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PROFILES OF MEN AND WOMEN SMALLHOLDER FARMERS
IN THE LILONGWE RURAL DEVELOPMENT PROJECT,
MALAWI
DR. ANITA SPRING
UNIVERSITY OF FLORIDA
MARCH 1984
FINAL REPORT OF THE WOMEN IN AGRICULTURAL DEVELOPMENT PROJECT
IN MALAWI. SUBMITTED TO THE OFFICE OF WOMEN IN DEVELOPMENT
SAID, WASHINGTON DC. CONTRACT NO. AID-OIR 0300-C-2081
TABLE OF CONTENTS
Pages
Acknowledgments ..................................................
Abbreviations and Acronyms ............ ........................ii
CHAPTER 1 THE WOMEN AND AGRICULTURAL DEVELOPMENT PROJECT
AND DISAGGREGATION CF DATA BY SEX....................1
Introduction ............................ ..................... .
Malawi's National Rural Development Program...................2
The Women in Agricultural Development Project....................5
Involvement of WIADP in Disaggregating NSSA Data...............8
Involvement of WIADP in LADD................................... 13
Lilongwe Rural Development Project.............................14
The LRDP Survey .............................................. 18
Previous LRDP Studies and Findings.................... 18
Indicators for the LRDP Survey.......... .................21
CHAPTER 2 THE NATIONAL SAMPLE SURVEY OF AGRICULTURE ..........25
Description of the NSSA........................................ 25
Survey Instruments.... ........................... .... ........25
Sample............. ...... ..... ... ........ ... 26
Administration -...... ....................................27
WIADP's Analysis of LRDP NSSA Materials........................28
Results of the NSSA............................................29
Household Composition Survey .......................... ...29
Resources Survey......................................... 32
Extension Survey..........................................34
Garden Survey ... .......... .... .................... ..... 40
Yield Survey.............................................45
CHAPTER 3 THE LILONGWE RURAL DEVELOPMENT PROJECT SURVEY.;.....57
Description of the Survey. ............................. .... ...57
The Survey Instruments.. .................... ..............57
The Sample..............................................58
Personnel and Design.....................*.. *...*....*..59
Analysis of the Data .......... ....................... 60
Demographic and Social Indicators.... ...... .... ................61
Household Composition..... .. ..... .... ... .. .... ... .*61
Migration and Residence ................ .......... .....** **.62
Natality History............ ... .. ..*o** ...* **oo- .. 65
Education. ..... ..... .. .... ...... .... .. .... *****65
Status Positions ....................... ......*.** .*** **.. 68
Resources and Access to Infrastructure....................70
Distances ...... ...... .. .. .. .. .... .. .******...... 74
Extension Services ...,................. ....... .... ....... 74
Garden and Cropping Patterns.................. ... .. .... **..76
Garden Inventory and Land Tenure........... ....... .......76
Crops Grown................... *... ............. .. .79
Maize Production and Inputs............. .......... ....... 84
Farm and Off-farm Income..... .... ................. .... .... 89
Perceived Changes During the Past De.cade................. .....94
Farm Planning and Maize Knowledge.............................96
CHAPTER 4 COMPARISONS AND IMPLICATIONS ...................... 111
Comparison of the NSSA and the LRDP Survey....................111
Household Composition Survey...................... ...... 113
Garden Survey. ...... ........ .. .. .. .. ... ..... .... 117
Profiles of Male and Female Smallholders in LRDP............121
Implications of this Report for LRDP....... .................125
Sex of Household Head ........... ......... .... ..... ..... .125
Cropping System.... ........... ...........** ...... : .126
Extension Services.... ........... .. .... ....... ............ 127
Interpretation of Sex-Disaggregated Survey Data.......... 128
Implications for Other WID Projects ........... .. ......... ... 129
Appendix A List of WIADP's Reports........................132
Appendix B Sex disaggragated reporting formats for LADD.....135
Bibliography ..... ........ ..... ...... .... ... ...... *..... 140
WOMEN IN AGRICULTURAL DEVELOPMENT PROJECT IN MALAWI
USAID/WID
Reports
1. Dr. A. Spring
2. Dr. A. Spring
3. Dr. A. Spring
4. Dr. A. Spring
5. Dr. A. Spring
6. Dr..A. Spring
7. Miss F. Kayuni
8. Dr. A. Spring
9. Mr. C. Smith
10. Miss F. Kayuni
-Farm Home Assistants and Agricultural Training.
September, 1981 (9 pages)
-NSSA Series: KRADD A Preliminary Analysis of 3 Surveys
in terms of Male and Female Household Heads, October
1981 (10 pages)
-Soyabean Production in Unit 2. December, 1981 (6 page,'
-Stall-feeding in LRDP.
January, 1982 (8 pages)
-Adapting CIMMYT Farming Systems Survey Guidelines to ti..
Malawian Situation. February, 1982 (4 pages)
-Background data on Women and Men Farmers in Kawinga and
Lake Chilwa, Liwonde Agricultural Development Division
March, 1982 (5 pages)
-Agricultural Refresher Course for LADD Female Extension
Workers. April, 1982 (5 pages)
-Women in Agricultural Production in Malawi.
Extension Workers. April, 1982 (5 pages)
Address to
-Report on Unit 2 Soyabean Trials. April, 1982 (3 pages:
-Female Extension Workers and Agriculture: Training for
Women, Address to Extension Workers. April, 1982 (3
pages)
11. Mr. C. Smith
12. Dr. A. Spring
13. Dr. A. Spring
Miss F. Kayuni
Mr. C. Smith
14. Mr. C. Smith
-Agronomic Report on Unit 2 Soyabean Trials.
(7 pages)
May, 1982
-Report on Soyabean Farmers in the Thiwi-Lifidzi Project
Area. June, 1982 (4 pages)
-Karonga Farmer Survey. June, 1982 (28 pages)
-NSSA Series: Comparisons between Female and Male-headed
Households From the NSSA 1980-81 Garden Survey of LRDP,
Malawi. October, 1982 (4 pages)
15. Dr. A. Spring
16. Mr. C. Smith
-Farmer Survey in Karonga:
in Agriculture. October,
-NSSA Series:
Yield Survey
Households.
Considering the Role of Women
1982 (6 pages)
An Analysis of the Yields from the NSSA
of LRDP in terms'of Male and Female-Headed
December, 1982 (13 pages)
17. Miss K. Utterback
18. Dr. A. Spring
19. Dr. A. Spring
-Appropriate Technology: Women's
Operated Chitedze Maize Sheller.
Responses to the Hand
(8 pages)
-Women in Agricultural Development: Project Description.
January, 1982 (9 pages)
-Studies of Agricultural Constraints Facing Women Farmers
in Phalombe RDP. April, 1983 (19 pages)
20. Mr. C. Smith
-WIADP Soyabean
project. May,
Programme in the Lilongwe Rural Development
1983 (11 pages)
Proceedings/Final Reports
1. Dr. A. Spring
(editor & compiler)
2. Dr. A. Spring
Mr. C. Smith*
Miss F. Kayuni
3. Dr. A. Spring
-Proceedings of the National Workshop on Women in
Agricultural-TeveeTopment, March 9-10, T9.82. Com-piled
and edited by Dr. A. Spring, September, 1982 (76 pages)
-Women Farmers in Malawi: Their Contributions to
Agriculture anT-Participation.n Development Projects.
Report submitted to the Ministry of Agriculture and
USAID/WID, April, 1983 (193 pages)
-Priorities for Women's Programmes.
to the Ministry of Agriculture and
(92 pages)
Report submitted
USAID/WID, April,
4. Dr. A. Spring
-Profiles of Men and Women Smallholder Farmers in the
Lilongwe R-uraDevelopment Project in Malawi. Final-
Report Submied to USAID/WID, i~arc'k/g-T/haye
Extension Aids Circular
"Reaching Female Farmers Through the Male Extension Staff." (prepared by Dr.
Spring in conjunction with Extension Aids Staff). Printed by Extension Aids,
Ministry of Agriculture, and circulated to all extension personnel. August,
A.
1983.
Evaluation of Women's Programmes
Reports on the Evaluation of Women's Programmes for Ministry of Agriculture:
Agricultural Development Divisions (ADD) and Training Institutes Dr. A. Spring
Mr. C. Smith and Miss F. Kayuni.
1. An Evaluation of Women's Programmes in Salima ADD: How SLADD Sections and
Projects can incorporate More Women Farmers in their Programmes. January,
1983 (15 pages)
2. Kasungu ADD. February, 1983 (15 pages)
3-. Blantyre ADD. February, 1983 (15 pages)
4. Ngabu ADD.
June, 1983 (12 pages)
5. Liwonde ADD. May, 1983 (11 pages)
6. Lilongwe ADD. April, 1983 (30 pages)
7. Karonga ADD. July, 1983 (19 pages)
8. Mzuzu ADD. July, 1983 (21 pages)
9. Thuchila Farm Institute/National Resources College and the Training of
Female Extension Workers. March, 1983 (4 pages)
10. Malawi Young Pioneers: Report on Agricultural Training. March, 1983 (8 page:
Miscellaneous Handouts
1. Recommendations for Growing Soyabeans (English and Chichewa Versions) Novembr
1981
2. Syllabus for Teaching Soyabean Agronomy and Recipes to Farmers, Dr. A. Spring id
Training Section, LADD. March, 1982 (7 pages)
3. Tables Analyzing the Breakdown of Classroom Hours of Agriculture and Home
Economics Courses in the Syllabus for Farmers Training at Day Training Centres,
Residential Training Centres and Farm Institutes prepared7 Mr. C.R. Smith)-
November, 1982 (7 pages)
4. Tables from "The Work Done by Rural Women in Malawi", by B. Clark (6 pages)
5. Summary of Women and Handicrafts: Myth and Reality by J. Dhamija (adapted
by Dr. A. Spring) (5 pages)
6. Tables on Male and Female Labour Allocation in LRDP extracted from J. Kydd
"Farm Management Report No. 1, Labour Allocation and Crop Labour Requirements"
LRDP, 1978.
7. Annual Work Plans (prepared by Dr. A. Spring, December, 1982)
a) Format
b) Recommendations and strategies for increasing women's participation
in credit programmes
c) Recommendations and Strategies for introducing the Chitedze Maize
Sheller to women farmers
Monthly Reports
December, 1981 April, 1983
For information concerning these materials please contact:
Dr. Anita Spring '< ~', ,," .
1350 GPA /r ,' /1
Department of Anthropnlogy
University of Florida 7 /
Gainesville, FL 32611
(904) 392-2031
y
LIST OF MAPS
Pag
Map 1 The Agricultural Development Divisions (ADD) in Malawi....c.
Map 2 The Lilongwe Agricultural Development Division (LADD)
and Lilongwe Rural Development Project (LRDP).............. 7
LIST OF TABLES
Page
Table 1-1
Table 1-2
Table 2-1
Table 2-2
Table 2-3
Table 2-4
Table 2-5
Table 2-6
Table 2-7
Table
Table
Table
Table
2-7b
2-7c
2-8
2-9
Table 2-10
Table 2-11
Table
Table
Table
Table
Table
Table
Table
Table
Table
Table
2-12
2-13
2-14
2-15
2-16
2-17
2-18
2-19
2-20
2-21
Table 2-22
Table 2-23
Table 2-24
Table
Table
Table
Table
2-25
2-26
3-1
3-2
Preliminary Report: NSSA 1980/81 Household
Characteristics........................... .............
Clubs and Credit by Sex in LRDP 1982/83 ...............
Marital Status of Household Heads, LRDP NSSA..........
Number of Years in the Village, LRDP NSSA.............:
School Education of Household Heads, LRDP NSSA.........
Attendance of Farming Courses, LRDP NSSA .............3
Wage Employment and Status, LRDP NSSA.................
Approximate Distance to Closest Facilities,
From Households, LRDP NSSA .........................3.
Types of Household Items Owned By Households,
LRDP NSSA ........................................ 3
Condition of Main House, LRDP NSSA ................
Types of Farm Equipment Owned, LRDP NSSA...............
Source of Extension Advice, LRDP NSSA ............ ...03
Sources of Advice On Extension Topics of Those
Receiving Advice, LRDP NSSA ......................... 3
Types of Contact From Extension Agents to Those
Household Heads and Wives Receiving Advice,
LRDP NSSA... ....................... ......... .........3
Type of Advice Received by Those Receiving Advice,
LRDP NSSA ........................................ 3S
Classes of Holding Size For LRDP NSSA................43
Sources of Gardens, LRDP NSSA......... ............43
Areas Planted to Major Crops in LRDP NSSA.............43
Major Crops Grown, LRDP NSSA .........................47
Sources of Maize and Groundnut Seed, LRDP NSSA........ 47
Crop Mixtures in Groundnut Plots, LRDP NSSA........... 4
Month of First Soil Preparation for Maize and
Groundnut Plots,. LRDP NSSA ......................... 4
Time of Planting for Maize Plots, LRDP NSSA...........49
Time .of Planting of Groundnut Plots, LRDP NSSA........49
Time of Weeding for Maize and Groundnut Plots,
LRDP NSSA ........................................... 51
Number of Weedings for Maize and Groundnut Plots,
LRDP NSSA ........................................... 51
Type of First Fertilizer Applied to Maize Plots,
LRDP NSSA ....................................... .. 51
Plant Populations from Maize and Groundnut
Plots, LRDP NSSA ............................ ...... 53
Maize Yields from Plots, LRDP NSSA.................. 5
Groundnut Yields from Plots, LRDP NSSA................53
Marital Status of Household Head ....................63
Husband's Location At Time of Survey .................63
Table
Table
Table
Table
Table
Table
Table
3-3
3-4
3-5a
3-5b
3-6
3-7a
3-7b
Table 3-8a
Table
Table
Table
Table
Table
Table
Table
Table.
Table
Table
Table
Table
Table
Table
Table
Table
Table
Table
Table
Table
Table
Table
3-8b
3-9
3-10
3-11a
3-11b
3-1ic
3-12
3-13
3-14
3-15
3-16
3-17
3-18
3-19
3-20
3-21
3-22
3-23
3-24
3-25
3-26
3-27
Table 3-28
Table 3-29
Table 3-30
Table 3-31
Table 3-32
Table 3-33
Table 3-34
Table 3-35
Table 3-36
Table 3-37
Table 3-38
Table 3-39
Table 3-39
Table
Table
Table
Table
3-40
3-41
3-42
3-43
Reason for Residing In Present Village ..............63
Length of Residence In Present Village ...............64
Household Composition By Age Categories...............64
Household Composition By Kinship Catagories...........64
Average Number of Pregnancies, Births and Deaths......66
Education Experience of Adults .......................67
Current and Previous Children Educated
and Average Number of years of School Attendance.......67
Reading Ability in Chichewa (Vernacular)
and English ..........................................69
English Speaking Ability ................6........... 69
Christianity and Church Attendence ..................71
Traditional and Non-Tradititonal Statuses .............71
Condition of Main House ..............................73
Farm Equipment ........ ........................ .73
Household Items...................................... 73
Measured Distances To Facilities and Infrastructure...75
Training Courses ....... . .. ................. 77
Farming Club/Group Membership ........................77
Achikumbi (Recognized "Good Farmer") Status...........77
Household Head's Report as to Who Farms in
Household ....................................... 78
Extension Agent Visits ....................... ........78
Number of Gardens .... ............................. 80
Number and Type of Gardens Per Household
For 84 MHH and 17 FHH ......................... ........ 80
Source of Acquired Gardens ...........................81
Means by Which Gardens Were Acquired..................81
Varieties of Maize ...................................83
Miscellaneous Household Behavior......................83
Cropping Patterns 1981/82 ...... ... ......... ........ 85
First and Second Main Crops in 1980/81 ...............85
Fertilizers Used in 1980/81 and 1981/82..............88
Average Number of Bags Per Plot of Various
Types of Fertilizer Used in 1980/81 and 1981/82 ...... 88
Source of Fertilizer For 1980/81 and 1981/82.......... 88
Time of Fertilizer Application For 1980/81
and 1981/82 Maize Plots .............................. 90
Farmer's Knowledge of Fertilizer Application
For Maize Plots in 1980/81 and 1980/82................90
Household Selling Crops and Livestock ...............92
Relative Importance of Cash From Crops and Livestock..92
Households Gaining INcome Through Outside Employment..93
Households Obtaining Income From Village Industries...93
Sources Which Provide the Best Income ................93
Relative Importance of Sources of Cash Income.........95
Changes in Food Self-Sufficiency as a Result of
Project ............ .................. ..... ........ 95
Changes in Cash Income as Result of Project...........97
Changes in Use of Introduced Inputs as Result
of Project ..................... .. ................. .97
Changes in Use of Credit as a Result of Project......98
Changes in Marketing as a Result of Project...........98
Source of Hybrid Seed .............................. 00
Souce of Hybrid Maize Seed For Next Season...........100
Table 3-44
Table 3-45
Table 3-46
Table 3-47
Table 3-48
Table 3-49
Table
Table
Table
3-50
3-51
3-52
Table 3-53
Table
Table
Table
Table
Table
3-54
3-55
3-56
3-57
4-1
Table 4-2
Table 4-3
Table
Table
Table
Table
4-4
4-5
4-6
4-7
Table 4-8
Source of Groundnut Seed For Next Season............. .
Number of Farmers Who Plan To Use Commercial
Fertilizer Next Season ............................. *12
Fertilizers Known By Farmers ........................103
Average Number of Bags of Various Types of
Fertilizers Farmers Plan to Use......................i03
Source of Fertilizer for Farmers Who Will
Use It ................... ... ............ ...... .103
Farmers Knowledge of When to Clear Land
For Maize ... .......................... .............
Farmers Knowledge of When to Ridge Land For Maize.... :
Farmers Knowledge of When to Plant Maize ............
Farmers Knowledge of Recommended Spacing For
Maize...... ..... .... .......... ............
Farmers Knowledge of When to Apply 20:20:0 to
Maize .................. .......... ... .. ........... .
Farmers Knowledge of When to Apply S/A to Maize.......1'
Farmers Knowledge of Recommended Bags of 20:20:0.....1 I
Farmers Knowledge of Recommended Bags of S/A ......... 109
Farmers Knowledge of Price of Fertilizer ............. 0
De Jure Population by Age and Sex in LRDP from
NSSA Data ...... ...... .... ....... .... . ....... 1
Length of Village Residence of Household Head,
NSSA Data .................. ......................... 1U
Change of the Sex of the Household Head From
1980/81 to 1981/82 ..; ...............................]
Marital Status of Household Head, NSSA ..............11.
Major Crops Grown in LRDP, NSSA Data ................13.
Major Cropping Patterns in LRDP, NSSA Data........... 1
Average Crop Area For Producing Households, LRDP
From NSSA Data .............. .... ...............12
Holding Size For Households Producing Major
Cropping Patterns ............... ... ................... I
LIST OF FIGURES
Figure 3-1
Page ,
Established Fertilizer Prices and Government
Maize Recommendations..... ........... .. ***.**.. .. *.*. .
ACKNOWLEDGEMENTS
Many people helped to make this report possible. In Malawi
the staff of the Women in Agricultural Development Project, Mr.
C. Smith and Ms. F. Kayuni, worked as supervisors of the
interviewers along with the staff of the Farming Systems Analysis
Section under the direction of Dr. A. Hansen. Mrs. C.
Ndacheredwa, our secretary, kept the office running while we were
in the field. Ms. S. Philpott of Bunda College of Agriculture
aided in training the students from Bunda College in the
techniques needed for the Lilongwe Rural Development Project
(LRDP) Survey.
The management and staff of the Lilongwe Agricultural
Development Division (LADD) in which LRDP is located aided in
allowing the.Survey to be carried out and requesting that their
.field staff work with us. In particular, the Program Manager of
LADD and the Project Officer of LRDP lent their full support to
the Survey and to WIADP's endeavors. The same holds true for the
Evaluation Unit of LADD and other sections such as Animal
Husbandry, Credit, Women's Programs, Training, and Land
Allocation.
None of this research could have been carried out without
the support and encouragement of the Ministry of Agriculture
(MOA). The Chief Projects Officer, Chief Agricultural Research
Officer and Chief Agriculture Officer guided WIADP's stay in the
country and requested that certain documents and studies be
undertaken. They were interested in the results and made use of
many of the results. Some of the section heads in the Department
of Development were of particular assistance. My thanks goes to
the Women's Programs Officer, Food and Nutrition Programs'
Officers, Credit Officer and Training Officer, all at MOA
Headquarters.
To the personnel at the National Statistics Office and the
Evaluation Officers around the country a word of thanks for
listening to the need for sex-disaggregated data. Many of them
followed through in producing this type of data as well.
To people who helped in the U.S., I would like to
acknowledge the assistance of J. Albert (formerly of PPC/WID) and
N. Horenstein of the Women in Development Office, USAID. The
computer services of Mr. Evans were indispensable for this
report. Ms. C. Harshbarger assisted with the report,'and she and
Mrs. D. Wilkes and Ms. J. Weston helped with the typing.
Dr. A. Hansen read the manuscript and provided many helpful
ideas. However, the contents are solely the responsibility of
the author.
Finally, my biggest thanks of all goes to my family who put
up with late hours and files lost through computer errors.
A. Spring
Gainesville, FL. USA
March, 1984
ABBREVIATIONS AND ACRONYMS USED
ADD
ADMARC
AES
BLADD
SFHH(s)"
FSAS
FSR
GOM
KADD
KRADD
LADD
LLDP
LRDP
MOA
MHH(s)
MZADD
NSO
NSSA
PM
PO
RDP
SLADD
SAID
WIADP
WID
Agricultural Development Division
Agricultural Marketing and Development Corporation
AgroEconomic Survey
Blantyre Agricultural Development Division
Female Household Head(s)
Farming Systems Analysis Section
Farming Systems Research
Government of Malawi
Kasungu Agricultural Development Division
Karonga Agricultural Development Division
Lilongwe Agricultural Development Division
Lilongwe Land Development Project
Lilongwe Rural Development Project
Ministry of Agriculture
Male Household Head(s)
Mzuzu Agricultural Development Division
National Statistics Office
National Sample Survey of Agriculture
Program Manager
Project Officer
Rural Development Project
Salima Agricultural Development Division
United States Agency for International Development
Women in Agricultural Development Project
Women in Development
CHAPTER 1
THE WOMEN AND AGRICULTURAL DEVELOPMENT PROJECT
AND DISAGGREGATION OF DATA BY SEX
INTRODUCTION
This report describes some of the activities of the Women in
Agricultural Development Project (WIADP) in Malawi. Other
activities.have been described in previous reports (see
bibliography in Appendix A). This report examines some of
WIADP's work in studying the contribution of Malawian women to
agriculture and in disaggregating social, economic and agronomic
data by sex.
In this chapter a general outline of the WIADP Project is
given followed by a description of two of its major endeavors:
1. analyses of the National Sample Survey of Agriculture (NSSA)
and
2. execution of a large, multifaceted survey of agricultural
practices. The subject is an integrated rural development
project, the Lilongwe Rural Development Project (LRDP).
LRDP is then discussed briefly in this chapter as are the design,
methodology, sample, and indicators used in the LRDP Survey.
Chapter 2 describes the NSSA, its survey instruments, method
of data collection, and analysis. The results of the NSSA for
LRDP are presented with all data disaggregated by sex of
household head.
CHAPTER 1
THE WOMEN AND AGRICULTURAL DEVELOPMENT PROJECT
AND DISAGGREGATION OF DATA BY SEX
INTRODUCTION
This report describes some of the activities of the Women in
Agricultural Development Project (WIADP) in Malawi. Other
activities.have been described in previous reports (see
bibliography in Appendix A). This report examines some of
WIADP's work in studying the contribution of Malawian women to
agriculture and in disaggregating social, economic and agronomic
data by sex.
In this chapter a general outline of the WIADP Project is
given followed by a description of two of its major endeavors:
1. analyses of the National Sample Survey of Agriculture (NSSA)
and
2. execution of a large, multifaceted survey of agricultural
practices. The subject is an integrated rural development
project, the Lilongwe Rural Development Project (LRDP).
LRDP is then discussed briefly in this chapter as are the design,
methodology, sample, and indicators used in the LRDP Survey.
Chapter 2 describes the NSSA, its survey instruments, method
of data collection, and analysis. The results of the NSSA for
LRDP are presented with all data disaggregated by sex of
household head.
Chapter 3 describes the LRDP Survey instruments and analysis
procedures and gives the results of the Survey disaggregated by
sex of household head as well as by sex of the total sample
including women in male headed households, male heads, and female
heads. Intrahousehold differences in production, labor
experience with improved methods, and extension services are
presented.
Chapter 4 briefly compares the data from NSSA and the LRDP
Survey, discusses the concept of female headedness, and gives a
summary of the profiles of women and men smallholder farmers in
LRDP. It offers suggestions as to how LRDP more directly can aid
smallholders in general, and women farmers in particular, based
on the data presented here. Finally, a discussion of how a
project such as WIADP and its data collection and analysis
methods may enhance future integrated development projects as
well as women in development (WID) projects is presented.
MALAWI'S NATIONAL RURAL DEVELOPMENT PROGRAM
The Republic of Malawi, a landlocked country in south
central Africa, is bordered by Tanzania, Mozambique and Zambia.
The total area is 118,484 square kilometers, of which 21% is
covered by water (principally being Lake Malawi, the 9th largest
lake in the world). Malawi has a growth rate of 2.9%. With a
population of approximately 6 1/2 million people, there is an
average population density of 70, but the range goes from 29 to
103 persons per square kilometer. Land holding ranges from 0.97
hectares in Southern Region to 1.39 in Central Region and 3.45
hectares in Northern Region. People living in rural areas
constitute 90% of the population.
According to 1979 figures, agriculture produced 43% of the
Gross National Product with 92% of exports deriving from
agriculture. Malawi's agriculturally based economy is divided
into two sectors. The estate sector contributes approximately
70% of agricultural exports whereas the smallholder sector
contributes 30% in addition to feeding itself. Estates manage
25% of the land planted in the major cash crops such as tobacco,-
coffee, tea and sugarcane. In relation to the total land area,
15% is cultivated by smallholder farmers and 5% by commercial
estates. Women's extensive contribution to subsistence and cash
crop production has been documented by Clark (1975) and discussed
fully elsewhere (Spring 1982 1983b; Spring, Kayuni and Smith
1983b).
Beginning in 1977, the country embarked on a 20 year
National Rural Development Program (NRDP) in order to increase
smallholder production .that was lagging behind the estate sector.
The NRDP aims to 1) increase smallholder production; 2) conserve
national resources through better crop husbandry, conservation of
watershed areas and forests; and 3) provide inputs.and services
to smallholders (GOM 1978).
To accomplish these aims the country was divided into eight
contiguous units called Agricultural Development Divisions (ADDs)
for the purpose of administering development projects. There are
two ADDs in the Northern Region (Karonga and Mzuzu), three in the
Central Region (Lilongwe, Kasungu, and Salima), and three in the
Southern Region (Blantyre, Liwonde, and Ngabu) (Map 1). Each ADD
Mzuzu A.D.D.
Safna A.D.D.
Kasungu A.D.D.
Liongwe A.DD.
Uwonde A.D.D.
Blantyr
Ngabu A.D.D.
MAP 1 THE AGRICULTURAL DEVELOPMENT DIVISIONS (ADDs) IN MALAWI
has two to six Rural Development Projects (RDPs) under its
control. There are approximately 40 RDPs today, 28 of which are
funded integrated development projects. The funds come from
international donors (19 projects) or general Government of
Malawi (GOM) revenue funds.
THE WOMEN IN AGRICULTURAL DEVELOPMENT PROJECT
The Women- in Agricultural Development Project (WIADP)
operated in Malawi from 1981-1983 under the auspices of the GOM,
Ministry of Agriculture (MOA), with funding from the Office of
1
Women in Development, USAID. Personnel consisted of an
anthropologist (who was Project Director) an agronomist, a
Malawian agriculturalist, and a secretary. Staff from the
Departments of Research and Development (extension) staff of the
MOA aided from time to time. The aim of the Project was to study
women and men farmers in relation to agricultural development in
Malawi in order to strengthen project planning and extension
services to rural women. Data on women in diverse agricultural
contexts were collected in terms of socio-economic and cultural
variables, indigeneous and improved agronomic practices,
knowledge and utilization of improved agriculture, and
interaction with development processes (activities and
personnel).
WIADP endeavors in Malawi included research, training, and
action-oriented projects. In its major intensive research
activities, WIADP concentrated in one area in each of the three
regions of the country at the request of the MOA. WIADP focused
its data collection in terms of farming systems research (FSR) in
Karonga ADD.(KRADD), Lilongwe ADD (LADD), and Blantyre ADD
(BLADD), but all ADDs were visited and staff interviewed in terms
of development planning and women farmers (Spring 1983a).
WIADP's agro-socioeconomic research activities focused on
FSR including reconnaissance surveys carried out in Liwonde ADD
(LWADD).(Spring 1982a) and KRADD (Spring 1982e; Spring, Smith,
Kayuni 1982), trials in BLADD and LADD (Spring 1981c; Smith
1982a, 1982b, 1983), investigations of groundnut, soybean and
stall-feeder enterprises in LADD (Spring 1982a, 1983), and an
in-depth investigation of farming systems in LADD. The latter is
described in this report (Map 2).
Another research endeavor involved the investigation of the
background and agricultural training of female and male extension
personnel at various levels with the help of the Women's Program
Section of the MOA (Spring 1981a, 1982b, 1983a; Kayuni 1982a,
1982b).
The third major research activity was concerned with
disaggregating by sex two large bodies of data. Sex
disaggregated labor data from the AgroEconomic Survey Reports
(AES 1968-83) that had been collected since 1968 were compiled
and analysed to provide a general picture of the farming systems
and women's contribution by area and commodity (Spring, Smith and
Kayuni 1983b). Another sex-disaggregation project, reported on
here, is concerned with a large data set from the National Sample
Survey of Agriculture (NSSA) that was carried out in Malawi in
1980-81. Survey data were analysed, and the various research
units responsible for analysing these data were introduced to the
\ LILONGWE AGRICULTURE DEVELOPMENT DIVISION
1
S\ULONGWE NORTHEAST
TO R,P. '
DEDZA HILLS
\ -HIWI/UJFI0ZI
R.D.P. \ 1.
NTCHEU
R.D.P. TO ST
KEY
Main Road
Project Boundary
Intrnatioal Boundary
'Ladd Boundary
Scale I 1,000,000
MAP 2 THE LILONGWE AGRICULTURAL DEVELOPMENT DIVISION (LADD) AND LILONGWE RURAL
DEVELOPMENT PROJECT (LRDP)
method of sex-disaggregation.
In terms of training, WIADP held a National Workshop on
Women in Agricultural Development for Women's Program Officers
and others (Spring 1982d), prepared a commodity training manual,
provided agronomic training and materials to farmers, and worked
with extension personnel at a variety of levels to train them in
agricultural topics.
The action and policy endeavors of WIADP included changing
reporting formats for RDPs (Spring, Smith and Kayuni 1983b;
Appendix B), working at the national level on credit policy for
women (MOA, 1982), preparing recommendations and methodologies
as to how male extension workers could work with women farmers
(MOA 1983), and having the National Statistical Office (NSO)
utilize the sex-disaggregated data (NSO 1982). A complete list
of WIADP's publications is given in Appendix A.
INVOLVEMENT OF WIADP IN DISAGGREGATING NSSA DATA
There has been much discussion about the need to have data
disaggregated by sex at the national level in order to have
adequate data bases with which to evaluate and plan projects to
benefit women (Dixon 1982; Burfischer and Horenstein 1982;
Safilios-Rothschild 1983). A major concern of WIADP and of this
report is to document the farming practices and delivery of RDP
services to women in married households and on their own, and to
compare male and female headed households. "It-is very important
to have detailed data on the nature of women's employment status
in agriculture in order to dispel the prevailing stereotypic
image of women as unpaid family workers" (Safilios-Rothschild
1983:1).
Various indicators at the macro-level on women's
contributions, needs, and potential must be known for planning
purposes. Because the many aspects of women's agricultural work
are unknown, national policies and field projects do not take
rural women into account thereby failing to prepare and provision
them adequately. WIADP saw as a very important goal the task of
providing sex disaggregated data both in its own work and in
.terms of the secondary data that it utilized. Some of the
results of this work in other RDPs were presented to the Planning
Division of the MOA at their request in April 1983 (Spring, Smith
and Kayuni 1983b).
WIADP targeted the NSSA as a major body of data that would
be used for policy making and investigated the possibility of
disaggregating by sex the data generated by the various surveys.
The NSSA was carried out in 1980-81 as a national survey of
smallholder agriculture. Approximately 7,000 households were
surveyed. The purpose of the NSSA was to study the use of
Malawi's agricultural resources in order to help policy makers
decide priorities and strategies for future agricultural
development.
The NSSA was a very intensive endeavor in terms of the
amount of data collected, the length of time involved (an entire
year), and the local specificity, i.e., its ability to assess
production at the ADD as well as the RDP level. Funds for the
NSSA came from the British (90%) and Malawi (10%) Governments,
and the work was conducted on a collaborative basis between the
MOA and the National Statistical Office (NSO) which is under the
Ministry of Finance.
Starting in one ADD, WIADP was able to obtain coding sheets
of three NSSA surveys prior.to their being processed by the NSO
and realized that data were collected in such a way as to contain
adequate information by sex of household head. The analysis as
planned by t~he NSO and other units of the MOA would ignore this
fact and lump female household heads (FHHs) and male household
heads (MHHs) together. WIADP was particularly interested in the
sex of household head because a distinction is often made in
terms of female household heads and women in married households
as being eligible or targeted for various RDP services.
On the basis of establishing the method of analysis and
seeing that the results might present some useful data, WIADP
presented these notions to MOA and NSO personnel in November
1981. WIADP stressed that it would be useful to know the
percentage of FHHs (as these households might need some
attention) in all the project areas for planning purposes and
noted that this easily could be gleaned from .the data. WIADP
argued that it would be then possible to rewrite the software
programs so that FHHs and MHHs could be compared in all the
surveys. Subsequent meetings with various ADD and NSO personnel
involved discussions about the need to disaggregate the data by
sex and the method for doing so.
By the time WIADP terminated its stay in the country the
following had been completed in terms of disaggregation by sex of
NSSA data on smallholder farmers (these items are not given in
chronological order). First the initial NSO publication on the
NSSA contains the percentage of FHHs for each ADD and RDP in the
country (Table 1-1), allowing area-specific and nationwide totals
to be seen for the first time (NSO 1982:2).
Various ADDs were "inspired" to disaggregate their NSSA
data. Liwonde ADD (LWADD) re-entered all its data from the three
Core Surveys (discussed in Chapter 2) into the University of
Malawi's computer and analyzed the data using its own method.
Since this particular ADD has a high proportion of FHHs (37%
compared with the national total of 29%), some attention was
focused on these households in subsequent rural development
project proposals (LWADD 1982).
The Evaluation Unit of Ngabu ADD (NADD) followed the model
laid out exactly, analyzing by sex of household head for the same
three surveys as in the original paper (Spring 1981b), in spite
of the fact that they had access to data on other surveys as well
(NADD 1982). They then used the data gleaned in this way to
understand the lack of contacts by their extension staff to women
farmers in the area.
BLADD analyzed all the surveys by sex of household for one
RDP area with 35% FHHs and added a refinement to the concept of
household head by distinguishing between FHHs who were married
and those who were not. The analysis showed that married FHHs
were more similar to MHHs, while unmarried FHHs were quite
different in their cropping, income and expenditure patterns
(BLADD 1982a, 1982b).
Of the remaining ADDs, LADD and KRADD were preparing to
disaggregate the data; Kasungu ADD (KADD) was considering the
process; and the Salima ADD (SLADD) and Mzuzu ADD (MZADD)
TABLE 1 PRELIMINARY REPORT NSSA 1980181 NATIONAL SAMPLE SURVEY Of AGRICULTURE FOR CUSTOMARY LAND
HOUSEHOLD CHARACTERISTICS
I FtEALE MEAN DE FACT MEAN AREA SAMPLE NO
HM HEADS HH SiZE CULTIVATED HOUSEHOLDS
HECTARES)
CHITIPA 13.2 5.1 1.07 100
KARON6A 17.7 4.5 0.88 120
KARONSA ADD 15.8 4.8 0.96 220 H
RUMPHI-COFFEE 22.7 6.1 0.77 60 X
HENGA-KASITU 27.7 4.6 1.14 60
HEN6A-KASITU EJT 11.1 5.1 1.79 80
RUKURU-KASITU 17.4 4.7 1.57 s80 J
IEST ZllNBA 16.1 4.8 1.72 120 V
SOUTHWEST MIHBA 33.1 3.9 1.42 60 OH
NKHATA BAY 24.0 1.& 0.88 120 t4
MHUIU ADD 21. 4. 1.39 580
KASUNGp NORTH 12.0 4.8 2.26 220
RUSA 9.3 5.7 2.36 100
NTCHISI 12.0 4.5 2.10 100 tl F-
DOVA WEST 14.9 5.3 2.06 220 h3
DOUA HILLS 16.1 4.4 164 120 2 0
NCHINJI SOUTH 16.4 4.7 2.04 180
KASUNGU ADD 14.1 4.9 2.06 940 1l .
H
NKHOTA-KOTA 25.6 $.1 0.71 80 c Z
SALINA NORTH 27.0 4.3 1,01 220 H n
SALIHA SOUTH 30.4 4.1 1.11 200 HE
SALIKA ADD 28.4 4.1 1.02 500
LILONGWE 20.4 4.4 1.72 540 F
LILONG6E EAST 20.0 4.4 1.16 219 00
THIVI-LIFIDZI 32.8 4.2 1.36 180
DEDZIAHILLS 38.5 4.6 0.99 160
NTCHEU 38.2 4.6 1.08 219
LILONGUE ADD 27.4 4.4 1.38 1318
MANGOCHI 33.2 4.0 0.79 240
NAHWERA 42.3 3.9 0.97 160
BALAKA 42.3 4.3 1.01 220
KAWINGA 31.2 3.9 0.94 260
ZO1NA 36.9 4.0 0.77 480
LIMONDE ADD 36.S 4.0 0.87 1360
SHIRE HIGHLANDS 33.6 4.7 0.75 660
BLANTYRE 37.9 4.8 0.77 220
MUANZA 30.9 4.8 1.27 120
PHALOMPE 34.7 4.3 0.89 259
MULANJE 33.0 4.6 0.67 320
BLANTYRE ADD 34.3 4.6 0.80 1579
CHIKMAUA 23.7 4.4 1.46 240
NSANJE 24.5 4.5 1.18 140
NGABU ADD 24.0 4.4 1.36 380
PALAUI 28.8 4.5 1.16 A877
appeared disinterested.
Shortly before WIADP terminated in Malwai, the programmer at
NSO rewrote a program for the Extension, Household Composition
and Resources Surveys for two of the project areas, one of which
was LRDP. Therefore, in total WIADP was able to obtain the data
and analyze five of the ten NSSA surveys for LRDP.
INVOLVEMENT OF WIADP IN LADD
WIADP was located at Chitedze Agricultural Reserach Station
which is in the LRDP area and which was designated as one of our
research areas by the MOA. The Program Manager (PM) of .LADD and
the Project Officer (PO) of LRDP were receptive to WIADP's work.
A variety of studies and training activities took place in LRDP
and focused on stall-feeding (Spring 1982b, 1983d), soybean
demonstrations and trials (Spring 1981c; Smith 1982a, 1982b,
1983) and training of extension personnel (Spring 1981a, 1982c;
Kayuni 1982a, 1982b, MOA 1983).
A request from the MOA to evaluate Women's Programs in the
ADDs required extensive contact with the management and staff of
all ADDs. The PM of LADD, however, requested that WIADP present
its findings about LADD at.an all day seminar to its staff. He
and his staff worked with WIADP to prepare a document specifying
stategies that the various sections and programs could use to: 1)
increase their benefits to women farmers and 2) account for Lhe
presence of rural women in agriculture (Spring, Smith and Kayuni
1983a). To this end sex-disaggregated reporting formats were
designed to monitor the progress of extension contacts, training
I
courses, and credit programs for staff and management at all
levels. These formats are now in use for all of the RDPs within
LADD (Appendix B).
LILONGWE RURAL DEVELOPMENT PROJECT
The Lilongwe Rural Development Project (LRDP) is located to
the west and south of Lilongwe City, the capital, in an area of
gently undulating plains. The area has an altitude of
1,090-1,230 meters, a temperature range of15. to 23 degrees
celsius, and a rainfall ranging from 640-1,090 mm (November to
April). The soils are moderately fertile and well suited for
growing maize, groundnut and tobacco. The area was originally
selected for funding in the late 1960's because it was in the
"major granary area of Malawi and people were accustomed to cash
cropping and had shown interest in land reorganization and
improved farming" (Kinsey 1973; Lele 1975).
The people in the Project area primarily monocrop maize
(corn), groundnuts (peanuts), tobacco, beans and sweet potatoes
under rainfed conditions. The project aim was the "production of
major crops (maize, groundnut, and tobacco) in a concentrated
area of 465,587 ha. through improvements in rural infrastructure,
land reorganization, training, credit, extension, marketing and
livestock development" (Lele 1975:10-11). Benefits to the nation
included increased government revenue, taxes and exportable
surpluses, plus the formation of an experienced group of
development officers ( LLDP 1973, 1979; Kinsey 1973; Lele 1975).
Benefits to the farmer included an increase in net income
and the establishment of a stable pattern of agriculture based on
land registration. It was believed that matrilineal inheritence
and post-marital matrilocal residence precluded stable,
commercial agriculture, and so land registration was supposed to
stabilize men on the land.' The project's original name was the
Lilongwe Land Development Programme (LLDP) because a major aspect
of the original proposal focused on land reorganization,
consolidation and registration.
Currently in its fifth and final phase, LRDP was largely
funded by the International Development Association and the GOM.
The structure of LRDP is that six administrative groups oversee
40 units (recently changed to EPAs or Extension Planning Areas)
that have been developed since 1968. Each unit has a Development
Officer and a number of grass roots technical assistants (four or
more general extension agents and occasionally other personnel
such as tobacco, forestry, livestock/veterinary assistants who
are male, and half the units have one farm home assistant who is
female).
During the first two years of LRDP, there was one extension
worker for every 200 families; the next 2 1/2 years the ratio was
one for every 400 families compared with one for every 1,200
-1,300 families in the non-program area. In addition there are
development/planning committees for farmers organized at village,
unit, group, and project levels. Day training courses take place
at the unit center while one to two week courses are given at the
two residential training centers. Most agricultural courses are
for men while women recieve home economics courses.
Originally LRDP.dispersed credit on an individual basis, but
abandoned that system in favor of farmers groups/clubs where
seasonal loans are guaranteed by the members. Medium term loans
and credit for livestock are still made on an individual basis
(see Table 1-2). Most units have primary schools; some have a
dispensary; and many have a government market owned by the
Agricultural Marketing and Development Corporation (ADMARC).
WIADP examined many of the LRDP proposals and project
completion reports and determined that there was little about
women either as farm managers (FHHs) or family laborers in the
proposals or reports (LLDP 1973; 1979). Women are mentioned only
as "farmer's wives" to be trained in home economics classes, and
their participation in LRDP services is only measured by
attendance at home economics courses. WIADP determined that
although the aims of Phases IV and V relate directly to women's
concerns and needs, no mechanisms exist to connect women to
project services.
The current situation in terms of women in groups/clubs and
in obtaining various types of credit is given in Table 1-2. In
almost none of the six groups does the percentage of women
participating in project services come close to the percentage of
female heads of household or farm laborers. Although at least
20% of farms are headed by women in LRDP, only 12% of the-
membership of clubs/groups is female, and many of these women
members are married to men who are members. The same can be said
for the percentage of women getting seasonal credit (13%),
stall-feeding (17%) and medium term credit (0.4%). It is hoped
that documenting women's contribution and needs as well as
meeting with the staff to discuss strategies will result in women
CLUBS AND
GROUP (Division)
CLUBS
Total Clubs
Total Members
Men
Women
7 Women
CREDIT
Seasonal
Men
Women
% Women
Medium Term
Men
Women
% Women
Stall-feeders
Men
Women
7 Women
244
5265
4690
665
137.
Table 1-2
CREDIT BY SEX IN LRDP 1982/83*
Total
2 3 4 5 6 Project
266
6859
5887
972
147.
35
9124
3274
840
97.
428
10241
8436
1805
187%
274
6404
5906
198
87.
218
5752
4767
962
177.
3824 5840 7995 8061 4701 4268
434
107.
972
11%.
798
97.
1699
177.
403
87%
928
187.
69 38 36 62 37 11
0% 0% 07 0. 0-. 8.
07 070 0 07 07. 87.
121
66
357.
118
5
47.
154
31
177.
100
22
187.
1465
43645
37870
5442
12%
34689
5234
137
253
1
0.47.
642
130
17%
18 5 21
1
07. 07 57
3 2 36
* Source, Project Officer, LRDP
Dairy
Men
Women
% Women
receiving more attention in present programs and future
proposals.
THE LRDP SURVEY
In addition to the data from the NSSA on the LRDP, this
report focuses on a large (15 instrument) survey carried out by
WIADP with 'the Farming Systems Analysis Section (FSAS). The FSAS
was part of another USAID project on Agricultural Research
conducted through the MOA and was responsible for farming systems
research in the country. It was able to provide personnel,
transport, some supplies, and computer facilities for the Survey
(Hansen and Ndengu 1983). The households in the LRDP Survey are
a sub-sample from the NSSA. It was therefore possible to obtain
a great deal of information about the same households over a two
year period and combine both primary and secondary data. The
purpose of the Survey was to study:
1. sex differences in farming practices between a) male and
female household heads, b) men and women in the same
household, and c) women in the two types .of households;
2. the effects of a development project on the farming system
of men and women smallholder farmers; and
3. the major indicators of smallholder agricultural
development.
Previous LRDP Studies and Findings
receiving more attention in present programs and future
proposals.
THE LRDP SURVEY
In addition to the data from the NSSA on the LRDP, this
report focuses on a large (15 instrument) survey carried out by
WIADP with 'the Farming Systems Analysis Section (FSAS). The FSAS
was part of another USAID project on Agricultural Research
conducted through the MOA and was responsible for farming systems
research in the country. It was able to provide personnel,
transport, some supplies, and computer facilities for the Survey
(Hansen and Ndengu 1983). The households in the LRDP Survey are
a sub-sample from the NSSA. It was therefore possible to obtain
a great deal of information about the same households over a two
year period and combine both primary and secondary data. The
purpose of the Survey was to study:
1. sex differences in farming practices between a) male and
female household heads, b) men and women in the same
household, and c) women in the two types .of households;
2. the effects of a development project on the farming system
of men and women smallholder farmers; and
3. the major indicators of smallholder agricultural
development.
Previous LRDP Studies and Findings
The first survey in LRDP was a Farm Management Survey
carried out on 1,000 growers from November 1969 to June 1971 by
LLDP's Evaluation unit. It studied cropping patterns, the
household, livestock ownership, knowledge of "correct" (i.e.,
extension) recommendations, farming practices, and farm planning
(LLDP 1971; 1973). Unlike Kydd (1982b blow) who used a figure
of 11% for female heads of households, it concluded that 30% of
the farms were managed by women, the average holding was 5 acres,
36% of growers cultivated vegetable seepage gardens, the average
household had 4.9 persons; and polygyny occurred in 26% of male
headed households. Fifty nine percent of the rainfed land was in
unimproved maize; only 3% of arable land under cultivation was
intercropped, and 9% ever.received a fallow period. The
following proportion of households owned livestock: cattle-(19%),
work oxen-(8%), poultry-(60%), other fowl-(14%), sheep-(2%) and
pigs-(8%). Bicycles were owned by 25%, stores by 2% and 1% had
vehicles.
Of particular importance to the design of the 1982 LRDP
Survey is Kydd's work in LRDP (1978, 1982a, 1982b). His key
indicators are activity patterns, income, consumption,
productivity, management and resources. The data Kydd uses were
collected in two Farm Management Surveys that were administered
by the Evaluation Section of LRDP in 1969/70 and then in 1978/79.
The first survey was the predecessor to the Core Surveys of the
NSSA (see Chapter 2). It
"measured household composition (monthly), garden (one
measurement-double checked), the incomes, expenditures
and labour allocation of all household members and the
work performed by the hired labour (by daily visits).
The surveys spanned the twelve months October to
September, and during this period enumerators were
stationed in the selected villages. Each enumerator
was required to make daily visits to between eight and
ten households" (Kydd 1982a:i).
Kydd's compares the two surveys. He shows that between
1969/70, the start of the Project, and 1978/79, nine years later,
there were significant changes in income, labor allocations,
resources and expenditures. He found that the number of female
heads increased from 11% to 28% between the two samples, but
there was no change in the average age of the household head.
Holding size decreased commensurate with.the estimated population
growth rate in LDRP (2.5%), but the land-person ratio was less
affected, probably because of increased male labor migration.
"Farm units of all sizes ... experienced declining land
availability per worker" (1982b:99) with households having the
most and least land suffering the greatest decline. Men who do
not have sufficient land tended to migrate, accounting for the
increase in female headed households.
Over the nine year period farmers planted their maize
earlier following extension recommendations, but there was an
overall increase in the labor expended. Cultivation of improved
maizes declined, and more labor was expended on tobacco than
maize at the expense of livestock, vegetables and other crops.
Agricultural labor allocated to local maize increased from 35% to
44% of total agricultural work, while labor applied to improved
maizes fell from 3.5% to zero. Work on tobacco increased from
13% to 21% of total agricultural work. Work on groundnutss was
stable with improved varieties becoming important (5 to 11 times
more labor time). Labor devoted to vegetables and other crop and
livestock declined. The proportion of work done by hired labor
was unchanged.
Kydd also shows that overall income increased but purchasing
power remained stable. Cash income increased from agriculture,
but the importance of agricultural income declined while that of
non-agricultural income increased. However, there was no change
in the share of tobacco in agricultural receipts (1982b:93).
Also unchanged was the share for livestock although the labor
allocation decreased, and increased expenditure. could be due to
the introduction of stall-feeding. Similarly, labor on
vegetables and other crops declined, but income from these
activities increased probably due to increased demand from
Lilongwe City. The income from non-agricultural wage labor and
non-farm business increased markedly.
Indicators for the LRDP Survey
A guiding idea in the design of the LRDP Survey was the use
of key indicators of development (Castro, Hakansson and Brokensha
1981; Kydd 1982a, 1982b). Castro, et. al. suggest that it is
useful to consider control of land, productive resources such as
capital equipment, consumer durables, income (farm and nonfarm),
and livestock, as well as non-productive indicators such as
housing, consumer goods, fuel, ceremonial expenditure and diet
(1981:401). The authors also attempt to delineate local people's
perception of development. Following Castro, et. al. and Kydd
the indicators used in the LRDP Survey are;
.1. Land: types, major and minor crops grown, land tenure and
acquisition, use of fertilizers and inputs, yields and
stored grain, experience cultivating improved maizes.
2. Capital equipment other than land and livestock: farm
implements, consumer durables.
3. Income: self provisioning ability, sources'of income from
farm and non-farm. (Amounts and expenditures were not
possible to collect properly, and retrospective data on
these topics are inaccurate.)
4. Non-productive property: condition of main house, number of
granaries.
5. Fuel firewood sources
6. Education: of household head, spouse, children.
7. Household size and composition: number and age of adults
and children, residency status, sex of household head.
From the smallholder study (LLDP 1973) the following types
of information were added to the survey instruments:
8. Knowledge of correct maize cultivation practices and
recommendations.
9. Farm Planning: sources of seed and inputs, plans and
operations for the next growing season.
In addition, the following other indicators were then added:
10. Labor: persons participating by crop and farm operation,
labor hired.
11. Perceived changes as a result of the Project: perceptions
of "development", utilization of project services, and
committee/club membership.
12. Distances to resources/project services.
13. Religiousity, traditional and non-traditional status
14. Migration, urban and international experiences of men and
women.
The previous surveys and analysis described above provide a
foundation for the 1982 WIADP/FSAS LRDP Survey. Chapter 2
expands upon the 1980/1981 NSSA survey instruments and results
since this was the sample from which the 1982 subsample was
drawn. Then Chapter 3 discusses the instruments and results of
the 1982 LRDP Survey. Chapter 4 compares the NSSA and LRDP
Survey and argues that they are producing comparable data so that
profiles about smallholder agriculture or farming systems of male
and female household heads can be reliably made from either or
both.
24
FOOTNOTES
1. The funding from the office of Women in Development, USAID
commenced in March 1982.
2. In Malawi, only the MOA issues technical agricultural
recommendations. Ideas and advice from other sources are
considered suggestions.
3. Beginning in 1982, LADD began targeting women for
agricultural courses as well as home economics courses. Thirty
percent of places in agricultural courses were being reserved for
women.
CHAPTER 2 -
THE NATIONAL SAMPLE SURVEY OF AGRICULTURE
DESCRIPTION OF THE NSSA
Survey Instruments
The National Sample Survey of Agriculture utilized ten
survey schedules to assess agricultural, social and economic
variables which affect rural farm families. The first three
survey instruments (Household Composition, Garden, and Yield)
have been used previously and are known as the Core Surveys.
The Preliminary Report (NSO 1982) describes the survey
instruments as follows:
"1. HOUSEHOLD COMPOSITION SURVEY: A listing of all.members by
age and sex together with questions covering personal
characteristics of the household head.
2. GARDEN SURVEY: Area measurements together with questions
covering land tenure and land husbandry.
3. YIELD STUDY SURVEY: Harvest record with other questions
covering cultivation practices.
4. RESOURCES SURVEY: Distance of the household from various
important amenities together with questions concerning
ownership of various household and farm implements and the
condition of the main dwelling unit.
5. EXTENSION SURVEY: A set of questions answered separately by
the household head, and where possible by his wife (sic),
concerning types of advice, methods of receiving advice and
frequency.
6. CROP STORAGE SURVEY: Measurement of all storage structures
with records of the amount of crops in the structure, pests
CHAPTER 2 -
THE NATIONAL SAMPLE SURVEY OF AGRICULTURE
DESCRIPTION OF THE NSSA
Survey Instruments
The National Sample Survey of Agriculture utilized ten
survey schedules to assess agricultural, social and economic
variables which affect rural farm families. The first three
survey instruments (Household Composition, Garden, and Yield)
have been used previously and are known as the Core Surveys.
The Preliminary Report (NSO 1982) describes the survey
instruments as follows:
"1. HOUSEHOLD COMPOSITION SURVEY: A listing of all.members by
age and sex together with questions covering personal
characteristics of the household head.
2. GARDEN SURVEY: Area measurements together with questions
covering land tenure and land husbandry.
3. YIELD STUDY SURVEY: Harvest record with other questions
covering cultivation practices.
4. RESOURCES SURVEY: Distance of the household from various
important amenities together with questions concerning
ownership of various household and farm implements and the
condition of the main dwelling unit.
5. EXTENSION SURVEY: A set of questions answered separately by
the household head, and where possible by his wife (sic),
concerning types of advice, methods of receiving advice and
frequency.
6. CROP STORAGE SURVEY: Measurement of all storage structures
with records of the amount of crops in the structure, pests
CHAPTER 2 -
THE NATIONAL SAMPLE SURVEY OF AGRICULTURE
DESCRIPTION OF THE NSSA
Survey Instruments
The National Sample Survey of Agriculture utilized ten
survey schedules to assess agricultural, social and economic
variables which affect rural farm families. The first three
survey instruments (Household Composition, Garden, and Yield)
have been used previously and are known as the Core Surveys.
The Preliminary Report (NSO 1982) describes the survey
instruments as follows:
"1. HOUSEHOLD COMPOSITION SURVEY: A listing of all.members by
age and sex together with questions covering personal
characteristics of the household head.
2. GARDEN SURVEY: Area measurements together with questions
covering land tenure and land husbandry.
3. YIELD STUDY SURVEY: Harvest record with other questions
covering cultivation practices.
4. RESOURCES SURVEY: Distance of the household from various
important amenities together with questions concerning
ownership of various household and farm implements and the
condition of the main dwelling unit.
5. EXTENSION SURVEY: A set of questions answered separately by
the household head, and where possible by his wife (sic),
concerning types of advice, methods of receiving advice and
frequency.
6. CROP STORAGE SURVEY: Measurement of all storage structures
with records of the amount of crops in the structure, pests
and protection methods used.
7. LIVESTOCK SURVEY: A count of all cattle, sheep, pigs, goats
and all types of poultry together with a recording of
deaths, births and slaughterings during a set recall period.
8. INCOME AND EXPENDITURE SURVEY: A record of all income by
source, expenditure by type and barter transactions.
9. NUTRITION SURVEY: Weight and length measurements for
children under five years. /
10. ENERGY SURVEY: A survey of types of energy used for various
tasks with questions concerning the availability of wood"
(NSO 1982:v).
All households in .the sample received the Household
Composition, Garden, Yield, Resources, Livestock, and Nutrition
Surveys. Thirty -five percent of the sample were queried on the
Extension, Crop Storage, and Energy Surveys; only 20% were given
the Income and Expenditure Survey. Household Composition, Yield,
Resources and Extension Surveys were administered once. Garden,
Crop Storage, Nutrition and Energy were given twice. The
Livestock Survey was given thrice; and the Income and Expenditure
Survey involved weekly visits to record data.
This chapter analyzes the.data pertaining to the Core
Surveys plus the Resources and Extension surveys. Data from the
remaining surveys were still being processed by the NSO when
WIADP stopped its work in Malawi.
Sample
The sample of households was chosen through a sequential
process that utilized both stratification and randomness. The
first strata were the 180 Eastern Planning Areas (EPAs) into
which the rural countryside is divided. All EPAs contain
approximately the same number of farm families. Each EPA was
subdivided in the mid 1970s into subunits that were used as
enumeration areas (EAs) for the 1977 National Population Census.
Each of these EAs had a population of between 500 and 1500 people
in 1977. A random sample of. twenty households was selected from
the complete list of all households.within each of the randomly
selected EAs. Each of the 344 enumerators for the NSSA was
assigned 20 households within an EA, giving a possible national
sample of 6,880 smallholder households from 344 EAs. The
enumerators -resided for 12 months in the villages close to their
clusters of 20 families.
For the NSSA a household was defined as:
"being made'up of all members who make common provision
for food, or more simply, people who eat together from
a common pot. A household head is the person making
day to day decisions (especially concerning
agriculture) in the household. In some cases female
headed households may be supported by husbands working
elsewhere." (NSO 1982:1)
Administration
The NSO was ultimately responsible for the NSSA. At the
field level one supervisor managed 6 enumerators, and a field
officer monitored the progress of a number of supervisors. Each
ADD has its own Evaluation Unit that is responsible annually for
collecting and analyzing data in project areas that have already
received international funding. These Evaluation Units
administered the NSSA in the EAs within those project areas. In
project areas that are not yet funded and, thus, do not have an
Evaluation Unit assigned to them, the NSO directly hired
enumerators, field officers and supervisors and also utilized the
staff of the Agro-Economic Survey office. There were 344
enumerators who collected data, each man being responsible for 20
households and residing in the villages where households were
located.
In terms of data analysis, the responsibility rests with
NSO. However, some ADD Evaluation Units produced preliminary
results for their areas, by computer or hand tabulation, usually
only of the Core Surveys.
It should be pointed out that the NSO shares a computer with
only 24K of memory (Apple home micro-computers have 64K or 128K)
with other government agencies, hence processing and analyzing
the data has been slow. Thus far NSO has produced a nationwide
preliminary analysis of the NSSA that gives household
characteristics (percentage of female household heads and de
facto household size), mean cultivated area by RDP, cropping
patterns by ADD, and yields of seven major crops by RDP (NSO
1982).
WIADP'S ANALYSIS OF LRDP NSSA MATERIALS
The Evaluation Unit of LADD was responsible for the NSSA
enumerators working within existing projects such as LRDP.
Because the Evaluation Unit of LADD had been administering the
Core Surveys for years prior to NSSA, the Unit received the
print-outs from NSO. WIADP worked to analyze the LRDP.NSSA
materials because of its interest in disaggregating the data and
because the Unit was not currently working on it. Print-outs
from the three Core Surveys were obtained from the Evaluation
Unit. Tables were prepared that disaggregated the data by sex of
household head. Extension and Resources Surveys were
subsequently analyzed more easily because the programs were
rewritten by NSO and the data computerized. WIADP was able to
analyze five of the NSSA surveys: the three Core Surveys
(Household Compostion, Garden and Yield), Resources, and
Extension, because the data were available for analysis;
Print-outs from the remaining five surveys are still in progress
by the NSO.
RESULTS OF THE NSSA
Household Composition Survey
The Household Composition Survey collected demographic data
on the.number and age of residents, education, employment and
social status, as well as facts concerning the household head.
For the Survey, a household consisted of those people who
regularly eat from the same pot, and the head of the household is
the person who makes major decisions for the household. The
Household Composition Survey required that "The wife should be
listed as Head if the male of the household returns home less
frequently than once a month" (NSSA: enumerators' manual 1980).
Figure 1-1 in Chapter 1 shows each ADD and RDP in terms of
percentage of female heads, mean de facto household Size, mean
area cultiv-ted and number of households sampled. LADD averaged
because the Unit was not currently working on it. Print-outs
from the three Core Surveys were obtained from the Evaluation
Unit. Tables were prepared that disaggregated the data by sex of
household head. Extension and Resources Surveys were
subsequently analyzed more easily because the programs were
rewritten by NSO and the data computerized. WIADP was able to
analyze five of the NSSA surveys: the three Core Surveys
(Household Compostion, Garden and Yield), Resources, and
Extension, because the data were available for analysis;
Print-outs from the remaining five surveys are still in progress
by the NSO.
RESULTS OF THE NSSA
Household Composition Survey
The Household Composition Survey collected demographic data
on the.number and age of residents, education, employment and
social status, as well as facts concerning the household head.
For the Survey, a household consisted of those people who
regularly eat from the same pot, and the head of the household is
the person who makes major decisions for the household. The
Household Composition Survey required that "The wife should be
listed as Head if the male of the household returns home less
frequently than once a month" (NSSA: enumerators' manual 1980).
Figure 1-1 in Chapter 1 shows each ADD and RDP in terms of
percentage of female heads, mean de facto household Size, mean
area cultiv-ted and number of households sampled. LADD averaged
27% female household heads (FHHs) compared with 29% for all of
Malawi. LRDP showed 20.4% in the NSO corrected sample. However,
in the uncorrected print-outs used by WIADP for this Survey,
21.9% or 114 out of 520 households were female headed. Other
RDPs in LADD such as Dedza Hills and Ntcheu have 38% of their
households headed by women.
The marital status of FHHs and male headed households (MHHs)
is shown in Table 2-1. Unlike KRADD in the Northern Region where
62% of FHHs are widows and 18% are married (Spring 1981), in LRDP
39% of FHHs are married; 30% are separated or divorced; and 31%
are widows. There are no questions that provide information
about the location of the husbands, though one assumes they are
in Malawi (estates, urban areas or living with other wives on a
regular basis) or elsewhere. No information was collected
concerning remittances from or frequency of contact with
husbands. LRDP is located in the matrilineal/matrilocal areas of
Malawi. Table 2-2 shows that FHHs have lived in their village as
long or longer than MHHs.
Concerning education, most FHHs (72%) have no education
compared with 36% of MHHs. The 28% of the FHHs with some
education are divided equally between vernacular (Chichewa) and
some primary school education. Only 1% of FHHs have completed
primary school compared to 8% of MHHs. Secondary school was
attended by 1% of MHHs and no FHHs (Table 2-3).
Thirty six percent of MHHs have attended farming courses
compared to only 10% of FHHs; few household heads have attended
residential courses (Table 2-4). Other information not given in
the tables show that no FHHs had vocational training whereas 5%
MARITAL STATUS OF HOUSEHOLD HEADS, LRDP NSSA (PERCENTAGES)
MHH=406
FHH=114
non polygynist* 72 39
polygynist 24 --
separated 2 18
divorced 1 12
widowed 1 31
never married 1 1
Total % 101 101
* A man with more than one wife is recorded as a polygynist.
A woman married to a polygynous husband is recorded as a non-polygynist.
TABLE 2-2
NUMBER OF YEARS IN THE VILLAGE, LRDP NSSA (PERCENTAGES)
MHH=406
FHH=114
0- 5 years 10 3
6-10 years 7 7
11-20 years 10 10
21-40 years 45 43
40+ years 27 .38
Total % 99 101
TABLE 2-3 SCHOOL EDUCATION OF HOUSEHOLD HEADS, LRDP NSSA (PERCENTAGES)
MHH=406
FHH=114
No education 36 72
Vernacular 23 14
Some Primary 31 14
Primary Completed 8 1
Some Secondary 1
Total % 99 101
TABLE 2-1
S of MHHs did. Two percent of FHHs had experience on farming
estates compared with 6% of MHHs.
The wage employment histories differed significantly for
S MHHs and FHHs with 72% of the MHHs compared with 6% of the FHHs
having wage laboy experience. Of the males, 4Z% had two to five
e:: years; 12% had tVb years; and 17% had six or more years
S experience (Tablf 2-5).
The question'bn traditional status showed that 14% of MHHs
and 5% of FHHs had some traditional status. Traditional status
categories are Aaguely.defined, and- it is difficult .to tell if
one or both sexes were queried properly. Enumerators were simply
told to "make a 'ist of the positions of traditional status" in
their field notebooks. Non-traditional status was acquired by
33% of MHHs and 13% of FHHs. One assumes since non-traditional
statuess were specified as minister, local political party
member, and project committee officers, that women's statuses
such as midwife were not counted (Table 2-5).
-Resources Survey
The Resources Survey measured distances to government and
T infrastructural facilities within LRDP in three broad categories:
7 less than 2 kilometers, 2-8 kilometers and more than 8
t kilometers. Table 2-6 shows there are few differences between
the male and female heads, but female heads tend to be closer to
improved water supplies. Most households tend to be within 2
r- kilometers of improved water, firewood supply and a grocery
store. The majority of households are between 2 and 8 kilometers
TABLE 2-4 ATTENDANCE OF FARMING COURSES, LRDP NSSA (PERCENTAGES)
MHH=406
None 65 90
Day 29 9
Residential 4 1
Both 3
TABLE 2-5 WAGE EMPLOYMENT AND STATUS, LRDP NSSA (PERCENTAGES)
Wage Employment
MHH=406
FHH=114
no. experience 29 94
2 years 12 2
2-5 years 42 2
6-10 years 11 1
10+ years 6 1
Status
No status
Traditional status
Non-traditional .status
TABLE 2-6
APPROXIMATE DISTANCE TO CLOSEST FACILITIES
FROM HOUSEHOLDS, LRDP NSSA (PERCENTAGES)
2km
2-8km
MHH=80 FHH=53
MHH=80 FHH=53
MHH=80 FHH=53
Improved Water 78 91 14 9 8 0
Firewood Supply 76 72 17 26 7 2
Medical Dispensary 9 17 58 53 33 30
Under 5 Clinic 22 23 67 64 10 11
Primary School 58 47 38 49 5 4
Secondary School 0 0 21 9 79 91
Training Centre 8 4 59 51 32 45
ADMARC Market 21 23 68 64 10 13
Grocery Store 53 60 45 34 3 6
Dip Tank 5 28 91 64 4 8
FHH=114
8km
from a medical dispensary, Under 5 Clinic, Training Center,
Government (ADMARC) Market, and cattle dip tank. Primary schools
are less than 2 km for most MHHs and divided between the first
two categories for the FHHs.
The Resources Survey also measured ownership of household
items and farm equipment as well.as the condition of the house.
MHHs own more household goods than FHHs (Table 2-7a). MHHs are.
four times more likely to own a bicycle (32% compared with 8%)
and own twice as many chairs, tables, beds and lamps as FHHs
(Table 2-7a). Sixteen percent of MHHs own a radio compared with
6% of FHHs. Only 4% of both types of households own sewing
machines. Overall MHHs have more improved housing than FHHs
(Table 2-7b), but 8% of FHHs have sun dried bricks compared with
3% of MHHs. MHHs have more tin roofs and glass windows. Sixty
percent of MHHs have latrines compared to only 38% of FHHs. The
low frequencies of latrines in households headed by women has
been noted elsewhere (Spring 1981a). Latrines have to be redug
and replaced more frequently than other parts of the house and
FHHs lack labor to do so.
Table 2-7c shows that all households have the basic farm
implement, the hoe, and most (63%) of the MHHs have a watering
can compared with only 26% of the FHHs. Other farm equipment is
rarely owned but 13% of MHHs have an ox-cart compared to 8% of
FHHs.
Extension Survey
TABLE 2-7&. TYPES OF HOUSEHOLD ITEMS OWNED
LRDP NSSA (PERCENTAGES)
MHH=76
BY HOUSEHOLDS,
FHH=53
Bicycle 32 8
Chair 42 19
Table 32 11
Bed 29 15
Lamp 43 24
Watch/Clock 10 8
Radio 16 6
Sewing Machine 4 4
Stove 4 2
None 0 0
TABLE 2-7b. CONDITION OF THE MAIN HOUSE, LRDP NSSA (PERCENTAGES)
MHH=76
FHH=53
Sun dried Bricks 3 8
Fired Bricks 1 2
Latrine 60 38
Glass Windows 26 9
Cement Floor 3 2
Tin Roof 13 6
TABLE 2-7c TYPES OF FARM EQUIPMENT OWNED, LRDP NSSA (PERCENTAGES)
MHH=80
FHH=53
Hoe 100 100
Watering Can 63 26
Sprayer 0 0
Ox-Cart 13 8
Plough 3 2
Ridger 3 2
Wheel Barrow 1 0
The Extension Survey was given to seven of the twenty
households in each of the 27 strata in LRDP and 7 of the possible
189 were not usable, so the sample consists of 182 households, 35
of which are FHHs and 147 were MHHs. Additionally 135 wives of
MHHs were queried. The Extension Survey asked about the sources
of advice, types of farmer contacts with extension workers
(personal and field visits, group meetings, demonstrations) and
exposure to Extension Aids programs (radio programs, cinema and
puppet shows). In addition farmers were questioned about the
topics on which they received advice.
Table 2-8 shows the sources of advice for Household Heads
and Wives and includes the percentage of those who received no
advice. Forty five percent of MHHs received some agricultural
advice compared to 27% for FHHs and 26% for Wives. Table 2-9
shows sources of advice for recipients only. The data on the
sources of advice for the major extension topics shows that
extension workers provide the major source of advice for both men
and women farmers. Slightly more FHHs (14%) than MHHs and Wives
received more advice from other farmers/friends and traditional
leaders. For both men and women little agricultural advice was
obtained from yellow-van puppets, cinema shows, traditional or
party leaders, and agricultural shows.
Table 2-10 shows the type of contact by extension agents for
those being contacted. More men than women receive personal
visits by extension workers. Forty one percent of MHHs were
personally contacted compared with 28% of their wives and 23% of
FHHs. Group meetings tended to reach more farmers than personal
contacts, although women did not benefit as much as men. The
TABLE 2-8 SOURCE OF EXTENSION ADVICE, LRDP NSSA (PERCENTAGES)
WIVES=135
No Advice
Other Farm/Friend
Party Leader
Traditional Leader
Extension Worker
Farmers' Training Course
Radio Prograrm
Yellow-Van Cinema Show
Agricultural Show
Yellow-Van Puppet Show
Other Sources
Total %*
* May not total 1007. due to rounding
TABLE 2-9
SOURCES OF ADVICE ON EXTENSION TOPICS OF THOSE
RECEIVING ADVICE, LRDP NSSA (PERCENTAGES)
MHH=147
FHH=77
WIVES=135
Other Farmer/Friend 5 14 9
Party Leader 1 3 3
Traditional Leader 2 6 3
Extension Worker 75 58 66
Training Course 4 6 6
Radio Program 7 5 6
Yellow-Van Cinema 2 3 4
Agricultural Show 1 1 0
Yellow-Van Puppets 1 1 0
Other Sources 1 1 3
Total 7 99 99 100
MHH=147
FHH=35
. 99
__
data show that 25% more men were contacted by meetings compared
with personal visits (Table 2-10). Women benefit considerably
more by meetings than personal visits. However, more men attend
such gatherings with greater frequency. Sixty six percent of
male heads were contacted by extension agents at group meetings,
compared to 44% of their wives and 49% of FHHs.
Relatively few male or female farmers saw extension
demonstrations. However, twice as many men. as women learned
through this method. Field visits also reached a smaller
proportion of farmers than personal visits or group meetings;
again women appear to be contacted less than men. One reason may
be that women are not summoned to listen as the extension agent
instructs the men he finds working in the field. Thirteen
percent of the MHHs were visited in the field compared with 9% of
wives and 6% of FHHs.
The respondents were asked on which of eleven major
extension topics they had received advice (Table 2-11). For most
topics, except home economics, MHHs received more advice than
Wives or FHHs. The most frequent advice to men was on land and
crop husbandry and credit; women most frequently received advice
on crop husbandry. Crop husbandry was the most commonly taught
subject for both men (76%) and women (63%), although wives (47%)
received less advice than household heads. Only small
differences were found between men (25%) and women (22% for FHHs
and Wives) for advice on vegetable growing. This could be
because this subject is covered by female extension agents. Land
Husbandry and Agricultural Credit are two commonly taught
subjects for which women tended to receive less instruction than
TABLE 2-10
TYPE OF CONTACT FROM EXTENSION AGENTS TO THOSE HOUSEHOLD
HEADS AND WIVES RECEIVING ADVICE, LRDP NSSA (PERCENTAGES)
MHH=147
FHH=35
WIVES=135
Personal Visit 41 23 28
Group Meeting 66 49 44
Demonstration 13 6 6
Field Visit 13 6 9
TABLE 2-11 TYPE OF ADVICE RECEIVED BY THOSE RECEIVING
ADVICE, LRDP NSSA (PERCENTAGES)
EXTENSION TOPIC MHH=147 FHH=35 WIVES=135
Land Husbandry 61 34 28
Animal Husbandry 42 31 18
Crop Husbandry 76 63 47
Vegetables 25 22 22
Woodlots 47 9 14
Credit 64 43 33
Food Storage 31 9 19
Agricultural Show 29 6 12
Farmer Clubs 32 11 13
Training 34 11 16
Home Economics 25 26 39
4.5 2.7 2.6-
Total number or topics
Average # of topics/farmer
o00
4.5
2.7
2.6
men. About half as many female heads and wives (34% and 28%)
learned Land Husbandry compared with male household heads (61%).
Wives (33%) tended to receive about half the instruction on
credit as their husbands (69%). This may be due to beliefs that
the household head should be responsible for credit within th.e
family. Home Economics was the one topic in which more women
than men received advice. Twenty five percent of MHHs and 26% of
FHHs were taught home economics versus 39% of wives. The average
number of extension topics was greater for men (4.5%.) than for
women (2.7 for FHH and 2.6 for Wives).
Garden Survey
The Garden Survey of the NSSA was conducted from January to
May of 1981. The Survey measured the area of fields cultivated
by selected households and collected information on their land
tenure and land husbandry practices. The Evaluation Officer of
LRDP was responsible for collecting the data from the LRDP and
the other four projects in LADD. Data given below is from the
NSSA sample of 519 households of which 113 were identified as
FHHs (Data for one household were not available for this survey).
The data show that the average number of gardens the FHHs
cultivate is less than the average number for MHHs. More than
60% of FHHs cultivate only one or two gardens, whereas less than
50% of MHHs do so. Only 12% of FHHs cultivate four or more
gardens, compared with 30% of MHHs. These statistics also reveal
the heterogeneity of both FHHs' and MHHs' land holdings. Table
2-12 shows that proportionally twice as many FHHs as MHHs
cultivate less than 1.00 hectare. Furthermore, only half the
percentage of FHHs as MHHs cultivate more than 2.50 hectares.
Half the FHHs (50%) and MHHs (61%) cultivate between 1 and 2.49
hectares, but a larger proportion of FHHs cultivate less land
than MHHs.
A garden is considered by the NSSA to be a continuous piece
of land comprised of plots of varying crop enterprises. No
differences are detected between MHHs and FHHs in the size'of
their individual gardens or plots. Gardens average 0.6 hectares
and plots average 0.4 hectares. The average number of. plots per
garden are also very close for FHHs and MHHs.
A sizable difference was found in the average number of
gardens per household: 2.3 for FHHs and 2.9 for MHHs. This 26%
increase in the number of MHHs' gardens is correlated with 24%
larger average holding: 1.8 hectares for MHHs compared with 1.4
hectares for the FHHs.
Table 2-13 shows a large difference in the source of
permission to use gardens. Over twice as many gardens of MHHs as
gardens of FHHs were acquired from a male relative by birth.
Conversely, over twice as many of the FHHs gardens were obtained
from a female relative by birth. These relationships imply that
women tend to give their gardens to women in their lineage, and
men tend to give gardens to men in their lineage. No major
differences existed in acquiring gardens from people other than
relatives by birth.
The previous users of the gardens show the same patterns as
the source of permission. Male relatives by birth previously
used 35% of the MHHs' gardens and 18% of the FHHs' gardens.
Females related by birth were the previous users of 49% of the
FHHs' gardens and 21% of the MHHs' gardens. It can be inferred
from this correlation that the previous user was usually the one
who gave permission. For both MHHs and FHHs, 17% of the gardens
were cleared from bush so no previous operator existed.
It seems that both MHHs and FHHs have controlled their
gardens for similar number of years. Gardens controlled for less
than five years comprised 38% of the FHHs' gardens and 45% of the
MHHs' gardens. Likewise,the distance from the household to the
garden seemed to be evenly distributed between MHHs.and FHHs.
Gardens between 500 to 2000 meters from the household made up 50%
of the FHHs' gardens and 48% of the MHHs' gardens.
Considering cropping patterns, Table 2-14 shows that both
MHHs and FHHs plant tobacco and improved maize, cash crops not
generally grown for home consumption. The Survey found that 6%
of the land for the average FHH was planted in tobacco and
improved maize while the average MHH grew about twice that
percentage. The areas planted to local maize groundnuts, pulses
and sweet potatoes were similar for both MHHs and FHHs.
Although the differences were not great, more FHHs had fewer
trees than MHHs. Households with 1 to 19 trees comprised 76% of
the FHHs and only 66% of the MHHs. Only 4% of the FHHs owned
more than 30 trees compared with 14% of the MHHs.
No major differences could be found in the methods in which
FHHs or MHHs ridge or prepare the soil for their gardens. Plots
ridged by hand comprised 87% and 85% of the plots of the FHHs and
MHHs. Ridges were prepared on-contour for 77% of the FHHs plots
and 80% of the MHHs' plots.
TABLE 2-12 CLASSES OF HOLDING SIZE FOR LRDP NSSA
HOLDING SIZE
MHH
FHH
Households
TOTAL MHH=406
FHH=113 TOTAL=519
Percentages
0.00 0 0 0 0 0 0
0.01 0.99 82 45 127 20 40 24
1.00 2.49 246 57 304 61 50 58
2.50 & above 78 11 89 19 10 17
Total Households 406 113 519 100 100 99
Total Hectares .. 730 159 839 -
Hectares Per Household 1.8 1.4 1.7 -
TABLE 2-13 SOURCE OF GARDENS, LRDP NSSA
MHH FHH TOTAL MHH FHH TOTAL
Plots Percentages
Male relative by birth 498 48 546 42 18 38
Female relative by birth 240 119 359 20 46 25
Male relative by marriage 78 23 101 6 9 7
Female relative by marriage 143 15 158 12 6 11
Village Headman 136 36 172 12 14 12
Scheme/Project 0 0 0 0 0 0
Borrowed 69 17 86 6 7 6
Other 13 1 14 1 0 1
TOTALS 1177 259 1436 99 100 100
TABLE 2-14 AREAS PLANTED TO MAJOR CROPS IN LRDP NSSA
MHH FHH TOTAL MHH FHH TOTAL
Ha. 7.
Tobacco 0.18 0.09 0.16 10 6 10
Improved Maize 0.24 0.09 0.21 14 6 12
Local Maize 0.90 0.79 0.87 51 56 52
Groundnuts 0.40 0.48 0.40 23 30 24
Pulses 0.02 0.01 0.02 1 1 1
Sweet Potatoes 0.02 0.01 0.02 1 1 1
Totals 1.76 1.42 1.68 100 100 100
The results show that the FHHs have less land than MHHs
because they cultivate fewer gardens. The sizes of those gardens
are the same for both MHHs and FHHs. Practically all MHHs are
married and, therefore, usually have an extra adult to work in
agriculture. In contrast, nearly two thirds of FHHs are not
married and so are missing the labor of a spouse. Despite this
labor shortage, many FHHs cultivate as much or more land than
many MHHs who have the added labor of a wife or wives.
Perhaps the reason that FHHs have fewer gardens is the
source of permission to use the land. Women tend to acquire land
from female relatives by birth, and men gain more land through
their male relatives by birth. Presently, although the system is
matrilocal near Lilongwe, the married couple will often choose
to live in the village of the spouse who can offer the most land.
Since almost all MHHs are married, they can make this choice. In
contrast, only one third of the FHHs are married and so most do
not have the option to acquire gardens through the husband's
relatives.
It is commonly thought that women do not grow cash crops and
are restricted to growing food crops consumed at home. This
survey discovered that 14% of the FHHs grow tobacco and 8% grow
improved maize. Tobacco in particular is thought to be a "man's
crop" and, therefore, technical aid and credit assistance are
targeted towards men. The fact that so many FHHs have overcome
these biases is proof that women can be innovators and adopt more
lucrative technologies.
No differences were found in the ways which FHHs and MHHs
prepare or ridge their fields. This supports the idea that they
are equal in their skill at farming because their practices are
the same. Major differences were not found between FHHs and MHHs
in the distance from garden to household, garden size, or years
the garden was controlled. It can be inferred that the natural
and social factors which influence farming are the same for both
FHHs and MHHs. This again implies that skill in farming is
similar for FHHs and MHHs.
It can be concluded that the differences between MHHs amd
FHHs are economic and not ability to farm. Women acting as heads
of households are responsible for growing about half the amount
of tobacco and improved maize as their male counterparts. This
is despite the fact that only 12% of credit holders in LRDP are
women. Many FHHs farm land areas similar to MHHs despite a
shortage of labor.
Yield Survey
The Yield Survey is an extension of the Garden Survey;
enumerators physically harvested a small area within each plot
measured in the Garden Survey. In LRDP, major crops harvested
were maize, groundnuts, and tobacco. The first two crops are
analyzed here as -the number of FHHs in the sample is too small to
be significant. Additional questions in the Yield Study focused
on the timing of soil preparation, planting, weeding, and the use
of plant nutrients or pesticides.
Certain maize and groundnut tables are chosen here that
might show interesting comparisons between yield plots of female
and male household heads. All quantities are converted to
percentages, and subjected to chi-square analysis. For some
tables, the chi-square variation is partitioned between
categories according to the method of L.A. Goodman (Blalock
1979). Using Table 2-16 as an example, chi-squared is equal to
2
13.76 (x2-13.76). Since the probability of a chi-squared
2
relationship equals 99% (P(x )-0.99), it can be 99% certain that
a relationship exists between head of household and source of
maize seed.
The data shows that almost all farmers (97%) grew local
maize, followed by groundnuts (84%); a third of the households
cultivated improved maize and tobacco, with slightly more than a
fifth growing sweet potatoes and pulses (Table 2-15). Female
headed households in LRDP tended to have less diverse cropping
patterns than MHHs. About 30% more MHHs than FHHs grew improved
maize, and the same trend is seen with tobacco. Both improved
maize and tobacco are primarily cash crops. Most households who
grow improved -maize also cultivate local maize for home
consumption, and the few households who did not raise local maize
probably grew exclusively improved maize. Table 2-15 also shows
that slightly more MHHs than FHHs grew sweet potatoes and pulses.
The opposite is true with groundnuts since slightly more FHHs
cultivated this crop.
Table 2-16 considers the sources of maize and groundnut
seed. Three fourths of the farmers used their own maize seed;
the remaining fourth obtained their seed from a Project credit
package, government market (ADMARC) or elsewhere. Groundnut
seeds are obtained by 52% of farmers from their own supply, but
48% obtained theirs elsewhere: 35% from Project sources, 3% from
MAJOR CROPS GROWN, LRDP NSSA (PERCENTAGES)
MHH=406
FHH=113
TOTAL=519
Local Maize 97 99 97
Improved Maize 41 11 35
Groundnuts 83 88 84
Tobacco -42 14 36
Sweet Potato 23 13 21
Pulses 25 18 23
TABLE 2-16:
SOURCES OF MAIZE AND GROUNDNUT SEED,
LRDP NSSA (PERCENTAGE OF PLOTS)
Maize
MHH=933 FHH=198
Total=1131 MHH=476
Groundnuts
FHH=122 Total=598
Self Grown 85 74 76 63 49 52
Credit Package 4 14 12 25 37 35
ADMARC 2 3 3 4 3 3
Other 8 9 9 7 11 10
TOTAL 99 100 100 99 100 100
XZ =13.76
P(X2)= 0.99
TABLE 2-17:
X Z =9.31
P(X 2)=0.97
CROP MIXTURES IN GROUNDNUT PLOTS,
LRDP NSSA (PERCENTAGE OF PLOTS)
MHH-471
FHH=127
Total=598
Pure Stand 98 96 96
With Maize 2 1 1
With Pulses 0 1 1
With Other 1 2 2
TOTAL 101 100 100
X2 = 3.34
P(X2)= 0.06
TABLE 2-15
ADMARC and 10% from other sources.
It can be deduced from Table 2-16 that FHHs have less access
to credit seed than do MHHs. About 10% more maize plots of MHHs
were planted with seed obtained via credit packages. This
corresponds to self.-grown seed planted on nearly 10% more maize
plots of FHHs which may be related to greater use of local maize.
The same pattern is seen with groundnuts in which over 10% more
plots of FHHs were planted with self-grown seed, and over 10%
more plots of MHHs were planted with seed from credit packages.
Data for both maize and groundnuts produced a significant
chi-squared value which implies differences between source of
seed for FHHs and MHHs.
In LRDP most crops are planted in pure stands rather than
interplanted. This is not true in many other areas of Malawi,
especially where holding size is small. Table 2-17 shows that
96% of the groundnut crop is pure stand and that there are
virtually no differences for the MHHs and FHHs. Table 2-18 shows
that most farmers prepared the soil for their maize gardens in
October in the 1980 cropping year, and 85% prepared the soil by
November. Few differences are found between the types of
households. Usually groundnut fields are prepared after maize;
it can be seen in Table 2-18 that 49% of the groundnut plots of
FHHs were first prepared before November compared with 38% of
MHHs. This difference largely results from more groundnut plots
of FHHs being first prepared in October (37% compared with 25%
for MHHs).
The time of planting for maize and groundnuts appears very
similar for both FHHs and MHHs (Tables 2-19 and 2-20). The
TABLE 2-18
MONTH OF FIRST SOIL PREPARATION FOR MAIZE AND
GROUNDNUT PLOTS, LRDP NSSA (PERCENTAGE OF PLOTS)
Maize
MHH=907 FHH=202
TOTAL=1109
Groundnuts
MHH=467 FHH=126 TOTAL=593
August 8 4 7 2 4 2
September 14 9 13 11 8 10
October 37 46 39 25 37 27
November 26 22 25 19 19 19
December 10 12 10 37 28 35
January 2 2 2 4 4 4
Other 3 4 3 3 0 2
TOTAL 100 99 99 101 100 99
X2 = 12.00
P(X2)= 0.94
TABLE 2-19.
X2 = 15.35
P(X2)= 0.98
TIME OF PLANTING FOR MAIZE PLOTS
LRDP NSSA (PERCENTAGE OF PLOTS)
MHH-918
Maize
FHH=201
TOTAL=1119
Nov. 1-15 20 20 20
Nov. 16-30 30. 34 33
Dec. 1-15 31 25 26
Dec. 16-31 9 13 12
Other 10 8 8
TOTAL 100 100 99
X2= 5.79
P(X2)= 0.78
TABLE 2-20 TIME OF PLANTING FOR GROUNDNUT PLOTS
LRDP NSSA (PERCENTAGE OF PLOTS)
MHH=918 FHH=201 TOTAL=1119
October 1 1 1
November 15 14 14
December 1-15 49 44 45
December 16-30 .27 33 32
January 8 8 8
TOTAL 100 100 100
X2 = 1.84
P(X2)= 0.23
value of chi-squared implied no relationship exists between the
head of household and when maize or groundnuts were planted.
This table shows that about half of the maize plots of both FHHs
and MHHs were planted before December, compared with less than
one fifth of groundnut plots. Most farmers plant maize before
groundnuts.
No large differences were found between FHHs and MHHs for
the timing and number of weedings for maize and groundnuts. The
significant chi-squared interaction in Table 2-21 should be
related to MHHs weeding slightly more maize plots twice, and to
more plots of FHHs being.weeded between 4 to 6 weeks or not at
all. Table 2-22 also displays only slight differences between
household types for weeding practices of groundnut plots based on
the head of household.
Thirty seven percent of MHHs and 28% of FHHs apply various
2
types of fertilizer to maize (x2 .99). Table 2-23 shows that as
a first fertilizer 20:20:0 was applied to 18% of the maize plots
of MHHs versus 9% for FHHs. Seventy two percent of the maize
plots of FHHs did not receive any fertilizer compared with 63%
for MHHs. The difference between household types using 20:20:0
fertilizer and no fertilizer accounts for 96% of the chi-squared
variation in first fertilizer used. The two nitrogen
fertilizers, Sulphate of Ammonia and Calcium Ammonium Nitrate,
were used the same regardless of household head. Manure was used
as a fertilizer on only 4% of the maize plots and 0% of the
groundnut plots surveyed. Extension agents visited 0% of the
sampled plots of maize and groundnut plots in this survey.
For most plots of both FHHs and MHHs, plant populations were
TABLE 2-21
TIME OF WEEDING FOR MAIZE AND GROUNDNUT
PLOTS, LRDP NSSA (PERCENTAGE OF PLOTS)
Weeks after planting
Maize
MHH=929 FHH=201
Groundnuts
Total=1130 MHH=447 FHH=128
None
0 to 3
4 to 6
0 to 3 & 4 to 6
beyond 6
0 to 3 & beyond
4 to 6 & beyond
0 to 3 & 4 to 6
TOTAL 7
X2 = 21.42
P(X2)= 0.99
TABLE 2-22
X2 = 5.74
P(X2)= 0.43
NUMBER OF WEEDINGS FOR MAIZE AND GROUNDNUT
PLOTS, LRDP NSSA (PERCENTAGE OF PLOTS)
Maize
MHH=929 FHH=201
Total=1130
Groundnuts
MHH=477 FHH=128
Total=605
0 2 6 3 4 5 4
1 72 74 72 76 79 76
2 26 20 23 1 0 1
3 1 0 1
TOTAL 100 100 101 101 101 100
X2 = 9.25
P(X2)= 0.99
TABLE 2-23
X2 = 2.49
P(X2)= 0.52
TYPE OF FIRST FERTILIZER APPLIED TO MAIZE
PLOTS, LRDP NSSA (PERCENTAGE OF PLOTS)
MHH=742
FHH=162
Total=904
None 63 72 65
20:20:0 18 9 16
Sulphate of Ammonia 11 11 11
Calcium Ammonium Nitrate 3 2 3
Mixture 5 6 5
TOTAL 100 100 100
X2 = 10.14
P(X2)= 8.96
2
23
39
10
10
6
10
ond 6
Total: :
6
6
& bey
100
1UU
LUU
_ ___
---
below levels recommended for optimum yield of maize and
groundnut. Farmers may plant less due to the lower soil
fertility in the fields of most LRDP farmers compared to the
research trials which formulated the recommended plant population
levels--but this is conjecture--as probably farmers are not aware
of these technical differences. Only about 40% of the maize
plots sampled (Table 2-26) approach the optimum of 3.6 plants per
square meter (plants/m2) recommended for fertilized maize (MOA
1979-80). Similarly, only about 25% of the sampled groundnut
plots approximate the suggested level for certified (Chalimbana)
2
groundnut -seed of 7.4 plants/m2 (personal communication with
Chitedze groundnut agronomist).
Recognizing the overall lower yields, maize and groundnut
plots grouped according to plant population varied less than 5%
between type of household head (Table 2-24). This implies that
most farmers in both types of households cultivate maize and
groundnuts at the same spacing between and within the rows. The
proportion of plots in the medium ranges of maize yields was
similar regardless of.household head (Table 2-25). The variation
in number of plots was less then 5% between FHHs (61%) and MHHs
(64%) for yield classes ranging from 500'to 2,499 kilograms per
hectare. This implies that most of the maize plots of both
household types have comparable growing conditions and therefore
produce comparable yields. Although about 80% of the total plots
had similar maize yields regardless of household heads,
proportionately more plots of MHHs achieved the highest yields,
and a greater fraction of maize plots of FHHs ranked in the
lowest yields. Of the maize plots managed by male household
TABLE 2-24
PLANT POPULATIONS FROM MAIZE AND GROUNDNUT
PLOTS, LRDP NSSA (PERCENTAGE OF PLOTS)
Maize
MHH=918 FHH=200
Total=1118
Groundnuts
MHH=479 FHH=125
Total=604
0-0.9 10 10 10 12 16 13
1-1.9 7 11 8 2 2 2
2-2.9 38 40 38 16 18 16
3.3.9 33 28 32 27 22 26
4-4.9 11 8 10 22 24 22
5-over 1 2 1 22 1i 21
TOTAL 100 99 99 101 100 100
TABLE 2-25
MAIZE YIELDS
kg/ha
X2 = 11.7 X2 = 3.30
P(X2)= 0.96 P(X2)= 0.34
MAIZE YIELDS FROM PLOTS, LRDP NSSA (PERCENTAGE OF PLOTS)
MHH=844
FHH=200
TOTAL=1044
0- 499 10 30 14
500- 999 18 22 19
1000-1499 21 17 20
1500-1999 15 10 14
2000-2499 10 12 10
2500 & above 26 8 22
TOTAL 100 99 99
X2 70.25
P(X2)= 0.99
TABLE 2-26 GROUNDNUT YIELDS FROM PLOTS, LRDP NSSA (PERCENTAGE OF PLOTS)
GROUNDNUT YIELDS
kg/ha
MHH=400
FHH=98
TOTAL=498
1- 99 12 11 11
100-199 32 30 31
200-299 26 25 25
300-399 14 14 14
400-499 6 11 10
500 & above 10 8 9
TOTAL 100 99 100
X2 = 2.17
P(X2)= 0.17
PLANTS/m
heads, 26% yielded above 2500 kg/ha. compared with only 8% for
FHHs. At the lower end of the yield spectrum, 30% of the maize
plots of FHHs produced below 500 kg/ha. versus only 10% for MHHs.
No large differences could be found between household types
for groundnut yields (Table 2-26). Only about 10% of the
harvested plots yielded above 500 kg/ha. which could be related
to the low plant populations recorded in Table 2-24. The fact
that fertilizer was not applied to groundnuts would remove yield
advantages available to progressive maize growers.
For those crop operations which do not need access to
agricultural development inputs, few differences were apparent
between households headed by females or males. This uniformity
in farming practices implies that knowledge and skill with maize
and groundnuts is the same for both household types. However,
some FHHs may have less access to the extension services which
promote improved agriculture and therefore may be slower to adopt
innovations.
Pure stands of maize and groundnut were overwhelmingly
popular with both household types. The conditions which suppress
mixed cropping in the Lilongwe Plain affect both types of
households equally. Manure and pesticides are uncommon for both
MHHs or FHH's in LRDP and for maize or groundnut crops.
The timing of seasonal activities is dependent on the
agricultural environment and the farmer's preferences and
abilities. The great similarity in the timing of crop operations
implies that both types of households operate under comparable
conditions. One exception was that more groundnut plots of FHHs
were prepared earlier than those of MHHs. The reason may be that
more FHHs are unable to begin growing other cash crops and
therefore spend greater time on groundnuts as a cash crop.
Households headed by women tend to have one less working
adult because of the absence of a father or husband. They may
need to do agricultural day work for others to buy food. This
can increase the chances of labor shortages whbch could hinder
necessary crop operations. This might be the reason why a few
more maize plots of FHHs were weeded late or only once compared
with MHHs, who often have more available labor.
Fertilizer is neither recommended nor commonly used on
groundnuts, and this is evident by plant population levels of
farmers falling much below the optimum level. Fertilizer was
applied to about 40% of maize plots, which correlates with about
40% of maize plots approaching the recommended population. The
numerous factors which influence plant spacing seem to equally
affect female and male farm managers.
The similarity in groundnut yields between the two household
types could be due to the same disease/pest problems as well as
cultural practices, and so access to inputs would not be a
factor. Also, groundnuts are considered a "woman's crop", so
primarily women are growing the crop in both types of households.
In contrast, a larger proportion of maize plots managed by FHHs
produced the poorest yields. The same pattern is seen with the
best maize yields, which were achieved by a greater fraction of
plots of male household heads.
The women managers in the lowest maize yield ranges could
have faced labor constraints which prevented them from timely
weeding of certain plots. The households headed by men may have
56
more access to fertilizer because extension staff tend to deal
with men. MHHs with one or more wives have more available labor
than most FHHs. These factors may favor some MHHs to achieve a
greater proportion of maize plots with high yields.
CHAPTER 3
THE LILONGWE RURAL DEVELOPMENT PROJECT SURVEY
DESCRIPTION OF THE SURVEY
The Survey Instruments
Following the indicators used by Castro et_. al. (198.1),. Kydd.
(1982a, 1982b), the 1969-71 LRDP Farm Management Survey (1971,
1973), as well as the NSSA instruments, a series of 15 survey
instruments were designed by WIADP and FSAS for their 1982 LRDP
Survey. The relatively short length of time that the
interviewers were able to devote to data collection (one week per
household) was taken into account as was the fact that all crops
were already harvested. The following instruments were prepared
and administered:
1. HOUSEHOLD COMPOSITION: A listing of all members by sex,
age, relationship to household head, educational level
attained and current location.
2. NATALITY HISTORY: A history of women's reproductive
experiences and a listing for women and men of all children
born, their ages, sex, education and present location.
3. EDUCATION: A test of literacy in Chichewa and English.
4. MIGRATION AND WORK: Questions or migratory experience,
current sources of employment and income, and changes in
farming practices in the past decade.
5. STATUS AND RESOURCES: Questions on status, religiosity,
labor hired, use of maize mills, purchase of firewood,
extension visits, condition of main house, and ownership of
CHAPTER 3
THE LILONGWE RURAL DEVELOPMENT PROJECT SURVEY
DESCRIPTION OF THE SURVEY
The Survey Instruments
Following the indicators used by Castro et_. al. (198.1),. Kydd.
(1982a, 1982b), the 1969-71 LRDP Farm Management Survey (1971,
1973), as well as the NSSA instruments, a series of 15 survey
instruments were designed by WIADP and FSAS for their 1982 LRDP
Survey. The relatively short length of time that the
interviewers were able to devote to data collection (one week per
household) was taken into account as was the fact that all crops
were already harvested. The following instruments were prepared
and administered:
1. HOUSEHOLD COMPOSITION: A listing of all members by sex,
age, relationship to household head, educational level
attained and current location.
2. NATALITY HISTORY: A history of women's reproductive
experiences and a listing for women and men of all children
born, their ages, sex, education and present location.
3. EDUCATION: A test of literacy in Chichewa and English.
4. MIGRATION AND WORK: Questions or migratory experience,
current sources of employment and income, and changes in
farming practices in the past decade.
5. STATUS AND RESOURCES: Questions on status, religiosity,
labor hired, use of maize mills, purchase of firewood,
extension visits, condition of main house, and ownership of
CHAPTER 3
THE LILONGWE RURAL DEVELOPMENT PROJECT SURVEY
DESCRIPTION OF THE SURVEY
The Survey Instruments
Following the indicators used by Castro et_. al. (198.1),. Kydd.
(1982a, 1982b), the 1969-71 LRDP Farm Management Survey (1971,
1973), as well as the NSSA instruments, a series of 15 survey
instruments were designed by WIADP and FSAS for their 1982 LRDP
Survey. The relatively short length of time that the
interviewers were able to devote to data collection (one week per
household) was taken into account as was the fact that all crops
were already harvested. The following instruments were prepared
and administered:
1. HOUSEHOLD COMPOSITION: A listing of all members by sex,
age, relationship to household head, educational level
attained and current location.
2. NATALITY HISTORY: A history of women's reproductive
experiences and a listing for women and men of all children
born, their ages, sex, education and present location.
3. EDUCATION: A test of literacy in Chichewa and English.
4. MIGRATION AND WORK: Questions or migratory experience,
current sources of employment and income, and changes in
farming practices in the past decade.
5. STATUS AND RESOURCES: Questions on status, religiosity,
labor hired, use of maize mills, purchase of firewood,
extension visits, condition of main house, and ownership of
farm and household items.
6.' DISTANCES AND MAIZE PRODUCTION: Distance of household from
various important amenities and infrastructural facilities,
as well as measurements of granaries as an estimate of
stored maize, and an estimation of the length of time stored
maize would feed the family.
7. GARDEN LAND INVENTORY: A listing of all gardens controlled
by the household.
8. GARDEN LAND TENURE: Information on how the garden was
acquired and from whom.
9. GARDEN LABOR: A recall of those who worked on each crop by
operation.
10. GARDEN HISTORY: Major and minor crops grown in each garden
over a three year period, plus information on fertilizer
usage and source of fertilizer and seed.
11. MAIZE: Experience with different varieties.
12. CHANGE AND DEVELOPMENT: Use of LRDP services such as
training, credit, extension visits, amount and change in
livestock ownership, perceptions of development as a result
of LRDP.
13. FARM PLANNING AND MAIZE AGRICULTURAL KNOWLEDGE: Farmer's
plans for the coming agricultural season, sources of seed
and fertilizer, and knowledge of extension recommendations.
14. DIETARY SURVEY: A five day volumetric intake of the
household as a whole.
15. ANTHROPOMETRY: Measurement of all household members in
terms of height, weight and skinfold adiposity.
Data from all surveys except for the Dietary, Anthropometry,
Labor and parts of Maize Production and Change and Development
are analyzed here.
The Sample
Of the approximately 7000 households in the 1980-81 NSSA,
520 were located in LRDP. Half of these 520 households (260
households) were reinterviewed the next year (1981/82) in the
annual evaluation that is normally carried out by the Evaluation
Unit of LADD. From these 260 households, WIADP and FSAS selected
a stratified random sample of 102 households (6 households per
NSSA cluster in seventeen clusters) for the intensive survey.
Unlike the NSSA that only queried household heads, the LRDP
Survey designed by WIADP and FSAS was administered to male
household heads, their wives and female household heads in order
to obtain intrahousehold data as well as data on women farmers.
Personnel and Design
In order for WIADP and FSAS to conduct the LRDP Survey,
interviewers who-could live in the villages, speak the language
and carry out the detailed surveys were required. Twenty
students from Bunda College of Agriculture were hired during
their vacation period to collect the data. It was reasoned that
they could understand the nature of the Survey, learn how to
administer the instruments in a short time, provide, the necessary
skills in terms of language, anthropometry, dietary and surveying
techniques, and conduct themselves in an appropriate manner.
The LRDP Survey administered in August through September
1982 took into account the limited amount of time of the
interviewers and the available personnel in terms of supervising
the data collection from the two projects. The students were
brought to Chitedze Agricultural Research Station for a week of
training. The Survey was scheduled for the dry season following
the harvest in May-June. This timing is important to note
because it influenced various aspects of the data and its
collection.
1. Food supplies are plentiful during this post-harvest
season.
2. People have more leisure as it is the non-agricultural
season, and this facilitates answering long questionnaires.
However, people are involved in beer drinking and
ceremonies.
3. School children are home on holidays, and husbands who
work in agriculture on estates are likely to be home.
4. It is not possible to take plot yields, and exact garden
boundaries are not measurable.
5. Roads are easily accessible and the students could use
their bicycles to get around the villages; the two project
directors and five staff supervisors could travel easily to
check on the interviewers.
Analysis of the Data
The data were transferred to coding sheets and entered into
a storage program on a microcomputer in Malawi. Analysis
preceded after the data were transferred to a statistical program
on a mainframe computer at the University of Florida.
Sex-disaggregated data in terms of household heads, husbands and
wives, and women in male and female headed households are
presented whenever possible or appropriate. Of the 102
households, one household dropped out when t-he family went to
Mozambique in the middle of the Survey. The 101 households
studied contain 84 (83%) male headed households and only 17 (17%)
female ones which is lower than the NSSA. It is suspected that a
reason for this is the presence of husbands who ordinarily are
away working on estates. Since the Survey took place over a
short time period, it was not possible to apply the NSSA
definition of a female household head as one whose husband does
not return more often than once per month. Men who were present
during the LRDP Survey were counted as the household head if they
said they were. Additionally, the Survey queried the wives of
male heads, but only the wife who resided in the designated
household, was queried; co-wives were.not. Three female relatives
who lived in MHHs where the man was not married were counted as
"Wives".
DEMOGRAPHIC AND SOCIAL INDICATORS
Household Composition
Table 3-1 shows that two thirds of the MHHs are married
monogamously; 30% are polygynists; and 3% are not married.
Thirty five percent of FHHs are married; 35% are widows; and 30%
are divorcees. Table 3-2 shows that husbands of these married
female household heads are working in Malawi (18%), outside
Malawi (12%) or elsewhere (6%).
Although 30% of the male heads of households are polygynous,
only the wife or female relative residing in the household in the
survey was queried on survey instruments, giving a maximum total
of 84 "Wives". They are called "Wives" here even though 3 are
studied contain 84 (83%) male headed households and only 17 (17%)
female ones which is lower than the NSSA. It is suspected that a
reason for this is the presence of husbands who ordinarily are
away working on estates. Since the Survey took place over a
short time period, it was not possible to apply the NSSA
definition of a female household head as one whose husband does
not return more often than once per month. Men who were present
during the LRDP Survey were counted as the household head if they
said they were. Additionally, the Survey queried the wives of
male heads, but only the wife who resided in the designated
household, was queried; co-wives were.not. Three female relatives
who lived in MHHs where the man was not married were counted as
"Wives".
DEMOGRAPHIC AND SOCIAL INDICATORS
Household Composition
Table 3-1 shows that two thirds of the MHHs are married
monogamously; 30% are polygynists; and 3% are not married.
Thirty five percent of FHHs are married; 35% are widows; and 30%
are divorcees. Table 3-2 shows that husbands of these married
female household heads are working in Malawi (18%), outside
Malawi (12%) or elsewhere (6%).
Although 30% of the male heads of households are polygynous,
only the wife or female relative residing in the household in the
survey was queried on survey instruments, giving a maximum total
of 84 "Wives". They are called "Wives" here even though 3 are
not Wives but other female relatives of the unmarried MHHs.
The tables presented give the number of male headed
households (MHH), female headed households (FHH) and total
households (MHH and FHH), as well as data from the Wives who are
is not added to the total households. Data on Wives is presented
in order to compare intrahousehold answers.between husbands and
wives as well as to compare women in malee.and female headed
households. Where appropriate, data on the total number of women
are tallied.
Migration and Residence
Over half of the household heads reside in their natal
village (Table 3-3), but about one fifth respectively moved to be
with relatives or spouses. Almost as many wives moved to join
their husbands (43%) as were born in the villages (44%). Being
born in the village is reflected in the high number of years
household heads have lived there (Table 3-4). The international
and urban experiences of respondents show that many MHHs (57%)
have international work experience compared with only 12% of FHHs
and 5% of Wives. Similarly most MHHs (65%) but only 13% of Wives
and 30% of FHH have lived in urban areas previously.
The average number of people per household is 5.3, but this
figure obscures the fact that FHHs have 4.2 people per household
(Table 3-5a). Table 3-5a shows that the difference between MHHs
and FHHs is the absence of an adult man; the average number of
women and children does not differ in the two types of
households. These differences and similarities are reflected in
MARITAL STATUS OF HOUSEHOLD HEAD (PERCENTAGES)
MHH=84 FHH=17
TOTAL MHH
and FHH=101
Non-polygynist 67 35 62
Polygynist 30 25
Divorced 1 30 6
Separated 1 1
Widowed 1 35 7
Total % 100 100 101
TABLE 3-2 HUSBAND'S LOCATION AT TIME OF SURVEY (PERCENTAGES)
TOTAL MHH
MHH-84 FHH=17 and FHH=101
Present in household 87 -73
With other wife 8 7
Working outside Malawi 12 2
Working in Malawi 1 18 4
Elsewhere 3 6 4
FHH 65 11
Total % 99 101 101
TABLE 3-3 REASON FOR RESIDING IN PRESENT VILLAGE
(PERCENTAGES)
TOTAL MHH
MHH-76 FHH-16 WIVES-79 and FHH=93
Born here 54 41 44 52
Moved here to be with 21 24 10 22
relatives
Moved here because of 20 18 43 19
marriage
Other reasons 4 18 2 6
Total % 99 101 99 99
TABLE 3-1
LENGTH OF RESIDENCE IN PRESENT VILLAGE (PERCENTAGES)
MHH=76 FHH=16 WIVES =79
TOTAL MHH
and FHH=92
0-5 years 8 6 13 7
6-10 years 8 19 10 9
11-20 years 16 6 25 14
21-40 years 33 25 33 32
More than 40 36- 43 19 37
Total % 101 99 100 99
TABLE 3-5a HOUSEHOLD COMPOSITION BY AGE CATEGORIES
(AVERAGE NUMBER PER HOUSEHOLD)
TOTAL MHH
MHH-84 FHH=17 and FHH-101
Adult men (16 yrs. +) 1.5 .5 1.3
Adult women (16 yrs. +) 1.3* 1.5 1.3
Boys 6-15 yrs. .8 .8 .8
Girls 6-15 yrs. .8* .8 .8
Boys 0-5 yrs. .5 .2 .4
Girls 0-5 yrs. .7* .5 .6
Total Household Size 5.5 4.2 5.3
*n-83
TABLE 3-5b HOUSEHOLD COMPOSITION BY KINSHIP CATEGORIES
(AVERAGE NUMBER PER HOUSEHOLD)
TOTAL MHH
MHH-84 FHH=17 and FHH=101
Family of procreation 4.6 3.0 4.3
Family of orientation ..1 .1 .1
Other relatives .5 1.0 .6
Visitors .2 .1 .2
Hired servants/ .2 .2
laborers
Total Household Size 5.6** 4.2 5.4**
**Totals may differ from Table 5a due to rounding
TABLE 3-4
Table 3-5b. The family of procreation (mother, father and
children) is larger for MHHs where fathers are present. The
family of orientation (grandparental generation) is the same for
both types of households, but FHHs have slightly more other
relatives, and MHHs have hired servants and/or laborers living
with them.
Natality History
The reproductive experiences of women in male and female
headed households are tallied in terms of completed pregnancies,
reproductive wastage (miscarriages/.stillbirths), and child
mortality (neonatal deaths, deaths to 1 year and beyond). Table
3-6 shows virtually no differences between households. The
average number of completed pregnancies is 6.9, while the average
reproductive wastage is 0.4, and average number of living
children is 4.0.
Education
Although the educational experience of women is inferior to
that of men, and FHHs' education is inferior to Wives (Table
3-7a). However the educational experiences of children of these
households are not as dissimilar (Table 3-7b). Sixty four
percent of MHHs have attended some primary school compared with
42% of Wives and only 29% of FHHs. Although the number of female
compared to male children who attend school currently as well as
the total years for each sex is lower for girls than boys, the
Table 3-5b. The family of procreation (mother, father and
children) is larger for MHHs where fathers are present. The
family of orientation (grandparental generation) is the same for
both types of households, but FHHs have slightly more other
relatives, and MHHs have hired servants and/or laborers living
with them.
Natality History
The reproductive experiences of women in male and female
headed households are tallied in terms of completed pregnancies,
reproductive wastage (miscarriages/.stillbirths), and child
mortality (neonatal deaths, deaths to 1 year and beyond). Table
3-6 shows virtually no differences between households. The
average number of completed pregnancies is 6.9, while the average
reproductive wastage is 0.4, and average number of living
children is 4.0.
Education
Although the educational experience of women is inferior to
that of men, and FHHs' education is inferior to Wives (Table
3-7a). However the educational experiences of children of these
households are not as dissimilar (Table 3-7b). Sixty four
percent of MHHs have attended some primary school compared with
42% of Wives and only 29% of FHHs. Although the number of female
compared to male children who attend school currently as well as
the total years for each sex is lower for girls than boys, the
TABLE 3-6
AVERAGE NUMBER OF PREGNANCIES, BIRTHS AND DEATHS
WIVES =83
FHH-17
TOTAL WOMEN =100
Number of completed 6.9 6.8 6.9
pregnancies
Number of live births 6.5 6.0 6.4
Number of miscarriages/ .4 .4 .4
stillbirths
No. of neonatal deaths .5 .6 -
No. of deaths to 1 yr. 1.3 -
No. of living children 4.0 3.8 4.0
EDUCATION EXPERIENCE OF ADULTS (PERCENTAGES)
MHH=76 FHH=17 WIVES=83
TOTAL MHH
and FHH=93
None
Primary
Standard
Standard
Standard
Standard
Secondary
Form 1-2
TABLE 3-7b
CURRENT AND PREVIOUS CHILDREN EDUCATED (PERCENTAGES)
AND AVERAGE NUMBER OF YEARS OF SCHOOL ATTENDANCE
MHH* FHH* WIVES*
TOTAL MHH
and FHH*
% children currently
in primary school
% children currently
in secondary school
% of male children
who ever attended school
% of female children
who ever attended school
Average no. years male
children attended school
Average no. years female
children attended school
*Household frequencies vary depending on available data
1-2
3-4
5-6
7-8
36
16
11
21
16
Total %
101
101
.7
.9
.7
7.9
7.3
.6
.7
6.9
5.6
8.3
5.6
TABLE 3-7b
differences are not great.
It appears that the present generation is being educated
more than their parents. In the Malawian educational system,
there are 8 years of primary school (Standards 1-8 which are
roughly equivalent to U.S. grades 1-6) and 6 years of secondary
school (Forms 1-6 which are roughly equivalent to U.S. grades
7-12). The number of primary schools close to the villages is
increasing and is a direct result of the LRDP infrastructure.
Forty percent of households have primary schools within one mile
walking distance and 74% are within 3 miles as noted below (Table
3-12).
Household heads and Wives were asked if they could read and
if they answered affirmatively, they were given passages from the
national newspaper in Chichewa (the national language) and
English. Respondents were asked to read the selections as a test
of literacy. In terms of literacy, men and women differ.
Thirty-eight percent of MHHs, 82% of FHHs and 76% of Wives are
unable to read the selections (Table 3-8a). Of the MHHs, 23%
find the vernacular difficult; 38% find it easy; and 15% find
English difficult, whereas 6% find it easy. None of the FHHs are
able to read English at any level while 10% of Wives find it
difficult. Twelve percent of FHHs and 10% of Wives find Chichewa
difficult to read while 6% of each of these groups are able to do
so easily. English speaking ability was queried verbally, and
15% of husbands, and 5% of Wives spoke English compared with no
FHHs (Table 3-8b).
Status Positions
TABLE 3-8a
READING ABILITY IN CHICHEWA (VERNACULAR)
AND ENGLISH (PERCENTAGES)
MHH=77 FHH-17 WIVES=83
TOTAL MHH
and FHH=94
None 38 82 76 46
Vernacular-difficult 23 12 10 21
Vernacular-easy 17 6 4 15
Vernacular and English- .1 2 1
difficult
Vernacular easy-English 14 8 12
difficult
Vernacular and English- 6 5
easy
Total % 99 100 100 100
TABLE 3-8b ENGLISH SPEAKING ABILITY (PERCENTAGES)
TOTAL MHH
MHH-84 FHH-17 and FHH=101
None 79 100 82
Husband 15 13
Wife 5 4
Husband and wife 1 1
Total % 100 100 100
Self reported answers on church membership and attendance (as
opposed to observed behavior) indicate that most people consider
themselves Christians, but attendance may or may not be regular.
Women (FHHs and Wives) consider themselves members and attenders
much more than men (Table 3-9). Thirty five percent of FHHs hold
church positions compared with 16% of Wives and 13% of MHHs. The
denominations are not recorded. Most Protestant churches do not
allow their members to drink or brew beer, yet about 60% of all
samples participate in these activities; beer brewing is a major
source of income for women (see below).
The main categories of traditional status are village
headman, member of the Nyau (secret society), midwife, initiator,
diviner and healer. Non-traditional statuses include membership
in the Malawi Congress Party (MCP) as well as the LRDP Village
Planning Committees (VPCs). There are no participants in VPCs or
diviners/healers in the sample. Twelve percent of FHHs and 15%
of Wives are midwives, and 6% of each are MCP Women's League
Officers. Twenty-two percent of MHHs, no FHHs and 6% of Wives
are MCP members, and an additional 12% of MHHs are MCP Youth
League members (Table 3-10).
Resources and Access.to Infrastucture
Interviewers primarily observed rather than asked about the
resources of the households, using the NSSA categories (condition
of the main house and ownership of farm equipment and household
items) plus adding an additional item for women, ownership of the
CHRISTIANITY AND CHURCH ATTENDANCE (PERCENTAGES)
MHH-76 FHH=17 WIVES=80
TOTAL MHH
and FHH=93
Non-Christian 51 18 30 45
Christian-infrequent 8 18 9 10
attendance
Christian-frequent 28 29 45 28
attendance
Christian-church position 13 35 16 17
Total % 100 100 100 100
TABLE 3-10 TRADITIONAL AND NON-TRADITIONAL STATUSES
TOTAL MHH
MHH-78 FHH-17 WIVES-78 and FHH=95
Chief headman 16 12 15
Nyau society 27 3 22
Midwife 12 15 2
Diviner/initiator 1 6 1 2
Malawi Congress Party 22 6* 18
MCP Women's League Officer 6 6* i
MCP Youth League Officer 12 9
Other -- 1
*n-79
TABLE 3-9
"Mbumba uniform". Tables 3-11a-c record the percentage of
households owning these items.
The house structures of the MHHs are more improved than
those of the FHHs. Only a sixth of all households have metal
roofs ("iron sheets"), and a fifth have glass windows. FHHs have
fewer latrines (41%) than MHHs (69%) as shown in Table 3-11a,
probably because of the lack of labor to construct them. This has
been noted elsewhere in Malawi (Spring 1981b).
All farmers in the survey own hoes (the major agricultural
tool), a third of MHHs have watercans compared with 12% of FHHs.
More MHHs have ox carts (17%) than FHHs (6%), but plows and
ridgers are hardly differential (Table 3-11b). With the
exception of a bicycle (MHHs 31%), both types of households
have similar amounts of chairs, tables and radios, although MHHs
own more lamps (69%) than FHHs (53%).
A garment known as the "Mbumba uniform" is worn by women
when they attend Malawi Congress Party functions and dance for
the President of Malawi. It must be purchased, and all women are
eligible to wear it. Only 8% of women in MHHs owned the item
while no FHHs own them (Table 3-lic).
Other information not tabularized shows that two MHHs own
grinding mills and one is a storeowner. All households utilize
grinding mills for the processing of maize (although the
frequency of usage was not determined), and 10% of MHHs use mills
for other grains as well. Only 15% of households purchase
firewood. Virtually all households pay cash for milling and
firewood, obtaining the money from agricultural sales and other
sources.
RESOURCES (PERCENTAGES)
3-11a
CONDITION OF MAIN HOUSE (PERCENTAGES)
TOTAL MHH
MHH=84 FHH=17 and FHH=101
Iron sheets 17 12 16
Baked bricks 4. 12 5
Cement floor 7 6
Sunfired bricks 4 6 4
Glass windows 21 12 20
Latrine 69 41 64
3-11b FARM EQUIPMENT (PERCENTAGES)
TOTAL MHH
MHH-84 FHH-17 and FHH-101
Hoes 100 100 100
Ox cart 17 6 15
Plough 8 6 8
Ridger 4 6 4
Watercan 33 12 30
3-lie HOUSEHOLD ITEMS (PERCENTAGES)
Total MHH
MHH-84 FHH-17 and FHH-101
Chair 40 35 39
Table 33 35 33
Bicycle 31 26
Radio 20 23 21
Vehicle 1 1
Paraffin lamp 69 53 66
Mbumba uniform 8 7
TABLE 3-11
Distances
The interviewers were required to walk using pedometers
calibrated to their own stride to the closest infrastructural
facilities such as the grinding mill, medical dispensary, primary
school, Unit Center and ADMARC market as well as to the water
.supply. Table 3-12 shows that most people live less than a mile
from their water supply and other data show that more households
have improved taps as compared with an unimproved water supply.
Fifty seven percent of households are within 2 miles of a primary
school, and 50% are as close to a maize mill, -but only 17% are as
near to a dispensary, 27% to ADMARC, and 21% to a Unit Center.
About half of the dispensaries are permanent and the others are
mobile.
Extension Services
Some of the services and activities that are available to
farmers are training courses, membership in farming clubs and
groups, Achikumbi (good farmer) status, and extension visits.
Credit is given to farmers in clubs and groups. Table 3-13 shows
that most of the household members have never attended either a
day or residential training course, but 27% of MHHs have attended
courses (about equally divided between day and residential),
compared with 12% of FHHs for day courses only and 14% of Wives
mostly for day courses at the Unit Center. Similarly few FHHs
are members of farmers clubs/groups (12%), compared with 39% of
Distances
The interviewers were required to walk using pedometers
calibrated to their own stride to the closest infrastructural
facilities such as the grinding mill, medical dispensary, primary
school, Unit Center and ADMARC market as well as to the water
.supply. Table 3-12 shows that most people live less than a mile
from their water supply and other data show that more households
have improved taps as compared with an unimproved water supply.
Fifty seven percent of households are within 2 miles of a primary
school, and 50% are as close to a maize mill, -but only 17% are as
near to a dispensary, 27% to ADMARC, and 21% to a Unit Center.
About half of the dispensaries are permanent and the others are
mobile.
Extension Services
Some of the services and activities that are available to
farmers are training courses, membership in farming clubs and
groups, Achikumbi (good farmer) status, and extension visits.
Credit is given to farmers in clubs and groups. Table 3-13 shows
that most of the household members have never attended either a
day or residential training course, but 27% of MHHs have attended
courses (about equally divided between day and residential),
compared with 12% of FHHs for day courses only and 14% of Wives
mostly for day courses at the Unit Center. Similarly few FHHs
are members of farmers clubs/groups (12%), compared with 39% of
TABLE 3-12
MEASURED DISTANCES TO FACILITIES AND INFRASTRUCTURE
(PERCENTAGES)
Number of Miles
<1 1 2 3 4 5 6 7 8 9
FACILITY
Total
10 %
Medical M 1 6 11 11 10 26 10 2 5 4 1.5 101
Dispensary F 6 6 12 6 41 30 101
Total 2 6 9 11 9 29 8 2 4 3 18 101
Primary M 13 27 15 17 14 8 4 1 99
School F 18 18 23 18 18 6 101
Total 14 26 17 17 15 8 3 1 100
ADMARC M 5 9 12 10 19 27 10 4 4 1 101
Market F 11 18 11 18 24 11 6 101
Total 6 11 10 10 19 27 10 4 3 1 101
Unit center M 1 11 10 10 17 33 11 4 4 1 101
F 6 12 12 18 35 12 6 101
Total 2 11 8 10 17 34 11 4 3 1 101
Water Supply M 77 20 1 1 99
F 76 18 6 100
Total 77 20 1 2 100
Maize mill M* 7 20 25 22 18 3 .3 1 99
F* 23 15 23 31 8 100
Total* -6 21 23 22 21 4 3 1 100
MHH-84 FHH=17 Total-101 M*-65 F*=65
Total*=78
MHHs and 20% of Wives (Table 3-14).
On the other hand, 29% of FHHs are recognized as Achikumbi
(good farmers) compared with 14% of men and 9% of Wives (Table
3-15). Achikumbi status means that the person has been cited by
the extension agent to LRDP, and the farmer receives a
certificate of award. These farmers are usually members of
farmer's clubs. It is surprising, given the fact that 29% of
FHHs are Achikumbi, that their membership in clubs is much lower
and may reflect past rather than current membership.
Household heads were asked to report on who does the farming
in the household. In 4% of MHHs the wife does the farming, and
in the same amount the women does not farm. Interestingly, 18%
of FHHs claim that their husbands help them and an additional 6%
note occasional help. Hence married FHHs may receive some labor
assistance from spouses (Table 3-16). Only 16% of the entire
sample receive no extension visits at all (Table 3-17), masking
the fact that this situation obtains for bver one third of the
FHHs compared to only 12% of MHHs. Most farmers do report that
the extension agents visit frequently.
GARDEN AND CROPPING PATTERNS
Garden Inventory and Land Tenure
The average number of gardens per household is 4.3 with MHHs
having 4.6 and FHHs having 3.7 (Table 3-18). The majority of
these gardens are rainfed, and almost every household has one or
more of these gardens where the major staple crop, maize, is
MHHs and 20% of Wives (Table 3-14).
On the other hand, 29% of FHHs are recognized as Achikumbi
(good farmers) compared with 14% of men and 9% of Wives (Table
3-15). Achikumbi status means that the person has been cited by
the extension agent to LRDP, and the farmer receives a
certificate of award. These farmers are usually members of
farmer's clubs. It is surprising, given the fact that 29% of
FHHs are Achikumbi, that their membership in clubs is much lower
and may reflect past rather than current membership.
Household heads were asked to report on who does the farming
in the household. In 4% of MHHs the wife does the farming, and
in the same amount the women does not farm. Interestingly, 18%
of FHHs claim that their husbands help them and an additional 6%
note occasional help. Hence married FHHs may receive some labor
assistance from spouses (Table 3-16). Only 16% of the entire
sample receive no extension visits at all (Table 3-17), masking
the fact that this situation obtains for bver one third of the
FHHs compared to only 12% of MHHs. Most farmers do report that
the extension agents visit frequently.
GARDEN AND CROPPING PATTERNS
Garden Inventory and Land Tenure
The average number of gardens per household is 4.3 with MHHs
having 4.6 and FHHs having 3.7 (Table 3-18). The majority of
these gardens are rainfed, and almost every household has one or
more of these gardens where the major staple crop, maize, is
TABLE 3-13
TRAINING COURSES (PERCENTAGES)
MHH=77 FHH=17 WIVES=83
TOTAL MHE
and FHH=94
Mone 73 88 86 76
Day Training 14 12 13 14
Residential TC 12 1 10
Both D + R 1 1
Total % 100 100 100 101
*Training Center
TABLE 3-14 FARMING CLUB/GROUP MEMBERSHIP (PERCENTAGES).
TOTAL MHH
MHH-73 FHH17 WIVES=83 and FHH=156
None 62 88 80 67
Member 29 12 19 26
Member and officer 10 1 8
Total % 101 100 100 101
TABLE 3-15
ACHIKUMBI (RECOGNIZED "GOOD FARMER") STATUS
(PERCENTAGES)
TOTAL MHH
MHH-84 FHH=17 and FHH=101
None 85 71 83
Man and woman 8 7
Man 6 5
Woman 1 29 6
Total % 100 100 100
TABLE 3-16
HOUSEHOLD HEAD'S REPORT AS TO
(PERCENTAGES)
WHO FARMS IN HOUSEHOLD
TOTAL MHH
MHH=84 FHH=17 and FHH=101
Man and woman farm to- 93 18 81
gether
Woman farms alone 77 13
Woman farms alone, man 4 3
with other wife
Man helps on some op- 6 1
Man farms alone. 4. 3
Total % 101 101 101
TABLE 3-17
EXTENSION AGENT VISITS (PERCENTAGES)
MHH-77 FHH-17 WIVES=81
TOTAL MHH
and FHH=94
None 12 35 31 16
Visits-no frequency given 5 4 4
Visits-infrequent 5 18 4 7
Visits-frequently 78 47 62 72
Total % 100 100 101 99
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