BANANA PRODUCTION AND ITS ECONOMIC IMPORTANCE IN UGANDA

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Background

In Uganda, agriculture is the most important economic activity, providing income, employment and foreign exchange. The sector contributes 43 per cent of the gross domestic product (GDP) and 85 per cent of national export earnings. It also provides most of the raw materials for Ugandan industries (Ministry of Agriculture, Animal Industry and Fisheries [MAAIF] and Ministry of Finance, Economic Planning and Development [MFEPD], 2000). The agricultural sector is dominated by food crop production, contributing 71 per cent of the agricultural GDP. Only one third of the food crop produced is marketed, implying that the agricultural economy is still oriented towards subsistence production (MAAIF and MFEPD, 2000). Much of the agricultural output comes from about three million smallholder farmers, who constitute three-quarters of the total farming population, but a large proportion of these people live under conditions of poverty. About 48 per cent of the rural population lives below the poverty line and 25 per cent cannot even meet their daily food requirements (MAAIF and MFEPD, 2000). Given that about 85 per cent of the population live in rural areas and derive their livelihood primarily from agriculture, a strategy to develop agriculture as a stepping-stone for poverty reduction in rural areas is realistic.

Statement of the research problem

Understanding the determinants of technology adoption has long preoccupied economists concerned with the crop productivity potential in developing economies (Feder et al., 1985; Feder and Umali, 1993). The effect of both the endogenous (i.e. human capital, attitudes towards risk and uncertainty or access to financial capital) factors and the exogenous factors (i.e. agro-ecological factors or market constraints) on the adoption process has been examined. However, most of the earlier adoption studies were conducted on the green revolution technologies (i.e. improved seed and complementary inputs such as fertilizers, pesticides and mechanization) that were basically high external input technologies, introduced into the communities from external sources. After the green revolution, other than the continued releases of highyielding varieties, many of the crop management technologies recommended for small farmers in developing economies have entailed relatively low levels of external inputs. There are a number of reasons for the growing interest in these technologies, among which is their affordability to poor farmers and their environmentally nondegrading nature (Lee, 2005).

Hypotheses

Social capital in the form of social networks provides various services to individuals in developing economies. These services could link social capital to the choice and extent of use of a crop management technology through different mechanisms. Some of these mechanisms may be complementary while others are independent or offsetting. At least three services provided by social networks that may interact with a household’s technology adoption decisions can be distinguished. These are: (1) a social learning environment; (2) bilateral transfers that may relax the household’s credit or risk tolerance constraints; and (3) facilitation of collective action where coordination is needed due to technological externalities. Since no substantial technological externalities are involved in the adoption of banana production management practices, the present study focuses on the first two. Social capital, social learning effects and technology adoption In many developing economies, informal information dissemination mechanisms remain the only available source of information for many farmers. Farmers can passively or actively seek information from their neighbours or observe their neighbours’ experiments (Foster and Rosenzweig, 1995; Collier, 1998) during social interactions. Since information may come in the form of an externality, social capital reduces the cost of information accumulation and enables farmers to adopt new farming practices. The following testable hypotheses can be derived.

Organization of the dissertation

The next chapter provides a brief overview of banana production and its economic importance in Uganda and describes the characteristics of the crop management technology. Recommended production technologies are described with special mention of relevant production constraints targeted by the improved technology. The intention is to highlight the practical problems of banana production and link them with the conceptual approach of this dissertation. Chapter 3 presents a review of the theoretical and empirical literature on the adoption and diffusion of crop innovations, differentiating seed-based innovations from those related to mulching, manure application and crop sanitation for a perennial crop. The role of information and economic constraints in explaining adoption behaviour is discussed and empirical factors that influence access to information are reviewed. The chapter also highlights the key features of an agricultural household model.

The economic importance of bananas

Bananas are a major food staple of the country as well as a cash crop. The crop provides an estimated 30 per cent of the calories, ten per cent of the protein and five per cent of the fat intake of the population, representing 25 per cent of the total value of agricultural output (Kalyebara, 2002). The per capita annual consumption of bananas in Uganda is the highest in the world at approximately 0.70 kg per person per day (International Network for the Improvement of Banana and Plantain [INIBAP], 2000; National Agricultural Research Organization [NARO], 2001). Compared to other important crops in the country, banana occupies the biggest proportion of utilized agricultural land (about 1.4 million hectares or 38 per cent of the total utilized land), making it the most widely grown crop (Figure 1) and serves as one of the most important food security crops for central, western and eastern Uganda (NARO, 2001).

Banana production

The exact period when the banana crop was first introduced to Uganda is not known, but there are speculations that the crop may be as old as agriculture itself (McMaster, 1962). Since its introduction to the country, banana cultivation has steadily expanded in both acreage and popularity. For example, in 1958 the crop occupied a total area of about 485 800 hectares and supplied the main subsistence to 35 per cent of the total population (McMaster, 1962). In 2000, it was estimated that bananas occupied about 1 510 000 hectares of land (MAAIF and MFEPD, 2000), representing about 60 per cent expansion in about 40 years. At present, the crop is grown in almost every part of the country, though at varying intensities (Figure 2). Clearly visible patterns of banana growing can be observed from the south up and along the central part of Uganda (known as “the banana belt”).

READ Aims of agricultural policy implementation

TABLE OF CONTENTS :

ACKNOWLEDGEMENTS
ABSTRACT
LIST OF TABLES
LIST OF FIGURES
ACRONYMS AND ABBREVIATIONS
CHAPTER 1: INTRODUCTION
- 1.1. Background
- 1.2. Statement of the research problem
- 1.3. Objectives of the study
- 1.4. Hypotheses
- 1.5. Organization of the dissertation
CHAPTER 2: BANANA PRODUCTION AND ITS ECONOMIC IMPORTANCE IN UGANDA
- 2.1 The economic importance of bananas
- 2.2. Banana production
- 2.3 Banana production management technology
- 2.4. Dissemination of banana management practices
- 2.5. Factors affecting banana production
- 2.5.1. Characteristics of improved banana management technology
- 2.5.2. Socio-economic factors
- 2.6. Summary
CHAPTER 3: DETERMINANTS OF TECHNOLOGY ADOPTION
- 3.1. Determinants of farm-level adoption behaviour in the literature
- 3.2. Determinants of the adoption of low external input crop management technologies
- 3.3. The role of institutions and social networks in adoption decisions
- 3.4. Agricultural household models and technology adoption University of Pretoria etd, Katungi E M (2007)
- 3.5. Summary
CHAPTER 4: SOCIAL CAPITAL AND TECHNOLOGY ADOPTION
- 4.1. Manifestations and definitions of social capital in the literature
- 4.1.1. Manifestations of social capital
- 4.1.2. Social network definition of social capital
- 4.2. Social networks and technology adoption
- 4.2.1. Social network and information accumulation
- 4.2.2. Social networks, bilateral transfers and technology adoption
- 4.3. Overview of the literature on the determinants of social capital
- 4.3.1. Determinants of participation in associations
- 4.3.2. Determinants of private social networks
- 4.4. Summary
CHAPTER 5: CONCEPTUAL FRAMEWORK: CHOICE OF A CROP MANAGEMENT TECHNOLOGY IN AN AGRICULTURAL HOUSEHOLD MODEL WITH SOCIAL CAPITAL
- 5.1. Choice of a crop management technology under incomplete markets
- 5.2. Choice of a crop management technology when markets are complete
- 5.3. Choice of a crop management technology under technology relevance uncertainty
- 5.4. A summary of the household choice of a crop management technology
- 5.5. Concluding remarks
CHAPTER 6: DATA SOURCES AND SAMPLE CHARACTERISTICS
- 6.1. Data sources
- 6.2. Sampling frame
- 6.3. Selection of the sub-samples for the present study
- 6.4. Data collection methods
- 6.5. Basic characteristics of the sample
- 6.6. Summary
CHAPTER 7: MEASUREMENT AND ESTIMATION PROCEDURES University of Pretoria etd, Katungi E M (2007)
- 7.1. Econometric estimation procedure
- 7.1.1. Data aggregation, reduction and factor analysis
- 7.1.2. Econometric modeling and estimation of banana production management decisions
- 7.1.3. Econometric estimation of household participation in associations and private social networks
- 7.2. Definition and measurement of variables
- 7.2.1. Econometric approaches in technology adoption studies
- 7.2.2. Dependent variables for adoption models
- 7.2.3. Dependent variables for social capital models
- 7.2.4. Independent variables used in adoption equations
- 7.2.5. Independent variables used in social capital models
- 7.3. Summary
CHAPTER 8: DESCRIPTIVE STATISTICS ON BANANA MANAGEMENT AND SOCIAL CAPITAL
- 8.1. Banana management
- 8.2.1. Local associations
- 8.2.2. Characteristics of associations
- 8.2.3. Household private social networks
- 8.2.4. Bilateral transfers
- 8.3. Summary
CHAPTER 9: RESULTS OF THE STUDY
- 9.1 The decision to use improved management practices
- 9.1.1. Effect of household characteristics
- 9.1.2. Effect of farm characteristics
- 9.1.3. Effect of market factors and characteristics
- 9.1.4. Effect of information diffusion parameters
- 9.1.5. Effect of social capital
- 9.1.6. Likelihood ratio test of joint significance of groups of factors
- 9.2. Extent of use of management practices
- 9.2.1. Effect of household characteristics
- 9.2.2. Effect of farm characteristics
- 9.2.3. Effect of market factors and characteristics
- 9.2.4. Effect of information diffusion parameters
- 9.2.5. Effect of social capital variables
- 9.2.6. Joint significance test of a group of factors
- 9.3 Determinants of household social capital
- 9.3.1. Membership in associations
- 9.3.2. Social capital intensity at the household level
CHAPTER 10: SUMMARY, CONCLUSIONS AND POLICY IMPLICATIONS University of Pretoria etd, Katungi E M (2007)
- 10.1. Summary of the study
- 10.1.1 Background
- 10.1.2. Purpose of the study
- 10.1.3. Research methods
- 10.2 Major findings of the study
- 10.2.1 Use of banana management practices
- 10.2.2 Determinants of use of banana management practices
- 10.2.3 Social capital in the banana-growing areas
- 10.2.4 Determinants of social capital
- 10.3. Implications for policy
- 10.3.1. Implications of social capital as an asset in agricultural development
- 10.3.2 Improving the smallholder access to markets
- 10.3.3 Implications for banana production management technology
- 10.4. Limitations of the study and recommendations for future research
- 10.4.1 Additional mechanisms through which social capital influences the adoption of management technologies
- 10.4.2 Gender and social capital formation
- 10.4.3 Measurement of social capital
- 10.4.4 Scale of the data used to analyse the determinants of social capital
- 10.4.5 Modeling and estimation approaches
- Appendix A. Farmer classification as of banana management practices according to
- whether the practice is considered to be ancestral or introduced
- Appendix B. Correlation matrix of explanatory variables used in the analysis
- Appendix C. Estimation results for factors affecting use of improved banana
- management practices
- Appendix D: Estimation results of factors influencing social capital accumulation