924 resultados para Sun farm


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This article explores how data envelopment analysis (DEA), along with a smoothed bootstrap method, can be used in applied analysis to obtain more reliable efficiency rankings for farms. The main focus is the smoothed homogeneous bootstrap procedure introduced by Simar and Wilson (1998) to implement statistical inference for the original efficiency point estimates. Two main model specifications, constant and variable returns to scale, are investigated along with various choices regarding data aggregation. The coefficient of separation (CoS), a statistic that indicates the degree of statistical differentiation within the sample, is used to demonstrate the findings. The CoS suggests a substantive dependency of the results on the methodology and assumptions employed. Accordingly, some observations are made on how to conduct DEA in order to get more reliable efficiency rankings, depending on the purpose for which they are to be used. In addition, attention is drawn to the ability of the SLICE MODEL, implemented in GAMS, to enable researchers to overcome the computational burdens of conducting DEA (with bootstrapping).

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The resilience of family farming is an important feature of the structure of the farming industry in many countries, due largely to the 'smooth' succession of farms from one generation to the next. The stability of this structure is now threatened by the widening gap between the income expected from farming when compared with non-farming occupations in an economy like Ireland, operating at almost full employment. Nominated farm heirs are increasingly unlikely to choose full-time farming as their preferred occupation. To identify the factors that affect this occupational choice, a multinomial logit model is developed and applied to Irish data to examine the farm, economic and personal characteristics that influence a nominated heir's decision to enter farming as opposed to some non-farming occupation. The results show a significant negative relationship between higher education and the choice of full-time farming as an occupation. The interdependence between education and occupational choices is further explored using a bivariate probit model. The main findings are: the occupational choice and the decision to continue with higher education are made jointly; the nominated heirs on more profitable farms are less likely to pursue tertiary education and therefore more likely to enter full-time farming. The model developed is sufficiently general for studying the phenomenon of succession on farms.

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This paper assesses the impact of the 'decoupling' reform of the Common Agricultural Policy on the labour allocation decisions of Irish farmers. The agricultural household decision-making model provides the conceptual and theoretical framework to examine the interaction between government subsidies and farmers' time allocation decisions. The relationship postulated is that 'decoupling' of agricultural support from production would probably result in a decline in the return to farm labour but it would also lead to an increase in household wealth. The effect of these factors on how farmers allocate their time is tested empirically using labour participation and labour supply models. The models developed are sufficiently general for application elsewhere. The main findings for the Irish situation are that the decoupling of direct payments is likely to increase the probability of farmers participating in the off-farm employment market and that the amount of time allocated to off-farm work will increase.

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In this paper, the yield increases resulting from the cultivation of Bt cotton in Maharashtra, India, are analysed. The study relies on commercial farm, rather than trial, data and is among the first of its kind to be based on real farm and market conditions. Findings show that since its commercial release in 2002, Bt cotton has had a significant positive impact on yields and on the economic performance of cotton growers in Maharashtra. This difference remains even after controlling for different soil and insecticide inputs in the production of Bt cotton. There is also significant spatial and temporal variation in this 'benefit', and much depends upon where production is taking place and on the season.

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If the fundamental precepts of Farming Systems Research were to be taken literally then it would imply that for each farm 'unique' solutions should be sought. This is an unrealistic expectation, but it has led to the idea of a recommendation domain, implying creating a taxonomy of farms, in order to increase the general applicability of recommendations. Mathematical programming models are an established means of generating recommended solutions, but for such models to be effective they have to be constructed for 'truly' typical or representative situations. The multi-variate statistical techniques provide a means of creating the required typologies, particularly when an exhaustive database is available. This paper illustrates the application of this methodology in two different studies that shared the common purpose of identifying types of farming systems in their respective study areas. The issues related with the use of factor and cluster analyses for farm typification prior to building representative mathematical programming models for Chile and Pakistan are highlighted. (C) 2003 Elsevier Science Ltd. All rights reserved.

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The paper explores the impact of insect-resistant Bacillus thuringiensis (Bt) cotton on costs and returns over the first two seasons of its commercial release in three sub-regions of Maharashtra State, India. It is the first such research conducted in India based on farmers' own practices rather than trial plots. Data were collected for a total of 7793 cotton plots in 2002 and 1577 plots in 2003. Results suggest that while the cost of cotton seed was much higher for farmers growing Bt cotton relative to those growing non-Bt cotton, the costs of bollworm spray were much lower. While Bt plots had greater costs (seed plus insecticide) than non-Bt plots, the yields and revenue from Bt plots were much higher than those of non-Bt plots (some 39% and 63% higher in 2002 and 2003, respectively). Overall, the gross margins of Bt plots were some 43% (2002) and 73% (2003) higher than those of non-Bt plots, although there was some variation between the three sub-regions of the state. The results suggest that Bt cotton has provided substantial benefits for farmers in India over the 2 years, but there are questions as to whether these benefits are sustainable. (c) 2004 Elsevier Ltd. All rights reserved.

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A questionnaire survey of 408 households explored the role of socio-economic and cultural factors in rice (Oryza sativa L.) varietal diversity management on-farm in two contrasting eco-sites in Nepal. Multiple regression outputs suggest that number of parcels of land, livestock number, number of rice ecosystems, agro-ecology (altitude), and use of chemical fertilizer have a significant positive influence on landrace diversity on-farm, while membership in farmers' groups linked to extension services has significant but negative influence on landrace diversity. Factors with significant positive influence on diversity of modern varieties on-farm were number of parcels of land and of rice ecosystems, access to irrigation, membership in farmers' groups, and use of insecticide. Within communities, resource-endowed households maintain significantly higher varietal diversity on-farm than resource-poor households and play a significant role in conserving landraces that are vulnerable to genetic erosion and those with socio-cultural and market-preferred traits. Resource-poor households also contribute to local diversity conservation but at lower richness and area coverage levels than resource-endowed households. Households where a female had assumed the role of head of household due to death or migrant work of her husband had less diversity due to lower labor availability. Landraces with socio-cultural and market-preferred traits are few in number but have potential to be conserved on-farm.

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Recent reform of the EU’s Common Agricultural Policy (CAP) has led to a further decoupling of farm support. The EU believes that the new Single Payment Scheme, which replaces the former system of area and headage payments to farmers, tied to production, will qualify for green-box status in the WTO. We examine this contention, particularly in light of the recent WTO panel report on upland cotton.

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Logistic regression, supported by other statistical analyses was used to explore the possible association of risk factors with the fluoroquinolone (FQ)-resistance status of 108 pig finisher farms in Great Britain. The farms were classified as 'affected' or 'not affected' by FQ-resistant E. coli or Campylobacter spp. on the basis of isolation of organisms from faecal samples on media containing 1 mg/l FQ. The use of FQ was the most important factor associated with finding resistant E. coli and/or Campylobacter, which were found on 79% (FQ-resistant E. coli) and 86% (FQ-resistant Campylobacter) of farms with a history of FQ use. However, resistant bacteria were also found on 19% (FQ-resistant E. coli) and 54% (FQ-resistant Campylobacter) of farms with no history of FQ use. For FQ-resistant E. coli, biosecurity measures may be protective and there was strong seasonal variation, with more farms found affected when sampled in the summer. For FQ-resistant Campylobacter, the buying-in of grower stock may increase risk and good on-farm hygiene may be protective. The findings suggest that resistant organisms, particularly Campylobacter, may spread between pig farms.

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A Bayesian method of classifying observations that are assumed to come from a number of distinct subpopulations is outlined. The method is illustrated with simulated data and applied to the classification of farms according to their level and variability of income. The resultant classification shows a greater diversity of technical charactersitics within farm types than is conventionally the case. The range of mean farm income between groups in the new classification is wider than that of the conventional method and the variability of income within groups is narrower. Results show that the highest income group in 2000 included large specialist dairy farmers and pig and poultry producers, whilst in 2001 it included large and small specialist dairy farms and large mixed dairy and arable farms. In both years the lowest income group is dominated by non-milk producing livestock farms.