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American Journal of Economic and
Management Business
e-ISSN: 2835-5199
Vol. 2 No. 4 April 2023
FINANCIAL INCLUSION POLICY AND PLANNED TRIBES IN
MAYURBHANJ DISTRICT, ODISHA
Rupak kumar Tung
The Maharaja Sriram Chandra Bhanja Deo University (MSCB), India
Email: tungrupakkumar@gmail.com
Abstract
The government's policy of opening bank branches in tribal areas and funding priority
areas is very welcome. Facilities offered in these tribal areas include basic savings bank
deposit account (BSBDA) and no-frills deposit account opening, making it easy for
customers to know their requirements. Self-help group bank liaison programs are another
way to increase the income of poor households by providing financial services through
public institutions. Macro-level data analysis showed high scores in Chhattisgarh,
Jharkhand, Rajasthan, Madhya Pradesh, Andhra Pradesh, Maharashtra, Orissa, Gujarat,
Tamil Nadu and Karnataka. rice field. Financial inclusion is considered achieved. At the
same time, it was low in Bihar, Harayana, Assam, Kerala, Punjab, West Bengal and Uttar
Pradesh. Government programs such as the MGNREG program, microcredit facility,
PMJDY, old age pension, SHG bank account, and Kisan credit card have had a significant
impact on the economic status of the tribesmen in some villages in Mayurbhanj district.
The majority of selected Indigenous households have bank accounts, and program
rewards are paid through each program beneficiary's individual bank account. The
gradual introduction of government and banking programs contributes significantly to the
success of indigenous integration
Keywords: financial inclusion policy, PMJDY, financial services, Tribes, FII, FIP
This article is licensed under a Creative Commons Attribution-ShareAlike 4.0
International
INTRODUCTION
According to economic literature, "inclusive growth" refers to the equitable
distribution of resources that benefits every segment of society. The achievement of the
equality goal in growth is made possible by the participation of all societal segments and
geographical areas in economic progress and in reaping its advantages (Dixit & Ghosh,
2013). Economic growth with equal opportunity for all is referred to as the inclusive
growth concept. It simply entails generating possibilities for progress and making them
available to everyone, especially the underprivileged (Ali & Zhuang, 2007).
Since the inception of national plans, India has stressed the role of finance in
encouraging equitable progress. The creation of rural cooperatives, Regional Rural Banks
Rupak kumar Tung
145
(RRB), National Bank for Agriculture and Rural Development (NABARD),
nationalisation of commercial banks, emphasis on social banking, rural credit, priority
sector lending, Lead Bank Schemes, interest rate ceilings, subsidies, etc., are a few
significant steps taken in this direction. Even now, after all of India's policy efforts to
promote financial inclusion, official banking services still haven't reached a significant
portion of households, and the poor and outcasts of society are still unable to access any
financial services.
Review of Literature:
1. Onta-Bhatta, (2000) The homeless and underprivileged are given access to economical
meal services by street vendors. The availability of regional and local delicacies at
these kiosks is another factor. The mechanics of the city's daily betting and the poor's
food vending machine supply. Because it contributes to the availability of affordable
food for the urban populace, urban street food survives.
2. Singh et al., (2020) The project will take steps to support community organisations
technically, create business plans for providers to enter the market, and collect and
disseminate best practises from throughout the nation. It details what you require.
3. Bhoi et al., (2022), examines how street vendors perceive digital payments and how
they affect the success of their businesses. Data will be gathered for this purpose from
Cuttak, Kurda, and Berhanpur, three Tier 2 cities in Orissa, utilising both structured
questionnaire and interview methodologies. To fully achieve the aforementioned
goals, this empirical study also includes both primary and secondary data.
4. Tung, (2023) The report makes an effort to examine financial inclusion in all of
Odisha's districts on a comprehensive basis. The current study examines the financial
inclusion of Odisha at the district level for the years 2010 to 2020 using two variables:
the number of branches and the number of bank accounts. The chosen variables
represent, at least generally, how the banking business is distributed and, subsequently,
how much it is present or absent. While a deposit account shows how to utilise and
access banking, the distribution of branch locations shows how deeply people are
incorporated into the financial system. Thereafter, individual indices are built for each
component, resulting in the composite index known as the Index of Financial Inclusion
(IFI).
The socioeconomic profile (the main respondents of the survey) was widely
discussed in his 29 terms in Baripada city, based on field data. According to a preliminary
report from the 2011 Indian Census, Baripada has a population of 110,058, of which
57,008 are male and 53,050 are female. Baripada City has 110,058 inhabitants. The
city/city has 116,874 inhabitants, of which 60,535 are male and 56,339 are female. Also,
in the education sector, there are a total of 89,421 illiterate people in Baripada city, of
which 48,388 are men and 41,033 are women. Baripada City has an average literacy rate
of 89.31% with male and female literacy rates of 93.45 and 84.88 respectively.
By investigating whether social work professions can contribute to financial
literacy, Designated Tribes can develop an understanding and knowledge of financial
literacy (Anderson et al., 2013). The contribution of social work to general financial
education can be justified in terms of vocational theory. Social workers should promote
financial education to alleviate poverty by connecting economically vulnerable people to
key financial education providers.
RESEARCH METHODS
American Journal of Economic and Management Business
Vol. 2 No. 4 April 2023
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The information was gathered from both primary and secondary sources This study
is descriptive and analytical in nature as it aims to describe the situation of tribes in terms
of access to banking services in Baripada city, Mayurbanji district, Odisha. Field studies
are conducted for research purposes. A sample size of 360 is obtained and responses are
collected in a structured timeline questionnaire. Researchers determined the samples
using practical sampling methods. The scheduled survey consists of 25 questions (A. S.
Singh & Masuku, 2014). Quantitative methods are used to analyze the collected data.
Secondary data were collected from secondary sources such as websites, news channels,
newspapers and government, statistical reports.
For categorical data, data were summarised and assessed using frequency and
percentages. Mean, Standard Deviation, and Median were used to analyse interval data
and rating scales. The economic and social impact of financial inclusion on rural and
urban households has been assessed using multiple regression analysis.
In the study, the total score of the individual sub-components of the constructs was
obtained by adding up the scores of each question falling under those components,
followed by standardisation and sorting out using the property of normal distribution,
while measuring the components of financial inclusion and its impact on socioeconomic
status. The component of financial inclusion and its impact was measured independently,
while the final component of inclusive growth was considered dependent. They were
evaluated and classified as average, below average, and above average using normal
distribution and percentile values.
The above mentioned objectives have been verified by the application of Chi-
Square test (x^2) for observed results with expected results, T test for compare the means
of two groups and Eigenvalues for reducing dimension space.
The Logit model was used in this quantitative analysis because it captures the
persistence of dependent variables with binary yes or no outcomes (Alemayehu, 2014).
In this context, variables with binary outcomes are financial inclusion. Whether the
respondent is financially involved. In this study, financial inclusion is measured by
account availability and frequency of access to financial services
RESULT AND DISCUSSION
Observations on the Nature, Extent, and Impact of Financial Inclusion in Rural
and Urban Populations.
Table 1 :Distance as a Barrier to Banking Services
Distance as barrier to banking services
Rural
Urban
Total
No
74.8
96.1
85.45
Yes
25.2
3.9
14.55
Total
100
100
100
Note: x
2
=115.353, d=1, p =0.000<0.01, HS
Source: Survey Data
Rupak kumar Tung
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In terms of distance to access banking services, nearly 78.6% of households
If the distance from which basic banking facilities or other banking facilities can be
accessed is less than 5 kilometers, About 20.6% of households were within 5-10
kilometers of a formal bank, and only 0.8% of households he had to travel more than 10
kilometers to get banking services. Rural BPL households had distance problems to
access basic banking and other facilities compared to urban households, which was highly
statistically significant and confirmed by the chi-square test. (z2 = 115.353, df = 1, p =
0.000 < 0.01 , HS )
Table 2:
Distribution of Households based on the Nature of Financial Inclusion
(Figures in percentage)
Note: x
2
=402.372, df=2, p=0.000<0.01, HS
Source: Survey Data
Among rural and urban households surveyed in the income sector of Orissa, CB emerged
as the main channel of banking service delivery. The majority of households had access
to two or more formal financial institutions for banking services and benefited from
poverty eradication, risk reduction, productivity enhancement and government-sponsored
human resource development programs (Hussain et al., 2014). Across income sectors,
there were disparities in access and use of formal banking services, but those with lower
incomes who had recently started using banking services were unaffected. In this regard,
inter alia: 66.5% of rural households had below average financial inclusion flat. Only
7% of rural households were in the above average category and almost 46.8% of urban
households had above average levels of financial inclusion, while 9.1% were in the below
average category. rice field. Overall, approximately 37.85% of households had a below-
average type of financial inclusion, and 26.9% of households were in the above-average
category. Across income bands, the difference between rural and urban households was
statistically significant and confirmed by the chi-square test (x2=402.372, df=2,
p=0.000<0.01 HS).
Nature of
Financial
Inclusion
Rural
Region
Urban
Total
Below Average
66.5
9.2
37.85
Average
26.5
44.0
35.25
Above Average
7.0
46.8
26.9
Total
100.0
100.0
100.0
American Journal of Economic and Management Business
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148
Table 3: Distribution of Households based on the Extent of Financial Inclusion
Note x
2
: =246.720, df=2, p=0.000<0.01, HS
Source: Survey Data
On average, 79.3% of rural households had below average levels of financial
inclusion. Overall, about 8.1% of households had an above-average level of financial
inclusion. Among urban households, about 31.3% had below average levels of financial
inclusion and were below average. 55.3% of households had above average levels. The
difference between rural and urban households across income strata was highly
statistically significant, as indicated by the chi-square test (x2=246.720, df=2,
p=0.000<0.01HS).
Table 4: Inter-Tribal Financial Inclusion Index (IFI) variables
Sl. No.
Variables in IFI
Mean Scores among Tribes in
‘t’ Statistics
Urban
Rural
1.
Loan from financial institution
3.4812
3.8895
-2.2273*
2.
Loan under schemes
3.4981
3.9189
-2.5503*
3.
Loan under microfinance
3.5046
3.5599
-2.3286*
4.
Loan through SHG
4.4542
3.8676
-2.5314*
5.
Savings in saving account
3.4218
3.1887
2.8942*
6.
Savings in recurring deposits
3.8114
3.2583
2.5647*
7.
Savings in fixed deposits
3.9027
3.2528
2.7119*
8.
Daily savings in banks
3.9194
3.4187
2.6914*
9.
Payment of health and life insurance
3.8123
3.0985
2.8194*
10.
Payment of family insurance
3.7558
3.2122
2.7243*
11.
Usage of cheques and drafts
3.8999
3.1142
2.9988*
12.
Usage of mobile banking
3.8213
3.0341
3.0986*
13.
Usage of net banking
3.7199
2.9783
2.8571*
14.
Usage of money transfer
3.5693
2.8434
2.9294*
15.
Usage of other banking instruments
3.7550
3.1756
2.6576*
Significant at 5% level.
The table shows that IFI bank term deposits and daily savings are variables highly
valued by urban tribes. The average values are 3.9027 and 3.9194 respectively. Among
rural tribes, there are SHG loans and microfinance loans, with average values of 3.8676
The extent of
Financial
Inclusion
Rural
Region
Urban
Total
Below Average
79.3
31.3
55.3
Average
4.1
12.1
8.1
Above Average
16.6
56.6
36.6
Total
100.0
100.0
100.0
Rupak kumar Tung
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and 3.5599 respectively (Hoffmann et al., 2021). Regarding the IFI variables, significant
differences between urban and rural tribes were found at the levels of all 15 IFI variables.
This is because the corresponding 't' statistic is significant at the 5% level.
Table 5 : Important Banking Activities in Financial Inclusion (IBAFI)
Sl.
No.
IBAFI
No. of
Variables
in
Eigenvalue
Percent of Variation
Explained
Cumulative
Percent of
Variation
Explained
1.
Loans
4
4.0867
28.27
27.29
2.
Savings
4
3.7096
24.85
51.99
3.
Value-added
Services
4
3.1918
20.73
72.69
4.
E-banking
services
4
2.3985
14.94
88.61
KMO measure of sampling
adequacy: 0.8116
Bartletts test of Sphericity: Chi-square value:
111.99*
Significant at 1% level
The table above shows that the first two IBAFIs recognized by EFA for the intrinsic
value of loans and savings are 4.0867 and 3.7096 respectively. 28.27% and 24.85% are
the percentages of variability explained by these two activities. The cumulative
percentage of variation interpreted by these two activities is 27.29% and 51.99%
respectively. The two main activities identified by the factor analysis are value-added
services and e-banking services. Their eigenvalues are 3.1918 and 2.3985 respectively.
The percentage of variation explained by these two significant activities is 20.73% and
14.94% respectively. The four IBAFIs described show 16 variables at 88.61%. All four
of these IBAFIs are considered for further analysis.
Correlation analysis:
Correlations between study components were assessed by the Karl Pearson
correlation coefficient and grouped into three categories. For 'r' values greater than 0.8,
the first category is 'strong correlation'; for 'r' values between 0.5 and 0.8, the second
category is 'good correlation' and the third category is 'moderate It was correlation. The
'r' value is between 0.3 and 0.5 between study components. Overall, the correlations
between the components of financial inclusion and inclusive growth and the
socioeconomic impact components of formal financial service use and inclusive growth
are measured as 'good' and 'strong' correlations. was done (0.801 and '0.660' p < 0.01),
statistically significant.
Regression analysis:
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To assess the impact of formal financial service use on inclusive growth outcomes, a
multiple regression analysis was performed using inclusive growth as a baseline and the
impact of financial inclusion and financial service use as predictors. . The analysis was
statistically significant (t=30.044 & 26.257, p<0.01) and at the aggregate level, the
components of “financial inclusion” (type of financial inclusion + degree of financial
inclusion) and “impact of financial services consumption” was suggested. ' (material
change + cognitive change + perceptual change + relationship change after consumption
of financial services) had a significant impact on the 'inclusive growth' component,
confirmed by the standard beta values (each §= 0.572 and 0.500). This accounts for 0.622
of the variability indicated by the R° statistic. The regression equation that predicts the
impact of financial inclusion on inclusive growth and access to finance is Y = 13.335 +
0.774 X1 + 0.848^X2. Domínguez-Almendros et al., (2011) The Logit model was used in
this quantitative analysis because it captures the persistence of dependent variables with
binary yes or no outcomes (Gujarati 2003). In this context, variables with binary outcomes
are financial inclusion. Whether the respondent is financially involved. In this study,
financial inclusion is measured by account availability and frequency of access to financial
services.
A; The estimated equation;
Y= β0+β1x1+β2x2+β3x3……+μ
In this study, financial inclusion is measured by account ownership and frequency of
access to financial services. We used five explanatory variables, Gender, education,
marital status, and financial institution defining the dependent variables.
(1) . Frequency of assessing = c+β1male+β2educ+β3amount+β4single+β5financial
institution. The above formula estimates financial inclusion potential based on various
characteristics. In this study, too, financial inclusion is measured by the frequency with
which financial services are rated. The variables gender (= 1 if male), education,
employment level, marital status (= 1 if single), having an account with a financial
institution.
Table 6: Definition of variables;
Variable name
Definition of variables
Sex
=1 if male
Marital Status
=1 if single
Level of education
Level of education of tribes
No of education
=0 if no education
Primary
=1
Secondary
=2
Higher Secondary
=3
Graduation
=4
Higher Studies
=5
Daily Amount
Amount of money in Baripada town that the individual
earns per day
Availability of financial
institution
In any bank, micro-finance or other financial institutions
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Type of financial
institution
Type of bank, micro-finance and other financial
institution of Baripada town
Frequency
How many times do you access , use, afford your bank
account or other financial institution
Source: Interview data from field work (Dec 2022)
The choice is between logit model and Probit model and I did both but am going to
report the logit model.
Table 7: Logit/ Frequency of assessing financial services
Dependent variable: Frequency of assessing
Method: ML- Binary Logit ( Newton-Raphson / Marquardt step)
Variable Coefficient Std. Error Z- Statistics Prob.
Male 0.839387 0.652732 1.165321 0.2104
Education 0.333887 0.348108 1.087714 0.2897
Amount 0.000110 6.38E-05 1.642977 0.0984
Single 0.217349 0.687126 0.382152 0.7256
Institution 1.346988 0.596285 2.560042 0.0116
C -5.219927 1.172432 -4.581918 0
McFadden R-squared 0.275675 Mean dependent var 0.24
S.D dependent var 0.441953 S.E of regression 0.36738
Akaike info criterion 0.989812 Sum squared resid 13.0732
Schwarz criterion 1.046222 Log likelihood -38.981
Hannan-Quinn criterion 0.964074 deviance 76.9813
Restr. Deviance 105.8653 restr. Log likelihood -54.918
LR statistic 33.78553 Avg. Log likelihood -0.3898
Prob (LR statistic ) 0.000007
Obs with Dep=0 269 total Obs 357 Obs
With Dep=1 88 .
Standard errors
*** P<0.01, ** p<0.05, * p<0.1
In my sample of 357 observations. The results show that 88 tribes accessed or used
his account at least once a month in the last six months, while 269 tribes had not accessed
their accounts in the last six months.McFadden's r-squared of 0.275675 indicates that
some variables (gender, education, marital status) have the expected signs, but are not
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statistically significant, so the model works logically well indicates that Furthermore, the
likelihood ratio test statistic of 33.78553 and the associated p-value of 0.000007 indicate
that the model fits significantly better when he uses all five of his explanatory variables
than when he uses fewer explanatory variables. I'm here. A coefficient of 0.00 associated
with the variable amount is statistically significant at the 10% significance level. This
suggests that higher income tribe are more likely than lower income tribe to access or use
their accounts at least once a month in the past six months.
Furthermore, the coefficient of 1.3 associated with the availability of financial
institutions within the city is statistically significant at the 5% significance level
(Kostovetsky, 2015). Also, schooled and single tribe access and use their accounts more
than once a month in the past 6 months than out-of-school and married single tribe. more
likely but this is not statistically significant. In summary, as noted above, financial
inclusion in this study is measured by the presence of accounts and the frequency of
access or use of financial services (Demirgüç-Kunt & Singer, 2017). As shown in Table
7, all five explanatory variables are positive: gender, education, marital status, amount of
money, and financial institution. However, the amount is statistically significant at the
10% significance level, as shown in Table 7. Additionally, they are more likely to be
financially involved, as shown in the table above. Thus, having an account and frequency
of accessing or using financial services were the two dependent variables that defined
financial inclusion in the study, with the availability of financial institutions in the city
increasing the financial inclusion of tribe . more likely.
CONCLUSION
Based on observations, analyses, and insights, this paper draws the following
conclusions.There is a mismatch between macro-level financial inclusion in the Indian
economy and revenue sources in Odisha. At the macro level, even after financial inclusion
initiatives have been implemented, there are large inequalities in the economy, with most
farmers, the poor and marginalized segments of society lacking access to financial
services. The study identifies differences in income distribution within states and among
households belonging to socially disadvantaged sections of the population. There is a
positive association between the use of banking services and socioeconomic status of
households belonging to vulnerable groups. Therefore, financial inclusion of households
belonging to vulnerable groups .It can be seen as an important factor in improving the
socioeconomic status of households.
The positive correlation between financial inclusion and inclusive growth can be
seen as a factor underscoring the role of innovative, low-cost formal banking products in
the process of inclusive growth. In addition to basic banking products, households
belonging to vulnerable groups have access to Human Development Packages, Risk
Reduction Packages and Productivity Enhancement Packages. This phenomenon
demonstrates the role of welfare packages in improving the absorptive capacity of
vulnerable people, lifting them from cycles of economic exclusion and making them more
bankable. One key segment, households, would benefit from increased financial inclusion
if promoted in the broader context of economic inclusion alongside social packages.
Rupak kumar Tung
153
Formal financial networks have the potential to unlock the creative power of
disadvantaged households, driven by increased incomes and consumption of a large
proportion of the population belonging to disadvantaged groups.
A formal banking system can improve the financial condition and living standards
of households belonging to vulnerable groups and generate wealth, income and
emergency funds to deal with unforeseen circumstances and economic crises; increase. It
also benefits from the non-leak transfer of social benefits to disadvantaged segments of
the population.
Financial inclusion expands banking networks with more transactions, brings new
ways of earning a living in society, and leads to inclusive growth of the economy. Given
the existence of financial exclusion associated with the Indian economy, the study
rationalizes public policies focused on financial inclusion. By confirming the link
between financial inclusion and its impact on positive changes in the socioeconomic
status of households in the sample area, the study supports financial sector reforms to
promote financial inclusion. emphasizes the need to centre development agenda.. .
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Copyright holders:
Rupak kumar Tung (2023)
First publication right:
AJEMB – American Journal of Economic and Management Business
