Relationship Between Various Determinants and Dimensions of Financial Literacy Among Working Class

Abstract

The purpose of this empirical research work was to identify the relationship between various determinants of Financial Literacy among the working class of National Capital Region of India. It was a descriptive study based on the survey of 596 working class respondents. The data has been analyzed by factor analysis, correlation and regressions analysis. Based on the factor analysis, three factors have been found of financial knowledge, three factors of financial behaviour and in a similar manner four factors of financial attitude have been extracted. Further, based on the multiple regression models the contribution of financial attitude has been found highest in explaining the financial literacy and it has been followed by financial behaviour and financial knowledge. It means that both financial attitude and financial behaviour are better estimators of financial literacy in comparison to the financial knowledge. Therefore, the policy makers, financial system regulators and governments should do more efforts to improve the level of financial attitude and financial behaviour in comparison to the financial knowledge to improve the level of financial literacy because significant difference has been found in the level of financial attitude and financial behaviour across some of the demographic factors. The increased financial literacy would be helpful in improving the saving and investment behaviour of the public. This improved level of financial literacy of public will save the required level of capital for the capital formation for the targeted economic growth. Consequently, more employment opportunities will increase the social security in the society. Like every study, this study also have certain limitations like the universe of the study was limited to a particular geographical region i.e. National Capital Region of India, along with time and money constraints. In future similar study can be conducted by changing the target population and geographical area with a bigger sample.