Agricultural Economics Research Review
  • Year: 2021
  • Volume: 34
  • Issue: 1

An analysis of Indian agricultural workers: A ridge regression approach

1Department of Physical Sciences and Languages, COBS, CSK HPKVPalampur, Himachal Pradesh

2Sher-e-Kashmir University of Agricultural Sciences & Technology-Jammu (J), Chatha, 180 009, J&K

*Corresponding author: manshstat@gmail.com

Online published on 29 September, 2021.

Abstract

The agriculture sector in India cannot productively employ the growing rural labour force, and farmers are forced to look for other employment for their livelihood. This paper attempts to understand the increasing marginalization of the Indian agricultural workforce through different parameters which were influenced with multicollinearity. To handle multicollinearity in the data, this paper uses the ridge regression technique. The results shows that the value of the ridge constant K was found to be 0.02, at which the ridge regression model estimated the number of Indian agricultural workers more precisely than the ordinary least squares model.

Keywords

Agricultural workers, Multicollinearity, Variance inflation factor, Ridge regression, R square