THE STRUCTURE AND EFFICIENCY IN RESOURCE
USE IN MAIZE PRODUCTION IN THE 
ASAM&NKESE DISTRICT OF GHANA
BX
CIURLES YAW CMSI AMANKWAIl
A THESIS SUBMITTED TO THE DEPARTMENT OF 
AGRICULTURAL ECONOMY AND FARM MANAGEMENT, 
UNIVERSITY OF GHANA, IN PARTIAL FULFILMENT 
OF THE REQUIREMENT FOR THE AWARD OF THE 
DEGREE, MASTER OF PHILOSOPHY (M.PIIIL.)
IN AGRICULTURAL ECONOMICS
DECEMBER, 1996.
354323
DEDICATION
dedicate this work to my mum, dad and siblings.
DECLARATION
I, Charles Yaw Gyasi Amankwah, author of this project report 
do hereby declare that the work presented in this thesis
"THE STRUCTURE AND EFFICIENCY IN RESOURCE USE IN MAIZE 
PRODUCTION IN THE ASAMANKESE DISTRICT OF GHANA"
was done entirely by me in the Department of Agricultural Economy 
and Farm Management, University of Ghana.
This work has never been presented in whole or in part for 
any other degree of the University or elsewhere.
This work has been submitted for examination with my approval as 
supervisor
Charles Xaw Gyasi Amankwah
Dr. (Mrs.) R. Al-Hassan 
(Co-Supervisor)(Principal Supervisor)
ii
ACKNOWLEDGEMENT
I first of all give thanks to the Lord Almighty for 
successfully seeing me through the completion of this work.
The next thanks go to my two supervisors, Dr. G.T-M. Kwadzo, 
the principal supervisor and Dr. (Mrs.) R. Al-Hassan, the co­
supervisor for their constructive criticisms and immense 
contributions towards the work. I am in addition very grateful to 
them especially Dr. G.T-M. Kwadzo for allowing me to use his 
computer to type and print my work. Thanks also go to my two 
colleagues, Osei Kwajo and Erasmus at the Computer Science 
Department who in the course of the work introduced me to the 
principles and use of the computer and thereafter allowed me to use 
their computers for my work. My sincere appreciation goes to the 
Asamankese District Extension Department especially Kennedy, an 
extension officer who conducted me around the study villages during 
the administration of the questionnaires. My sincere thanks go to 
the Emmanuel and Mr. Afare both of Asamankese Post Office who 
helped me in securing accommodation during the field work. I am 
also very grateful to my uncle, Mr. W.F. Krofah, managing director 
of Research and Marketing Services (RMS) for the moral support 
given me.
Finally, I thank Mr. Adika the Librarian, Reindorf, Mr. 
Amegashie, Mrs. Honu and other members of the department who in 
diverse ways helped me in my work.
Charles Yaw Gyasi Amankwah 
August 199 8.
iii
ABSTRACT
The study sets out to find out on one hand, the present 
structure of resources in agricultural production and secondly, to 
delve deeper into the controversy surrounding the comparative 
efficiency in resource use by sharecroppers and owner farmers in 
agricultural production.
The approaches used to assess the structure of the resources 
are frequency distributions, descriptive analyses and estimation of 
cost composition of individual resources. In assessing the 
comparative efficiency in the use of resources by sharecroppers and 
owner farmers, the gross margins method and the allocative 
efficiency method based on the profit maximizing assumption were 
used.
The findings of the study indicate that, there is limited use 
of fertilizers, weedicides and improved seeds. Cutlass is widely 
used. Mixed cropping is widely practiced, land areas cultivated to 
maize fall mostly below one hectare and the major source of labour 
on almost all the farms studied is the family. The study also 
found that there were no significant differences in the efficient 
use of land and labour by owner and sharecropping farmers.
It is therefore concluded that the traditional way of farming 
based on the structure of the resources has not changed in the 
study district. With the efficiency in the use of land and labour 
by sharecroppers and owner farmers, the conclusion is that both 
farmer groups use land and labour inefficiently.
iv
CONTENTS
CHAPTER ONE PAGE
1.0 Introduction .......................................  1
1.1 Background Statement ............................... 1
1.2 objectives of the Study ...........................  6
1.3 Relevance of the Study ............................. 6
1.4 Study Area .......................   8
1.5 Limitation of the Study ............................ 10
1.6 Organization of the Study .........................  10
CHAPTER TWO
2.0 Literature Review ..................................  13
2.1 Introduction ........................................ 13
2.2 Concept of Structure ...............................  14
2.2.1 Labour Structure   ............................. 17
2.2.1.1 Pattern of Labour Use in Ghana .................  21
2.2.2 Capital Structure .............................  23
2.2.2.1 Pattern of Capital Use in Agricultural
Production in Ghana ...........................  26
2.2.3 Structure of Land .............................  2 7
2.4 Comparative Efficiency of Tenancy 
(Sharecropping) and owner-operatorship
Systems in Resource Use ............................  3 0
2.5 Concept of Efficiency .............................. 35
v
2.5.1 Methods of Measuring Resource Use Efficiency . 38
2.5.2 Theoretical frameworks of Analytical Methods . 45
CHAPTER THREE
3.0 Methodology  ........................................  46
3.1 Data and Sampling Technique .......................  48
3.2 Methods of Analysis ................................ 50
3.2.1 Structure of Resource Use .......   50
3.2.2 Comparative Efficiency of Resource Use .......  50
3.2.2.1 Gross margins ..................................  51
3.2.2.2 Allocative Efficiency .........................  52
CHAPTER FOUR
4.0 Results and discussion.......   56
4.1 Introduction .......................................  56
4.2 structure of the Resources (as defined by
their composition) .................................  56
4.2.1 Land Structure .................................  56
4.2.1.1 Farm Sizes .....................................  56
4.2.1.2 Cropping Pattern ...............................  58
4.2.1.3 Bush Fallow ....................................  61
4.2.1.4 Land Tenure System in the Area ................ 63
4.2. Labour Structure ...................................  65
4.2.2.1 Size of Labour Force ........   66
4.2.2.2 Distribution of Type of Labour by Task: .......  71
vi
4.2.2.3 Age and Gender Distribution of Farm
House holds .................................... 73
4.2.3 Structure of Capital ..........................  74
4.2.3.1 Types of Capital Inputs .......................  74
4.3 Structure of Resources in Terms of
Proportions .................................... 77
4.4 Resource Use Efficiency.......................  82
4.4.1 Gross Margins Results .........................  82
4.4.2 Allocative Efficiency .........................  85
CHAPTER FIVE
5.0 Sumnary, Conclusions and Recommendations .......... 91
vii
LIST OF TABLES
Table 1 Distribution of Land Sizes Cultivated to
only Maize in the 1994 Major Season .............  57
Table 2 Distribution of Farmers by type of crop
mixtures ....................................... 59
Table 3 Farmers' Reasons For Adopting Particular
Cropping Pattern .... '.........................  60
Table 4 Distribution of Farmers by Reason for
Practising or not Practising Bush Fallow ....  62
Table 5 Distribution of fallow periods ................ 63
Table 6 Distribution of Farmers by type of tenurial
arrangement ..................   ...... 64
Table 7 Percentage Distribution of Farmers by Type 
of Tenure and Source of Land Acquisition
Percentage ..................................... 65
Table 8 Type of Labour Used on the Farms Studied .....  63
Table 9 Average Labour Supply per Hectare and Distribution
of Hired and Family Labour Supply per Hectare on
Mixed and Monocropped Farms ...................  69
Table 10 Percentage of Household Members Engaged in
Farming ......................................... 70
Table 11 Distribution of Farmers by Type of
Tenurial Arrangement ............................  72
Table 12 Age and Gender Distribution of
Farm households ................................  73
viii
Table 13 Distribution of Farmers' Reasons for not
Planting the Improved variety of Maize .......... 75
Table 14 Distribution of Weedicide, Fertilizer and
Improved Seeds Used Among Farmers in the
Study District ...........................   77
Table 15 Average Total cost per hectare of Inputs
Used in Maize Production households ............  78
Table 16 Average Percentage Share of Inputs in
Cost of Production ...............................  79
Table 17 Average Percentage Cost Composition of various
Inputs per Hectare Among Farmer Groups ......... 80
Table 18 Average Gross Margins per Labour Input
for Farmer Groups ...............................  84
Table 19 Average Gross Margins per Hectare for Farmer
Groups ...........................................  85
Table 20 Production elasticities, marginal value products, 
factor prices and allocative efficiency indices 
for sharecroppers, owners and the pooled sample 90
ix
CHAPTER ONE
1.0 INTRODUCTION
1.1 Background Statement
Agricultural production requires the use of resources such as 
land, labor, capital, as well as managerial skills. These factors 
are however used in different proportions depending on available 
technologies.
The Structure of resources in an agricultural system refers to 
either (i) the proportion of each of the resource used in 
production or (ii) the composition of the resources. Composition 
of a resource refers to the make of the resource. For example the 
composition of land refers to the size of land cultivated, type of 
cropping pattern and the form of land tenure. Composition of 
labour refers to the size of labour (i.e. number of labour force), 
types of labour used on farms (i.e. family and hired), age and sex 
of labour of employment status (i.e. which type of labour does 
what). The composition of capital refers to the amounts and types 
of capital inputs employed by farmers in production or the equity- 
credit ratio of capital (Hill and Hay, 1987).
The structure of the resources used gives an idea of the 
structure of farms or the structure of agriculture in a given 
nation. The essence of studying the structure of resources is to 
know the strengths and weaknesses of agricultural production 
(Rourke, 19 69).
Changes in economic conditions, population increases and 
changing agricultural technologies among other alters the structure 
of resources in farming which may have implications on output 
levels (Heady, 1961; OECD, 1975 and Hill and Ray, 1987). In Ghana, 
there have been changes in the economic environment especially 
relative prices, increase in the population and changes in 
agricultural technology which indirectly affect the structure of 
the resources used and hence output. But there has not been any 
recent study to document the structure of resources in agricultural 
production which could form the basis of reference if the above 
changes are to be examined on the structure of resource use in 
future.
In sub-Saharan Africa, due to rapid population growth and 
other demands on arable land, there is a strain on agricultural 
land. This has resulted in a significant reduction in the fallow 
period and the cultivation of marginal lands. In the absence of 
sound soil management practices or the economic use of fertilizers 
and other additives, declining fallow periods result in accelerated 
depletion of nutrients, increased weed populations, erosion and 
decreased moisture retention (Lai 1983, IITA, 1992). Consequently, 
soil fertility declines, adversely affecting crop yields, labour 
productivity and returns from farming. What then has been the 
structure of land in terms of sizes cultivated, the type of 
cropping pattern adopted and the tenurial arrangements among others 
all of which affect output levels?-
2
In Ghana, agricultural production is largely rainfed and 
therefore seasonal. There is a peak demand for labour for certain 
farm activities and because labour has competing uses with 
associated higher prices, the small scale farmer mainly depends on 
family members. However, due to the increasing monetization of the 
economy, decreasing family size, increasing rural-urban migration 
and increasing school attendance of children (GSS, 1995), the small 
holder farmers will have to rely more and more on hired labour 
which is getting more and more expensive. Thus, the availability 
of family labour during peak season is a crucial factor determining 
the level of farm output (Ewusi et al.. 1983). Against this
background, what has been the structure of agricultural labour?-
Capital inputs are required in the right proportions in 
combination with land and labour inputs to augment production. Due 
to the rerroval of agricultural input subsidies, the prices of 
productivity enhancing inputs such as fertilizers, weedicides and 
other improved inputs are relatively high. This situation, coupled 
with the high cost of agricultural labour which is beyond the 
pocket of most farmers and seasonal low output prices (HARP, 1983) 
call for the examination of the ways farmers allocate their 
available resources and the structure of capital inputs in terms of 
forms and amounts employed in agricultural production.
The second aspect of the study concerns the efficiency in the 
use of resources by small scale farmers. With the increasing costs 
of agricultural inputs such as labour, fertilizer, improved seeds 
and weedicides, it is important that small scale farmers use the
3
available resources at their disposal efficiently to increase 
yield. Special focus is placed on different groups of farmers by 
type of land tenure in the study of efficiency in the use of 
resources by small scale farmers. This is because many studies 
have indicated that the type of landholding affects the efficiency 
in the use of resources by small holder farmers (Dadson, 19 69; 
Baumik, 1991; Junankar, 1976).
There has been some controversy oyer the efficiency in the use 
of resources by tenant (sharecroppers) and owner farmers. An owner 
farmer owns the land he cultivates and provides all resources (i.e. 
land, labour, capital and management). A tenant farmer (i.e.
sharecropper) does not own land but as an agreement for the use of 
land for farming, he gives out a stated proportion of his total 
produce as rent to the landlord. One school of thought known as 
the “Marshallian view" associates inefficiencies with sharecropping 
systems due to insecurity of tenure (Feder and Ochan, 1987), while 
another school (the equal efficiency view), contends that 
sharecropping systems are not associated with inefficiency in the 
use of resources but do use resources as efficiently as owner- 
operator systems provided there is fair sharing of production cost 
between the landowner and the tenant farmer (Bishop and Toussaint, 
1958). In Ghana, there is the belief that because sharecroppers 
bear all production costs, there is no incentive for the 
sharecropper to employ the required levels of inputs hence the 
sharecropper produces inefficiently or obtains lower outputs 
compared to owner farmers. This situation has led once to a call
4
for the abolishment of sharecropping systems and Ghana in replacing 
it with a cash tenancy system which is considered a better system 
in terms of efficiency in the use of resources (FAO, 1985). Dadson 
(19 69) also notes that for developmental purposes, owner-operator 
systems and cash tenancy should be of priority. These 
recommendations for the replacement of sharecropping system in 
Ghana are not based on empirical evidence. There has not been any 
study in Ghana to substantiate quantitatively the comparative 
efficiency in the use of resources by sharecroppers and owner 
operators. A study carried out by Mi^ot-Adholla et al., (1990) on 
“Land Tenure and agricultural productivity in Ghana" examined the 
insecurity of the use of farmland by tenant farmers in three 
districts of Ghana. They found that so far as security of tenure 
was concerned in the study districts, tenant farmers enjoy maximum 
security and that they found no evidence of tenure insecurity 
contributing to agricultural inefficiencies. This study still did 
not deal with the issue of efficiency in the use of resources by 
tenant and owner farmers. It should also be noted that due to 
differences in the social and traditional set up of different 
communities in Ghana, their findings which are based on only three 
districts in Ghana cannot be concA.usfi.ve for Ghana. Against this 
background, what is the relative efficiency in the use of resources 
between owner and sharecropping farmers?.
The study focuses on the foodcrop subsector specifically 
maize. This is because the foodcrop subsector contributes the 
highest percentage of agricultural gross domestic product (MOFA,
5
1991) and the fact that foodcrops form the major source of our 
diets. This study limits itself to the maize foodcrop because 
statistics on average and achievable yields of major foodcrops from 
1987 to 1990 indicated that maize had the highest yield gap 
percentage of 317% (MGFA, 1991).
1.2 Objectives of the study
The primary objective of the study is to investigate the 
structure and efficiency in the use of resources in maize 
production.
The specific objectives of the study are:
(i) To document the present structure of resource use in maize 
production in the study area.
(ii) To determine the implications of thee existing land tenure 
systems on maize production in the study area.
(iii) To conduct a comparative assessment of the efficiency in
the use of resources between sharecroppers and owner-operators in 
the study area.
(iv) To recommend measures to improve factor use efficiency.
1.3 Relevance of the Study
This study has food security implications because it concerns 
increased production by way of efficient use of resources. Food 
security is one of the specific objectives of the Medium Term 
Agricultural Development Programme meant to provide all Ghanaians
6
with food security through adequate and nutritionally balanced
diets at affordable prices.
It is also a policy of the Eastern Region to improve
agricultural productivity (through efficiency of production) to 
increase farmers' income, diets of people and raise the general 
standard of living of all engaged in agriculture (DED, 1990). This 
study could form the basis upon which the efficiency of maize 
production by farmers in the area could be further discussed.
Another relevance of the study is that, there is little work 
done in this area. Few related studies conducted by Atsu and Owusu 
(1971) and Atsu, Ewusi and Gyekye (1983) indicate how agricultural 
labour and land are utilized but have not touched on the efficient 
use of these resources. In addition, studies conducted on the 
impact of land tenure on agricultural production efficiency used a 
qualitative approach in explaining how tenancy affects agricultural 
production efficiency. This study adopts an econometric approach 
to determine the relative allocative efficiency of owner and
sharecropping farmers.
Knowing the structure of resource use is important because it 
may help to understand the current structure of agriculture of 
which the effect of the changing economic policies, increasing 
population and agricultural technology could be studied in future 
and what policy directions to take in drawing up a programme for 
agricultural development for the country.
Finally, the study will add to the understanding of issues 
particularly on land tenure and agricultural production efficiency 
and will serve as a reference piece for further related studies.
1.4 Study Area
The study was conducted in the West-Akim district of the 
Eastern region of Ghana. Recent agricultural statistics on the 
region indicate that West-Akim, Kwawu North and Fanteakwa districts 
contribute the highest proportion of total maize production in the 
region. In the 1993 production year, the districts produced 
12,700mt of maize each which was the highest in the region, (PPMED, 
1993). The West-Akim district was selected for this study because 
of proximity to area of the author's residence and cost in terms of 
transportation and accommodation which are affordable in this area. 
Three sub-districts namely:- Adeiso, Osenase and Oworam were 
selected for the administration of the questionnaires. The 
selection of these sub-districts was based on information obtained 
from the District Extension Department that they are the main maize 
producing areas in the district. Within these sub-districts six 
villages were randomly selected from a list of villages. These 
selected villages are Asuofori, Akanteng, Ekoso, Pabi, Oworam and 
Kwametia. Figure 1 presents the map of the study area showing the 
locations of the study villages.
The vegetation of the study areas is mainly forest, 
characterized by high humidity and temperature. The rainfall is 
bimodal i.e., from April to July and from August to November. The
8
annual rainfall figure falls between 1500 and 2 00mm which is 
suitable for maize production.
The study area comes under the forest ochrosol type of soils 
(figure 2). information on the nature of the soils in the study 
villages shows that the soils can be sub-divided into the Swedru, 
Nsaba and Akroso Series (Adu and Asiamah, 1992). The Swedru series 
is reported to consist of grey-brown clay loam on the topsoil while 
the Nsaba series comprises a brown less completely-drained 
associate of Swedru series. The Akroso soils are said to be 
associated with Swedru and Nsaba soils and are reported to be more 
silty and heavier in texture. These soil series are according to 
Adu and Asiamah (1992) very good soils for crops such as maize, 
cassava, plantain, cocoa among others.
The topography of the area is gently undulating. The 
population density of the study area is 93/km2, (1984 population
census). This shows that the area is densely populated. The major 
occupation of the people in the study villages is farming, 
specifically maize and cassava cultivation.
Infrastructural development in the study villages is low. 
There is no electricity and access roads are lacking. All the 
study villages use bore-holes as their sources of water supply. 
The health delivery system is mainly the unorthodox type but some 
of the people seek medical assistance from the district hospital. 
There are lack of schools and the few existing ones are 
inadequately equipped.
9
1.5 Limitation of the Study
The major limitation of the study was that the author was not 
able to adopt the recommended method of collecting field data on 
exact land areas cultivated by the farmers. Upton (19 87) has 
recommended that, to obtain accurate data on land areas cultivated 
to a given crop, the researcher must visit individual farms and 
carry out field measurements. This was not possible because the 
data collection exercise was carried out months after the major 
growing period. Rather farmers were interviewed at their homes. 
since with small scale farming, there is the possibility that some 
farmers may not have exact knowledge about the land areas they 
cultivate, they may overestimate or underestimate them. The 
expected errors of underestimation or overestimation of land areas 
cultivated by farmers were minimized by cross checking the data 
provided with help of Extension Officers. Because the officers 
visit the farms of the sampled farmers, they have fair knowledge of 
the land areas cultivated to maize by these farmers.
1.6 Organization of the Study
The study is organised into five chapters. Chapter Two 
reviews the existing literature on the concept of structure of 
resources, how resource structure affects agricultural 
productivity, concept of efficiency of resource use and review on 
the comparative efficiency of sharecroppers and owner-operator 
systems. Chapter Three presents the study methodology. 
Presentation and discussion of results is in Chapter Four. In 
Chapter Five, the final chapter, is presented the summary, 
conclusions and recommendations from the study.
10
Fig 1  } MAP OF THE STUDY AREA IN THE WEST AKIM DISTRICT
Fig. A MAP SHOWING THE MAJOR SOILS OF GHANA
Ra i n  ( o r c s t : -  
\ m \  O x y ta l i
M o i s t  S e m i - D c c i d u o u s  F o r e s t :  
--Z -J  fo rc s (  O cluoso ls
Forest O c h ro s o l-O x y jo l 
ln (e rg f*d e s
R u b fiso l O c h ro to l in te rg n d e s
I n t e r i o r  W o o d e d  S a v a n n a : -  
|  * ■* G ro u rv d w ilc r  l^ le r ic ic  Soils
S a v in a *  O ch ioso ls
A c k i G k ito ls
Southeast Coastal S ivanna:-
N j f j t j  O chco toU
L * lc (K ic  S a r * ! /  Soi(s
Trop4c*J Dl*ct Clays ck 
M.utc toHs
Tropic*< G rey Carthc 
S odkrm  V W iso is .
Coastal S andy  Soils
0 00 km
<— — I---1 l I /
Accra
Ta ko o d i
------------W EST  AKIM  D IS T R IC T
Durce: D i c k s o n  a n d  B e n n e h .
12
CHAPTER TWO
2.0 LITERATURE REVIEW
2.1 Introduction
The chapter is divided into four sections. The first section 
reviews the concept of structure of resource use in agriculture, 
followed by a review on land tenure, then the concept of efficiency 
and that of resource use by tenant and owner farmers and finally, 
a review on the measures of assessing resource use efficiency.
It should be noted that the concept of structure of resources 
in some studies refers to the structure of a farm and in others as 
the structure of agriculture. In other words, the structure of 
resources gives a picture of the state of agriculture or the 
structure of a farm.
The second section of the chapter reviews studies on land 
tenure systems in Ghana. It reviews the different forms of land 
tenure systems in Ghana and how the traditional form of land tenure 
has transformed to other forms.
Section three reviews (i) the concept of efficiency and (ii) 
the comparative efficiency in the use of resources by owner farmers 
and sharecroppers . Measurements of efficient resource use and the 
theoretical frameworks are reviewed in the last section.
With regard to the structure of the resources, the review will 
come out with what the structure of the resources mean and how the 
structure is influenced by economic transformation and
13
technological changes. The review on the land tenure will help in 
knowing which types of land tenure arrangements exist and their 
terms of holding. This is important because it is hypothesized 
that the type and terms of agreement of landholding influence the 
type of farming technique and input usage adopted, (Junankar, 
1976). The review on the comparative efficiency of resource use by 
owner and sharecropping farmers provides various arguments that 
have been put forward to support the efficiency in the use of 
resources by the two farmer groups. Finally, the review on the 
measures of efficient resource use will help to identify the best 
measure to use for the comparative assessment of efficiency in the 
use of resources.
2.2 Concept of Structure of Resources
A review of the literature reveals that the structure of 
resources are examined with two different perspectives. One view 
of structure is the composition of a particular resource, the other 
view is the proportions of resources to each other in any 
production.
Stabler (19 75), refers to the structure of a farm as the 
proportion of each resource used. He further notes that generally, 
the structure of a resource in relation to other resources i.e. its 
combination with the other resources is also an indication of farm 
structure. Kwadzo (1995) in a Socio-economic study of small scale 
farm households on the Vertisols of the Accra Plains, looked at the 
proportions of resources used in terms of their production cost
14
structure. This was to find out the extent to which resources are 
utilised in the face of changing agricultural technologies and 
increasing cost of productivity enhancing inputs such as 
fertilizer, improved seeds, weedicides and tractor services. The 
method used to analyse the proportions of the resources in the 
study was to estimate the cost per hectare of each of the resources 
for each farmer. He found that for all farmers, labour input 
constituted the single highest cost of production (50-80%) which 
implies that less labour saving techniques were used.
Syndgrass and Wallace (19 75) similarly examined the changes in 
the use of major United States farm inputs such as labour, 
machinery, fertilizer and seeds over a period of 44 years i.e. from 
1929 to 1973 in a period of economic adjustments and changing 
agricultural technologies. They used the indices of prices of the 
major farm inputs to study the pattern of change in the use of the 
inputs. The findings were that, farm labour use continuously 
dropped and use of machinery/power, fertilizer and seed increased 
throughout the period. This finding indicates that over the period 
of study, labour saving techniques replaced farm labour which had 
positive implications on total production.
Harvey (1966) discusses the concept of structure in which he 
outlines the economic structure of agriculture in Europe and 
examines how this structure has been influenced by past economic 
and legislative circumstances. His concept of structure covers the 
number and sizes of farms; type and intensity of enterprise mix; 
land and labour use among farms. Hill and Ray (19 87) defined
15
structure as a term referring to the inner composition of 
something. They used for example, the structure of a building to 
mean it's subordinate parts which make up the whole. They noted 
that the purpose of knowing the structure of something goes beyond 
simple curiosity. Such information gives insight into how the 
particular thing being referred to functions or works and even more 
importantly allows for possible explanations why certain things 
have happened in the past and enables future responses to be 
predicted. They looked at the change in the structure of an input 
like labour as being the reduction/increase in manpower it engages 
and the rise/decrease in use of machine. Hill and Ray (1987) 
examine the structure of United States' agriculture in the 
following way: They look at land structure in terms of size group 
of farms, type of farming and form of tenure.. With regard to 
labour structure, parameters like the size of labour force, age, 
sex, employment status and family and hired labour composition. 
With capital, the amounts and types employed are examined.
Shawyer (1990) in studying farm structure and farm families of 
a Nottinghamshire field area used number of farms, size of the 
farms, capital such as mechanization and the use of chemicals, 
amount of labour employed to represent the farm structure. The 
study revealed the following changes over a period of 40 years: a 
reduction in the number of farms by half and an increase in the 
size of remaining farms; an increase in mechanization and in the 
use of chemicals; and a reduction in the amount of labour employed, 
all of which contributed to yield increases in the United Kingdom.
16
2.2.1 Labour Structure
In agriculture, labour is measured in man-hour or man-day of 
normal work by an individual for a specified period of time. One- 
man hour is the amount of work, output per man hour- In much of 
rural Africa, access to labour, rather than land, is the basis of 
economic and political power (Upton, 1987). This reflects the 
relative sparseness of population and absence of labour saving 
machinery, as a result of which the labour available for critical 
tasks like planting and weeding is an effective constraint on 
production. The amount of labour used (actual labour input) over 
a given period on a particular farm, depends upon the family 
structure, the number of hours worked and the rate of working per 
hour (Kwadzo, 1995). A common trend in the traditional system is 
the extended or joint family unit, consisting of more than one 
married man plus dependents which is breaking up into nuclear 
family units, one married man plus dependents within the same 
household (Kwadzo, 1995). Labour used in agricultural production 
can be classified into various groups: family labour, comprising, 
male adults, female adults and children; hired labour made up of 
adult males and females and communal labour among others. within 
the farm family, there is some form of division of labour. Many 
tasks are traditionally linked to age, sex, family or hired labour 
specific. Most domestic works like raising children in addition to 
planting, harvesting and processing are the responsibility of 
women. Men, generally, carry out heavier tasks such as land 
clearing, land preparation and weeding. Kwadzo (1995) and Adegeye
17
and Dittoh (1985) found that the major type of labour employed on 
small farms are family labour (adult male, adult female and 
children). Hired labour was found to be mostly used for land 
clearing and weeding. Norman (1972), Spencer (1976), Byerlee 
(1980) and Kwadzo (1995), have shown that the percentage of labour 
input supplied by hired labour is usually below 2 0 percent on small 
farms. Therefore, hired labour is not a critical factor in 
increasing agricultural productivity, (Ewusi et al., 1983).
Seasonal labour supply is a major constraint on expansion of 
production characterized by the use of traditional technologies. 
The availability of family labour during peak season is a crucial 
factor that determines the level of farm output and income, (Ewusi 
et al., 1983; Anthonio & Upton, 1965). Anthonio and Upton (1965) 
observe that although hired labour is often used to supplement the 
family labour, it has not played a major role in increasing the 
supply of labour and alleviating seasonal bottlenecks in sub- 
Saharan Africa.
In many areas, the supply of family labour is falling due to 
rural-urban drift and increasing number of children attending 
school. In many parts of the tropics, the area of land cultivated 
is decided by the amount of work the family can do. If the farmer 
could get more labour, he could cultivate more land. In such a 
case, the labour supply is limiting the size of farm.
Reviewing agricultural policies in the Organization for 
Economic Co-operation and Development (OECD) member countries, it 
was noted that the general image of agriculture has changed
18
considerably since 1950 in most countries (OECD, 1975). Infact, 
economic forces from 1950 to 1975 induced the application of labour 
saving techniques thus increasing land and labour productivity. 
These forces led to structural improvements and new forms of 
agricultural co-operation and made it easier for farmers to earn 
additional income outside agriculture. The adjustment process had 
been greatly determined by the special circumstances of individual 
farms, such as natural production conditions, possibilities for 
enlargement of cultivated area or intensification of production, 
financial position and the capacities of the farm operators as well 
as the family labour available and the desire of farmers or their 
heirs to stay in farming. The agricultural adjustment process 
makes agriculture more capital intensive with respect to both real 
and non-real estate investments. Moreover, adaptation to new
conditions is unavoidable in that holdings of farmers, who neglect 
the exigencies of modern times and stick to their traditions, 
became inviable. Though they generally allow the operator a 
minimum income during his lifetime, such farms on the whole do not 
survive transfer between generations. This type of holding is 
often to be found in the small and medium size groups for which the 
financial implications of modernization are generally burdensome 
(OECD, 1975).
Sendaro and Forster (1992) examined the effect of technical 
stagnation and the changes in age structure of peasant producers in 
rural Tanzania. It was noted in the study that agricultural 
production has been progressively declining in recent years. The
19
explanations offered for this situation include factors such as 
environmental and climatic conditions, low producer prices, poor 
marketing facilities, poor infrastructure and transport facilities. 
However, Sendaro and Forster found that less attention has been 
given to the age structure as an important factor in explaining the 
decline in production. They indicated that the agricultural 
producing population has become old and as a result there has been 
no significant technical change. Evidence indicates that at any 
given time it is those aged 3 0 to 64 years and above who engage in 
agricultural production. The young people involve themselves in 
other economic activities until they have grown older and settle 
down to farm. This therefore implies that there will be more older 
people in farming which may have negative implications on yield 
because labour productivity may fall due to the ageing farming 
population. Ofori (19 71) found that the problem of rural 
development in Nigeria has been accentuated as a result of rural 
migration. Young rural labour particularly those who have acquired 
some formal education, have continued to migrate to urban centres 
in search of wage price jobs. The consequence of this is that 
there is shortage of rural labour. This leaves agriculture in the 
hands of the older, non-literate rural population with consequent 
repercussions on managerial ability and productivity.
Majerova (1991), writing on the impact of privatization on the 
structure of agricultural labour, used age as an element of 
agricultural labour structure. He notes that the changing age
20
structure of the farming population i.e. towards old age has 
adverse implications for productivity.
Hill and Ray (1987) also found that due to a constant state 
of flux or adjustment in agriculture in the United Kingdom, the 
structure of its inputs has changed - notably the reduction in 
manpower it engages and the rise in use of machinery. Secondly, 
the number of small sized farms has fallen sharply and replaced 
by larger sized farms since the 40's. These changes have greatly 
influenced increases in outputs.
Writing on the changes in the Korean agriculture due to 
rapid economic development, Chung and Park (1991) found that as 
farming has changed from subsistence to commercial production, 
average farm size h. increased. ThJ®y al3o found that small farm 
size is one of the basic obstacles to increasing production. 
Improved technology, increased farm size, group fa, ing and co­
operative utilization of farm equipment are all ways of 
increasing output.
2.2.1.1 Pattern of Farm Labour Use in Ghana
In Ghana, the pattern of farm labour use differs 
significantly between the two southern and northern sectors. In 
the northern sector, characterized by prolonged dry season, all 
farm activities are concentrated in approximately one-half of the 
year and farm -labour-use is distinctly seasonal. Here the farm 
household normally provides all the labour needed. Few children 
go to school;also wives and husbands tend to participate actively 
and jointly in the farm operations. Hired labour is occasionally
21
The foremost factor behind the existing pattern of allocating 
farm labour is food security. The small scale farmers in the 
southern sector, unlike their counterparts in the North, do not use 
farm manure or chemical fertilizers to enrich the soil (Atsu et al, 
1980). Diminishing returns to labour thus quickly sets in as 
labour-use is intensified; rather than drive the marginal product 
of labour further down through a more intensive use on a piece of
land, the farmer chooses to distribute his labour over a number of
farms, since the land costs him little or nothing at all. This 
way, the farmer is assured of a greater total production from all 
the farms combined (Atsu et al., 1980).
2.2.2 Capital Structure
Capital is an important factor in production. Knowledge of 
the structure of capital in agricultural production may indicate 
whether agricultural production is subsistent or on commercial 
basis. In agriculture, capital is classified into two forms: fixed 
(investment capital) and variable capital (working capital). Fixed 
capital is the form of capital which does not vary with
agricultural output while variable capital on the other varies with 
output levels. Working capital can also be classified by type of 
input i.e. seed (improved or local), chemical technology,
mechanical technology and labour. The proportions of these capital 
types differ in usage in agricultural production depending upon
whether the scale of operation is small or commercial. The
structure of capital in agricultural production may have its
23
implications on agricultural output. For example, in small scale 
or traditional agricultural production, rudimentary capital inputs 
such as cutlasses and hoes are employed and there is also little 
use of output increasing inputs such as fertilizer and weedicide. 
The result of this is low agricultural outputs. The opposite is 
true for large scale production where there is investment in 
machinery and land, application of improved technologies on larger 
scale which ensure greater agricultural outputs.
Economic theory emphasis capital formation as the lever of 
development, (Phiri, 1991). Nurske (1953) believes that the route 
of escape from countries caught in the vicious circle of poverty 
lies in capital injection into their economies. Mellor (1962) 
points out that in order to increase output of traditional 
agriculture, there must be injection of capital. Similarly, Heady 
(1966) notes that the injection of capital is the ideal step in 
displacing human resources and increasing total production as well 
as raising productivity during farm modernization and economic 
development. This injection of capital could come in two ways. 
First, is the direct substitution of adaptive and/or new mechanical 
power for labour. This will enable each person to manage more 
hectares. Second, is the indirect substitution of biological and 
agro-cherrdcal innovations for labour. These biological and agro­
chemical innovations of new capital forms include fertilizer, feed 
additives, new crop varieties, improved seeds, insecticides, 
herbicides, fungicides and others which increase output per hectare 
while causing less labour to be required per unit of output per
24
while causing less labour to be required per unit of output per 
hectare.
Heady and Jensen (1954) reveal that many studies of 
production economics have shown that substantial potential exists 
for increasing the efficiency of resource utilization. Studies 
dealing with large aggregates and employing roughly defined 
variables, as well as micro level studies based on experimental 
and survey data, have convincingly attested to the existence of 
potentials under modernization based on injection of the two 
forms of capital (Heady and Jensen, 1954).
La-Anyane (1985), has observed that fertilizer, farm
tractors and equipment and processing machinery will be the key 
inputs in the next twenty years from 1985. He further noted that 
as their costs have been increasing, it is important that they 
should be used efficiently so that the greatest number of farmers 
can have access to them for increasing food and agricultural 
production. In addition to efficient fertilizer use, improved 
seed and better husbandry practices should be adopted by the 
farmers.
A NARP (1993) report notes that, in order to sustain maize 
production at the current level of near self sufficiency, 
production growth rate should be at least 5% per annum. This 
rate according to the document can be achieved by farmers 
provided they adopt improved technology and inputs such as seed, 
fertilizer, other agro-^chemicals and mechanization of operation.
25
2.2.2.1 Pattern of Capital Use in Agricultural Production in
Ghana
In Ghana, the bulk of food is produced by small scale 
farmers. It is generally known that small-scale farmers adopt 
traditional way of farming i.e. the use of rudimentary tools like 
cutlass and hoe, mixed cropping and dependence on family labour 
for farming among others. Huge investments in capital equipment 
is absent in the Ghanaian agriculture. Though improved inputs 
such as fertilizer, weedicide, high yielding seeds, tractor 
services are employed in agricultural production in Ghana, they 
are employed on limited scale. The employment of these inputs 
may differ from one geographical region of the country to 
another. For example, soils in the Northern sector are' 
relatively poor in organic matter and nutrients due to lack of 
vegetative cover. This situation compels farmers in the North to 
use fertilizer and other fertility enhancing chemicals more than 
their counterparts in the south where the soils are considered 
richer in nutrients (Atsu et al. 1980).
Quantitative estimates from crop budgets of the pattern of 
capital use on small farms in Asutuare and Somanya show that 
fixed capital inputs contribute only 5% of the total capital 
input cost, variable capital inputs contribute 27% and the 
remaining 68% come from labour (Kwadzo, 1995).
26
2.2.3 Structure of Land
Agricultural land tenure according to Dadson (19 69), refers to 
the legal, political and socio-economic arrangements governing the 
ownership and management of agricultural land. He identifies three 
main forms of land tenure outside the communist system where 
farming is undertaken under state control:
(i) communal or group tenure
(ii) owner-operationship or owner-occupiership
(iii)tenancy.
The particular patterns of tenure in any given place depends 
on the customs and history of the area, the economic opportunities 
for land relative to its supply and the outcome of bilateral 
bargaining between the immediate landowner and the operator, 
(Dadson, 1969). As with other resources, the condition under which 
land is held influences the pattern and efficiency of use and the 
production of food, (Dadson, 1969; Karan et al, 1982).
Traditionally, in Ghana as in most parts of tropical Africa, 
land is generally owned communally by people having common descent 
or owing allegiance to a symbol of collective authority, for 
example, ■ the 'stool' arrong the Akan of southern Ghana, (Bensti- 
Enchil, 1964; Ollenu, 1962; Parsons, 1971; Pogucki, 1962). 
Therefore the community or family constitutes the basic medium of 
access to land, (Gyasi, 1994). The individual members are supposed 
to enjoy free inheritable usufructuary rights over communal land on 
the basis of kinship (i.e., member of community without prejudice
27
to the communal ownership). Strangers or non-members may have 
access to communal land through the transfer of rights of use by 
the land-owning family usually through the leader, chief or 
occupant of the land. Another increasingly used medium to access 
land is the government, which may acquire land compulsorily from 
the original owners, through legislation for government's own use 
or by use of others, in so far as the acquisition is deemed to be 
in the interest of the public, (Gyasi, 1994).
One school of thought sees the traditional communal land 
tenure system as nebulous, inherently conservative, incapable of 
adapting fast enough to change and therefore a drag on development 
(La-Anyane, 1962; Migot-Adholla et al, 1990). It was for example 
observed that: "innovative and investment-oriented agricultural
enterprise ... are inhibited" (King, 1973, P7). Other constraints 
on development have been associated with lack of clarity about the 
allocating authority and boundaries which rnay result in disputes. 
There is trespassing, inequitable tenancies, lack of security for 
tenants, especially alien or stranger farmers and inability to use 
corrtnunally owned land as collateral for loans. In addition to 
these factors, the customary system of inheritance, which in 
certain cases, excludes females, and entails the subdivision of 
land among succeeding generations with consequential fragmentation 
of holdings is also reported to be a constraint to development 
(Arhin, 1985; Johnson, 1962; Migot-Adholla et al., 1990; Ninson, 
1989).
28
Though the communal system of land tenure was a bane to 
development, it was not static. The system in Ghana did not 
prevent extensive acquisition of land, even by strangers or 
migrants who do not belong to any of the land-holding groups in the 
locality, for cocoa farming especially from 189 0s to about 1950 
(Hill, 1963; Johnson, 1962), but also from 1950 onwards, (Arhin, 
1985). Nor did it prevent the phenomenal post-1970 oil palm 
farming expansion, involving an over five fold increase in oil palm 
hectare in 20 years. This would seem to underscore the view that 
basically, the traditional system is a dynamic one, capable of 
adapting in good times to favourable economic opportunities, 
(Gyasi, 1994).
Individual ownership and tenancy appear to be the forms that 
emerge in development, (Dadson, 1969). Under owner-operatorship, 
the farmer owns the land he cultivates and provides all other 
resources (labour, capital and management). He has complete 
control over the farm. Under tenancy, there is a division of 
economic function between the landlord and the tenant. The 
landlord usually provides land only, and the tenant provides labour 
and capital in the production unit. The terms of the contract 
determine how the resources of the landlord and the tenant are to 
be combined and how the returns are to be distributed. It is this 
question of resource allocation and returns distribution that the 
economic problem of tenancy arises, (Dadson 1969).
29
There are two types of tenancies: cash and share tenancies. 
Under cash tenancy (or cash lease), a fixed sum is charged per 
hectare of farmland and payment is independent of production. 
Under share lease, the rent is a stated proportion of the total 
yield. There are two forms of the share lease namely 'ABUSA' 
system and Abunu system. Under the Abusa, one-third of the produce 
goes to the landlord and the remaining to tenant. 'ABUNU' tenancy 
is where the share is half each, (Dadson, 1969). Dadson, reported 
that the economics of the different forms of tenure may be examined 
or demonstrated with reference to their effects on the amount of 
various resources applied and the level of production induced, the 
size of farm business, the selection of enterprises ie, type of 
products; the horizon of investment; the length of lease; 
willingness to invest; the life of investment and arrangements 
regarding compensation for unexploited resources.
2.4 Comparative Efficiency of Tenancy (Sharecropping) and Owner-
Operatorship Systems in Resource Use
A lot has been written and debated about the comparative 
efficiency of resource allocation in agriculture under alternative 
forms of land tenure in the economic literature related to land 
reform and agricultural development in less developed countries. 
According to Ip and Stahl (1978), a large body of economists and 
other social scientists concerned with underdevelopment contend 
that tenancy (especially sharecropping) results in an inefficient 
allocation of resources as well as a reduced incentive to improve
30
agricultural land. This school of thought also holds the opinion 
that the persistent poverty of the rural population of less 
developed countries is due to substantial variations of tenancies 
as forms of contractual arrangement. To this school of thought, 
land reform measures such as reduction in cash rental rate, 
abolition, of sharecropping and minimum term leases are viewed as 
policy instruments that can improve development prospects.
Others, however, disagree with this view. Those of the "equal 
efficiency" school argue that the form of land tenure has no 
bearing on allocative efficiency and would attribute the poverty in 
t^« agricultural sector of less developed countries not to the 
prevailing land tenure arrangements but to their factor endowment 
which is a large body of unskilled labour relative to land and 
capital. This school also believes that arguments of landireform 
proponents' in support of reform are more often than not on 
normative welfare criteria rather than positive criterion of 
economic efficiency, (Ip and Stahl, 1978). An empirical dimension 
has been added to the debate in an attempt to resolve the 
controversy. Results have varied, but generally it has been found 
that tenancy is not necessarily less efficient than owner 
cultivation. According to Ip and Stahl (1978), the theoretical 
arguments of the equal efficiency school as well as the empirical 
studies purporting to support the equal efficiency school seem to 
be seriously misleading. The limitations of their analysis stem 
from their failure to take account of the interactions and linkages 
of the agricultural and other sectors throughout the development
31
process (Ip and Stahl, 1978). It is contended that the 
"efficiency" of alternative land tenure arrangements and associated 
land reform recommendations cannot be analysed out of context of 
these intersectorial linkages and interactions. Land reform, and 
the choice of an optimum land tenure system, has implications not 
only for the efficiency of resource allocation in the farm sector 
as a whole. In their conclusion, Ip and Stahl (1978) noted that 
when transaction costs, the role of entrepreneurship, and economic 
incentives are explicitly introduced and analysed in the framework 
of intersectoral interactions and linkages, land reform measures 
redistributing land to the peasants, substituting owner-cultivers 
for share tenants, tend to improve agricultural production 
efficiency, resource allocation between farm sector and other 
sectors, and contribute to economic development of less developed 
countries, contrary to conclusions reached by writers of -equal 
efficiency1' school.
Bhaumik (1991) in his paper on “Tenancy and Resource 
Allocation" covering 224 tenant households in 12 villages in West 
Bengal of India, found that on the whole there seems to be a 
tendency on the part of farmers to use higher levels of inputs per 
acre and to achieve better yields on their owned land compared with 
land farmed by sharecroppers. This, according to Bhaumik 
illustrates the negative aspects of crop-sharing systems. Such a 
situation emerges due to the ineffective monitoring of tenants' 
activities by landlords. He further found that there is no 
significant difference in economic performance between the owner-
32
operator and fixed cash rent tenant households. It is shown that 
for the small marginal and landless rural people, sharecropping is 
a means for their survival, but it plays a negative role by 
discouraging agricultural investment and hindering agricultural 
productivity, (Momin, 1991).
Feder and Ochan (1987), hypothesised that the negative effects 
of sharecropping can be attributed to two related factors: (a)
ownership insecurity: with ownership insecurity, investments in 
land improvements and equipment for land cultivation may be more 
lacking than under secured ownership. This is due to the 
uncertainty as to the length of tenancy which may affect a farm's 
long term planning. This situation will induce farmers to shift 
investment to activities not related to land cultivation or to 
invest less (and consume more), (b) Ownership insecurity does not 
allow land to be used as a collateral for loans. Lack, of 
collateral limits the farmers' ability to borrow from institutional 
lenders because unsecured loans are more risky for such lenders. 
Constraints on credit limit the farmers' investment possibilities. 
Both factors imply that ownership insecurity reduces farm capital 
formation and land developments and hence productivity is affected.
Migot-Adholla et al (1990), while sharing the same views on 
tenancy systems limiting land improvements and access to 
institutional credit, debunk the notion that tenure insecurity is 
a source of agricultural resource use inefficiencies. In their 
study which was carried out in three districts in Ghana, they found 
that tenure security is high as measured by rights over land and
33
low incidence of dispute, except for migrant farmers from other 
regions. They further noted that, the issue is not gross 
inequality in land distribution as some writers claim, but the 
extent to which indigenous land rights may be a constraint on 
agricultural development.
Reynolds (19 77) held the view that as the share tenant 
receives only a fraction of the output and only a portion of the 
marginal product of any tenant-supplied input, he would be 
encouraged to undersupply these inputs and thus produce 
inefficiently compared with fixed-rent and owner-operated 
contracts. Empirical work, by Vernon (1971) tends to undermine the 
proposition that share tenancy is less efficient than fixed-rent 
and owner operated systems. He exemplifies the theoretical 
inefficiency of labour input by constructing hypothetical partial 
budgets for the use of fertilizer and insecticide on the assumption 
that the landlord shares in cost. He notes that "the analysis is 
consistent with the proposition that share tenancy does reduce the 
incentive for intensive use of labour inputs and for the use of 
output increasing inputs such as fertilizer and insecticides. 
However, in his study, it appears that share tenancy where landlord 
provided other inputs apart from land may actually encourage a more 
rapid rate of adoption of labour saving technologies than would 
occur under fixed rent holders or owner-operatorship system. This 
is expected since the farmer gets rrore for less labour input. He 
further notes that an empirical evidence collected in the 
Philippines tends to show that, on small farms, a higher output per
34
hectare was observed under share tenancy than under owner operation 
for the same size of farm growing the same crops; the converse was 
found for larger farms. Moreover output per man was lower on share 
tenancy again on small farms. In his conclusions, he notes that it 
is difficult to assess the statistical significance of his findings 
and as a result support from them for the traditional view of 
inefficiencies associated with share tenancy.
However, some studies have established that in terms of 
superiority in the efficient use of resources, land improvements 
and increased output levels, owner-operatorship and cash rent 
systems should be recommended, (Bhaumik, 1991 and Dadson, 1969).
Migot-Adhollar et al. (1990) study on "land tenure and
agricultural productivity in Ghana” is the most recent study 
conducted with regard to land tenure and agricultural production. 
Their study covered selected communities and their conclusions were 
based on qualitative explanations of the data they collected. 
Therefore a study using a quantitative approach and conducted in a 
different geographical area could contribute to clearing the 
controversies surrounding tenancy and agricultural production 
efficiency.
2.5 Concept of Efficiency
Efficiency in general refers to a ratio of what is produced to 
input used, (Makeham and Malcolm, 1986). For example, Raleigh 
(1958), notes that land is said to be used efficiently when it 
yields optimum returns from a given enterprise. In the literature
35
on the concept of efficiency of resource use, the concepts of 
economic efficiency (ie. allocative or price efficiency) and 
technical efficiency are normally encountered. Technical 
efficiency refers to the ability to obtain the highest amount of 
output with given amounts of factor inputs and allocative 
efficiency is the concept of efficiency in which resources are 
allocated in the "Pareto" sense (optimum output) so that marginal 
value products of resources are equal to their unit prices, 
(Onyenwaku, 1991).
Heady and Jensen (1954), outlined a number of factors which 
affect labour efficiency. These include enterprise combination, 
replacement of labour with capital and equipment, the amount of 
capital combined with a given amount of labour and how labour is 
managed and supervised. As has already been noted, substituting 
capital and high capacity machinery for labour can also increase 
work, output per man. Optimizing output results in economic 
efficiency. On many farms, substitution of capital for labour can 
greatly increase labour productivity and incomes if the displaced 
labour can be combined with more capital to expand output and size 
of operations. The efficient use and productivity of any single 
resource depends on the quantity of other resources it combines 
with (Heady and Jensen, 1954). According to them, the major reason 
why labour is used so inefficiently on many farms is that the farms 
are small and don't have enough resources to combine with labour on 
hand. A very large part of the labour inefficiency and low incomes 
on subsistence and sharecropper farms and even on many commercial
36
farms can be solved by adding more capital to the available labour 
supplies. Adding more capital on farms with limited funds requires 
the use of the opportunity cost principle so that capital is put 
into highest profit enterprises for maximum labour efficiency and 
income.
Land productivity relates to the ability of land to yield 
crops. There are a number of factors that determine the magnitude 
of crop yields. Among these factors are fertility of the soil, 
water supply, the availability and the relative proportions of 
capital and labour input and physical condition of the soil. Soil 
fertility, according to Acquaye (19 69) refers to the capacity of 
the soil to supply nutrients both major and minor, in adequate and 
balanced amounts to plants . A soil may be fertile yet unproductive 
due to poor and unfavourable physical conditions. Conversely, a 
soil may be poor in fertility, yet by the use of fertilizers and 
irrigation, it may be made to produce high yields . Land per se is 
unproductive unless combined with capital and labour inputs. The 
proportions in which these resources are combined may determine how 
efficient land is used. In Africa for example, land productivity 
is considered low because of the mismatch between surplus land and 
limited labour and capital inputs, (Bishop and Toussaint, 1964). 
To improve upon productivity of land, factors such as crop and soil 
management should be of prior concern. Crop management entails 
first and foremost the selection of high yielding varieties adapted 
to local conditions. Secondly, the selected varieties should be 
resistant to local pests and diseases. Weed control measures,
37
irrigation and other requirements of the crop must be met.
Soil management in crop production is particularly concerned 
with soil water supply, soil fertility level and soil physical 
condition. Measures to improve soil fertility include green
manuring, addition of organic matter to the soil, use of 
fertilizers and intercropping with leguminous crops.
2.5.1 Methods Of Measuring Resource Use Efficiency
The debate regarding the best method to measure farm
performance and resource-use efficiency predates the subjects of 
farm management and agricultural economics as it is known today, 
(Phiri, 1991). Following the principles of production economics 
exemplified in the theory of the firm, maximizing profit has been 
regarded as the primary objective of the farm business. For
example, Bernard and Nix (1979) stated that the objective of farm 
management is to arrive at the particular output that gives greater 
profit than any other level of output. Similarly, Drucker (1968) 
stated that management must, in every decision and action, always 
put economic performance first. The above statements are in line 
with the theory of the firm which implies that a farm is performing 
well if it organizes resources in such a way that it maximizes 
profit. However, the assumption of perfect competition that is 
implicit in this approach has been criticized by many economists. 
They argue that, because knowledge about the future is imperfect, 
agricultural production decision making takes place in an 
environment of uncertainty. Dillon (1979) notes that this is
38
especially true in under-developed agricultural systems where 
underdevelopment itself compounds the uncertainty, regardless of 
whether the decision maker is a subsistence owner, landlord or 
commercial producer- Economists argue that in the face of risk and 
uncertainty, smallholder farmers select crop combinations that 
facilitate sufficient food income for the family's needs. This 
situation is described by Simon (1955); Cyert and March (19 63) as 
"satisficing" and by Lipton (1968) as a "Survival algorithm".
Where the profit maximizing and household objectives 
approaches have been applied to small-scale agriculture, the 
results have almost been at odds with each other (Phiri, 1991). 
Measures of farmer performance based on the profit maximization 
approach invariably lead to conclusions that small scale farmers 
allocate resources ineffienciently and that they are lazy and 
irrational decision makers. Measures based on the household 
objectives approach lead to conclusions that farmers allocate 
resources efficiently according to their subjective judgement of 
future outcome. Whether or not uncertainty is incorporated into 
the analysis, gross margins or linear programming method is helpful 
in comparisons and farm modelling especially in traditional 
agriculture (Phiri, 1991). Despite criticisms levelled against the 
profit maximizing approach of assessing resource use efficiency, 
many studies have used the approach. Kumbhakar (1994) applied the 
profit maximizing model using flexible production function to 
estimate efficiency in the use of resources. In his study, a 
translog production function is used to estimate the efficiency of
39
227 small-scale farms. Kumbhakar (1994) used the profit maximizing 
framework to estimate technical and allocative efficiencies of the 
farms. The empirical results show that so far as allocative 
efficiency is concerned, majority of the farms are found to be 
under-users of endogenous inputs such as fertilizer, human and 
bullock labour. Sankhayan (1993) used the Cobb-Douglas production 
function and the marginal value product and marginal cost 
techniques to respectively examine the resource productivity and 
allocation efficiency on a number of farms. The results of the 
study indicated that resources were inefficiently used or 
allocated. Matekwa and Mbata (1993) studied the resource use 
efficiency among small-scale farmers in selected areas of Western 
Kenya. A production function and the allocative efficiency of the 
resources are estimated. The results of the study indicate that 
farmers underutilized modern types of inputs such as fertilizer, 
pesticides and improved inputs but overutilized farm labour - 
Olomla (1991) compared capture fisheries with aquaculture (fish 
farming) in Ondo State, Nigeria to determine how efficient the 
systems were utilizing resources and how production could be 
economically increased. In determining the efficiency of resource 
use, factor productivity and returns to scale, production functions 
were estimated using the Cobb-Douglas production function. In his 
study, the marginal value product was compared with the input price 
to determine the resource use efficiency. Hopper (1965) made an 
attempt to study allocative efficiency on a sample farms by 
determining: first the production functions underlying the
40
traditional village production and secondly, the actual allocation 
of resources the farmers made among their production alternatives . 
The Cobb-Douglas production function was used for the estimation. 
In estimating or determining the allocative efficiency, Hoper 
(19 65) notes that if a farmer has allocated his inputs among his 
production alternatives efficiently and if he is operating under 
conditions of competition in the product and factor markets, then 
the marginal value product of the input must equal to the input 
price. Other approach based on the profit maximizing assumption 
used extensively to determine resource use efficiency is the unit 
profit function approach. Dittoh (19 88), Lau and Yotopoulos 
(1972), Sidhu (1974), Xotopoulos, Lau and Lin (1976) and Garcia et 
al (19 77) have used the unit profit function approach in assessing 
resource use efficiency. The use of the unit profit function to 
determine resource use efficiency according to Dittoh (1988) has 
its limitations. Chard and Kaul (1986) outlined certain in built 
characteristics in the use of the unit profit function which make 
its use a bit complex. These characteristics are that (i) own 
price elasticity of factor demand is always elastic with Cobb- 
Douglas function (ii) all variable factors are complementary to 
each other and hence the substitutive relation is ruled out by this 
function (iii) cross-price elasticity of all factors with respect 
to price of any other factor is the same in magnitude and in sign 
(iv) the effects of change in any fixed factor is symmetric on all 
the variable inputs and (v) price elasticity df factor demand with 
respect to output price is always more than one (elastic). All
41
these factors must be satisfied if the unit profit function is to 
be applied. The unit profit function is most appropriate for 
determining relative efficiencies of large and small farms, of 
different technologies and of different scales of operation eg 
large and small scale irrigation schemes (Dittoh, 1988). As has 
been previously noted by (Phiri, 1991), gross margins analysis is 
more suitable for comparing resource-use efficiency among different 
groups of farmers producing especially on small-scale basis. This 
method is used to determine farm profitability which according to 
Garcia et al. (1977), is influenced by the enterprise mix and
efficiency in input usage.
The Gross Margins is measured as the difference between the 
total value of output and the total variable cost of production. 
The gross margins method is used to study the financial performance 
of an enterprise, i.e. the productive components of a farm to 
obtain information about the enterprise's strengths and weaknesses 
in greater depth than can be derived by whole farm analysis 
(Buckett, 1981).
Taylor and Turner (1989), note that the technique has the 
advantage of being a quick and simple method of assessing 
enterprise performance. It is probably the most commonly used 
measure in farm analysis and planning and also is now used 
extensively in publications (Makeham and Malcolm, 1986). The Gross 
Margins per hectare of crop and per head of livestock are widely 
used for comparative analysis of activities on one farm and between 
farms in similar environments. For example, if the Gross Margins
42
(GM) on one farmer's maize crop is £150 per hectare and the average 
GM of a neighbouring farmer is <£300, then he should seek; advice on 
the technical reasons for his poorer performance given marketing 
conditions and both farmers using identical inputs. Valid 
comparisons can be made in terms production unit common to all of 
the farms or activities being compared. This unit can be land 
area, if the land used by each is equally suitable. It could also 
be per unit of labour, (Makeham and Malcom, 1986). The GM method 
is claimed to have more value for inter-farm comparisons than the 
whole farm efficiency factors because they are less influenced by 
farm size and type (Buckett, 1981).
Gross Margins are frequently criticised because they neglect 
fixed costs. Proponents of full costing, the time-consuming 
technique which attempts to allocate fixed costs to activities even 
if it is arbitrary, suggest that it is infinitely better than GM 
analysis. Properly undertaken, the GM method would help avoid such 
mistakes (Buckett, 1981).
In contradiction to the view normally help that the full 
costing is better than the Gross margins, it has been suggested 
that farmers have more control over fixed costs than over variable 
costs. This idea can have an element of truth in some situations. 
If a farmer has intentions of maximizing his Gross Margins, he 
possibly has little choice in the variable cost levels he must 
employ to attain his goal. He can, however, exercise his judgement 
on the machinery and other fixed costs items, (Buckett, 1981).
43
Phiri (1991) used the GM technique to determine the efficient 
resource use among different groups of small scale farmers. He 
compared the average GM per hectare and per unit of labour among 
the different groups of farmers. In his analysis, he noted that, 
if the GM per unit of input is greater for a given group of 
farmers, then that group used that input more efficiently than the 
other and vice-versa.
The strengths of the GM technique are the (i) it is a simple 
method of assessing efficiency, (ii) the records and accounting are 
easy and quick., (iii) it does indicate areas of strengths and 
weaknesses in terms of resource use (Taylor and Turner, 1989). The 
major weakness as has already been noted is the exclusion of fixed 
costs in the calculation of GM. This weakness is not a major 
problem as far as small scale agriculture is concerned. The reason 
is, small scale agriculture does not normally involve substantial 
investments in fixed cost items and hence their exclusion will have 
little, if any, impact on the analysis.
Though the use of gross margins may be beneficial, for policy 
purposes the profit maximizing approach of determining resource use 
efficiency is more preferable. This is because the gross margins 
analysis is more useful for the comparison of individual farms than 
aggregate farms for a given growing period. Since it is assumed 
that the production levels of small-scale farmers do not vary much 
over time, meaningful policy conclusions can be drawn if the 
production function approach in determining resource use efficiency 
is adopted.
44
The structure of resources is viewed in two ways. One 
examines the proportions of the resources and the other concerns 
the composition of each individual resource. Below is the 
theoretical foundation for objective I.
Small scale agriculture in Africa is characterized by excess 
supply of land and limited labour and capital, (Mellor, 1966). 
With the economic transformation and changing agricultural 
technologies, more capital intensive technologies are adopted as 
observed in the developed countries to meet the fast growing 
population and industrialization. As a result, the type of farming 
system, the sizes of farms cultivated, the type of capital inputs 
employed, the age structure of farmers, the type of manpower used 
on the farms in terms of technical and managerial skill and the 
form of farm tenure among others in agriculture must change with 
changing times to move from subsistence production to commercial 
oriented production.
The theoretical foundation for objective II is that land 
problems and policies of a nation depend partly on the physical 
characteristics of the land itself but more importantly upon the 
stage of economic development, customary or legal rights and the 
prevailing national attitudes of the people of the country towards 
land, (La-Anyane, 1969). customary institutions and prevailing 
attitudes determine the land tenure arrangements of a nation. 
There are many different types of tenure arrangements in Ghanaian 
agriculture. These arrangements influence the efficiency with
2.5.2 Theoretical Framework of Analytical Methods
45
which inputs are used. The arrangements also affect the degree of 
uncertainty encountered in the operation of the farm, (Bishop and 
Toussaint, 1958). The specific features of land tenure which have 
constituted barriers to improvement in agriculture are the 
fragmentation of holdings, the difficulties involved in acquiring 
new land, the inability of a farmer to make permanent improvements 
or plant permanent crop on land which is commonly owned or on land 
which is held by pledging short-term lease, and the absence of 
registration (La-Anyane, 1969). The tenure system can and do shape 
the production structure and the land use pattern, (Ofori, 1973). 
The system can influence the organization of farms by placing 
constraints upon the accessibility and exploitation of 
opportunities on the land thereby affecting the security of use of 
land.
With resource use efficiency, the farmer is considered to be 
a rational producer and that he allocates resources in a way to 
maximize profit. A rigorous comparison of the allocative 
efficiencies of any groups of farms requires that the farms be (i) 
characterized by constant returns to scale (ii) that the farms be 
represented by the same production function and (iii) that the 
farms face the same configuration of input and output prices 
(Onyenwaku, 1991). To determine the allocative efficiency, a
production function is estimated. The production function is 
assumed to satisfy the condition that the marginal physical product 
of any input is positive and should be declining. It is also 
assumed that all inputs can divided into two categories: fixed and
46
variable where in the short run the inputs are fixed and in the 
long run they are variable (Mansfield, 1994). A farm is said to be 
allocative or price efficient if it maximizes profit by equating 
the value of the marginal product of each variable input to its 
price.
Theoretically, it has been noted by Taylor and Turner (1989), 
that though full cost accounting has its advantages, for most farm 
businesses, it is impractical. As a result of this situation, a 
system has been developed which overcomes the problem of cost 
allocation largely by ignoring the costs which are difficult to 
allocate (regarding them as overhead cost) and concentrating solely 
on the performance of the enterprises relating to output and 
variable costs. This is called the Gross Margins system which has 
the advantage of being a quick and simple method of assessing 
enterprise performance. No fixed costs are taken into 
consideration. But it should be noted that when fixed cost is a 
substantial proportion of total cost, this method is unacceptable.
47
CHAPTER THREE
3.0 METHODOLOGY
3.1 Data and Sampling Technique
Both primary and secondary data were used for the analyses.
The actual field work was done in April, 1995 but the data 
collected was based on the 1994 major growing season. Data on 
the 1994 minor growing season was not included because, according 
to the sampled farmers, harvest was very poor 'and insignificant 
as a result of poor rains.
A total of 100 farmers comprising 35 owner farmers, 50 
sharecroppers, 9 fixed renters and 6 leaseholders were sampled 
and interviewed. A random sampling technique was used to select 
the studied farmers. This was accomplished by the help of an 
extension officer. At each studied village, farm households were 
picked with a sampling gab of one i.e. farm household selection 
was alternated. After a farm household was selected, any member 
of the household who is actively involved in the cultivation of 
maize and farmed during the studied period was selected for the 
interview. Personal interviews were carried out with the sampled 
farmers by the use of structured questionnaires in their homes. 
The extension officer was present throughout the interview period 
which lasted for about a month to confirm some of the information 
provided by the respondents because he has been working with them 
for most of the time.
48
Data was collected on the total output of maize harvested in 
kilos, the amount of mandays used by each farmer (both hired and 
family), the land sizes cultivated in hectares, quantity/value of 
fertilizer, weedicide, seed, cutlass hoe and basket used for the 
major growing season. The output price used is the average of the 
farm gate prices received by all the sampled farmers. The prices 
used to value fertilizer, weedicide, cutlass, hoe, seed and basket 
were 1994 district level prices obtained from the district 
extension department. The cost of labour for farm work was 
calculated by finding the average of the cost per manday and the 
cost of cooked/raw food for hired labour. with regard to price 
paid for the use of land by different categories of sampled 
farmers, different prices were obtained. For sharecroppers, the 
price paid for the use of land was calculated based on the portion 
of the value of output received by the landlord. The sampled owner 
farmers do not pay any rent on the use of land, but for purposes of 
this study, how much they would have paid if they were to rent land 
for farming was used to represent the cost of land to them.
Information was also collected on the types of cropping 
patterns, mode of land acquisition by tenant farmers, length of 
tenancy, age and gender structure of sampled farmers, cost 
estimates of inputs, and types of labour and capital used by 
sampled farmers.
Secondary data was also collected on the climatic conditions, 
topography, population density, and vegetation of the study area 
from the district extension service department. Information on the
49
types of soils present in the study area was obtained from 
secondary source.
3.2 Methods of Analysis
3.2.1 Structure of Resource Use
For the structure of resource use in agricultural production, 
two methods were used. One method based on Hill and Ray's (1987) 
approach was used to analyse the composition of the resources and 
the other method, based on the cost estimates of the resources was 
used to analyse the proportions of the resources. In Hill and 
Ray's approach, the field data obtained were either described in 
the raw form or presented in a frequency distribution tables or 
cross-tabulation depending upon the objective in question.
In the second approach, the share of each resource in total 
cost was estimated. This gives an indication of the extent to 
which each of the resources is employed (Olomola, 1991).
3.2.2 Comparative Efficiency of Resource Use
With regard to the comparative efficiency of resource use in 
maize production in the study area by owner and sharecropping 
farmers, the Gross margins method on one hand, and the allocative 
efficiency method, based on the profit maximizing approach on the 
other hand were used. These methods from the literature have been 
widely applied to analyse resource use efficiency. The results 
from both methods were compared to find out if there were any
50
any differences but more focus was given to the latter method for 
policy purposes.
3.2.2.1 Gross Margins
The Gross Margins of an enterprise, say a farm unit, is 
defined as the value of the total product of the farm unit in a 
given period of time less the total variable cost of the farm 
unit in the same period. The Gross Margins per unit of the 
inputs were computed and compared between sharecroppers and owner 
farmers to determine which of the two farmer groups used the 
resources more efficiently.
Mathematically, the Gross Margins formula is given as
follows:
Gross Margins Q iP i  -  S X i X i
i=l
where Qj Total output obtained by a farmer in the last
crop year
Pi Price of 1kg of maize received by an ith
farmer
Total quantity of an ith input used up in the 
course of production during the crop year. 
Unit price of an ith input used up in the
course of production during the crop year.
i n .
51
In computing the Gross Margins per unit of an input say, 
labour, for a farmer, the total variable cost of production was 
deducted from the total output per farmer. The difference was then 
divided by the labour input to obtain the Gross Margins per unit 
labour for a farmer. The same procedure was applied to the other 
inputs for all the farmers. To compare the Gross Margins between 
the farmer groups, the average Gross Margins was computed for each 
farmer group. The decision criterion is, the higher the average 
Gross margins per unit of an input for a farmer group, the more 
efficient the group uses the input. This conclusion is based on 
whether there is a significant difference between the means of the 
Gross margins per hectare or per unit labour between the two farmer 
groups. The paired t-test was used to test whether there is any 
significant difference between the gross margins of the two farmer 
groups.
3.2.2.2 Allocative Efficiency
To compare the allocative efficiencies of owner and 
sharecropping farmers, it is assumed that these two groups of farms 
are characterised by (i) constant returns to scale (ii) represented 
by the same or neutral production function and (iii) facing the 
same configuration of inputs and out prices (Onyenqaku, 1991).
It is also assumed that the farmer is a rational producer and 
that he is a profit maximizer.
52
In determining the relative allocative efficiencies of the two 
farmer groups, a Cobb-Douglas production function was estimated 
using Ordinary Least Squares regression analysis. Cobb-Douglas 
production function was used among the other production functions 
because it is rrostly used in applied research and easiest in 
handling mathematically (Koutsoyiannis, 1979).
Assuming output of maize is affected by land, labour and 
capital given other factors which might also affect output of 
maize. Then a production function is specified as follows:
Q = f(Xw X2, X3, u) ........... (1).
where Q = output of maize, = land, X2 = labour, X3 = capital 
and U = error term.
To estimate the Cobb-Douglas production function, the equation 
used is:
Qi = A X ^ X ^ X / ^ ........ Ut ............... (2)
where Ql = total output of maize in kilos harvested by an ith 
farmer
A  = a constant term
Xt = total land area cultivated to maize in hectares
X2 = total amount of labour used in mandays on the maize
farms studied
X3 = value of capital inputs used on the studied farms.
53
Ut = error term assumed to satisfy all the stochastic 
assumptions.
a*, a3, are the respective coefficients of land, labour
and capital variables.
To obtain the estimation equation from equation 2, the log- 
log function was applied. The regression coefficients, the t- 
ratios, the R2-ratios and the F-ratios were determined for
sharecroppers, owner farmers and the poded sample.
A farmer is said to be allocative efficient if he maximizes 
profit by equating the value of the marginal product of each 
variable input to its unit price. Thus the allocative efficiency 
index for each farmer group was computed as follows:
MVPU = PjMPPij = rlJKij
Kjj = MVP*, ...................... (3)
ru
marginal value product of the ith input for the
jth farmer group
the marginal physical product of the ith input for 
the jth farmer group
average price of per kilo maize received by jth 
farmer group
price of the ith input paid by the jth farmer
group
the allocative efficiency index of the ith input 
of the jth farmer group.
which implies 
where MVPi:j =
MPPjj =
Pj =
54
Since the coeffiencients of land, labour and capital are 
straight elasticities, equation (2) is re-written to include the 
production elasticities as follows:
*ij = Piai A
where MPPi = a^Q^/X^
ai;j = output elasticity of ith input for jth farmer group
Qj = mean output for jth farmer group
Xi;j = mean of ith input for jth farmer group.
Other parameters are as defined previously.
The allocative efficiency index is a measure of efficiency in 
resource use. The input is overutilized if K<1 and underutilized 
if K<1. Absolute allocative efficiency requires that K = 1 for all 
inputs (Onyenwaku, 1991; Ellis, 1992).
To test whether there was any difference in the coefficients 
of the inputs between the two farmers groups, the Chow test was 
used. Returns to scales were also computed to find out if the 
sampled farms are characterised by constant returns to scale.
55
CHAPTER IV
4.0 RESULTS AND DISCUSSION
4.1 Introduct ion
In this chapter is presented a discussion on the results of 
the analysis. The chapter begins with discussions on the 
composition and proportions of land, labour and capital which 
constitute the structure of the resources. In the discussion of 
the structure of the resources, comparisons are made with related 
studies where necessary. The second section of the chapter
discusses the efficiency in the use of land and labour by
sharecroppers and owner-operators.
4.2 Structure of the Resources (as defined by their Composition)
4.2.1 Land Structure
Land structure is considered in terms of farm sizes, type of 
cropping pattern and forms of land tenure.
4.2.1.1 Farm Sizes
The land areas cultivated to maize by the sampled farmers 
during the 1994 growing season ranged between 0 and 2.4 hectares. 
Table 1 shows the percentage distribution of land sizes cultivated 
solely to maize by sampled farmers. It is seen from the table 
that, 47% cultivated land sizes between 0 and 0.4 hectares, 20% 
between 0.41 and 0.60, 13% between 0.61 and 0.80, 5% between 0.81
56
and 1.0 and 15% cultivated land sizes greater than one. 
Cumulatively, 85% of the farmers cultivated land areas less than or 
equal to one hectare to maize only and 15% cultivated land areas 
greater than one hectare but less than or equal to 2.4 hectares. 
The distribution of land sizes cultivated to maize shows that a 
higher percentage of the farmers cultivated small areas. The 
distribution of land holdings in the area also compares with 
distribution by size holdings in the Eastern region (MOA, 1991). 
Asked why they operated land areas of such sizes, about 90% of the 
farmers responded that, the cultivated areas are based on their 
capabilities to manage the farm, particularly in terms of labour 
availability: 8% responded that, those were the land areas they 
could lay their hands on and the remaining 2% did not give any 
definite response. The implication of these responses is that, 
provided labour could be made available, larger areas could be 
cultivated.
Table It Distribution of land sizes cultivated
to maize only in the 1994 major season
Land sizes in hectares Number of farmers
0 - 0.4 47
0.41 - 0.60 20
0.61 - 0.80 13
0.81 - 1.0 5
> 1 15
Source: Appendix C.
57
4.2.1.2 Cropping Pattern
The predominant farming practice in the study area is mixed 
cropping. Out of the 100 farmers interviewed, 83% grew maize as an 
intercrop and 17% as a monocrop in the 1994 major crop season. 
Maize is intercropped mainly with cassava though there are few 
instances of a third crop (Table 2). It can be seen in Table 2 
that out of the 83% who mix-cropped, most (76%) mix-cropped maize 
and cassava, 3% mix-cropped maize, cassava and cocoyam, 2% mix- 
cropped maize, cassava and plantain and 2% mix-cropped maize, 
plantain and cocoyam. The average land areas cultivated to the 
common types of cropping patterns i.e. maize-cassava intercrop and 
maize monocrop show that almost the same land sizes are cultivated 
to both types of cropping patterns.
Those farmers who monocropped maize attributed the practice to 
two main reasons: (i) land which is prone to waterlogging and
therefore not suitable for cassava and (ii) the possibility of 
growing at least two crops of maize within the year. The 
distribution of farmers by reason for choice of cropping pattern in 
maize production is presented in Table 3.
58
Table 2: Distribution of Farmers by Type of Crop Mixtures
Type of Crop mixtures % of Farmers Average land area (Ha)
Maize only 17 0.6
Maize and Cassava 76 0.7
Maize, Cassava & Plantain 2 0.9
Maize, Cassava SCocoyam 3 0.6
Maize, Plantain &Coc-oyam 2 1.1
Total 100 0.7
Source: Field Data
Note: The mix-cropped farmlands are first cultivated to maize
and later intercropped with cassava.
59
Table 3t Farmers' Reasons for Adopting Particular Cropping 
Pattern
Cropping Pattern Reason % of Farmers
Monocropping 1. area gets waterlogged and 
does not allow for 
cassava cultivation
2. allows for continuous
13
cropping 14
Total 16
Mixed cropping 3. Security against crop 
failure
4. land suitable for both
55
maize and cassava 10
5. Consume cassava and sell
maize for other needs 6
6. Cropping pattern inherited 
from our fathers 5
7. Land use is maximized 8
Total 84
Source: Field Data
60
It is observed from Table 3 that out of the 17 farmers who 
monocropped, 13 attributed the practice to a technical constraint. 
This implies that had it not been the waterlogged nature of the 
lands, they would have cultivated maize and cassava. In the case 
of mixed cropping, the major reason given for practising such a 
system is security against crop failure i.e. in case there is 
failure of the maize crop, the farmers would at least be left with 
a second crop.
4.2.1.3 Bush Fallow
This is a system where land is left uncultivated for a number 
of years to allow it to regenerate its fertility before it is 
cultivated again. This is a common practice in the study area. 
Data collected on the number of farmers who practise bush fallowing 
indicates that 89% of the farmers use the system and only 11% do 
not fallow land (Table 4).
It was found that the average number of years that lands are 
left to fallow in the area is three years, (Table 5). From table 
4., 47.2% of the farmers stated 3 years as the period of fallow, 
22.5% stated 2 years and 16.8% stated 4 years. 13.5% stated 5 
years and above. This distribution shows that the average number 
of years land is left to fallow in the area is 3 years. This 
period of fallow has been drastically shortened compared to the 
fallow periods in the past which could range between 7 and 15 
years. With this shorter fallow period, the soils may not fully 
regain their fertility and this may have negative implications on
61
production levels. It also means that the planning horizon of
sharecroppers may be inadequate and this could mean little 
investment in the land which could result in low productivity.
Table 4 j Distribution of Farmers by Reason for Practising
or not Practising Bush Fallow
Practice Reason % of Farmers
Users 1. replenishment of soil
nutrients 89
Total 89
2. application of fertilizer 
and animal manure 3
Non-Users
3. Not easy to acquire 
land for farming 8
Total 11
Source: Analysed Field Data
62
Table 5: Distribution of Fallow Periods
Fallow Period (Years) Frequency % of Farmers
2 20 22.5
3 42 47.2
4 15 16.8
5 5 5.6
6 3 3.4
7 3 3.4
8 1 1.1
Total 89 100
Source: Appendix B.
4.2.1.4 Land Tenure System In the Study Area
Information obtained on the land tenure arrangements shows 
that owner-operation, share tenancy, fixed rent and leasehold 
systems are present in the study villages. Amongst these 
arrangements, sharecropping is widely practiced, followed by owner- 
operation, then fixed rent and lastly leasehold, (Table 6). Fixed 
rent and leasehold arrangements are not common in the study 
villages because of unavailable funds to rent or lease farmlands by 
prospective farmers.
It was discovered from the data collected that, farmlands can 
be acquired from community members, families, chiefs and 
landowners. Among these sources of land acquisition, community 
members form the major source of acquiring farmlands by tenant 
farmers (Table 7). The common mode of acquiring farmland by
63
tenants in the study villages is to provide a drink, usually local 
gin. in few cases where drinks are not demanded by landowners, 
tenants are made to pay a token amount in lieu of the drink. 
Acquiring farmland in the study villages is not a difficult task if 
the lands are available. The problem is with the length of tenancy 
which from the data collected is an average of three years after 
which the farmland should be left to fallow. Normally, the 
landlords do not specify the period these farmers can farm the 
land. In few instances, tenants are allowed to farm the land for 
as many years as the farmers deem necessary. This uncertainty 
about tenancy period can influence land use decisions by tenants, 
which may be inimical to land development.
Table 6» Distribution of farmers by type Tenurial Arrangement
Type of Farmer Groups Number of farmers in each group 
(*)
Cwner-operators 35
S harec ro ppers 50
Fixed-renters (cash) 9
Leaseholders 6
Total 100
Source: Appendix C.
64
Table 7: Percentage Distribution of Farmers by Type of Tenure
and Source of Land Acquisition
Source Owner Sharecropping Fixed Rent Leasehold Total
Community
Members
- 47 6 6 56
Family 12 1 2 _ 18
Own Land 20 _ _ 21
Chief 3 2 1 _ 6
Total 35 50 9 6 100
Sources: Field Data.
In summary, the description on the structure of land use in 
maize production indicates that most of the farmers operate land 
sizes less than one hectare, that mixed cropping is widely 
practiced, that farmers are predominantly sharecroppers and owner 
operators and that fallow periods are short. Small farm sizes with 
limited use of improved technology of farming may have adverse 
implications on output because all things being equal, land area is 
positively related to output levels. Short fallow periods in the 
absence of use of fertilizer affects soil productivity and hence 
output.
4.2.2 Labour Structure
Labour is an important input in small-scale agricultural 
production. This is because the availability of labour determines 
the farm size in small-scale farming. It is known that small-scale 
agricultural production relies on family labour and therefore the
65
size of the adult farm family determines in most cases, the size of 
the family farms. Labour structure is examined in terms of its 
size (including household and hired labour), age and gender of 
farmers and type of labour by task.
4.2.2.1 Size of Labour Force
Different types and combinations of labour are used for maize 
production in the study area. In the 1994 growing season, hired 
labour (ie, by day labour and contract labour), exchange labour or 
"nnoboa", and family labour were used on the various farms. Family 
labour is reported to be used by 98% of the farmers (Table 8).
Table 8: Type of Labour Used on The Farms Studied
Labour Type Percentage of Farmers 
Employing Labour Type
Family labour 98
Hired labour (contact and by day) 75
Exchange labour 9 I
Family labour ONLY 18
Hired labour ONLY 2
Family and hired labour ONLY 64
Family and exchange labour ONLY 5
Hired and exchange labour ONLY 7
All types of labour 4
Source: Appendix B.
66
From Table 8, it can be seen that 75 and 9 percent used hired 
labor and exchange labour respectively. Eighteen percent used only 
family labor, 2% used only hired labour and none used only exchange 
labour, sixty-four percent (64%) used both family and hired labour 
5% used both family and exchange labour and 7% used both hired and 
exchange labour. Family labour is the major source of farm labour 
and exchange or hired labour is used as supplementary labour. 
Hired labour, comprising of contract and by day labour was rarely 
used alone by the farmers. Hired labour in most cases was used to 
supplement the efforts of family labour though there were instances 
where hired labour employment was higher than family labour. it 
was observed that hired labour employment was mainly for specific 
farm tasks such as land clearing which is a strenuous task, and 
weeding under the crop. Although hired labour was rarely used 
alone by the farmers, its importance should not be glossed over 
since it is the second popular form of farm labour used (Table 8). 
It is observed from Table 8 that, 4% of the farmers interviewed 
used all forms of labour during the growing period. This small 
percentage is due to the small number of farmers who exchanged 
their labour. This implies that exchange labour is scarcely used 
in the study area. Farmer co-operative were not found in the study 
area.
A look at the average labour supply per hectare on mixed and 
monocropped farms shows that labour supply per hectare is higher on 
monocropped farms than on irdx-cropped farms (Table 9). This 
finding is supported by work done by Kwadzo (19 95) and Mensah
67
(1982) in which they found that the total labour supply per hectare 
on maize intercropped with cassava was less than the labour supply 
on maize rronocrop. The supposed reasons are that: (i) on mixed- 
cropped farms there is less weed population compared to rronocrop 
farms and as a result, the labour input requirement for controlling 
weeds is lower on rrdxed-cropped farms and (ii) on mixed-cropped 
farms, labour input is shared between/among the different crops and 
therefore the amount of labour input devoted tothe major crop is 
reduced. On the contrary, on monocrop farms, all the labour input 
is devoted to the single crop.
Information documented by Mensah (1982) on the average labour 
input per hectare at different locations on small-scale maize farms 
in Ghana indicates that for maize rronocrop, the average labour 
input per hectare is 134 mandays. The average labour input per 
hectare on maize intercropped with cassava is 56 mandays. 
Comparing these figures i.e. 56 and 134 mandays to the ones 
obtained for this study i.e. 194 and 287 mandays in Table 9, it is 
observed that labour was not optimally employed onthe farms studied 
in this work. This might principally be due to the fact that 
farmers took longer time in completing specific tasks which could 
have been completed earlier had there been adequate labour input. 
Table 9 also shows the distribution of the average labor (hired and 
family) supply per hectare on mixed and monocropped farms. On the 
mix-cropped farms, hired labour constitutes 34% of the total labour 
input and family labour constitutes 66%. Hired labour on the 
monocropped farms constitutes 2 7% of total labour input and family 
labour constitutes 73% (Table 9). The presentation in Table 9 
indicates that family labour is mostly used on both types of
68
cropping patterns. Kwadzo (1995) and (Atsu et al. 1983) have 
reported that less than 20% of the total labour input comes from 
hired labour on maize farms. The results of this study in terms of 
hired labour input usage differs from that of (Kwadzo, 1995 and 
Atsu et_ aX., 1983). On both mixed and monocropped farms, the hired 
labour inputs are 34% and 2 7% respectively which are both higher 
than the 20% reported by (Kwadzo, 1935 and Atsu et al., 1983). 
This shows that hired labour is becoming increasingly important in 
terms of labour usage.
Table 9: Average Labour Supply per Hectare and Distribution of
Hired & Family Labour Supply per Hectare on Mixed & 
Monocropped Farms for the 1994/95 Growing Season
Type of Cropping 
Pattern
Average Labour 
Supply in 
MD/Hec
Hired Labour 
Supply in 
MD/Hec.
Family Labour 
Supply in 
MD/Hec.
Total 
in %
Mix-Cropping 194 5497 (43%) 10569 (66%) 100
Monocropping 287 1299 (27%) 3574 (73%) 100
Sou res: Analysed data from Appendix P.
Family labour is noted to be the major source of labour for 
the farmers in the study area. It is, therefore, important to have 
knowledge about the composition of farm family sizes. It can be 
seen from Table 10 that 82% of the farmers have family sizes 
between 1 to 4,18% have family size between 5 to 9 and 1% have 
family size of 10. The average family size is computed to be 3.5.
69
Comparing this average figure to the average family size of 5.1 for 
rural households in the Eastern region of Ghana as reported in the 
1984 Analysis of Demographic Data by the Ghana Statistical 
Services, it is clear that the family size in the study area is 
lower than the regional average. It is also important to note that 
not all the farm household members were engaged in farming during 
the cropping season. In the Table 10, it is observed that not all 
farm household members are in farming. In 95% of the cases, 
children in farm households attend school and only help when they 
are on vacation.
Table 10: Percentage of Household Members Engaged In Farming
Family No. of Farm Total % Farm Total % in Farming
Size Households Household Household Household (5)(4) x 100
(1) (2) Members (3) Sizes (4) Farmers (5)
1 6 6 1.7 5 83
2 19 38 10.9 32 84
3 29 87 25 82 94
4 27 108 31 97 90
5 10 50 14.3 30 60
6 7 42 12 32 76
7 1 7 2 4 57
10 1 10 2.8 6 60
Total - 348 10 0 288 83
Source: Appendix B.
70
4.2.2.2 Distribution of Type of Labour by Task
The production of maize involves a number of activities from 
land clearing through to harvesting, each of which was undertaken 
by specific type(s) of labour. Land clearing is considered very 
strenuous but time specific and so farmers prefer to hire labour to 
achieve this timely demand. However, due to financial constraints, 
the farmers try to handle the task themselves. This handicap 
causes delays depending on the size of the farm. Forty-two percent 
of the farmers hired labour for land clearing in addition to their 
own labour. Land clearing is carried out by men. The next task, 
land preparation, is mainly undertaken by the farmer himself with 
the help of his wife and sometimes children. Planting which 
follows land preparation when the rains set in is one of the 
important tasks on the farming calendar. This farm activity was 
mainly done by the farm family. In few instances, farmers employed 
the services of communal labour to complement their efforts. The 
next farm task is weeding or brushing under the crops. This task 
is also important since inability to control the weeds on timely 
basis may affect the yield. This task is considered difficult and 
requires some skill since the crop can be destroyed if not 
carefully undertaken. It was discovered that, 75% of the farmers 
prefer to use weedicide in controlling the weeds because it is 
considered rrore effective than manual weeding. In 22 cases, where 
weedicide was applied, the spraying was mostly performed by hired 
labour. Where weedicide was not applied, about 70.5% of the farm 
households interviewed performed the weeding by themselves, 19.2%
71
hired labour for the weeding, (Table 11). An estimate of the 
labour input used in manual weeding reveals that about 25% of the 
total family labour input was devoted to this task; and 30% of the 
total hired labour input went in to the same task. These 
percentages show that weeding is an important task to the farmer. 
Harvesting ends the direct farm work. This task was undertaken 
mainly by the farm family. Communal labour services were sought 
for harvesting. In two instances, only hired labour was used for 
harvesting. This was only in situations where all farm activities 
were performed solely by hired labour. After harvesting, the 
produce are hauled by the same labour doing the harvesting for 
storage.
Table 11s Distribution by Type of Labour for Manual
Weeding of Farms
Type of Labour Frequency Si by Type of Labour
Family 55 70.5
Hired 8 10.2
Family and Hired 15 19 .2
Total 78 99.9
Source: Field Data.
72
4.2.2.3 Age and Gender of Farm Household
The Analysed data on age distribution of the farm households 
shows that 24.3% are aged 19 years and below, 51.7% are within the 
age group 2 0 - 3 9  years, 21.8% aged between 40-59 years and 2% are 
aged above 60 years (Table 12). Cumulatively, 76% of the farm 
household are below 40 years. This age distribution indicates that 
there are more young people than older and middle aged farm 
household members in the study villages.
The gender composition also shows that 59.4% are males and 
40.6% are females (Table 12). The percentage distributions of 
males and females include adult males and females and male and 
female children. This percentage gender distribution is consistent 
with what pertains in the country (GSS, 1995). The young farming 
population may have positive implications on productivity because 
it is believed that the younger the farming population, the more 
productive labour is and consequently higher outputs are obtained 
(Hill and Ray, 1987).
Table 12: Age and Gender Distribution of Farm Households
Age Male Female Total & of Total
0 - 9 46 24 70 24 .3
20 - 39 78 71 149 51.7
40 - 59 42 21 63 21.8
60+ 5 1 6 2.0
Total 171 (59.4%) 117 (40.6%) 288 100
Source: Analysed field Data.
73
In summary, some farm activities are labour and gender 
specific. Family labour was used in undertaking all farm 
operations but hired labour was employed for specific farm 
operations. The farm population is young because rrost of the farm 
hands fall within the economically active age group of 19-40 years.
4.2.3 Structure of Capital
The structure of capital inputs is examined in terms of the 
types and amounts of capital inputs employed. The amounts of the 
capital inputs is discussed under section 4.3 on proportions of the 
individual resources.
4.2.3.1 Types of Capital Inputs
Capital inputs that the farmers used during the last crop year 
were fertilizer, seeds both local and improved, weedicide, hoes, 
cutlasses, baskets, sacks and spraying machine. Cutlass is widely 
used in land clearing, land preparation and weeding, the number of 
cutlasses used by the farmers reflected in rrost cases the number of 
the farm family members who actually worked on the farms. Hoes are 
used but to a limited extent because the fields do not have many 
stumps. Spraying machines were used for spraying weedicides. One 
farmer owns a spraying machine while the others who sprayed 
weedicide either borrowed or hired the machine. Apart from the 
spraying machine which was borrowed or hired, all other inputs were 
owned by individual farmers. With regard to seeds, the improved
A
varieties used were Obatanpa (15%), Dobidi (3%), the improved
74
varieties used were Obatanpa (15%), Dobidi (3%), AbWPAftPljyX’12%) and 
Oleomas a (5%). The remaining 65% of the farmers used the local 
variety. It should be noted that in most of the cases where 
improved varieties were planted, they were mixed with the local 
variety in the proportion of 2:1. Table 15 shows the distribution 
of farmers' reasons for not planting the improved variety of maize.
Table 13: Distribution of Farmers' Reasons for not Planting
the Improved Variety of Maize
Reason Frequency % of Farmers
1. Not readily available and costly 55 55
2 . Their use involves regular maintenance 
which will require extra labour IS 18
3. Less storable/resistant to infestation 40 40
4. Less tasty 20 20
5. For optimum yield, complementary inputs 
such as fertilizer and weedicide must 
be used 10 10
6 . Reliability of the local variety has 
been tested 10 10
Source: Field Data.
75
The main reasons why the farmers do not use the improved 
varieties of maize are (i) cost and availability and (ii) because 
of poor storability and lower resistant nature of the improved 
varieties to infestation (Table 13). The implication is that high 
resistant and storable varieties must be developed and must also be 
affordable and readily available to the farmers.
It is also seen from the Table 14 that, use of improved inputs 
differ among farmer groups. The use of agrochemicals such as 
weedicide and fertilizer was limited. Out of the 100 farmers 
interviewed, 22% used weedicide, 7% used fertilizer and 35% used 
improved seeds. In absolute terms, it can be said that among the 
improved inputs, improved seed usage is mostly catching on with the 
farmers. The figures in parenthesis are the ratios of the number 
of farmers in a given group of farmers who used an input to the 
total number of farmers in that farmer group. Comparing the ratios 
among the groups of farmers by tenancy, it is observed that 
fixed/leasehold farmers have the highest proportion (0.5) of! 
farmers using weedicide, followed by owner farmers (0.27) and then 
sharecroppers (0.10). with fertilizer use, the proportions of th^ 
groups are 0.07 for owner farmers, 0.02 for sharecroppers and 0.2] 
for fixed/leasehold farmers. The ratios for improved seed use ars
0.71 for fixed/leasehold, 0.41 for owner farmers and 0.19 fo. 
sharecroppers. The ratios show that, in all three cases of inpu 
use, fixed/leasehold farmers rank first followed by owner-farmer 
and lastly, sharecroppers. The ratios seem to imply the 
sharecroppers tend not to employ improved inputs. But it should I
76
noted that due to the small number of farmers who used these 
improved inputs in each farmer group, a statistical test of 
significance between the ratios was not possible. Therefore it 
cannot be reliably concluded that sharecroppers tend not to employ 
improved inputs.
Table 14: Distribution of Weedicide, Fertilizer and improved 
Seeds used Among Farmers in the Study District
Farmer Group Weedicide Fertilizer Improved Seed
Owner-Opera tor 10 (.25) 3 (.07) 16 (.41)
Sharecropper 5 (.10) 1 (.02) 9 (.19)
Fixed-rent-Leaseholder 7 (.5) 3 (.21) 10 (.71)
Total 22 7 35
Source: Appendix C.
4.3 Structure of Resources in Terms of Proportions
The section on proportions of resources examines (i) the 
average total cost per hectare of each resource (ii) shares in the 
average cost per hectare to each input and (iii) the shares in 
average cost per hectare to inputs for different landholding groups
i.e. owner farmers, sharecroppers, leaseholders and fixed rent 
farmers.
The computed average total cost per hectare of the individual 
inputs shows that land, labour and cutlass constitute the major 
cost items (Table 15).
77
Table 15s Average Total Cost per hectare of Inputs Used in 
Maise Production in 0/hec.
Input Average Total Cost/Hec.
Land 65625
Labour 44596
Weedicide 8571
Fertilizer 8320
Cutlass 12048
Basket (raphia and cane) 4113
Seed (improved and local) 5730
Sack 2417
Hoe 1947
Source: Appendix D.
Table 16 presents the average cost shares per hectare of the 
inputs. It is seen from the Table 16 that labour and land 
contribute 37.4% and 37.5% of cost respectively. Cutlass ranks 
third in terms of cost contribution (12.2%). The rest of the 
inputs, fertilizer, weedicide, basket, seed, sacks and hoes 
together constitute 12.8% of average cost. This cost composition 
shows that land, labour and cutlass are most important inputs to 
the farmers. Fertilizer, weedicide and improved seeds have little 
contribution to farmers' production costs. It can be seen from 
Table 16 that the share of cost per hectare of variable inputs 
(i.e. labour, cutlass, fertilizer, weedicide, raphia basket and 
seeds) is 60.4% and that of the fixed inputs (i.e. land, cane
78
baskets, sacks and hoes) is 3 0.6%. The cost sharing between fixed 
and variables inputs costs show that little investment is made in 
fixed capital items.
Table 16s Average Percentage Share of Inputs in Cost 
of Production
Inputs % Share
Labour 37.4
Weedicide 5
Fertilizer 1.7
Cutlass 12.2
Basket Raphia type (1.8) and cane (0.6)
Seed Improved (1*3) an<3 local (0.7)
Sack 1.2
Hoe 0.3
Land 37.5
Source: Appendix D.
Table 17 shows the average percentage cost sharing of the 
various inputs used by the different groups of sampled farmers in 
the study area. It is generally observed from the Table 17 that 
all the farmer groups except sharecroppers, have the highest cost 
contribution from labour. The cost contribution of labour for 
owner and leasehold farmers constitute more than 60% of total cost 
of production. That of fixed rent farmers is 32.2% of their total 
cost. The percent share of cost of labour for sharecroppers is 
22 .6%.
79
Table 17. Average Percentage cost Composition of Various
Inputs per Hectare Among Farmer Groups
Inputs Owner Farmer Sharecropper Fixed Rent Leasehold
Land - 60.4 21.6 14.3
Labour 63.3 22.6 32.2 68.2
Weedicide 9.95 2.3 8.6 1.5
Fertilizer 2 . 3 0.07 13.7 -
Cutlass 15.0 11.0 12 .8 9.4
Seed 29 .0 1.0 5.9 3.4
Raphiabasket 2 . 5 1.3 2.6 4.5
Cane basket 1.6 0.3 1.4 0.3
Sack 2.0 0.7 1.3 1.6
Hoe 0.4 0.2 0.4 -
Total 10 0 99.9 99.8 100.2
Source: Appendix D.
The average cost of land per hectare among the different 
farmer groups differ and is highest for sharecroppers. This is 
because the cost of land to sharecroppers is calculated as the 
value of produce received by the landlord. Owner farmers incur no 
cost on land ownership since in the study area, owners do not pay 
any land charges. The estimated percent cost shares of land per 
hectare per annum for fixed rent and leasehold farmers are 21.6% 
and 14.3% respectively. Land constitute the second highest cost 
contributor in their individual groups.
Cutlass is an important implement used by the farmers . It was 
the next highest cost component after labour and land. With owner 
farmers, cutlass constituted the second highest cost component
80
after land and labour but with the other farmer groups, it is the 
third highest cost component after land and labour. Comparing the 
percentage share costs of cutlass among the farmer groups, it is 
observed that there are no significant differences though the cost 
contribution is highest for owner farmers, followed by fixed rent 
farmers, then sharecroppers and lastly leaseholders (Table 17).
The agrochemicals used by the farmers are fertilizer and 
weedicide. It is seen from Table 16 that the cost contribution of 
weedicide constituted less than a-tenth of the total cost of 
production in all farmer groups even though variations exist. With 
regard to fertilizer, the cost contribution for owners is 2.3%, 
sharecropping (0.07%) and fixed rent farmers (13.7%). Leaseholders 
did not use any fertilizer. Comparing the cost contributions of 
the individual inputs of fixed rent farmers, it is observed that 
the cost contribution of fertilizer was the third highest after the 
cost of labour and land whereas with owner farmers and 
sharecroppers, the cost composition of fertilizer were among the 
lowest cost contributions of the inputs.
The cost contributions of seeds in all farmer groups are less 
than 6%. The cost share for owner farmers is 2.9%, that of 
sharecroppers is 1%, fixed rent farmers, 5.9%, and leaseholds, 
3.4%. of these cost contributions, two-thirds constitutes cost of 
improved seeds and the remaining one-third from local varieties. 
These cost contributions of seeds show that the amounts of improved 
seeds used by the farmers are very small within all farmer groups 
with the least amount used by sharecroppers (Table 17).
81
The other inputs used are basket (raphia and cane types), 
sacks and hoes. Their cost contributions are small compared to the 
other inputs. Aggregating the cost shares of these remaining 
inputs for the farmer groups, one obtains 6.5% for owner farmers, 
2.5% for sharecroppers, 5.7% for fixed rent farmers and 6.4% for 
leaseholders. With the exception of sharecroppers, there are not 
much differences in the cost shares among the other farmer groups. 
Looking at the individual cost contributions of hoe for the farmer 
groups, it is seen that the shares are almost negligible. This 
shows that the use of hoes to farm in the study area is low.
In summary, the structure of capital inputs employed on the 
farms studied shows that there is little investment in fixed 
capital inputs. Employment of output enhancing technological 
inputs such as fertilizers, planting materials and weedicide was 
low. With the increasing population and the dwindling land to man 
ratio in Ghana, it is these improved inputs which could bring about 
increases in yield Atsu et al. (1983).
4.4 RESOURCE USE EFFICIENCY
4.4.1 Gross Margins Results
The comparison of the efficiency in resource use is restricted 
to sharecroppers and owner-operators although the sampled farmers 
included leaseholders and fixed renters. This is because, (i) in 
the literature, the controversy over the efficiency of tenancy 
systems focuses on sharecropping systems rather than leasehold and
82
fixed rent systems and (ii) sharecroppers and owner-operators 
formed the majority of farmers studied in this work.
The average Gross Margins per hectare and the average Gross 
Margins per unit of labour between the two groups of farmers were 
computed. The Gross Margins per unit of the other inputs such as 
fertilizer and weedicide were not included because of the small 
number of farmers who used these agro-chemicals in each of the two 
groups. Table 18 shows that, the average Gross Margins per unit of 
labour for sharecroppers was lower than that for owner-operators,
i.e. 0937 and 0968 respectively. The Gross Margins per hectare was 
also found to be higher for owner farmers than for sharecroppers 
(Table 19). But statistical tests of significance (using the t- 
test) of the difference between the means of the Gross Margins per 
hectare and Gross Margins per unit of labour between the two farmer 
groups show no significant differences in the two cases. For the 
Gross Margins per unit of labour for the two farmer groups, the 
calculated t-value is 0.57 and the table values at 5% and 10% 
levels of significance are respectively 2.042 and 1.69 7. The 
implication is that the difference between the means of the Gross 
margins per unit of labour between the two farmer groups at both 
alpha-levels is insignificant. Regarding the test of significance 
between the means of the Gross Margins per hectare of the two 
farmer groups, the calculated t-value is 1.04. This t-value is 
less than the table values of 2.042 and 1.697 at the respective 
alpha levels of 5% and 10%. This second case also shows no 
significant difference between their means. These results
83
therefore mean that, in absolute terms, owner farmers used land and 
labour more efficiently than sharecroppers but the differences in 
land and labour use efficiencies are not significant between the 
two farmer groups. This finding corroborates the view held by the 
proponents of the equal efficiency that there is no difference in 
resource use efficiency between sharecroppers and owner farmers. 
The calculated coefficients of variations indicate that there is 
little deviations of the Gross Margins from the mean which implies 
that the results can be relied upon.
Table 18* Average Gross Margins per Labour Input for 
Farmer Groups
Farmer Group Average Total 
Value of 
produce per 
Unit of labour 
input in <b/MD
Average Total 
Variable 
Cost per Unit 
of labour 
input in 0/MD
Average Gross 
Margins Unit 
of labour 
input in 0/MD
coefficient 
of variation 
Average Gross 
Margins
Owner Farmer 1348 380 968 0.70
Sharecropper 1268 331 937 0.72
Source: Appendix D .
84
Table 19: Average Gross Margins per Hectare for Farmer Groups
Farmer Group Average Total 
Value of 
produce per 
hectare in 
0/hec.
Average Total 
Variable 
Cost per 
hectare 
0/hec.
Average Gross 
Margins 
per/hec. in 
®/ha
coefficient 
of variation 
Average Gross 
Margins
Owner Farmer 207055 54558 152497 0 .92
Sharecropper 260536 66481 194055 0 .87
Source: Appendix E.
4.4.2 Allocative Efficiency
The results of the estimated Cobb-Douglas production function 
using the ordinary least squares method are presented in Table 20. 
The table shows the production elasticities, sample means, factor 
prices and allocative efficiency indices of land, labour and 
capital for sharecroppers, owner farmers and the pooled sample 
respectively. For each of the farmer groups, the allocative 
efficiency index of the variable, value of capital was not 
computed. This is because, the value of capital was an aggregate 
of the values of weedicide, insecticide, seed, hoe, cutlass and 
basket. As a result, the single factor price to use for capital to 
compare with its marginal vale product to determine efficiency 
becomes difficult. These inputs were aggregated due to inadequate 
data on them. Regarding fertilizer and weedicide, the number of 
farmers who used these inputs during the growing period was small 
even for the pooled sample. Therefore disaggregating these inputs 
into separate variables would not help for the analysis. In the
85
case of seed, since about five varieties of maize were used by the 
sampled farmers with different retail prices, the price per kilo of 
seed to use to compare with its marginal value product again 
becomes difficult to determine.
From table 20, the production elasticities of land, labour and 
value of capital for sharecroppers are 0.61, 0.48 and -0.04
respectively. The elasticities of land and labour are both 
positive and significantly different from zero at 5% level of 
significance while that of the value of capital is negative and 
insignificant. The negative coefficient might be due to the small 
number of sharecroppers who used fertilizer, weedicide and improved 
seeds (Table 14). Therefore the dominant factors which influence 
maize output are land and labour though land had a higher output 
effect than labour for sharecroppers. The R-squared is 55.7 which 
then implies that 55.7% of the total variation in the output of 
maize was mainly explained by land and labour. The computed F- 
ratio of 54.68 compared to the table value of 8.9 at 5% confidence 
level means that the F-ratio is significant implying that land, 
labour and value of capital jointly affect the output of maize.
The allocative efficiency indices for land and labour for 
sharecroppers are respectively 1.72 and 0.15 (Table 20). These 
indices indicate that both land and labour are inefficiently used 
in maize production by sharecroppers in the study area. The 
allocative efficency index for land means that land is 
underutilized i.e. less of it is used and 0.2 6 for labour means 
that labour is overutilized implying that more labour than required
86
to attain efficiency is used.
For owner farmers, the production elasticities are 0.33, 0.50 
and 0.37 for land, labour and value of capital respectively. These 
elasticities imply that land, labour and value of capital inputs 
positively affect maize output but only labour and value of capital 
inputs significantly affect maize output at 5% level of 
significance while the effect of land, though positive, is 
insignificant at 0.05 alpha level but significant at 10% level of 
significance. The R-squared is 76.2 which means that about 76% of 
the total variation in the output of maize is accounted for by 
changes in land, labour and value of capital. The F-ratio in this 
case is also significant implying that land, labour and value of 
capital jointly affect the output of maize.
The allocative efficiency indices of land and labour for owner 
farmers are 2.98 and 0.27 respectively. These indices mean that 
both inputs are inefficiently used by owners on the maize farms 
studied. From the indices, land is underutilized while labour is 
overutilized by owner farmers.
Regarding the pooled sample, the production elasticities are
0.48, 0.53 and 0.18 for land, labour and value of capital inputs 
respectively (Table 20). All the elasticities are positive and 
significantly different from zero. The R-squared is 66.9% meaning 
almost 67% of the total variation in the output is accounted for by 
the changes in land, labour and value of capital. The test also 
shows that land, labour and value of capital jointly influence 
output of maize (Table 20).
87
The allocative efficiency indices for land and labour for the 
pooled sample are respectively 5.8 and 0.24 implying that both 
inputs are inefficiently used. The indices show that land is 
underutilized while labour is overutilized.
Looking at the allocative efficiency indices of land and 
labour for sharecroppers, owner farmers and the pooled sample, it 
is observed that all the three groups underutilized land and 
overtulized labour. The indices show that the pooled farmers 
underutilized land rrost, followed by owner farmers and then 
sharecroppers. This means that sharecroppers use land most 
efficiently among the three farmer groups. The most efficient use 
of land by sharecroppers is due to the fact that, land rent 
constituted the highest cost item (60%), among other inputs to 
sharecroppers, (Table 17). Therefore if they do not use land 
efficiently to obtain higher yields, they cannot meet the rent 
charges and the cost of other production inputs. Regarding labour, 
the indices show that owner farmers least overutilized labour, 
followed by sharecroppers and then pooled sample. This also means 
that owner farmers use labour most efficiently. This can be 
attributed to the fact that, labour input constituted the highest 
cost item among other inputs used by owner farmers, Table 17, which 
implies that more labour was hired by owner farmers.
The estimated scale elasticities (returns to scale) are 1.139 
for sharecroppers, 1.109 for owner farmers and 1.183 for the pooled 
sample (Table 20). The deviations of the returns to scale from 
unity is non-significant for all the three samples implying that
88
all the three sample farms are characterised by constant returns to 
scale. The chow test shows that there is no significant difference 
between the production elasticities of owners and sharecroppers 
which implies that their production functions are the same.
The regression equation is as follows:
In Qi = In A +a1InX1 + a2InX2 + a3InX3t . . . Ut 
where Q - output of maize 
A = a constant
S.! a 2 and Q2 are the production elasticities of land, labour and 
capital.
X17 X2 and X3 are the indpendent varies of land, labour and capital 
respectively.
89
Table 20* Production elasticities, marginal value products, 
factor prices and allocative efficiency indices
for sharecroppers, owner farmers and the pooled sample
Item sharecroppers
n=50
owner farmers 
n=35
pooled sample 
n=85
Production elasticities
land 
Labour 
V. Cap
Returns to scale 
Const.
0.612 
0.483 
-0.044* 
1.139 
4.452
0.331 
0.505 
0.373 
1.209 
0.418
0.487 
0.529 
0.177 
1.193 
2 .158
Sample means
land (ha) 
labour (MD) 
v. cap. (0)
0.544
107.3
11004
0.757 
142 .2 
18623
0.632
121.7
14141.9
Marginal value products
land (S/ha) 
labour (0/MD) 
v.cap (0)
127947
512
Factor
90119
731
prices
116983
666
land (0/ha) 
labour (0/MD) 
v.cap (£)
74258
2678
30214
2678
19864
2678
Allocative efficiency indices
land
labour
1.72 
0.15
2.98
0.27
5.98
0.24
R2 55.7 78.3 65.7
Adj. R2 52 .8 76.2 66.9
F-ratio 54.7 37.2 54.7
Note: The F-ratios for sharecroppers, owners and the pooled
sample are all significant at 5% confidence level*.
All the production elasticities are significant at 5% 
confidence level except value of capital which is 
insignificant(*). ** means the coefficient is
insignificant at 5% but significant at 10% confidence 
level.
90
CHAPTER FIVE
5.0 SUMMARX, CONCLUSION AND RECOMMENDATIONS
5.1 SUMMARX
The study looked at the structure of farm resources; land, 
labour and capital in maize production in the Asamankese District 
of the Eastern region of Ghana from two different perspectives: 
their composition and their proportions in production. Land tenure 
system and its importance to maize production in the study area 
were examined. Finally, a comparative assessment of the efficiency 
in resource use by sharecroppers and owner farmers was made.
Under the structure (i.e. composition) of resource use, it is 
observed that farm sizes were small, mixed cropping was widely 
practiced and rudimentary tools such as cutlass and hoes were used. 
Baskets and sacks were also used. The type of labour widely used 
for farm work is family labour though hired labour was found to be 
important in maize production. The age structure of the farm 
households shows that most of the farm hands are young people. A 
small number of farmers used agro-chemicals such as fertilizer, 
weedicide and improved seeds but in limited quantities.
Looking at the proportions of the resources, it was observed 
that labour and cutlass were the main inputs used by the sampled 
farmers. The other inputs, fertilizer, weedicide, seeds, basket, 
hoe and sack do not constitute major cost items. A comparison of 
the proportions of the various inputs used in farming among the
91
different farmer groups showed that, sharecroppers tended to employ 
less amounts of inputs.
With regard to the land tenure system in the area, factors 
such as mode of land acquisition, length of tenancy and forms of 
tenancies were discussed. The length of tenancy was found to 
average 3 years. Four types of land tenure arrangements exist in 
the area. They are share tenancy, owner operation, fixed rent and 
leasehold systems. Fixed rent and leasehold tenancies were found 
to be uncommon but owner and sharecropping systems are the main 
types of landholding arrangements. As far as the study area is 
concerned, the information gathered on the land tenure system 
indicates that land acquisition by tenant farmers does not involve 
any rigid demands from landlords . The problem identified with the 
use of land by tenant farmers is the short duration of tenancy 
period. Few tenant farmers are allowed to use the land for as many 
years as they deemed necessary but are not certain as to when they 
would be asked to leave the land. Most of the tenant farmers, 
about (90%) are allowed a maximum of three years to farm the land 
after which they have to abandon them to fallow.
Concerning the efficiency in the use of resources, the finding 
from the gross margins method is that, in absolute terms owner 
farmers tend to use both land and labour rrore efficiently than 
sharecroppers but statistically there are no significant 
differences in labour and land use efficiencies between the two 
farmer groups. The allocative efficiency indices of land and 
labour for sharecroppers and owner farmer show that both farmer
92
groups use land and labour inefficiently although from the nominal 
values of the indices, one farmer group tends to use land or labour 
more efficiently than the other. The result of the chow test 
showed that there is no significant differences between the 
coefficients of land, labour and capital of the two farmer groups 
which is consistent with the results of the gross margins.
5.2 CONCLUSIONS
The structure of land, labour and capital from the findings 
typifies small-scale agricultural production. In other words, the 
traditional way of farming has not changed in the area. This may 
have adverse implications on output since with traditional 
technology of farming, subsistence levels of production will 
continue to exist.
Regarding the cost structure of the various inputs for the 
farmer groups, sharecroppers used least amounts of the various 
inputs except land. This finding cannot be conclusive because it 
was impossible for the author to carry out a test of significance 
to substantiate whether there was actually any difference in the 
amounts of inputs employed among the farmer groups.
The short fallow period may discourage prospective tenant 
farmers because after deserting a land to fallow, one may find it 
difficult to acquire another since land may not be readily 
available and even if available, may sometimes not be at an 
accessible location. It is therefore important to take a critical 
look at the length of tenancy.
93
Concerning the efficiency in the use of land and labour 
between sharecroppers and owner farmers, no definite conclusion can 
be made based on the Gross margins as to which farmer group used 
land or labour more efficiently. This is because there were no 
significant differences in land and labour use efficiency between 
the two farmer groups.
Based on the allocative efficiency measure, the efficient use 
of land by the two farmer groups can be achieved by increasing the 
total land area under cultivation. Labour use efficiency can also 
be achieved by reducing the quantity of labour employed on the 
maize farms. These findings indicate that sharecropping systems 
are not generally less efficient than owner operation systems.
5.3 Recommendat ions
Based on the findings of the study, the following 
recommendations are made.
The present structure of land, labour and capital documented 
in this study with regard to maize production could serve as a 
reference point for comparison in future research if one wants to 
examine the effects of changing economic environment, increasing 
population and changing agricultural technology on the structure of 
resources.
The short duration of tenancy period could be increased to at 
least 15 years. This can be achieved by involving private 
landowners, farmers, government, chiefs, family heads and the local 
assembly to deliberate on the appropriate length of tenancy. The
94
major landowning group should be identified and a specified amount 
of money be paid to them from the District Assembly common Fund to 
serve as an incentive in addition to whatever they may receive from 
prospective tenant farmers. This in a way could make landowners 
rent their lands to prospective tenant farmers over this longer 
period of time suggested.
With the efficiency in the use of resource by sharecroppers 
and owner farmers, it is recommended that further studies be 
carried out to assess the comparative efficiency in the use of the 
resources, this time to include fertilizer and weedicide between 
the two farmer groups in a different district to augment the 
present study. It should be carried out in a different area 
because land tenure systems differ from one area of the country to 
another. In addition, since this work did not report adequately on 
fixed rent and leasehold systems, any study on tenancy systems 
could incorporate them. To improve upon whole farm efficiency or 
sharecropping and owner efficiencies, adequate credit must be 
provided to enable farmers employ the required levels of inputs. 
In employing the required amounts of inputs to achieve efficiency, 
farmers should receive intensive extension service.
5.4 Policy Directions
It is a policy of the region to improve agricultural 
productivity through efficient resource use; to increase income of 
farmers; improve diets of the people and raise the living standard 
of all engaged in agriculture. Among the measures outlined to
95
achieve these objectives are (i) to ensure continued new 
technological output and flow by strengthening research/extension 
linkage and (ii) to improve and strengthen the visiting 
capabilities of all field staff. The priority policy measure of 
the region is apparently Extension delivery. For maize production 
to increase in the area, then the use of improved inputs such as 
fertilizers, new planting materials, weedicide and new techniques 
of farming must be encouraged. Therefore, a regional policy should 
focus on research into why these improved inputs are underemployed. 
In addition, there should be land use policy which will guarantee 
prospective tenant farmers longer use of land for farming.
96
LIST OF REFERENCES
1. Acquaye, D.K. (1969): Some Aspects of Soil Productivity in
relation to Agricultural Development. Background to 
Agricultural Development Policy in Ghana. Proceedings
of a Seminar Organised Faculty of Agriculture, 
University of Ghana. Legon.
2. Adu, S.V., and Asiamah, R.D. (1992): Soils of the
Ayensu/Densu Basin of Ghana. Soil Research 
Institute, Memoir N°.9.
3. Adegeye, A.J.,, and Dittoh, J.S. (1985): Essentials of
Agricultural Economics. Impact Nigerian Ltd., 
Ibadan, p.56.
4. Anthonio, Q.B.O., and Upton, M. (1965): Farming as a
business. 2“d edition, Oxford University Press, 
Ely House, London. Pp 5-39.
5. Arhin, K. (1985): The Expansion of Coca Production: the
working conditions of migrant cocoa farmers in the 
Central and Western regions. Legon: Institute of 
African Studies, University of Ghana.
6. Atsu, S.Y., Ewusi, K., and Gy.ekye, L.O. (1983): Land
Utilization and Labour Productivity in Agriculture 
in Ghana. Technical Publication, number 4 6,
ISSER, University of Ghana, P.31.
7. Barnard, C.S., and Nix, J.S. (1979): Farm Planning and
Control. Cambridge University Press, Cambridge, 
England.
8. Bauer, P.T., and Yamey, B.S. (1957): The Economics of
Underdeveloped Countries. London. Nisbet.
9. Bentsi-entsil, K. (1964): Ghana Land Law: An Exposition
Analysis and Critique. London: Sweet and
Maxwell.
10. Bhaumik, S.K. (1991): Tenancy and resource allocation - a
review with fresh data. Indian Journal of
Agricultural Economics, vol. 46: p.4.
11. Bishop, C.E. and Toussaint, W.D. (1958): Agricultural
Economic Analysis.John Wiley &Sons, Inc.Pp,153 155.
97
12. Buckett, M. (1981): An introduction to farm organization
and Management♦ Pergamon Press, oxford, New York. 
Pp. 119-127.
13.
14.
15.
16.
Byerlee, D.M.P. (1980): Planning Technologies Appropriate
to Farmers' Concepts and Procedure, Mexico CMMYT.
Cyert, R.M., and March, J.G. (1963): A behavioural Theory
of the Firm. Prentice Hall, Inc., Englewood
cliffs, NJ, USA.
Dadson, J.A. (1969): Land Tenure Reform. Background to
Agricultural Policy in Ghana. Proceedings of a
seminar organised by the Faculty, University of 
Ghana, Legon.
DAES (1990): Mid Year Review. Department of Agricultural
Extension Services, Eastern Region of Ghana (DAES). 
January - June, 1990.
17. Dillon, J.L. (1979): "Bernoullian decision theory: Outline
and problems". In J.A-Roumasset, J.M. Boussard and 
I. Singh (eds.). risk Uncertainty and Agricultural 
Development. Southeast Asian Regional Centre for 
Graduate Research Agriculture, Laguna, Philippines.
18. Dittoh, S. (1991): Efficiency of agricultural production in
small-scale and medium-scale irrigation in Nigeria. 
Issues in African Rural Development. vol. 1.
Winrock International Institute for Agricultural
19,
2 0 .
2 1 .
22 .
Development Winrock. P.159.
Drucker, P.F. (1968): The Practice of Management.
Books Ltd., London, England.
Pan
Ellis, F. (1992): Peasant Economics. Farm households and
agrarian development. Cambridge. Pp.16 - 24.
FAO, (1985): Land tenure, Agrarian systems and Rural
development in Ghana. Seminar Report of Food and 
Agricultural Organization.
Farrington, J. (1975): Farm Surveys in Malawi. Development
Study 16. Department of Agricultural Economics and 
Management, University of Reading, England.
23. Feder, G. , and Ochan, T. (1987): Land Ownership Security
and Farm Investment in Thailand. Journal of 
Agricultural Economics and Farm Management. Vol. 
69, No. 2, pp. 311-320.
98
25. GSS (1995): Analysis of Demographic Data in Ghana.
Preliminary Analysis .Reports. vol. I. Ghana 
Statistical Service, p.126.
26. Gyasi, A.E. (1994): The adaptability of African communal
land tenure to economic opportunity. "The example 
of land acquisition for oil palm farming in 
Ghana"- Africa, 64 (3), P. 31.
27. Harvey, D.R. (1986): The response of agriculture's
structure to current technical and economic 
possibilities. Occasional-Paper, Department of 
Geography, University of Leicester.
28. Heady, E.O. (1952) : Economics of Agricultural Production
and Resource Use. Prentice-Hall Inc., Englewood 
Cliffs, NJ. P.52.
29. Heady, E.O., and Jensen, R. (1954): Farm Management
Economics. Prentice Hall, USA. P.400.
30. Hill, B., and Ray, D. (1962): 'Ghanaian Capitalist Cocoa
Farmers. Ghana bulletin of Agricultural Economic, 
2 ( 1 ) , 2 6 - 3 0 .
31. Hill, B., and Ray, D. (1987): Economics for agricultural
Food farming and the Rural Economy. Macmillan 
Education Ltd. P. 223.
32. Hopper, D.W. (1965): Allocative Efficiency in a Traditional
India Agriculture. Journal of Farm Management 
Economics. vol. 47, N°3. Pp. 611-617.
33. IITA (1992): Sustainable Food Production in Sub-Saharan
Africa. International Institute of Tropical 
Agriculture, Ibadan.
34. Ip., C.P., and Stahl, C.W. (1978): Systems of Land Tenure,
Allocative Efficiency and Economic Development. 
America Journal of Agricultural Economics. vol. 
60, No.1.
35. ISSER (1991): The State of the Ghanaian Economy in 1991.
Institute of Statistical, Social and Economic 
Research, University of Ghana, Legon. Pg. 83.
99
36. Johnson, Lily De-Graft (1962): 'The development of Land
Tenure Systems in Ghana and attempts at reforms in 
the past'. Ghana Bulletin of Agricultural
Economics, 2(1), 16-20.
37. Johnson, M. (1964): 'Migrant Progress'. Bulletin of the
Geographical Association 9(2), 4-27-
38. Karan, K.P., Ngugi, D.N., and Nguyo, W. (1992): East Africa
Agriculture. Revised edition, Macmillan.
39. King, D.J. (1973): 'Land Reform and Participation of the
Rural Poor in the Development Process of African 
Countries'. Madison, Wis : Land Tenure Center,
University of Wisconsin, mimeo. Draft, prepared 
for the international Bank for Reconstruction and 
development.
40. Kumbhakar, S.C. (1994): Efficiency estimation in profit
maximizing model using flexible production 
function. Agricultural - Economics, (Netherlands), 
vol. 10(2). Pp. 143 - 152.
41. Kwadzo, G.T-M. (1995): Socioeconomic Study of Small Scale
Farm Household in the Vertisols of the Accra 
Plains. A report prepared for IBSRAM & ODA.
42. La-Anyane, S. (1962): 'Agriculture in the general economy',
in J.s. wills (ed.), Agriculture and Land use in 
Ghana, Accra and New York: Oxford University
Press. Pp. 192 - 200.
43.   (1985): Economics of Agricultural Development in
tropical Africa. John Wiley and Sons, New York. 
P. 71.
44. Lai, R. (1983): Erosion causes productivity decline in
Soils of the humid tropic. Soil Taxonomy News. 
No.5, Pp. 4 - 11.
45. Lau, L.J., and P.A. Yotopoulos (1972): “Profit, Supply, and
Factor Demand Functions". American Journal of
Agricultural Economics. Vol. 54. Pp. 11 - 18.
46. Lewis, w .A . (1955): The theory of Economic Growth.
Homewood, Irwin.
47. Lipton, M. (1968): “The theory of Optimising Peasant".
Journal of Development Studies. Vol. 4, No.3, Pp. 
327 - 351.
100
48. Majerova, V. (1991): Manpower during the transformation
period on farms. Sociologie-Venkova-a-Zemedelstvi, 
vol. 27, issue 2. Pp 103 - 108.
49. Makehalm, J.P., and Malcolm, L.R. (1986): The Economics of
Tropical Farm Management. Cambridge University 
Press, Cambridge, London. Pp. 25 - 31.
50. Mbata, J.N., and Matekwa, J.C. (19 83): Resource use
efficiency among small-scale farmers in selected 
areas of Western Kenya. Trpenlandwirt, (Germany). 
Vol. 94 (2). Pp. 119 - 134.
51. Mansfield, E. (1994): Microeconomics. Eighth edition.
W.W. Norton and company, New York. London. P. 198 
- 203.
52. Mellor, J.W. (1966): The Economics of Agricultural
Development. Cornell University Press, Ithaca, New 
York. P. 335.
53. Mensah, P. (1982): Per Acre Production Costs & Income of
major Food Crops in Ghana. Ministry of
Agriculture, Economic Research and Planning 
Service, Accra.
54. Migot-Adholla, S.E., Benneh, G., Atsu, S., and Place, F-
(1990): Land Tenure Issues and Agriculture,
Economic Research and Planning Service, Accra.
55. Momin, M.A. (1991): Impact of Agrarian Structure on
agricultural growth of Bangladesh. Journal of
Rural Development, Hyderabad, Vol. 10, No.3, Pp.
253-263. BIDS.
56. Ministry of Agriculture (1990): Ghana Medium Term
Agricultural Development Programme. An Agenda for 
Sustained Growth & Development (1991-2000). 
Prepared by Ministry of Agric., Republic of Ghana, 
February, 9.
57- National Agricultural Research Programme (1993): 'Cereals'.
A report by the commodity committee of the National 
Agricultural Research Project. Final revised 
version, vol. 1. July 1993.
58. Ninsin, K.A. (1989): The Land question since the 1950's in
E. Hansen and K.A. Ninsin (eds.), The State: 
development and politics in Ghana. Pp. 165 - 183.
101
59. Norman, D.w. (1972): An Economic Study of Three villages in
Zaria Province, Zaria, Nigeria, ABU.
60. Ofori, l.M. (1973): Factors of Agricultural Growth in West
Africa. Proceedings of an International Conference 
held bv Institute of Statistical, Social and 
Economic Research (ISSER), University of Ghana, 
Legon.
61. olomola, A. (1991): Capture Fisheries and Aquaculture in
Nigeria: A Comparative Economic Analysis. Issues 
in African Rural Development. Vol. I. winrock 
Institute for Agricultural Development. Pp 343 - 
359.
62. Onyenwaku, C.E. (1991): Economics of Irrigation in Crop
Production in Nigeria. Issues in African
Development. vol. II. Department of Agricultural 
Economics and Extension, Federal University of 
Technology, Nigeria. Pp. 132 - 133.
63. Organization for Economic co-operation and Development
(1975): Review of Agricultural Policies. General 
Survey. Organization for Economic Co-operation and 
Development Agricultural Policy Reports. OECD, 
Paris.
64. Policy Planning, Monitoring and Evaluation Department
(1993): Annual Sample Survey of Agriculture.
Ministry of Food and Agriculture, Policy Planning, 
Monitoring and Evaluation Division of Agricultural 
Statistics and Census Division, Ghana.
65. Phiri, C.D. (1991): An Economic Evaluation of Small Holder
Farming systems in Chinguluwe Settlement Scheme, 
Malawi. Issues in African Rural Development, Vol.
1. Winrock International Institute for
Agricultural Development. Pp. 92 - 93.
66. Reynolds, L.G. (1977): Agriculture in Development Theory.
A Publication of the Economic Growth Center, Yale 
University. New Haven and London. Yale University 
Press, p.110.
67. Sankhayan, P.L. (19 83): Resource productivity and
allocation efficiency in a traditional agriculture 
- a study in Zambia. Journal - of - Research 
(India). Vol. 20(2). Pp. 174 - 180.  ~
102
68. Sidhu, Surjit S. (1974): Economics of Technical Change in
Wheat Production in the Indian Punjab. American 
Journal of Agricultural Economics. vol. 56. Pp. 
217 - 2 6 .
69. Sidhu, Surjit S. and Carlos, A. Baanante (1979): "Farm-
level Fertilizer Demand for Mexican Wheat varieties 
in the Indian Punjab". American Journal of 
Agricultural Economics, vol. 61. Pp. 455 - 62.
70 Spencer, D.S.C. (1976): "Micro-level Farm Management and
Production Economics. Research Among Traditional 
African Farmers: Lessons from sierra Leone".
African Rural Employment, Paper No.3.
71. Synodgrass, M.M. and Wallace, L.T. (1975): Agriculture,
Economics, and Resource Management. Prentice-Hall, 
Inc. Englewood Cloffs, New Jersey.
72. Upton, M. (1987): African Farm Management. Cambridge
University Press, Cambridge, P.56.
73. Vernon, W.R. (1971): "Tenure and Productivity of phillipine
Rice Producing Farms". Phillipine Economic
Journal, Vol. 79. Pp. 587 - 595.
74. Yotopoulos, P.A., L.J. Lau and W.L. Lin (1976): “Micro­
economic Output Supply and Factor Demand Functions 
in the Agriculture of the Province of Taiwan". 
American Journal of Agric. Economics. Vol. 58. 
Pp. 333 - 40.
103
A SAMPLE QUESTIONNAIRE ON THE STRUCTURE AND EFFICIENT RESOURCE 
USE IN MAIZE PRODUCTION AT THE WEST AKIM DISTRICT, EASTERN REGION
A. GENERAL
Questionnaire serial number: ...............................
Date of interview: ..........................................
Interviewers code: ..........................................
Location code: ..............................................
B . SOCIO-ECONOMIC CHARA.CTE RI ST ICS
1. Name of respondent: .............................
2. Age: .............................................
3. Sex: .............................................
4. Marital status: 1. single 2. Married
3. Divorced 4. Separated 5. Widowed.
5. Ethnicity: 1. Ewe 2. Akan 3. Krobo/Ada
4. Ada 5. Others (Specify): ......... .
6. Distance between house and farm: ................... .
7. Place of birth: ......................................
8. Household Members Characteristics
Name Sex
M=1
F=2
Age Relationship 
to head
Occupation Education Years in- 
farming
Education Code : 1. Primary 2. Middle 3. JSS
4. '0' level 6. 'A' level 7. Vocational/Technical
8. Post-Secondary 9. University 10. None.
Relationship Code: 0. Self 1. Wife/husband 2. Sons/daughter
3. Niece/nephew 4. Sister/brother
5. Sister/brother-in-las 6. Mother/Father-in-laws
7. Grandchild 8. No relation
9. Others (Specify ) .................
104
LAND USE
9a. What was the size of land holding last year in hectares?
SECTION B
b. Could you please tell why you cultivated land area of this 
size? ......................................................
10. What proportion of this land holding was cultivated to maize 
last year in hectares?
Minor season ..........................................
Major season ..........................................
11. What was the number of location(s) of your land holdings?
12. What variety or varieties of maize did you cultivate?
1. Oleomas a 2. Obatanpa 3. Dobide 4. Abrotia
5. Local 6. Others (specify) .
13. Why do you prefer to plant the local or the improved variety
of maize? ..................................................
14. What is the nature of the soils in this area?.
1. Sandy 2. coarse textured 3. clayey
4. loamy 5. other (specify) .
b. Are they favourable to maize cultivation? 1. Yes 2. No.
15. What method of land preparation do you normally apply?
1. slash and burn 2. slash and burn 3. mechanised
4. other (specify) .........................................
b. Could you explain why you use this method above? ..........
16. Do you practice bush following? 1 Yes 2. No.
(a) If Yes or No, why? ...................................
(b) If Yes, how long is a piece of land left to fallow in 
years? .................................................
FARMING PRACTICES
17. What type of farming do you undertake?
1. Mixed cropping 2. Mono cropping.
18. If mixed farming, what main crop(s) are mixed with maize? 
1. cocoyam 2. yam 3. cassava 4. plantain
5. other (specify) .....................................
105
19. Which of these farming practice is prevalent in this area?
1• OR 2. in Q 17.
20. Give reasons why you practice either mixed farming or
monocropping .................................................
21. What method of planting do you normally adopt and why?
1. row planting 2. traditional planting
Why? ..........................................................
LAND TENURE
22. From whom did you acquire your land for farming?
1. Chief 2. family head 3. own land
4. government 5. other (specify) ...... .
23. What was the type of your holding?
1. tenant 2. owner operator
4. other (specify) ..............
3. tenant and owner
24, If tenant farmers, what type?
1. fixed rent (amount per acre per annum
Abunu (sharecropping) ................
Abusa (sharecropping) ................
provision of labour (mandays per week) 
Other (specify) ......................
25. Indicate the Quantity or Cash Value
Land Rent Option Unit Qty. of Output Value of Output
Fixed Rent 
Abunu 
! Abusa 
owners 
Other (specify)
26. If abunu, how was cost shared? ...................
27. What do you find wrong with the following systems? 
(a ) Abunu ..........................................
(b) Abusa ..........................................
(c) Fixed rent ....................................
(d) Leasehold .....................................
106
28. What is the mode of land acquisition in this area?
1. provide drink?
2. drink and cash?
3. goat?
4. Others (specify) ................................
29. After your first approach to acquire land for farming, how
long did it take before finally acquiring it?
1. 0-1 month 2. 1-3 months 3. 4-6 months
4. 7-12 months 5. greater than one year
6. Others (specify) ................................
30. As a tenant farmer, does the land owner influence your
production decision? (1) yes (2) No.
If Yes, why? ..........................................
31. Who decides what to grow? Tenant or landlord?
32. As a tenant farmer, are you restricted in the types of crops 
to grow by the landlord? 1 Yes 2. No.
If Yes, what types of crops are you allowed to grow and why?
33. How long as a tenant farmer can you farm this type of land in 
years? .............................................
34. Is the length of period allowed you enough? Yes or No?
If Yes or No, why? ...................................
35. If the response in Q34 is No, then what length of time will 
you consider adequate in years? .....................
36. What was the going land rent per 0.4 Ha last crop season in 
cedis? ................................................
37. As an owner farmer, do you pay any levy to the local council 
or authority? (1) Yes (2) No.
If Yes from Q37, how much did you pay last year in cedis?
107
Labour Use
38. What was the composition of your farm labour supply for last 
year in mandays?
Type of Labour
SECTION C
Family Labour J F M A M J J A S O N D
Own
Wife/ husband 
Children over 15yrs 
Relations (adult)
Hired Labour 
Male 
Female 
Child
Others 
Communal 
,Exchange Labour 
Others (specify)
39. Amount of cash/kind spent each month on hired labour
Hired Labour J F M A M J J A S 0 TJ D
Male
Female
Child
Others 
Communal 
Exchange Labour 
Others (specify)
39 b. What was the cost of labour per day per hectare?
Minor season Major season
108
39 c .
Hired Labour Cash Value of cooked food Value of raw food
Male
Female
Child
Exchange
Communal
Others ( )
40. Provide labour demand and period for the following farming 
activities
Labour demand/Activity/Month in Mandays
Activity J F M A M J J A S 0 H D AV LD AV LS
I. land clearing 
2 . land Prep.,
3. Planting
4. 1st Weeding
5. 2nd Weeding
6. Spraying
7. Fert. appl.
8. 3rd Weeding
9. Bagging
10. Carting
II. Manure appl.
AV LD = Average labour demand; AV LS = Average labour supply.
41. For which activity were you short of labour and why? 
ACTIVITY REASON
109
42. Machine Hours Used on Maize Last Year
a c t i v i t y
Machinery ? E R r o d
Cost/hour
J F M A M j j A S o II D
Land clearing 
Land
preparation 
Planting 
Spraying 
Fert. appln. 
Harvesting
43. Specific Tasks Undertaking by type of Labour and Crop budget
A c t i v i t y
1
Qty 
in units
2
Method
l=Manual
2=mechanical
Cost
in
cedis
Person responsible
Male Female Child
1. land clearing
2. land preparation
3. Planting
4. Fertilizer 
i - NPK
- Ammonia
5. Fert appln.
6. Manure
7. Weedicide
- Weedicide appln.
- Weeding
8. Pesticide spraying
9. Harvesting
10. bagging
11. Carting
12. Processing
13. Storage
110
SECTION D
CAPITAL / CONSUMABLE INPUTS
44 .
I t e m Qty
Unit Price 
in cedis
useful life 1. rented
2. shared 
3 . owned
Hoe 
Cutlass 
Tractors 
Power tiller 
Spade 
Basket 
Sacks 
Spraying machine 
Seed 
Fertilizer 
Insecticide 
Other (specify) ..
SECTION E
Output and Marketing Information 
45. Output
Season Crop
variety
Output
(Kg)
Home
Consumpt
Qty
Sold
Time 
of sale
Price/
Unit
Sale
Minor
Major
46._____________________________ Marketing
Season Qty
Sold
Location Time/month Price Revenue Cost of Sale
Goods Owners
Minor
Major
111
APPENDIX B
HO FA BD CO NN FM CM OT FS PR ST FN
2 3 * * * * * 1
3 3 * * * 2
3 4 * it ★ 3
3 3 * it * 4
2 3 * * * 5
2 3 * * ie 6
10 3 * ★ * * 7
5 . * * it it 8
1 . * it CHIEF 9
6 ■ * * CHIEF 10
5 3 * it it it 11
4 3 * OWN ie 12
3 2 * * 13
3 2 ★ * •k 14
4 3 * ie ie 15
6 3 it it it 16
3 3 * * it 17
2 3 * ' . * * it 18
4 3 * it it it 19
2 2 * if if ie 20
3 3 * is * 21
3 6 ie * * 22
3 . ie OWN 23
1 3 it * 24
4 3 * ie OWN 25
2 3 ie * ir 26
2 2 it OWN 27
5 3 * Hr ie 28
1 3 OWN OWN 29
4 2 * * 30
3 4 * it * 31
4 . * it it 32
5 4 OWN OWN 3 3
4 4 * * ie 34
4 3 * it it it 35
5 4 * ie if it 36
4 2 * ie OWN 37
HO FA BD CO NN FM CM OT FS PR ST FN
6 8 it * * 38
2 . * * 39
4 7 * * * * 40
7 2 * * * 41
3 2 * CHIEF 42
3 3 * * 43
2 4 * * * 44
1 3 * * 45
4 4 ■k * if OWN 46
5 4 * 47
2 2 * * * 48
2 3 * •k CHIEF 49
3 3 * ■k * 50
4 5 * * * 51
4 3 * *  ^- * 52
4 6 * * •* * 53
3 3 * OWN * * 54
3 7 * * ’ f. ? *• 55
3 7 * * OWN 56
5 3 * + * 57
2 3 * •k * * 58
3 2 it * 59
1 2 •k * 60
1 . * 61
4 5 ■k k CHIEF 62
3 3 if * * * 63
3 2 •k ★ 64
2 2 * it * 65
3 3 it * it * 66
6 . * * * 67
4 . 68
4 2 69
3 3 70
5 3 71
2 2 72
2 3 73
3 2 74
HO FA BD CO NN FM CM OT F S PR ST PH
* * * * 68
* * * 69
* * * 70
* * ★ 71
* * * ★ 7 2
* * * 7 3
* ★ * * 74
6 6 * * * 75
4 ★ ★ * * 76
3 5 * * * 77
3 3 * * * 78
2 3 * it 79
2 4 * ★ ★ * 80
4 4 * * * * 81
4 3 * , 8 2
3 2 * * * * 8 3
3 . * * 84
4 2 * * * 85
4 4 ★ 86
3 3 * * 87
3 3 * * 88
5 5 * * * 89
4 2 * ★ * * 90
2 2 * * 91
6 3 ★ # * 9 2
3 4 * * * 9 3
4 4 * * ★ * 94
4 3 * * * * 95
2 5 * * * * 9 6
5 4 t * * it 97
5 4 * * •k * 98
3 3 it * * 99
4 3 it * 1 0 0
Note: HO = household size
FA = fallow period
BD = type of labour (by day)
CO = type of labour (by contract)
NN = typo of labour (exchange labour)
FL = type of labour (family labour)
CM = type of labour (communal labour)
OT = type of labour (others)
FS - type of labour family source of labour
PR = type of labour private source of labour
SL = type of labour stool land
FL = type of labour farmer serial number
APPENDIX C
QN ou LS LZ FT WD VI V2 V3 V4 D1 D2 AG D3 D4 D5 QT
1 750 78 . 6 3.0 1 0 0 0 0 1 22 0 0 0 8.0
2 700 75 .4 0 1 0 0 1 0 22 0 0 1 4.0
3 225 99 . 6 0 1 0 0 1 0 36 0 0 0 4 . 0
4 400 210 1.0 0 1 0 0 1 0 50 1 0 0 4.0
5 270 108 .4 0 1 0 0 1 0 46 1 0 0 6.0
6 200 56 .3 0 0 0 0 1 0 45 0 1 0 1.0
7 2000 340 .8 1 0 0 0 0 1 48 1 0 0 6.0
8 2100 342 1.2 3.0 0 1 0 0 0 1 32 0 0 0 27
9 850 96 .6 0 1 0 0 1 0 35 0 1 0 4.0
10 330 153 .4 100 0 1 0 0 1 0 42 0 0 0 4.0
11 800 121 1 . 2 50.0 0 1 0 0 1 0 32 0 0 1 10
12 150 49 .4 0 1 0 0 1 0 50 0 0 1 3.0
13 150 60 .4 0 1 0 0 1 0 22 0 0 1 4.0
14 132 83 .2 0 0 1 0 0 1 21 1 0 0 2.0
15 350 44 . 4 0 1 0 0 1 0 38 1 0 0 3.0
16 1000 123 . 6 0 0 1 0 0 1 35 1 0 0 4.0
17 300 49 .6 0 0 1 0 0 1 22 0 0 1 4.0
1 18 1350 322 .6 1 0 0 0 0 1 24 0 0 1 4.0
19 400 93 . 8 0 1 0 0 1 0 35 0 0 1 4.0
20 198 148 .6 0 1 0 0 1 0 32 0 0 1 5.0
21 300 114 1.0 0 1 0 0 1 0 51 1 0 0 2.0
22 1214 318 .4 1.0 0 1 0 0 1 0 23 0 1 0 14
23 100 38 ,4 0 1 0 0 1 0 42 1 0 0 2.0
24 225 39 . 2 0 1 0 0 1 0 43 0 0 1 4 . 0
25 250 56 .4 0 1 0 0 1 0 73 1 0 0 3.0
26 816 299 .4 0 1 0 1 23 1 0 0 5.0
27 520 280 .8 0 1 0 0 1 0 65 , 0 0 1 3.0
28 350 139 .8 0 1 0 0 1 0 26 1 0 0 6.0
29 250 37 .4 1 0 0 1 20 0 0 1 2.0
30 650 131 1.6 0 1 0 1 44 1 0 0 10
31 500 110 .8 0 1 0 0 1 0 50 0 1 0 5.0
32 200 66 1.2 0 1 0 0 1 0 40 1 0 0 4.0
33 750 296 1.2 2.0 0 1 0 1 50 0 1 0 8.0
34 330 64 .7 0 1 0 0 1 0 42 0 0 0 6 .0
35 160 44 . 4 1 . 0 0 1 0 0 1 0 48 0 1 0 6 . 0
36 412 122 1.0 • 0 1 0 0 1 0 42 1 0 0 4.0
37 450 79 .8 0 1 0 0 1 0 43 0 0 1 13
QN OU LS LZ FT WD VI V2 V3 V4 D1 D2 AG D3 D4 D5 QT
38 340 34 . 6 0 1 0 0 1 0 31 0 0 1 3 . 0
39 840 214 1 . 8 0 0 0 1 0 I 45 1 0 0 220
40 1310 321 1.2 0 1 0 0 1 0 49 1 0 0 6.0
41 154 46 .4 0 1 0 0 1 0 45 0 0 1 3.0
42 150 51 . 3 0 1 0 0 1 0 28 0 0 1 2.0
43 640 289 .6 0 1 0 0 1 0 28 0 1 0 10
44 550 141 1.0 0 1 0 1 48 0 0 0 15
45 400 268 .6 0 1 0 0 1 0 39 0 0 1 5
46 150 84 .4 0 1 0 0 1 0 71 1 0 0 2.5
47 750 269 .8 0 1 0 1 31 0 1 0 7.0
48 250 112 .3 0 1 0 0 1 0 40 0 0 1 10
49 160 70 .3 0 1 0 0 1 0 80 0 0 1 6.0
50 160 89 .4 0 1 0 0 1 0 41 0 0 1 2.0
51 100 95 .6 0 1 0 0 1 0 70 0 0 1 8.0
52 140 58 .4 0 1 0 0 1 0 71 0 0 0 4.0
53 500 177 1 .2 0 1 0 0 1 0 44 0 0 1 10
54 140 199 .4 0 1 0 0 1 0 62 1 0 0 2.0
55 300 75 . 3 0 1 0 0 1 0 55 0 0 1 10
56 180 71 .2 0 1 0 0 1 0 26 0 0 1 5
57 166 34 .2 0 1 0 0 1 0 20 1 0 0 2.0
58 97 20 .3 0 1 0 0 1 0 20 1 0 0 2.0
59 500 278 .6 1 0 0 0 0 1 60 1 0 0 8.0
60 4200 373 2.0 1 0 0 0 0 1 57 1 0 0 36
61 512 74 . 3 1 0 0 0 0 1 39 0 0 0 4.0
62 350 74 .3 1 0 0 0 0 1 41 1 0 0 2.0
63 310 41 .8 1 0 0 0 0 1 39 1 0 0 1 . 6
64 172 60 .2 1 0 0 1 45 1 0 0 1.5
65 600 286 .4 1 0 0 0 0 1 45 0 0 0 10
66 648 290 1 .0 25 25 1 0 0 0 0 1 45 0 0 0 13
67 1700 330 .8 1 0 0 0 0 1 41 1 0 0 1 6
68 600 61 .7 1 0 0 0 0 1 40 0 0 0 7.0
69 350 62 . 4 1 0 0 0 0 1 38 1 0 0 7.2
70 600 26 . 4 1 0 0 0 0 1 31 0 0 0 5
' 71 525 74 1 . 2 75 75 1 0 0 0 0 1 35 0 0 0 6.0
72 874 300 1 .2 0 0 0 0 0 1 31 0 0 0 18
73 1386 324 1.2 0 1 0 0 1 0 46 0 1 0 15
74 3404 250 2.4 150 150 0 0 0 1 0 1 49 1 0 0 36
QN OU LS LZ FT WD VI V2 V3 V4 D1 D2 AG D3 D4 D5 QT J
75 225 41 . 4 2.0 0 1 0 0 1 0 34 1 0 0 4 . ° I
76 674 69 . 6 0 1 0 0 1 0 48 1 0 0 8.0 1
77 100 33 .3 5.0 0 1 0 0 1 0 30 0 1 0 ! .6 [j
78 200 59 .4 0 1 0 0 1 0 50 1 0 0 4.°
79 300 43 . 3 0 1 0 0 1 0 36 0 1 0 2.0 1
80 116 47 . 3 0 1 0 0 1 0 61 0 0 1 2.0
81 250 58 .3 0 1 0 0 1 0 52 0 0 1 2.0 1
82 160 71 .3 0 0 0 1 0 1 29 1 0 0 4.0 1
83 600 180 .4 0 0 0 1 0 1 54 1 0 0 6.0 [I
84 160 41 .3 0 1 0 0 1 0 20 0 1 0 2.°
85 300 37 .6 0 1 0 0 1 0 31 0 0 1 5.0 |
86 830 243 1.6 0 1 0 0 1 0 54 1 0 0 13 1
87 1020 309 2.0 0 1 0 0 1 0 50 0 0 0 20 I
88 492 58 .6 0 1 0 0 1 0 43 0 0 1 6.0
89 126 73 .4 0 1 0 0 1 0 35 0 1 0 4.0 |
90 340 58 .8 0 1 0 0 1 0 35 0 0 1 10 1
91 300 38 . 4 1 . 5 1 0 1 0 0 1 39 0 0 1 4.0 j
92 540 103 . 4 0 0 0 0 0 1 40 0 1 0 6.6 |
93 120 36 ,4 1 0 0 0 0 1 36 0 1 0 3.0 1
94 500 74 .6 i - ' 0^ 1 0 0 1 0 48 0 0 1 5.0
95 550 87 .6 J o" i 0 0 1 0 43 0 0 1 6.° I;
96 800 101 .8 1 0 0 0 0 1 52 1 0 0 10 1
97 600 115 .6 0 1 0 0 1 0 48 0 1 0 6.0 j
98 1
99
100 350 74 .3 . • 1 0 0 0 0 1 41 1 0 0 2.0 |
Note: QN 
OU 
LS 
LZ 
FT 
WD 
VI 
V2 
V3 
V4 
D1 
D2 
D3 
D4 
D5 
AG 
QT
farmer serial number
output of maize in kilos per hectare
labour supply in mandays
land area cultivated to maize in hectare
fertilizer quantity used in kilos
quantity of weedicide in kilos
dummy variable for maize variety Abeleehi
dummy variable for maize local variety
dummy variable for maize variety (Obaatampa)
dummy variable for maize variety (Okomasa)
dumrry variable for local variety
dummy variable for local improved variety
dummy variable for local owner farmer
dummy variable for local Abunu farmer
dummy variable for local Abusa farmer
age of f arrrer
quantity of seeds in kilos.
appendix d 
ESTIMATED COSTS O f INPUTS PER HECTARE

QN
81
8 2
8 3
84
85
86
87
8 8
89
90
91
9 2
9 3
94
95
96
97
98
99
10'
. 4
. 3
6 8 0 0 0 1 6 5 0 0 5 2 5 0
1 4 6 6 7 4 6 6 7
37333 3 6 6 6 7 4 6 6 7
22000 4 6 6 7
1 4 6 6 7 5 3 3 3
1 6 5 0 0 8 7 5 0
. 6 1 4 6 6 7 1 7 5 0
1,6 0 7 5 0 6 0 7 5 3 7 5 0 0 5 0
2.0 20000 4 4 0 0 1 7 5 0
6 1 8 3 3 6 6 7
2 6 2 5
1 6 5 0 0 4 3 7 5
1 0 5 5 6 3 11000 4 3 7 5 1 2 5 0 0
7 0 0 0 0 5 5 0 0
4 6 8 5 0 11000 3 5 0 0 5 0 0 0
4 6 4 1 7 1 4 6 6 7 4 6 6 7 1 8 7 5
1 3 7 5 0 1 7 5 0
7 9 1 6 7
Note: QN
LA
CL
WD
FT
CT
BT
SD
SK
CB
HO
LD
farmer serial number 
land area in hectare 
cost of labour per hectare 
" " weedicide per hectare
" fertilizer "
■ " cutlass 1
" basket 
" " seed 1
1 1 sack "
1 1 basket (cane)
1 1 hoe "
1 1 and
APPENDIX E
CALCULATION OF GROSS MARGINS FOR OWNER AND 
SHARECROPPING FARMERS
THE VARIABLES ARE LISTED IN THE FOLLOWING ORDER:
OUTFUT VALTQUTF TVARCOST GKOSSMAK TOTLABSU TOTLAHAR GROSSMPL GROSSMPUL ATVPHEC ATVCHEC ATVPL ATVCL
1400 397600 88704 308896 210 1.0 1471 308896 397600.0 88704.0 1893.33 422.40
270 76680 37700 38964 108 .4 361 97450 191700.0 94250.0 710.00 349.07
2000 568000 85900 482100 340 .8 1418 602625 710000.0 107375.0 1670.59 252.65
132 37488 23750 13738 83 .2 170 68690 187440.0 118750.0 451.66 286.14
350 99400 13400 86000 44 .4 1955 215000 248500.0 33500.0 2259.09 304.55
1000 284000 46200 237800 12 3 .6 1933 396428 473333 .3 77000.0 2308.94 375.61
300 85200 5450 79750 114 1.0 670 79750 85200.0 5450.0 747.37 47.81
100 28400 2900 25500 38 .4 671 63750 71000.0 7250.0 747.37 76.32
250 71000 19400 51600 56 .4 921 129000 177500.0 48500.0 1276.86 346.43
816 231744 12700 219044 299 .4 736 547610 579360.0 31750.0 775.06 42.47
350 99400 8000 91400 139 .8 658 114392 12 4250.0 10000.0 715.11 57.55
650 184600 97100 87500 131 1.6 668 54616 115375.0 60687.5 1409.16 741.22
200 56800 8000 48800 66 1.2 739 40761 17333.33 6666.67 860.61 121.21
412 117008 14000 103008 122 1.0 844 103008 117008.0 14000.0 959.08 114.75
840 238560 186800 51760 214 1.8 242 28851 132533.3. 103777.8 1114.77 872.90
1310 372040 37700 334340 321 1.2 1042 278997 310033.3 31416.67 1159.00 117.45
640 181760 27760 154000 289 .6 533 256762 302933.3 46266.67 628.93 96.06
150 42600 8800 33800 84 .4 402 84500 106500.0 22000.0 507.14 104.76
140 39760 34900 4860 199 .4 24 12150 99400.0 87250.0 199.80 175.38
166 47144 5100 42044 34 .2 1237 210220 235720.0 25500.0 1386.59 150.00
ijS IUTFUT 1 VALTOUTP TVARCOST GROSSMAR TOTLABSU TOTLANAR GROSSKFL GROSSMFUL ATVFHEC ATVCHEC ATVFL : ATVCL
97 27548 3000 24548 20 .3 1227 81732 91626.67 10000.0 1377.40 150.00
500 142000 81700 60300 278 .6 217 100406 23666.7 136166.7 510.79 293.88
f 4200 1192800 119400 1072400 373 2.0 2878 536700 596400.0 59700.0 3197.86 320.11
512 145408 52100 93308 74 .3 1261 311027 484693.3 173666.7 1964.97 704.05
350 99400 34380 65020 ' 47 . 3 879 358828 331333.3 114600.0 1343.24 464.59
-}: 310 88040 54940 33100 41 .8 807 41517 110050.0 68675.0 2147.32 1340.0
| 172 48848 13308 35540 60 .2 592 177700 244240.0 66540.0 814.13 221.80
1700 482800 112300 370500 330 .8 1123 463125 603500.0 140375.0 1463.03 340.30
I 350 99400 48200 51200 62 .4 826 128000 248500.0 120500.0 1603.23 777.42
| 3404. 966736 229036 737700 250 2.4 2951 307280 402806.7 95431.67 3866.94 916.14
I 225 63900 35400 23500 41 .4 695 71392 159750.0 88500.0 1558.54 863.41
674 191416 38466 152950 69 .6 2217 254822 319026.7. 64110.0 2774.14 557.48
200 56800 35900 20900 59 .4 354 52250 142000.0 89750.0 962.71 <■-08.47
160 45440 6000 39440 71 .3 555 131372 151466.7 20000.0 640.00 8-:..
1 600 170400 10100 160300 180 .4 890 400750 426000.0 25250.0 946.67 56.11
630 235720 31500 204220 243 1.6 840 127708 147325.0 19687.50 970.04 129.63
540 153360 54290 99070 103 .4 962 247675 383400.0 135725.0 1488.93 527.09
120 34080 34500 -420 36 .4 -12 -1050 85200.0 86250.0 946.67 958.33
800 l------ 227200 46200 181000 101 • .8 1792 226250 284000.0 57750.0 2249.50 457.43
Note: OUTPUT : Total output of maize obtained by a fanaer
VALTOUTF : Value of total output
TVARCQST : Total variable cost of production
GROSSMAR : Gross margins
T0TLA3SU : Total labour supply
TOTLABAR : Total land area cultivated to maize
GROSSMFL : Gross margins per unit of labour
ATVFHEC : Average total value product per hectare
ATVFHEC : Average total variable cost per hectare
ATVPL : Average total value product per unit labour
APPENDIX r 
LABOUR SUPPLY BS TYPE IN MAHDAXS
HL FL TL TLHEC HLH'EC FLHEC PQ FM
32 46 78 1 3 0 5 3 77 2 5 0 M
44 31 75 1 8 8 78 1 1 0 3 0 0 M
14 85 99 1 6 5 2 3 1 4 2 3 0 0 H
11 2 98 2 1 0 210 1 1 2 98 2 0 0 M
24 84 1 0 8 2 7 0 60 2 1 0 2 0 0 M
14 42 56 1 87 47 140 2 5 0 M
35 3 0 5 3 4 0 4 2 5 44 3 8 1 3 0 0 N
1 42 2 0 0 3 4 2 2 8 5 1 1 8 1 6 7 3 0 0 M
30 66 96 1 6 0 5 0 1 1 0 300 M
12 1 4 1 1 5 3 3 8 3 5 0 3 5 3 5 0 0 M
66 55 1 2 1 1 0 1 5 5 46 3 0 0 N
21 2 8 49 1 2 3 5 3 70 3 5 0 M
60 6 0 1 5 0 1 5 0 3 0 0 M
6 77 6 3 4 1 5 30 3 8 5 3 5 0 M
4 40 44 1 1 0 1 0 1 0 0 3 5 0 M
38 9 5 1 2 3 2 0 5 47 158 3 0 0 H
. 49 49 82 . 82 5 0 0 M
182 14 0 3 2 2 5 3 6 3 0 3 233 35 0 H
38 55 9 3 1 1 6 47 69 3 0 0 M
93 55 1 4 8 2 4 7 155 92 3 0 0 M
7 1 0 7 1 1 4 114 7 1 0 7 2 5 0 M
25 2 9 3 3 1 8 7 9 5 6 2 7 3 3 3 0 0 N
. 38 38 95 . 95 2 0 0 M
. 39 39 1 9 5 . 195 3 5 0 H
14 42 56 1 4 0 35 1 0 5 5 0 0 M
10 30 40 1 0 0 2 5 75 4 0 0 M
58 2 4 1 2 9 9 7 4 6 1 4 5 6 0 3 3 0 0 H
1 4 2 1 3 8 2 8 0 3 5 0 1 7 7 1 7 3 3 0 0 M
. 1 3 9 1 3 9 174 . 1 7 4 2 5 0 M
2 35 37 9 3 5 88 2 5 0 M
99 32 1 3 1 82 62 20 5 0 0 N
| 64 46 1 1 0 1 3 8 80 58 3 5 0 M
, 66 66 55 5 5 2 5 0 H
1 9 3 203 2 9 6 2 4 7 78 16 9 3 0 0 M
P lZ 26 64 91 37 54 3 0 0 MI e _ 36 44 11 0 20 90 35 0 M
HL FL TL TLHEC HLHEC FLHEC PQ FM
8 114 122 1 2 2 0 114 3 5 0 M
54 79 1 3 3 1 6 6 67 99 3 00 M
6 28 34 5 7 47 10 40 0 M
192 22 2 1 4 1 1 0 1 0 7 11 2 5 0 M
110 2 0 3 3 2 1 2 6 8 99 16 9 450 M
46 46 1 1 5 115 3 5 0 M
51 5 1 1 7 0 1 7 0 3 0 0 M
1 1 2 1 7 7 2 8 9 4 8 2 1 8 7 2 9 5 2 5 0 M
84 5 7 1 4 1 1 4 1 84 5 7 5 0 0 M
1 3 2 1 3 6 2 6 8 447 2 2 0 22 7 3 5 0 M
64 84 2 1 0 . 2 1 0 2 5 0 M
2 0 0 69 269 336 2 5 0 86 3 5 0 H
6 3 49 1 1 2 3 7 3 2 1 0 1 6 3 3 5 0 M
12 58 70 2 3 3 40 1 9 3 3 0 0 M
49 40 89 2 2 3 1 2 3 1 0 0 3 0 0 M
50 45 95 1 5 8 8 3 7 5 300 M
28 68 96 1 6 0 2 7 1 3 3 3 5 0 M
5 2 6 5 8 1 4 5 1 3 0 15 3 50 H
1 1 1 66 1 7 7 1 4 8 9 3 5 5 3 0 0 M
49 1 5 0 1 9 9 4 9 8 1 2 3 3 7 5 3 0 0 M
20 55 75 2 5 0 67 1 8 3 2 5 0 M
40 31 7 1 3 5 5 2 0 0 1 5 5 2 0 0 M
. 34 34 1 7 0 . 1 7 0 2 5 0 M
. 2 0 20 67 . 67 3 0 0 M
1 2 7 7 2 7 8 4 6 3 1 4 6 2 400 N
92 2 8 1 3 7 3 1 8 7 46 1 4 1 3 0 0 M
36 38 74 2 4 7 1 2 0 1 2 7 3 5 0 N
34 40 74 2 4 7 1 1 4 1 3 3 4 0 0 N
26 1 5 41 5 1 3 3 18 5 0 0 M
11 49 60 3 0 0 5 5 2 4 5 3 0 0 M
1 00 1 8 6 2 8 6 7 1 5 2 5 0 465 5 0 0 M
17 0 1 2 0 2 9 0 2 9 0 1 7 0 1 2 0 5 0 0 N
300 30 3 3 0 4 1 3 3 7 5 38 2 5 0 N
12 49 61 87 17 70 2 5 0 M
24 38 62 1 5 5 60 95 3 0 0 N
17 9 26 65 4 3 2 2 3 0 0 M
44 30 74 62 3 7 25 4 0 0 M
200 1 00 3 0 0 2 5 0 1 6 7 8 3 3 0 0 M
HL FL TL TLHEC HLHEC FLHEC PQ FM
170 1 9 6 32  4 2 7 0 1 0 7 1 6 3 3 0 0 M
170 00 2 5 0 1 0 4 72 32 300 M
24 17* 41 1 0 3 . 60 4 3 2 5 0 N
3 3 36 69 1 1 5 5 5 60 2 5 0 M
. 3 3 3 3 1 1 0 « 1 1 0 3 0 0 M
15 14 29 4a 25 2 3 300 N
34 25 29 1 4 8 85 6 3 5 0 0 M
4 3 4 3 1 4 3 1 4 3 5 0 0 N
20 27 47 1 5 7 67 9 0 3 0 0 M
. 5 8 5 0 19-3 . 1 9 3 30 0 H
8 6 3 71 2 3 6 26 2 1 0 3 5 0 M
. 180 1 0 0 4 5 0 . 14 5 3 5 0 N
41 41 1 3 6 . 1 3 6 3 5 0 M
37 37 62 62 300 M
100 1 4 3 2 4 3 1 5 2 6 3 89 5 0 0 M
1 4 9 1 6 0 3 0 9 155 75 00 300 M
4 64 68 1 1 3 7 1 0 6 3 0 0 M
2 5 40 7 3 1 0 3 6 3 120 4 0 0 M
10 40 5B 7 3 1 3 60 3 0 0 M
18 20 38 1 95 45 50 350 M
36 67 1 0 3 2 5 8 9 0 1 6 8 3 5 0 M
32 4 36 90 00 10 2 5 0 N
26 48 74 1 2 3 4 3 00 5 0 0 M
30 5 7 87 1 4 5 50 95 3 0 0 M
46 5 5 1 0 1 1 2 6 5 8 68 3 5 0 M
45 70 1 1 5 1 9 2 75 1 6 7 350 M
Note : HL = Hired labour supply in mandays
FL = Family labour supply in mandays
TLHEC = Total labour supply per hectare
HLHEC = Hired labour supply per hectare
FLHEC = Family labour supply per hectare
PQ  = Per kilo price of output received by
FM = Type of cropping pattern
FM
a farmsr