INTRODUCTION:

An important determinant of economic growth is the level of investment in the economy. Mobilisation of domestic savings is thus warranted to improve investment. Financial inclusion is one of the ways to ensure mobilisation of savings of the masses. Also it improves the status of employment and livelihood of the marginalised by providing access to mainstream capital market by introducing them to the institutional network of financial houses. In this paper we explore the extent of financial inclusion of Bhuiya community of Jharkhand. Section I presents the literature survey of the related issues. Section II presents the methodology of the paper. In section III the results of the study have been discussed.

Section I:

Literature Review:

The present section presents a literature survey of the issues related to financial inclusion. Financial inclusion is considered as a catalyst of economic growth by bringing the pent up financial capital into the mainstream market and providing avenues for both demanders and suppliers of financial capital. The Indian capital market is not much integrated which has led to efforts by government in the recent past to increase financial access and improve financial penetration. Despite these efforts the extent of financial inclusion in India, by the end of year 2014, was only 53 percent which is quite low.

Factors affecting Financial Inclusion:

There are many factors like physical and geographical which affect financial inclusion of different individuals. More explicitly these factors are access (through the process of risk management by financial service provider), price of financial service, marketing of financial product and self exclusion due to fear of refusal to access by the service providers [1].

One of the public scheme that has resulted in financial inclusion as a by product upon implementation is MNREGA. It has been concluded that MNREGA has contributed positively towards financial inclusion [2]. Again telecom revolution has accelerated the process of financial inclusion by improving access to mobile telephony. Financial access has improved also because of Aadhar, the unique biometric identification process leading to increased financial inclusion [3].

Financial Inclusion among the Dalits:

There is no denial to the fact the most economically and socially marginalised sections of the society are more financially excluded. As per Dr Rangarajan Committee report 49.77 percent of Scheduled Caste households are financially excluded [4].

Result of Financial Exclusion:

It has been observed that financial exclusion is more intense among the Scheduled castes, Scheduled Tribes and Other Backward Castes especially those living in semi-urban and rural areas. The result of this is that such households lack in savings and hence investment. Again the high rates of interest charged by indigenous money lenders discourages them from taking loan for self employment and hence results in increased in unemployment [5]. The existing stereotypes in the society fed upon casteism pose a serious challenge in ensuring financial inclusion for all.

Section II:

Methodology:

The Bhuiya constitute one of the 22 Scheduled Castes of Jharkhand. The study explores the financial inclusion status and factors affecting financial penetration of the Bhuiya community of Jharkhand using primary data. One of the districts where greater concentration of the Bhuiya is found is Palamu. In the first step Chhatarpur block has been chosen randomly from Palamu district. In the next step out of the 130 villages of Chhatarpur block two villages have been selected randomly and the villages are –Khajuri and Khendrakala. All the households of the Bhuiya community living in all the tolas in the respective villages of Chhatarpur block have been taken in the sample. A total of 62 households of Bhuiya community belonging to the two villages have been taken in the study. The various tools and techniques that have been used for data collection are the following- Household Schedule, Village Schedule, Focused Group Discussion, Key Informant Interview. Further in order to explore the extent of financial inclusion of the Bhuiya, the paper makes use of Logit analysis as outlined below.

Empirical Strategy:

The financial inclusion status of a household depends on a number of socio-economic factors like income, level of education, ownership of assets and possession of MGNREGA job card. In order to trace the extent of financial inclusion the paper measures the relation between possession of savings bank account by the household in banks or post office or holding saving with Non-bank financial institution (NBFIs) and level of household income, possession of land, educational qualification of the head of the household and possession of MGNREGA job card in an econometric framework. The dependent variable in the study is possession of savings bank account by the household in banks or post office or holding saving with Non-bank financial institution (ACC) which takes values one and zero. One standing for possession of bank account and zero for no bank account. Household monthly income in rupees, (INC), possession of land in acres, (LAND), educational qualification of the head of the household (EDU) and possession of MGNREGA job card (CARD) are the independent variables. The variable EDU in the study has only two categories of literate and illiterate in the paper. This has been taken after examining the possibilities of the sample population as none of the Bhuiya reach higher levels of education. Here again the value one stands for literate and zero for illiterate. Similarly the variable CARD also takes only two values : one for possessing MGNREGA job card and zero for not having the job card. Since the dependent as well as independent variables are qualitative in nature the study makes use of Logit analysis. The Logit model assumes that the probability distribution of the error term follows a logistic probability distribution.

The functional form of Logit model adopted for the present study is of the following form:

………………………………………(1)

where Pi is the probability of financially included household and

The probability that the household is not financially included is then given by:

.............................................................(2)

Taking the ratio of equations (1) and (2), we get odds ratio in favour of financial inclusion as shown below:

……………...............................(3)

Taking log of equation 3 would give us

.............................(4)

Equation (4) which is log of odds ratio is thus a linear function of variable Xs. So L_i is the Logit. The functional form of the variables used for this study is

Where,

ACC = possession of savings bank account by the household in banks or post office or holding saving with Non-bank financial institution

INC = household monthly income in rupees

LAND= possession of land in acres

EDU = educational qualification of the head of the household

CARD = possession of MGNREGA job card

A Brief Profile of Sample Community:

Bhuiya constitute about 21 per cent of the total SC population in Jharkhand and about 87 per cent Bhuiya live in rural areas. Their literacy rate is 41 per cent and male-female literacy rate is 50 and 32 per cent respectively which is much lower than the value for the SCs of the state. Owing to poverty and general apathy, their children drop out from schools at an early age and consequently their literacy and educational standards are very low. The sex ratio among the Bhuiya is 967 and the child sex ratio is 1000. The Bhuiya are mainly landless, but a few of them possess cultivable land. They mostly depend on daily wage labour, casual wage labour, agriculture wage labour, rickshaw-pulling, bricks-laying etc. About 62.1 per cent Bhuiya works as agricultural labour.

As far as the sample households are concerned the level of literacy is very low among them. Only 32 percent of sample population is literate. Again considering the educational level of household heads it can be seen from table 2, only 2 percent of the household heads are literate.

Table 1: Literacy rate and Sex ratio of the sample population

Community	Literacy rate			Sex ratio
Community	Male	Female	Total	Sex ratio
Bhuiya	38.3	24.8	32.2	907

Source: Primary data

Table 2: Educational status of the heads of the sample households

Educational Status	Household heads
Illiterate	57(91.94)
Literate	1(1.61)
Below primary	3(4.84)
Primary	1(1.61)

Source: Primary data

Sources and Uses of Credit:

As far as the source of credit of the sample population is concerned there are basically five sources of credit for them- banks, village men, local traders (Paikari) relatives and the contractors who take them for causal wage labour. Firstly it can be seen that only 37 percent of the households take credit. Again only 20 percent of the households have taken credit from institutional source. This happens the case of the households belonging to Khendra Kala village who have borrowed from Grameen Bank. The loan was allotted under a scheme as per which even the landless and marginalised section were to receive a loan up to Rs 30000 for livestock rearing and agriculture but those who received the loan amount spent it for other purposes. They received an average amount of Rs 21538 and the loan amount varied from Rs 10000 to Rs 30000. They have pledged the papers of their house as collateral security but they have no idea about the rate of interest being charged on their loan. Although the loan was meant to promote agriculture and allied activities the purpose of the scheme remains negated as all the households have spent the money for addressing different issues like daughter’s marriage, medical treatment, meeting food expenses, settling old debt, construction of houses. The households resort to other sources of credit like local contractors who charge exorbitant rate of interest and unethical terms of loan, while some borrow from relatives and local villagers. The loans are basically spent under unproductive heads.

Section III:

Result and Discussion:

The following section presents the results of the Logit regression undertaken to explore financial inclusion of Bhuiya in Jharkhand. Possession of savings bank account by the household in banks or post office or holding saving with Non-bank financial institution (NBFIs) has been taken as an indicator of financial inclusion of the Bhuiya. The possession of bank account has been taken as dependent variable. Since the variable can take values one and zero Logit regression analysis has been undertaken. Table 3 below presents the results of the Logit analysis. The p-values for only INC variable is less than 5 percent. This means changes in income has an impact on possession of bank account. Moreover the coefficient associated with income variable is positive. This means that there is a positive relation between income and financial inclusion. Apart from income the other variables do not affect financial inclusion of the households. As far as MGNREGA job card is concerned only 26 percent of the households possess MGNREGA job card which is very small proportion. The card holders do not get much work under MGNREGA. This is because of social exclusion, as work under MGNREGA is first offered to those belonging to the general category and not to the scheduled castes. Thus, MGNREGA job card also does not serve as a useful factor in explaining the extent of financial inclusion in the present case. The land holdings of the Bhuiya is very small which do not serve as a source of income and do not generate savings in cash which may would have encouraged them to have bank accounts.

Table 3: Determinants of Financial Inclusion

Independent Variables	ACC
	Coefficient	P-value
INC	0.000270	0.0000
LAND	0.337887	0.1346
EDU	-1.177940	0.2624
CARD	0.188430	0.1939

Source: Author’s own calculation from Primary Survey Data.

CONCLUSION:

Thus it is found that improvement in income leads to more financial inclusion of Bhuiya. However the other factors like level of education of household heads, possession of MGNREGA card and land assets do not affect the extent of financial inclusion of the Bhuiya. This is because firstly the level of education of household heads is very low to have an effect on financial inclusion. Again the sample households hardly posses any fairly sized plot of land which does not affect their earnings and hence savings. The Bhuiya also suffer from social discrimination which is evident in the fact that they do not find much work and income under MGNREGA. Thus even possession of MGNREGA job card also does not ensure financial inclusion of the Bhuiya.

REFERENCES:

1. Kempson, Elaine, Claire Whyley, John Caskey, and Sharon Collard (2000): “In or Out? Financial Exclusion: A Literature and Research Review.” Financial Services Authority, London.

2. Ghosh, S (2017): “Did MGNREGS Improve Financial Inclusion?”, Economic and Political Weekly, Vol.LII, No. 12, Mumbai, pp106-114.

3. Ghosh, S (2017): “Biometric Identiﬁcation, Financial Inclusion and Economic Growth in India: Does Mobile Penetration Matter? ,” Information Technology for Development

4. Dhan Sa (2010): Policy interface 2010: A Report, The Association of Community Development Finance Institutions, New Delhi.

5. Agrawal, Reena (2011): 100 % Financial Inclusion: A Challenging Task Ahead present at Conference on Global Competition and Competitiveness of Indian Corporate, IIM. Lucknow, pp 276-279.

Received on 11.12.2018 Modified on 19.01.2019

Int. J. Rev. and Res. Social Sci. 2019; 7(1):83-86.

DOI: 10.5958/2454-2687.2019.00006.6