Quantitative modelling at the industry level: The sheep and beef industries

Abstract

If we wish to assess the usefulness of quantitative supply model then first we must define the problems for which we, as agricultural economists, seek solutions. I suggest there are at least two types of problem where quantitative supply models can potentially be of use. The first is the need to provide the agricultural service industries and marketing organisations with short and medium term forecasts of agricultural output, so that they may plan their activities accordingly. Some industries need these forecasts only 1-3 months in advance, but other industries, in which the lead times are longer, may require forecasts 2-3 years ahead. The second type of problem is the need to provide policy makers with information as to the supply implications of alternative macro-economic policies. For example, if New Zealand devalued its currency 2 0 per cent would the extra farm income be spent on the farms or on overseas trips? And if it was invested on farms would it induce extra output, and if so, how much, or would it induce factor substitution (for example, capital intensive methods replacing labour intensive methods) with aggregate output remaining constant? Regardless of whether it is the policy makers or the service industries whose information demands we are attempting to satisfy, there is clearly a need to analyse and quantify the factors which influence the output of agricultural products. This implies some form of positive analysis, and the most common way of doing this is to analyse historical data within the framework of a time series regression model.