Sustainable Cotton Production through Skill Development among Farmers: Evidence from Khairpur District of Sindh, Pakistan

This study on farmers’ training in environment friendly production practices for cotton crop was conducted in the Khairpur district of Sindh province. Data used in this study comprises baseline and post IPM Farmer Field School (FFS) impact surveys conducted during 2001 and 2003 respectively. The programme impacts were estimated on gross margins and changes in farmers’ attitude towards environment and biodiversity. The effect of training on social recognition of farmers, their experimentations abilities, and decision making skills were also examined. Beside single difference comparisons of change in production practices between trained and non-trained farmers, the difference in difference (DD) method was also used for comparisons among FFS farmers, exposed farmers and un-exposed farmers from control villages. The stochastic production frontier model incorporating inefficiency effects is also estimated to analyze the impact of farmers’ training (through FFS) on productivity and efficiency at cotton farms in the study area. Results show better cotton yield and reduction in cost of pesticides and fertilizer inputs enabled FFS farmers to fetch significantly higher gross margins (US$391/ha) than non-FFS (US$ 151/ha) and Control farms (US$ 25/ha). The total application of pesticide chemicals was largely reduced (44%) on FFS farms. The cost of inefficiency at FFS farms was lower (23.71%) as compared to those on non-FFS farms (30.50%) which implies that FFS farmers were able to maintain higher level of technical efficiency. It is concluded that the FFS approach is not only cost efficient but also improves farm level technical efficiency. Information generated through Agro-ecosystem analysis on pest and predator dynamics helps farmers to understand pest-predator interaction to allow nature to work with lesser or most appropriate interventions. A well-planned technical backup support mechanism is recommended to be evolved through integrating research system into farmer-led experimentation. The Programme achievements show that FFS approach in Pakistan has furthered from only crop management to systems management and community development approach and should be supported further to enter into mass scale expansion state.Cotton Production; Skill Development; Production Frontier; Efficiency; Pakistan

Sustainable Cotton Production Through Skill Development among Farmers: Evidence from Khairpur District of Sindh, Pakistan.

This study on farmers’ training in environment-friendly production practices for cotton crop was conducted in the Khairpur District of Sindh province. Data used in this study comprises baseline and post- IPM Farmer Field School (FFS) impact surveys conducted during 2001 and 2003 respectively. The programme impacts were estimated on gross margins and changes in farmers’ attitude towards environment and biodiversity. The effect of training on social recognition of farmers, their experimentation abilities, and decision-making skills were also examined. Beside single difference comparisons of change in production practices between trained and non-trained farmers, the difference in difference (DD) method was also used for comparisons among FFS farmers, exposed farmers, and unexposed farmers from controlled villages. The stochastic production frontier model incorporating inefficiency effects is also estimated to analyse the impact of farmers’ training (through FFS) on productivity and efficiency at cotton farms in the area under study. The results show that better cotton yield and reduction in the cost of pesticides and fertiliser inputs enabled FFS farmers to fetch significantly higher gross margins (US$391/ha) than non-FFS (US$ 151/ha) and Control farms (US$ 25/ha). The total application of pesticide chemicals was largely reduced (44 percent) on FFS farms. The cost of inefficiency at FFS farms was lower (23.71 percent) as compared to those on non-FFS farms (30.50 percent), which implies that FFS farmers were able to maintain a higher level of technical efficiency. It is concluded that the FFS approach is not only cost efficient but also improves farm-level technical efficiency. Information generated through Agro-ecosystem analysis on pest and predator dynamics helps farmers to understand pest-predator interaction to allow nature to work with fewer or most appropriate interventions. A wellplanned technical back-up support mechanism is recommended to be evolved through integrating the research system into farmer-led experimentation. The programme achievements show that the FFS approach in Pakistan has furthered from only crop management to systems management and community

RISK EFFICIENCY OF ALTERNATE CANOLA MANAGEMENT DECISIONS

This study evaluates profitability and risk associated with eighteen different management decisions for canola production in Alberta. Expected payoff from cultivar selection outweighs the payoff from time of seeding and from time of weed control. Expected payoff was higher from hybrid compared to inbred cultivars. Early spring seeding was more profitable than fall or mid-May seeding. A typical decision in the sample showed positive and significant upper limit risk-expected return tradeoffs. The generalized stochastic dominance analysis revealed that early spring seeding was dominant over fall and mid-May seeding across all risk averse and risk neutral farmers. Weed control at the six-leaf stage was risk efficient for a risk averter. A risk neutral farmer preferred weed control at the three to four-leaf stage or six-leaf stage, depending on cultivar.Risk and Uncertainty,

TESTS FOR THE ROLE OF RISK AVERSION ON INPUT USE

Agricultural inputs can create negative externalities. For risk averting agents, risk will alter production decisions while the existence of institutions to insure against adverse states of nature will likely restore decisions toward levels under risk neutrality. In this paper, conditions are identified on a stochastic technology to test that risk averters choose smaller input levels than risk neutral agents, and that an increase in risk aversion reduces input use. A robust statistical method (Klecan, McFadden, and McFadden) to test for dominance is adapted to stochastic production relations. It is found that the first hypothesis is likely true for nitrogen application on Iowa corn. Weaker evidence is found in favor of the second hypothesis.dominance tests, incomplete risk markets, ollution, stochastic technology, Farm Management, Risk and Uncertainty,

The Economics of Biotechnology under Ecosystem Disruption

Economic analysis of chemical pesticide use has shown that the interactions between plants, pests, damage control technology and state of the ecosystem are important variables to be considered. Hence, a bio-economic model was developed for the assessment of Bt variety and pesticide-based control strategies of the cotton bollworm in China. The model simulates plant growth, the dynamics of pest populations and of natural enemies. The model predictions are used as major inputs for a stochastic partial budgeting procedure of alternative control strategies. Results show that: (1) productivity effects of Bt varieties and pesticide use depend on the action of natural control agents, and (2) the profitability of damage control measures increases with the severity of ecosystem disturbance. The findings highlight the importance of the choice of a counterfactual scenario in the assessment of the impact of agricultural biotechnology. Also, some doubts are raised whether the high benefits of Bt cotton varieties based on cross section comparisons are realistic.Research and Development/Tech Change/Emerging Technologies, Q57, Q55, O13, O3,

The Impacts of Farm Size and Economic Risk on No-Till Rice Whole-Farm Profitability

This study evaluated the impacts of farm size and stochastic return variability on no-till (NT) rice profitability at the whole-farm level. Mixed integer programming was used to determine optimal machinery complements, fuel consumption, and machinery labor requirements for conventional till (CT) and NT rice-soybean farms of 1200, 2400, and 3600 acres in size. Crop yields, market prices, and prices for key production inputs were simulated to construct stochastic whole-farm net returns for each farm size under CT and NT management, and both first and second degree stochastic dominance analysis were used to rank cumulative distribution functions of whole-farm returns according to specified risk preferences. The results indicate NT farms exhibit second degree stochastic dominance over CT farms regardless of farm size, and high input prices have less downward effect on the profitability of NT farms relative to CT farms.mixed integer programming, no-till, profitability, rice, risk, simulation, stochastic dominance, whole-farm, Farm Management, Production Economics, Risk and Uncertainty,

Cost and Efficiency in Alberta Dairy Production

This study investigates the relationships between farm size, milk yield, cost of production, and technical efficiency in the Alberta dairy industry. Estimates of a stochastic production frontier are obtained with two alternative methods; an iterative "average frontier: (AF) procedure and a maximum-likelihood composed error (CE) term method. An index of technical efficiency is calculated for every herd in the sample, with the AF method resulting in an average efficiency ratio of 85 percent, and the CE method producing an average efficiency ratio of 83 percent. Regressions of production cost on milk output, herd size, and efficiency are used to test for the effects of size economies, yield economies, and technical efficiency on production cost. These results suggest that herd expansion, on average, would lower the average cost of production throughout the province. Romain and Lambert use a similar method in a study of Quebec and Ontario dairy farmers which shows a limited potential to exploit economies of herd size. While not a formal test of the similarity of the two industries, the results of this study indicate a significant difference between the optimal structure of dairy production in Alberta and Quebec. Such regional differences will have important implications for the possible reapportionment of the national milk market, whether by regulatory or free-market mechanisms.Livestock Production/Industries,

Mitigating Cotton Revenue Risk Through Irrigation, Insurance, and Hedging

This study focuses on managing cotton production and marketing risks using combinations of irrigation levels, put options (as price insurance), and crop insurance. Stochastic cotton yields and prices are used to simulate a whole-farm financial statement for a 1,000 acre furrow irrigated cotton farm in the Texas Lower Rio Grande Valley under 16 combinations of risk management strategies. Analyses for risk-averse decision makers indicate that multiple irrigations are preferred. The benefits to purchasing put options increase with yields, as they are more beneficial when higher yields are expected from applying more irrigation applications. Crop insurance is strongly preferred at lower irrigation levels.cotton, crop insurance, irrigation, options, puts, risk, simulation, stochastic efficiency with respect to a function, Farm Management, Risk and Uncertainty, D81, Q12, Q15,

BARLEY PRODUCTION COSTS: A CROSS-BORDER COMPARISON

Barley production costs are compared for five states and three Canadian provinces. A stochastic simulation, incorporating yield and exchange-rate risk, is used to characterize regional cost advantages in terms of probabilities.barley, production costs, yield risk, simulation analysis, Agricultural Finance, Production Economics,

EVALUATION OF ALTERNATIVE RISK SPECIFICATIONS IN FARM PROGRAMMING MODELS

The use of alternative probability density functions to specify risk in farm programming models is explored and compared to a traditional specification using historical data. A method is described that compares risk efficient crop mixes using stochastic dominance techniques to examine impacts of different risk specifications on farm plans. Results indicate that a traditional method using historical farm data is as efficient for risk averse producers as two other methods of incorporating risk in farm programming models when evaluated using second degree stochastic dominance. Stochastic dominance with respect to a function further discriminates among the distributions, indicating that a density function based on the historic forecasting accuracy of the futures market results in a more risk-efficient crop mix for highly risk averse producers. Results also illustrate the need to validate alternative risk specifications perceived as improvements to traditional methods.Risk and Uncertainty,