UNIVERSITY OF NIGERIA, NSUKKA DEPARTMENT OF AGRICULTURAL ECONOMICS

GENDER AND RESOURCE USE EFFICIENCY IN COCOYAM

PRODUCTION IN ANAMBRA STATE, NIGERIA.

AN M.Sc DISSERTATION SUBMITTED TO

THE DEPARTMENT OF AGRICULTURAL ECONOMICS

UNIVERSITY OF NIGERIA, NSUKKA

BY

OKOYE, FRANCISCA .UZOOYIBO.

PG/M.Sc/08/49854

SUPERVISOR: PROF. C. U. OKOYE

HEAD OF DEPARTMENT: PROF.E.C.OKORJI

FEBRUARY, 2014

TITLE PAGE

GENDER AND RESOURCE USE EFFICIENCY IN COCOYAM PRODUCTION IN

ANAMBRA STATE

BY

OKOYE, FRANCISCA.UZOOYIBO

REG NO: PG/M.Sc/08/49854

AN M.Sc DISSERTATION SUBMITTED TO THE DEPARTMENT OF

AGRICULTURAL ECONOMICS, FACULTY OF AGRICULTURE, UNIVERSITY OF

NIGERIA, NSUKKA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR

THE AWARD OF MASTERS DEGREE IN AGRICULTURAL ECONOMICS WITH

SPECIALIZATION IN RESOURCE AND ENVIRONMENTAL ECONOMICS

FEBRUARY, 2014.

APPROVAL PAGE

GENDER AND RESOURCE USE EFFICIENCY IN COCOYAM PRODUCTION

IN ANAMBRA STATE, NIGERIA

BY

OKOYE, FRANCISCA UZOOYIBO

REG NO:PG/M.Sc/08/49854

A DISSERTATION SUBMITTED TO THE DEPARTMENT OF AGRICULTURAL

ECONOMICS IN FULFILMENT OF THE REQUIRMENTS FOR THE AWARD OF

MASTERS (M.Sc) DEGREE IN AGRICULTURAL ECONOMICS.

APPROVED BY:

…………………….. ……………………

Prof.C.U, Okoye Date

(supervisor)

………………………… ....…………………

Prof.E.C, Okorji Date

(Head, Dept. of Agric. Economics).

CERTIFICATION

Okoye Francisca.U. a post graduate student of the Department of Agricultural Economics,

University of Nigeria, Nsukka with Registration Number PG/M.sc/08/49854 has satisfactorily

completed the requirement of a research work for the award of masters Degree in Agricultural

Economics. The work embodied in this project is original and has not been submitted in part or

whole for the award of any Degree in this/any university.

____________________ ___________________

Prof. C.U, Okoye Prof. E.C, Okorji

Project Supervisor Head of Department

Date______________ Date_______________

________________________

External Examiner

Date_________________

DEDICATION

This work is dedicated to Almighty God for his grace, guidance and protection.

ACKNOWLEDGEMENT

I indeed owe a lot of gratitude, thanks and praises to God Almighty who has out of his

special mercies and favour kept me to see these days. My profound and heartfelt gratitude goes to

my Supervisor Prof. C.U. Okoye who stood out as an indispensable contributor to this work,

morally and technically. I jealously cherish Professors S.A.N.D. Chidebelu; E.C. Okorji; E.C.

Nwagbo; C.J. Arene; N. J. Nweze and (Mrs.) A. I. Achike, Doctors F.U. Agbo, Ben Okpupara; N.

Chukwuone and other academic staff of the Department of Agricultural Economics, UNN who

have contributed to the success of this work in one way or the other. I sincerely appreciate you all.

On a very important note, I wish to register my genuine appreciation to my dear friends

Taofeeq Amusa, Inyada Ladi, Mgbebu Ezekiel, Chinelo, Emeka Okoye, Rev. Fr. Maurice

Abasilim, Dr. Emeka Okoye and Chukwuemeka Kadurumba who has been my source of joy and

happiness throughout the course of study. I appreciate your kind gesture.

To my sweet parents, Chief and Mrs. Okoye Lazarus, honestly you are wonderful and

bunch of gift to me. God Almighty will continue to keep you in good health. My siblings Okoye

Calistus, Okoye Elijah, Okoye Chijioke, Okoye Amala, Okoye Chisom, including Ekenechukwu

Okafor, Chinonso Okafor and Chigozie Okafor (Adazion) I sincerely thank you for your care,

love and good wishes. I appreciate your words of encouragement that cannot be neglected in

telling any success story about this work.

Okoye, Francisca. U.

February, 2014

TABLE OF CONTENTS

Title Page i

Approval Page ii

Certification iii

Dedication iv

Acknowledgement v

Table of Contents vi

List of Tables viii

Abstract ix

CHAPTER ONE – INTRODUCTION 1

1.1 Background Information 1

1.2 Problem Statement 3

1.3 Objectives of the Study 4

1.4 Hypotheses of the Study 4

1.5 Justification of the Study 5

CHAPTER TWO - LITERATURE REVIEW 6

2.1 Under Utilization of Cocoyam 6

2.2 Potentials of Cocoyam 7

2.2.1 Nutritive Values of Cocoyam. 7

2.2.2 Economic Values of Cocoyam 8

2.2.3 Agronomic Values of Cocoyam 9

2.3 Gender Issues in Agriculture 9

2.4 Gender and Farm Input Delivery System, Supply and Productivity 11

2.5 Cost and Returns 13

2.6 Resource Problems and Resource Allocation of Rural Economies 13

2.6.1 Resource Problems 13

2.6.2 Rural Resource Allocation 14

2.7 Evidence of Resource Productivity and Efficiency Studies 16

2.8 Theoretical Framework 17

2.9 Analytical Framework 21

CHAPTER THREE: METHODOLOGY 23

3.1 Study Area 23

3.2 Sampling procedure 23

3.3 Data Collection. 24

3.4 Data Analysis 25

3.5 Hypotheses Testing 28

CHAPTER FOUR: RESULTS AND DISCUSSION 29

4.1 Socio-Economic Characteristics of the Respondents 29

4.2 Comparison of Mean Output of male and female Cocoyam Farmers 33

4.3 Estimation of Technical and Allocation Efficiency in Cocoyam Production 33

4.4 Comparision of Technical and Return to Scale of the male and Female Farmers 40

4.5 Cost and Returns of Male and Female Cocoyam Farmers 41

4.6 Problems Encountered by Cocoyam Farmers Based on Gender 42

CHAPTER FIVE: SUMMARY, CONCLUSIONS & RECOMMENDATION 44

5.1 Summary 44

5.2 Conclusion 45

53 Recommendation 45

REFERENCE 47

Appendix I: Estimated output of major agric commodities (000 tons) 58

LIST OF TABLES

Table 3.1: Selection of Cocoyam Farmers in the Study Areas 24

Table 4.1: Distribution of Male and Female Cocoyam Farmers According to Socio-economic

Characteristics 31

Table 4.2: Two Sample t-test of Cocoyam Output by Gender 33

Table 4.3: Maximum Likelihood Estimates of the Cobb-Douglas Stochastic Production

function for male and female farmers in Anambra State. 35

Table 4.4: Results of Multiple Regression Analyssis of Female Cocoyam Farmers 38

Table 4.5: Results of Multple Regression Analysis of Female Cocoyam Farmers 38

Table 4.6: Estimation of Allocative Efficiency for Male Cocoyam Farmers 39

Table 4.7: Estimation of Allocative Efficiency for Female Cocoyam Farmers 40

Table 4.8: Elasticities of Production for Male and Female Cocoyam Farmers 41

Table 4.9: Costs and Returns of Male and Female Cocoyam Farmers 42

Table 4:10: Distribution of male and female respondents according to constraints in cocoyam

production 43

Abstract The study was designed to investigate the gender and resource use efficiency in cocoyam

production in Anambra State, Nigeria. Socio-economic characteristics of the farmers were

determined as well as the production problems affecting the farmers in the study Area. The study

presents the results of analysis of data collected on 160 male and female cocoyam farmers across

two Agricultural zones. A multi-stage randomized sampling technique was used to select the

zones, blocks, circles and contact farmers Descriptive statistical tools such as percentages,

frequencies and mean were used in analyzing farmer’s socio-economic characteristics and

production problems. The result showed that women constituted a greater percentage (68.75%) of

those involved in cocoyam production in the state, which comprises those within who the age

range of 41 to 50 years. The Maximum Likelihood Estimation (MLE) technique was used in

estimating the technical efficiency and determinants of efficiency of male and female farmers

with the Cobb-Douglas production function as the lead model. The result of estimation of

technical efficiency using the Cobb- Douglas stochastic function showed that the coefficients of

male and female farmers for the production variables used were all positive. Cocoyam setts,

labour and fertilizer use were significant while capital inputs were not significant for female

cocoyam farmers. The result indicates that socio-economic conditions influenced technical

efficiency of both categories of farmers. The coefficients of determinants of efficiency used were

all positive except farm size that was negative and significant for both male and female cocoyam

farmers while age, level of education, extension contact, knowledge index were all positive and

significant for male farmers while other variables were not significant. Test of allocative

efficiency revealed that none of defined farmer groups achieved absolute allocative efficiency.

Male farmers underutilized fertilizer and over utilized other inputs in production while female

farmers over utilized all the inputs. This result suggests that there exists the possibility of

increasing output under existing level of technology through the use of lower levels of all inputs

by male and female farmers except fertilizer for males. There is also scope to use higher levels of

fertilizer for the male farmers. The result shows the mean output/kg of 2,450.20kg and 2,519.09kg

with an average net profit of N62, 592.87 and N88, 378.12 and BCR of N1.85 and N2.16 for the

male and female farmers respectively. This implies that cocoyam production was profitable in the

study area. The results also showed the elasticities of productions of male to be 0.43246 and that

of female to be 1.1987, this shows a decreasing return to scale for male cocoyam farmers and

increasing return for female cocoyam farmers. Finally, the survey revealed that most of the

farmers (male and female) encountered problems of root rot diseases at 90% and 90.91%

respectively.

CHAPTER ONE

INTRODUCTION

1.1: Background information

In Nigeria of about 140 million people, men constitute about 50.4% and women

49.6%(N.P.C, 2006).Both gender are responsible for producing nation’s food and one of the

major problems confronting mankind in recent times is food crisis (Ndukwu et al 2010).Gender

has often been misunderstood as being about the promotion of women only, but it focuses on the

relationship between men and women, their roles, access to and control over resources, division

of labour and needs. Men and Women are affected differently in their operation in factors like

markets and socio- economic environments. Women are more constrained than their men

counterparts in terms of access to credits, agricultural inputs, and information technology and so

on. Some crop are men’s, like yam production, while others like sweet potatoes and cocoyam

production are regarded as women’s especially in the southeastern Nigeria (Ndukwu et al 2010).

Dimelu et al (2009) reported that women are involved in crop production generally and cocoyam

production in particular

Agriculture is the largest single sector in the Nigeria economy, providing food, income

and employment for sustainable livelihood of both the rural and urban population (CBN, 2003).

Agriculture is the largest non-oil export earner and the largest employer of labour accounting for

88% of the non-oil foreign exchange earnings and 70% of the active labour force of the

population. Food crops constitute the largest component of the crops sub-sector of the Nigeria’s

agriculture (CBN,2003). Root and tuber crops which are among the most important groups of the

staple foods in many tropical African countries(Osagie,1998) Constitutes the largest source of

calories for Nigeria population(Olaniyan et al 2001)

Cocoyam originated from Asia and about forty (40) species are mostly grown in West

Africa (Asumugha and Mbanasor, 2002).Cocoyam,both Xanthosoma species and Colocasia

species belong to the family (Aracea).The cocoyam specie colocasia esculata in sub-Sahara

Africa was introduced to this continent one thousand or more years ago from South East Asia

while cocoyam specie Xanthosoma Mafafa was introduced more recently from tropical America

(11TA, 1992; FAO, 2005a).

Nigeria is the largest producer of cocoyam in the world, accounting for about 37% of the

total world output (FAO, 2007b; NRCRI, 2009). From 0.73 million metric tones in 1990,

cocoyam production in Nigeria rose to 3.89million metric tones in 2000 (Ojiako et al; 2007;) and

further by 30.30% to 5.068 million metric tones in 2007 (FAO, 2007b). Further estimate in

Nigeria, showed a figure of 5,387 million metric tones out of 11.77 million metric tones of world

output of cocoyam per annum since 2008 (FAO STAT, 2010).

Cocoyam ranks third in importance after cassava and yam among the root and tubers crops

cultivated in Nigeria (see Appendix 1) (FAO, 2005a, National Breau of Statistics, 2006, Okoye et

al; 2008). Cocoyam both Xanthosoma sp and colocasia sp is an important staple food in the plant

family, cultivated in South Eastern and South Western part of Nigeria (Onyenweaku et al, 2005;

Ojiakor et al, 2007; Chukwu et al, 2009). It is a food security crop variously grown by resource

poor farmers especially women who often intercrop it with yam, maize, plantain, banana,

vegetable (Ikwelle et al, 2003).

Cocoyam is highly medicinal for diabetic patients because it has low starch content, is

easily digestible and contains protein more than the other root tubers. The leaves of colocosia

esculenta have been shown to be a rich source of folic acid, ribo flavin, vitamin A and C, calcium

and phosphate (Arene and Ene, 1987). The leaves are consumed because they are rich in protein

and vitamins while the root is rich in carbohydrates and minerals (Duru and Uma, 2002).

Cocoyam is a useful cover crop and the corms are ready to harvest in 8 – 12 months (Uguru,

1996). The corms and cormels are boiled, baked and tubers are sometimes ground to produce

paste for use in stews and soups. Also in Southeast Asia, cocoyam leaves are consumed as a

green or dry vegetables and the stem is either cooked or eaten on its own or together with other

dietary staples or pounded into flour (Serem et al; 2008).The dried peeled corms are grinded to

produce flour which is considered to be as palatable as cassava flour but more nutritious

(Igbokwe, 2004).

In the traditional farming system women "own" and plant cocoyam after the men have

planted their yam, hence it is regarded as a women's crop (Igbokwe, 2004). As a result of male

out migration into urban and semi urban areas, certain task that were traditionally done by men

(e.g. ridging) are now being done by the women folk. Thus the gender based differentiation of

farm tasks appears to be disappearing. Some scholars believe and argue that majority of the

small scale farmers who produce the bulk of Nigeria's agricultural output especially cocoyam

are women. It is still their contention that women also play key roles in storage preservation,

processing, utilization and local marketing of agricultural produce (Dixon, 1983; Ekumankama

and Ekumankama, 1996). Females constitute the greater percentage of the Nigerian population

in the rural areas (Musa, 1987)

Given the importance of cocoyam and the fact that its cultivation is receeding, it

becomes compelling to examine the production methods, practices and resource inputs for its

production methods, practices and resource inputs for its production in other to identify

opportunities for improvements in terms of cultivation and efficient use of available resources.

Government research effort under cocoyam expansion programme had led to

development of several technologies aimed at adding value to cocoyam production (NRCRI,

1999). Also, dissemination of the improved technologies as well as advocacy supports for

overall development of cocoyam are effective strategies for optimizing utilization of the

abundant potentials associated with cocoyam in Nigeria.

3.1 Problem Statement

The resource allocation to cocoyam is significantly low when compared to other crops

such as yam and cassava. Technical difficulties involved in managing cocoyam, especially the

post harvest losses usually not encountered in the rival crops have made cocoyam comparatively

less attractive especially the male farmers thereby affecting productivity (Ekwe et al; 1999).

Cocoyam production in South Eastern Nigeria is threatened by some factors such as the cocoyam

root, not blight complex, high cost of labour, which is almost entirely manual (Okoye et al; 2008).

Also the preference of other crops to seriously cocoyam in household production, and

consumption decision became fundamental reasons for its neglect and under utilization. Empirical

findings of earlier research like (Dimelu et al; 2008) on cocoyam have reported reasons such as

high cost of labour, disease outbreak etc. for decline in output of cocoyam, none of these studies

tried to explain output decline from point of view of gendered use of production resources nor

did they consider that the people (women) who are left to carry on its production might have

some gender-related constraints in resource utilization which could affect entry into cocoyam

farming as well as productivity.

Hence, there is need to sustain the level of production through productivity and

resource use studies, agricultural production in Nigeria has always been seen as dominated by

men and this assumption undermines the women involvement in agricultural production.

Okoye et al (2007) pointed out that women farmers for several years have been the pillars of

cocoyam production. Unfortunately as noted by Durno and Stuart (2005), they are not

recognized as farmers and are not critically involved in the process of farm problem analysis,

planning and decision making, or provided with the training, credit and support they need.

They equally noted that development opportunities are usually offered to those who are better

off and better educated, majority of whom are men. Many extension programmes are focused

on the "family headed" that is the husband as women are considered as helpers in the farm.

The presumption is that women are less economically efficient than men in Agricultural

production.

The problems of this study therefore are to analyze the possible ways in which

equitable gender involvement and resource use will help increase output in cocoyam

production in Anambra state.

In view of this forgoing, this study attempted to answer the following questions:

- to what extent are men and women involved/engaged is cocoyam production?

- do women have access to the same quantity and quality of resources as men in

Cocoyam production?

- does being a woman influence how resources are applied for cocoyam production?

- how efficiently do women farmers employ resources for cocoyam production?

- what are the sources of inefficiency in women's use of cocoyam resources?

1.3 Objective of the study

The broad objective of this study was to determine by gender the resource use efficiency in

cocoyam production in Anambra State.

The specific objectives are to:

(i) examine the socio-economic characteristics of cocoyam farmers in Anambra State

(ii) estimate and compare the mean output of men and women cocoyam farmers.

(iii) estimate and analyse the technical and allocative efficiencies of cocoyam farmers by

gender

(iv) compare the technical and returns to scale of the farmers based on gender.

(v) determine the profitability of cocoyam farming by gender.

(vi) identify the major problems/constraints faced by the men and women cocoyam

farmers.

(vii) Recommendation based on the research findings

1.4 Statement of Hypotheses

The following hypotheses were tested:

HO1 There is no significant difference in technical and allocative efficiency of the cocoyam

in the use of farm resources across gender

HO2 There is no significant difference in the mean output of male and female cocoyam farmers

HO3 Cocoyam production is not profitable in the study area

1.5 Justification of the Study

Improving cocoyam productivity, achieving self sufficiency in cocoyam production and

other food crops has been a major concern to scholars and policy makers as well as farmers

themselves, majority of who live in the rural areas (Okoye et al; 2007). This is more worrisome

considering the fact that Nigeria is endowed with rich and abundant cocoyam growing

environment and hence has the potential to greatly increase its cocoyam production.

Women are actively involved in agricultural production in Nigeria, In Sub Saharan

Africa, women grow 80 percent of the food destined to the Kitchen (Mamman, 1994). They

play a variety of roles in agriculture as farmers in their own rights, working in their husbands

farms and are increasing entering employment in the production of all kinds of crops for sale.

Akanji (1999) pointed out that the current state of knowledge is limited due to the under-

reporting of the contributions of women and children to commercial agriculture, this study will

highlight some of the problems confronting especially women farmers, pointing out the

direction for ensuring higher efficiency in farm resource utilization and productivity in their

operations in cocoyam farms.

This study will be essential to understand the nature of the constraints women face in

order to effectively help women farmers because failure to take into account gender relationships

leads to the marginalization of the disadvantaged sector of the society and a large part of the

agricultural work force

It will equally provide the much needed micro level data and the empirical basis for farm

planning, policy formulation and implementation, for no society can afford to neglect the needs,

rights, aspirations and contributions of half of its population. It will ensure policies that will

improve the productivity of male and female cocoyam farmers as well as information on relative

access to and control over resources will be important in the development of food security

strategies.

The study will also provide a basis for equitability, effective and better allocation of

resources between male and female cocoyam farmers. This study will add to the already existing

literature on production which may aid further researchers in other geographical areas. It will also

be useful to potential investors interested in cocoyam business in Anambra state. It can also

provide useful information, which will help in decision making for improvement of cocoyam

business in Nigeria. The study will also be of immense benefits to researchers as well as policy

makers on the need to keep the government at various levels abreast with the economic value of

cocoyam. It is used for teaching purposes. Finally, in the developing countries where technologies

are rarely developed, efficiency is the means of improving production and productivity

CHAPTER TWO

REVIEW OF RELATED LITERATURE

Related literature will be reviewed in this chapter under the following sub headings

� Under Utilization of Cocoyam

� Potentials of Cocoyam

� Gender Issues in Agriculture

� Gender and Farm Input Delivery System, Supply Productivity

� Cost and Return

� Research Problems and Resource Allocation of Rural Economies

� Evidence of Resource Productivity and Efficiency Studies

� Theoretical Framework

� Analytical Framework

2.1 Under Utilization of Cocoyam

Ekwe et al (1999) posits that the reasons for under exploitation of the values of cocoyam

in Nigeria may be attributed to the competition for relevance in the farming and food systems, and

degenerating, unenterprising of the commodity. This has led to the extinction of the crop as a

staple food which is over showed by the new crops, which soon gained ascendancy as a staple

food. The consequence is that the cocoyam becomes grossly marginalized while it rich value

remain underexploited for enhancing household food security and economic empowerment.

The production ccocoyam has not been given priority attention probably due to its

inability earn foreign exchange and its unacceptability to the high income groups for both

consumption and others purposes ( Onyenweaku and Ezeh, 1987). The market demand for

cocoyam is very elastic and by far less than that of its competitors, as a result, its production is

often discouraged by prevailing unfavourable market forces which seriously erode every incentive

to invest in cocoyam production.

According to (Arene and Ene ;1986) the average in daily calories supply of cocoyam was

45.98cal/day which was low compared to 314.8cal/day from cassava and 281.4cal/day from yam

and this data places cocoyam at the periphery of Nigerian diets. Thus cocoyam competes most

unfavourably with these rival crops not only in land areas under cultivation but also in dietary

uses. Nutritionally, the edible corms and cormels of cocoyam contain raphides which are minute

bundles of crystals of calcium exalates which causes irritation to the skin if not well cooked.

Cocoyam also have unattractive mucilage which could discourage consumptions.

Traditionally, cocoyam are consumed by the low income earners and avoided by the high

income and upper social classes. This distinctive attitude earned cocoyam certain socio-cultural

prejudices and untoward perceptions which discourage its production, consumption and choices

as farm business enterprise.

2.2 Potentials of Cocoyam

2.2.1 Nutritive Values of Cocoyam.

Nutritionally, taro and tannia are very similar. Their corms and cormels are composed of

77-86% edible materials and 14-23% scaly peels. These corms and cormels are rich in calcium

phosphate and vitamin A,B and C. Their leaves are very nutritious as they contain up to 20%

protein on a dry weight basis as well as appreciable amount of vitamins and minerals Onwueme

and Sinha, (1991). This agrees with Duru and Uma, (2002)where they stated that in South East

Asia cocoyam leaves are consumed because they are rich in protein and vitamins while the root is

rich in carbohydrates and minerals.

The corms and cormels of cocoyam are rich sources of carbohydrates which provide

energy for man’s physical and mental activities. They also contain protein for body building more

than cassava and yam. Moreover, cocoyam compares favourably with these rival crops and in

some aspects excels in content of such nutrients as protein, vitamin and minerals. In consideration

of these attributes, cocoyam can be fully exploited as a specialist for food resource for the invalid,

babies and nursing mother (Ekwe et al, 1999). Cocoyam has relatively small sized starch grains

which are easily digestible and therefore acclaimed to be very good carbohydrates source for

persons that may be diabetic. This rare attribute is indeed a great value which can be utilized in

management of sugar related diseases that severally occur even among the high income

individuals who ordinarily may not consume cocoyam.

Apart from the corms and cormels the young succulent part of xanthosoma leaves are rich

in thiamine (Arene and Ene;(1987). He also stated that similarly colocasia leaves are rich sources

of folic acid, riboflavin, vitamin A and C, calcium and phosphorus, thus making them

particularly useful for blood and bone build up in the body. The cocoyam leave has great values

for nutritional care of pregnant and nursing mothers.

A beverage made of colocasia powder, sugar, coco milk and salt had been observed to be

a tasteful relish. It is conceived that the colocasia powder could also be a nourishing ingredient in

ice creams and chocolates (Agboola, 1987). Cocoyam also plays very important roles in animal

nutrition, considering the high costs of conventional feeds; use of cocoyam bye-products in local

formulation could significantly reduce cost of livestock production in Nigeria.

2.2.2 Economic Values of Cocoyam

Although cocoyams (taro and tannia) in recent years appear neglected and underutilized

when compared with other food crops, they still maintain important economic values in several

Nigerian households where they are produced for consumption, sales, and planting. In South

Eastern Nigeria cocoyam production and marketing are twin enterprises sustaining the livelihoods

of many rural households.

Specifically, in Anambra and Enugu States rural women invest their resources intensively

for cocoyam production so as to maintain a regular sale of their produce in the local markets or

occasionally at urban markets. This trend also earned the crop a perception as a “women’s crop”.

Income from such sales is used by the women to buy other food stuffs for the household up keep

consumption as well as settle some financial matters. By these practices cocoyam lend substantial

boost and support to the economy of rural households.

Cocoyam still occupies important position in the menus of many low income urban

dwellers. as a result cocoyam marketing enterprises thrive in urban centres. Middlemen travel to

remote rural markets to purchase cocoyam corms and cormels for sale in city markets. The

emergent varied food forms of cocoyam through value addition is also making a big promotion of

cocoyam marketing enterprises, with these value added product like cocoyam soup thickener,

flakes, beverage powder and balls gaining stands in super markets and shops. Cocoyam corms

and cormels have good manageable sizes which make for easy crating and export. Although,

Nigeria is not yet known for cocoyam export, there are unofficial reports that Nigeria cocoyams

are available at African shops in United State of America and Europe (Ekwe et al, 1999).

Industrially, cocoyam can also be useful in boosting the Nigerian economy. It has been

shown that cocoyam starch can be efficiently converted into alcohol which is an essential raw

materials for the manufacture of myriads of products like perfumes fire extinguishes, soaps,

hydraulic fluid, deodorants e.t.c. (Ejiofor, 1987). These products command large domestic and

export markets, yet the potentialities of cocoyam for the products are yet to be fully unlocked in

Nigeria.

Also cocoyam alcohols and starches are required in pharmaceutical and food industries for

production of vitamins, flavours, toothpastes and blood boosting drugs and fortified wines

(Ejiofor, 1987, Okwuowulu et al, 2002), with substantial content of protein, vitamin and minerals

in cocoyam leaves silage could be made from cocoyam leaves and petioles after harvest for use in

livestock feeding.

2.2.3 Agronomic Values of Cocoyam

Cocoyam are early maturing (8-12 months after planting) crops (Uguru, 1996). Although

yield under peasant culture range between 6 to 10 tones per hectare, a yield of 30-60 tonnes per

hectare is attainable if clean healthy and good sized planting materials are used and cultural

practices optimally maintained (Eleje, 1987). Today, even with minimal improvement on the

farmers practice, Nigeria produces about 4 million metric tones per annum which accounts for

40% (largest) of the world production of the commodity (FAO, 2005). Serem et al (2008) pointed

out that cocoyam have also been established to be low maintenance crop that will maintain a

ground cover crop in the field to reduce soil erosion. With potential capacity of 30-40mm/ha

cocoyam, like other tropical root crops has very high propensity for supplying large quantities of

utilizable calories per unit area of land cultivated, (Arene and Ene;1987). Also cocoyam’s

importance as a component of the farming system is easily observed in the rural farm

environments where it is cultivated, sold or in mixture with such crops like yam cassava, plantain,

banana e.t.c. In fact they are more abundantly available in homestead farms than even yam and

cassava.

2.3 Gender Issues in Agriculture

Gender relation refers to social norms and practices that regulate the relationship between

men and women in a given society. Gender relations determine household security, well being of

the family, planning of agricultural production and many other aspects of rural life (Frishmuth,

1997). It is important to understand gender contribution to agricultural production. This

understanding will ensure efficient allocation of scarce resources among competing enterprises in

the household (Onyemauwa et al; 2008). In a Nigerian case study, it was found that women

participated in all aspects of farm work often to an extent as men but decision making concerning

economic activities is mostly the reserve of men, (FAO, 2004). Durno and Stuart (2005) noted

that women produce the bulk of basic food stuffs both for household consumption and for sale,

although it is widely documented that women are more involved in trading and farm food

processing. Several studies have shown a clear departure and a distinctive place of women in all

categories of farm operation. Mkpado and Arene, (2003), and Efifu, (1999) stated that gender

studies in agriculture should analyze the roles and activities of male and females by focusing on

their experience and not on their biological or sex differences in a society. This agrees with

Uzokwe, (2009) that the ability to increase production in developing countries has great gender

implication.

Gender inequality tends to slow economic growth and make the rise from poverty more

difficult World Bank, (2005). It is therefore view the third millennium Development Goals of

promoting gender equality and empowering women as a major central component to its overall

mission of reducing poverty and stimulating economic growth. The current dwindling national

revenue and its economic consequence has put pressure on the male to the extent that women are

no longer permitted to sit at home and adopt the wait-to-be-fed attitude (Ogbosuka & Salahu,

2005). Furthermore Ironkwe et al, (2007) observed that lack of adequate gender specific data and

statistics has given rise to assumption on the contribution of men and women in agricultural

production which negatively influenced agricultural policies, development of improved

agricultural production technology and programmes aimed at increased farm productivity.

Both men and women play critical roles in agriculture throughout the world in producing,

processing and providing the food we eat. FAO (2004) pointed out that women in developing

countries are the main stay of agricultural sectors, the farm labour force and food systems (and

day to day family sustenance), the last to benefit from resources and in some cases have been

negatively affected by prevailing economic growth and development process.

Gender bias and gender blindness persists, policy makers, development planners and

agricultural services deliverers still generally perceive farmers as “male” (Durno and Stuart,

2005) for this reason women find it very difficult than men to gain access to valuable resources

such as land, credit, agricultural inputs, technology, extension training and services that will

enhance their production capacity.

Wieczorec-Zuel (2007) opined that in Sub Sahara Africa, women produce up to 80 percent

of all staple foods, own only 10% of farm land and have little to less than 26 percent of land

across the developing world. According to Verma (2001) women accounted for 70 to 80 percent

of household food production in Sub Saharan Africa, 65 percent in Asia and 45 percent in Latin.

America, and the Caribbean, (FAO, 2004), (Durno and Stuart, 2005) also noted that in South East

Asia, women provide up to 90 percent of labour for rice cultivation. Dimelu et al, (2009) found in

their paper “Determinants of gender efficiency of small holder cocoyam farmers” in Nsukka

agricultural zone of Enugu State, Nigeria, that mean efficiency score for male and female

cocoyam farmers was 20 and 56 percent respectively.

In Sub Saharan Africa women produce up to 80 percent of basic food stuffs both for

consumption and for sale. Women perform from 25 to 45 percent of agricultural field tasks in

Columbia and Peru, women constitute 53 percent of the agricultural labour in Egypt; fewer than

10 percent of women farmers in India, Nepal and Thailand own land, (FAO 2004, Durno and

Stuart 2005).Analysis of credit schemes in five African countries found out that women received

less than 10 percent of the credit awarded to males small holders farmers and only 15 percent of

world’s agricultural extension agents are women (Durno and Stuart 2005). Also FAO (2004)

found out that both men and women in most developing countries do not have access to adequate

resources but women’s access is even more constrained as a result of cultural, traditional and

sociological factors.

There is apparently no strict dichotomy of gender specific crops but it has noted that men

grow more yams and tree crops while women produce cassava, cocoyam, vegetables (Efiful,

1999). Chinaka and Emerole (2006) also conducted a study involving 300 females who were yam

producers in Imo State Similarly Okoye and Onyenweaku (2006) have demonstrated that 74

percent and 26 percent of cocoyam producers in Anambra state were females and males

respectively. Accurate information about men and women’s relative access to and control over

resources is crucial in the development of food security strategies. Rural women form the most

important of majority of the developing nations. In India for example, there are 75 million women

engaged in dairying, 20 million in animal husbandry as compared to 1.5 million men (DAC,

2004). This justifies FAO (2004) recognition that the empowerment of women is key to raising

level of nutrition, improving the production and distribution of food and agricultural products and

enhancing the living conditions of the rural population.

2.4 Gender and Farm Input Delivery System, Supply And Productivity

The adequacy and timeliness of agricultural input supply affects the productivity of farm

enterprises. Farm inputs encompasses among others setts, fertilizers and agro chemicals, cropping

patterns, effective credit institutions, soil and water conservation, irrigation investments as well as

appropriate marketing and price structures and other basic agricultural support services. Mejeha

and Obunadike (1998), in their study on the impact of credit on adoption of innovations on

fertilizer use, yam minisett and cassava in Anambra state of Nigeria found out that farmers spent

more on innovation adoption with credit than without credit, the reason being that credit

availability afforded farmers the opportunity for more access to farm inputs. Their result showed a

positive correlation between credit and innovation adoption. They noted that the rate of adoption

of new technology by farmers is generally high if the profitability of a change over to the new

technology, the economic position of the farmer and the effectiveness of the extension agents are

high.

Nwaru (2004) emphasized that credit provision should be with the supportive services

needed to make the credit facilities work. Short term and long term credit is needed to pay for

inputs and hired labour. However, in the developing world, banks and credit associations are less

inclined to lend to women because without property and land rights, they lack collateral. These

improved inputs such as fertilizers and pesticides are vital means of enhancing production but

extension services and cooperatives distributing inputs rarely reach women who also lack the

necessary cash to purchase even government subsidized inputs. FAO (2005a) reported that few

extension services were targeted to rural women, few of the worlds extension agents were women

and most of the extension services focused on commercial rather than subsistence crops- the

primary concern of women.

FAO (2004) reported that extension is often biased towards cash crops that tend to be

grown by men and large scale farmers. Most programmes targeted towards women tend to focus

on home economics and nutrition rather than farm production and processing. Women are under

represented and sometimes not represented at all among extension staff and trainer, therefore,

there is need for an effective and efficient extension delivery system. In addition, credit should be

made available to small scale farmers especially women. As Desai and Meller (1993) correctly

noted farm level credit, when extended properly, not only for crop farming but for dairying and

other directly related farm level economic activities encourages diversified agriculture which

stabilizes and perhaps increases resources productivity, agricultural production, value added and

net income of farmers, credit availability stirs up farmers, latent entrepreneurship qualities and

that credit equality constitutes the key to unlock the farmers latent vision, talents, abilities and

opportunities that in turn act as the mover of economic progress (Nwaru, 2004). Moreover,

Krause et al (1990) and Immink and Alarcon (1993) noted that lack of access to credit prohibits

smallholder farmers from assuming risks of financial leverage associated with the adoption of

new technology and that lack of access to market reduces gross margins. They reported that

adoption of new technology was also found to be sensitive to the amount of equity capital.

Though access to credit offers liquidity there is usually no rural financial intermediation by

formal credit institutions.

High cost of intermediation is disposed and thin rural market lack of acceptable collateral

and high default rate inhibit the extension of the services of formal credit institutions (Nwaru,

2004). The innovative strategies are required to reduce the cost of rural financial intermediation

which provides small-scale farmers with credit, and facilitates successful technological change

and enhances productivity. This could be through risk sharing schemes between farmers and their

partners, the spreading of credit over farm and non-farm activities that can help farmers build up

their own liquidity and the linking of formal and informal local credit/saving associations.

Ownership of land has a significant bearing on resource use and productivity and that the

divergence between existing and optimal net returns clearly demonstrates the scope of increasing

net returns through optimal and reallocation of resources on owner-cum-tenant and pure tenant

farmers.

2.5 Cost and Returns

Cost: Agricultural production decisions cannot hold without cost considerations Arene (2008).

Cost refers to the value of inputs used in production and the cost of producing commodity such as

cocoyam refers to the expenses incurred in producing a particular quantity of the commodity in a

given period of time. Olayide and Heady, (1982) defined cost as the change in equity caused by

the performances of some special operations. Cost concepts are of great importance as they enable

the farmer to make choices among present alternative actions. Types of costs include;

a) Variable cost: This refers to operating cost and they vary in direct proportion to the level of

activity and include costs of land clearing, cultivation, setts, fertilizer and weeding.

b) Fixed cost: They are the expenses that cannot be changed or altered in the short run (Oji

2002,) fixed cost items include implement action such as machetes, wheel barrow e.t.c. According

to Upton (1996)`, Agom and Idiong (2002) developing countries do not necessarily incure explicit

fixed cost. It is expected that farmer net return will equate the gross margin. If increase in gross

margin can be achieved with existing supply of fixed resources (often the case in rural agricultural

production, profit will be raised by the same amount as the gross margin (Upton, 1996). Hence

the gross margin represents profit and net farm income of the enterprise under this condition.

c) Total cost: This is derived from the summation of variable costs and fixed costs. Total cost

of production is an important parameter in estimating the net profit associated with a given

enterprise.

Returns: This is the revenue, income that is received from the sale of farm output (Olayide &

Heady 1982). The net profit therefore, is given by total revenue less total cost.

2.6 Resource Problems and Resource Allocation of Rural Economies

2.6.1 Resource Problems

Farm resources are inputs of labour, capital, land and management. These inputs are

combined in various ways to produce outputs. Olayide and Heady (1982) refer productivity as the

index of the ratio of the value of the total farm output to the value of total inputs used in

production, they also stated that maximum resource productivity implies obtaining the maximum

possible output from the minimum possible set of inputs. Thus optimal productivity of a resource

denotes an efficient use of the resources in the production process, subject to constraints.

Olayide and Heady (1982) noted that the kinds and quantities of resources used in primary

production activities are characterized by old techniques and simplicity of farms that tend to give

rise to low output. These low outputs results in low food supply and subsequent food and

nutritional, problems which are manifested in subsequent malnutrition disease and socio-political

economic discontent.

Total resource productivity in agriculture is estimated to have grown by an average of 1.3

percent annually between 1961 and 1991 for Africa as a whole. Land productivity rose by an

average of 1.9 percent per year. By contrast, labour productivity fell by an average of 1 percent

per year. Meanwhile growth in agricultural productivity appears to be slowing and land

degradation has been blamed as contributing factor. Moreover, the main problem of resource use

centres on scarcity. This raises the fundamental need for “economizing” productive resources,

consumption goods, money, time and energy in any eco-system. These resources are

characterized by three set of conditions viz scarcity interpreted to mean a situation whereby

people want more of it or of the thing it can help to produce than is freely available, alternative

uses to which the resources can be put and finally its transferability which implies possibility of

movement from one individual or use to another Olayide and Heady (1982).

The available resources, there have not been effective and efficient utilization as in most

cases, they are either under utilized or over utilized (Effiong and Nwaru, 2002, Nwaru, 2002,

2003). Effiong and Nwaru (2002) pointed out that the hub of efficient resource husbandry is the

manipulation of available scarce resources and technical know-how to achieve the possible

highest benefits within given natural and socio-economic environment. Nwaru (2001) noted that

rural resource users must come to a dynamic and innovative level where they can create, establish

and nurse economic activities with greater success through mobilizing and allocating available

rural resources more efficiently. He also pointed out that this will help them conquer the myriads

of constraints and be released from the ugly vicious web of low output, poor income unimproved

inputs and technology leading to low level entrepreneurship. The rural farmers are severely

limited in many respects and the limitations include labour, technical constraints including

inadequate infrastructure dependence on unimproved inputs and rudiment technology (Njoku

1988).

2.6.2 Rural Resource Allocation

Hardwick et al (1994) noted that all methods, resource allocation have social welfare

maximization as their over-riding aim and resource allocation involves decoding what, how and

for whom to produce. According to Upton (1996), traditionally village society is often

characterized as a rural self-sufficient community of people linked through kingship and other

ties. Production distribution and consumption takes place within the closed community while

social and economic relations are based on the status of the individual members. There is strict

observance of social norms and customs including religious beliefs and practices. These

established customs laws and relationships make up the traditional institutions, which governs the

allocation and use of resources and the distribution of agricultural products, which are geared to

securing a minimum level of subsistence for all community members.

Markets have provided opportunities for specialization and division of labour with each

type of farming zone concentrating on those areas for which it has the greatest comparative

advantage. Barau et al (1999) opined that the measurement of output was the first major element

of productivity analysis, since the objective of productivity measurement was to find out how to

produce outputs of desired goods and services with minimum amount of human and physical or

natural resources. Olagoke (1990) emphasized that the problem of low productivity was the

inability of farmers to efficiently make use of available resources. It implies that the problem of

low productivity can be solved if the farmers are exposed to various input combinations, which

may enable the enable the efficient management of resources with the view of increasing output.

Specialization will lead wider choice range of consumer good for rural households, the use

of manufactured chemical, equipment and other inputs from outside system, easier movement of

labour and other resources between regions and greater opportunities for the accumulation of

capital (Adeniyi,1998; Upton, 1996). This on overall should allow increases in production

efficiency, increased income for farm households and a general improvement in social welfare.

Hardwick (1994) opined that market economy will rely on prices as signals to consumers and

producers and the consumer express their preferences for goods and services to producers through

their spending decision viewed as “money vote”. The more money is spent on a particular good,

the greater will be the incentive or producers to supply that good. Farmers allocate their resources

to those productive ventures that earn higher returns for their resources. These resources are

allocated bearing in mind the opportunity cost of allocating them in a particular area. The

quantities of resources used are largely the result of conscious human decisions. More so, for

crops to be produced at optimum profit, variable factors of production should be employed at

levels such that the value of the marginal product is equal to the factor price of each variable

factor. Some inputs are fixed at different levels in different farms such as land supply, the family

size and managerial ability of the farmer. Alternatively, there may be variations between farm in

the price paid by them for resources.

However, inputs according to Upton (1996) do not vary at random between farm firms but

are chosen by farmers or allocated by the society according to some set of decision rules such as

customary rights and traditions. Therefore efficient manipulation of productive resources in the

rural economy of Nigeria can increase output and incomes of farmers for instance, inefficiency in

resource allocation and use has been reported by Effiong and Nwaru (2002) and Nwaru (2003).

This implies that there is room for increasing the current level of food production through a more

efficient use of available agricultural resources.

2.7 Evidence of Resource Productivity and Efficiency Studies

Resource productivity is the quantity of good or service (outcome) that is obtained through

expenditure of unit resources (Hargroves and Smith, 2005). Resource productivity and resource

efficiency are two concepts closely tied to production function. They concern the relative

performance of resources used in production process Eze (2008). Ogundari et al (2004) in the

study of impact of economies of scale and cost efficiency in small scale, resource poor farmer are

efficient in their use of resoures and the expansion of their level of expansion will reduce cost per

output. This is in accordance with result from earlier study of Yotopolus and Lau (1973) where

they indicate higher relative efficiency for small farmers.

In a study on “Rural credit markets and resource use in Arable crop production, in Imo

state of Nigeria, Nwaru (2004) found out that none of the defined farmer groups (credit users and

non credit users) achieved absolute allocatve efficiency because non achieved an allocative

efficiency index of unity. The credit user farmers achieved better allocative efficiency than non-

credit users in the use of material inputs and capital while the non credit users are better in

allocating farmland. While the credit user farmers over utilized hired labour, capital, material

inputs and fertilizer and underutilized farmland the non credit users farmers over utilized hired

labour, family labour and capital and underutilized farmland and material inputs.

Nwaru and Ekumankama (2002) studied the economics of resource use by women arable

farmers in Abia state and found out that on the average, men cultivated 2.15 hectares and women

1.47 hectares and that the women farmers were allocatively more efficient in the use of fertilizer

and capital while men performed better in the use of labour, other inputs and farm land. Nwagbo

and Onwuchekwa (1998) found out that hired labour contributed to low productivity due to high

labour hiring rate in farm operations. Family labour is the most important source of farm labour in

Nigeria and is influenced by household size farm size, composition of household among others

(Okoye 1989). This agrees with Chidebelu (1990) where he noted that family is the most

important input of unpaid labour.

Ohajianya and Onyenweaku (2001) using profit function approach, found equal economic

efficiency between small scale and large scale farmers in the swamp rice production system in

Ebonyi state of Nigeria. Also in their earlier study of gender and relative efficiency in rice

production system in Ebonyi state of Nigeia, Ohajianya and Onyenweaku (2001), using profit

function approach observed no significant difference in economic efficiency between male and

female farmers in swamp and upland rice production systems.

Alabi and Aruna (2006) studied the technical efficiency of family poultry production in

Niger Delta, Nigeria, it was discovered that inefficiency parameters show age as being negatively

related to poultry production. It further showed that family size, gender, innovation adoption have

negative relationship with efficiency of poultry production.Ogar et al (2002) while studying the

allocative efficiency of labour resources in swamp rice in Obudu, Cross River state of Nigeria

found inefficient allocation of labour during clearing and weeding operation among rice farmers

in the area.

Onyenweaku and Ohajianya (2005) measured the level of technical efficiency of upland

and swamp rice farms in South Eastern Nigeria using stochastic frontier production function.

They noted that the estimated farm level technical efficiency ranges from 28.19 percent to 93.13

percent with a mean of 63.87 percent for swamp fields and from 17.19 percent to 92.15 percent

with a mean of 65.24 percent for the upland fields they concluded that wide variation in technical

efficiency in the production system shows that ample opportunities exists for rice farmers to

increase their productivity and income through improvements in technical efficiency.

A study by Ajibefun and Abukadri (2004) on impact of farm size operation on resource

use efficiency in small scale farming shows that resources availability does not translate into

efficiency. In the study, it was discovered that farmers with less intensive use of land, labour and

capital resources are efficient in the use of the resources than farmers that use resources

intensively. A study by Awudu and Huffman (2000) on economic efficiency of rice farmers in

northern Ghana shows that 29 percent of potential maximum profit was lost due to inefficiency.

The study further shows that high level of education reduced profit inefficiency.

2.8 Theoretical Framework

A theory is a set of related statements that are arranged so as to give functional meaning to

a set of events. The basic theories on which this work could be based are theories of resource use,

production and efficiency. This work could also be underpinned in one or more hypotheses

relating to gender and agricultural production. Farm resources are inputs of labour, capital, land

and management. These inputs are combined in various ways to produce some output. A resource

is any good or services which has the capability of satisfying human wants. It varies with the

qualities of scarcity and value and therefore choices must be made about the use to which a

resource will be put. Onyemauwa et al (2008) content that resource use refers to allocation of all

resources between competing alternative with aim of deriving maximum returns such as profit,

food calories or national income from given resources. Production of farm commodities like

cocoyam involves numerous relations between resource inputs and products. it is concerned

essentially with deriving a maximum level such as profit food calories or national income from

given resources, and products is very important because it provides the tools by which the

problems of productions and resource use can be analysed.

Production refers to the principles to be applied in making production decisions (Oji

2002). Production decisions include the decision include the decision to acquire resources, utilize

resources, organise production, distribute the product of the productive activity and in general to

manage the services of production resources. Therefore, production is the process whereby some

goods and service whereby some goods and services called inputs are transformed into other

goods and services called output. Production function refers to the technical relationship which

connect factor inputs with outputs in a production process (Oji, 2002). The production function

could be expressed in the implicit form as:

Y = +(x1, x2, x3 ……. xn) . . . . . . .(2.1)

Where: Y is the output or the product level inputs and xi = (1 are the resource levels. Nwaru

(1993) noted that production function has no part in choice or decisions making in investment as

it seldom defined which production pattern or resource use is the best level. He noted that the

most desirable combination of factors or production could only be determined when economic

principles are applied. This application moves agricultural production from the fields of biological

science to the field of economics (Nwaru, 2004) Equation (2.1) gives the total physical product

(TPP). A number of production parameters can be derived from this production function. they

include average physical product (APP), Marginal Physical Product (MPP), Elasticity of

Production (EP) and return to scale. Onyebinama (2000), Oji (2002) and Hendersen and Quandnt

(2003) described this parameter.

In Agriculture, there are marked and persistent gender inequalities mostly in cocoyam

production. Concept of gender often enters discussion within agricultural development either

through distinctions between male and female headed households or through distinction between

men and women roles in farm activities (Doss, 2002). This distinction affects the resource use

efficiency and the output of cocoyam. Gender bias influences resource allocation between men

and women, attitudinal barriers against women are deeply rooted in patriarchy based socialization

where men are considered more superior to women in socio economic activities and low women

presence in decision making bodies (Amaechina 2002). if women should become more and well

equipped as well as male with needed skills and financial capacity to be more relevant in farm

resource allocation and decision making the output and productivity of cocoyam will increase in

the study area.

Efficiency is central to economic analysis because it provides the yard stick for evaluating

decisions on choices regarding the use of scarce resources. If these resources (land, labour, capital

and management) are not efficiently utilized low productivity and waste results. The crucial role

of efficiency in increasing agricultural output has been widely recognized by researchers and

policy makers alike. Thiam et al, (2001) highlighted the importance of efficiency as a means of

fostering production which has led to proliferation of studies in agriculture on technical efficiency

around the globe micro economic production function studies have usually been used as tools for

examining problems of efficiency of resource use and productivity at farm enterprise level. This

study is based on the theory of resource use efficiency to maximize cocoyam output per hectare of

land area by gender, therefore, the problem of low productivity of agriculture can be solved by

improving efficiency of resources used (Ojo, 2003). Firms lying on the production frontier are

100 percent technically efficient with (T.E. = 1) and Technical inefficiency of the firm increases

with distance from the production frontier (Forsund et al 1990 in Ugwu 2008).

Technical Efficiency:

Technical efficiency in production is ability of the farmer to produce at the maximum output

frontier production given quantities of inputs and production technology (Amaza and

Maurice,2005). The definition of technical efficiency implies that differences in technical

efficiency between firms exists. Variation in technical efficiency of producers might arise from

managerial decisions and specific-farm characteristics that affect the ability of the producer to

adequately use the technology. In Farrell’s(1957) concept, the overall efficiency (O.E) is a

multiplicative combination of technical(TE) and allocative efficiency(AE) i.e OE=TE & AE.

Technical efficiency is the ability to produce a level of output with minimum quantity of inputs

under a certain technology. It is a micro concept observed differentials in technical efficiencies

which may be due to differences in managerial ability, the presence of different environmental

conditions such as soil quantity,rainfall,temperature,soil radiation, precipitation e.t.c non technical

and non economic factors which can prevent the user of the resources from working so hard

enough, thus failing to achieve the best level of output such as sickness (Nwaru,1993,2004).

Ogundele (2008) maintained that technical efficiency of a farm are characterized by relationship

between production or efficient production frontier. Omotosho et al (2008) stated that technical

inefficiency arises when actual or observed output from a given input is less than that of the

maximum possible. This agrees with Kadurumba et al (2010) when they found out that technical

inefficiency exists among palm oil farmers in Imo state.Onyenweaku and Nwaru (2005) used the

application of stochastic frontier production in the measurement of technical efficiency in food

crops in Imo State,Nigeria.

According to Nwakolobo (2000), a farmer who is said to be technically efficiently

produces as much output as possible from a given set of inputs or if he uses the smallest possible

amount of inputs for a given level of output. Technical efficiency is thus calculated as Technical

efficiency = actual output/ potential output. However,several other methods of research

philosophical view of importance of measurement error (Forsund et al 1980 in Ugwu 2007).The

various methods calculate a technical efficiency index ( TESCORE) which measure the distance

of the observed firm from a point on the production frontier (Brock et al;2006). Firms lying on

the production frontier are 100 percent technically efficient with (T.E=1) and technically

inefficiency of the farm increases with distance from the production frontier (Forsund et al 1990

in Ugwu 2008)

Allocative Efficiency:- Allocative efficiency has to do with the extent to which farmers

make decision by using inputs up to the level at which the marginal value product (MVP)equal to

the Marginal Factor Cost (MFC). Allocative efficiency measures the extent to which an analyzed

Diminishing Marginal Utility (DMU) produces its outputs in a production that minimizes cost of

production, assuming that the unit is already fully technical efficient i.e. when allcoative is pareto

efficient. A firm therefore is considered allocatively efficient in the use of a production resources

if the farm is able to equate the value of the marginal value product (MVP) of the factor to that of

factor price is able to maximize profit with respect to that factor.

Economic Efficiency: Economic efficiency is the ability of a firm to maximize profit. It is also

known as production efficiency and it is described as the product of technical and allocative

efficiencies. An economically efficient input/output combination would be both on the frontier

and the expansion path way (Ogundari and Ojo; 2006). Economic efficiency exists when the

MVP is not significantly different from MFC. (MVP = MFC). To achieve economic efficiency,

the ratio of MVP to MFC must be equal to one. Economic efficiency is concerned with maximum

profit. That is when a firm chooses resources in such a way that its marginal value product is

sufficient to offset marginal cost. The MVP is calculated from the respective regression

coefficients using appropriate optimum levels of output price depending on the lead equation of

the functional forms. The MFC is the market price of one unit of input. A ratio of less than one

implies that input is being over utilized while a ratio greater than one implies that input is under

utilized (Onojah 2004; Haruna et a;l 2008).

A study by (Egwu et al; 2010) on a Technical Efficiency of commercial vegetable

production in Akwa Ibom State, Nigeria. The estimated results shows that technical efficiency of

the farms varied between 0.71 – 0.99 with mean technical efficiency of 0.86 implying average

technical efficiency as 81.7% of the difference between observed and best practical output among

the sampled farms was explained by technical inefficiencies.

A study carried out by (Anyaegbuna et al; 2009) on a translog stochastic cost inefficiency

among small holder cassava farmers in South East agricultural zone of Nigeria. The parameter of

the stochastic frontier cost function were estimated using the maximum likelihood method. The

result of the analysis shows that individual farm level cost efficiency was about 69%. A study

carried out by (Ndukwu et al; 2010) on gender and relative economic efficiency in sweet potatoe

farms of Imo State, Nigeria. A stochastic cost frontier approach. The result of the analysis showed

that the mean economic efficiency for the female farmers group was higher 82% than the male

71% counterpart.

2.9 Analytical Framework

Production efficiency is concerned with the relative performance of the process used in

transforming inputs into output (Arene, 2003, Eze, 2008). The four major methods used in

efficiency and productivity measurement are Least Square Econometric Production Models

(LSEPM), Total Factor Productivity Indices (TFPI), Data Envelopment Analysis (DEA) and

Stochastic Frontier Production Function (SFPF) analysis Ogundari (2006). Eze (2008) reported

that Stochastic Frontier Production Function (SFPF) analysis and Data Envelopment Analysis

(DEA) became the most commonly used methods. Both methods estimate the efficiency Frontier,

which shows the best performance observed among firms. The major reason why Stochastic

Frontier Production Function (SFPF) is commonly used is that it takes into account measurement

errors and other noise in the data, previous research on Stochastic Frontier Production Function

(SFPF) include Battesse and Coelli (1995), Amaza P. S. & Maurice (2008), Kadurumba (2010).

In this study, the Stochastic Frontier Production Function will be used for the analysis.

The Stochastic Frontier Production Function (SFPF) as defined by Coelli (1996) is specified as:

Y: = F (xi;β)exp (Vi – Ui); : = 1,2, --n -------------------------- (2.1)

Where,

Yi = Denotes output of the ith farm

Xi = is a vector of functions of actual input quantities used by the ith farm

β = is a vector of parameters to be estimated

Vi - Ui = is the composite error term (Aigner et al, 1977, Meeusen and van den Broeck, 1977)

Where,

Vi and Ui = are assumed to be independently and identically distributed

Ui = is a non-negative random variable, associated with technical inefficiency in production.

Vi = is a random error, which is associated with random factors not under the control of farmers.

Technical efficiency of an individual farmer is defined as the ratio of the observed output

to the corresponding frontier output, conditional on the levels of inputs used by the farmer. The

technical efficiency of farmer (i) in the contest of the stochastic production function in equation

(1) is:

TE = Yi/Yi* …………………………………… (2.2)

= F (Xi; β) exp (Vi – Ui)/ F (Xi; β) exp (Vi) …………………………………… (2.3)

= exp (-Ui) ……………………………………. (2.4)

Where,

Yi = is the observed value of output

Yi* = is the frontier output (Potential output)

Given the density function of Ui and Vi the frontier production function will be estimated by

maximum likelihood techniques.

The value of the technical efficiency lies between zero and one. The most efficient farmer

will have value one, while farmer having value lying between zero (0) and one (1) is described as

inefficient.

(b) Allocative Efficiency: This will measured as follows:

AE = EE/TE

Where AE: Allocative Efficiency

EE: Economic Efficiency

TE: Technical Efficiency.

Determinants of Allocative Efficiency will be modeled in terms of socio-economic

variables of cocoyam farmers. The allocative efficiency in the model was simultaneously

estimated with their determinants following kaldJan (1991) Exp. (.vi) = β0 + β1 Y1 + β2 x2 + β3 x3

= … +Σi (2.5)

Where Exp (-u) = efficiency of the ith farmer.

CHAPTER THREE

METHODOLOGY

3.1 STUDY AREA

The study will be carried out in Anambra State. The State is made up of 21 Local

Government Areas. It is located between latitudes 60 45

1 and 5

0 44

1 N and longitudes 6

0 36

1 and

70 20

1 E of the area with meridian. The temperature of the State during the dry seasons,

especially in January, ranges from 25.5 to 30.50C while during the raining season especially in

July it ranges from 25 to 27.50C (ANSEP 2000). The rainfall between November and April ranges

from 250 to 500 millimeters while between May and October it is over 2000 millimeters “(Duze

and Afolabi, 1985)”. The State is divided into four Agricultural zones namely, Aguata, Awka,

Anambra, and Onitsha. The zones are further delineated into 24 extension blocks and 120 circles

(Nkematu, 2000, ANSEP 2000). Anambra State is bounded to the North by Kogi State, to the

South by Imo and Abia States, to the East by Enugu State and to the West by Delta State. The

State, according to the N.P.C. Census figure has a population of 4,185,032 persons distributed as

2.1 million males and 2.1 million females (NPC, 2006).

Yam and cassava-based mixed cropping enterprises dominate small scale farm holdings in

the State besides rice production in Ayamelum, Ogbaru, Anambra East and West Local

Government Areas. Other crops gaining prominence in the area include potatoes and cocoyam

(Okoye and Onyenweaku, 2006). Still other crops grown in the State are maize, okro,

amaranthus, melon, pumpkin, perpes and garden eggs which are intercropped with base crops.

Legumes such as groundnuts and some varieties of cowpea are also cropped. Tree crops grown in

Anambra State include oil palm, mangoes, oranges, oil bean tree and fruits crops like pineapple,

bananas, paw-paw (Ugbajah, 2007).

With respect to animals, sheep and goat production, rabbitory, fish farming and poultry

enterprises are also practiced. Farmers in the State also engage in a wide variety of off farm

activities such as shoe repairing and petty trading on non-farm produce, especially during the off

farm seasons. Farmers dominate the State population hence, food production, processing and

marketing constitutes the major occupation.

3.2 Sampling procedure

Multi-stage sampling techniques will be used in selection of Agricultural Zones, blocks,

circles and contact farmers.

Stage I: Aguata and Awka Agricultural Zones will be purposely selected based on

intensity of cocoyam production (ANSEP, 2000) and two blocks each from each zone.

Stage II: From the selected blocks two (2) circles each will be selected from the blocks

given a total of (eight) 8 circles. From the selected circles, 20 contact farmers (comprising male

and female) will be randomly selected from the circle which will give a total of one hundred and

sixty (160) contact farmers.

Table 3.1: SELECTION OF COCOYAM FARMERS IN THE STUDY AREAS

_____________________________________________________________________

Agricultural zone Blocks Circles Cocoyam farmers

_______________________________________________________________________

Aguata Aguata Ekwulobia 20

Ajali 20

Orumba South Ogboji 20

Ezira 20

Awka Njikoka Nimo 20

Umunachi 20

Dunukofia Ukpo 20

Abagana 20

________________________________________________________________________

2 4 8 160

________________________________________________________________________

3.2 Sampling procedure

Multi-stage sampling technique was used in selecting of Agricultural Zones, blocks,

circles and farmers.

Stage I: Aguata and Awka Agricultural Zones was purposively selected based on intensity

of cocoyam production (ANSEP, 2000) and two blocks each from each zone.

Stage II: From the selected blocks, two (2) circles were selected from each block given a

total of (eight) 8 circles. From the selected circles, 20 farmers were randomly selected from each

circle which gave a total of one hundred and sixty (160) farmers (comprising male and female).

3.3 Data Collection

Both primary and secondary data were used. Secondary information was collected from

relevant literatures, journals and periodicals. Primary data were collected by the researcher

through field survey using structured questionnaire/interview schedule which elicits responses

from cocoyam farmers. Primary data collected include socio-economic characteristics of the

respondents, such as age, sex, household size, educational background, farming experience etc

Others was based on farm inputs like fertilizer, labour use farm size, capital assets, credit and

extension services; cost and returns (input and output) arising from cocoyam production.

3.4 Data Analysis

Objectives (i),and Objective (vi) were realized using descriptive statistical tools like

frequencies, means and percentages

Objective (ii) was analysed using T-test

1

2

2

1

2

1

21

nn

XXt

SS+

−=

−−

X1=The mean technical efficiencies of male cocoyam farmers

X2=The mean technical efficiencies of female cocoyam farmers

S12=The variance of technical efficiency of male cocoyam farmers

S22=The variance of technical efficiency of female cocoyam farmers

n1=The sample size of male of male cocoyam farmers n2= The sample size of female cocoyam

farmers.

Objective (iii) was realized using stochastic production function and multiple regression analysis.

The following functional forms via linear, semi log, exponential and double log forms following

Coelli (1994).The best was chosen based on high R2

values and no of significant factors and

apriori expectations

i) The Cobb-Douglas function

eixlbxlbxlbby nnn +++= 5522110 ......ln

(3.1)

ii) Semi-log function.

y= b0 + bllnx1 + b2lnx2……b5lnx5 + ei (3.2)

(iii) Exponential.

ln y = b0 + b1lnx1 + b2lnx2 …b5lnx5 + ei (3.3)

(iv) Linear function

y = b0 + b1x1 + b2x2 + …b5x5 + ei (3.4)

Where

Y = output of the farm in Kg

qty of fertilizers used in Kg

thi

1x =

X2=capital input (N) made up of depreciation on fixed assets

= Family labour in mandays used in production

X4= farm size measured as total land areas in hectares

X5= qty of cocoyam setts planted in Kg.

= Intercept

= coefficients estimated

ln = represents the natural logarithm.

For technical efficiency;A Cobb Douglas Stochastic Frontier Production Function was also used

through maximum likelihood estimate approach to determine the technical efficiency of the

cocoyam farmers for both gender.

Cobb-Douglas functional form is given by:

ln y = β0 + β1lnx1 + β21nx2 + β3lnx3 + β4lnx4 + β5lnx5 + vi - ui (3.5)

Y = total farm output of cocoyam (kg/ha)

ln = the natural logarithm

β0 – β5 = parameter to be estimated.

= fertilizer (kg)

= capital inputs (N) (depreciation changes on farm machinery, implements and tools,

interest on loan, land rent).

=labour (mandays)

= farm size (ha) other inputs (N) planting materials and other expenses like

=cocoyam sett.

vi = independency and identically distributed random error

ui = Random error associated with technical inefficiency in production.

Farm socio-economical and farm specific factor were determined using.

Exp (-u) = β0 + β1z1 + β2z2 + β3z3 + β4z4 + β5z5 + β6z6 + β7z7 + β8z8 + β9z 9 + vi – ui (3.6)

Where

Exp (-U1) = technical efficiency of the ith farm

Z1 = marital status

Z2 = age of farm in years

Z3 = Household size

Z4 = level of production in years of schooling

3x

oB

isB

1x

2x

3x

4x

5x

Z5 = farming experience in years

Z6 = extension contact (no of times)

Z7 = member of co-operative society

Z8 = farm size

Z9 = Access to credit

Vi = independently and identically distributed error

Ui = random error associated with technical inefficiency in product intercept

β 1 - β 9 = Parameters to be estimated

Allocative efficiency, was determined by equating the marginal value product (MVP) of the ith

input to its price or marginal factor cost (MFC) that is

MVPx1 = Px1 ……… (3.7)

MVPx1 (I = 1,2…….5) = the marginal value product of the ith

input = Py fx

PX1 (i = 1,2 -------- 5) = the marginal value product of the ith

input

Py = unit price of output

According to Okoruwa and Ogundele (2008), for all the resources measured in physical terms, the

allocative efficiency index, Wij, for each farmer type is given

MVPx1 = Pyf1 = Wij

As Px1 Px1 ------------- (3.8)

Where i, is a particular resource, j is the farmer group and all other variable are as previously

defined for any resource that will be measured in monetary or value terms, the unit input price

becomes irrelevant and equation 5 translate to:

MVPx = PyF1 = Wij = (3.9). In this study, the dependent variable y will be measured in

physical terms while other inputs and capital inputs will be measured in value on monetary terms.

Accordingly, the MVP of the resources measured in value terms are directly equal to their

allocative efficiency indices. This is because the marginal value products were already deflated

factor prices since the value of factor are the products of the quantity employed and the unit factor

prices. Maximum or absolute allocative efficiency for a particular farmer group is confirmed with

respect to a given resources. If wij = 1. The resources is over-utilized if Wij < 1 and under-

utilized if Wij > 1.

Returns to scale of the male and female cocoyam farmers was derived through the

summation of the elasticity of production (EP) for the various resources. With the double log

functional form as the lead equations for the men and women cocoyam farmers, the regression

coefficients are directly the elasticity of production.

Objective (v) was realized using cost and return analysis This Gross Margin is given by Gm =

GFI – TVC

Where;

GM = Gross margin (N/ha)

GFI = Gross farm income (N/ha)

TVC = Total variable cost (N/ha)

And Return Per Naira Invested is given by

RNI = TVGM ÷

Where:

GM = Gross Margin

TVC = Total Variable Cost.

3.5 Hypotheses

(1) Age is significant and negatively related to technical efficiency

(2) Marital status, House hold size, Education, Farming Experience, Extension contacts, Co-

operative society, Farm Size and Access to credit are significant and positively related to

technical efficiency.

(3) There is no significant difference in allocative efficiency of the cocoyam farmers in the use of

farm resources by gender.

(4) There is no significant difference in output of cocoyam across gender.

CHAPTER FOUR

RESULTS AND DISCUSSION

4.1 SOCIO-ECONOMIC CHARACTERISTICS OF THE RESPONDENTS BY GENDER.

4.1.1Marital Status

Table 4.1 shows that 74% and 72.93% of the male and female farmers respectively were

married while only 26% and 27.27% of the male and female farmer were single. This implies that

the area was dominated by cocoyam farmers who were married.

4.1.2Age

Table 4.1 indicates that only 8% and 8.18% of the male and female farmers were less than

31 years of age. Further results showed that 46% and 60.35% of the male and female farmers fell

within the age range of 31-50yrs. Also 46% and 26.36% of the male female farmers were more

than 50yrs of age. This implies that the study area was dominated by farmers who are still in their

most productive years, strong and agile. Nwaru (2004), Ndukwu et al (2010) and Dimelu et al

(2009) found out that the ability of a farmer to bear risk, be innovative and be able to do manual

work decreased with age.

4.1.3 House Hold Size

Table 4.1 depicts that 40% and 62.73% of the male and female farmers respectively had

households of 1-5 persons while 52% and 37.27% of the male and female farmers respectively

had households of 6-10 persons. Only 2% of the male farmers had households greater than 10

persons. Effiong (2005), Idiong (2005) and Dimelu et al (2009) reported that a relatively large

household size enhanced the availability of labour.

4.1.4 Education

Table 4.1 shows that only 4% and 4.54% of the male and female farmers respectively had

no form of formal schooling. The result also show that 54% and 45.45% of the male and female

farmers respectively attended primary level of education. About 38% and 46.34% of the male and

female farmers respectively attended secondary level education. Only 4% and 3.64% of the male

and female farmers respectively attended tertiary level of education. The finding indicates that

relatively literate farmers dominated the study area. Educated farmers are expected to be more

receptive to improved farming techniques, while farmers with low level of education or without

education would be less receptive to improved farming techniques (Okoye et al; 2007;Okoye and

Onyenweaku, 2007 and Ajibefun and Aderinola, 2004).

4.1.5 Farming Experience

The data in table 4.1 shows that only 18% and 13.64% of the male and female farmers

respectively had 1-5years of farming experience. Also the results showed that 48% and 51.81% of

the male and female farmers had between 6-15yrs of farming experience each. Further studies

showed that 34% and 34.54% of the male and female farmers respectively had more than 15yrs of

farming experience. This implies that the study area was dominated by experienced farmers.

Nwaru, (1993), Dimelu et al (2009) and Okoye et al (2008) reported that farmers count more on

their experience than educational attainment in order to increase in their productivity.

4.1.6 Extension Contact

The data in table 4.1 shows that 20% and 18.18% of the male and female farmers

respectively had no form of contact with extension. More so 62% and 66.35% of the male and

female farmers respectively had 1-4 number of extension contacts. Further studies indicated that

4% and 2.73% of the male and female farmers had respectively had 5-6 number of extension

contacts while 6% and 12.73% had more than 6 extension contacts for the male and female

farmers respectively. Good extension programmers and contacts with producers are key factor in

technology dissemination and adoption (Bonabana-Wabbi, 2002).

4.1.7 Membership of Cooperatives

The data in table 4.1 indicates that 52% of the farmers belonged in one form of social

organization or the other while 48% of male did not. The implication of the result is that the

females are likely to have more access to agriculture, information and production input

(Onyenwaku and Nwaru 2005). Acquisition of information about a new technology demystifies it

and makes it more available to farmers (Bonabana-wabbi, 2002). Information reduces the

uncertainty about technology’s performance hence may change individual’s assessment from

purely subjective to objective over time

4.1.8 Farm Size

The data in table 4.1 showed that 86% and 74.54% of the male and female farmers

respectively owned between 0.1-0.6ha of land. The results also show that 14% and 25.45% of the

male and female farmers respectively owned between 0.7-1 ha of land. This implies that the areas

were dominated by small-holder farmer. Farm size can also encourage farmers to intensify

agricultural production.Hazarika and Subramanian (1999) are of the opinion that if farm size is

small, farmers are able to combine their resources better.

4.1.9 Income.

The result in table 4.1 showed that 4% and 5.45% of the male and female farmers

respectively had an income less than N21,000. Further results showed that 24% and 27% of the

male and female farmers respectively also had between N21,000 – N40,000 only, The result also

shows that 4%, 28% and 10% of the male farmers had between N41,000 – N60,000, N61,000 –

N80,000 and N81,000 – N100,000 respectively in the study area. The result also shows that

2.73%, 25.45% and 33.64% of the female farmers had between N41, 000 – N60, 000, N61, 000 –

N80, 000 and N81, 000 – N100, 000 respectively. The high income cocoyam production by the

female farmers may be as a result of the years of experience spent in cocoyam production. This is

in consonance with Okoye et al (2008) who have similar view.

Table 4.1: Distribution of Male and Female Cocoyam Farmers According to Socio-Economics

Characteristics. ______________________________________________________________________

Male Female ________________________________________________________________________

Variable Frequency Percentage Frequency percentage

________________________________________________________________________

Marital status

Married 37 26.00 80 72.73

Single 14 74.00 30 27.27

________________________________________________________________________

Total 50 100.00 110 100.00

Mean 0.74 0.73

________________________________________________________________________

Age

< 31 04 08.00 08 8.18

31-40 07 14.00 27 24.45

41-50 16 32.00 45 40.90

51-60 08 18.00 17 15.45

>60 14 28.00 12 10.95

________________________________________________________________________

Total 50 100.00 110 100.00

Mean 50.94 46.16

________________________________________________________________________

Family Size

1-5 23 46.00 69 62.73

6-10 26 52.00 41 37.27

>10 01 2.00 - -

________________________________________________________________________

Total 50 100.00 110 100.00

Mean 5.38 4.98

________________________________________________________________________

Education

No Schooling 02 4.00 05 4.54

Primary 27 54.00 50 45.45

Secondary 19 38.00 51 46.34

Tertiary 02 4.00 04 3.64

________________________________________________________________________

Total 50 100.00 110 100.00

Mean 7.68 7.40

_________________________________________________________________________

Farming Exp. 1-5 yrs 09 18.00 15 13.64

6-10 yrs 20 40.00 40 36.36

11-15 yrs 04 8.00 17 15.45

>15 yrs 17 34.00 38 34.54

________________________________________________________________________

Total 50 100.00 110 100.00

Mean 14.08 13.51

________________________________________________________________________

Ext Contact None 14 28 20 18.18

1-2 21 42 56 50.90

3-4 10 20 17 15.45

5-6 02 4 03 2.73

>6 03 6 14 12.73

__________________________________________________________________________

Total 50 100.00 110 100.00

Mean 2.14 3.35

__________________________________________________________________________

Cooperative Yes 26 52 54 49.09

No 24 48.00 56 50.91

____________________________________________________________________________

Total 50 100.00 110 100.00

Mean 0.52 0.49 _____________________________________________________________________________

Farm Size(ha) 0.1-03 13 26.00 21 19.09

0.4-06 30 60.00 61 55.45

0.7-0.9 05 10.00 16 14.54

1ha 02 4.00 12 10.91

______________________________________________________________________________

Total 50 100.00 110 100.00

Mean 0.49 0.54

______________________________________________________________________________

Income(N)

<21,000 02 4.00 06 5.45

21,000-40,000 12 24.00 19 17.27

41,000-60,000 02 4.00 03 2.73

61,000-80,000 14 28.00 28 25.45

81,000-100,000 19 10.00 37 33.64

______________________________________________________________________________ Total 50 100.00 110 100.00

Mean 72,430 83,100

________________________________________________________________________________________________

Source; Field Survey, 2011

4.2 COMPARISON OF MEAN OUTPUT OF MALE AND FEMALE COCOYAM FARMERS.

Table 4.2. shows that the mean outputs of male and female farmers were 2,450.2kg and

2519.091kg respectively. The mean output of the female cocoyam farmers was higher than that of

their male counterparts. This could be as a result of their higher experience in cocoyam

production. A t-value of -0.4065 indicates that there is no significant differences between the

male and female cocoyam outputs in the study area. Therefore policies that would enable the

women to remain in cocoyam production should be put in place. Such policies should equally

enable the male farmers to improve on their productivity .

Table 4.2. Two sample T-test of cocoyam output by gender

________________________________________________________________________

Variable Obs Mean output/kg Std.Error Std Devi t P> t

______________________________________________________________________

Men 50 2450.2 129.1907 913.5164 -0.4065 0.6849

Women 110 2519.091 97.9770 1027.6

_________________________________________________________________________

Source field survey, 2011

4.3 ESTIMATION OF TECHNICAL AND ALLOCATIVE EFFICIENCY IN COCOYAM PRODUCTION.

4.3.1 Technical Efficiency

Table 4.3 shows the maximum likelihood estimates of the stochastic production frontier

function for male and female farmers in Anambra State. The coefficients for fertilizer were

positive and significant at 10% and 5% levels of probability for the male and female farmers

respectively. The coefficients of cocoyam setts were also positive and significant at 5% and 1%

levels of probability for the male and female farmers respectively. The results also showed that

the coefficients for labour were positive and significant at 10% level of probability for the male

and female farmers respectively. The coefficient for capital input was also positive and significant

at 1% level of probability for the male farmers only while the coefficient was not significant for

the female counterparts. These results are expected and in accordance with apriori expectation.

Any increase in these variables will lead to a corresponding increase in cocoyam output. The

coefficients for farm size were positive but not significant. This goes contrary to (Kaldjian, 2001)

who stated that small farmers “ having all ones land in a single soil type, in a small location and

single exposure is considered risky. The coefficient for extension contacts for both gender were

not significant and negative too. The coefficient for membership of cooperatives for both gender

were not significant but negative and positive for male and female cocoyam farmers respectively.

The coefficient for Access to credit was not significant but negative and positive for the male and

female cocoyam farmers respectively. The estimated variance (r2 ) was statistically significant at

10% and 1% levels of probability for the male and female farmers respectively. This indicates

goodness of fit. The gamma (γ) is estimated at 0.77 and 0.97 for the male and female farmers

respectively and is significant at 5% and 1% level of significant respectively. This indicates that

77%and 97% of the total variation in cocoyam output for the male and female farmers

respectively was due to technical inefficiencies.

Table 4.3: Maximum Likelihood Estimates of the Cobb-Douglas Stochastic Production function for

male and female farmers in Anambra State. ______________________________________________________________________________________

_____________________________________________________________________________________________________

Source: computed from frontier 4.1 MLS/survey data 2011 *,**,***, is significant at 10%,5%,1% level of significance

Figures in parenthesis are t - values

Production Factors _________________________________________

Parameter ____________

Coefficient

_____________________________________

Males Females Constant term Β0 8.6229

(7.4599)***

6.6324

(12.3883)***

Fertilizer used(kg) Β1 0.2159

(2.5366)**

0.1589

(2.5352)**

Capital(N) Β2 0.3704

(4.1169)***

0.0264

(0.5182)

Labour (mandays) Β3 0.1309

(7.2523)***

0.4288

(11.4957)***

Farm size(Ha) Β4 0.2332

(1.4143)

-0.0942

(-0.7822)

Cocoyam sett (kg) Β5 0.0425

(2.6354)**

0.0511

(4.3486)***

Efficiency factors

Constant term Z0 2.5064

(1.8274)*

-0.3649

(-0.4879)

Marital status Z1 -0.0373

(-1.0209)

0.0236

(1.2930)

Age(yrs) Z2 -0.0579

(-1.7091)*

-0.0374

(-1.8416)***

Household size Z3 0.1940

(1.8615)*

0.0226

(1.2401)

Education(yrs) Z4 0.0362

(2.8928)**

0.03098

(3.0303)***

Farming experience (yrs) Z5 0.0332

(6.9864)***

0.0537

(3.6457)***

Extension Contacts(Nos) Z6 -1.0072

(-0.8209)

-0.0070

(-0.4113)

Membership of coop Soc Z7 -0.0016

(-0.0030)

0.2047

(0.5505)

Farm Size Z8 -0.0369

(-2.5783)**

-0.5505

(-3.2829)***

Access to Credit

Z9

-0.2406

(-0.7997)

0.1864

(0.5772)

Sigma squared Γ2 0.3169

(2.0387)*

0.6044

(4.8789)***

Gamma Γ 0.7752

(2.8361)**

0.9733

(51.3708)

Log likelihood function N -30.4007 18.7118

4.3.1.1 Determinants of Technical Efficiency

The determinants of technical efficiency are presented in table 4.3. The coefficients of age

for male and female farmers were negative and significant at 10% and 1% level of probability

respectively. This means that any increase in age will lead to a decrease in efficiency. This result

agrees with Okoye et al (2007) and Okoye et al (2008) who found out that ageing farmers would

be less energetic to work. The coefficients of households’ size for male farmers were positive and

significant at 10% level of probability. This shows that male headed household with large family

size are likely to be more technically efficient than their counterparts with smaller family size.

Large household size is a source of labour for most farm operations, as noted by Effiong and

Idiong (2005).

The coefficients of education for male and female farmers were positive and significant at

5% and 1% levels of probability. This implies that increase in education will lead to increase in

technical efficiency, ceteris paribus. Education might be regarded as a factor for increased

efficiency, this agrees with Kadurumba et al, (2010). The coefficients for farming experience

were positive and significant at 1% level of probability. This agrees with apriori expectations that

increase in years leads to increase in technical efficiency. This also agrees with Okoye et al,

(2007); and Onyenweaku and Nwaru, (2005) who found out that farming experience had a direct

relationship with technical efficiency. The coefficients of farm size were negative and significant

at 5% and 1% level of probability for the male and female farmers respectively. This indicates

that increases in farm size will lead to decrease in technical efficiency and agrees with Hazarika

and Subramanian (1990) who found out that if farm size is small, farmers are able to combine

their resources efficiently. However, whether this relationship will follow in all cases, and at what

farm size threshold reversals might occur is not known.

4.3.2. Allocative Efficiency.

Regression result of allocative efficiency for male and female cocoyam farmers Linear,

exponential, semi-log and Cobb Douglas functional forms were fitted to the data and the results of

analysis are presented in tables 4.4 and 4.5 for male and female farmers respectively. The Cobb -

douglas functional form was chosen as the lead equation for the two estimates based on the

number of significant variables and extent of realization of apriori expectations for the farmers.

The R2 values for male and female farmers were 0.9910 and 0.8546 respectively. This implies

99.10% and 85.46% variability in cocoyam output for the male and female farmers respectively

were explained by the independent variables. The t values were also highly significant at 1% level

of probability indicating goodness of fit of the regression line. The coefficients for farm size were

significant at 10% and 5% levels of probability for the male and female farmers respectively. This

is in agreement with apriori expectation. The coefficients for fertilizer were positive and

significant at 10% and 5% levels of probability for the male and female farmers respectively. This

implies that any increase in fertilizer application will lead to a corresponding increase in output.

This also expected. The coefficients for cocoyam setts were also positive and significant at 1%

level of probability and imply that any increase in planting material will increase output. The

coefficients for depreciation in capital items were positive and significant at 10% and 5% for the

male and female farmers respectively.

This implies that any increase in capital items will lead to a corresponding increase in

cocoyam output. The coefficients for labour of male and female farmers were positive and

significant at 10% level of probability and indicate that any increase in labour will lead to a

corresponding increase in output. The coefficients of labour for female farmers were positive but

not significant.

Table 4.4 Results of Multiple Regression Analysis of Male Cocoyam Farmers

Factors Linear Exponential Cobb Douglas+ Semi Log

______________________________________________________________________________________

Constant - 98633 9.30459 -7.40110 -420937

(-13.92)*** (151.39) (-14.53)*** (-4.02)***

Fertilizer 132.2014 -0.00135 0.05573 12483

(2.14)* (-2.52)* (2.43)* (2.21)*

Capital -11.6797 0.00008484 0.11061 32496

(-3.8)** (2.66)* (3.26)** (4.07)*

Labour -0.3152 0.00000379 0.04291 -6739.40389

(-1.34) (1.86)* (2.59)** (-0.76)

Farm Size -21.6231 0.00015312 0.18397 34.925

(-2.19)* (1.79)* (1.93)* (1.45)

Cocoyam Setts 5512.79263 0.04024 0.03924 271262

(32.32)*** (27.19)*** (26.02)** (14.82)***

______________________________________________________________________________________

R2 0.9832 0.9858 0.9910 0.9534

F 339.46*** 403.92*** 525.69*** 98.17***

Source: field survey 2011

+ lead equation.

*,**,*** is significant at 10%,5%,1% level of probability

Figures in parenthesis are t - values

Table 4.5 Results of Multiple Regression Analysis of Female Cocoyam farmers.

________________________________________________________________________

Factors Linear Exponential Cobb Douglas+ Semi Log

______________________________________________________________________________________

Constant -163421 9.70209 6.83014 278821

(-13.72)*** (129.73) (8.26)*** (2.09)***

Fertilizer 134.10153 -0.00055453 0.01008 -237.57436

(1.23) (-0.81) (2.78)** (-0.04)

Capital -2.14937 0.00001202 0.15264 -27120

(-4.28)*** (3.81)*** (3.42)* (3.77)***

Labour 0.685584 0.00000275 0.10310 -11503

(2.89)** (2.09)* (1.32) (-0.91)

Farm Size 2.04558 -0.00008162 0.90419 -18720

(0.12) (-.074) (2.61)** (-0.80)

Cocoyam Setts 6670.12124 0.03143 0.02869 7013.29290

(22.65)*** (17.00)*** (14.60)*** (22.13)***

______________________________________________________________________________________

R2 0.9619 0.8533 0.8546 0.8613

F 318.17 257.21 222.93*** 263.64

Source: field survey 2011

+ lead equation.

*,**,*** is significant at 10%,5%,1% level of probability

Figures in parenthesis are t - values

4.3.2.1 Estimation of Allocative Efficiency of Male and Female Cocoyam farmers

The results in table 4.6 and 4.7 show the estimated allocative efficiencies of the male and

female cocoyam farmers in Anambra State. The decision rule is that if r = 1, it implies that

resources are efficiently utilized i.e. MVP = MFC = 1, r > 1, implies that resources are under

utilized r < 1, implies that resources are over utilized. The ratios of marginal value product (MVP)

to marginal fixed cost (MFC) of male farmers shows that fertilizer, capital, labour, farm size and

cocoyam setts inputs had values of 3.08, 0.21, 0.00043, 0.0219 and 0.0039 respectively. This

result implies that none of the inputs were efficiently utilized by the male farmers. The results

further indicates that male farmers over utilized capital, labour, farm size, and cocoyam setts

while they underutilized fertilizer. The results also show the allocative efficiency values of

0.0094, 0.0107, 0.0000554, 0.1608 and 0.0001125 for fertilizer, capital, labour, farm size and

cocoyam setts for female farmers. Indicating that all the inputs were over utilized. This result

suggests that there exists the possibility of increasing output under existing level of technology

through the use of lower levels of all inputs by male and female farmers except fertilizer for male

farmers. There is also need to use higher level of fertilizer for the male farmers.

Table 4.6 Estimation of Allocative Efficiency for Male Cocoyam Farmers

Item Product Elasticity Sample Mean MVP MFC Allocative Efficiency

Indices

______________________________________________________________________________________

Fertilizer 0.05573 0.9884 138.15 44.74 3.08 (under utilization)

Capital 0.11061 1,263.70 0.21 1.00 0.21 (over utilization)

Labour 0.04291 240.14 0.43 1,000 0.00043(over utilization)

Farm Size 0.18397 0.4850 929.40 1,018.50 0.0129 (over utilization)

Cocoyam Setts 0.03924 490.04 0.1062 49.00 0.0039 (over utilization)

____________________________________________________________________________________________

Source: field survey 2011

Table 4.7 Estimation of Allocative Efficiency for Female Cocoyam Farmers

Item Product Elasticity Sample Mean MVP MFC Allocative Efficiency

Indices

______________________________________________________________________________________

Fertilizer 0.01008 2.5418 0.4362 46.65 0.0094 (over utilization)

Capital 0.15264 1,562.45 0.0107 1.00 0.0107 (over utilization)

Labour 0.10310 255.51 0.0443 800.00 0.0000554 (over utilization)

Farm Size 0.90419 0.5427 183.27 1139.73 0.1608 (over utilization)

Coco yam Setts 0.02869 503.82 0.0063 55.98 0.0001125 (over utilization)

Source: field survey 2011

4.3.2 comparison of technical efficiency of male and female cocoyam farmers

Looking at the efficiency factors in table 4.3, the coefficients for age for male and female

farmers were negative at 10% and 1% levels of probability. This means that any increase in age

will lead to a decrease in efficiency. The coefficients for farming experience were positive and

significant at 1% level of probability. This implies that any increase in farming experience is

expected to lead to increase in technical efficiency.

4.4 COMPARISON OF RETURNS TO SCALE OF THE MALE AND FEMALE FARMERS

The results in the table 4.8 show the comparison of returns to scale of the male and female

cocoyam farmers in the study area. The elasticity of production which is the measure of the

percentage change in output to percentage with respect to individual input resources used in

cocoyam production and the sum of elasticity (return to scale) which is the response of output to a

proportionate change in the inputs were estimated following Gujarati(2004) ,if this sum is 1,there

is constant return to scale, if the sum is less than 1,there are decreasing returns to scale and if the

sum is greater than 1 there are increasing returns to scale. With the double log function as the lead

equation, the regression coefficients are now automatically the elasticites found in table 4.8

.returns to scale was calculated as the sum of the individual production inputs elasticities. The

sum elasticities resulted to a value of 0.4326 and 1.1987 for the male and female farmers

respectively. This implies decreasing returns for the male farmers and increasing returns for

female farmers. Women are operating at increasing returns to scale (ΣEP>1) which implies that

they are operating in region of the total product curve which is irrational. The implication is that

they can improve on their productivity by employing more resources. This result is consistent

with the report from Nwaru and Ekumankama (2002) who reported increasing returns to scale for

women arable crop farmers but deviates from the decreasing returns to scale they reported for the

men. Also the results of increasing returns to scale are in line with Ajibefun and Aderinola

(2004). Furthermore men are producing below capacity and there is need to increase the inputs

used in production. This could be as a result of decreasing returns caused by inefficiency in inputs

utilized.

Table 4.8: Elasticities of production for Male and Female Cocoyam Farmers in the Study

Area.

________________________________________________________________________

Production Factors Male Female

________________________________________________________________________

Input Elasticity Elasticity

Fertilizer 0.05573 0.01008

Capital 0.11061 0.15264

Labour 0.04291 0.10310

Farm Size 0.18397 0.90419

Cocoyam Setts 0.03924 0.02869

_______________________________________________________________________

Σ EP 0.43246 1.1987

_______________________________________________________________________

Source: field survey 2011

4.5 COST AND RETURN ANALYSIS OF COCOYAM PRODUCTION BY GENDER.

The result in table 4.9 shows the cost and return analysis for male and female cocoyam

farmers respectively. The total cost for male and female farmers was N73, 833.17 and N

75,892.59 respectively. About N 78,509.60 and N 106,007.99 were the Gross Margin realized

from cocoyam production by the male and female farmers respectively. The net profit from the

enterprise was N 62,592.87 and N 88,378.12 for the male and female farmers respectively. For

every N 1 spent the male farmers realized N 1.85 while N 2.16 was realized by the females. This

shows that female cocoyam farmers had a higher profit margin than male cocoyam farmers which

might be as result of experience in cocoyam production; this is in line with Ewuziem et al (2010)

that farmers with longer years of farming experience tend to combine their resources better in an

optimal manner. In other words cocoyam production is a profitable enterprise in Anambra State.

Table 4.9 Cost and Return of Male and Female Cocoyam Farmers/ha

Item Male (=N=) Female (=N=)

Revenue 136,426.04 164,270.71

Variable Costs

Planting Materials 28,011.96 26,873.59

Fertilizer 4,800.20 4,736.92

Wage Bill 25,104.57 26,652.17

TVC 57,916.73 58,262.72

Fixed Costs

Depreciated Cost of Capital Inputs 13,263.70 14,691.56

20% Contingences of Fixed Cost 2,652.73 2,938.31

TFC 15,916.44 17,629.87

TC 73,833.17 75,892.59

GM 78,509.60 106,007.99

Net Profit 62,599.87 88,378.12

BCR/RNI 1.85 2.16

_________________________________________________________________________

Source: field survey, 2011

4.6 DISTRIBUTION OF MALE AND FEMALE RESPONDENTS ACCORDING TO

CONSTRAINT IN

Cocoyam Production

The Table 4.10 presents the constraints/problems facing male and female Cocoyam

farmers in Anambra State. From the table, a high percentage of the farmers, (90.00% of the male

and 90.91% of the female) identified pests and diseases as their major problem. Other problems

confronting the farmers as identified by them include poor feeder roads, lack of credit, poor

storage facilities, high cost of planting materials, lack of extension contact. The viral disease in

cocoyam production has led to a reduction in output of cocoyam. Majority (70%) of the female

respondents experienced rot and decay of cocoyam during storage and 98% of the male

respondents encountered this problem also. This agrees with findings of Nwauzor, (2001) that rot

had earlier been identified as one of the problems which militate against maximum production is

cocoyam. Attempts to solve these problems have been at the core of most agricultural, rural and

extension programmes in Nigeria, Also Breeding programmes may help to eliminate or minimize

some of these problems of rot and disease of cocoyam in storage. Storage problem received

(60%) for the male farmers and (61.81% )for the female farmers. Njoku (2008) reported that any

strategy developed for achieving sustainable crop production by Cocoyam farmers in the 21st

century must tackle the problem posed by the following inputs supply, pest and diseases, storage

facilities, production facilities and access to credits.

Table 4.10: Distribution of male and female cocoyam farmers according to problems

encountered.

Male Female

____________________________________________________________________________ Problems Frequency Percentage Frequency Percentage

Encountered

___________________________________________________________________________________________

Lack of credit 20 40 95 86.36

Root and decay during

Storage 35 70 77 70.00

High cost of planting

Materials 32 64 68 61.82

Poor Infrastructural

Facilities 48 96 79 71.82

Low soil fertility 10 20 50 45.45

Poor feeder and road 32 64 70 63.64

Poor storage facilities 30 60 68 61.81

Pest and diseases 45 90 100 91.91

Limited lands 22 44 58 52.73

High cost of labour 18 36 50 45.45

Poor Knowledge of

Technology 28 56 35 31.82

Lack of extension

Contact 19 38 29 26.36

Lack of fertilizer 32 64 30 27.27

_________________________________________________________________________________________________

Source: Field survey 2011, Multiple responses

CHAPTER FIVE

5.0 SUMMARY, RECOMMENDATION AND RECOMMENDATIONS

5.1 Summary

The study was designed to investigate the gender and resource use efficiency in cocoyam

production in Anambra State. Socio-economic characteristics of the farmers were determined as

well as the production problems affecting them. The study presents the results of analysis of data

collected on 160 cocoyam farmers ( male and female ) across the two Agricultural zones. A multi-

stage randomized sampling technique was used to select the zones, blocks, circles and contact

farmers. Descriptive statistical tools such as percentages, frequencies, means and were used in

analyzing farmer’s socio-economic characteristics and production problems. The result showed

that women constitute a greater (68.75%) percentage of cocoyam production in the state. The

maximum likelihood Estimation (MLE) technique was used in estimating the technical efficiency

and determinants of efficiency of male and female farmers using the Cobb-Douglas stochastic

function as the lead model. The result of the technical efficiency estimation showed that the

coefficients of both farmers for the production variables used were all positive. Cocoyam setts,

labour, and fertilizer use were significant while capital inputs were not significant for female

cocoyam farmers. The result indicates that socio-economic conditions influenced technical

efficiency of both farmers. The coefficients of determinants of efficiency used were all positive

except farm size that were negative and significant for both male and female cocoyam farmers

only while age, level of education, extension contact and knowledge index were all positive and

significant for male farmers while other variables were not significant.

Test of Allocative Efficiency revealed that none of the defined farmer groups achieved

absolute allocative efficiency. Male farmers under-utilized fertilizer and over-utilized other inputs

used in production while female farmers over-utilized all the input. This result suggests that there

exists the possibility of increasing output under existing level of technology through the use of

lower levels of all inputs by male and female farmers except fertilizer for males. There is also

need to use higher levels of fertilizer for the male farmers. Finally, the survey revealed that most

of the farmers (male and female) encountered problems of root rot diseases at 90% and 90.91%

respectively.

5.2 Conclusion

It could be concluded from this study that resources were poorly allocated by male and

female farmers. Farmers should be amply and properly empowered, this will enable them to

exhibit higher level of entrepreneurial capabilities, policies and programmes that could help to

increase their efficiency should be put in place. The study revealed that cocoyam farmers in

Anambra State who were predominantly women were not fully technically and allocatively

efficient in their use of resources. Farmers’ level of technical efficiency was higher than allocative

efficiencies.

All factors related to technical and allocative efficiencies call for policies aimed at

incorporation of all the significant variables, especially those that will encourage farmers of their

tendency to allocate the bulk of their landholdings to cocoyam production and those that limit

women’s access to production inputs. The promotion of cocoyam cultivation as well as

encouraging of new entrants would also be a key component in government policy strategy of

cocoyam growth. This would raise the level of technical and allocative efficiencies and hence the

level of productivity.

5.3 Policy Implications and Recommendations

Given the input requirements for cocoyam production, improving farmers’ efficiency both

technically and allocatively would be a necessary step towards allocating more widespread

resources in cocoyam production.

(1) The study showed that rising age would lead to decline in the efficiency of farmers,

Government policy should focus on ways of attracting and encouraging the youths who are agile

and strong. This group of people would be able to put in a lot of efforts at raising the current level

of efficiency, given conducive policy environment.

(2) The study revealed that increase in farm size would lead to a decline in efficiency. The finding

suggests that government policy should concentrate on how to encourage new entrants to

cocoyam production and not necessarily increased farm size. The government could encourage

that trend by removing policies and distortions that favour large farms over small farms.

(3) The high percentage of the aged, most of who were illiterates but had to rely on their many

years of experience affected the productivity of cocoyam in the study area. Government policy on

encouraging the youths to take to cocoyam production should have a multifaceted approach and

an adequate program on education and extension services.

(4) Government should enact policies that would encourage experienced farmers to remain in

farming as well as decreasing further the current fertilizer subsidy level while the fertilizer

distribution network should be completely over hauled

(5) Policies to reduce inflation and enhance subsidies in the form of cheap credit should be

strengthened. This will assists farmers in acquiring the resource inputs as at when due since most

operations in the farm are time bound

(6) Since it has been confirmed that women dominate the production process, women’s access to

production inputs should be increased.

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APPENDIX 1

Table 1.1: Estimated Outputs of Major Agric Commodities (000 tonnes)

Item 2004 2003 2002 2001 2000

________________________________________________________________________

Cocoyam 3,500 3,500 3,929 3,886 3,385

Yam 27,000 27,000 26,849 26,201 25,873

Cassava 33,379 33,379 34,479 32,010 32,010

Potatoes 2,150 2,150 2,503 2,468 2,473

________________________________________________________________________

Source: FAO Statistics, 2005