Analysis of environmental and economic efficiency using a farm population micro-simulation model

doi:10.1016/j.matcom.2010.04.018

Mathematics and Computers in Simulation

Volume 81, Issue 7, March 2011, Pages 1344-1352

https://doi.org/10.1016/j.matcom.2010.04.018 Get rights and content

Abstract

New Zealand's success in raising agricultural productivity has been accompanied by higher input use, leading to adverse effects on the environment. Until recently, analysis of farm performance has tended to ignore such negative externalities. The current emphasis on environmental issues has led dairy farmers to target improvements in both environmental performance and productivity. Therefore, measuring the environmental performance of farms and integrating this information into farm productivity calculations should assist in making informed policy decisions which promote sustainable development. However, this is a challenging process since conventional environmental efficiency measures are usually based on simple input and output flows but nitrogen discharge is a complex process affected by climate, pasture composition, cow physiology and geophysical variability. Furthermore, the outdoor pastoral nature of New Zealand farming means that it is difficult to control input and output flows, particularly of nitrogen. We present a novel approach to measure the environmental and economic efficiency of farms, using the Overseer nutrient budget model and spatially micro-simulated virtual population data. The empirical analysis is based on dairy farms in the Karapiro catchment, where nitrogen discharge from dairy farming is a major source of nonpoint pollution.

Section snippets

Modeling environmental performance

New Zealand's success in raising agricultural productivity has been accompanied by higher input use, leading to adverse effects on the environment. Until recently, analysis of dairy farm performance in New Zealand has often ignored undesirable effects on the environment [13], [14], [17]. The eco efficiency study by Basset Mens et al. [3] provides a notable exception by indentifying farms which were both economically and environmentally efficient. This was achieved by including nitrogen

DEA model specifications

We define technical efficiency as the ability of a farm to reduce inputs including nitrogen discharges for a given level of output. Our model set up (Eq. (1)) is input oriented and reflects constant returns to scale. Input oriented approaches are useful in situations where the environmental focus is on reducing pollution while maintaining production [26].

For each farm j = 1, …, J. there are data on i = 1, …, i, farm inputs (x), where z is the vector of nitrogen discharges and q is the output.

Empirical analysis

Environmental efficiency is affected by factors such as management, input use, topography, and soil type. These variables were regressed against the DEA efficiency estimates using the maximum likelihood approach (Tobit). This two stage approach was preferred because of its ability to accommodate multiple, continuous and categorical variables and because it does not require prior assumptions about the direction of influence of environmental variables [7]. The explanatory model for the regression

Results and discussion

We use DEA to assess the efficiency of a simulated population of dairy farms based on four different measures. These measures include both separate measures, e.g. technical and economic efficiency and also joint environmental and economic efficiency (joint efficiency). We provide definitions for each of these measures below:

Efficiency measure	Definition
Technical	Ability to reduce inputs including nitrogen discharges for a given level of output
Economic	Ability to minimize farm expenses for a given

Implications

Data on environmental and economic efficiency should allow farmers to benchmark their performance and assist policy makers to make informed decisions which promote sustainable development. Agri-environmental policies need to take account of differences in the inherent efficiency of farms and the different factors that explain efficiency levels. Some improvements in environmental efficiency can be achieved by improving environmental efficiency of input use; particularly towards lower stocking

Acknowledgements

An earlier version of this paper was first presented in 2009 at the MODSIM09 conference. This improved and fully revised version of the paper has benefitted from the comments of conference participants and the Guest Editors of this Journal.

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