Livestock Research for Rural Development 23 (6) 2011 Notes to Authors LRRD Newsletter

Citation of this paper

Hedonic price analysis to guide in breeding and production of Indigenous chicken in Kenya

H K Bett, K J Peters and W Bokelmann

Department of Crop and Livestock Sciences, Humboldt University of Berlin,
Philippstr. 13, Haus 9, 10115 Berlin, Germany
* Department of Agricultural Economics and Social Sciences,
Humboldt University of Berlin, Philippstr. 13, Haus 12a, 10117 Berlin, Germany


The aim of the study was to determine indigenous chicken attributes and the socioeconomic characteristics that influence the price differentials for live indigenous chicken in the market using a hedonic model. Data was collected from six selected counties of Kenya. A total of 720 respondents were interviewed using structured questionnaires. Bivariate correlations were used to determine the relationships between attributes, type and the per kg live weight prices of indigenous chicken. Weighted indices were computed to determine the attributes and type of Indigenous chicken preferred by the traders. Factors and attributes that influence the variation in the prices of indigenous chicken were identified. Price variations and formation were determined to depend mainly on the buyers’ assessment.

Attributes such as weight, body size, plumage colour and the general body condition significantly influenced the price. However, traders generally preferred weight, body size and body condition at the local, secondary and terminal levels of the market. Cocks, hens and cockerels were preferred in that order. Other important factors were the gender of the trader, transport costs, number of traders and the presence of market information. The attributes and types identified to influence the prices and those preferred by traders are important to the farmers in making their production and marketing decisions.

Key words: Attributes, buyer and seller preferences, marketing, price variations


Indigenous chicken (IC) rearing in rural areas is predominantly based on a free-range system with low levels of production and feed resources varying depending on the local conditions. The economic productivity of IC is hampered by slow growth rate, poor egg production and reproductive performance (Pedersen 2002; Phiri et al 2007), which is compounded by high predation and high mortality rates (Mungube et al 2008). Despite the problems numerous opportunities in the current production systems such as development of small sustainable chicken enterprises that would provide regular outputs using low inputs and therefore improving food security and livelihoods of the rural poor farmers (Kitalyi 1998; Nielsen et al 2003; Miao et al 2005), still exist and need to be exploited. This low input system in the rural areas, and the widespread preference for the meat and eggs of indigenous birds, are together likely to ensure the retention of indigenous breeds for a considerable period of time to come (Pym et al 2006).

 Local chicken are largely raised by smallholder farmers, providing a unique opportunity for them to benefit from the market growth and health improvements (Ifft et al 2008), through provision of food and monetary contribution to the household economy. Market growth can be achieved by a well facilitated marketing structure that complements production in the rural areas. However, marketing of IC in the smallholder sector is informal and mostly localised within rural markets and between farming households who mostly depend on exploitative middlemen buying for the urban markets (Gondwe et al 2005; Muchadeyi et al 2005; Bett et al 2009a). The market failures coupled with the nature of trade have enticed producers to rely on traditional production and market practices overtime, in spite of IC fetching higher prices compared to exotic breeds (Bett et al 2009a; Heft-Neal et al 2009).

 This study therefore undertook to determine if the price differentials for live indigenous chicken in the market are influenced by socioeconomic factors and non-market attributes. By conducting such survey, it is possible to determine the specific attributes or factors which are most important in explaining the variations in prices which can then be matched to preferences of the consumers. This is important for making breeding, production and efficient marketing decisions.

 Materials and methods

 The study area and sampling design

The study was carried out in six selected counties of Kenya. These were Kakamega (1°14′N 35°07′E) and Siaya (0°14′N 34°16′E) counties in the Western region, West Pokot (1.2333°N 35.1167°E) and Turkana (03°07′ 31″ N, 35° 35′ 23″ E) counties in the North Rift Valley region and Bomet (0°47′S 35°21′E) and Narok (1°05′S 35°52′E) counties in the South Rift Valley region of Kenya. Six divisions per county based on chicken population according to MOLD (2006) estimates were finally identified. A survey was then carried out in all the towns and market centres within the selected divisions including the County’s administrative town. A total of 720 respondents were interviewed from the six Counties using structured questionnaires. Information from major markets was also collected in Nakuru (00°17′S 36°04′E) municipality and in the cities of Kisumu (0°6′0″S 34°45′0″E) and Nairobi (1°17′S 36°49′E). Data collected included information on the source of IC to be sold, prices (at the point of origin and at the market), transaction costs (e.g transport, levy or council charges, storage, disease control treatments) including the mode of transport to the market. The attributes or traits of the IC preferred by buyers and sellers (such as weight, sex, age, size, body condition, genotype, plumage colour). The type of bird preferred ( e.g cock, breeding cock, hen, laying hen, cockerel, pullets and chicks), purpose of purchase (e.g. slaughter, breeding), total number of chicken sold at the market day, total number of buyers operating at the market, and  the type of sellers and buyers (farmer, trader, breeders) among others were incorporated in the data. The IC attributes, socioeconomic characteristics and the identified factors made it possible to explain the variation in prices.

 Hedonic pricing 

 A hedonic model of prices is one that decomposes the price of an item into separate components that determine the price (Martínez-Garmendia 2010). According to Lancaster (1966; 1976; 1979), goods are seen as bundles of quality characteristics and the ‘marginal value’ consumers attribute to each of the characteristics explains the variation in prices of goods. Rosen (1974) introduced a market-based approach for deriving a hedonic price function, where utility-maximizing buyers and sellers interact to establish the market value for a given attribute. A differentiated product can therefore be completely described by the vector of objectively measured characteristics of the product such that the observed price will be a composite of the coefficients of the embedded attributes. This technique can be used in relating the price per animal to its various attributes and characteristics (Jabbar and Diedhiou 2003).

According to Rosen (1974) and Oczkowski (1994) the price of the product excludes the attributes of the buyers and sellers implying differentiation of products and not their markets, buyers or sellers in the competitive markets. On the contrary, most studies have found that the product prices are as well related to the attributes of buyers or sellers (Francis 1990; Andargachew and Brokken 1993; Parker 1993; Williams et al 1993; Rodríguez et al 1995; Jabbar et al 1998), consequently reflecting that the markets are non-competitive. This study therefore hypothesises the interplay of buyer or seller characteristics and the product attributes to determine the price of IC in urban and rural markets.

 Model specification

 This analysis adopts hedonic pricing and regression analysis to estimate the value of specific attributes of live indigenous chicken from within the bundled price. The regression analysis treats the price as a function of various attributes. The general implicit function is expressed as:

where Pi is the price of the product i in the market, X1, X2….Xn are product attributes, and Z are the buyer or seller characteristics. The variable Z can be omitted from the function if there are no existing differences between the buyers or sellers (Rosen 1974).

The above function then takes the following empirical multiple regression models’ derived short form:

where Pi is the market value or price for live IC which is log transformed, X are the product attributes and Z are characteristics of the sellers or buyers including other relevant market characteristics, while a is the constant effect and ei the homoskedastic error term with zero mean. The natural log transformations were used on all non-binary continuous variables to allow for implicit prices of attributes to vary with the amount of the attribute depending on the level of the attribute. The variables used in the model are presented in Table 1. To obtain the parameters the model was estimated using STATA 10.1 (StataCorp 2009).

 Attributes and types of IC preferred in the market

Attributes and the type of IC preferred by buyers and sellers in the market were ranked. Through this the indices were then calculated. The indices represent weighted averages of all rankings for a particular attribute or the IC type. The formula used was adopted and modified from Bett et al (2009b) as follows:


where Ii is the index value, Xj is the percentage of respondent ranking the attribute or trait i in the jth rank, m is the last rank of the trait or attribute, and k is the sum of ranks for n number attributes or purposes.


 Descriptive results

 In this study, the mean age of the traders was 33.4 years, 74% of them were men and 26% women. The mean number of years of schooling for the respondents was 11.5, equivalent to secondary level of education. The average log price of chicken was KES 5.75 per live weight with a range between 5.0 and 8.0 in the markets. Other variables used in the analysis are described in Table 1.

Table 1. Descriptive Statistics for variables used in the models










Natural log for price of live IC per kilogram(KES/kg)








Age of the household head(years)


17- 72


Natural log of age




1 if the respondent is male




Number of years of formal education




Natural log of years of education




1 if market status/level affects prices




1 if plumage colour is considered




1 if genotype is preferred when buying or selling




1 if body size is preferred when buying or selling




1 if age of IC is preferred when buying or selling




1 if weight of IC is preferred when buying or selling




1 if general body condition is preferred when buying or selling




1 if sex of IC is preferred when buying or selling




1 if festival season affects purchase and sale of IC




Natural log-transport cost of IC(KES per month)




Natural log-treatment cost of IC(KES per month)




Number of IC traders(numbers)




Natural log of number of traders




1 if information on IC supply and prices is available



1$ = 76 Kenya Shillings (KES).

Table 2 shows the price distribution per kg of live IC according to the market status or levels, which are the primary or local, secondary and tertiary, or the terminal market levels. At the local market level, prices were higher at the markets along the major highways. On average, the tertiary markets offered the highest price.

Table 2. Distribution of IC prices according to market status or level


Primary/Local markets (KES/Kg)

Secondary Markets (KES/Kg)

Tertiary/terminal markets (KES/Kg)









Average price




Figure 1 shows the trend of chicken meat production and the prices per kg for live chicken and meat. Chicken prices have been gradually increasing over the years, with the highest increase reported between 2005 and 2006. Dressed chicken or meat fetched higher prices. It also shows that the prices have been continuously increasing despite the increase in production. This indicates that there has been a continuous increase in demand rendering supply to have little effect on the variation of chicken prices. The highest supply of chicken meat coincided with the highest producer prices.

Figure 1: Trend of chicken meat production and the producer prices for live chicken and meat. 
Bivariate correlation results

Table 3 gives the correlations between the attributes, IC type and the prices per kg at the three market levels. It shows that cock type and weight were correlated with the prices at all three levels of markets. The attributes and types of IC were all correlated to the prices at the local markets. As the market advances, fewer attributes and types of the IC are related to the prices indicating that the traders are more selective at these markets and pricing is mainly based on the most important attributes and types required by the consumers. 

Table 3. Bivariate correlations between attributes, IC type and live chicken prices per kg at the three market levels


Primary/Local market

Secondary market

Tertiary/Terminal Market

IC type*price












Breeding  cock




Laying hen




























Body size



0. 049









General body condition




** Correlation is significant at the 0.01 level.     * Correlation is significant at the 0.05 level.

 Attributes and type of IC preferred by buyers and sellers in the market

Figure 2 and 3 shows the index values of the attributes and type of IC that are preferred by traders in the urban and rural markets. The IC weight, body size and the general body condition are the most preferred attributes (Figure 2). Weight has the highest index value of 0.26 (25.6 %) and plumage colour has the least value of 0.07 (7.2%). However, weight has the highest preference in both secondary and terminal markets. While at the primary market body size has the highest index value of 0.26 (26.3%). 

Figure 2:
Attributes preferred by traders in Marketing of IC

Cocks and hens attain the highest preference at all market levels (Figure 3), while, breeding cocks are least preferred except at the local market. This means that the three types of IC at the local market would be highly priced. Farmers should therefore adjust to the traders requirements in order to take advantage of the available market opportunity.  

Figure 3:
Type of IC preferred by traders in the Market

 Empirical Results

Econometric results are presented in Table 4. All variables in the regression, measured by the R2, explained 85 percent of the model. Eleven of the variables significantly determined the IC market prices. These were; gender of trader, market status, plumage colour, body size, weight, general body condition, sex of IC, festive season, transport cost, the number of traders and information availability. The variables gender, plumage colour, sex of IC, number of traders, festive season, and transport cost had a positive effect on the IC prices, while the general body condition, body size, market status and information availability had a negative effect.

Table 4.  Determinants of IC prices



Robust Std. Error




















































* Significant at 10%; ** significant at 5%; *** significant at 1%


Results indicate that the gender of the traders (Gender) positively influenced the price. This means that the IC price increased by one unit if the trader was a male, indicating that disparities exist in price formation in the rural and urban markets in the study area. The role of gender in pricing was also noted by (Pym et al 2006; Williams et al 2006; Aklilu et al 2007; Halima et al 2007).

Apparently, there is a positive and significant relationship between the variation in price of IC and the market status. As also indicated in Table 2, the prices of IC were lower at the local markets and advanced at the tertiary markets. Consequently, it was observed that the day-to-day price variations existed within these three levels of markets. Generally, consistent with other studies (Mlozi et al 2003; Emuron et al 2010; Moges et al 2010), IC have higher demand and fetch higher prices in the urban markets. This implies that consumers at the terminal markets would pay premium prices for both live and dressed IC. Moreover, this would much depend on the motivation in relation to the perceived quality of IC compared with the other available product’s substitutes. This may be attributed to the production patterns of extensive systems, which contribute to the better meat quality in terms of taste and flavour as well as texture and firmness resulting from a higher slaughter age of IC. Moreover, the demand for IC is often not satisfied despite their high prices (Heft-Neal et al 2009). Prices would therefore respond to supply rather than the demand (Serem et al 2007).

In this study, the characteristics that were useful in the judgement of chicken prices included the plumage colour, body size, weight and the general body condition. These attributes were used by traders as a form of grading IC at the different market levels. The plumage colour influenced positively and significantly the IC prices. This means that the physical attractiveness of the IC to the buyers significantly improved its marketability. Plumage colour was also seen to influence the disparity in livestock prices in the rural markets of Ethiopia (Solomon et al 2003; Mengesha et al 2008). As expected, the weight and general body condition positively influenced the pricing of IC. This means that heavy and healthy birds would have higher acceptance in the market and therefore attract favourable prices. The IC weights at most of the rural markets in the study area were based on approximations. This was mainly done manually and depending much on the experience of traders. However, at the terminal markets weighing scales were used. Contrary to our expectations body size affected prices negatively. Proper transmission mechanisms need to be setup in order to pass the market information especially on the identified market preferences to the farmers.

The consideration of the IC sex greatly influenced their market prices. This variable therefore affected the variation in the prices positively. Evidently the male IC was highly preferred to female IC all market levels (Figure 3). The IC sex among other characteristics such as plumage colour, comb type and age are important traits for socio-religious functions and in turn have shown a huge effect on the price also in the Ethiopian chicken market (Tadelle et al 2003; Moges et al 2010).

During every festive season, there is a significant increase in prices of IC. This scenario is not only confined to urban areas but there are considerable changes in prices as well in the rural local markets. The IC prices in this study were enormously influenced by the festive seasons. This means that over the festive seasons, there is a high demand and therefore traders get a chance to sell IC at exorbitant prices to make more profits. This covers for the backdrop resulting from the uncertain low price periods over the year. Some of the occasions mainly noted by traders were Christmas and Easter holidays. Similarly, other studies noted the existence of the same scenario relating to the price and the socio-cultural events especially the Christian and Muslim festivals (Aklilu et al 2007; Halima et al 2007; Emuron et al 2010; Moges et al 2010). The IC farmers should therefore take advantage of the demand shifts resulting from these festivals.

The results indicate that the transport costs affected the prices positively. This implies that the cost incurred during transportation can be attributed to the variations in IC market prices and not only the characteristics of the product. Buyers would then pay higher prices coupled with the costs of transport including other transactions at the various levels of the markets, which eventually are passed on to the buyers at the urban markets. These costs are also transferred back to the farmers by middlemen at the local markets and farm-gate in form of low prices for IC purchases (Owuor and Bebe 2009). The transaction costs that include the risks in marketing and credit should therefore be carefully assessed in order to improve market access and participation (Mathuva 2005; Aklilu et al 2007). The low level of output per farm contributes to the IC farmers’ inability to access high value markets. However, the low cost of production may have ensured the continuity in the rearing of IC among the rural poor farming households.

The present study showed that the concentration or the number of traders participating in the market influenced the prices negatively. This means that with a higher concentration of traders in the market, the prices of IC are depressed significantly and vice versa. This is the result of competition between the traders, extensively varying the prices for both purchases and sales of IC. Urban market traders often acquire their IC from the brokers who are paid some commission for assembling the products from the producers at a specific place in the market. These brokers also buy from the farmers and sell directly to their customers, therefore obtaining substantial amounts of profits from the higher prices. In most cases the sales of IC by farmers are done when need arises as recognized by (Gausi et al 2004; FAO 2009).

It was revealed that information the availability of market information especially the prices and supply negatively affected the selling prices of IC. However, it was observed that traders had more access to market information than the farmers did. This was a disadvantage to the farmers since it limited their marketing decisions and consequently affecting production and sales decision. On the contrary, the well informed traders were able to exploit the presence of information asymmetries or lack of information by charging high prices at different markets for their IC sales and paying lower for the purchases from the farmers who accepted whatever they were offered. Upton (2000) acknowledges that the lack of information results in poor integration of spatially dispersed markets and cyclical fluctuations in production and prices. However, the relatively high margins for the intermediaries reflect opportunities present at the market (Aklilu et al 2007). These opportunities can therefore be effectively utilised by the farmers if they are provided with adequate and reliable information as well as through group marketing.


This study identified that various factors and attributes influence the variation in the prices of IC. It recognises that the determination of prices heavily depends on the assessment by the buyers and that any source of variations in prices poses some risks to both farmers and traders. Traders or intermediaries often encounter fewer risks than the farmers do. The risks associated with the prices are transferred back to the farmers and to the end users. In addition, traders often do not provide adequate and reliable information to the farmers about the market conditions especially regarding prices and the preferences of the consumers. Therefore, to avoid exploitation from the intermediaries, farmers should be encouraged to form marketing groups for better access to market information sources, improvement of their bargaining power to negotiate for reasonable higher prices for their IC and consequently concentrating more on raising chicken based on the preferred attributes for the market.


The authors are very grateful for the financial support from the Yousef Jameel Scholarship, and Humboldt University of Berlin. The inputs from the Kenya Agricultural Productivity Project (KAPP) through the Indigenous Chicken Improvement Project (INCIP) are also recognized.


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Received 4 March 2011; Accepted 23 May 2011; Published 19 June 2011

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