Capítulo 2 Marco de referencia
2.1 Marco teórico
2.1.7 Contexto Nacional y Regional de la Innovación
Mugambi, D., K.1, 2*, Wambugu, S.K.2, Gitunu, A.M.M3, Maina, M4
1Ministry of Livestock Development, P. O. Box 672 Embu, Kenya; 2Department of Agribusiness Mangament and Trade and 4Department of Agricultural Science and Technology, Kenyatta University, P. O. Box 43844, Nairobi, Kenya. 3Kenya Agricultural Research Institute, Embu.
*5Corresponding author e-mail: [email protected] ABSTRACT
Dairy cattle farming is a major economic activity in Kenya contributing 3.5% of the national gross domestic product (GDP), and income, employment and food to many small-scale farmers. The country’s dairy herd size is the biggest in sub-Saharan Africa. Kenya enjoys preferential market access for its products in the eastern and southern African region. However, the country’s milk consumption level is low, at 76Kg per capita against the World Health Organization’s recommendation of 210Kg. Kenya’s milk is not sold in economic quantities beyond its borders; partly due to comparatively low per cow average daily production of 6 kg and unsustainably high cost of production. Questions on the milk production efficiency especially technical and cost efficiencies arise. These issues are being investigated in an ongoing study whose obejective is to assess and document the technical and cost efficiencies of dairy farmers, and relate these parameters to the farm gate price of milk and how this affects demand.
Key words: Technical efficiency, cost efficiency, cost leadership, per capita consumption
INTRODUCTION
Dairy production is a major farm activity in Kenya, where it accounts for about 14% of agricultural gross domestic product (GDP), 3.5% of the National GDP, and contributes to the livelihoods of many dairy farmers through income, employment and food (Omiti et al, 2006) and the attaintment of Kenya Vision 2030. The country’s dairy cow population is approximated to be about 6.7 million, the biggest in sub-Saharan Africa, (SDP, 2006). Kenya’s membership to the regional trade blocks provide its products such as milk preferential market access within them, notably, the East African Community (EAC) and the Common Market for Eastern and Southern Africa (COMESA) (GoK, 2007).
Available data indicates that Kenya has not fully taken advantage of its privileged position. The country’s per capita milk consumption averages 76Kg (SDP, 2006), which is way below the World Health Organization’s (WHO) recommendation of 210Kg (FAO, 2007). This undesirable situation is related to the country’s low production per cow, at only six (6) Kg [an average of1,800 Kg per lactation cycle],over the last thirty years, (Gichungu, 2009), compared to global average of 6000Kg under best practice conditions (Karanja, 2003).
Previous studies have focused on understanding genetics (Kahi, 2004), production systems (Bebe, 2003), and nutrition (Ongadi, 2006). Several studies (Staal, et al, 1997; 1998; 2008; Thorpe et al, 2000; SDP, 2006, 2005; Ngigi, 2002; Moll et al, 2001; Muriuki and Thorpe, 2003; Karanja, 2003) have dwelt
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In: Contributions of agricultural sciences towards achieving the Millenium Development Goals. FaCT Publishing, Nairobi. 175 pp. Mwangi, M. (Ed.) ISBN: 978 9966 7415 2 6. Published online at http://www.m.elewa.org
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on the dairy cow milk and milk marketing. Studies on farm-level milk production include SDP, (2006, 2007), Baltenweck (2006), Staal, (1997); Kimenju and Tscherley, (2008), Gamba, (2006); Romney et al, (2005), among others. A few studies on farmers’ adoption of production technologies include Makokha et al, (2007), and Hooton, (Undated).
PRODUCTION EFFICIENCY
Production efficiency is concerned with the relative performance of the process used in transforming inputs into output. The analysis of efficiency is generally associated with the possibility of farms producing a certain optimal level of output from a given bundle of resources or certain level of output at least cost. The economic literature on production efficiency typically distinguishes two types of efficiency: technical efficiency and allocative efficiency. Farrell (1957) proposed that the economic efficiency of a firm consists of two components: technical (or physical) efficiency and allocative (or price) efficiency.
Technical efficiency in production is defined as the ability of the farmer to produce at the maximum output (frontier production), given quantities of inputs and production technology (Aigner et al.,
1977). The greater the ratio of production output to the factor input, the greater the magnitude of technical efficiency and vice versa. Variation in technical efficiency of producers might arise from managerial decisions and specific-farm characteristics that affect the ability of the producer to adequately use the existing technology.
Allocative efficiency represents the ability of a firm to utilize the cost-minimizing input ratios or revenue-maximizing output ratios. Allocative inefficiency occurs if the ratio of marginal physical products of two inputs does not equal the ratio of their prices. Therefore, a firm is allocatively efficient if it uses the optimal combination of inputs with respect to their prices. Similarly, first-order conditions from revenue maximization can be used to determine optimal output ratios based on output prices and marginal costs. The economic efficiency of the firm is the product of technical and allocative efficiency. Hence, in order to be economically efficient, a firm must be both technically and allocatively efficient.
Review of literature on factors affecting dairy cow milk production efficiency
Farm size:
The size of the farm on which dairying is practiced affects the dairy farm’s efficiency (Tzouvelekas et al, 2001; Paul et al, 2004). Mishra and Morehart (2001), Short (2000), and McBride and Greene (1997) agree that farm size has significant, positive impact on the financial success of dairy farms. Gardebroek (2002) found farm size in the Netherlands to explain significant variation in the choice to farm organically, highlighting the importance the acreage base plays in organic dairy management. Nivievskyi and Taubadel (2008) found the size of the farm to have a strong, positive and non-linear effect on competitiveness. Marek et al. (2007) in a study in Poland found an increase in herd size and average milk yield to improve milk production profitability as well as to increase the agricultural income per cow.Herd size:
Many researchers agree that the size of a dairy herd has a positive correlation with the farm performance. Bhuyan and Postel (2009) found the number of milking cows to have a positive impact on the net farm income. An additional milk cow typically added 119cwt of milk to annual production in 2005. It can be noted here that such addition would generally not mean an addition of proportionate cost to the herd in the short term. Others (Sahin, 1993, Sanar, 1993), (Headley et al, 2002)), and El-Osta and Johnson (1998) found herd size to be the most significant contributing factor to net farm income among dairy farms. According to Bebe (2003), milk production in Kenya can be increased through keeping more cows by between 14 and 47 percent. Nivievskyi and Taubadel (2008) in a study in Ukraine found the farm size to have a strong positive and non-linearFaCT: Publishing online at http://www.m.elewa.org 43
effect on competitiveness. These studies appear to have dwelt only on the economies of scope of dairy cattle keeping, leaving a gap on yields per cow.
Farm income-activity diversification:
Diversification of farm activities with a view to get extra income has been found to be a factor in dairy farm performance. Mishra and Morehart (2001) found diversification to negatively correlate with dairy farm profitability. The detraction from specialization, they suggested, had a negative impact on conventional U.S. dairy farm profitability.Farm technology:
Integrating new technology into a dairy enterprise may offer several advantages. Short (2000) and El-Osta and Johnson (1998) agreed that more advanced milking parlors were positively correlated with U.S. dairy farm profitability. Staal et al (Undated) noted that improved technology would reduce production costs and induce shifts towards more commercial systems; adapting to changes in other factors would be dependent on the availability of technological alternatives, either existing or new. Therefore, technology measures are hypothesized to have a positive impact on the smallholder dairy farm profitability.Dairy breed:
Staal et al, (Undated) found genetic improvement to have a dramatic impact on development and growth. Ratuki (2004), after finding the Fiji cow’s average productivity to be low, advised on the need to increase cow productivity, farmer productivity and land productivity through integrated measures.Feeding:
El-Osta and Johnson (1989) and Nivievskyi and Taubadel (2008) recommend dairy farms to produce most of their feed themselves and keep arable land per animal equivalent as low as possible to increase the farm’s competitiveness. Owuor and Ouma (2009) found fertilizer and feeds to be major constraining factors in enterprise productivity among the resource poor farm households in western Kenya.Farmer experience:
Experience is expected to have a positive impact on performance. Sipil’ainen and Lansink (2005) found a significant learning effect in analyzing the efficiency of organic versus conventional dairy farms in Finland, estimating roughly seven years as the inflection point. Using age as a proxy for the dairy farmer’s experience, Lucila et al (2005) found it to have a significant effect on the cost efficiency of dairy farms. In this case, age was shown to be inefficiency reducing, implying that more experienced farmers are less cost-inefficient than their younger counterparts.Farmer’s age:
An operator's age may influence the way one manages the farm operation. El- Osta and Johnson (1998), Wubeneh and Ehui (2006), McBride and Greene (1997), are in agreement that age positively correlates with the costs of dairy farms. In a different study results on age indicated that older farmers were not able to use up to date farm management methods or are less adaptive to modern technologies. They prefer to be associated with older methods of production thus reducing efficiency (Owuor, 2009). On the contrary, Bhuyan and Postel (2009) found the operator age to have a significant and positive impact on net farm income.Farmer education level:
A successful dairy farm manager must have ability to plan well and possess a thorough knowledge of livestock production. Hashmi, (2004), and Tzouvelekas, Pantzios, and Fotopoulos (2001), are in agreement that farmer’s age and education have significant power in explaining variation in economic efficiency. Wubeneh and Ehui (2005) found a significant difference in milk produced and marketed between farmers who had training in livestock production and those who hadn’t, while there was no difference in number of cows they own, use of feed and veterinary services. Udomsak and Khanna (2004) found the production efficiency of dairy cattle farming in Thailand to be low because of long calving interval of 450 to 500 days. They attributed this to lack of education and knowledge by farmers to manage the dairy cattle.Mishra and Morehart (2001) found that farmer’s education and use of cooperative extension agents had a significant and positive impact on financial success of U.S. dairy farms. Contrary to expectations, Owuor (2004) found education to increase inefficiency, in a study amongst smallholder farmers in western Kenya.
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