Participatory Farm Management methods for assessing the suitability of potential innovations. A case study on green manuring options for tomato producers in Ghana

This paper examines the potential of using Participatory Farm Management methods to examine the suitability of a technology with farmers prior to on-farm trials. A study examining the suitability of green manuring as a technology for use with wet season tomato producers in Ghana is described. Findings from this case-study demonstrate that Participatory Budgeting can be used by farmers and researchers to analyse current cultivation practices, identify the options for including green manures into the system and explore the direct and wider resource implications of the technology. Scored-Causal Diagrams can be used to identify farmers' perceptions of the relative importance of the problem that the technology seeks to address. The use of the methods in this examine evaluation process appears to have the potential to improve the effectiveness and efficiency of the adaptive research process. This ensures that technologies subsequently examined in trials ate relevant to farmers' interests, existing systems and resources, thereby increasing the chances of farmer adoption. It is concluded that this process has potential for use-with other technologies and in other farming systems. (C) 2002 Elsevier Science Ltd. All rights reserved.

Ranking efficiency units in DEA using bootstrapping an applied analysis for Slovenian farm data

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).

An investigation into factors affecting the occupational choices of nominated farm heirs in Ireland

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.

Assessing the impact of the 'Decoupling' reform of the common agricultural policy on Irish farmers' off-farm labour market participation decisions

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.

Farm-level performance of genetically modified cotton - A frontier analysis of cotton production in Maharashtra

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.

Typification of farming systems for constructing representative farm models: two illustrations of the application of multi-variate analyses in Chile and Pakistan

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.