P0360 Rural Survey June Embargo: 11:00 Date: 17 June 1999

Transcription

1 P0360 Rural Survey June 1999 Embargo: 11:00 Date: 17 June 1999

2 Rural survey, 1997 Data and metadata set The data and metadata set from the 1997 Rural survey is available on CD-ROM at the following prices: Africa Elsewhere Students R 400 R 800 Academic researchers R1 600 R3 200 Non-profit institutions R1 600 R3 200 Consultants and researchers for profit R3 200 R6 400 Institutions for profit R3 200 R6 400 For more details, and to place orders, contact Users Enquiries Statistics South Africa Private Bag X44 Pretoria 0001 South Africa Tel: (012) Fax: (012) info@statssa.pwv.gov.za CONTENTS Key findings Access to land, subsistence farming, important source of income, most needed assistance and employment creation Relationship between income generation and the size of land, farming reason, agriculture as a main source of income and the most needed assistance Households according to selected income-generating activities Income generated from sales of livestock by province Paid and unpaid farm workers who helped on the farm; by highest school class they completed, if they spent an hour or more on farm work most days, and the type of employment they had Unpaid family members and workers who were paid in kind Notes 1. Sample design 2. Weights Definitions of terms

3 Tables 1 Information on households 1.1 Dwellings Number of dwellings that households occupy by province Number of rooms in which households live by main type of dwelling 1.2 Services Households with electricity by province Access that households have to piped (tap) water, either inside the dwelling or on the property by province Distance of households from nearest source of water by province Sanitation facilities that households have by province 3. Income 1. Households income after tax in month prior to survey by province 2. Most important source of income in the past 12 months by households and province 2 Information on individuals 1. Population structure 1. Population by geographical location 2. Survey population by age: Total male and female/female/male Highest completed level of education of the population aged 20 years or more by province: Total male and female/female/male 2.2 Employment-unemployment 1. Occupational distribution of employed people by province: Total male and female/female/male 2. Unemployment rate among the economically active population by province: Total male and female/female/male 3. Unemployment among the economically active population by age group: Total male and female/female/male

4 3 Information on farming 3.1 Land 4. Persons that spent at least an hour per week on farming by age, sex and province: Total male and female/female/male 1. Access to land for farming purposes 2. Method of gaining access to land for farming purposes by province Households with some farming activities Access to land for animal grazing by province Type of land access by province Whether households have permission to occupy the land on which they live by province Whether households have been moved since 1913 by province 3.2 Activities and experience 8. Steps taken to reclaim the land by province 9. Size of arable land under cultivation by farming activity 10. Total size of arable land under cultivation or fallow Reasons for engaging in farming activities by province Type of training received by province Experience of crop failure on any of the land over the past year Main cause of crop failure by province 4 Farm processes and products 4.1 Livestock 4.2 Chickens 1. Households with some livestock (excluding chickens) by province 2. Type of animals that households own by province 3. Livestock slaughtering for own consumption over the past 12 months 4. Whether or not households sold livestock over the past 12 months by province 5. Gross income from sales of livestock over the past 12 months 1. Whether or not households had any chickens by province 2. Number of chickens by province

5 3. Selling of chickens by province 4. Revenue generated among those households that sold chickens in the past year by province 4.3 Animal products 1. Whether or not households engaged in farming activities produced animal products such as eggs, milk and wool by province 2. Animal products produced over the past 12 months by province 3. Quantity of milk produced over the last months by province 4. Quantity of eggs produced over the last 12 months by province 5. Households that sold eggs, milk and other animal products (such as hides, wool or silk) over the past 12 months Quantity of eggs and milk sold for all provinces over the last 12 months 4.4 Crops, vegetables, fruits and other Households that grow farm produce (such as maize, sorghum, etc.) by province 2. Type of farm produce grown over the past 12 months by province 3. Quantity in kilograms produced over the past 12 months of some selected products 4. Whether or not households sold fresh farm produce by province 5. Quantity of products sold of some selected products over the past 12 months 6. Gross income generated from the sale of selected products in the past 12 months 7. Aggregated gross income generated from the sale of products in the past 12 months 8. Most important customers (outlet sources) by province 9. Maintenance and operating costs (excluding fixed costs) for farming transport by province 5 Agricultural inputs and implements used 5.1 Inputs 5.2 Water 1. Use of agricultural inputs in the previous year by province 2. Gross expenditure on any kind of agricultural input by province 1. Whether or not the household has any source of water on the land on which crops, fruits and vegetables are grown 2. Main source of water on the farm for watering farm produce by province 3. Drying up of water source by province 4. Whether or not there is an irrigation system by provice 5. Source of water for watering farm produce for those who do not have a source in their land

6 5.3 Implements 1. Use of implement(s)/equipment (such as tractors, trailers and hand-held tools) for farming over the past year by province 2. Type of implement(s)/equipment used for farming in the past year by province 3. Ownership of implement(s)/equipment for all provinces 4. Cost of hired implement(s)/equipment for all provinces 6 Farming assistance, loans and operating costs 6.1 Employment on the land for farming activities 1. Assistance 1. Children and adults (both paid and unpaid) assisting in farming activities by sex for all provinces 2. Type of employees by households and province 3. Expenditure on food, clothing, housing and other goods for the people who helped with farming (excluding family members) 1. Type of assistance that farming households would need most by province 2. Whether or not households used ploughing services by province 3. Whether or not any contact had been made with an agricultural extension officerin the past year by province 4. Main type of advice received from an agricultural extension officer in the past 12 months by province 5. Usefulness of the advice received by province 6. Whether any support was received from sources outside of government (e.g. non-governmental organisations and farmers cooperatives) for the past 12 months by province 7. Type of advice received from organisations outside government (NGO and farmers cooperatives) by province 8. Helpfulness of advice received from organisations outside government (NGO and farmers cooperatives) by province 9. Whether an application had ever been made for a loan for farming purposes by province 2. Operating costs 1. Whether or not records of all farm related income and expenditure are kept by province 2. Record keepers on all income and expenditure for the past 12 months by province 3. Whether any money was spent on putting up any houses for workers, farm buildings, sheds, pigsties, fowl runs, etc. over the past 12 months by province 4. Operating and fixed costs by item of expenditure and provinces over the past 12

7 months 5. Operating and fixed costs by items of expenditure for all provinces Rural survey, 1997: KEY FINDINGS In June 1997 about 12.7 million people (31,4% of the population) lived in rural areas in the former homelands of South Africa. Access to farming land is very important for rural households. These households either depend entirely on farming activities for their survival and income generation, or depend on these activities to supplement other sources of income. The 1997 rural survey was designed to determine to what extent rural households in the former homelands had access to land and to income-generating activities. In addition the survey sought to obtain data on actual farming activities. The survey was the first of its kind undertaken by Statistics South Africa. The results of the survey indicate that access to land alone is not sufficient to ensure a proper livelihood. The size of arable land and the availability of assistance in agricultural activity also affect the ability to improve the land, produce more crops and increase income. Access to land, subsistence farming, important source of income, most needed assistance and employment creation As many as 71% of 2.4 million households (approximately 1.7 million) in the rural areas in former homelands had access to land for farming purposes. About (50% of the 1.7 million) households who had access to land reported that the farming land they used for crops in the past year was smaller than one hectare. The overwhelming majority of households (93%) were engaged in subsistence farming. Income-generating activities were insignificant. For instance, very little income was generated from the sale of a variety of crops, livestock and animal products. The study shows that the average income from livestock, chickens and maize per annum was R1 656, R235 and R203 respectively. Only a small proportion (3%) of the 2.4 million households in the sample relied on farming activities for their main source of income. Households received other income such as salaries and wages, mostly from members of the household. Approximately 71% of 1.7 million households who had access to land had some form of farm help with crop production or animal herding. The employment created in this way was for family members or else for payment in kind or land access rather than for cash payments. The relationship between income generation and the size of land; reasons for farming; agriculture as a main source of income and the most needed assistance. Only households of 1.7 million, (6%) who had access to farming land, actually sold crops including vegetables and fruit. a. Table 1 indicates the following:

8 Of the households who were generating an income by selling produce, 57% were earning R201 or more in the past year. As many as 34% of the households who sold produce, was farming on a piece of land less than a hectare in size. Of the households who were selling produce, only 6% had access to ten or more hectares of land. Access to water was the most needed assistance for a high proportion of all households. Of the households who were selling crops and needed assistance, slightly more than one out of three (35%) said that they needed access to water more than any other type of assistance.

9 Table 1: Description of those who sold produce Variable Income generated R 1 - R 50 R51 - R100 R101 - R200 R201+ Total N % 13,9 11,5 17,8 56,8 100 Size of land in hectares (ha) ha< ,7 1<= ha< ,9 2<= ha< ,0 ha> ,5 Total Reason for farming Subsistence ,4 Profit ,6 Other ,0 Total Agriculture main source of income Yes No ,7 Total Where assistance is most needed Training ,8 More land ,8 Finance ,9 Water ,5 Total

10 (b) Table 2 shows the following: Almost one out of every five (18% of ) households who were selling produce and farming on less than one hectare earned less than R50 in the past year. This could mean that the size of land used for crop growing is not sufficient to generate more income. In addition, these households could not rely on long fallow periods for sections of their land to maintain high fertility levels. As a result, the small piece of land becomes over-used after a period of time. The relationship between size of land and income generation was more significant as the size of the land increased above two hectares. A larger proportion of households with larger farming land had incomes in the highest income-generating category (R201+) in the past year. For instance, almost three out of every four households (73% of ) who had plots of land between two and just less than ten hectares earned in the highest income category. Of the households whose land size was ten hectares or more, 75% earned in the highest income category in the past year. This suggests that the more arable land the rural households have access to the more likely it is that they will produce and sell farm produce and thus generate more income. An annual income of R201 or more among such a small proportion of households (6% - see earlier bullets) suggests that rural households are generating very little income from selling crops. Among the households whose main source of income derives from some form of agricultural activity, 78% earned in the highest income category from selling crops in the past year. As would be expected, this suggests that productivity is higher for the rural farming households who depend on agriculture as a main source of income. Of the four types of assistance, namely, training, access to more land, access to more finance and access to water, the highest income group had a higher proportion of households who needed each of these. For example, among the households who said that they needed training more than any other type of assistance, 62% were in the highest income category. Table 2: Distribution of households who had access to farming land for crops and had generated income by selling crops in the past year by selected characteristics (a) Size of land in hectares (ha) R1 50 R R R201+ N %* %* %* %* Total %*

11 ha< <=ha< <=ha< ha> (b) Farming reason Subsistence Profit Other (c) Agriculture - main source of income Yes No (d) Assistance needed most Training More land Finance Water *The unspecified category was excluded when calculating these percentages Households according to selected income-generating activities

12 The characteristics mentioned are just a few of a whole spectrum of characteristics that affect production in farming, and hence affect income generation. The following finding highlights the extent of subsistence farming compared to income generating farming: Of the households who had livestock, 18% were selling livestock. Of the households who had chickens, only 8% were selling them. Nearly 1.2 million households were growing produce including maize but only 3% were selling maize. Among those who were farming for commercial purposes, earning an income from sales of livestock was more common in Free State and generating income from maize was more common in Eastern Cape. (See Figure 1) Source: Rural survey, 1997

13 Figure 1: Households according to income generating activity in the past year Income generated from sales of livestock by province Taking the sale of livestock as an example, Figure 2 shows that, in the past year, of the six provinces with homelands, Northern Province was least likely to generate an income from sales of livestock while Free State was the most likely province. Even though KwaZulu-Natal had the lowest number of households selling livestock in Figure 1, on closer inspection, Figure 2 indicates that 66% of households, who were selling livestock in KwaZulu-Natal, earned more than R1 000 in the past year. On the other hand, only 37% of households who were selling livestock in Northern Province earned more than R Source: Rural survey, 1997 Figure 2: Income in the past year from sales of livestock by province Paid and unpaid farm workers who helped in the farm by highest school class they completed, if they spent an hour or more on farm work most days and the type of employment they had Table 3 shows the percentage of households who did not have any assistance with farming from family members and employees and those who did have help in farming by type of assistance and whether or not they used employees.

14 Table 3: Households with and without farming assistance in the past year, by province E. Cape Free State KwaZulu- Natal Mpumalanga North West Northern Province Total % % % % % % % No help Unpaid family members Payments in kind Compensation by living and growing produce on a portion of land Regular paid workers Casual paid workers ** Percentages may sum to more than 100% as some households hired more than one type of employee Slightly more than a half (53%) of 1.7 million households received farming help from unpaid family members while 35% of these households did not receive any help at all. KwaZulu-Natal had a high proportion (64%) of households who used unpaid family members as farm help.

15 Of the households who were paying their farm assistants, almost one out of ten (10%) paid them in kind. Eastern Cape households in particular had a higher proportion (22%) of households that paid farm assistants in kind. The proportion of households who had regularly or casually paid employees, and those who compensated employees by giving them access to a portion of land were a small proportion, especially in Eastern Cape (3%), compared to 8% for South Africa as a whole. Unpaid family members and workers who were paid in kind The adult population of the rural areas was overwhelmingly female. Considering the legacy of male migrant labour from these areas, this is not surprising. There were female adult employees compared to male adult employees who were helping in farm work. Figure 3 indicates that more unpaid adult females were assisting in farming activities compared to their male counterparts. This was also true for female children compared to male children. But for paid categories, for example, those that were paid in kind, the reverse was true. The paid workers used by farming households were mainly males, irrespective of their age. The figure also shows that child labour is more prevalent than adult labour. Source: Rural survey, 1997 Figure 3 Adults and children assisting in farming activities by whether they were unpaid or paid in kind NOTES Very little is known about earning a living in rural households in South Africa. The 1997 rural survey is a Stats SA project which is a first of its kind. It aims to describe the rural economy and farming activities by which rural households earn a living which are not covered by the Stats SA s current OHS series. The

16 information obtained in the survey is of great importance for planning purposes in the country, especially the rural areas. For the purpose of this survey, the definition of employed population is as follows i. persons who did any formal work, e.g. for salary, wage, etc. ii. persons who did any informal work, e.g. making things for sale, rendering service, etc. iii. persons who worked on a farm or on the land, whether for a wage or as part of the household s farming activities. Farming has seasonal peaks of activity, e.g. during maize harvest time, resulting in increased employment opportunities. As this survey was conducted in June, when employment was high, the unemployment rate could be higher in some cases than reflected in the results. This is particularly true for provinces that have larger numbers of households that produce and sell maize, e.g. in Eastern Cape, KwaZulu-Natal and Northern Province (see Figure 1 above). When comparing these results with those of other surveys this comment should therefor be carefully considered. 1. Sample design The database that was established during the 1996 census constituted the sampling frame for selecting EAs for the 1997 rural survey but it was restricted to the former homeland areas, i.e. Transkei, Bophuthatswana, Venda, and Ciskei (TBVC states); KaNgwane, KwaNdebele, KwaZulu, Gazankulu, Qwaqwa and Lebowa (self governing territories). A total of 600 enumeration areas (EAs) were drawn and 10 households were selected from each EA, yielding a sample of about households. Sample selection was carried out independently in each stratum applying a two stage sampling procedure; a systematic sample of EAs followed by a systematic sample of households. A power allocation scheme with 0.25 as the power was used to allocate the sample to each stratum. Former homelands in six provinces were regarded as natural occurring strata and as a result Western Cape, Northern Cape and Gauteng were not part of the strata of interest. Since the sample design was not necessarily a self-weighting design, weights had to be used. 2. Weights Two types of weights were calculated, namely, person weights and household weights. Household weights were calculated by using the reciprocal of the product of an EA inclusion probability and a household inclusion probability. Relative scaling was done on the household weight due to the changes in the EA sizes from the initial database which was used for drawing of the sample to the Final Census database which was used for weighting. Relative scaling was also used to take into account the growth rate of the population, from 1996 to Person weights were calculated by first post-stratifying the data by province (former homeland in a province) gender and 5 year age groups. The 1996 Census population figures were used as benchmarks for the post stratum. Since the target areas were former homelands, which are largely African populated, population group was implicitly taken into consideration in the benchmarks. DEFINITIONS OF TERMS A household consists of a single person or a group of persons who:

17 i. eat together and who share resources; and ii. normally resides at least four nights a week at the specific visiting point. For the purpose of this survey, a live-in domestic worker is considered to belong to a separate household. A visiting point is a physical address or a dwelling. For the purpose of this survey, employed population includes: i. persons who did any formal work, e.g. for salary, wage, etc. ii. persons who did any informal work, e.g. making things for sale, rendering service, etc. iii. persons who worked on a farm or on the land, whether for a wage or as part of the household s farming activities. The economically active population consists of both those who are employed and those who are unemployed. The official unemployment rate includes all those who are unemployed, who are available for work, and who would accept a job within a week after the interview. But it also includes those who have not looked for a job in the four weeks prior to the interview. An urban area is one which has been legally proclaimed as being urban. Urban areas include towns, cities and metropolitan areas. For the purpose of this survey, a farmer refers to a person who operates a farming unit for his/her account. The term farmer also refers to a manager, foreman or other person to whom the control of the farming unit was entrusted. A participating member of a cooperative or any other business concern actively engaged in farming is also regarded as a farmer. Livestock are animals that are regarded as an asset to the farmer; i.e. the animals are of value to the farmer, either in terms of monetary value or subsistence value or status, as is the case in many traditional cultures. Workers include the self-employed, employers and employees. Extension officer is a person trained in agriculture and employed by the Department of Agriculture or any other body responsible for rendering assistance to farmers to promote good farming practices.

18 1. Information on households 1.1. Dwellings Number of dwellings that households occupy by province, among all households in the survey Dwellings Total E. Cape Free State KZN Mpumalanga North West N. Province Shared dwelling One dwelling Two dwellings Three dwellings Four dwellings More than four dwellings Total

19 1. Information on households 1.1. Dwellings Number of rooms in which households live by main type of dwelling, among all households in the survey Size of the dwelling Total Houses or other brick structure Traditional dwelling/hut Shack Other N % N % N % N % N % 1-3 rooms rooms rooms Total

20 1. Information on households 1.1. Dwellings Households with electricity by province, among all households in the survey Electricity Total E. Cape Free State KZN Mpumalanga North West N. Province Yes No Total

21 1. Information on households 1.2. Services Access that households have to piped (tap) water, either inside the dwelling or else on the property by province, among all households in the survey Acces to piped (tap) water Total E. Cape Free State KZN Mpumalanga North West N. Province Yes No Total

22 1. Information on households 1.2. Services Distance of households from nearest source of water by province, among all households in the survey Distance Total E. Cape Free State KZN Mpumalanga North West N. Province Inside dwelling/on property Less than 100m m - less than 200m m - less than 500m m - less than 1 km km or more Total

23 1. Information on households 1.2. Services Sanitation facilities that households have by province, among all households in the survey Sanitation facility Total E. Cape Free State KZN Mpumalanga North West N. Province Flush toilet inside the dwelling Flush toilet outside the dwelling Pit latrine Bucket toilet No facility Unspecified Total

24 1. Information on households 1.2. Services Household income after tax in month prior to survey by province, among all households in the survey Net income Total E. Cape Free State KZN Mpumalanga North West N. Province None R R R R R R R R Unspecified Total

25 1. Information on households 1.2. Services Most important source of income in the past 12 months by household and province, among all households in the survey Source of income Total E. Cape Free State KZN Mpumalanga North West N. Province Salaries and wages from member/s of this household who actually live here Pension (e.g. state pension, private pension, disability grants, maintenance grants) Remittances/allowances received from family members living elsewhere Farming activities Other sources Unspecifed Total

26 2. Information on individuals 2.1. Population structure Population by geographical location, sex and province Province Total Rural area/farm former homeland area Semi-rural/denser settlement Semi-urban/small town Total Female Male Total Female Male Total Female Male Total Female Male Eastern Cape Free State KwaZulu-Natal Mpumalanga North West Northern Province Total

27 2. Information on individuals 2.1. Population structure Survey population by age Total male and female Age Total E. Cape Free State KZN Mpumalanga North West N. Province Total

28 2. Information on individuals 2.1. Population structure Survey population by age Female Age Total E. Cape Free State KZN Mpumalanga North West N. Province Total

29 2. Information on individuals 2.1. Population structure Survey population by age Male Age Total E. Cape Free State KZN Mpumalanga North West N. Province Total

30 2. Information on individuals 2.1. Population structure Highest completed level of education of the population aged 20 years or more by province Total male and female Level of education Total E. Cape Free State KZN Mpumalanga North West N. Province None Grade Grade Grade Grade Grade Grade Grade Grade Grade Grade Grade Grade Grade Certificate Diploma Bachelor's Degree Other Unspecified Total

31 2. Information on individuals 2.1. Population structure Highest completed level of education of the population aged 20 years or more by province Female Level of education Total E. Cape Free State KZN Mpumalanga North West N. Province None Grade Grade Grade Grade Grade Grade Grade Grade Grade Grade Grade Grade Grade Certificate Diploma Bachelor's Degree Other Unspecified Total

32 2. Information on individuals 2.1. Population structure Highest completed level of education of the population aged 20 years or more by province Male Level of education Total E. Cape Free State KZN Mpumalanga North West N. Province None Grade Grade Grade Grade Grade Grade Grade Grade Grade Grade Grade Grade Grade Certificate Diploma Bachelor's Degree Other Unspecified Total

33 2. Information on individuals 2.2. Employment-unemployment Occupational distribution of employed people by province Total male and female Occupation Total E. Cape Free State KZN Mpumalanga North West N. Province Legislators, senior officials, managers Professionals Technicians and associate professionals Clerks Service workers and shop and market sales workers Skilled agricultural and fishery workers Craft and related trade workers Plant and machine operators and assemblers Elementary occupations Occupation not elsewhere classified Unspecified Total Due to rounding, numbers do not necessarily add up to the totals

34 2. Information on individuals 2.2. Employment-unemployement Occupational distribution of employed people by province Female Occupation Total E. Cape Free State KZN Mpumalanga North West N. Province Legislators, senior officials, managers Professionals Technicians and associate professionals Clerks Service workers and shop and market sales workers Skilled agricultural and fishery workers Craft and related trade workers Plant and machine operators and assemblers Elementary occupations Occupation not elsewhere classified Unspecified Total Due to rounding, numbers do not necessarily add up to the totals

35 2. Information on individuals 2.2. Employment-unemployment Occupational distribution of employed people by province Male Occupation Total E. Cape Free State KZN Mpumalanga North West N. Province Legislators, senior officials, managers Professionals Technicians and associate professionals Clerks Service workers and shop and market sales workers Skilled agricultural and fishery workers Craft and related trade workers Plant and machine operators and assemblers Elementary occupations Occupation not elsewhere classified Unspecified Total Due to rounding, numbers do not necessarily add up to the totals

36 2. Information on individuals 2.2. Employment-unemployment Unemployment rate among the economically active population by province Total male and female Unemployment rate Total E. Cape Free State KZN Mpumalanga North West N. Province N N N N N N N Number of unemployed Number of employed Total Rate Female Unemployment rate Total E. Cape Free State KZN Mpumalanga North West N. Province N N N N N N N Number of unemployed Number of employed Total Rate Male Unemployment rate Total E. Cape Free State KZN Mpumalanga North West N. Province N N N N N N N Number of unemployed Number of employed Total Rate

37 2. Information on individuals 2.2. Employment-unemployment Unemployment among the economically active population by age group Total male and female Age Total E. Cape Free State KZN Mpumalanga North West N. Province Total

38 2. Information on individuals 2.2. Employment-unemployment Unemployment among the economically active population by age group Female Age Total E. Cape Free State KZN Mpumalanga North West N. Province Total