




































Indian Journal of Finance and Banking 

 Vol. 9, No. 1; 2022 

                                       ISSN 2574-6081   E-ISSN 2574-609X 

Published by CRIBFB, USA 

83 

 

DETERMINANTS OF FINANCIAL WELLNESS OF RURAL 

HOUSEHOLDS IN THE HILL DISTRICTS OF UTTARAKHAND: 

AN EMPIRICAL APPROACH 

 
Ajay Purohit  

Research Scholar 
School of Management 

IMS UNISON University, Dehradun, Uttarakhand, India 

 E-mail: ajaypurohit_in@hotmail.com 

https://orcid.org/0000-0001-9369-6083 

 

Dr. Gaurav Chopra 

Assistant Professor  
School of Management 

IMS UNISON University, Dehradun, Uttarakhand, India 

E-mail: gauravschopra19@gmail.com 

https://orcid.org/0000-0002-1238-6831 

 

Dr. Parshuram G Dangwal 

Associate Professor  
School of Management 

IMS UNISON University, Dehradun, Uttarakhand, India 

E-mail: pgdangwal@gmail.com 

https://orcid.org/0000-0002-9504-1344 

 

 

Received: October 27, 2021      Accepted: December 30, 2021        Online Published: January 24, 2022  

 

DOI: 10.46281/ijfb.v9i1.1566            URL: https://doi.org/10.46281/ijfb.v9i1.1566 

 

 

ABSTRACT 

The study examines significant contributors to financial wellness for rural households in the hill districts 

of Uttarakhand. The study takes a sample of 666 respondents through multi-stage stratified random 

sampling from Self-Help Groups (SHGs) and Cooperatives members, and all are small and marginal 

farmers. A field survey was conducted using a structured questionnaire. Except for financial knowledge 

and numeracy, all other constructs, such as cash management, savings behavior, risk-credit 

management, financial attitudes, and financial wellness, were measured on a seven-point Likert scale 

ranging from strongly disagree to strongly agree. Exploratory Factor Analysis (EFA), Confirmatory 

Factor Analysis (CFA), and Structural Equation Modelling (SEM) were conducted on 628 valid samples 

using SPSS 23 and AMOS 23. The results from the analysis revealed that cash management, savings 

behavior, and financial attitudes significantly contribute to financial wellness. The study found that 

households have the reasonable financial knowledge and financial numeracy skills. The study also found 

that savings behavior has a mediating effect on the relationship between cash management and financial 

wellness. The study is useful for rural development stakeholders and policymakers to strategically focus 

on financial inclusion programs.  

mailto:%20E-mail:%20ajaypurohit_in@hotmail.com
mailto:gauravschopra19@gmail.com
mailto:pgdangwal@gmail.com


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Keywords: Financial Wellness, Financial Behavior, Financial Literacy, Financial Inclusion, Rural, Self-

Help Groups. 
 

JEL Classification Codes: D14, G51, G52, G53, I30. 

 

INTRODUCTION 

Financial wellness or financial well-being or economic well-being or financial satisfaction denotes 

financial situation or financial health. It is a multidimensional aspect and objective as well as subjective 

concept in nature (Vieira et al., 2021), (Iramani & Lutfi, 2021), (Tanoto & Evelyn, 2019), (Brüggen et 

al., 2017). Financial inclusion, financial behavior, financial attitude, financial literacy are other 

terminologies associated with financial wellness in multiple studies. Financially well households easily 

meet the current needs and deal with sudden needs of an individual or a household (Vieira et al., 2021), 

(Masenya & Dickason-Koekemoer, 2020), (Michael Collins & Urban, 2020), (Simonova, 2019), (CFPB, 

2017), (CFPB, 2015). Holistically, financial wellness is directly and indirectly connected to economic 

upliftment and an essential growth driver to achieve sustainable development goals (Wadhwa, 2020), 

(Rickard & Johnsson, 2018), (Klapper et al., 2016), (UNCTAD, 2015). Factors like demographic aspects 

(gender, education, etc.), income, savings, opportunities, accessibility, the package of practices, urban, 

rural, and others impact financial wellness.  

In the rural hilly areas, due to distinct geographical scenarios, situations are different from the 

plains. The plain area has more opportunities than the hills; therefore, high-income inequalities are 

reflected in plain and rural areas (Suryanarayana & Mamgain, 2017), (Mamgain & Reddy, 2015). 

Around 86% of geographical areas are under hilly terrain in the state, and 71.05% are covered under 

forest. 70.37% of the state population lives in rural areas and is primarily engaged in agriculture and 

allied activities (DES, 2020). Horticulture and agriculture are identified as growth drivers of the state 

economy in the state vision 2030 (GoUK, 2018). However, income from agriculture and allied activities 

is not significantly high at the individual household’s level because of less volume, high marketing cost, 

and other distinguishing factors of hills (Kandpal & Kavidayal, 2020). For economic growth and 

sustainable livelihood, households have organized in the Self-Help Groups (SHGs) at the village level 

and into Cooperatives at the cluster level.  The present study has been conducted with SHGs members 

from the hill districts of Uttarakhand. All members are small and marginal farmers (Note 1).  

State Rural Livelihood Mission (SRLM) and Integrated Livelihood Support Project (ILSP) are 

two main programs being executed in Uttarakhand. SRLM promotes women's SHGs exclusively (RBI, 

2019), whereas ILSP has more than 85% of women members in their groups (CPCU, 2020). SHGs 

followed the core concepts of ‘Panchasutras’ (Note 2) for cohesiveness, sustainability, and mitigating 

financial constraints in tough times. Under financial inclusion, they provide training and facilitate 

financial instruments e.g., accounts, investment, insurance e.g., PM Jeevan Jyoti Bima Yojana, PM 

Suraksha Bima Yojana, credit schemes e.g., Kisan Credit Card, Mudra loan, etc. (CPCU, 2020). 

The main objective of this study is to identify the significant factors behind financial wellness in 

the context of rural households in the hill districts of Uttarakhand. All households are members of SHGs, 

and Cooperatives and also come small and marginal farmers. To identify the construct, exploratory 

factor analysis (EFA), and confirmatory factor analysis (CFA) have been used. Further, structure 

equation model (SEM), and path analysis have been used to find the mediating role of savings behavior, 

and results are presented. 

 

LITERATURE REVIEW 

Financial Wellness 

Based on previous studies  (Botha & New, 2021), (OECD, 2020), (Mahdzan et al., 2020), (Heath et al., 

2018), (Predergast et al., 2018),  (CFPB, 2017), (CFPB, 2015) financial wellness refers to household’s 

(i) financial health (like income, savings) to fulfill daily and emergency requirements in current as well 

as future, (ii) financial security and financial freedom in the life course, and (iii) ability of effective 

financial management. (Masenya & Dickason-Koekemoer, 2020), (Heo et al., 2020) study revealed that 

financial wellness positively correlates with satisfaction with life, whereas life satisfaction refers to an 



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individual’s satisfaction towards happiness and subjective well-being. In a nutshell, financial wellness 

is a reflection of fulfilling the household’s financial necessities, enhancement of economic status, better 

living conditions, cost-effective package of financial practices and perception of satisfaction.  

According to (PwC, 2020), (PwC, 2014) employee financial wellness survey, financial wellness 

is significantly correlated with financial literacy for decision-making and financial behavior towards 

savings, investments, credit, and others. Multiple reports and research (Botha & New, 2021), (OECD, 

2020), (Heath et al., 2018), (Gautam & Andersen, 2016) (Brüggen et al., 2017), (CFPB, 2017), 

(Coşkuner, 2016), (CFPB, 2015) examined financial wellness with multiple corresponding constructs - 

financial behavior, financial attitude, financial knowledge, financial solvency, income, education, and 

individual characteristics. 

    

Financial Behaviors 
Financial behavior is a kind of behavior that influences taking a correct financial decision about cash, 

credit, risk, and savings (IGI-Global, 2021b), (Iramani & Lutfi, 2021), (Zulaihati & Widyastuti, 2020). 

Financial behavior is a direct and indirect influencer of financial wellness and is associated with financial 

literacy, income, gender, marital status, homeownership, education, to name a few. Innovative practices 

of cash and savings reduce the consequences of any emergency or mishap. The financial behavior of 

rural households is significantly correlated with financial literacy and savings (Murari, 2019). Therefore, 

financial behaviors can be measured through one’s practice and perception, including cash management 

in day-to-day life, savings for the future, risk, and credit management to reduce the debt and mitigate 

the financial losses. 

 

Cash Management 

Cash management is maintaining cash in hands and effectively utilizing income so that the person can 

be inclined towards achieving future goals while fulfilling the present needs and realizing future needs. 

Every household prepares a tentative plan or budget for recurring expenses and other investment 

purposes (Widyastuti et al., 2020), (Murari, 2019). Cash management is a practice of allocation and 

distribution of income for day to day expenses, savings for futuristic goals, and assets creation which 

has a significant impact on financial wellness (Adiputra, 2021), (Fazli Sabri et al., 2020), (Wahab & 

Yaacob, 2018), (Ameliawati & Setiyani, 2018). Thus, from the pioneering studies, the following 

hypothesis has been formulated: 

 

H1: Cash management has a significant impact on financial wellness. 

 

Savings Behaviour 

It is natural to set aside a portion of one's earnings for future aspirations and emergencies. Sufficient 

savings reduces unexpected social and financial shocks (Despard et al., 2020), (Gaisina & Kaidarova, 

2017). Banks and Post Offices are common financial institutions for savings. SHG members also save 

regularly in their respective groups. Generally, it is small in terms of amount, but regular as decided in 

the group like weekly or monthly. Group savings have been utilized for specific and prominent needs 

(DAY-NRLM, 2017). Households also save their cash at home and deposit savings with friends, family 

members, moneylenders (Coleman & Wynne-williams, 2006). Several researchers (Gaisina & 

Kaidarova, 2017), (Nguyen et al., 2017), (Lee & Hanna, 2015) examined saving behavior and revealed 

that it has a significant influence on financial wellness. Therefore, based on literature support, we found 

savings are self-actualization of financial wellness. Thus, from the literature, the following hypothesis 

has been formulated: 

 

H2: Savings behavior has a significant impact on financial wellness. 

 

Risk and Credit Management 

Risk management is conceptualized to reduce the impact of any jolt from any risk in life, health, assets, 

crops, livestock, and others. (Robb & Woodyard, 2011) identified risk and credit management are best 



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financial practices. Unexpected financial risk is reduced through insurances and increased savings 

(Murugesan & Manohar, 2020), (Woodyard, 2013), and  (OECD, 2013). Insurance is a one-time or 

regular investment; however, it requires income, accessibility, and financial literacy. Low-income 

households face different risks and shocks e.g., income volatility, livelihood risks, health, weather 

(Vishwanath et al., 2020). They can’t afford insurance  (Rampini & Viswanathan, 2016). However, the 

government is promoting credit cum insurance schemes, which are affordable to low-income 

households. As per need, rural households take loans from SHG at a nominal interest rate, which is 

extremely low compared to other sources. Still, households avoid taking loans except in emergencies. 

Overall, high credit, unforeseen risk affect savings, increase stress, and impact financial wellness. Based 

on the literature, the following hypothesis has been formulated: 

 

H3: Risk-credit management has a significant impact on financial wellness. 

 

Financial Literacy 

“National Strategy for Financial Education 2020-2025” (RBI, 2021) indicates that “the achievement of 

Financial Literacy empowers the users to make sound financial decisions which result in financial well-

being of the individual.” According to (Chong et al., 2021), (Stella et al., 2020), (N. Ismail & Zaki, 

2019), (OECD, 2018), (Topa et al., 2018), (Skagerlund et al., 2018), (Jayanthi & Rau, 2017), and (Bilal 

& Zulfiqar, 2016) financial literacy is one’s perception and knowledge about financial resources, 

effective utilization of financial instruments and financial decision-making skills towards economic 

sustainability and improvement during one’s life course. It is a set of skills influenced by knowledge, a 

package of practices, awareness, and practices in the community, accessibility of resources, education, 

income, and self-actualization. Definitions indicate that the two core elements of financial literacy are 

financial knowledge and financial attitude, and they complement each other. 

 

Financial Knowledge 
Previous research revealed a strong association among financial knowledge, financial behavior, and 

financial wellness (Adiputra, 2021), (Stella et al., 2020), (Choudhary & Kamboj, 2017), (Gaisina & 

Kaidarova, 2017), (Kamakia et al., 2017), and  (Potrich et al., 2016). Financial knowledge helps to make 

profitable financial decisions, effective use of financial products and services, improve financial 

behaviors towards sustainable economic growth and happiness  (Atmaningrum et al., 2021), (OECD, 

2020), (Nguyen et al., 2017), (Aren & Aydemir, 2014). Training, capacity buildings, and exposures 

mainly in financial products and services increase financial knowledge. It is necessary for all to take a 

correct financial decision in terms of financial products and services that increase financial wellness (N. 

Ismail & Zaki, 2019), (Kamakia et al., 2017), (Phani Kumar, 2016), and (Muleke & Muriithi, 2013). 

(Zhan et al., 2006) assessed pre-post financial training of low-income population and suggested that 

financial literacy training significantly increases economic management practices that lead to financial 

wellness. 

  

Financial Attitude 
A financial attitude is a perception or tendency towards financial products and services (IGI-Global, 

2021a). Financial attitude influences financial management, which impacts future wellness  (RBI, 2021), 

(OECD/INFE, 2013). It means that a positive financial attitude towards budgeting, savings, and money 

has positive financial behavior. It varies from person to person, depending upon financial knowledge as 

well as demographic variables. Several researchers (Adiputra, 2021), (Abdullah et al., 2019), 

(Ameliawati & Setiyani, 2018), (Forouzani & Mohammadzadeh, 2018), (Garber & Koyama, 2017), 

explained the significant relationship between financial attitude and financial wellness. (Potrich et al., 

2016) explained in their model that financial knowledge and financial attitude have positive impacts on 

financial wellness. Based on the literature review, the following hypothesis has been formulated: 

 

H4: Financial attitude has a significant impact on financial wellness. 

 



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Demographic Factors 

Demographic cohorts like age, gender, education, income, family size, assets, and socio-economic status 

always influence financial wellness and its other contributors. (Collins & Urban, 2020) the study 

explained that age and income have a significant impact on financial wellness and relative variables. 

(Woodyard & Robb, 2012) examined gender and age-wise financial satisfaction and financial behavior.  

(Vosloo et al., 2014) study indicates that less income and less or lack of financial benefits, higher debt 

levels create financial stress, which impacts negatively on a person performance at work. (N. Ismail & 

Zaki, 2019) explained that factors like employment opportunities, income instability, family size, 

financial self-efficacy, and financial help-seeking behavior impact the financial wellness of the low-

medium class. (Kesavan, 2020) recommended that the regular and multiple sources of income like 

agriculture, livestock, and community works support catalyze financial inclusion. Based on the literature 

review, demographic cohorts like gender, age, education, land size, income, and savings were included 

in the study.  

 

Savings Behavior as a Mediator 

The primary source of income is agriculture and allied activities in the rural areas. Revenue from these 

sources varies due to a number of factors like production, market, and weather. Hence, the income is 

irregular, and savings is one of the crucial sources in every situation for all households. (Lulaj et al., 

2021), (Jin et al., 2021), (S. Ismail et al., 2018), (Shin & Kim, 2018), (Magendans et al., 2017) research 

indicated that savings play an important role in emergencies and significant contribution to financial 

wellness. (Gjertson, 2016) the study found that savings are a kind of insurance of low-income 

households which protects against hardship. (Iramani & Lutfi, 2021) explained that a household’s 

savings and income are positively correlated with their financial wellness. (Wieliczko et al., 2020) 

highlighted in their study that savings as a growth driver of sustainable development of farmers and a 

core pillar of financial security. (Martin & Hill, 2015) establish financial situation- poverty-well-being 

relationship, and found savings is a core factor of well-being. Briefly, we can conclude that effective 

cash management and positive savings behavior increase savings, and subsequently, financial wellness. 

As such, we predict the following mediation hypotheses: 

 

H5: Savings behavior mediates the relationship between cash management and financial wellness. 

 

RESEARCH METHODOLOGY 
The primary objective was to identify the groups of factors that significantly explain financial wellness, 

especially in the context of rural households in hill districts of Uttarakhand. All are members of SHGs 

and Cooperatives and also come under small and marginal farmers. The study was conducted in the 21 

hill blocks from hill districts of Uttarakhand through multi-stage stratified random sampling. Total 666 

samples were collected from upper hills, middle hills, and foothills. The Survey method was used to 

collect the data with the help of a structured questionnaire. A structured questionnaire was used to gather 

data from the respondents. The questionnaire was developed through literature review and translated 

into the native language, “Hindi”. To improve the questionnaire’s accuracy, a pilot test on 70 

respondents was conducted with rural households, and related modifications have been implemented. 

Then, a sample of 50 respondents, distinct from those included in the pilot test, were asked to pre-test 

the questionnaire. Other than the demographic cohort, the questionnaire consisted of 5 major sections, 

i.e., cash management, savings behavior, risk-credit management, financial knowledge, and financial 

attitude. All sections except financial knowledge were measured on a seven-point Likert scale ranging 

from strongly disagree to strongly agree. After data cleaning (missing values, outliers), 628 responses 

were analyzed using SPSS 23 and AMOS 23.  

 

 

 

 



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Table 1. Demographic features 

 

Measure Items Frequency % 

Gender Male 79 12.6 

Female 549 87.4 

Total 628 100.0 

Education 

Qualification 

Less than Eight Class 182 29.0 

Intermediate 300 47.8 

Graduate 92 14.6 

Postgraduate 54 8.6 

Total 628 100 

Age 20 to 30 87 13.9 

30 to 40 273 43.5 

40 to 50 171 27.2 

50 to 60 80 12.7 

More than 60 17 2.7 

Total 628 100 

Average Monthly 

Income (including all 

sources) 

Less than INR 6000 247 39.0 

INR 6000 to INR 9000 189 30.1 

INR 9000 to INR 12000 89 14.2 

INR 12000 to INR 15000 49 7.8 

More than INR 15000 54 8.6 

Total 628 100 

Average Monthly 

Savings (including all 

sources) 

Less than INR 600 257 40.9 

INR 600 to INR 900 150 23.9 

INR 900 to INR 1200 80 12.7 

INR 1200 to INR 1500 54 8.6 

More than INR 1500 87 13.9 

Total 628 100 

Land Size (in hectare) Less than 0.04  100 15.9 

Between 0.04 to 0.08 146 23.2 

Between 0.08 to 0.120 155 24.7 

Between 0.120 to 0.160 118 18.8 

More than 0.160 109 17.4 

Total 628 100 

Who is responsible 

for making major 

financial decisions 

(like investment, 

purchase, etc.) in your 

family? 

Myself  127 20.2 

Wife / husband 144 22.9 

Both, after discussion 278 44.3 

Elder family Members 79 12.6 

Total 628 100 

 

DATA ANALYSIS AND RESULTS 
Demographic data Table-1 indicates 87.4% of respondents were female respondents. 76.8% have 

education qualification up to intermediate. 43.5% of the respondents were between the ages of 30 and 

40. About 69.1% of the respondents had an average monthly income of less than INR 9000, and 64.8% 

had an average monthly saving of less than INR 900. Interestingly, the financial decision in 44.3% 

family is taken after discussion and mutual consent of husband and wife.  

 

 



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Table 2. Financial Knowledge 

 

 Items Yes (%) No (%) 

Financial 

Knowledge 

FL1K1 79.6 20.4 

FL2K2 86.6 13.4 

FL2K3 93.2 6.8 

FL2K4 87.9 12.1 

FL2K5 78.3 21.7 

 Items Correct Answer (%) Incorrect Answer (%) 

Numerical 

Skills 

FL2NS1 91.9 8.1 

FL2NS2 73.7 26.3 

FL2NS3 87.9 12.1 

FL2NS4 42.5 57.5 

 

Table-2 indicates that 79.6% of respondents were aware that if they save their savings in Bank / 

Post office, they will get more benefits than other informal arrangements. Interestingly, 86.6% of 

respondents know about the interest rate of fixed deposits. 93.2% of respondents know about PM Jan 

Dhan Account, and 87.9% of respondents know the details of PM Kisan Samman Nidhi Scheme. The 

results indicate that respondents have good financial knowledge. It reflects the outcome of training, 

capacity-building programs, and other activities implemented under financial inclusion by different 

institutions (RBI, 2021), (Wadhwa, 2020).  

91.9% of respondents correctly calculated day-to-day financial calculations. 73.7% of 

respondents correctly calculated group savings. The results indicate that the members of informal 

savings groups actively participate in the group meetings. 87.9% of respondents can calculate dividends, 

which indicates that all shareholders know how dividends are calculated. However, only 42.5% of 

respondents correctly calculated simple interest, and 52.4% gave mathematically wrong answers.  

Overall, the study shows that the rural households in the hill districts have financial knowledge. 

 

Reliability Test 

The quality and consistency of the survey were further assessed using Cronbach's alpha (.820) which is 

greater than .7, hence acceptable (George & Mallery, 2016).  

 

Table 3. Reliability statistics 

 

Cronbach's Alpha N of Items 

0.820 19 

 

Exploratory Factor Analysis 

EFA has been conducted for dimension reduction through varimax, principal component analysis, and 

rotated component matrix. Total 19 items with a sample of 628 were used for analysis. Five factors were 

extracted through eigenvalue (>1) and scree test (Figure 1) with the significant (> 0.40) loadings (Hair, 

Sarstedt, et al., 2017). Table-4 states that all assumptions of EFA are met. All the items have been loaded 

appropriately in the factor analysis (Table-5) and have passed the reliability test.  Three items have been 

grouped into financial wellness, four items in cash management, three items in attitude towards savings, 

five items in credit-risk management, and four items in financial attitude. 

 

 

 



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Table 4. Assumptions for EFA 

 

 Conditions Reference  (Chopra et al., 2019) 

Sample size is 628 n > 200 (Kyriazos, 2018) 

Barlett’s test of sphericity is significant p < 0.001 (Watkins, 2018) 

KMO value is 0.879 measure of 

sampling adequacy 

> 0.70 (Watkins, 2018) 

Satisfactory communalities values > 0.50 (Field, 2018) 

Total variance explained is 74.685% > 50% (Podsakoff & Organ, 1986) 

The variance for the first factor is 

17.461% 

< 50% (Podsakoff & Organ, 1986) 

 

 
Figure 1. Scree Plot 

 

Table 5. Rotated Component Matrix 

 

  Component   

1 2 3 4 5 Cronbach's Alpha 

FW1 
  

.879 
  

0.935 

FW2 
  

.875 
  

FW3 
  

.788 
  

FB1CM1 
 

.726 
   

0.871 

FB1CM2 
 

.686 
   

FB1CM3 
 

.858 
   

FB1CM4 
 

.843 
   

FB2S1 
    

.755 0.831 

FB2S2 
    

.733 

FB2S3 
    

.805 

FB3RCM1 .776 
    

0.863 

FB3RCM2 .698 
    

FB3RCM3 .892 
    

FB3RCM4 .901 
    

FB3RCM5 .738 
    

FL3A1 
   

.809 
 

0.864 

FL3A2 
   

.838 
 

FL3A3 
   

.870 
 

FL3A4 
   

.788 
 



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Rotation Sums of 

Squared Loadings 

17.461 33.063 48.633 63.105 74.685  

Extraction Method: Principal Component Analysis.  Rotation Method: Varimax with Kaiser 

Normalization. a. Rotation converged in 5 iterations. 

 

Confirmatory Factor Analysis 

According to (Xia & Yang, 2019), (Hair, Hult, et al., 2017), and (Kline, 2016) studies, the model must 

have acceptable convergent and reliability validity as well as model-fit indices through first-order CFA.    

 
Figure 2. Confirmatory Factor Analysis 

 

The Goodness of Fit Indices 

The recommended fit indices' values and their threshold limits are presented in Table-6, which shows 

that all values meet the threshold criteria. However, p-value of χ2 < 0.05, which may be because of the 

large sample size (>200) (Kline, 2016), (Bentler & Bonett, 1980). However, absolute fit indices, relative 

fit indices, and non-centrality-based indices values make the model acceptable. 

 

Table 6. Goodness of fit indices 

 

Fit index Limit Values in the 

present study 

References 

(Hooper et al., 2008), 

(Chopra & Madan, 2021), 

(Gaskin, 2021) 

Acceptability 

Absolute fit indices 

χ2  495.819   

df  142   

p value > 0.05 0.000  No 

χ2 / df 1.00 - 5.00 3.492 (Kline, 2016) Yes 



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SRMR < 0.08 0.063 (Hu & Bentler, 1999) Yes 

GFI > 0.90 0.923 (Hu & Bentler, 1999) Yes 

AGFI > 0.80 0.897 (Hu & Bentler, 1999) Yes 

Relative fit indices 

NFI > 0.80 0.937 (Bentler & Bonett, 1980) Yes 

PNFI > 0.50 0.778 (Bentler & Bonett, 1980) Yes 

IFI > 0.90 0.954 (Bollen, 1990) Yes 

TLI > 0.90 0.945 (Tucker & Lewis, 1973) Yes 

Non-centrality-based indices 

CFI > 0.90 0.954 (Hu & Bentler, 1999) Yes 

PGFI > 0.50 0.690 (Mulaik et al., 1989) Yes 

RMSEA < 0.08 0.063 (Xia & Yang, 2019) Yes 

 

Convergent Validity 
According to (Hair, Hult, et al., 2017), the composite reliability of all the constructs must be more than 

0.7, for attaining the construct reliability. The average variance extracted (AVE) required is above 0.500, 

and MSV must be less than AVE for convergent validity. All recommended conditions are passed for 

the proposed model (Table 7), so we can conclude that the proposed model has a convergent validity. 

 

Table 7. Convergent validity parameters 

 

Construct Items Factor 

Loading 

(above 0.5) 

Composite 

reliability 

(above 0.7) 

AVE 

(above 

0.5) 

MSV (less 

than AVE) 

Financial Wellness 

(FW) 

FW1 0.928 0.940 0.840 0.411 

FW2 0.959 
   

FW3 0.860 
   

Cash Management 

(CM) 

FB1CM1 0.801 0.872 0.631 0.463 

FB1CM2 0.773 
   

FB1CM3 0.823 
   

FB1CM4 0.778 
   

Savings Behavior (SB) FB2S1 0.927 0.840 0.642 0.463 

FB2S2 0.818 
   

FB2S3 0.631 
   

Risk-credit 

Management (RCM) 

FB3RCM1 0.667 0.865 0.572 0.015 

FB3RCM2 0.564 
   

FB3RCM3 0.917 
   

FB3RCM4 0.929 
   

FB3RCM5 0.626 
   

Financial Attitude 

(FA) 

FL3A1 0.819 0.869 0.624 0.162 

FL3A2 0.797 
   

FL3A3 0.824 
   

FL3A4 0.714 
   

 

Discriminant Validity 
Discriminant validity expresses the uniqueness of each construct from other constructs by empirical 

standards (Hair, Hult, et al., 2017). To examine discriminant validity, we analyzed AVE > MSV, and 

the square root of AVE is greater than inter-construct correlations (Table-8). Thus, we can conclude that 

all the constructs in the proposed model have discriminant validity.  

 



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Table 8. Discriminant validity 

 

  Financial 

Wellness 

Cash 

Management 

Risk-credit 

Management 

Savings 

Behavior 

Financial 

Attitude 

Financial Wellness 0.917 
   

 

Cash Management 0.637 0.794 
  

 

Risk-credit Management 0.029 0.048 0.756 
 

 

Savings Behavior 0.641 0.680 0.122 0.802  

Financial Attitude 0.402 0.349 -0.007 0.368 0.790 
 

Structured Model 
After verify model fit, and validity, path analysis has been run on AMOS 23. Figure 3 shows the results 

of a structure model drawn on AMOS graphics. The goodness of fit indices was Chi-square/df = 3.593, 

SRMR = 0.067, GFI = 0.920, AGFI = 0.894, NFI = 0.934, PNFI = 0.787, IFI = 0.952, TLI = 0.942, CFI 

= 0.951, PGFI = 0.697, and RMSEA = 0.64. Table-9 presents standardized regression weights of all the 

relationships present in the model. Apart from RCM, all values are significant (p-value < 0.05). 

Therefore, hypothesis H1, H2 and H4 are accepted and H3 rejected. Therefore, we can conclude that 

cash management, savings behavior, and financial attitude have significant impact on financial wellness. 

 

Table 9. Standardized Regression Weights: hypothesis testing 

 

Hypothesis Estimate S.E. C.R. P Acceptance / rejection 

H1 – “Cash management has a significant impact on financial wellness.” 

FW <--- CM 0.346 0.104 6.441 *** Accepted 

H2 – “Savings behavior has a significant impact on financial wellness.” 

FW <--- SB 0.355 0.037 16.418 *** Accepted 

H3 – “Risk-credit management has a significant impact on financial wellness.” 

FW <--- RCM -0.290 0.110 -0.908 
0.36

4 
Rejected 

H4 – “Financial attitude has a significant impact on financial wellness.” 

FW <--- FA 0.152 0.070 4.214 *** Accepted 

 

 
Figure 3. Structure Model 



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Mediation Analysis 
The mediating effect of the savings behavior on the financial wellness of rural households has been 

tested using a bootstrapping method in AMOS (Kline, 2016), (Hopwood, 2007). The results of 

bootstrapping methods have been shown in Table 10. The total effect of cash management on financial 

wellness was significant (β = .591, p = 0.002), such that better cash management led to better financial 

wellness. The direct effect of cash management on financial wellness was significant (β = .346, p = 

0.001), and the indirect effect of cash management on financial wellness in the presence of savings 

behavior was also significant (β = .245, p = 0.001). The p-value of indirect effect and total effect are > 

0, hence partial mediation exists (Aguinis et al., 2017). The Sobel z-value of 6.4790 > 2.58 with p-value 

of 0.0189 (less than 0.05) indicated that the mediation effect is significant at 95% confidence interval 

(Abu-Bader & Jones, 2021), (Preacher & Hayes, 2008), (Baron & Kenny, 1986). The results confirmed 

that savings behavior significantly mediates the relationship between cash management and financial 

wellness. Thus, hypothesis H5 is accepted, and we can conclude that savings behavior has a partial 

mediating effect on the relationship between cash management and financial wellness. 

 

Table 10. Results of bootstrapping for mediation analysis 

 

Type of effect Standardized beta p-value Remark 

Total effect .591 .002 Significant total effect 

Direct effect .346 .001 Significant indirect effect 

Indirect effect .245 .001 Significant direct effect 
 

DISCUSSION AND CONCLUSION 
The study investigated significant contributors to financial wellness in rural households in the hill 

districts. These households are members of SHGs and cooperatives, and all are small and marginal 

farmers. The demographic statistics indicate that most of the members in SHGs and cooperatives are 

female (87.4%). 76.8% of members were intermediate and below educated, 70.7% were between the 

age group of 30 to 50, average monthly income of 69.1% members was below INR 9000, and 64.8% 

had average monthly savings less than INR 900 per month. Landholding data validate that all are small 

and marginal farmers. Reliability analysis (Cronbach’s alpha = .820 > 0.7) of all items confirms the 

internal consistency of items. Through exploratory factor analysis (EFA) and confirmatory factor 

analysis (CFA), five constructs such as financial wellness, cash management, savings behavior, risk-

credit management, and financial attitude were identified from 19 items. The goodness of fit indices, 

convergent validity, and discriminant validity support the analysis.  

To test the hypothesis, path analysis was conducted. Results revealed that cash management, 

savings behavior, and financial attitude are significant impacts on financial wellness, which is supported 

by the hypothesis. The findings are substantiated with the recent literature (CHAVALI et al., 2021),  

(Gichuhi & Mwangi, 2021), (Maina et al., 2020). The results indicate that if households have positive 

attitudes towards financial practices and manage their income effectively with proper and regular 

savings, their financial wellness will increase. The results also indicate that risk-credit management does 

not significantly impact financial wellness. However, all items of risk-credit management were loaded 

significantly in EFA and CFA. It indicates that rural households are aware of insurance and credit 

schemes, but they do not take full advantage of such schemes. The study inspects the mediating effect 

and has found that savings behavior has a mediating effect on the relationship of cash management to 

financial wellness.  

According to (Anand et al., 2021), (Word Bank, 2020) financial knowledge contributes to the 

financial wellness of rural households and makes them more robust for tough times. The study also 

found that rural households have sound financial knowledge about different financial schemes and 

welfare programs. The results show that households know the essential difference between financial 

instruments and are well skilled in day-to-day numerical calculations. The results also found that the 

financial decision is mainly taken after mutual consent of both husband and wife, demonstrating 



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women's empowerment. These results refer that intensive development activities, including financial 

literacy programs, and the package of financial practices, significantly impact financial wellness. The 

results show that SHGs and cooperatives play a significant role in implementing financial inclusion 

programs  (Omar & Inaba, 2020), (Wadhwa, 2020). They not only support income-generating activities 

but also facilitate knowledge capitalization. Through SHGs, households’ savings behavior has increased 

directly or indirectly, and female participation in financial decision-making has also increased. The study 

concludes that cash management, savings behavior, financial knowledge, and financial attitude lead to 

the financial wellness of rural households in hill districts.  

 

PRACTICAL IMPLICATIONS 
The study identified factors of financial wellness through theoretical and empirical analysis. The 

research findings of the study can be more relevant in the areas of rural development, banking, 

agriculture, and allied sectors. This study can assist in improving the livelihood programs of rural areas, 

including financial inclusion, especially those implemented in rural hilly areas. This research finding 

will also support the policymakers to emphasize more on sustainable livelihood opportunities and 

customized financial inclusion in the hill districts, which will increase financial knowledge and 

subsequently improve the financial behavior, and financial attitude. Frequent capacity building, regular 

information dissemination, and service delivery mechanism can also improve the risk-credit schemes. 

Overall, an increase in financial knowledge, income, and savings is positively related to economic 

upliftment and contributes to achieving sustainable development goals.  

 

RESEARCH LIMITATION AND FUTURE RESEARCH DIRECTION 
This research has highlighted that financial wellness is a function of cash management, savings behavior, 

and financial attitude, where savings behavior mediates the relationship between cash management and 

financial wellness. This study has some limitations. The research has been conducted on SHGs and 

Cooperatives members only. Furthermore, the seasonal migration between rural and semi urban areas 

of rural households in hill districts has not been considered. These two aspects can be considered for 

future research. Food security and health affect everyone in remotest rural areas and need to be studied.  

              

AUTHOR CONTRIBUTIONS 

Conceptualization: Ajay Purohit, Gaurav Chopra, Parshuram G Dangwal 

Data Curation: Ajay Purohit, Gaurav Chopra, Parshuram G Dangwal 

Formal Analysis: Ajay Purohit, Gaurav Chopra, Parshuram G Dangwal 

Funding Acquisition: Ajay Purohit 

Investigation: Ajay Purohit, Gaurav Chopra, Parshuram G Dangwal  

Methodology: Ajay Purohit, Gaurav Chopra, Parshuram G Dangwal  

Project Administration: Gaurav Chopra, Parshuram G Dangwal 

Resources: Ajay Purohit 

Software: Ajay Purohit 

Supervision: Gaurav Chopra, Parshuram G Dangwal 

Validation: Ajay Purohit, Gaurav Chopra, Parshuram G Dangwal 

Visualization: Ajay Purohit 

Writing – Original Draft: Ajay Purohit 

Writing – Review & Editing: Ajay Purohit, Gaurav Chopra, Parshuram G Dangwal 

                                             

CONFLICT OF INTEREST STATEMENT 

The authors declare that they have no competing interests.  

 

ACKNOWLEDGEMENT 

All authors contributed equally to the conception and design of the study. 

 
 



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NOTES 

Note 1. Small and Marginal farmers who have less than 2-hectare operational agriculture landholdings. 

The average landholding in Uttarakhand is 0.85 hectares (PIB, 2019). 

Note 2. Panchasutras - Regular meetings; Regular savings; Regular inter-loaning; Timely repayment; 

and Up-to-date books of accounts (RBI, 2019).   

 

 

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