2010
DOI: 10.1111/j.1477-9552.2010.00272.x
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Technology Adoption and Pest Control Strategies Among UK Cereal Farmers: Evidence from Parametric and Nonparametric Count Data Models

Abstract: This paper examines technology adoption and integrated pest management strategies employed by UK farmers, using both parametric and nonparametric methods. We employ a unique survey data set collected from UK cereal farmers to assess the determinants of technology adoption in relation to pest management. Our preferred model specification is nonparametric which makes use of the recently developed methods of Li and Racine (2007) and Racine and Li (2004). These methods allow us to combine categorical and continuou… Show more

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Cited by 71 publications
(43 citation statements)
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“…However, these methods provide computational difficulties when the number of technologies becomes greater than two in the case of MNL or more than four in the case of multivariate probit. Lohr and Park (2002), Rahelizatoro and Gillespie (2004) and Sharma et al (2010) have used the total number of technologies as a measure of adoption intensity. However, count regression models are not commonly used in this literature because most studies focus on the adoption of each specific technology.…”
Section: Literature Reviewmentioning
confidence: 99%
See 1 more Smart Citation
“…However, these methods provide computational difficulties when the number of technologies becomes greater than two in the case of MNL or more than four in the case of multivariate probit. Lohr and Park (2002), Rahelizatoro and Gillespie (2004) and Sharma et al (2010) have used the total number of technologies as a measure of adoption intensity. However, count regression models are not commonly used in this literature because most studies focus on the adoption of each specific technology.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Measures of adoption intensity have been investigated by Mazvimavi and Twomlow (2009) in the case of CA. Adoption of CA is more appropriately modelled as a multiple technology selection because it is promoted as a package and understanding adoption intensity has become important especially in an environment where farmers have to make complex agronomic choices (Sharma et al, 2010).…”
Section: Literature Reviewmentioning
confidence: 99%
“…Cost associated with AD plants has been identified as one of the generic limitations to its development (Zglobisz et al 2010;Bywater 2011). Similarly, Sharma et al (2011) broadly stated that the constraints with technological adoption are usually socio-economic in nature in their study of the determinants of technology adoption among UK cereal farmers. The second most popular factor considered by the farmers was knowledge of its benefits.…”
Section: Implication Of Findings For Ad Adoption In the Ukmentioning
confidence: 99%
“…In developed countries like the UK, agricultural innovations have been applied to several aspects of agriculture other than irrigation, fertilizer application and drainage. These include land use changes (Burgess and Morris 2009), pest control (Sharma et al 2011), organic farming (Tiffin and Balcombe 2011) and farm monitoring (Purdy 2011). Innovations in the area of renewable energy like anaerobic digestion (AD) technology, have been extensively used in agriculture for energy generation, source of income and organic fertilizer in some parts of Europe and the Unites States but are not well adopted in the UK (Zglobisz et al 2010).…”
Section: Introductionmentioning
confidence: 99%
“…Although the UK scores relatively highly for internet speed and access within the European Union (ITU 2011), these values will be skewed by urban densities, whereas sheep producers are located in the more remote areas (AHDB Beef and Lamb 2016, Scottish Government 2016), This has been highlighted as an issue for some time; one that has led to a ‘digital divide’ between the relatively extensive, smaller, more rurally based cattle and sheep producers and the larger-scale intensive arable and dairy sectors (Warren 2002, 2004). Cultural barriers may include the older age of the average farmer (Sharma and others 2011, Matthews 2012) at 59 years old (Defra 2015), decision-making styles (Jørgensen and others 2007) and preferences for more traditional methods of information provision (Kaler and Green 2013). However, perhaps one of the most pertinent factors may be the view that sheep farmers hold: the view that sheep farming is complex; they are the experts with unique understanding and insights—particularly into the management of their own flock—to which any outsider can make only a limited contribution (Kaler and Green 2013).…”
mentioning
confidence: 99%