The Relationship between Population and Labor in the Agricultural Sector: A Regression Model for Dependency Forecasting
Shiv Shankar Soni
Department of Agriculture Statistics, National PG College Barhalganj Gorakhpur, U.P., India.
Navin Upadhyay *
Department of Mathematics and Statistics, Deen Dayal Upadhyaya Gorakhpur University, Gorakhpur, U.P., India.
Himanshu Pandey
Department of Mathematics and Statistics, Deen Dayal Upadhyaya Gorakhpur University, Gorakhpur, U.P., India.
*Author to whom correspondence should be addressed.
Abstract
A sizable section of the population still relies heavily on agriculture for their livelihood, particularly in developing nations. Effective planning, policymaking, and resource allocation require a clear understanding of how population changes influence agricultural dependence. This study develops both linear and exponential regression models to forecast the number of individuals dependent on agriculture by incorporating population growth and key socioeconomic variables. Using historical population and agricultural workforce data, the models identify the strength and direction of the relationship between population size and agricultural dependency. The results show a strong positive correlation, indicating that population expansion continues to place significant pressure on the agricultural sector. These predictive models provide valuable insights for researchers, planners, and policymakers seeking to design sustainable agricultural strategies and promote rural development.
Keywords: Workforce forecasting, population expansion, agricultural reliance, regression analysis, agricultural planning