INTRODUCTION:

Labour is the vital input in agriculture. Census of India(2001) defined agricultural labour as any person who worked on another person’s land only as labourer, without exercising any supervision in cultivation, for wage in cash or share such as share of produce (GoI, 2001). Agricultural labour supply was abundant and wages for agricultural operations were very low in India last two decades ago. But now, Indian agricultural sector has been changed a lot due to various reasons.

Scarcity of agricultural labour supply is one of them. Even though, India is the second largest country in population in the world, agricultural labour supply has been declining continuously. Due to labour scarcity wages in agricultural operations are increasing rapidly. Today’s agricultural sector scenario has been changed. Agricultural labours are shifting to non-agricultural activities. Income from agricultural operations is not the main source of income to the labours family in rural areas today. Young labours are not showing interest in agricultural activities and only middle aged labours whose age above forty and forty five years are available for agricultural activities. Therefore, there is a paradoxical situation exists in rural India. On the one hand, there is acute scarcity of labour for agricultural operations. On the other hand, wages are increasing for agricultural operations. In this context that the study was taken up in Davangere district of Karnataka to analyse what factors are influencing agricultural labour supply.

MATERIAL AND METHODS:

The present study was based on primary data and conducted in Davanagere district of Karnataka with the sample size of 200 respondents. A multistage random sampling procedure was adopted for the selection of the study area. Out of seven taluks, four taluks were selected in Davangere district in which two taluks from dry land area and two from irrigated area. One village was chosen from every taluk and 50 agricultural labours selected were from every village. Hence totally 200 samples were selected for the study using a well-designed and pre-tested schedule. Among 200 respondent agricultural labours, 100 agricultural labours from dry land and 100 agricultural labours from irrigated land. Tabular analysis, per centages and Chi square test were used to analyse the data.

RESULTS AND DISCUSSION:

Labour supply is determined by various factors. Among them factors like age, education, Caste and land holdings are greatly influencing the labour supply. These factors are analysed that how they will influence the supply of agricultural labour based on the primary data collected from the selected villages.

Age:

The age composition of respondents’ family members is one of the important factors which are expected to have influence on supply of agricultural labour. It helps to understand the age-wise distribution of agricultural labours’ family members and its influence on labour supply. For the study purpose, age composition of the sample respondents’ family members have been categorized under three groups namely young labourers (below 15-35 years), middle age labourers (36 to 50 years) and old age labourers (51- 65 years). Frequency distribution of respondents’ family members across the different age groups is presented in the table 1.

Distribution of agricultural labours’ family members across the different age groups presented separately for dry land and irrigated land. Overall labour represents total sample agricultural labour respondents and their family members in dry land and irrigated land. The data reveals that majority of the agricultural labours’ family members are belonging to middle age group followed by young age group in dry land as well as irrigated land. There were 758 working age people available in 200 sample respondents’ family. Out of 758 members, young people were 179, middle age people were 416 and old age people were 163. Among the 179 young people, 21.8 per cent of young people doing agriculture work whereas 78.2 per cent of young people not doing agriculture work. It means that majority of the young lobours are not taking up agricultural works. Among the 416 middle age labours, only 44.3 per cent of middle age labours doing agricultural works remaining 55.7 per cent of labours not doing agricultural works. It reveals that even though labours available in the rural area, majority of the labours are not interested to work in agriculture. With regard to old age labours, only 35.6 per cent of labours doing agriculture works while 64.4 per cent labours not participating in agricultural works. It clearly shows that most of the labours in the study area are not taking up agricultural works. Therefore availability of labours for agricultural operations has been declined drastically.

In the overall agricultural labours group, labour participation in agricultural activities more among the middle age group compare to the other age group. Especially participation in agricultural activities is lowest among the young labourers. Actually in this group it is expected to be more but in this group some family members are still continuing their education and those who have completed college education and above, they are not involved in agricultural activities but most of the young age labours working in non-agricultural works.

Table 1. Age of the agricultural labourers’ family members and labours participation in agricultural operations

Age	Labours participation in agricultural operations
Age	Doing agricultural works	Not doing agricultural works	Total	χ²
Overall
Young labours (15-35)	39 (21.8%)	140 (78.2%)	179 (100%)	27.219*
Middle age labours (36-50)	184 (44.3%)	232 (55.7%)	416 (100%)
Old age labours (51-65)	58 (35.6%)	105 (64.4%)	163 (100%)
Total	281(37%)	477(63%)	758(100%)

Notes:

1) Figures in parenthesis are per centage to total.

2) * indicate the significance at one per cent probability level.

In order to test the significance of association between age composition of respondents’ family members and the labours participation in agricultural operations, chi-square test has been calculated. The calculated chi-square (χ²) value for the overall category was found (27.219) to be more than the critical value (9.21) for 2 degrees of freedom at 1 per cent probability level. Therefore, it could be inferred that the association between level of participation in agriculture and age composition of respondents’ family members is statistically significant. Similar inference could be drawn for dry land and dry land.

Figure 1: Age and labours participation in agricultual operations

Education:

Education plays a vital role in choosing the employment and also determines the standard of living. Therefore data on the education level of the agricultural labours’ family members has been collected and the results are given in the table 2. The education level of the respondents’ family members has been mainly classified into four categories namely illiterates, primary education, secondary and college education.

Distribution of agricultural labours’ family members across the different education level presented separately for dry land and irrigated land. Overall labour group represents total sample agricultural labour respondents and their family members in dry land and irrigated land. Frequency distribution of respondents’ family members across the different educational level is presented in the table 2.

Table 2. Education of the agricultural labourers’ family members and labours participation in agricultural operations

Education	Labours participation in agricultural operations
Education	Doing agricultural works	Not doing agricultural works	Total	χ²
Overall
Illiterates	140(46.2%)	163(53.8%)	303(100%)	32.625*
Primary education	77(41.2%)	110(58.8%)	187(100%)
Secondary education	40(22.5%)	138(77.5%)	178(100%)
College education	24(26.7%)	66(73.3%)	90(100%)
Total	281(37%)	477(63%)	758(100%)

Notes: 1) Figures in parenthesis are per centage to total.

2)* indicate the significance at one per cent probability level.

Figure 2: Education and labours participation in agricultual operations

In the overall labours group, the total working age population of the dry land and irrigated land respondents’ family labours were 758 out of which 358 are belonging to dry land respondents’ family members and the remaining are irrigated land respondents’ family members.

The above table clearly shows that the prevalence of illiteracy was highest among the agricultural labours. Labours participation in agricultural works is found to be relatively more among the illiterate labours compared to educated labours. In the overall category among the illiterates, labours participation in agricultural activities was (46.2%) highest. Labours participation in agricultural activities among the labours with primary education was 41.2 per cent remaining 58.8 per cent labours not participating in agricultural activities.

Labours participation in agricultural operations among the labour who obtained secondary (22.5%) and college education (26.7%) was lowest whereas these labours participation was highest in non-agricultural activities. Researcher through discussion with respondents made the following observations. In the present scenario majority of educated youths, in rural area, are not willing to participate in agriculture work. They are striving for getting some white-collar job in urban centres. On the one hand they have developed aversion towards agriculture work realizing that they are difficult, dangerous and dirty works on the other hand they developed liking towards non-agriculture works in urban centres. Factors like decaling profitability caused by increasing explicit cost ratio, increased risk caused by natural calamities and volatility in agriculture price have greater contribution to develop aversion towards agriculture work among rural educated youth.

In order to test the significance of association between labours participation and education level of the agricultural labours’ family members the chi-square value has been calculated. For the overall labour group, the calculated chi-square (χ²) value is found (107.353) to be more than the critical value (5.99) for 3 degrees of freedom at 1 per cent probability level. The chi-square values have also been calculated separately for dry land and irrigated land labours. The calculated value found to be statistically significant at 1 per cent probability level. Therefore, it could be inferred that the education level of the respondents’ family members influence the agricultural labour supply.

Caste:

Caste system in India is prevalent since the ancient times. However, despite the growing changes the caste identity still holds a lot of importance in the Indian society. Most agricultural labourers belong to the depressed classes of the society which have been neglected for ages. For the study purpose, castes are categorized into three main groups namely Scheduled castes (SCs), Scheduled tribes (STs) and others. In the study area SC category mainly comprises Adi Karnataka, Bhovi and Lambani. ST comprises of only Nayaka community people and others category comprise all castes except SCs and STs Community.

Distribution of agricultural labours’ family members’ participation in agricultural activities across the different caste presented separately for dry land and irrigated land. Overall represents all the members of respondents’ family of dry land and irrigated land. Frequency distribution of respondents’ family members across the different caste is presented in the table 3.

In the overall agricultural labour group out of 758 total agricultural labours’ family members 388 are found to be belonging to SC followed by 208 are belonging to Others category and 162 are belonging to ST category. The significant feature of results is that among the various caste, scheduled caste labours’ family members accounts for higher share in participation of agricultural activities (46.9%) followed by ST category (27.8%) and Others category (26%). On the other hand, the most significant feature is that among the all castes labours are engaged in non-agricultural works. The percentage of labours participation is less than the labours engaged in non-agricultural activities. 74 per cent of Other category family members are not doing agricultural works followed by ST 72.2 per cent and SC 53.1 per cent. It clearly shows that labours participation in agricultural activities is drastically decreasing not only in upper castes like others category but also in backward classes like SC and STs.

Table 3. Caste of the agricultural labourers’ family members and labours participation in agricultural operations

Caste	Labours participation in agricultural operations
Caste	Doing agricultural works	Not doing agricultural works	Total	χ²
Overall
SC	182(46.9%)	206(53.1%)	388(100%)	33.093*
ST	45(27.8%)	117(72.2%)	162(100%)
OTHERS	54(26%)	154(74%)	208(100%)
TOTAL	281(37.1%)	477(62.9%)	758(100%)

Notes:

1) Figures in parenthesis are per centage to total.

2)* indicate the significance at 1 and 5 per cent probability level respectively.

Figure 3: Caste and labours participation in agricultural operations

In order to test the significance of association between labours participation in agriculture and caste of the agricultural labours’ family members the chi-square value has been calculated. For the overall zone category, the calculated chi-square (χ²) value is found (33.093) to be more than the critical value (9.21) for 2 degrees of freedom at one per cent probability level. The chi-square values have also been calculated separately for dry land and irrigated. The calculated value found to be statistically significant at one per cent probability level. Therefore, it could be inferred that the caste of the respondents’ family members influence the agricultural labour supply.

Land holding

In rural economy, land holding is determines the economic condition of the family and agricultural labour supply is influenced by the land holding of agricultural labour households. Data relating to the size of land holdings has been collected from the sample respondents. The land holding of the respondents ranges from 0 to 02 acres and thus respondents have been categorized under two groups viz land less labours (having no land) and land holding labours (less than 2 acres). The frequency distribution of agricultural labours family members’ participation in agricultural operation across the different land holding category is presented in the table 4.

Table 4. Land holding of the agricultural labourers’ family members and labours participation in agricultural operations

Land holding	Labours participation in agricultural operations
Land holding	Doing agricultural works	Not doing agricultural works	Total	χ²
Overall
Land less Labours’ Family members	197 (42.5%)	267 (57.5%)	464 (100%)	14.874*
Land holding labours’ family members	84 (28.6%)	210 (71.4%)	294 (100%)
Total	281 (37.1%)	477 (62.9%)	758 (100%)

Notes: 1) Figures in parenthesis are per centage to total.

2)* indicate the significance at 1 per cent probability level.

The above table shows that the participation of agricultural labours family members across different land holding size separately for dry land and irrigated land. In the overall category, out of 758 family members, majority of the family members were belonging to land less family category followed by land holding family. Labour participation for agricultural activities was 42.5 per cent in land less family while 28.7 per cent in land holding family. On the other hand, 57.5 per cent of land less family members and 62.9 per cent of land holding family members are not participated in agricultural activities. It means that labour participation in agriculture has been continuously declining and labours are shifting to non-agricultural works.

In order to test the significance of association between land holding of respondents’ family members and the labours participation in agricultural operations, chi-square test has been calculated. The calculated chi-square (χ²) value for the overall category was found (14.874) to be more than the critical value (6.63) for 1 degree of freedom at 1 per cent probability level. Therefore, it could be inferred that the association between level of participation in agriculture and land holding of respondents’ family members is statistically significant. Similar inference could be drawn for dry land and irrigated land. It clearly shows that labours participation in non-agricultural activities was highest and labours are finding better employment opportunities in the non- agricultural activities due to higher wage rate, availability of works in nearby cities and improved infrastructures like telephone, road connectivity and transportation has increased employment opportunities.

Figure 4: Land holding and labours participation in agricultural operations

CONCLUSION:

Once India was agricultural labour abundant country but now farmers are facing acute labour scarcity during the peak agricultural activities. The study has revealed that agricultural labour supply has been drastically decreasing in Davangere district of Karnataka. The study found that labour supply has been shifting towards non-agricultural sector rapidly. With the increase in education in rural area, youths of the present day are reluctant to work in agricultural sector and they are trying to search jobs in urban areas and want to settle there only. In view of decreasing agricultural labour supply in Davangere district of Karnataka, the study has made following suggestions for improving the labour supply.

· Educate the farmers to adopt modern labour saving implements or techniques. For example using weedicides instead of manual labour and it is better to use harvester/thresher instead of manual labour to reduce the cost of harvesting in crops like Finger millet etc.

· Government has to provide necessary farm implements on rental basis because most of the small and marginal farmers can’t afford to buy them.

· Agricultural universities/agricultural departments have to come up the new innovations/strategies to help farmers to reduce labour in agricultural activities.

CONFLICT OF INTEREST:

The authors have no conflicts of interest regarding this investigation.

REFERENCE:

1. R Mahesh. Labour mobility and paradox of rural unemployment-farm labour shortage: A micro level study. The Indian journal of labour economics. 2004; 47(1): 115-133.

2. C Prabhakar, K Sita Devi, S Selvam. Labour scarcity-Its immensity and impact on agriculture. Agricultural economics Research Review. 2011; 24: 373-380.

3. S H Baba, M H Wani, F A Shaheen, Bilal A Zargar, S S Kubrevi. Scarcity of agricultural labour in cold-arid Ladakh: Extent, implications, backward bending and coping mechanism. Agricultural Economics Research Review. 2011; 24: 391-400.

Received on 30.12.2022 Modified on 17.07.2023

Res. J. Humanities and Social Sciences. 2024;15(1)19-23.

DOI: 10.52711/2321-5828.2024.00004