Farmer′s Impact of the New Rural Pension Insurance

S Sitesh^*
*Correspondence: S Sitesh, Department of Engineering & Technology, Wollega University, Nekemte, Ethiopia, Email:

Keywords

Labour supply • Economic rationality • Optimal allocation

Introduction

Farmers should go with AMS to make up for the lack of family agricultural workers and save money on labour. The farmers' AMS inputs will rise in line with this. The crowding-out effect of non-farm labour transfer is the second aspect. According to some studies, elderly people will be more likely to care for their grandchildren when they receive a significant amount of unanticipated pension income. As a result, the number of young and middleaged workers in the family will rise. The NRPI effectively encourages the off-farm transfer of young and middle-aged household labourers by reducing pension risks for elderly farmers and constraints on child care. In addition, the off-farm transfer of young and middle-aged workers will reduce the quantity and quality of household agricultural labour supply, resulting in an increase in AMS inputs for older farmers' households. The following hypotheses are proposed based on the preceding analysis. Even though non-elderly farming households have not received NRPI pension income this year, they have increased their expectations for the pension security of participating farmers. This also has an impact on how the labour resources of farming households are distributed and encourages off-farm labour transfer, which has a positive impact on their AMS inputs, which is just as important.

Description

The crowding-out effect of the labour off-farm transfer is the primary way the NRPI contributes to the rise in farm mechanization service inputs for non-elderly farm households. Younger grandparents who are still able to work in non-farm households are more likely to work than to take care of their grandchildren. Young grandparents who are still able to work are more likely to work in such households than to take care of their grandchildren. As a result, in households without elderly members, the crowding out effect of NRPI caused by grandchild caregiving has little effect on AMS input. Increased investment in employment leads to an increase in the non-farm labour supply as participation in NRPI reduces uncertainty about future income sources. Farm household AMS inputs significantly rise in tandem with the increase in non-farm employment. Then, NRPI reduces the agricultural labour input per unit of arable land area for non-elderly farm households by encouraging off-farm transfer of farm household labour. As a result, their AMS inputs are accelerated as a result of this. As a result, we propose the following research hypotheses. In addition to the aforementioned key variables, this study controlled for variables based on previous research, including the primary characteristics of the labor force, farm household characteristics, village characteristics and regional characteristics. In particular, there were four primary variables:

The proportion of men, average age, average level of education and average health status were the variables of key labour force characteristics (features of non-elderly farming households between the ages of 25 and 59 and elderly farming households between the ages of 60 and 80). The household size, labour force percentage, value of agricultural machinery, borrowing restrictions, migrant worker remittances, agricultural income level, household net income per capita and government subsidies (whether they received various government income transfers) were the household characteristics variables. The distance from the county, proportion of village agricultural labour, number of children and elderly population were some of the village characteristics variables [1-5].

Conclusion

In this study, the primary grain-producing regions were designated as regional dummy variables for the purpose of the regional characteristic variables. Additionally, agricultural income level was used as an approximate proxy for arable land area and incorporated into the model as a control variable due to the lack of data on arable land area in the CFPS data used and the strong correlation between arable land area and agricultural income of food growers. The specific method consisted of dividing farm household income into low, medium and high agricultural income levels. The descriptions and descriptive statistics for each of the aforementioned variables are listed. Our understanding of the performance of the new rural insurance policy has been somewhat enhanced by the research presented in this paper on the spill over effect of the new rural insurance and household AMS expenditure. Additionally, we viewed this particular experience as a valuable source of inspiration for the sustainable growth of agriculture. Numerous international studies based on survey data from various nations have demonstrated that old-age security will increase the non-agricultural labour supply of young and middle-aged workers while decreasing the supply of elderly workers. Additionally, the mode of agricultural production will be altered by the shift in household labour supply. As a result, efforts ought to be put into enhancing the national pension security system, raising the pension and welfare levels of the elderly in rural areas and advocating for the best possible use of rural land resources.

Acknowledgement

None.

Conflict of Interest

No potential conflict of interest was reported by the authors.

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