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Integrating positive financial attitudes to nurture students’ identity as informed financial decision-makers in high power distance Chinese contexts

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Abstract

Research on financial literacy has focused on the influence of teachers and parents in financial literacy education, which mediates the impact on students’ financial behaviour. Much less attention has been given to the influence of traditional Chinese hierarchical culture on a child’s identity as a student. This paper applies Lee’s (2017) theory of identity grafting to examine how student self-identity towards personal financial management is reflected in their financial behaviour, and whether nurturing students with positive financial attitudes can improve the financial behaviour of students who are challenged by power distance values. We surveyed 1164 students from 39 secondary schools. We first focus on the influence of power distance on students that endorse the traditional Chinese values that superiors and subordinates should know their place and behave accordingly. Second, we focus on how students’ positive financial attitude interact with power distance effects. The results from structural equation modelling show that that high endorsement of power distance has a negative impact on financial behaviour in spending and that positive financial attitude has a positive influence on financial behaviour in spending, protection and planning. Further, students who highly endorse power distance values but have positive financial attitudes can still demonstrate positive financial behaviour. This paper is the first to validate identity grafting effects on students via statistical study. The implications of the findings on identity grafting are discussed.

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Appendices

Appendix 1: Abbreviations used in the passage

Abbreviation

Full form

Explanation

FLE

Financial Literacy Education

A process to acquire financial knowledge and skills in order to effectively manage personal finance and use financial resources to make proper decisions

FA

Financial Attitude

Refers to how an individual feel about personal financial management, which plays a crucial role in the individual’s ability to understand, analyze and manage personal financial matters

FB

Financial Behaviour

Behaviour related to personal money management, specifically regulating current finances to achieve future financial wellbeing

SEM

Structural Equation Modelling

A multivariate statistical analysis technique for testing the paths of influence of power distance and financial attitude FB in spending, protection and planning, which ultimately examine the distinctiveness of the measures

RMSEA

The Root Mean Square Error of Approximation

A supplementary statistic to determine the discrepancy between the hypothesized model, with optimally chosen parameter estimates, and the population covariance matrix. The RMSEA ranges from 0 to 1, with smaller values indicating better model fit. A value of .06 or less is indicative of acceptable model fit

CFI

Comparative Fit Index

Analyzes the model fit by examining the discrepancy between the data and the hypothesized model, while adjusting for the issues of sample size inherent in the Chi squared test of model fit, and the normed fit index. CFI values range from 0 to 1, with larger values indicating better fit

CI

Confidence Interval

A type of interval estimation to describe the amount of uncertainty associated with a sample estimate of a population parameter

IFI

Incremental Fit Indices

Known as “Bollen’s IFI”, which is based on the comparison of the fit of a substantive model to that of a null model. Values that exceed 0.9 are regarded as acceptable

χ2

Chi square

The original fit index for structural models

df

Degrees of freedom

The number of parameters of the system that may vary independently

GFI

Goodness of Fit Index

A measure of fit between the hypothesized model and the observed covariance matrix

CFI

Comparative Fit Index

Analyzes the model fit by examining the discrepancy between the data and the hypothesized model, while adjusting for the issues of sample size inherent in the Chi squared test of model fit and the normed fit index. CFI values range from 0 to 1, with larger values indicating better fit

NFIa

Normed Fit Index

Known as “Bentler-Bonett normed fit index”, which is an incremental measure of goodness of fit for a statistical model, which is not affected by the number of parameters/variables in the model. It analyzes the discrepancy between the Chi squared value of the hypothesized model and the Chi squared value of the null model. The fit index varies from 0 to 1—where 1 is ideal

TLIa

Tucker Lewis index

Known as “Non-normed fit index” (NNFI). It is an incremental measure of goodness of fit for a statistical model, which takes into account the size of the correlations in the data and the number of parameters in the model. This index provides an adjustment to the Normative Fit Index that incorporates the degrees of freedom in the model

OECD

The Organization for Economic Co-operation and Development

An international organization that works to build better policies for better lives. Our goal is to shape policies that foster prosperity, equality, opportunity and well-being for all

  1. aValues for both the NFI and TLI should range between 0 and 1, with a cutoff of 0.95 or greater indicating a good model fit

Appendix 2: Tables and figures

See Tables 1, 2, 3 and Figs. 1, 2.

Table 1 Sample characteristics
Table 2 Means, standard deviations and intercorrelations between main variables (N = 1306)
Table 3 Model fit summary and measure models comparison (N = 1164)

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Ho, C.S.M., Lee, H.L.D. Integrating positive financial attitudes to nurture students’ identity as informed financial decision-makers in high power distance Chinese contexts. J Educ Change 22, 247–270 (2021). https://doi.org/10.1007/s10833-020-09396-x

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