Agricultural and Biosystems Engineering Publications

Document Type

Article

Publication Date

1-2011

Journal or Book Title

Experimental Agriculture

Volume

47

Issue

17

First Page

111

Last Page

136

DOI

10.1017/S0014479710000979

Abstract

There are many reasons why agricultural researchers carefully evaluate approaches to experimental data analysis. Agricultural experiments are typically highly complex, with many types of variables often collected at a wide range of temporal and spatial scales. Furthermore, research in the developing world is often conducted on-farm where simple and conventional experimental designs are often unsuitable. Recently, a variant of stochastic dominance called stochastic efficiency with respect to a function (SERF) has been developed and used to analyse long-term experimental data. Unlike traditional stochastic dominance approaches, SERF uses the concept of certainty equivalents (CEs) to rank a set of risk-efficient alternatives instead of finding a subset of dominated alternatives. This study evaluates the efficacy of the SERF methodology for analysing conventional and conservation tillage systems using 14 years (1990–2003) of economic budget data collected from 36 experimental plots at the Iowa State University Northeast Research Station near Nashua, IA, USA. Specifically, the SERF approach is used to examine which of two different tillage systems (chisel plough and no-till) on continuous corn (Zea mays) and corn/soyabean (Glycine max) rotation cropping systems are the most risk-efficient in terms of maximizing economic profitability (gross margin and net return) by crop across a range of risk aversion preferences. In addition to the SERF analysis, we also conduct an economic analysis of the tillage system alternatives using mean-standard deviation and coefficient of variation for ranking purposes. Decision criteria analysis of the economic measures alone provided somewhat contradictive and non-conclusive rankings, e.g. examination of the decision criteria results for gross margin and net return showed that different tillage system alternatives were the highest ranked depending on the criterion and the cropping system (e.g. individual or rotation). SERF analysis results for the tillage systems were also dependent on the cropping system (individual, rotation or whole-farm combined) and economic outcome of interest (gross margin or net return) but only marginally on the level of risk aversion. For the individual cropping systems (continuous corn, rotation corn and rotation soyabean), the no-till tillage and rotation soyabean system was the most preferred and the chisel plough tillage and continuous corn system the least preferred across the entire range of risk aversion for both gross margin and net return. The no-till tillage system was preferred to the chisel plough tillage system when ranking within the continuous corn and the corn-soyabean rotation cropping systems for both gross margin and net return. Finally, when analysing the tillage system alternatives on a whole-farm basis (i.e. combined continuous corn and corn-soybean rotation), the no-till tillage system was clearly preferred to the chisel plough tillage system for both gross margin and net return. This study indicates that the SERF method appears to be a useful and easily understood tool to assist farm managers, experimental researchers and, potentially, policy makers and advisers on problems involving agricultural risk.

Comments

This article is from Experimental Agriculture 47 (2011): 111–136, doi:10.1017/S0014479710000979.

Access

Open

Rights

Works produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted.

File Format

application/pdf

Share

COinS