TITLE                                                                                                                         i

CERTIFICATION                                                                                                     ii

ABSTRACT                                                                                                               iii

DEDICATION                                                                                                           iv

ACKNOWLEDGEMENT                                                                                         v

TABLE OF CONTENTS                                                                                           vii

LIST OF TABLES                                                                                                     xi

LIST OF FIGURES                                                                                                   xiii

LIST OF APPENDICES                                                                                           xiv

CHAPTER ONE: INTRODUCTION                                                                                   1

  • Background Information of the Study 1
  • Problem Statement 4
  • Objectives of the Study 8
  • Research Hypothesis 9
  • Justification of the Study 9
  • Limitations of the Study 12
  • Plan of the Report 13

CHAPTER TWO: LITERATURE REVIEW                                                                        15

  • Morphological Description of Cassava 16
  • Cassava Production in the World 17
  • Advances in Root and Tuber Crop Production Technology 19
  • The Potential Economic Importance of Cassava 23
  • Farming Systems Adopted in Cassava Production 28
  • Farming Conditions of the Small-Holder Farmer 30
  • Efficiency of Resource Use by Cassava Farmers 31
  • Economics of Cassava Production and Marketing 36
  • Conceptual and Empirical Framework 38

2.10 Theoretical and Analytical Framework                                                               42

2.10.1 Tobit Model                                                                                         47

  • Efficiency Measures 49
    • Allocative Efficiency 50
    • Economic Efficiency 50
    • Profit Frontiers 51
    • Stochastic Frontier Production Function 51

CHAPTER THREE: RESEARCH METHODOLOGY                                           54

  • Description of the Study Area 54
  • Sampling Procedure 58
  • Data Collection 59
  • Data Analysis 59
  • Model Specification 60
  1. Technical Efficiency             60
  2. Inefficiency Model                                                                         61
  3. Tobit Model 63
  4. Normalized Profit Function 66

CHAPTER FOUR: RESULTS AND DISCUSSION                                                           68

  • Socio-Economic Characteristics of Respondents 68
    • Age of the Farmers 68
    • Gender Participation 70
    • Household Size 71
    • Farming Experience 73
    • Level of Educational Attainment of Respondents 74
    • Occupational Distribution of the Respondents                                 75
  • Farming Systems and Cassava Production in Abia state 77
    • Cropping System 77
    • Calendar of Farm Operations 78
    • Household Farm Holdings 81
    • Livestock Production in Abia state 82
    • Size of Cassava Farm 83
  • Cost Implications and Returns to Cassava Enterprise 84
    • Analysis of Costs and Returns ( Profitability Index ) 87
  • Estimation of Technical Efficiency 89
    • Determinants of Technical Efficiency 94
    • Elasticity of Production and Returns to Scale 97
    • Technical Efficiency Estimate of Cassava Farmers in Abia-State 98
  • Estimation of Economic Efficiency 99
    • Determinants of Economic Efficiency (Profitability) for Cassava

Production in Abia-State                                                                    103

  • Economic Efficiency Estimate of Cassava Farmers in Abia-State                                                                                                             105
  • Test of Hypothesis for Technical and Economic Efficiency of Cassava

Farmers in Abia-State using Generalized Likelihood Ratio (LR)          106


  • Estimation of the Factors that Influence Technology Adoption Rate and Use

Intensity                                                                                                          107

  • Constraints to Increased Cassava Production in the Study Area 110


  • Summary 113
  • Conclusion 115
  • Recommendations 117
  • Suggestions for Further Research 119

REFERENCES                                                                                                          121

APPENDICES                                                                                                           133



Table:                                                                                                                                      Page

4.1   Frequency Distribution of Respondents According to Age                                           68

4.2   Frequency Distribution of Respondents According to Gender                                      70

4.3   Frequency Distribution of Respondents According to Household Size                                    72

4.4   Frequency Distribution of Respondents According to Farming Experience                  73

4.5   Frequency Distribution of Respondents According to Level of Formal

Education Attained                                                                                                         74

4.6   Frequency Distribution of Respondents According to their Primary Occupation         76

4.7   Frequency Distribution of Respondents According to their Total Farm Holding          82

4.8   Frequency Distribution of Respondents According to their Cassava Farm Size           83

4.9   Results of Budgetary Analysis per Hectare of Cassava Enterprise                                86

4.10 Maximum Likelihood Estimates of the Cobb-Douglas Stochastic Production

Function   (Technical)                                                                                                     91

4.11 Maximum Likelihood Estimate of the Translog Stochastic Production Function

(Technical)                                                                                                                      92

4.12 Elasticity and Returns to Scale for Cassava Production (Technical)                              97

4.13 Frequency Distribution of Technical Efficiency Indices                                                98

4.14 Maximum Likelihood Estimate of the Stochastic Cobb-Douglas Cost function for

Cassava Farmers                                                                                                             100

4.15 Maximum Likelihood Estimate of the Translog Stochastic Cost Function for

Cassava Farmers                                                                                                             101

4.16 Frequency Distribution of Economic Efficiency Indices                                               105

4.17 Test of Hypothesis that Cassava Farmers in Abia-State are Fully Technically and

Economically Efficient                                                                                                  106

4.18 Tobit Model Estimates of Factors Affecting Adoption Rate and Use Intensity of

Cassava Production Technologies                                                                                 107

4.19 Frequency Distribution of the Respondents According to the Constraints they faced

in the Survey Year                                                                                                          111




Figure:                                                                                                                       Page

  • Location of Abia State in Nigeria                                                                     56

3.2     Map of Abia State showing all the 17 Local Government Areas                     57

4.1     Calendar of Farm Operations for Cassava Enterprise in Abia-State                78











Appendix:                                                                                                                              Page

  1. Letter to the Sampled Farmers / Respondents            133
  2. Questionnaire Design for the Cassava Farmers 134
  • Computer print-out of Output from the Program Frontier 4.1c (Technical)             148
  1. Computer print-out of Output from the Program Frontier 4.1c (Economic)             161
  2. Computer print-out of Tobit Estimate with Stata 8.2 (Statistics/Data Analysis) 173




  • Background Information of the Study

Cassava, (Manihot esculentum crantz), belongs to the family of euphorbiaceae. It is believed that the crop originated from Brazil and was introduced to West Africa by the Portuguese traders. It exists in many cultivars which can be distinguished by size, colour, shape of the leaf, branching habit, plant height, colour of the stem, root shape, size and colour, maturity time of the root and level of hydrocyanic content (Anyanwu, 2006). Cassava is Africa’s food insurance crop with stable yield, even with low rainfall, low fertility and low inputs (FAO, 2008). Cassava is becoming an important industrial raw material and a foreign exchange earner. Cassava’s role as food security crop as well as a cash crop is receiving high attention for poverty alleviation by the developing world and partners (FAO, 2008).

Cassava is ranked the 6th most important crop in the world in terms of area planted and production (FAO, 1986). Africa is the highest cassava producer in the world, and more than 100 million people in tropical Africa depend on it as their dietary staple (FAO, 2008). Globally, among the world’s producing regions, West Africa is known to have the greatest share of the world’s production of cassava (FAO, 2008). Interestingly, Nigeria is the largest world producer of cassava with yearly production of fresh tubers estimated at 10-13 million tons on a land area of 1.2-1.4 million hectares (NAQAS, 2002). Nigeria’s lead on cassava production in the world has been achieved through expansion of land areas devoted to cassava cultivation (Ano, 2003). Of Africa’s 72.7 million tons of cassava output in 1990, 26 million tons were produced in Nigeria (Ezedinma, 2003). Cassava is widely grown in Nigeria. For decades, cassava has been cultivated as a subsistence crop in Nigeria. Currently, cassava cultivation has become an income generating activity. This “enhanced” status is as a result of increased demand for cassava and cassava products outside the rural communities (Ikpi et al 1986), as well as the realization of the potentials it has for contributing to the attainment of self-sufficiency in food production (Kwatia, 1980).

Cassava plays a major role in Nigeria’s food security and 80% of the inhabitants in the rural areas eat cassava meal at least once a day (Ezedinma, 2003). The crop is also a good source of raw materials involved in the production of confectioneries, animal feed, alcohol, adhesives, flour starch, etc. The growth of cassava as a major economic and food security crop over the last two decades has generated significant research interest at both the National and International levels. For instance, the International Institute for Tropical Agriculture (IITA), Ibadan and the National Root Crops Research Institute, (NRCRI), Umudike have developed the Tropical Manihot Selection (TMS) 30555, 30572, 30211, 50395, 60506 and Umudike (U) 41044 varieties in the early 1970’s and 1980’s. Most recently, new varieties of cassava were developed and they include, TMS 90257, 84537M, 82/00661, 30001, 81/00110, 91934, 4(2)1425, nr 41044, nr 8212, 8082, 8083, 8208, nr 83107, TMS 419, TMS 98/0581 and TMS 98/0510 (Ezulike et-al,2006). These varieties are not only high yielding, but also are resistant to pests and diseases such as Cassava Mosaic Disease, Cassava Bacteria Blight, Cassava Mealy Bug and Cassava Green Spider Mite (Ezedinma, 2003).

Cassava’s combined abilities to produce high yields under poor conditions and store its harvestable portion underground up to nine months make it a classic “food security crop. In recent years, this has proved of critical importance to many people in Africa caught up in civil conflicts and unable to cultivate the normal range of annual crops. Displaced groups of people in Mozambique during that country’s 16 years’ war often survived on abandoned cassava fields (Ezedinma, 2003). Because, it is a vegetative propagated crop, such plantings can also serve as a ready supply of planting materials during rehabilitations following conflict or drought.

Cassava is well-known for being able to grow and produce food even in very poor soils. For that reason, it is often grown at the margins of farms where the better land has been reserved for the production of grain crops. In addition, once established, cassava is relatively drought tolerant and when matured can survive up to six months without rains. Cassava’s productive capacity in low-input conditions comes at a certain cost in terms of carbohydrate quality and protein concentrations. Cassava’s ability to produce food under marginal conditions has made it a popular crop of Africa’s poor farmers who are unable to invest in fertilizer or pesticides to protect the crop against environmental stresses and biotic constraints (Ezedinma, 2006).

Although still a subject of some debate, the center of origin of cassava is generally believed to be the Southern border of the Amazon basin. Cassava was introduced in Africa in the Congo River Delta by the Portuguese in the 15th century and spread rapidly to many agro-ecologies of the continent; however, cassava is most important in farming systems of the humid forest regions where the productivity of grain crops is reduced by sunlight, foliar pests and diseases and grain storage is more difficult. Cassava has very high yield potential, making it a viable alternative to grain crops where population pressures have led to trade-off between good quality and quantity (NAQAS 2002).

Commercial cassava yields as high as 20 metric tons per hectare have been registered under experimental conditions. Nigeria is presently the largest cassava producing country in the world (FAO, 2008).

Presently, cassava production is in the hands of small-holder farmers who rely predominantly on simple tools like the hoe and cutlass powered by human effort. In 2002, the Government of Nigeria launched a presidential initiative on cassava. The aim of the initiative was to develop cassava as the engine of growth and diversify Nigeria’s economic base away from its principal export-crude oil. If investments in the downstream sector of the cassava industry are made more effective, cassava can be used to improve rural and urban income and employment in Nigeria (Ezedinma and Okechukwu, 2007). But the initiative will be threatened if no substantial effort is made to improve the current production systems. The requirements of consistent supply of large volumes of fresh roots by cassava-based industries cannot be supported by the current production systems. The critical constraints, however under such production systems is labour cost which lies between 70 and 90% of total variable cost of production (Ezedinma, 2000 and Okorji , 1985) in small holder farming.

  • Problem Statement

Cassava is one of the major root crops in Abia state and following the presidential initiative on cassava in 2002, there has been an increased awareness and demand for the crop in the state till date (ABSG, 2006). This pre-supposes that increased land area will be put into cultivation. Onyenweaku and Okoye (2005), noted that cassava production in Abia state no longer keep pace with demand, in spite of the high potential for increasing its production by expanding the area under cultivation. Ezebuiro et al (2008) observed that Abia cassava farmers are peasants and are poorly endowed in terms of resources; yet they account for the production of up to 95% or more of food produced for consumption in the state. The inadequate use of improved inputs consequent upon the low resource endowment of the Abia cassava peasant farmers has made Abia agriculture to remain at the rudimentary and traditional level. The implication is increased drudgery and reduction in output. This might not be unconnected with the level of cassava farmer’s efficiencies (technical, economic and allocative). A fundamental requirement for correcting this problem is only through improvement in productivity of cassava farmer’s. In this context, technical and economic efficiency in the production of the crop is of paramount importance.

Available statistics show that despite increases in awareness and demand for cassava in Abia state consequent upon the presidential initiative, the objectives of sustainability has remained a mirage as its production has not kept pace with demand (Onyenweaku and Okoye, 2005). Given that cassava is an important staple food in Abia state, any attempt to increase its production and the farmers’ productivity would be a right step towards the resolution of the food crisis. Considering the recent increasing trend of demand for cassava cuttings (Onyenweaku and Okoye, 2005) it is envisaged that farmers may have adopted improved varieties and other technologies to strengthen their economic base. Furthermore, their adoption could depend on the yields realized by the farmers. Actually, farmers place a high value on maximum food security, psychological and/or cultural satisfaction. It is a known fact that it is primarily because of the poor resource base that the small-scale farmers are slower in adoption than the large-scale farmers.

Again, most studies on adoption of cassava technologies in Abia-state are based on potential adopter’s decision about whether or not to adopt an innovation and where the adoption variable is specified in binary form; 1, if he or she adopts, O, otherwise (Akinola and Young, 1991). The implication is that the chosen methodology provided no information on the intensity of use after adoption. It is therefore imperative to specify a model that permits a discrete and continuous dependent variable which will capture the simultaneous nature of the decision making process of potential adopters using the Tobit model instead of the usual probit and/or Logit models.

Most studies also show that aggregate food production in Nigeria has been growing at about 2.5% per annum in recent years. But the annual rate of population has been as high as 2.9% (Olayemi, 1998). The reality is that Nigeria has not been able to attain self-sufficiency in food production; more especially with regards to cassava production despite increasing land area put into food production annually. With recent presidential initiative on increased cassava production with a view to exporting garri and the realization that cassava could be used in bread production, Abia-state has witnessed an increase in hectares of land devoted to cassava cultivation (Abia brief, 2006).

Global cassava production reached over 160 million tons in 1991 and FAO (2003) forecast that production will rise to nearly 210 million tons by 2005. On average, farmers produce less than 10 tons of cassava per hectare in Nigeria; but high yielding varieties, improved pest and disease control and better processing methods could increase production by 150% (FAO, 2006). Traditionally, cassava has been a crop of the poor and expanding its production and market can bring direct economic benefits to farmers. It has been observed that peasant farmers in Africa usually control fewer productive resources compared with their counterparts in Europe and North America, with attendant low output of cassava (Johnson, 1982).

McNamara (1990), reported that although Sub-Saharan Africa’s food production has grown over the last three decades by about 2% a year, it has not actually kept pace with a population growth rate of about 2.8%. According to him, the current population which is estimated at 540 million is expanding at a rate of about 3.1% per year and that the region’s population could reach 1.6 billion by the year 2020. More still, as the region’s population has grown, the amount of arable land available per person has declined from an average of 0.5ha in 1965 to 0.3ha in 1987, he concluded. Ugboaja (2008), reported also that available land for cassava production in Abia state has consistently declined as a result of increased population growth. The implication is reduction in output. This low output, in spite of increasing trend of demand for cassava and availability of resources, improved varieties and technologies could be related to the profitability of cassava enterprise.

It is essential to understand the socio-economic and demographic factors that play leading role in the production process of cassava in order to achieve maximum outputs in Abia state. Generation of such information is critical in focusing programmes, in developing long term research policies and in understanding the subsistence farming situation. Therefore based on the aforementioned, this study would examine the economics of cassava production in Abia state. This would be with a view to identifying and quantifying social and economic factors affecting production; evaluating how resources could be deployed to increase resource efficiency, productivity, profitability of the enterprise and increased adoption of the innovations available in the multi-cropping system of subsistence producers in the humid rainforest ecology of South-Eastern Nigeria, with particular reference to Abia state.

  • Objectives of the Study

The broad objective of this research is to study the economics of cassava production in Abia state, Nigeria.

The specific objectives are to;

  • describe socio-economic characteristics of the cassava farmers and the farming systems adopted in cassava production in Abia state,
  • estimate the cost implications and returns to cassava enterprise in Abia state,
  • estimate technical and economic efficiencies of cassava farmers’ in Abia state,
  • identify and estimate the determinants of farmers technical and economic efficiencies,
  • identify and analyze the factors that influence the rate of technology adoption and the intensity of use after adoption by the farmers in Abia state and,
  • identify the constraints to increased cassava production Abia state.


  • Research Hypotheses
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