8.4 Explanation of Farm-Specific Profit Inefficiency in Terms of Differential Transaction and Environmental Mitigation Costs

The previous chapters and sections of this chapter now yield the data and methodology necessary to formally test hypotheses 4 and 5 from Chapter 1. For convenience, these are repeated here.

• Hypothesis 4: The relative profit efficiency of large-scale farms is more sensitive to environmental externalities than is the case for small farms.

• Hypothesis 5: Profits of small-scale producers are more sensitive to 'transaction costs' than are those of large-scale producers.

Understanding the determinants of relative profit efficiency clarifies which areas require policy intervention and improved technology and institutions in order to support the competitiveness of smallholder livestock farming. The measures of relative profit efficiency reported in the previous section are computed from the residuals of the stochastic profit frontier for the commodity and country concerned. An example of such a frontier is given for broiler farms in the Philippines in Table 8.5a. Any coefficient reported in this study is statistically different from zero at least a 90 percent confidence level or better.^[32] To paraphrase the discussion in Chapter 4, the coefficients in Table 8.5a are MLE estimates of the influence of prices and farm fixed resources on maximum profit that a farm in the category concerned can make. For independent and price contract farms, for example (column two), a one percent rise in the price of broilers, others things equal, is associated with almost a 5 percent rise in the per unit profit; a one percent rise in the feed price is associated with a fall in unit profit of less than 5 percent (note that feed price shows up in more than one place in the frontier).

With minor exceptions here and elsewhere, the coefficients of the frontiers are of expected sign and magnitude. These coefficients are of only indirect interest to the present study, because our main reason for estimating the frontier is not the analysis of production relationships per se, but the estimation of what the ideal level of unit profit would be for each farm. Plausible coefficients suggest that the estimated frontier is usable for our purposes. The previous section used the results from the stochastic profit frontier analysis to compare relative profit efficiency across classes of farms. The present section will examine results from the second stage of the model in Chapter 4. This regresses the residuals from the first stage (measures of the amount that a given farm falls below the frontier ideal, or (Y* - Yi) in Figure 4.1, against a series of proxy variables for farm-specific transaction costs/policy distortions and our measure of farm-specific environmental mitigation (instrumented where appropriate).

Results for broilers in the Philippines are given in Table 8.5b. When the analysis is limited to independent and price contract farmers only (second column), the only variable to significantly explain differences in profit efficiency within the sub-sample is access to credit for feed. A negative coefficient means that the variable reduces inefficiency. In this case, access to feed credit explains why some farms are closer to the frontier. All the other variables could be important elements of farm efficiency, but there is too much or too little variation in their role across the sub-sample that it is not possible to estimate a coefficient with the require degree of statistical confidence.

Clear results for hypothesis testing come from the last two columns of table 8.5b. For large farmers, most of whom are independent, greater age, higher education, having had training, and access to feeds credit are all associated with greater relative profit efficiency (decreased inefficiency). For smallholders as a whole, greater education of the household head is associated with decreased profit efficiency. Rather than an indictment of the educational system, this is probably due to the fact that more educated sample small-scale operators are probably primarily engaged in other income ventures, with livestock being a sideline. The two major explainers of greater smallholder efficiency in the Philippines sample are having access to phone service and access to feed credit.

Interestingly, the impact of including the measure of environmental mitigation ("environmental capture" in Table 8.5b) in the explanation of relative profit inefficiency is precisely opposite for smallholders and large-scale farmers. Having a higher degree of environmental mitigation effort per unit of output is associated with being less profit efficient for smallholders, and more efficient for large farmers. The effect is not significant in the pooled regression involving both sub-samples. The interpretation of these results is that within the class of smallholders, those who pursue more environmentally sustainable practices in manure and dead animal disposal pay a price in terms of competitiveness, but the reverse is true for large farmers. Some smallholders can get away with throwing manure over the back wall in the river instead of spreading it, and make more money per unit as a consequence. This is less of an option for large farms, and in addition, most likely those who follow better practices have lower mortality rates and other efficiency gains relative to large farmers who are less careful.

Table 8.6, on Thai broilers, gives both the frontier results and the results explaining relative profit inefficiency in the same table. Results in the bottom half of the table suggest that the most efficient broiler farms are run by younger, female decision- makers, and are located in areas with a higher density of chickens, closer to population clusters. Differences in environmental mitigation behavior do not affect differences in relative profit efficiency within the sample. In the Indian broiler sample (Table 8.7), the availability of family labor, wage rates, and the price of broilers are the keys to smallholder profitability; larger farms need to worry primarily about labor and feed costs. The only clear driver of relative efficiency for smallholders is that greater effort for environmental mitigation lowers relative profitability, whereas it has no effect on the relative profitability of large farms. Experience contributes to greater efficiency on large farms, but not on small.

On Brazilian layer farms (Table 8.8), regional differences are paramount. The least profit efficient farms have operators with higher educational levels (probably a similar non-farm occupation explanation as in the Philippines), work in areas of higher concentrations of animals, closer to big cities, and make a relatively greater effort to mitigate environmental externalities. The least profit efficient Indian layer farms (Table 8.9) work in the South, are younger, and make the greatest relative effort at mitigation of environmental externalities. The picture is clearer, however, if the large-scale layer sample is considered in isolation. Among them, the most profit efficient are those who do the most per unit for environmental mitigation (similar to large-scale broiler producers in the Philippines), and are the best educated. In this case, the higher education is more likely to be used to support the layer enterprise as opposed to commuting to a non-farm job.

Table 8.5a Profit efficiency estimated and explained on Philippines broiler farms-stochastic profit frontier

Note: "ns" means statistically insignificant at 10 percent.
Source: Costales, A., et. al., Annex I.

Table 8.5b Profit efficiency estimated and explained on Philippines broiler farms- explainers of inefficiency

Note: "ns" means statistically insignificant at 10 percent.
Source: Costales, A., et. al., Annex I.

Table 8.6 Profit efficiency estimated and explained on Thai broiler farms

Note: "n.s." means statistically insignificant at 10 percent.
Source: Poapongsakorn, N., et. al., Annex IV.

Table 8.7 Profit efficiency estimated and explained on Indian broiler farms*

*Contract farmers not included
Note: "n.s." means statistically insignificant at 10 percent.
Source: Mehta, R., et. al., Annex II.

Table 8.8 Profit efficiency estimated and explained on Brazilian layer farms

Note: "n.s." means statistically insignificant at 10 percent.
Source: Camargo Barros, G.S., et. al., Annex V.

Table 8.9 Profit efficiency estimated and explained on Indian layer farms

Note: "n.s." means statistically insignificant at 10 percent.
Source: Mehta, R., et. al., Annex II.

Swine production in the Philippines is analyzed in Tables 8.10a and 8.10b. Several patterns emerge from the analysis of the determinants of relative profit inefficiency in Table 8.10b. First, the transaction cost variables proxied by the independent variables show-which are correlated with household access to information and assets-matter more to smallholders than to large-scale swine farmers. Second, access to investment credit is a distinguishing feature of relative efficiency in all cases, but feeds credit access seems to contribute to relative inefficiency, a surprising and not very plausible result that needs further investigation. Third, having access to information is an important driver of relative efficiency for all farm classes except fee contractors, who presumably are not making the key production decisions in any event. Fourth, farmers who sell to itinerant traders (viajeros) are typically less efficient that farmers who have other marketing arrangements. Fifth, fee contractors are more efficient than independent and price contract farmers, other things equal, confirming the results from the previous section. Sixth, in all cases, greater efforts to promote environmental mitigation are associated with increased profit efficiency.

In the Brazilian sample (Table 8.11), the most efficient swine farms were headed by more educated decision-makers that had longer experience in swine, and were located far from big cities, in regions with high animal concentrations and high animal density on the farm. Engaging in environmental mitigation contributed strongly to reducing relative profit efficiency.

The results for dairy farms are shown in Tables 8.12 and 8.13. Disaggregated results for small and larger farms in India show considerable homogeneity in the driving forces of relative profit efficiency for small and medium dairy farms. This is not surprising, since having more than 10 milk cows counts as a large dairy farm in the Indian sample. A striking result is that the hypothesized explainers of relative profit efficiency have quite strong effects for small and medium scale farms, but no effect on relative profit efficiency within the large and commercial farm sample.

Table 8.10a Profit efficiency estimated and explained on Philippines swine farms-stochastic profit frontier

Note: "n.s." means statistically insignificant at 10 percent.

Source: Costales, A., et. al., Annex I.

Table 8.10b Profit efficiency estimated and explained on Philippines swine farms-explainers of inefficiency

Note: "n.s." means statistically insignificant at 10 percent.
Source: Costales, A., et. al., Annex I.

Table 8.11 Profit efficiency estimated and explained on Brazilian swine farms

Notes: "n.s." means statistically insignificant at 10 percent.
Source: Camargo Barros, G.S., et. al., Annex V.

This not to say that access to information and assets is not important for large farms; it only means that farm-specific differences in this area did not distinguish farms from each other with respect to profit efficiency. On the smallest farms, access to information and credit were the key drivers of relative efficiency. On farms with 4 to 10 milk cows, the key drivers were differences in education and information. Thai dairy farms (Table 8.13) exhibit the same pattern as the larger scale Indian dairy farms. The relative profit efficiency of Brazilian dairy farms (Table 8.14) is driven primarily by location, the degree of family involvement in the enterprise (good for efficiency), establishment of that farm in dairy, and access to information.

In sum, we can say the following with regard to hypothesis 4. Monetizing a measure of environmental mitigation, or internalization of negative externalities, helps explain why some farms are more or less profit efficient in the majority of cases. However the issues are different within the separate categories of large and small farms. Furthermore, differences in environmental mitigation do not seem to be strong explainers of differences in profit efficiency across sizes of operation. The brunt of evidence is that within large-scale operations for swine and poultry, greater effort for mitigation of environmental externalities seems to be associated with greater relative profit efficiency. This is clearest in the case of broilers and swine in the Philippines and layers in India. Interestingly, these tend to be mostly independent operations that are transitioning towards more industrial production, at least as compared with other samples studied. Results for smallholders are more mixed, particularly where contract and independent sub-samples are mixed, as in the Philippines. Most fee (or wage) contractors have to follow a standard set of environmental practices as part of their contract, and they resemble larger scale farms in this respect more than other smallholders.

Table 8.12 Profit efficiency estimated and explained on Indian dairy farms

Note: "n.s." means statistically insignificant at 10 percent.
Source: Sharma, V.P., et. al., Annex III.

Table 8.13 Profit efficiency estimated and explained on Thai dairy farms

Note: "n.s." means statistically insignificant at 10 percent.
Source: Poapongsakorn, N., et. al., Annex IV.

Table 8.14: Profit efficiency estimated and explained on Brazilian dairy farms

Notes: "n.s." means statistically insignificant at 10 percent.
Source: Camargo Barros, G.S., et. al., Annex V.

The environmental mitigation variable did not seem to have much influence on relative profit efficiency in the Thai sample. Egg and swine producers in Brazil, smallholder swine producers in the Philippines, and large-scale broiler farmers in India that spent relatively more on environmental mitigation tended to have lower relative profit efficiency at the end of the day, other things equal. It is interesting to speculate whether these sub-samples operated in conditions where it was relatively easier to ignore environmental issues, or perhaps harder to follow environmentally sound practices because of land scarcity.

With regard to hypothesis 5, farm-specific transactions costs seem to matter greatly to explaining relative profit efficiency across farms in most of the sub-samples studied. This means that relatively greater difficulties in securing access to assets and information for smallholders is a prime explainer of differences in relative profit efficiency within their group, and between them and large-scale farmers.

The most notable exceptions-where farm-specific differences in transactions cost proxy variables did little to explain differences across farms in relative profit efficiency-occurred for dairy farms. It is likely that transaction costs for dairy almost all occur in the marketing chain and not at the level of production, at least in the Indian and Thai contexts. Feed is mostly forage (avoiding the high credit and quality-related transactions costs packed into using concentrate feeds) and the timing of sales is a foregone conclusion, viz. daily. This is quite unlike farmers of monogastrics, where the timing of sale is more discretionary (requiring information), much less frequent, but critical to profit margins. For those cases where transaction cost variables matter most to smallholder producers, the main issues appear to be access to telephone service and the market information that goes along with this, and access to credit for feed purchase.