Determination of socio-economic factors affecting piggery business in Balaka District, Malawi

R E Phiri

ronaldphiri8@gmail.com
University of Malawi, Bunda College of Agriculture, Lilongwe, Department of Agribusiness Management, Lilongwe, Malawi

Abstract

This paper examines the socio-economic characteristics that affect piggery business groups in Balaka district in Malawi. This was based on the theory which stipulated that certain demographic and socio-economic characteristics of technologies affect productivity, profitability and its contribution to household income of beneficiaries.  Thirty six piggery groups were sampled in Balaka out of forty six piggery business groups using stratified random sampling. Another thirty six control groups were sampled. Data was collected through semi-structured questionnaire, business records assessments and focus group discussions. 

The study found that group experience in piggery business and numbers of sows are the major demographic and socio-economic factors that affected piggery business profitability and its contribution to household income. 

Key words: demographic characteristics, profitability

Introduction

The mission of Malawi Government is to create wealth through various programs including agriculture development. Agribusiness such as piggery is one of the priorities in the Malawi Growth and Development Strategy which is an overarching policy for poverty reduction and sustainable economic growth in Malawi. 2008 livestock survey reported an increase in national pig production trend from 481,108 from 1997 to 1,229,468 making piggery to be the third largest livestock population in Malawi after chicken (44,049,155) and goats (3,106, 271). In the same year, pigs became the second largest meat supplier in Malawi. It is believed that pigs are a tool to enhance household income and food security among vulnerable smallholder resource poor households. Promotion of piggery in Malawi is now characterized by many projects and a group approach for capital diversity considering that pigs are capital and labour intensive as they are monogastric animals which in many cases need better animal housing, good food and frequent vaccination. One such project was Skills Development Income Generation which operated from 2004 to 2009 in Balaka district in Malawi. Unfortunately there was no study to identify the demographic and socio-economic factors affecting piggery business. This study was commissioned to address the information gap.

Materials and methods

The study was conducted in Balaka district in the Southern Region of Malawi. The district headquarters is approximately 240 km from Lilongwe City, the Capital of Malawi, and about 130 km from Blantyre City, the main commercial centre in the country. The district had a population of 46 piggery groups whose composition by gender was such that women groups were 75%, mixed groups were 20% and men groups were 5%. Each group had an average of ten members. A representative sample of thirty six piggery business groups was drawn using stratified random sampling which represented 75% women groups, 19% mixed groups and 6% men groups. Other thirty six control groups were sampled. Control groups were trained in pig farming but were not in business due to some factors. Data was collected through group business records analysis, focus group discussions, and examination and appraisal of SDIG Project documents to obtain useful information about the operations of group piggery businesses in Balaka. Data was analyzed using SPSS 11, Stata 10 and Excel 2007. 

Data analysis involved use of descriptive statistics such as modes and frequencies. A multiple linear regression model was the key econometric model used to determine the significance level of the demographic and socio-economic factors affecting piggery business in Balaka. Production aspect was analyzed using break even analysis. The econometric model was specified by: 

i= Gross piggery production output (Malawi Kwacha)

= Number of sows

= Feed intake (kg)

= Veterinary costs (Malawi Kwacha)

= Group experience in piggery business (in years)

= Education level of the head of the group (in years of schooling)

= Group composition by gender

i= Number of groups

= Random error term (represented other factors held constant)

= Parameters estimated by the model (where j=1, 2, 3, 4, 5, 6)

One feature of this model is that, the slope coefficient () measures the elasticity of Y with respect to X, that is, percentage change in Y for a given (small) percentage change in X (Bamiro 2008). The adjusted coefficient of determination, R² was used to test the adequacy or validity of the regression model. This measured the proportion of total variation in Y that has been accounted for by regressing the dependent variable on the whole set of regressors. It explains the amount of variation in the dependent variable analyzed by the model. As a rule of thumb, a proportion of 60 to 90 percent is acceptable with less doubt about multicollinearity and other associated problems. 

Definitions of the variables 

Dependent variable 

The gross piggery production output was the dependent variable in this study. This was measured as a continuous variable in Malawi Kwacha. This data was collected from piggery group records. The study established that Balaka piggery business groups were mostly producing piglets whose price ranged from MK4,000 – K6,000 each (approximately US$25 – US$40), and weaners whose price range from MK 12,000 – MK18,000 each (approximately US$79 – US$118). 

Explanatory variables 

In this study, composition of the group by gender, number of sows, feed intake by the pigs, veterinary costs, education level of the head of the group, and group experience in piggery business were hypothesized to influence the gross piggery production output. These were the explanatory variables in this study. 

(a)     Number of sows 

Number of sows is an essential element in piggery business. When number of sows increases, then more piglets and other piggery products will be produced and then gross piggery production output will increase. Hence a positive relationship was expected. 

(b)     Feed intake by the pigs (kg) 

The volume of feed intake by the pigs was assumed to be a major determinant of the enterprise production costs. Ceteris paribus, the higher the feed intake, the higher the costs of production and the lower the gross piggery production output in the long run. Hence the variable was hypothesized to have a negative relationship. 

(c)     Veterinary costs (MK) 

A higher veterinary cost value was hypothesized to vary negatively with the gross piggery production output. A zero value was considered a disinvestment in that a high risk of disease was likely to lower production. 

(d)     Experience in piggery business 

Group experience in piggery business was assumed to have a positive relationship with gross piggery production output. Experienced piggery groups were expected to apply technical skills acquired from previous production. Hence a positive relationship was expected. Group experience was captured by the number of years a particular piggery group has spent in piggery business.  

(e)     Education level of the head of the group 

The education of the group head was captured by the number of years of schooling. This was an important variable because adoption of modern piggery practices depends on knowledge and creativity which education provides. An educated group head was expected to act as an opinion leader in influencing the group to adopt best practices in business. Level of education of the group head was assumed to vary positively with the gross production output.  

(f)     Group Composition by Gender 

Gender of the piggery group was one of the variables which this study analyzed. This was an important factor considering that SDIG Project was an initiative of a Ministry of Women and Child Development. It was hypothesized that men, women and mixed piggery groups performed differently due to different income levels emerging from gender differences.

Results and discussion

Results are presented in two ways. The first part deals with descriptive statistics about certain aspects of piggery business groups in Balaka. The second part presents econometric model and focus group discussion results. 

(i)     Descriptive statistics of piggery business groups by gender 

Descriptive statistics results for Balaka piggery business groups in the study area are presented in Tables 1 and 2 respectively. 

The composition of piggery groups by gender was such that women’s groups constituted 75%, while mixed groups were 19.4% and men’s groups were 5.56 percent. Most piggery groups under SDIG project had 3 to 4 years of experience (94.5%). Further, both piggery and control groups attended a 21 day course in pig farming and business management at a district centre. Piggery groups were trained in feed formulation, heat detection, construction of piggery pen, capital building, drug administration, marketing and record keeping. In terms of breeds, all piggery groups reared crosses and exotic pigs chosen by groups themselves. Most piggery group members were part-time piggery farmers as they combined group business activities with other enterprises and paid piecework of their own. Further, households from piggery and control groups were mostly involved in production of tomato, cotton, groundnuts, tobacco and maize. They treated piggery as another subsistence venture to supplement their household income levels. In terms of education, majority of the members (81%) possessed a Primary School Leaving Certificate (PSLC), obtained after eight years of primary schooling. The main selection criteria for members were literacy (61%) and personal performance (16%). None of the members in both groups possessed a tertiary educational qualification in agriculture, business management or animal husbandry.  

The business characteristics of piggery groups are presented in Table 2 and 3.  

All groups distributed revenue generated from their piggery without a clear business objective of doing that. The study established that group based savings was the only source of business capital. Most piggery groups solicited contributions from individuals ranging from K2,000 to K4,000 per member per group (about US$13 to US$26). Most groups saved their money in the Malawi Savings Bank.

Furthermore, some groups multiplied their money by investing in buying and selling of tomatoes, beans and fish among others. Most groups indicated that it was difficult to raise capital. Business records indicated that fixed costs for pigs ranged from K60,000 to K160,000 per piggery business i.e. about (US $395 and US $1,053). On average, each sow was bought at a price of K13,000 (US $86). Each group had an average membership of 10. The average herd size was about 10. Each group had 2 sows. On average, groups took 2 years to raise capital and engage into piggery. In terms of production, the study revealed that groups produced a mixture of weaners and piglets as in Table 3.

The reason why new groups opted for piglets and not weaners for breeding stock was that piglets were considered cheaper as their price ranged from MK4,000 to MK6,000 (US$26 to US$39). Weaners and fully grown pigs were expensive to purchase as their price ranged from MK15,000 to MK20,000 (US$98 to US$131). With no reliable capital source, most groups and individuals opted for piglets.  

Generally, in terms of production output, the share of piglets was 44% while that of weaners and fully grown pigs were 42% and 14% respectively (Table 3). The study established that women groups produced most pigs (33% of total share of piglets, 27% of total share of weaners and the whole share of fully grown pigs). Mixed groups were second best as they produced 8% share of piglets and 11% of the share of weaners 

(ii)     Determination of demographic and socio-economic factors affecting gross piggery production output in Balaka District in Malawi 

Multiple linear regression model results 

Adjusted R² was calculated to be 0.86 which indicates that about 86 percent of the variation in the dependent variable, gross piggery production output, was explained by the independent variables in model. Table 4 has the detailed model results. 

Main factors affecting piggery business groups in Balaka  

As indicated in Table 4, the major socio-economic factors affecting group piggery businesses in Balaka are number of sows and group’s experience in running piggery business. The findings suggest that the groups with adequate experience in piggery business were most likely to achieve a higher gross piggery production output than the inexperienced ones. The coefficient indicates that ceteris paribus, an increase in group experience by one year can lead to an increase in the gross piggery production output by MK21,764.37 (US$ 143). Further, number of sows was most likely to determine gross piggery production output. An increase in the number of sows leads to increase in the gross piggery production output. The coefficient shows that an increase in the number of sows by one increases the gross piggery production output by MK17,592.66 (US$ 115). 

The model also indicated a negative relationship between the gross piggery production output and veterinary costs although the result is not statistically significant. Further, a positive but non-significant relationship was noted between the gross piggery production output and education level of piggery group head. Group experience and number of sows determined the performance of piggery business and its contribution to household income in Balaka district.           

Breakeven Analysis Results 

This analysis used data on revenue (sales), total fixed costs and total variable costs. It was done to determine the number of sows required for an average group in Balaka to recover total costs. Breakeven analysis is a financial variable that measures the amount of revenue that must be achieved to recover total costs of piggery production. The first step was the determination of revenue required to breakeven. In the case of group piggery business analysis, this was a revenue value, whose amount equated the total costs. The second step involved determination of the number of sows required to produce piggery products in order to breakeven. A model was constructed to determine a number of sows required to breakeven: This model is presented in equations 2: 

Using records on sales, total fixed costs and total variable costs a model was constructed: 

Therefore total sales required to break even:

Based on this breakeven concept, an average piggery business group needed to keep more than four sows to breakeven. This was fundamental for each group to produce profit. It can be deduced that in Balaka, number of sows, was an important variable which needed to be addressed right at the beginning of the project.  

Focus Group Discussion Results 

Results from the focus group discussions revealed that both piggery and control groups business shared similar characteristics in training, group formation processes, leadership and management structure, and production plans. The roles of group leaders and members were similar in all cases. It was also learnt that the training design was not learner centred and provided very little room for members to understand how their group business would apply new knowledge in their own business situations. Topics like heat detection, weaning, castration, and value chain analysis were not covered. Focus groups reported that training organizers promised them a follow up training which did not take place until SDIG project closure. 

Most groups indicated that their businesses were not doing very well due to lack of skills in piggery farming and entrepreneurship. This was evidenced by inconsistent pricing, lack of knowledge of market research and customer analysis, which was also an observation by (Ajala et al 2006) who attributed this to lack of experience in pig keeping and level of investment in piggery. Lack of adequate capital at business level affected group’s capacity to invest in efficient production technologies. This was another reason why production levels were very low. This was also noted by (Lapa et al 2006). Further, piggery groups had serious management problems as they were unable to manage production, marketing and business growth. These are considered essential elements which matter in pig farming as also confirmed by (Chabo 2000) and (Adesehinwa 2007). This resulted into low productivity of sows as they were often serviced by boars after heat period is over. Surprisingly, twelve groups did not articulate the meaning of their plans. They were unable to figure out aspects of market research conducted to develop their plan. Almost all business plans lacked time frame, cash flow projection and sources of capital.  It was also noted that most groups treated their business plan just as a future resource mobilization tool. Furthermore, there was a lack of business growth plan, and financial management procedures which confirmed lack of knowledge and experience in business.  

Most groups relied on the group leader to give them final decisions on most management and leadership aspect of their business just for the sake of his/her being a group leader. Surprisingly, group leaders were not aware of the entrepreneurship issues that could raise the profile of the group piggery businesses. It was also leant that the group chairperson was mostly in charge of control of external communication including arranging bookings with customers, training and visitors.  

Married women lamented that their husbands were not giving them enough money to capitalize their group business. Widows and young girls mentioned that their income base was very limited. And that it was very difficult to contribute effectively and consistently towards group capital. This also supported the fact that targeting of mostly women groups, whose source of income was unreliable, to pursue capital intensive businesses like piggery was not the best option without gender training of their husbands. This was aggravated by the fact that group leaders seemed to own piggery businesses more than the members such that they exerted more powers and influence than other members.

Conclusion

• Several factors affect piggery business output in Balaka. Of particular importance were group experience in piggery business, and number of sows kept by the group. The implication is that ceteris paribus, (i.e. assuming no depreciation and other exogenous factors are held constant), an average Balaka group piggery business needs more than four sows and a group experience of at least three years to make profit. Breakeven analysis and multiple linear regression results support each other on the need to increase number of sows to increase profitability of piggery business in Balaka in Malawi.

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Received 21 December 2011; Accepted 18 July 2012; Published 1 August 2012

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