. Neural Computing and

Applications, 28(6), 1387-1395.

Savalei, V., & Bentler, P. M. (2006). Structural equation modelling. The handbook of

marketing research: Uses, misuses, and future advances, 330-364.

Shields, D. L., Funk, C. D. & Bredemeier, B. L. (2018). Relationships among moral and

contesting variables and prosocial and antisocial behaviour in sport. Journal of Moral

Education, 47(1), 17-33.

Shor, R. E. (2017). A phenomenological method for the measurement of variables important

to an understanding of the nature of hypnosis. In Hypnosis (pp. 105-136). Routledge.

Singh, S. F. (2015). Social sorting as ‘social transformation’: Credit scoring and the

reproduction of populations as risks in South Africa. Security Dialogue, 46(4), 365-

383.

Struwig, M., & Plaatjes, W. (2013). Developing a framework to investigate the personal

financial management knowledge of individuals. South African Journal of Economic

and Management Sciences, 10(1), 21-32.

Sudha, R., Ragavi, V., & Thirumalai, C. (2017). May. Analysing correlation coefficient using

software metrics. In Trends in Electronics and Informatics (ICEI), 2017 International

Conference (pp. 1151-1153). IEEE.

Symanowitz, C. D. (2006). The relationship between financial literacy, economic measures

and delayed gratification in South African high school learners (Doctoral dissertation,

Institute of Business Science, University of Pretoria).

Terceño, J. R., Vallés, J. E. G., & Domínguez, D. C. (2017). Application of a measurement

model and system of intangible variables in business environments. Revista Latina de

Comunicación Social, 72, 560.

Ullman, J. B., & Bentler, P. M. (2012). Structural equation modelling: Handbook of

psychology (2nd Edition), 2.

Usuda, K., Funasaki, A., Sekimura, A., Motono, N., Matoba, M., Doai, M., Uramoto, H.

(2018). FDG-PET/CT and diffusion-weighted imaging for resected lung cancer:

Correlation of maximum standardized uptake value and apparent diffusion coefficient

value with prognostic factors. Medical Oncology, 35(5), 66.

Van Rooij, M. C., Lusardi, A., & Alessie, R. J. (2012). Financial literacy, retirement planning

and household wealth. The Economic Journal, 122(560), 449-478.

Venti, S. F., & Wise, D. A. (2000). Choice, chance, and wealth dispersion at retirement.

Working Paper, National Bureau of Economic Research.

Weinberg, S. L., & Abramowitz, S. K. (2016). Statistics using IBM SPSS: An integrative

approach. Cambridge University Press.

Zebende, G. F., & Da Silva Filho, A. M. (2018). Detrended multiple cross-correlation

coefficient. Physica A: Statistical Mechanics and its Applications, 510, 91-97

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Published

30.06.2021

How to Cite

Mbukanma, I., & Rena, R. (2021). CORRELATION BETWEEN FINANCIAL LITERACY VARIABLES AND HOUSEHOLD SAVINGS BEHAVIOUR IN TWO SELECTED MUNICIPALITIES IN SOUTH AFRICA. International Journal of Psychosocial Rehabilitation, 25(3), 77-89. https://doi.org/10.61841/djzbb919