Factors influencing farm income in livestock producing communities of North-West Province, South Africa

L K Mabe, M A Antwi and O I Oladele

Department of Agricultural Economics and Extension, North-West University,
Mafikeng Campus, Mmabatho 2735, PX 2046,South Africa
oladele20002001@yahoo.com

Abstract

Regression analysis was used to establish the factors influencing farm income in livestock producing communities of North-West Province, South Africa. A multistage sampling technique was used to select regions, districts, villages and 120 farmers from the community. Data were collected using a structured questionnaire and analyzed using frequency distribution and regression analysis.

The results show that majority of livestock farmers were above 50 years of age, married, without formal education (54.7%). Men kept a higher number of cattle (65.2%) compared to women (38%), while women kept more poultry than men, thus  men having more income than women livestock enterprises. Extension agents were the main  source of information to livestock farmers  Significant determinants of farm income were age (t = -2.18), gender (t = 2.19), marital status (t = 1.17), educational level  (t = 1.89), number of chicken (t = 1.78) and number of cattle (t = 4.95).

Key words: access to input, livestock based incomes, rural communities, socio-economic characteristics

Introduction

The role and contributions of agriculture in South Africa’s economy is highly significant (Bembrigde 1988). Over 50% of total land in South Africa is used for agriculture and forestry, which contributes 5% of the Gross Domestic Product (GDP) and over 13% to employment in South Africa (Statistics South Africa 1996). Poverty in rural areas is associated with agricultural policies the persistency of which marginalizes small‑scale farmers as their access to production resources such as land, credit and technical know‑how (FAO 1993).  

Livestock is an important and integral component of farming systems and contributes greatly to agricultural and rural development in South Africa (Bembrigde 1988).  Livestock is an important and integral component of farming systems. In nomadic and semi-nomadic societies, livestock rearing is the main production activity and the source of most, if not all, economic output. Livestock also contributes a large proportion of the income of farmers with the small-landholdings, which are by far the most common type of farms in the African continent. The recognition of the role-played by communities is fundamental to rural development. Communities work in animal husbandry is significant and in general, women are more involved livestock production, especially small ruminants. They tend to be heavily involved in all aspects of livestock production, with the exception of herding and marketing, which require absence from home, they also perform duties such as fodder gathering, collecting dung for fertilizer and fuel, cleaning stalls and milking in large animal systems (Oladele and Monkhei 2008).

In countries where pastoral communities rely predominantly on livestock as their main economic activity, they contribute substantially to livelihoods . Pastoral responsibilities are mainly centred on milking and watering, as well as in transforming wool and hide onto clothes, rugs and tents. It is worth mentioning that the role in pastoral societies is becoming increasingly difficult in light of rapid declining pasture. Sub-Saharan and Near Eastern, women play a major role in household animal production enterprises. They tend to have the primary responsibility for the husbandry of small animals and ruminants and perform duties such as herding, providing water and feed, cleaning stalls and milking in large animal systems. In all types of animal production systems, women have a predominant role in processing, and marketing of milk and milk products (Gladwin 1991). Perhaps the only enterprise that is entirely a woman’s domain is poultry raising.

The Northwest Province contributes nearly 33% of South Africa’s maize and large quantities of wheat, sunflower and other agricultural products. The province is also prominent in livestock production such as sheep, goat, cattle, poultry and pigs. The main objective of this study was to determine factors influencing farm income in livestock producing communities of North-West Province, South Africa. Specifically, the demographic characteristics were identified, access to production resources ascertained and farm income estimated. Agriculture plays an important economic role in the province with approximately 60% to rural livelihood. Crop and livestock production are practiced and contribute substantially to the provinces economic growth, with 80% of the labour force substantially being women. Livestock is the largest farming activity in the Bophirima, Central and Bojanala Platinum districts. The dominance and locality of agricultural activities within these regions were the guiding force for the selection of the study area. The study was conducted in the Bojanala Platinum, Bophirima, and Central regions of the Northwest Province. A district was identified from each region, and within that district a village was selected.

Methodology 

The study was conducted in North-West Province of South Africa that is the sixth largest Province in the Republic of South Africa. It has a total land area of 116 320 (119855.3) square kilometres. The Province is divided into five municipal districts namely Central, Bojanala Platinum, Bophirima, Kgalagadi and Southern districts. Nationally the province is bordering Northern Cape, Free State, Gauteng and Limpopo Province). Internationally within the SADC countries, is bordering the Republic of Botswana in the west. The province lies between 22 and 28 degrees longitude East of the Greenwich Meridian and between 25 and 28 degrees Latitudes South of the Equator (Cowley 1985).

Agriculture plays an important economic role in the province with approximately 60% to rural livelihood. Crop and livestock production are practiced and contribute substantially to the provinces economic growth, with 80% of the labour force substantially being women. Livestock is the largest farming activity in the Bophirima, Central and Bojanala Platinum districts. The dominance and locality of agricultural activities within these regions were the guiding force for the selection of the study area. The study was conducted in the Bojanala Platinum, Bophirima, and Central regions of the Northwest Province. A district was identified from each region, and within that district a village was selected.

A multistage sampling technique was used to select farmers for the study. From the 5 regions in the province 3 were randomly selected. This was followed by the selection of 3 districts from the selected regions and from each of the selected districts, a village was selected. Forty farmers were randomly selected from each village to give a sample size of 120 respondents. Data were collected with a structured questionnaire, which was developed based on the study objectives and review of literature. The questionnaire consisted of demographic, access to production resources and farm income sections. Data were analyzed with Statistical Packages for the Social Sciences (SPSS) version 15.0 using frequency distribution and regression analysis. The model use was depicted as:

Y = a + b₁x₁ + b₂x₂ + b₃x₃ + b₄x₄ + b₅x₅ + b₆x₆ + b₇x₇ + b₈x₈ + e

where:

Y = Amount from livestock enterprises measured in Rands,

a  =  the intercept,

b₁-b_{8  =}  regression coefficients and
e = error.        

Results and discussions 

Demographic characteristics

The findings of the study show that the age of farmers ranged from 29 to 94 years with a mean of 57 years. Figure 1 shows that while many men were between 41 to 50 years, majority of the women were between 51 and 60 years. According to Bembridge (1987) an individual’s age is one of the most important factors pertaining to his personality, because his needs, behaviour and thinking are closely related to the number of years of existence. Chronological age may have impeding efforts on physical abilities, which is important to family members.

The study reveals that a large percentage of women farmers were married (32%). This may be attributed to the facts that through marriage farmers gain access to family labour. According to Bembridge (1988) education is regarded as a basic human need, essential for meeting other basic needs and acceleration of overall development through training skilled workers and enable farmers to make fruitful use of existing resources and accurate assessment of new ones.

The Land Bank of South Africa (2000) states that farmers who have passed standard five are regarded as literate enough to make decisions about production and the requirement of agriculture. This is contrary to the findings of the present study, as presented in Table 1 below which shows that in general 56% of respondents did not attend school, whereas 78% of respondents had access to education with a pass in grade 4 (46%) women and men (32.2%). Rural-urban migration may have a significant impact on the engagement on farming incomes.

Table 2 shows that most of the respondents owned livestock. Men dominated ownership of cattle, goats, and poultry enterprises in the study area.

Whilst the study showed higher number of cattle (65.2%) than women (38%), however on average women had larger herds of 16 as compared to men with herds of 11. Although more men participated in the poultry enterprise, on average women had larger number of 43, than men for 37. On the contrary, more women participated in sheep and pigs enterprises but on average men had larger numbers of 24 and 2 pigs respectively, as compared to the average number of 8 and 1 for women. Gladwin (1997) states that women tend to have a primary responsibility for the husbandry of small-animals and ruminants, and take duties such as herding, providing water and feed.

Table 3 shows income derived from livestock by male and female farmers.

The Table states that the highest income was derived from cattle. This was followed by sheep for both men and women. The mean income from livestock enterprises was R1,867.60 and R639.60 for men and women respectively. The income represents the major source of their livelihoods and they strive to sustain it.

Table 4 presents the findings regarding the frequency of extension contact to respondents, especially women farmers from the field extension staff.

It indicates that field extension agents visited a large percentage of women farmers (49%) in the study area. Furthermore, the findings also reveal that extension agents visited nearly 23% of women farmers on occasional basis. This may be due to the fact  that, where a larger number of women farmers had been contacted by extension agents, official communicated to the extension service to the field agents to target women in their regular extension programme, both separately and together with male contact farmers. Moreover, an existing extension strategy to work with women farmers could have caused an increase in the number of women contacted regularly for agricultural advice. Conversely, the women may be more keen/diligent in using extension advise

Respondents from the study area had various sources of information through which they received advice on agricultural matters. The majority (87%), of who were women rated extension workers as their primary sources of advice as compared to (83%) male farmers. A very negligible percentage of women farmers considered extension agents as a source of advice for solving farming problems. Most male farmers (13.5%) received their advice on agricultural matters by attending farmer’s days where possible as compared to (11%) women farmers. Furthermore most male farmers had access to information technology such as computers and were able to use them.

The results of the regression analysis in Table 5 show that there is a strong correlation between farm income and socio-economic and access to input variables.

The adjusted R² was 97.1 meaning that only 97.1% of the changes that occurred in the total revenue of farmers were explained by the selected independent variables.  Table 5 shows that 5 out of 8 independent variables in the regression equation were significant. These are age (t = -2.18), gender (t = 2.19),  marital status (t = 1.17), educational level (t = 1.89), number of chicken (t = 1.78).

The number of cattle had a highly significant impact on the total revenue of farmers (t = 4.95). The implications of this was that a unit increase in number of cattle leads to 74.3% an increase in the total farm revenue of farmers of all other things held constant. This is followed by gender and age. It can be deduced that the more the number of female farmers involved in livestock enterprises, the higher the educational level, the more the number off chicken and cattle kept, the higher the farm income. However there is an inverse relationship between age and farm income which implies that the older the farmers age, the lower the farm income. This may be due to the fact that age affects decision innovation decision making, as young farmers adopt innovation than old farmers, also, the  older farmers may be  more risk averse compared to the young. Priorities may also change. Older people keep livestock to occupy their time rather than strictly to gain incomes. This confirms Bembridge (1991) report that education accelerates the overall development of workers and production. Therefore, the above regression implies that women would receive more income that the men.

Conclusion  

This study has clearly shown that:

•  Men kept a higher number of cattle than women while women kept more poultry than men

  
  

• Men had more income than women from livestock enterprises  

  
  

• Farmers had contact frequently with extension agents as  the most prominent source of information to livestock farmers  

  
  

• Significant determinants of farm income were   age, gender, marital status, educational level, number of chicken, and number of cattle.

References 

Bembrigde TJ 1988 Agricultural development problems in three rural areas of Ciskei, 1987, Development Southern Africa 5 (1): 124 - 126

Bembridge TJ, 1991 The Practice of Agricultural Extension, A Training Manual, Development Bank of South Africa, Halfway house. Development Southern Africa 8 (2): 289 - 290

Crowley E 1999 Women’s right to land and natural resources: Some implications for a human rights based approach, Food and Agriculture Organisation Rome pp 10-30 http://www.fao.org/sd/LTdirect/LTan0025.htm

FAO 1993 Agricultural Extension and Farm in the 1980’s, Food and Agriculture Organisation Rome pp15-25.

FAO 1995 The population parameters of rural development, Food and Agriculture Organisation, Rome. pp 40-55 http://www.fao.org/docrep/x0252e/x0252e01.htm#P31_2974

Gladwin CH 1991 Structural Adjustments and African Women Farmers, University of Florida Press, Florida, USA pp 25-35 http://www.questia.com/PM.qst?a=o&d=42418196

Land Bank South Africa 2000 Agriculture in South Africa http://old.southafrica.co.za/agriculture_29.html. Accessed January 2010

Oladele O I and Monkhei M 2008: Gender ownership patterns of livestock in Botswana. Volume 20, Article #156. http://www.lrrd.org/lrrd20/10/olad20156.htm

Statistics South Africa 1996 Census  Data: Provincial level: Households     http://www.statssa.gov.za/census01/Census96/HTML/default.htm  Accessed January 2010

Received 18 May 2010; Accepted 12 June 2010; Published 1 August 2010

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