Relative competitiveness might be thought of as having the ability to produce at a lower unit cost of production than one's competitors. In fact, if large farms can produce livestock at a lower unit cost than small ones, they will clearly drive small farms out of the market over time. The market price that applies to both large and small, by this reasoning, will fall as large-scale producers expand production, and the smallholders will get squeezed out. The only future for smallholders then will be to stay in a few higher-priced niche markets not served by larger farms, if these markets exist, and to cut costs by remunerating their own (family) labor less than what a large farmer pays to hired labor. Even so, it is unlikely that smaller producers will be able to stay in business long under this situation.
However, the reverse is not necessarily true. If small farms can produce at lower unit costs than large farms, they may still be squeezed out. This is because large-scale farms can remain profitable with very thin profit margins; they make up in volume what they lose in per unit profit. Very low per unit profits coupled with a small sales volume may not provide enough income for a smallholder to stay in business. Thus, if large farms have lower per unit costs of production when all labor is costed at market wages, the next question is whether this finding still holds if smallholders do not cost their family labor. If it does, then it is not necessary to proceed further; there is little hope for smallholders in this activity.
If, on the other hand, small farms can produce at lower per unit cost in the same markets as large farms, perhaps by not costing their own labor at full market wage rates or for some other reason, there is at least hope for them. Thus, having higher unit profit, with or without the cost of family labor, is a necessary condition for competitiveness of smallholders, but is not a sufficient one.
To get a more satisfactory measure of relative competitiveness that gets around the issue of larger farms being able to expand production while small ones cannot, it is necessary to appeal to the notion of efficiency. Small farmers are most likely to be able to stay in business-and perhaps to gain market share-if they are more efficient users of farm resources, both in a technical sense (being on the production possibility frontier given existing technology) and the allocative sense (being on the right place on the production frontier, given prevailing prices). If small farms are more efficient users of farm resources, perhaps because they put more care per unit of input into what they do, then they have a market advantage over large-scale producers that will be difficult to dislodge. This then yields a measurable index of relative competitiveness: relative farm efficiency in securing profit per unit of output. Ceteris paribus, farmers that are more efficient users of farm resources to secure profits per unit of output are more likely to be able to maintain market share than larger producers who are less efficient in the same sense. Over time, the more efficient are in a position to invest more into the farm enterprise and to grow, whatever their starting size.
A standard way of assessing farm-specific relative profit efficiency is to estimate a "profit frontier" across a sample of farms, and then to measure how far each farm in the sample lies below the frontier. Conceptually, such a frontier can be thought of a function Figureping profit per unit to relative input and output prices and quantities of non-traded factors of production, where each point is the maximum profit per unit that a farm can achieve given those relative prices and access to resources. Given a set of prices, the average farm with that level of resources will fall below the frontier. Thus an ordinary least squares regression on data from a sample of farms of different sizes of profits per unit of output against input and output prices and fixed factors of production (land, labor, etc.) will always lie below the theoretical frontier. The frontier itself has to be estimated in some fashion looking at data for farms that perform best at each level of resources. A variety of approaches to this are described by Fried, Lovell and Schmidt (1993).
The measurement of "most efficient" can be improved by estimating a stochastic profit frontier, which allows for measurement error in the econometric estimation of the frontier itself, and thus for the fact that observations for some farms will lie above the estimated "best" frontier (see Battese 1992 for a survey of this literature). In our case, the dependent variable is profit per unit of output, and the explanatory variables are farm-specific fixed resources (land, family labor, sunk capital), farm-specific input prices (feed, medicines, stock, etc.), and farm-specific output prices. In the developing country situations studied, farm resources such as land may be non-tradable inputs and must be accounted for in the frontier in terms of the amount available, and not their price. The unit prices received for output and prices paid for inputs can also be expected to vary greatly, and reflect (and control for) quality differences and differential transactions costs such as bargaining power and riskiness.
The actual performance of each farm in terms of unit profit can then be compared to an ideal unit profit for that farm, given its resources and prevailing input prices. The difference between the ideal and the actual profit per unit for that farm is the farm's relative profit inefficiency. Following Ali and Flynn (1989), Figure 4.1 traces a profit frontier for a sample of farms; each dot corresponds to the actual outcome in terms of profit per unit for a specific farm; points on the stochastic frontier curve (estimated by maximum likelihood methods and labeled MLE) are fully efficient farms (on the frontier) and all points below are inefficient farms in terms of their specific resources at prevailing input prices.
Figure 4.1 Frontier (MLE) stochastic profit function for a sample of farms
Farm-specific profit efficiency (deviations below the frontier) are measured as the ratio of actual profit per unit (Yi in Figure 4.1 for a farm i) and ideal profit (Y*). Note that the curve denoting average profit for any given level of resources (shown as the locus of points Y in Figure 4.1)-estimated by Ordinary Least Squares Regression (OLS)-is less than ideal profit. The measure of farm efficiency embodied in Yi/Y* is bounded by 1 (best; on the frontier) and 0 (worst; no profit). Farm-specific inefficiency is the distance below the frontier, (Y* - Yi).
If small farms have on average significantly higher profit efficiency per unit of output when family labor is not costed, then there is hope. This is even more true if it holds when family labor is costed at market wage rate. However, this methodology allows going beyond simply making this determination; it also permits the investigation of which elements contribute most to explaining relative unit profit efficiency for large and small farms. Individual farms, large or small, may lie well below the profit frontier for reasons other than technical or allocative inefficiency: farm-specific transactions cost barriers or policy distortions may also influence their position relative to the frontier.