determinants of technology adoption by UK farmers using Bayesian model averaging: the cases of organic production and computer usage

• Published in: The Australian journal of agricultural and resource economics 2011-10, Vol.55 (4), p.579-598
• Main Authors: Tiffin, Richard, Balcombe, Kelvin
• Format: Article
• Language: English
• Subjects: Agricultural economics; Agricultural production; Agriculture; Attitudes; attitudes and opinions; Bayesian method; Bayesian model averaging; Chemicals; Choice of technology; Computer equipment; Computers; Demographic factors; Economic models; Economic theory; Economics; Education; educational status; Environmental management; Farm income; farm size; Farmers; Farming methods; Farms; foods; Great Britain; innovation adoption; net farm income; Organic farming; organic production; probability; reversible jump algorithm; society; Studies; Technological change; Technology adoption; Uncertainty; United Kingdom; Worker numbers
• ISSN: 1364-985X; 1467-8489
• DOI: 10.1111/j.1467-8489.2011.00549.x

We review and implement a reversible jump approach to Bayesian model averaging for the Probit model with uncertain regressors. Two applications are investigated. The first is the adoption of organic systems in UK farming, and the second is the influence of farm and farmer characteristics on the use of a computer on the farm. While there is a correspondence between the conclusions we would obtain with and without model averaging results, we find important differences, particularly in smaller samples. Concerning the adoption of an organic system, we find that attitudes to the sustainability of the current system along with the ability of organic farms alone to satisfy society’s needs for food are influential. Additionally, the source of management information used by the farmer has a significant impact. Regarding the adoption of computers, we confirm the findings of previous work that the level of education affects uptake and that age is a factor determining adoption. We also find that dairy and organic farms are more likely to use a computer. The physical size of the farm is positively associated with the probability of computer use while net farm income has a limited impact.