*Research Scholar, School of Management Studies, Jawaharlal Nehru Technological University, Hyderabad, India.
**Professor & Chairman BOS, School of Management Studies, Jawaharlal Nehru Technological University, Hyderabad, India.
Online published on 31 August, 2012.
Agriculture in our country has not received as much attention as that in the field of agricultural production. In an agricultural country like India, the most of the agricultural crises are faced by the agriculturist and so on effect will be passed to laborers. The instability yield and prices more in the case of commercial crops that has been showing a greater implications and become a serious problem in generating the stability in income of the farmers. In this scenario this paper looks at the determinants of agricultural wages and its linkage and effects with agriculturalist across a particular village called Bhoraj of Adilabad District. as we know the agricultural wages varies from region to region and within the region, this paper empirically analyses the patterns in agricultural wages and its impact on the agriculturist of village Bhoraj the results and analyses drawn from the study states that manpower prices as dramatically risen due to the various schemes adopted by the government of India for example like employment grantee scheme, rajiv roaj ghari yojana, sadahak yojana, MGNREGS and so on, due to this an small and medium farmers are in crises. This paper as shows and understand the insight of the agriculturist. In this paper we tried to concentrate on to check the reasons for sudden rise in prices of agricultural manpower, Is there any influence of government policies, Do farmers have any solution for the problem.The results shows that the reliability Statistics Cronbach's Alpha is.972 and R value in Regression is.955 and R-Square value is.912 and KMO and Bartlett's Test Measure of Sampling Adequacy is.883 more than0.5 which indicate statistically significant and Bartlle value is highly significant with.000. This is less than 0.05. The Extraction Sums of Squared Loadings are at 87% which indicate 13% data was extracted from the study which is nearly significant.
wage structure, cotton farmers, labors, crises