E-ISSN:2583-1747

Research Article

Financial Autonomy

Management Journal for Advanced Research

2025 Volume 5 Number 4 August
Publisherwww.singhpublication.com

Determinants of Financial Well Being: A Study of Urban Working Women in West Bengal

Bhattacharjya P1*, Chatterjee S2, Jha NK3
DOI:10.5281/zenodo.17060279

1* Patralika Bhattacharjya, Research Scholar (Ph.D), Department of Economics, Sister Nivedita University, Kolkata, West Bengal, India.

2 Susmita Chatterjee, Assistant Professor, Department of Economics, Maharaja Manindra Chandra College, Kolkata, West Bengal, India.

3 Navin Kumar Jha, Professor and HOD, Department of Economics, Sister Nivedita University, Kolkata, West Bengal, India.

This study investigates the facilitating role of Financial Skills and Financial Autonomy on Financial Well Being of Urban Working Women in West Bengal. In the methodology of the research study, a primary survey was carried out in a cross-sectional manner and 332 participants were studied. It investigates the structural covariance among latent factors like Financial Autonomy, Financial Skill (FSK), Financial Well-being (FWB), and Money Management Stress (MMS) through Structural Equation Modelling (SEM). The questionnaire comprised of validated questions that evaluated the constructs of interest, and it was developed through a literature review of financial behaviour and psychological well-being found in Behavioural Economics Literature. The final SEM model consisted of three latent variables as per a well-established theoretical framework. The findings indicate that Financial Skills in combination with Financial Autonomy or the ability of an individual to independently manage their finances, make informed financial decisions, and take effort towards their own financial goals emphatically increases Financial Well Being and reduces Money Management Stress in Urban Working Women.

Keywords: financial autonomy, financial skills, financial well being, money management stress, urban working women

Corresponding Author How to Cite this Article To Browse
Patralika Bhattacharjya, Research Scholar (Ph.D), Department of Economics, Sister Nivedita University, Kolkata, West Bengal, India.
Email: 		Bhattacharjya P, Chatterjee S, Jha NK, Determinants of Financial Well Being: A Study of Urban Working Women in West Bengal. Manag J Adv Res. 2025;5(4):48-54.
Available From
https://mjar.singhpublication.com/index.php/ojs/article/view/240

Manuscript Received Review Round 1 Review Round 2 Review Round 3 Accepted
2025-07-07 2025-07-26 2025-08-15
Conflict of Interest Funding Ethical Approval Plagiarism X-checker Note
None Nil Yes 4.39

© 2025 by Bhattacharjya P, Chatterjee S, Jha NK and Published by Singh Publication. This is an Open Access article licensed under a Creative Commons Attribution 4.0 International License https://creativecommons.org/licenses/by/4.0/ unported [CC BY 4.0].

Manag J Adv Res 2025;5(4)48
Download PDFBack To Article1. Introduction2. Literature Review3. Research Gap4. Objectives of the
Study5. Theorizing
Hypotheses6. Data and
Methodology7. Discussions and
Findings8. ConclusionReferences
Bhattacharjya P, et al. Determinants of Financial Well Being

1. Introduction

Financial Skills and Financial Autonomy are two terms which are relevant in recent times due to the challenges of long-term financial planning and the sustained demands of financial management often contributing to heightened stress, especially among women. As individuals attain financial independence and seek to navigate their finances effectively—managing discrepancies between income and expenditure in contemporary life—the acquisition of financial skills becomes essential.

Once Financial Skills are set in motion the path towards Financial Autonomy looks clearer and lessens risks associated with complex financial services and enables informed choices. Proactive financial education bolsters emotional, reflexive and functional autonomy among women.

This study aims to contribute to the existing literature on women's financial decision-making by providing a comprehensive analysis of the factors that influence urban working women's financial behaviours in West Bengal. By integrating insights from financial literacy and socio-economic dynamics, this research seeks to uncover the challenges these women face in their financial journey and the opportunities that can be leveraged for their empowerment.

2. Literature Review

The literature presents a detailed view of financial decision-making among urban working women in West Bengal. Studies highlight the significance of financial literacy in enabling women’s economic participation and financial autonomy while also illustrating the limitations imposed by conventional gender roles

2.1 Financial Autonomy: The Key to Financial Well Being

Financial Autonomy (FA) has been widely conceptualized as a state of reduced financial dependency on others (Collins et al., 1997) and the capacity to achieve personal financial goals through informed financial decision-making (FDM) (Jariwala, 2020). Rooted in the goal framing theory, particularly the “gain goal frame,” FA is positioned as a critical intangible resource necessary for achieving sound financial decisions and personal financial well-being (PFWB) (Lindenberg & Steg, 2007).

Within this framework, the enhancement of individual resources—here, financial autonomy—becomes essential for goal attainment.

2.2 Gender Roles in Financial Autonomy

The role of socialization in fostering FA has also received scholarly attention. Jariwala and Sharma (2013) underscore the influence of socialization agents, particularly parental interactions, as vital contributors to the development of FA. These findings are supported by studies that link early familial financial socialization to increased financial well-being in later life (Jorgensen et al., 2017; Xiao et al., 2014).

2.3 Socio -Economic Influences on Financial Well Being

Socio-economic variables such as income level, educational background, and employment status significantly impact the financial well-being and independence of working women in West Bengal. Kochar et al. (2022), in demonstrate that economic empowerment can lead to positive changes in women’s financial autonomy and household decision-making power.

3. Research Gap

However, despite these advancements, there remains a gap in the literature concerning the individual-level perception of FA and its facilitating role in the relationship between individual financial skills and outcomes such as increasing financial wellbeing and lessening money management stress.

This study addresses this gap by proposing that financial skills—encompassing knowledge, confidence, and behavioural control—contribute to a sense of financial independence. This, in turn, facilitates enhance long-term financial well-being and reduction of Money Management Stress in Urban Working Women.

4. Objectives of the Study

The current study aims to explore:

1. To assess the Role of Financial Skills and Financial Autonomy as a facilitator of Financial Well Being in Urban Working Women in West Bengal.

2. To assess the covariant structure between Financial Skills, Financial Autonomy, Money Management Stress and Financial Well Being.


Manag J Adv Res 2025;5(4)49
Bhattacharjya P, et al. Determinants of Financial Well Being

5. Theorizing Hypotheses

The following hypotheses could plausibly explain the covariant structure amongst the latent factors namely, FSK, FA and MMS

H1: FSK positively influences FWB

H2: FA positively influences FWB

H3: MMS negatively influences FWB

6. Data and Methodology

6.1 Data

For the purpose of the study, we have done the Literature Review and tapped primary sources of information to get data on financial decision making of urban working women in West Bengal. The study area has been West Bengal.

Pretesting was done for proper articulation of questions and expert opinions were solicited to address the measurement issues, for assessing the face validity of the measurements. Pilot survey was conducted. Qualitative and quantitative methods were applied. The sampling procedure was purposive random sample. The study employed structural equation SEM modelling for validating and testing the data.

The period of data collection was between September 2024 to April 2025.

The research examines the structural correlations amid Financial Autonomy (FA), Financial Well-being (FWB), and Money Management Stress (MMS) through Structural Equation Modelling (SEM). A primary survey was carried out in a cross-sectional manner and 332 participants gave their response. The questionnaire comprised of validated questions that assessed the constructs of interest, and it was developed through a literature review of what existed in the literature with regard to financial behaviour and psychological well-being. Despite an initial consideration of several constructs, the final SEM model consisted of three latent variables as per a well-established theoretical framework.

Each latent variable was measured using a set of observed indicators:

  • Financial Skills (FSK): fsk15, fsk16, fsk20
  • Financial Autonomy (FA): fa3, L4, L5

  • Financial Well-being (FWB): fwb4, fwb5, fwb6
  • Money Management Stress (MMS): mms1, mms2, mms3

Data analysis was performed using the maximum likelihood estimation (MLE) method within the SEM framework. Standardized path coefficients, standard errors, z-statistics, p-values, and 95% confidence intervals were computed for both structural and measurement components of the model. Model fit was assessed using conventional indices including RMSEA, CFI, TLI, SRMR, and information criteria (AIC and BIC).

The number of data responses collected were 332 in number, The total number of variables were 10 in number in alignment with 10 questions asked. The types of women surveyed were urban working women across West Bengal. Variables of interest were fa3 (Financial Autonomy), fsk15 fsk16, fsk20 (Financial Skill), fwb4, fwb5, fwb6 (Financial Well Being), mms1, mms2, mms3 (Money Management Stress). The questionnaire is based on a widely accepted working definition of financial literacy which stresses general behaviors, attitudes and knowledge that could be attained in a variety of ways.

Likert-type scales are used (such as strongly agree through to strongly disagree) instructions tell the interviewer to probe well, and to provide the respondent with a web-based Google Form, mail survey, Face to face interview and hard-copy printed scale if the respondent finds it cognitively difficult to put themselves on a scale without a visual aid.

The research examines the structural covariance among latent factors namely, Financial Skill (FSK), Financial Autonomy (FA), Financial Well-being (FWB) and Money Management Stress (MMS) through Structural Equation Modelling (SEM). A primary survey was carried out in a cross-sectional manner and 332 participants gave their responses. The questionnaire comprised of validated questions that assessed the constructs of interest, and it was developed through a literature review of what existed in the literature with regard to financial behaviour and psychological well-being. Despite an initial consideration of several constructs, the final SEM model consisted of four latent variables as per a well-established theoretical framework.


Manag J Adv Res 2025;5(4)50
Bhattacharjya P, et al. Determinants of Financial Well Being

Table 1: Latent variable and set of observed indicators

LatentObserved Indicators
Financial SkillsFsk15Fsk16Fsk 20
Financial AutonomyFa3
Financial Well Beingfwb4fwb5fwb6
Money Management Stress (MMS)mms1mms2mms2

Data analysis was performed using the maximum likelihood estimation (MLE) method within the SEM framework. Standardized path coefficients, standard errors, z-statistics, p-values, and 95% confidence intervals were computed for both structural and measurement components of the model. Model fit was assessed using conventional indices including RMSEA, CFI, TLI, SRMR, and information criteria (AIC and BIC).

6.2 Data Analysis

6.2.1. Sample Composition of the Study

Table 2: Demographic Profile of Respondents (Urban Working Women in West Bengal)
AgePercentage of Responses
Up to 2973%
30 – 3920%
39- 597%
Educational LevelPercentage of Responses
HS5%
Graduate38%
Post Graduate35%
Post Graduate and Above22%
Current Work SituationPercentage of Responses
Paid Employment64%
Self-Employment36%
Sector EmployedPercentage of Responses
Formal71%
Informal29%
Segregation of Responses by SectorPercentage of Responses
Education Sector42%
IT12%
Education Sector Self Employed3%
Banking8%
Others Self Employed8%
Segregation by Public and Private SectorPercentage of Responses
Government Service37%
Non -Government Service and Others63%

Source: Author’s Calculations

6.3 Structural Equation Modelling Results

The standardized path coefficients for the structural and measurement components of the model are reported in Table 3.

Table 3: Standardized SEM Path Estimates Structural Model

MeasurementCoefficientStandard Errorz valuep
Structural
L2
Fa3.43337660.0635726.820
L4.25854390.0935072.760.006
L5-.442307-5.310

Table 4: Standardized SEM Path Estimates Measurement Models

MeasurementCoefficientStandard ErrorzP>z
fsk20 
L40.8544640.01344336.360
_cons1.7809740.089513519.90
fsk15 
L4 10.37635552.660.008
_cons2.4962520.132458318.850
fsk16 
L40.4859340.16586942.930.003
_cons2.6922120.116920723.030
fwb6 
L20.59350960.05190611.430
_cons1.8397150.154146111.930
fwb5 
L20.61314020.051870211.820
_cons 1.9524130.155553212.550
fwb4 
L20.50154170.0541019.270
_cons2.5495680.170451114.960
mms1 
L50.73717440.0931717.910
_cons2.5705610.11384322.580
mms2
L50.21176610.07307982.90.004
_cons1.8557030.090544120.50
mms3 
L50.56226140.08092316.950
_cons2.0665830.09717921.270
MeasurementCoefficientstd. err.zP>z
fsk20
L40.8544640.01344336.360
_cons1.7809740.089513519.90

Manag J Adv Res 2025;5(4)51
Bhattacharjya P, et al. Determinants of Financial Well Being

fsk15
L4 10.37635552.660.008
_cons2.4962520.132458318.850
fsk16 
L40.4859340.16586942.930.003
_cons2.6922120.116920723.030
fwb6 
L20.59350960.05190611.430
_cons1.8397150.154146111.930
fwb5 
L20.61314020.051870211.820
_cons1.9524130.155553212.550
fwb4 
L20.50154170.0541019.270
_cons2.5495680.170451114.960
mms1

Source: Author’s Calculations

6.3.1. Model Fit Statistics

Table 5: Overall goodness-of-fit indices for the proposed SEM model

Fit statisticValueDescription
Likelihood ratio
chi2_ms (33)36.688model vs. saturated
p > chi20.302
chi2_bs (45)147.21baseline vs. saturated
p > chi20
Population error
RMSEA0.035Root mean squared error of approximation
90% CI, lower bound0
upper bound0.087
pclose0.627Probability RMSEA <= 0.05
Information criteria
AIC2953.392Akaike's information criterion
BIC3029.046Bayesian information criterion
Baseline comparison
CFI0.964Comparative fit index
TLI0.951Tucker–Lewis index
Size of residuals
SRMR0.091Standardized root mean squared residual
CD0.99Coefficient of determination

Source: Author’s Calculations

6.3.2. Analysis

The visual SEM path diagram Figure 1 provides, an intuitive overview of the directional influences among latent constructs. Notably, the positive pathways from fa3 and L4 to L2 reinforce the theoretical proposition that both individual financial autonomy and skill-based factors contribute to perceived financial well-being.

Figure 1

mjar_240_01.PNG

Source: Author’s Calculations

The negative pathway from L5 to L2, while statistically significant, invites further interpretation. It potentially reflects the inverse association where heightened stress in managing money detracts from overall financial well-being, aligning with behavioral finance literature that links financial anxiety with lowered economic satisfaction.

The statistically significant negative path coefficient from L5 (MMS) to L2 (FWB) suggests that money management stress acts as a suppressor variable in the relationship. This implies that when financial stress increases, perceptions of financial well-being decline, regardless of the individual’s skills or autonomy. From a theoretical standpoint, this supports the "emotional cost hypothesis", which argues that financial decision-making burden leads to psychological fatigue, reducing perceived well-being even in the presence of capability or autonomy.

7. Discussions and Findings

The structural paths from Financial Autonomy (FA) to Financial Well-being (FWB) are all statistically significant, suggesting a robust positive association. Among the FA indicators, the strongest contribution comes from fa3 (β = 0.4334, p < 0.001), emphasizing the role of self-perceived financial control in enhancing subjective well-being. This is complemented by L4 and L5, both of which are also significant contributors, suggesting multidimensional effects of autonomy.


Manag J Adv Res 2025;5(4)52
Bhattacharjya P, et al. Determinants of Financial Well Being

In the measurement model, all indicators for FWB load significantly, with fwb5 (β = 0.6113) and fwb6 (β = 0.5936) being the most influential, thus confirming construct validity. Similarly, for MMS, the indicators show strong and significant loadings, particularly mms1 (β = 0.7371) and mms3 (β = 0.5622), which capture the cognitive and emotional burden of financial stress.

The general results confirm theoretical hypothesis that financial autonomy positively associates with financial well-being, and money management stress is one of the significant quantifiable constructs in individual financial behavior perception. The model provides empirical support arguing towards policy interventions aiming to enhance financial independence and lower the levels of stress as a method of promoting comprehensive financial health

8. Conclusion

1. The possession of financial skills creates the belief to apply financial tools as individuals are equipped with mathematical and analytical expertise to evaluate, and effectively judge financial products and services, while making informed comparisons within the complexity of the intricate financial environment.

2. This set of skills particularly analytical and budgeting promotes informed decision making and a positive approach with each successful financial decision creating confidence to make the next one thus building up expertise.

3. The expertise built up by systematic knowledge of financial products and services, including the ability to identify multifaceted financial risks, and apply it in decision making, in combination with Financial Autonomy induced behavioural characteristics in Urban Working Women enhances Financial Well Being.

4. Better Financial Autonomy and Financial Well Being reduce Money Management Stress in Urban Working Women. The outcome of Financial Skills, Financial Autonomy and Financial Well Being are fewer financial errors, ability to repay loans and comprehending and applying portfolio diversification in real time to build up wealth and achieve financial goals towards a more meaningful and less stressful life.

References

1. Anand, S., Mishra, K., Verma, V., & Taruna. (2021). Financial literacy as a mediator of personal financial health during COVID-19: A structural equation modelling approach. Journal of Financial Counselling and Planning.

2. Anand, S., Mishra, K., Verma, V., & Taruna. (2022). Measuring financial wellbeing with self-reported and bank-record data. International Journal of Financial Research, 13(1), 1–15.

3. Bahl, M. (2022). A comparative study to assess the financial decision-making among working women in India and Singapore. International Journal of Economics and Business Research, 21(3), 205–220.

4. Banerjee, T., & Roy, M. (2022). Financial literacy: An intra-household case study from West Bengal, India. Journal of Economic Studies, 49(3), 563–580.

5. Banerjee, T., & Roy, M. (2022). Financial literacy in the state of West Bengal: A study into its determinants with an impact analysis on financial inclusion and investment decision-making. Journal of Financial Education, 38(1), 27–50.

6. Gautama, C., Wadhwa, R., & Ramachandran, T. V. (2021). Examining behavioural aspects of financial decision-making: The working women perspective. International Journal of Behavioural Economics, 10(2), 83–96.

7. Ghosh, A. (2020). A study of the role of West Bengal government in women empowerment. Journal of Public Policy and Administration, 8(1), 75–92.

8. Jain, A. (2021). An empirical study on the investment behaviour of female investors in the city of Howrah, West Bengal. International Journal of Investment Research, 14(3), 145–158.

9. Joo, S. H. (2008). Personal financial wellness. in J. J. Xiao (Ed.), Handbook of consumer finance research (pp. xx–xx). Springer.

10. Kochar, A., Nagabhushana, C., & Sarkar, R. (2021). Financial access and women’s role in household decisions: Empirical evidence from India’s national rural livelihoods project. Development Policy Review, 39(1), 119–136.


Manag J Adv Res 2025;5(4)53
Bhattacharjya P, et al. Determinants of Financial Well Being

11. Kumar, P., Pillai, R., & Tabash, M. I. (2021). The interplay of skills, digital financial literacy, capability, and autonomy in financial decision-making and well-being. International Journal of Financial Studies, 9(3), 32. https://doi.org/10.3390/ijfs9030032

12. Kundu, K., & Das, J. K. (2021). Financial literacy among working women: A study in West Bengal. Journal of Women and Economy, 15(1), 58–75.

13. Mishra, L. (2022). Financial planning for educated young women in India. Journal of Financial Planning, 35(1), 25–37.

14. Organisation for Economic Co-operation and Development. (2009). Measuring financial literacy: Questionnaire and guidance notes for conducting an internationally comparable survey of financial literacy. OECD. https://www.oecd.org/finance/financial-education/49319977.pdf

15. Pauri, R. A., & Mehra, S. (2021). Financial attitude-based segmentation of women in India: An exploratory study. Journal of Consumer Marketing, 38(5), 543–558.

16. Panda, P. K. (2022). A study on the investment behaviour of the people of Malda town, West Bengal. Journal of Economic Behaviour, 40(2), 234–248.

17. Paul, R., Goswami, A., & Pal, B. (2021). Effect of socio-economic aspects on women workforce participation level in West Bengal, India. Asian Journal of Women’s Studies, 27(3), 329–344.

18. Roy, M. L., & Kadian, K. S. (2021). Participation in decision-making on farm and household-related economic activities: A study of West Bengal. Journal of Agricultural Economics, 73(4), 1028–1045.

19. Wagner, J., & Walstad, W. B. (2023). Gender differences in financial decision-making and behaviours in single and joint households. The American Economist, 68(1), 5–23. https://doi.org/10.1177/05694345231152267

Disclaimer / Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of Journals and/or the editor(s). Journals and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Manag J Adv Res 2025;5(4)54