| dc.description.abstract | Technological recommendations for maximizing green leaf production have been made available to
smallholder farmers by the Tea Research Foundation of Kenya (TRFK) through various publications.
Indeed TRFK has released clones, which are yielding in excess of 4000 kg mt/ha. Consequently, the
smallholder tea areas are planted with these clone compared to the estate sub sector with large areas of
land planted with old seedling tea cultivars, yielding lower than 2500 kg mt/ha per year. Nevertheless, tea
productivity in the smallholder sub sector has been relatively lower than in the estates sub sector over the
years and the yields are still well below potential. The Kenya Government projects to produce 350 thousand
metric tones by the year 2008, through putting emphasis on efficient use of strategic inputs such as
fertilisers and adoption of intensive technologies of tea production to enhance yields. This study investigated
the efficiency of adoption of tea production technologies and some policy factors contributing to low tea
productivity in the smallholder tea sub sector. Specific objectives were:
1. to identify the major resources being used by farmers in tea production, estimate the tea production
function and identify which of the identified resources significantly influenced tea production in
the smallholder tea sub sector;
2. to determine whether the farmers were utilising the identified resources efficiently;
3. to determine the economic rationality of small scale tea farmers;
4. to determine compare the relative efficiency between east and west of the Rift Valley regions;
5. to identify the factors influencing the supply of green leaf, estimate the green leaf supply function
and determine which of the identified factors significantly affect the supply of green leaf in the
smallholder tea sub sector and
6. to identify the major factors limiting tea production, green leaf supply, farm profits and seek
solutions to the problems.
The results of this study have policy implications at both the micro- and the macro-economic
levels. If the factors that constrain tea production at the farm level are identified, suitable measures can be
drawn to address the problems within the current policy framework in the short run. For example, if farmers
are inefficient in the use of strategic inputs such as fertilizer, they may profitably reduce the amount spent on
that input or increase supervision especially where labour for tea plucking is adequate. If the monthly
producer price has a significant effect on green leaf supply, it can be adjusted upwards in the short run to
give farmers incentives to supply more tea leaf etc.
Both primary data and secondary data were used in the study. Primary data were collected using
a questionnaire instrument from a randomly selected sample of 259 smallholder farmers in Kirinyaga,
Nyambene, Nandi and Nyamira Districts. Secondary data were obtained from Kenya Tea Development
Agency Limited (KTDA) and Tea Board of Kenya. The analytical procedures used were: Cobb-Douglas
production function, supply function and correlation and profit function analyses.
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The Cobb-Douglas production function was used to determine the economic efficiency of the
sample of farmers in the four districts. The data for each district was further categorized and analysed
according to tea growing agro-ecological zones (AEZs) i.e. Lower High Zone and Upper Midland Zone I.
The objective was to ascertain resource use efficiency not only for the districts but also for each agroecological zone. It was hypothesised that efficient use of inputs, particularly fertilizer, in each district surveyed
and the respective agro-ecological zones would improve productivity. The predictors of tea output/year
were: fertilizer bags used per year, number of tea bushes and the total labour used i.e. hired labour and
family labour in man-hours per year. The results showed that fertilizer input significantly (P < 0.01) influenced
tea output in the UM1 agro-ecological zone in every one of the four districts, and all the districts surveyed
except Nyamira District. The test of price efficiency indicated that the fertilizer input was efficiently used in
UM1 zone of all the districts, Nyambene and Nandi Districts. However, fertilizer use was inefficient in all the
LH zones. The lack of response to the input in the zone could be due to the high altitude leading to slow
growth rates. The results suggest a need to develop fertilizer use recommendations based on agroecological
zones rather than the present single blanket for the whole country. Factors leading to inefficient use of
fertiliser in Lower Highland Zone should be further investigated so as to remove the impediments and
improve tea yields. For the whole of the sample, fertilizer significantly influenced green leaf output. However,
an analysis of pricing efficiency showed that fertilizer input was inefficiently used in the smallholder sub
sector. Labour input influenced green leaf output significantly at 10 % level in Nyamira District and 5% level
in Nyamira LH zone. The analysis of price efficiency showed that labour was efficiently allocated in
Nyamira District and in particularly Nyamira LH zone. The labour input was inefficiently used in all other
Districts and AEZs.
One of the major concerns for smallholders is product quality. The recommended plucking
standard in KTDA is two leaves and a bud, resulting in high quality tea, while some estates harvest more
than two leaves and a bud, reflecting more but lower quality of made tea per plucking round. As a result, the
smallholder teas fetch high prices in the auction markets than the estates teas. It is therefore expected that
farmers would be guided by the price factor in the output markets to make quality decisions in the allocation
of strategic inputs, within the context of their variable factor price regimes and quantities of fixed factors.
Hence, they would be price-efficient in their operations. The extent of price-efficiency, which is a component
of economic efficiency, among the small-scale tea farmers needed to be determined. It was hypothesized
that the extent of rationality in allocation of resources in the tea enterprise is relatively low. Hence, the
smallholder tea productivity has remained relatively lower than in the estate sub sector, high yielding
clones and useful agronomic recommendations extended in the smallholder sub sector notwithstanding.
“A Test of Economic Rationality Model” was used whereby, the index of economic rationality, r is the
product moment coefficient of correlation between log (total variable costs-excluding labour costs) and
log (labour-in man-days) for each tea district and region.
The results showed that the product moment coefficient of correlation, r was: - 0.647 in Kirinyaga
District, 0.651 in Nyambene District, 0.793 in Nandi District, 0.743 in Nyamira District, 0.595 in the east of
the Rift Valley region, 0.752 in west of the Rift Valley region and 0.674 for all farms surveyed. It w as noted
that the lowest value of r was 0.595 in east of the Rift Valley Region. It means that at least 59% of the variance
in the logs of both inputs is due to the variation in the systematic profit-maximizing component of these
inputs. The balance of 41% is the maximum that could be occasioned not only by poor technology and/or
knowledge gaps but also by errors in the model and noise in the universe. The null hypothesis was rejected
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in favour of the alternative hypothesis. The conclusion is that smallholder tea farmers in Kenya are quite
price efficient in tea production.
The profit function was used to determine the efficiency of resource use in the districts surveyed
and their respective tea agro-ecological zones. This method assumes that farms are relatively homogeneous
in the way they use technology in the process of production. However, it is not a suitable method to use
when farm groups are relatively heterogeneous. For example, tea in Kenya is grown in the east and the
west of the Rift Valley regions. Tea farmers in these two regions face different regimes of prices of variable
factors such as fertilizer and labour for plucking tea. They also have different quantities of fixed factors
particularly land. Hence, it is imperative to determine relative efficiency between the two tea blocks. It is
assumed that these farms in the two regions behave according to a certain decision rule termed as profit
maximization. An estimation of the profit function for the tea farms in the two regions and comparison of the
relative economic efficiency between them was done. “A test for relative economic efficiency “ was performed
to bring forth an overall comparison of economic efficiency for the two sets of farms. A profit function model
was fitted on 212 smallholder farms. The dependent variable was gross margin per farm per year. The
independent variables were: number of tea bushes per farm per year, cost of fertilizer (KShs.) per hectare
per year, labour wage rate (KShs.) per man-day per year in each farm and a dummy variable where D=1 for
the east and D=0 for the west of Rift Valley, respectively. The results depicted that the coefficients of the
number of bushes, fertilizer cost/ha/year and labour wage rate/man-day were all positive and significant
(P< 0.01). It had been hypothesized that there is no efficiency difference between east and west of the Rift
Valley in tea production. Hence the coefficient of the region dummy would be zero. The results rejected the
hypothesis of equal efficiency between the two regions (P< 0.10). Further more, the positive sign of the
dummy variable indicates that east of the Rift Valley tea farms are more profitable, that is more economic
efficient, at all observed prices of the variable inputs given the distribution of the fixed factors of production.
It is concluded that east of the Rift Valley smallholder tea farmers are more successful in responding to the
set of prices (Price efficiency) and/or have higher quantities of fixed factors of production, including
entrepreneurship (technical efficiency). Factors responsible for low efficiency in the west of the Rift Valley
should be studied and alleviated to increase tea production.
The secondary data collected from KTDA was used to determine some of the factors contributing
to the low tea productivity in the whole of the smallholder tea sub sector. Part of the data was used to fit a
production function of the smallholder tea sub sector. It was hypothesised that efficient use of inputs would
improve productivity. To measure efficiency, Cobb-Douglas production function was used. The predictors
of tea yield/hectare were: fertilizer used/hectare, number of bushes/hectare, number of growers/hectare
and the number of extension staff/hectare per district. The results showed that fertilizer input significantly (P
< 0.05) influenced tea yield in 1994/95, 1995/96, 1996/97 and 1997/98. The test of pricing efficiency
indicated that the fertilizer input was inefficiently used at 1% level in the four consecutive years. The other
inputs were not significant (P< 0.05). The results suggest that fertilizer use efficiency can be increased to
improve tea production. Farmers need to be educated about the benefits arising from the application of the
fertilizer input according to agronomic recommendations in order to enhance efficiency and ultimately
increase tea productivity.
The other part of the secondary data was used to estimate the supply function of the green leaf in
the smallholder tea sub sector. The major factors considered to be influencing supply of green leaf were:
- the number of tea growers, price of fertilizer, monthly price of green leaf, and end of year price of green leaf
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over the years. The General Linear Model fitted the data best. The results revealed that, monthly mean
price lagged once (Pmt-1) and end year price (“bonus”) lagged five times (Pet-5) significantly (P < 0.05)
influenced the supply of green leaf. Elasticity of supply of green leaf was 32.88 for monthly average price
(Pmt-1) and 6.69 for the end year price lagged five times (Pet-5). Hence green leaf supply was relatively
responsive to tea price changes. Policy intervention should therefore be focused on improving producer
prices particularly the monthly payment in order to increase the quantity of green leaf in the short run and
end of year payment in the long run. | en_US |
