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Barriers and Drivers Underpinning Newcomers in Agriculture: Evidence from Italian Census Data

doi: 10.3390/su151410755
handle: 11695/123129
The present study addresses, for the first time, the difference between older and younger farmers (those aged over and under 40 years) and proposes a methodology to identify factors that affect generational renewal in the Italian agricultural sector in positive and negative ways. The study is carried out using data collected by the General Census of Agriculture of 2020. Firstly, a T-test is used to test the hypothesis of differences between farmers aged under 40 and those over 40. Secondly, linear regression models are constructed to address the factors that affect generational renewal in the Italian agricultural sector. The findings highlight some important initiatives that decision-makers can consider for further action in the Italian agricultural sector at a regional level. Large-scale farming is very likely to attract newcomers to Italian agriculture and has a strong impact on generational turnover. In contrast, sustainable agricultural practices are less attractive, as they require specific responsibilities, knowledge, and technical and organisational solutions that young people may not yet have. Similarly, educational attainment increases the probability that young farmers will move from rural to urban areas. Finally, older farmers, with respect to newcomers, have more capital for innovative investments in the agricultural sector and information technology for business management and have more experience with waste management.
- University of Molise Italy
- University of Molise Italy
agricultural sector, generational turnover, Italian regions, linear regression models, Student’s T-test analysis, Environmental effects of industries and plants, TJ807-830, TD194-195, linear regression models, Renewable energy sources, Environmental sciences, agricultural sector; generational turnover; Italian regions; linear regression models; student’s T-test analysis, Italian regions, student’s T-test analysis, GE1-350, generational turnover, agricultural sector
agricultural sector, generational turnover, Italian regions, linear regression models, Student’s T-test analysis, Environmental effects of industries and plants, TJ807-830, TD194-195, linear regression models, Renewable energy sources, Environmental sciences, agricultural sector; generational turnover; Italian regions; linear regression models; student’s T-test analysis, Italian regions, student’s T-test analysis, GE1-350, generational turnover, agricultural sector
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).2 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
