Sukant K. Misra

Crop-Yield Distributions Revisited

This article revisits the issue of crop-yield distributions using improved model specifications, estimation, and testing procedures that address the concerns raised in recent literature, which could have invalidated previous findings of yield nonnormality. It concludes that some aggregate and farm-level yield distributions are nonnormal, kurtotic, and right or left skewed, depending on the circumstances. The advantages of utilizing nonnormal versus normal probability distribution function models, and the consequences of incorrectly assuming crop-yield normality are explored.

Efficient Estimation of Agricultural Time Series Models with Nonnormal Dependent Variables

This article proposes using an expanded form of the Johnson S U family as a way to approximate nonnormal distributions in regression models. The distribution is one of the few that allows modeling heteroskedasticity and autocorrelation. The technique is evaluated with Monte Carlo simulation and illustrated through an empirical model of the West Texas cotton basis. Given nonnormality, this technique can substantially reduce the variance of slope parameter estimates relative to least squares procedures. Copyright 2003, Oxford University Press.

Cotton Farmers' Technical Efficiency: Stochastic and Nonstochastic Production Function Approaches

Technical efficiency for cotton growers is examined using both stochastic (SFA) and nonstochastic (DEA) production function approaches. The empirical application uses farm-level data from four counties in west Texas. While efficiency scores for the individual farms differed between SFA and DEA, the mean efficiency scores are invariant of the method of estimation under the assumption of constant returns to scale. On average, irrigated farms are 80% and nonirrigated farms are 70% efficient. Findings show that in Texas, the irrigated farms, on average, could reduce their expenditures on other inputs by 10%, and the nonirrigated farms could reduce their expenditures on machinery and labor by 12% and 13%, respectively, while producing the same level of output.

INCORPORATING THE IMPACTS OF UNCERTAIN FIELDWORK TIME ON WHOLE-FARM RISK-RETURN LEVELS: A TARGET MOTAD APPROACH

Given an equipment complement, a specific crop mix has a probability distribution for whole-farm net returns. Increasing crop acreage while holding the set of equipment constant will reduce fixed costs per acre, but it will also increase the length of time required to complete crucial field operations such as planting and harvesting. Thus, the probability of encountering weather-related delays in fieldwork will increase. This increase in delays may cause a decline in yields and changes in the distribution of net returns. This paper develops a Target MOTAD model capable of capturing intra-year impacts on profit that arise from the timing of planting and harvesting operations as well as inter-year impacts on profits that are due to variations in economic and weather-related factors. The model relies on estimates of available fieldwork time and a crops harvestable yield in different time periods throughout the harvest season.

Evaluating Crop and Revenue Insurance Products as Risk Management Tools for Texas Cotton Producers

This paper develops and illustrates the application of a procedure to evaluate and compare the cost effectiveness of alternative crop insurance products for cotton in terms of their effect on expected producer net returns and the variation of net returns. Farm unit-level cotton yields and state-level price distributions are estimated by a multivariate nonnormal parametric modeling procedure and used to simulate the net returns to alternative crop insurance products over a 10-year planning horizon. The ranking of alternative insurance products using third-degree stochastic dominance is presented for Texas cotton producers.

The effects of MFA quota elimination on Indian fibre markets

This article examines the effects of multi-fibre arrangement (MFA) quota elimination on Indian fibre market. The partial equilibrium Indian fibre model was developed using a theoretically consistent framework and incorporated regional supply response, substitutability between cotton and man-made fibres, and appropriate linkage between cotton and textile sectors. Baseline projections were developed for supply, demand and prices of cotton, man-made fibres and textiles under a set of exogenous assumptions. The effects of MFA textile quota eliminations were introduced into the model by conducting three scenarios, i.e. increasing textile exports by 10, 20 and 30% from the baseline level. The results suggest that on an average, cotton imports rise by 4–8% annually, while the man-made fibre exports from India decline with the opening of textile markets in the developed countries. The higher domestic cotton prices encourage acreage expansion in cotton in all the three regions in India, but not enough to meet rising mill demand under the scenarios of higher textile exports. The rise in cotton imports from India has little effect on world cotton prices.

Minimizing Farm-to-Mill Cotton Cleaning cost

This study focuses on least-cost farm-to-mill cotton cleaning configurations employing survey, regression, and simulation techniques. The resulting least-cost cotton cleaning configurations, employing standard textile technology, included the use of one lint cleaning in the ginning stage. The use of a field cleaner in the harvesting stage was also found to be optimal with some variation based on the desired yarn quality. Results of the study indicated that the optimal cleaning configurations were distinctly different from currently used practices, such that appropriate changes could save the cotton industry between

Perception of food safety and changes in food consumption habits: a consumer analysis

0.30 and

A Qualitative Choice Analysis of Factors Influencing Post-CRP Land Use Decisions

0.60 per bale of cotton, depending on the desired yarn quality.