A study on farmer behaviour influencers of agricultural credit in Raipur district (Chhattisgarh)

Introduction

Agriculture's progress is dependent on the acceptance of new technologies, and new technology necessitates the use of agricultural credit (Aroutselvam and Zeaudeen, 2000) [1] , which is the primary input in agriculture. Credit plays a key role in assisting the impoverished to escape poverty. Access to credit was positively connected with a decrease in rural poverty and a rise in secondary and tertiary outputs, according to evidence (Burgess and Pande, 2003) [2] . Agriculture credit is one of the requirements for farmers to increase agricultural output as part of a country's agricultural growth (Gandhimathi 2011) [5] . Agriculture credit is a critical component of the sector's expansion. Agricultural policies have been evaluated on a regular basis to ensure that appropriate and timely financing is available. There is no doubt that access to finance is of crucial importance for the ongoing and sustainable growth and profitability of micro enterprises sector through its role in facilitating the creation of new business and nurturing the innovation process as well as promoting the growth and development of existing business, which is turn, boost economic growth (SK Joshi and SR Lodhi 2017) [7] Agricultural credit is a significant part of the rural sector, accounting for over 85% of total rural credit requirements. During the 1990s, the growth of institutional lending for the agricultural sector slowed as well. Agricultural credit as a percentage of agricultural GDP has risen steadily over the years, from 5.4 percent in the 1970s, to 8.3 percent in the 1980s, 7.4 percent in the 1990s, and 6.7 percent in 2008-09, and it is now on the fall (Feder 2006) [4] . Commercial banks were instructed to lend more to agricultural after they were nationalised in 1969. Several policy measures were implemented, including the Lead Bank Scheme (1969), Regional Rural Banks (1975), Service Area Approach (1989), Micro Finance Scheme (192), and Kisan Credit Card System (1998-1999), as a result of which institutional credit, which includes commercial bank and cooperative credit, increased from 7.3 percent in 1951 to 60 percent in 1996. (Gandhimathi 2010) [6] .

Materials and Methods

Any scientific analysis of an issue necessitates the use of appropriate methods and procedures in order to reach a successful conclusion. This chapter attempts to describe and clarify the study's location, as well as the procedure used to choose respondents and create an interview schedule. The research method that was used is described under the following heads.

Sampling methodology

The data for the study were collected from primary sources. A multi-stage random sampling procedure was followed for selecting the sample of borrower farmers. It includes the following aspects,

Selection of district

The study was conducted in Chhattisgarh state. From this state, Raipur district was purposively selected based on a great borrowing percentage of Agri loans.

Selection of block

There were 3 blocks in Raipur district viz., Arang, Abhanpur, and Dharsiwa Out of which Arang and Abhanpur block were selected purposively based on major Agri loan borrowers from the blocks.

Selection of villages

Two villages were selected purposively from each block, thus a total of 4 villages were selected for the present study. Selection of farmers 50 farmers are will be selected randomly to comprise the sample of 200 for study. The entire number of borrowers was divided into four groups based on the magnitude of their holdings, as shown below.

Less than 1 ha (Marginal farmer-4) 1 to 2 ha (Small farmer-60) 2 to 4 ha (Medium farmer-59) Above 4 ha (Large farmer-77).

Sampling plan (multi-stage sampling)

Proportionate representation of marginal, small, medium, and large farmers is to size.

Method of data collection

The data was obtained utilizing the personal interview approach after the research design and interview schedule were finalized. The field survey approach was used to attain the given goals. For data collection, the investigator personally contacted all of the respondents. The investigator introduced himself to the respondents and explained the aim of the visit, the study's objectives, and its significance, as well as asking for their involvement in the study. After establishing a rapport with them, point-by-point information was requested of them according to the set schedule, and their responses were recorded. Those respondents who were absent at the time of the interview were also approached a second time. The real data collection effort took place between the 15 March to 15 April, 2022. However, all responders had given excellent responses and were therefore considered participants in the study.

Data Sources: Both primary and secondary data were collected for the study.

Primary Data: The investigation requires both primary and secondary data. On the basis of the data requirements of the respondents for different objectives in the study region, primary data from farmers was obtained by personal interview and questionnaire.

Secondary Data: Secondary data were collected from the banks, the internet, journals.

Statistical tool or framework

For analysis and inference development, the following statistic parameters were used. The parameters used are defined as under.

a. The data so collected is analyzed using the Percentage Method

The percentage method refers to a certain type of ratio that is used to compare two or more sets of data. The percentage method's formula is:

Where X = Number of respondents falling in a specific category to be measured. Y = Total number of respondents.

b. Discriminant Analysis to Identify Borrowing Behavior

The discriminant analysis was carried out by taking into account eight socio-economic characteristics: age, gender, education, occupation, annual income, landholding size, family size, Agri loan amount, using a linear multiple discriminant function of the form to identify the socioeconomic factors that influenced borrowings from farmers.

Where, Z = Total discriminant score for farmers, X 1 = Age, X 2 = Gender, X 3 = Educational level (1-illiterate, 2-primary, 3-Middle, 4-high school, 5-higher secondary, 6-collegiate), X 4 www.extensionjournal.com = Occupation, X 5 = Annual income, X 6 = Landholding size (ha), X 7 = Family size (No.), X 8 = Agri loan amount The majority of the respondents were in the male (83.5%), followed by the female (16.5%). The majority of the respondents (21 percent) had finished high school education," followed by 18 percent in the category of "higher secondary," followed by 16.5 percent in the category of "primary." Followed by 15.5 percent in the category of "middle" Only 27 responders (13.5) fell into the group of "collegiate." There were 15.5 percent of responders in the category "illiterate." 38.5 percent of the Agri loan borrowing farmers had large (4 to 10 ha) size of land holding, 30 percent of them had small (1 to 2 ha) size of land holding, 29.5 percent of them had medium (2 to 4 ha) size of land holding, only 2 percent of them had marginal (up to 1 ha) size of land holdings. More than half of Agri loan borrowing farmers (80%) have only farming as their main occupation, whereas had farming + business 14.5 percent and 5.5 percent of respondents had farming + government service as their occupation. Majority of the respondent's 65 percent were "nuclear family" and 35 percent were "joint family" respectively. 59% of respondents have a large family, while only 41% have a small family. Maximum number (37.5 percent) of the respondents had a medium annual income, i.e., between Rs. 50,001 to 100,000. The high annual income respondent's (above Rs. 100,000) were 36.5% whereas, 26 percent of them had low annual income (up to Rs. 50,000). 68% respondents said they pay regular loans and 32% of respondents said they do not repay regular loans. 78.5 percent respondents have borrowed the Agri loan from cooperative societies, Besides the other formal source used by the farmers were commercial banks (21.5 percent).

Results and Discussion Demographic / economic profile of respondents

Borrowing Behavior -Discriminant Analysis

To identify the socio-economic factors which led to discrimination between commercial bank and co-operative society for borrowing, discriminant analysis was carried out. The mean and standard deviations of the included variables were estimated as the first step in this study, as shown in Table 2.

Table 2 showed that borrowers from commercial banks had higher education, occupation, and had higher annual income, bigger size of landholding, large family size and higher Agri loan amount, whereas borrowers from cooperative society had taken out higher age, and gender. Wilk's lambda (U-statistics) and its corresponding univariate F-test (one-way analysis variance) were used to evaluate the mean differences between the selected groups, and the results are reported in Table 3 for the selected variables.

There is no significant difference between the means of two groups when the value of Wilk's lambda approaches one, and vice versa. The estimated value of Wilk's lambda approached one for all the factors, except annual income, landholding, Agri loan amount. It showed that the borrowers of Commercial banks and Cooperative society differed widely in relation to annual income, landholding, Agri loan amount. Correlation between discriminating variables and canonical discriminant function were the other tests used in the discriminant analysis process. Table 4 shows the pooled within-group correlation between the discriminating variables and the canonical discriminant function. The correlation co-efficient were ranked according to their contribution in the discriminating function. Table 4 shows that the Agri loan amount had the biggest contribution to the function (.835). Gender, on the other hand, had the smallest influence (-.045). It revealed that the gender did not contribute to the variation in borrowing behaviour from commercial bank and co-operative society.

Conclusion

The Agri loan amount and the size of the landholding have been recognized as the most important criteria in determining whether a borrower should go to a commercial or cooperative society. It demonstrates that farmers with larger landholdings and higher Agri loan amount borrow from commercial banks. The discriminant functional analysis between commercial bank borrowers and cooperative society borrowers revealed that the Agri loan amount was the major discriminator followed by gender. For commercial bank borrowers, the size of the landholding has been shown to affect the per hectare crop loan. Per acre investment loans have decreased in both commercial and cooperative societies, as well as among farmers. As a result, per hectare investment loans that are not related to the size of the landholding are sanctioned by both commercial and cooperative societies. It was deduced that the sample farmers' borrowing behavior was impacted solely by their economic features, rather than their social characteristics.

Suggestions

1. Farmers that have borrowed from commercial banks are large farmers; but, due to the lengthy process, marginal and small farmers are unable to borrow from these institutions. To shorten the operation, proper precautions should be adopted. 2. Marginal and small farmers have taken out a disproportionately small amount of investment loans.

Because they are afraid of being repaid, banking institutions have ignored them. As a result, regardless of the amount of the landholding, the farmers' repayment capacity should be adequately appraised. A sufficient quantity of investment credit should be made available to marginal farmers. 3. The loan process is quite cumbersome, and a typical borrower encountered numerous challenges. It is proposed that the difficult process of acquiring a loan be simplified. Collecting various documents from various agencies is a complex task, thus some arrangement may be made to obtain all of the essential documents at one time and in one location.

References

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