Technology adoption and competitiveness in small milk producing farms in Costa Rica: a case study (part two)
Explanation of behaviour of producers
As it has been shown, several differences exist between the proposed prototype and the alternatives adopted. These differences are related to the integration of biological and micro-economic factors at the farm level as well as macro-economic influences. The factors that have influenced most in the decisions of producers are:
BIOLOGICAL FACTORS: Soil Type and Pasture Species
Table 6 contains the main results of soil analysis performed in 1991. Even when the IDA base document (CATIE, 1981) talks about ecozones with similar characteristics, soil conditions differ substantially.
Initially P contents differed greatly between farms in Río Frío and Sonafluca (Murillo and Navarro, 1986), giving an idea of the original soil material when producers acquired the land. With time, P contents have evolved to similar levels, but their fixation levels in the last analysis show two soils with different development possibilities (Table 6): on one side, manageable (i.e., 67%) in Sonafluca and on the other side, almost impossible to correct (i.e., 92%) in Río Frío. This is due mainly to the content of other nutrients in the soil, especially calcium availability, which is higher in Sonafluca.
On the other side, the low P content has stimulated the invasion of ratana. Arosemena (1990) reported internal P requirements in ratana of 0.15% (as percentage found in tissue) vs. 0.19% in Brachiaria brizantha, a specie known to require less P than B. ruziziensis (CIAT, 1987).
Moreover, ratana competes favourable with other species. Arosemena (1990) reported a 28% reduction on the relative weight of biomass of B. brizantha with respect to ratana when these competed for light, space, and nutrients. Therefore, ratana not only requires less P but also outcompetes B. brizantha, suggesting ratana is more aggressive under these soil conditions than B. ruziziensis.
The problem of ratana invasion was exacerbated by the producers themselves in Río Frío (Murillo and Navarro, 1986), who initially saw an adequate vegetative behaviour in ratana. However, once they realized its limited productivity, it was almost impossible to revert this process. This can be observed in producers which began dairying > 1982 (last), who have been more careful in the management of this pasture (Table 2), but still there is a trend towards greater proportions of ratana.
|Table 6. Soil analysis at 20 cm depth containing levels of pH, calcium (Ca), magnesium (Mg), potassium (K), extracted acid, phosphorus (P), and phosphorus fixation (%) of farms in Río Frío, Sonafluca, and intensive milk production prototype of CATIE. Standard deviations are in parenthesis.|
|P fixation (%)||92.1||67.4||65.0|
* CATIE, 1991b
** meq/100 ml soil
*** mg/lt soil. Phosphorus content in same farms in 1983 was 3.5 in Río Frío and 4.2 in Sonafluca (Murillo and Navarro, 1986)
In Sonafluca, having a more fertile soil, this process has been slower, and given the P fixation levels, becomes an economically manageable problem.
Thus, soil characteristics have influenced at the farm level the adoption and non-adoption of the following technologies proposed by CATIE's:
(a) FERTILIZATION LEVELS: CATIE's prototype uses 250 kg N/ha/yr based on research response to N by C. nlemfuensis on the fertile soils of the Turrialba valley where CATIE is located.
In less fertile soils and with ratana invasion, the probability that producers obtained a response to N fertilization was low. For this reason, N is used strategically only in areas with cut-and-carry forage located next to the milking shed where manure is also dumped.
On the other hand, when producers began dairying between 1979 and 1984, average milk price was highest in the last 20 years [Table 7; (Cámara Nacional de Productores de Leche, 1991)]. This allowed a good price relationship with respect to nitrogen [1 kg N : 2 kg milk; (FERTICA, 1991)]. With the petroleum crisis in 1981-1982, N price increased and this relationship deteriorated (1 kg N : 2.8 kg milk), making milk production based on un-fertilized pastures more attractive since milk price stayed relatively stable during these five years. This short-term effect could have induced producers to use pastures (i.e., ratana) with low N (and labour) requirements since labour costs drastically increased >1982 [Table 8; (MTSS, 1991)]. Lately, this relationship has improved (1 kg N : 1.7 kg milk), and farmers have increased the amount applied per hectare, but its use has been strategically limited to small areas not in ratana.
|Table 7. Producer prices per kilogram of milk in 1990 dollars for the period 1970-1990.|
(b) SUPPLEMENTATION LEVELS: CATIE's prototype was designed to use molasses (i.e., digestible energy) in strategic form to complement protein produced by N fertilization of C. nlemfuensis. With a pasture of the characteristics of ratana, harvest cost is higher due to the lack of dry matter, thus dairy cows require concentrate feeds to achieve production levels obtained with other species such as B. ruziziensis.
With time, this induced producers to use greater quantities of concentrate feeds, re-enforcing their decision by the price relationship between concentrate feeds and molasses, especially in the last five years [1 kg concentrate : 4.5 kg molasses; (CATIE, 1991a)] relative to the period 1979-1984 (1 kg concentrate : 6.5 kg molasses).
|Table 8. Daily labour wages for the livestock sector in 1990 dollars including social benefits for the period 1970-1990.|
|Labour Wage||Labour Wage|
MACRO-ECONOMIC FACTORS: Government Incentives
The period from 1970 to 1980 was favourable for beef development. High international prices stimulated beef exports to the US and increased export earnings. Costa Rica went from exporting $92.4 millions in 1973 ($4.55/kg, in 1990 dollars) to $148.1 millions in 1979 [$4.69/kg; (BCCR, 1989)]. Likewise, high export earnings from beef stimulated high milk prices to maintain domestic consumption without having to import milk, currently at about $0.20/kg. Additionally, the government restricted dairy imports since 1979 (PNUD, 1979), stimulating the sector by protecting the market from dumping.
In the middle of the 70s the government began to stimulate beef and milk production, understanding that generating export earnings from beef and substitution of dairy imports required preferential conditions to stimulate the livestock sector.
This scenario has substantially changed in the beef sector since 1981. Due to consumption patterns, beef prices began to decrease in real terms in the US and its behaviour has been atypical with respect to production and price cycles which has occurred traditionally. Thus, Costa Rica went from exporting beef at $4.69/kg in 1979 to exporting it at $2.51/kg in 1989 (in 1990 dollars). The main consequences of these changes have been the following:
(a) SUBSIDIZED INTEREST RATES: Livestock credit allocated between 1970 and 1983 had negative average real interest rates, and in some years annual rates were greater than -10%. This was specially true for those credits given between 1973-1975 and 1979-1983 [Table 9; (BCCR, 1991b)]. Since then, Costa Rica has adjusted its nominal interest rates based on inflation, generating annual real rates close to 10%.
(b) INCREASE IN AMOUNT OF CREDIT: From 1970 to 1980 the amount of credit allocated to the livestock sector grew at a rate of 10% a year [Table 10; (BCCR, 1991b)]. However, since 1981 it has decreased to levels that in 1989 were similar to those allocated in 1970.
(c) INVESTMENT IN INFRASTRUCTURE: Significant investments were made with public funds. New roads were built and electricity provided. The road network tripled from 2,557 km in 1974 (67% paved) to 7,227 km in 1990 [50% paved; (MOPT, 1991)].
|Table 9. Real annual interest rates for credits allocated to the livestock sector during the period 1970-1990.|
|Table 10. Amount of credit allocated to the livestock sector in 1990 dollars during the period 1970-1990.|
|Year||(million $)||Year||(million $)|
These investments allowed a rapid change from beef to dairy and dual-purpose activities. Between 1973 and 1984, the inventory of females >2 years decreased 2.4% per year in beef herds and increased 9% per year in specialized dairy and 19.2% a year in dual-purpose herds (Censos Agropecuarios 1973, 1984). These investments also allowed producers to capture benefits created with public funds through land appreciation and reduced transport costs.
MICRO-ECONOMIC FACTORS: Effect of Government Incentives at the Farm Level
The effect of the above government incentives had the following impacts at the farm level:
(a) SUBSIDIZED CREDIT: Table 11 shows the amount of credit allocated and subsidies received by producers due to negative real interest rates by year they began dairying. As shown, average net subsidy per producer varied from $149 to $11,133 depending on beginning year. If credit institutions (i.e., public) would have charged a 10% real interest rate on credit, these subsidies would have been in the order of $6,200 to $18,300. These benefits contributed positively to the government policy of maintaining milk prices while labour wages (Table 8) continued to increase.
The increase in farm size (Table 1) is explained by the benefits received as well as by the early biological and economic performance of the replications. Table 12 contains the regression coefficients that explain this increase in Río Frío, which expanded the most. The effect with greatest importance is related to years in business expressed in quadratic form and in areas allocated to activities other than dairy or agriculture (i.e., forest and/or idle land). Producers who began dairying earliest with the entire farm area allocated to dairying had higher credits for acquisition of animals and benefited most from subsidized interest rates and high milk prices.
Those producers with most productive cows and,therefore, higher use of concentrate feeds, accumulated less capital and limited their increase in area.
In Río Frío increases in area happened before and during the opening of the highway and electrification in 1986. Additionally, this favoured those who began dairy activities first (1979-1981) since based on the subsidies received, they acquired land before it appreciated.
(b) CAPTURE OF BENEFITS: Table 13 shows the benefits captured by producers. As shown, Río Frío has captured greater benefits through land appreciation given the initial level of infrastructure. Likewise, Table 13 contains the net present value of savings by producers from milk transport costs due to the highway construction and installation of cooling tanks from availability of electricity.
|Table 11. Amount of credit given to each producer and subsidies received in Río Frío and Sonafluca due to negative real interest rates (as occurred) and the amounts that credit institutions could have recuperated if real annual interest rate would have been 10%.|
|As could have occured|
|YEAR||TO PAY||SUBSIDY||TO PAY|
* Unadjusted dollars
In Río Frío the increase in land value is 84%, reflecting investments of public funds not re-captured by the government through tax appreciation. In the case of Sonafluca, the benefits due to public fund investments have been lower (i.e., 29%) because the ecozone already had electricity and paved roads by the time producers began dairy activities, and also because dairies were located closer to a milking plant.
Considering the credit subsidy and the benefit captured by land appreciation, each producer has directly received between $31,051 for those who initiated last in Río Frío and $41,887 for those who initiated first in Sonafluca (Table 13).
In these two ecozones society has invested scarce public resources in land and infrastructure waiting for a return through higher production and lower consumer prices. Even when the invested amounts are adequate to stimulate production, the response of the system has been poor and decreasing with time. The main limiting factors to solve are:
Re-structuring of the sector
Traditionally, these systems have based their milk production on using family labour, which in 1990 accounted for 62% to 76% of production costs considered in this study. Additionally, wage rates have been increasing in real terms in the last 20 years, averaging 4% per year (Table 8). Including social benefits that producers have to pay, the average minimum wage for the livestock sector in 1990 was $7.79/day [$5.41/day plus 44% of social benefits, (MTSS, 1991)].
|Table 12. Estimated value, standard error, and significance level of analysis of variance explaining the expanding factors in farm area of producers in Río Frío.|
|in dairying (X1)||0.0762||0.0359||0.0488|
|Idle land (X2)||-1.3718||0.5453||0.0222|
|per cow (X4)||-0.0349||0.0268||0.2105|
* The mathematical model was Y = B1(X15)+B2(X2)+B3(X3)+B4(X4) with regression constant of 6.0239 with R5= 0.57 and mean square error=123 with four degrees of freedom for regression and 17 degrees for the residual
Thus, if labour wages continue to increase, these production systems with small areas (i.e, 10 ha) may not be competitive if they are to (1) have incomes similar to the minimum wage; (2) reduce production costs equal to those for international protection against imports, currently at about $0.20/kg milk; and (3) compete in an economy without subsidies. This re-structuring of the sector requires an analysis of the following factors:
(a) ACTUAL PRODUCERS: These producers are on average 47 years old. Because of the dynamics of their systems in the last decade, they have:
|Table 13. Estimated land commercial value in 1990 dollars, year of paved road and electricity construction and installation, and net present value of captured benefits by producers in Río Frío and Sonafluca through milk transport costs.|
|Land Commercial Value ($/ha)|
|Year of construction|
|Benefit from Milk Transport|
|via paved road*||1340||0|
|Total Value of Subsidy***|
* Calculated based on the following formula:
(KMLi * CT * Cm * PLj) - (KMCh * CT * PLj) / IR / ha WHERE:
KMLi= Distance in kilometres of dirt road between farm
andprocessing plant round trip (ie 200 km para Río Frío),
CT = Factor for transport cost/kg milk per kilometre (ie., 0.000168),
Cm = Overcharging factor for road under bad condition (i.e., 20%),
PLj = Annual milk production per farm,
KMCh = Distance in kilometres on paved road between farm andprocessing plant round trip (i.e., 120 km for RíoFrío and 70 km for Sonafluca),
IR = real interest rate (5%), and
ha = Total farm size in hectares.
** Calculated similar to above formula but dividing final
by a factor of 3 since milk truck now collects milk every three
days and not daily as before when milk tanks were not available
*** Calculated from the summation of credit subsidy [(Table 11),
averaging $6887/farm for those who initiated first and $1051/farm for those who initiated last] and land appreciation ($30,000/farm for Río Frío and $35,000/farm for Sonafluca).
Received greater benefit through subsidies (land appreciation and interest rates) than their efficiency of milk production. That is, social investment in these dairies is not in proportion to their production efficiency. As shown in Table 14, the actual systems would not be viable if society would ask them to return the subsidies given to them in a 10-yr period with a real annual interest rate of 10%. Under these circumstances, their net income, excluding family labour, would fluctuate between 33% and 60% of the 1990 minimum wage with actual labour efficiency.
These systems have only survived with their operational sizes at constant milk prices because they have received subsidies. This could be a limiting factor in an open economy, because of the reaction by similar producers to a more dynamic policy without subsidies and with mechanisms to re-capture public fund investments.
|Table 14. Net income per farm, (excluding family labour), subsidy payment if society would ask each producer to return it back, and annual net income per farm (excluding family labour) after paying subsidy compared to family labour cost valued as minimum wage for producers in Río Frío and Sonafluca who began dairying between 1979-81 (first) versus those who began after 1981 (last).|
|a. Annual Net Income*||7078||9027|
|b. Subsidy Payment**||5533||4658|
|c. Net Income after|
|Subsidy Payment* (a-b)||1545||4369|
|d. Family Labour Cost|
|Valued as Minimum Wage||4620||7227|
|a. Annual Net Income*||9952||9182|
|b. Subsidy Payment**||6283||5408|
|c. Net Income after|
|Subsidy Payment* (a-b)||3717||3774|
|d. Family Labour Cost|
|Valued as Minimum Wage||8327||8749|
* Excluding family labour
** Calculated from total value of subsidy received (Table 13)
payable in a 10-year period at a real annual interest rate
Low efficiency in the use of family labour. Table 15 shows the percentage of under-utilized family labour based on producers' criteria. Thus, family labour efficiency can be easily increased by 24% to 37% without the incorporation of additional labour and by 67% to 99% with incorporation of small equipment.
In a economic system where reducing production costs is necessary to compete, this could be a limiting factor given that family labour is a fixed cost (i.e., without possibility of sporadic use) and additionally, the most important resource of production costs (i.e., 62% to 76%) and the only one that has been systematically increasing in the last 20 years and that will continue to increase in a development process.
(b) OPERATION SIZE: With an open market economy, possibilities could exist where milk price is reduced to levels of international protection from imports (i.e., $0.20/kg). This would imply a 30% reduction in the actual milk price (Table 7).
|Table15. Percentage of labour under-utilized with hand and machine milking based on producers' criteria* in Río Frío and Sonafluca who began dairying between 1979-81 (first) versus those who began after 1981 (last).|
* Based on additional milking cows that family could manage with current available labour allocated to dairying
An analysis was done with an electronic spreadsheet to determine the number of years these producers could subsist receiving minimum wage for their family labour. Even when the parameters used were conservative with respect to what could happen (i.e., 5% opportunity cost on capital in animals and equipment; 4% annual increase in real terms in labour wages; and a 10% annual reduction in real terms in milk price until it is stabilized at $0.20/kg), the subsistence time of actual production systems would be less than 4 years, showing the need to increase family labour efficiency.
Labour efficiency can be improved by increasing land productivity or operation size. The first alternative has not demonstrated attractive results since the incorporation of new pastures to replace ratana would only increase the viability of the system by one to three additional years. In this analysis the area in ratana was substituted by B. ruziziensis as existed in the beginning, assuming this would last four years before degrading again into ratana. Also, based on producers' opinions, it was assumed that one hectare of brachiaria without fertilization increased stocking rate by 33% and produced 1.5 kg/cow/day of additional milk in relation to ratana.
With this operation size (10 ha), the cost of labour ($7.79/day) and its efficiency, and the cost of establishing new pastures ($350/ha), it is impossible to produce milk at $0.20/kg.
This suggest that the only alternative for reducing production costs under the actual scenario is to increase farm size above 20 ha. Reducing family labour is not viable because, in the majority of cases, family labour represents labour out of the formal job market (senior citizens or young people of school age) whose efficiency in many activities do not differ from an adult.
(c) CONTRIBUTION TO DEVELOPMENT: The objective of IDA has been to provide employment in rural areas by allocating land to settlers, thus avoiding migration to main urban centres. In this case study, producers were receiving a government subsidy of about $796/family/yr at the time the project was initiated.
These public fund investments in land and subsidized credit have drastically increased their standard of living. Thus, these subsidies represent the cost that society has paid to generate employment opportunities through milk production with small producers in the rural sector relative to investing these resources in other alternative uses.
The dilemma now is that the actual production systems are not economically viable with actual labour efficiency and cost. Thus, alternatives need to be developed to facilitate the transition to other uses of land under these soil conditions.
High milk prices, subsidized credit, and public fund investments in infrastructure have increased the market value of land. These factors have, in part, contributed to the deforestation process, a rate that in Costa Rica during the 80s was about 500 km5 per yr. Thus, in the last 10 years, about 10% of the total area of the country was de-forested (CCAD, 1991).
The solution to this problem appears to be decreasing the price of milk, reducing public fund investments in infrastructure in fragile soils, and developing alternative uses for farms located in these soil characteristics. Our research could contribute to this process to facilitate the transition of these farms to new alternatives and document impacts on natural resources of new options. Also, to look for mechanisms to induce expansion of dairy farms into ecozones with a comparative advantage in open markets.
Dairy development with small producers in these ecozones could not have been possible without investment of subsidized public funds. With realistic real interest rates, and with the family labour utilized, these producers would be receiving the equivalent of 33% to 60% of the minimum wage in 1990. Thus, this development model has been exhausted due to increasing labour rates, market restrictions (i.e., milk surplus) at current prices, and conflict with natural resource conservation.
The current capitalization amounts of producers are superior to those initially thought, even when their productivity was inferior to the initial proposal (CATIE, 1981). About 84% and 29% of the capitalization in Río Frío and Sonafluca, respectively, was due to public fund investments which were captured by producers.
Dairy farmers behaved rationally to biological and economic conditions. Differences with respect to the proposed model were caused by the rigid character of recommendations in relation to a dynamic economy (i.e., relative changes in input and output prices, interest rates, credit availability) and changing scenarios of biological conditions (i.e., soil degradation, nutrient loss).
Without subsidies, with the operation sizes found, and the existing labour efficiency, protection from dairy imports seems unfeasible if labour retribution similar to the minimum wage is to be maintained when this increases 4% per year in real terms.
As has been traditionally argued, credit was not a limiting factor in technology adoption. Producers who accumulated capital used it to expand farm size instead of increasing productivity. For the actual capitalization levels, this was a logic decision.
The subsidy per hectare fluctuates between $3100 and $4200 (Table 13). With these investment levels, the government should be more careful in selecting land for agrarian reform plans. The system should generate $310/ha to $420/ha (i.e., 3-4 MT of corn at international prices) just to pay interest on capital investment. This could only be feasible in fertile soils and with lower labour rates, which is not the case in Costa Rica.
The emphasis in farming systems research was to propose small changes in the system assuming stable macro-economic conditions. The experience from this study indicates these conditions were stable before the project began. Throughout its duration, great adjustments have been presented, permitting the same production system to capture from $149 to $11,133 (Table 11) based only on changing interest rates within a three-year period. Thus, this experience suggests a permanent feedback at all hierarchical levels to evaluate the evolution of production systems. With an open market economy, research systems will need more effective multi-disciplinary teams to continuously analyze the influence of macro-economic aspects.
The authors are grateful to the Regional Office for Latin America and the Caribbean of the International Development Research Centre (IDRC) for financing this study. We also thank IDA for its cooperation in facilitating technical personnel to conduct the survey.
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