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ANALYSIS OF THE VULNERABILITY OF SMALL SCALE FARMERS TO PRODUCTION RISKS IN MBALE CITY REGION.

CHAPTER ONE

INTRODUCTION.

Introduction

This chapter presents background of the study, the problem statement, purpose, objectives of the study, research questions, study scope, and significance of the study.

1.1 Background of the study

Smallholder farmers constitute a significant portion of the world’s population, with an estimated 450–500 million smallholder farmers worldwide, representing 85% of the world’s farms. Smallholder farmers are also estimated to represent half of the hungry worldwide and probably three-quarters of the hungry in Africa. Consequently, the fate of smallholder farmers will largely determine whether or not the world succeeds in reducing poverty and hunger worldwide (Poole, Chitundu, & Msoni, 2013).

Across the tropics, smallholder farmers already face numerous risks to their agricultural production, including pest and disease outbreaks, lack of enough market for their goods, extreme weather events and market shocks, among others, which often undermine their household food and income security. Because smallholder farmers typically depend directly on agriculture for their livelihoods and have limited resources and capacity to cope with shocks, any reductions to agricultural productivity can have significant impacts on their food security, nutrition, income and well-being (Mapfumo et al., 2013).

Climate change is expected to disproportionately affect smallholder farmers by further exacerbating the risks that farmers face. Recent studies using regional and global simulation models, for example, indicate that even moderate increases in temperatures will have negative impacts on rice, maize and wheat, which are the main cereal crops of smallholder farmers. Climate change is also expected to alter pest and disease outbreaks, increase the frequency and severity of droughts and floods, and increase the likelihood of poor yields, crop failure and livestock mortality. As many of the countries that will be the hardest hit by climate change are tropical countries with large populations of poor, smallholder farmers, there is an urgent need for the global community to focus its attention on identifying adaptation measures that can help these farmers reduce their vulnerability to climate change and cope with adverse consequences (Baributsa et al., 2019).

Climate change remains one of the critical issues affecting Uganda’s socio-economic development. Drought and dry spells, seasonal and flash floods and extreme temperatures are climate change impacts that the country is experiencing with adverse consequences for food and water security, water quality, energy and sustainable livelihoods of rural communities. In terms of sectoral impact, agriculture, forestry and water are the most affected. Climate change effect in the agricultural sector alone leaves 60% of the Ugandan population vulnerable and in danger of livelihood insecurity. Smallholder farmers on whose shoulders the Ugandan agricultural sector rests would be adversely affected. Climate change impact is also felt in the three agro-ecological regions (AER) of Uganda with each of the regions experiencing a set of peculiar impacts. AER I and II are highly vulnerable to frequent climate-induced drought (Thierfelder, & Wall, 2011).

According to the 2007 report from the United Nations Intergovernmental Panel on Climate Change (IPCC), climate change impacts in Sub Saharan Africa (SSA) will be felt even more during this century. Despite the current uncertainties on specific climate change impacts in the region, due to lack of qualitative and quantitative long-terms series of climatic data, as well as a lack of skills among regional institutions to produce accurate climatic predictions at local level (Hellmuth et al. 2007), it is very likely that increased climate variability, and/or the appearance of new climate stresses, will have negative impacts in SSA, which is defined as very vulnerable to climate change (IPCC 2007). The IPCC defines climate change vulnerability as: the degree to which a system is susceptible to, and unable to cope with, adverse effects of climate change. Climate change vulnerability depends on a system’s exposure and sensitivity to climate change impacts, and on its adaptive capacity. According to Adger (2003), adaptive capacities refer to the ability to cope, adapt, and recover from the impacts of climate change.

Climate variability is probably the most complex and challenging environmental problem facing the world today (IPCC 2014; Zizinga et al. 2015). The effects of climate variability are predicted to be more felt by the largely vulnerable smallholder farmers. Smallholder farmers in developing countries are highly vulnerable to variations and changes in climate (Bennett & Vanwey 2015; IPCC 2014) because of poverty and high marginalization (Bennett & Vanwey 2015).

Vulnerability is the degree to which a system is susceptible to, or unable to cope with, the adverse effects of climate change including climate variability and its extremes (IPCC 2014). It is a function of the character, magnitude and rate of climate variation to which a system is exposed, its sensitivity and its adaptive capacity. The determinants of adaptive capacity are directly correlated with measures of economic development (GDP per capita), and Africa has been noted to be already under pressure from climate stresses because of, among other things, lack of institutional capacity usually interpreted as lack of governance capacity (IPCC 2014). Effects of climate variability are predicted to be more felt in the mountainous regions compared to lowlands because of decreasing lapse rate (Viviroli et al. 2011). This is because mountainous areas are agriculturally rich and contain some of the world’s highest rural population densities, For instance, the Virunga volcano region of Rwanda recorded a population density of 400 people per km2, and Mount Elgon slopes had 700 people per km2 (UBOS 2016).

Countries in SSA have weak adaptive capacities (UNECA 2011) and, apart from climate change, they are already threatened by various challenges: political instability, high level of poverty, malnutrition and food insecurity, among others. In most African rural areas, rain-fed agriculture is the main economic activity and income source and is already exposed to climate risks (Hansen et al. 2011). In Benin, for instance, a small country in West Africa, food insecurity already affects 12 % of rural households, most of them situated in the southern part of the country (De Schutter 2009). In this part of Benin, farmers’ livelihood is very likely to be further challenged by increased climate variability and the appearance of new climate stresses.

According to (Ministry of Finance, 2020), Over 1.7 million rural residents who are mainly farmers in Uganda are predicted to have fallen back into poverty in 2020. The falling of back into poverty by the farmers is mainly due to the different risks that the agriculture sector faces and such risks are complex and the government may find it hard to deal with.

1.2 Statement of the problem

Uganda is a country in which understanding the vulnerability of farmers to agricultural risks and climate change is particularly important, as farmers comprise approximately 70% of the population and climate change impacts are expected to be significant. Uganda has one of the highest poverty rates in Africa, with 81% of the island’s inhabitants living on less than the international poverty threshold of $1.25 per day (PPP) and per capita gross national income (GNI) being just $600. Most farmers are smallholders cultivate primarily for subsistence, are chronically food insecure, and generally lack basic services, such as improved water sources and electricity. For the farmers in Mbale districts the risk has been so high in the resent two years that the horticulture farmers of the district hard to deal one of the challenges they faced with was the health risk on themselves which came inform of COVID-19, this did not only affect them in one way of the health but it also affected the whole world therefore affecting the country horticulture in ways like market accessibility. According to FAO, (2020) COVID-19) is having a devastating effect in terms of health and finance effects on the people and the most affected are the farmers whose livelihoods depend on farming. Farmers have lost market due to the closure of restaurants, schools, universities and Bars who were some of the largest consumers of farm products. The 17th Uganda Economic Update (UEU), From Crisis to Green Resilient Growth: Investing in Sustainable Land Management and Climate-Smart Agriculture, says that the COVID-19 shock caused a sharp contraction of the economy to its slowest pace in three decades, Household incomes fell when firms closed and jobs were lost, particularly in the urban informal sector. The country’s Gross Domestic Product contracted by 1.1 percent in 2020, and is estimated to have recovered to 3.3 percent during the 2021 fiscal year. One of the most affected sector is the Horticulture sector. The closure of schools, Hotels, Restaurants, Tourist has had one of the biggest effects on the Horticulture sector, despite previous researchers concentrating on different sectors of Uganda’s economy no research has been specifically carried out on analysis on the vulnerability of small holder urban horticultural farmers. It is against this Background that this study intends to investigate Analysis of the Vulnerability of Small Scale Farmers to Production Risks in Mbale City Region.

1.3 Purpose of the study

To contribute to reducing the vulnerability of small scale horticultural farmers to enhance urban food system resilience in Mbale city region.

1.4 Objectives.

To determine the horticultural food shed in Mbale City region.
To assess the production risk of small scale horticultural farmers at farm and sector levels.

To evaluate the efficacy of production risk reduction strategies adopted by small scale horticultural farmers in the Mbale City- region.

1.5 Research questions.

What is the percentage of food grown and consumed locally in Mbale City- region?

What production risk reduction strategies have been adopted by small scale horticultural farmers in Mbale City- region?

1.6 Study scope

This section will include the content, geographical and time scope.

1.6.1 Content Scope

The contents of the study will include; the horticultural food shed in Mbale City region, the production risk of small scale horticultural farmers at farm and sector levels and the efficacy of production risk reduction strategies adopted by small scale horticultural farmers in the Mbale City- region.

1.6.2 Geographical scope

The study will be carried out in Mbale. Mbale District is bordered by Sironko District to the north, Bududa District to the northeast, Manafwa District to the southeast, Tororo District to the south, Butaleja District to the southwest and Budaka District to the west. Pallisa District and Kumi District lie to the northwest of Mbale District. Mbale, the largest town in the district and the location of the district headquarters, is located approximately 245 kilometres (152 mi), by road, northeast of Kampala, the capital of Uganda, and the largest city in that country. The coordinates of the district are:00 57N, 34 20E. It has an area of 518.8 square kilometres (200.3 sq mi). The districts of Bududa, Manafwa and Sironko were part of Mbale District before they were split off as independent districts of their own

1.6.3 Time Scope

The period of study to carry out research will be From June to Dec 2021.

1.7 Significance of the study

The study will provide information on the influence of Economic trends on small holder Horticulture farmers to the government
The future scholars will also be able to have information regarding the influence of Environmental trends on small holder Horticulture farmers.

The study will also provide guide to the policy makers on design appropriate policies that can enable the improvement of livelihoods of Horticulture farmers.

CHAPTER TWO

LITERATURE REVIEW

2.0 Introduction

This section will include; the horticultural food shed in Mbale City region, the production risk of small scale horticultural farmers at farm and sector levels and the efficacy of production risk reduction strategies adopted by small scale horticultural farmers.

2.1 The production risk of small scale horticultural farmers at farm and sector levels.

According to Maertens and Swinnen (2006) It is expected that high standards will act as trade barriers for developing countries and cause increased poverty. The authors found that exports have grown sharply despite increasing standards, resulting in income gains and poverty reduction. They further explain that the tightened food standards caused a shift from small holder contract-based farming to large-scale integrated estate production, changing the means through which poor households benefit; that is through labor markets instead of product markets. The impact on poverty reduction is stronger as the poorest benefit relatively more from working on large-scale farms than from contract farming.

McCulloch and Ota (2002) sought to examine the linkage between export horticulture and poverty reduction in Kenya. The study makes use of household survey data to compare the incomes of households involved in export horticulture with those which are not. The findings of this study are that households that engage in export horticulture are better off than those which do not especially in the rural areas. Furthermore, farmers that engage in horticultural crops production often earn higher incomes than those who engage in cereal crops production. However, the authors also found that there exists some constraints faced by rural households in determining participation in the sector. These constraints mainly include post-harvest facilities, managerial and marketing skills.

Maertens and Verhofstadt (2012) analyze the indirect effects of a boom in horticultural exports on primary school enrollment and female off-farm wage employment. Using household survey data and an instrumental variable probit model, the authors found that female wage employment in the horticulture export industry had a positive and significant impact on primary school enrollment. Other factors that they found to affect primary school enrollment are household characteristics, village factor and individual child characteristics. Their study also shows the importance of the labour market especially for women in alleviating poverty by increasing the total household income.

Hichaambwa et al. (2015) assess the extent to which small holder horticulture contributes towards poverty reduction as compared to the maize sub sector in Zambia where most of the public resources in the agriculture sector are spent. The study also uses household survey data and a regression model to estimate the comparative household income impacts of participation in horticulture and maize markets. The study found that small holder horticulture market participation has higher income impacts than that of maize. Furthermore, female headed households and those with relatively younger heads are found to be more willing to participate in horticultural production.

Asfaw (2008) tests whether food safety and production oriented standards imposed by developed countries can affect the welfare of small scale horticulture producers in developing countries who are the main target in poverty reduction strategies. Using data collected by means of farm household surveys and application of various economic models including the two-stage Poisson regression model, the author finds that small scale farmers face more difficulties in complying with the standards as compared to the large scale farmers in terms of information, capital and labour. However, the study further suggests that the standards do not eliminate small holder farmers as a whole but discriminates within the group. It is the asset poor who may be left out from the export market chains but the rest of the small scale farmers who are able to invest in and adopt the standards will be able to enjoy higher net income and stronger bargaining positions with exporters.

Chege et al. (2015) assess the impact of export horticulture farming on the welfare of small holder farmers in Kenya in terms of food security using the Propensity Score Matching Method. They find factors such as regional climatic differences, marketing conditions and intra household income distribution patterns play a role in determining whether a shift from food production for home consumption to production for the market is a way out of poverty and a means to enhance food production.

Rao et al. (2010) analyze the effects of participation in supermarket channels on farm household income and poverty reduction in Kenya. The study uses endogenous switching regression on a survey of vegetable farmers in Kenya. The results from the study suggest that supermarkets can contribute to income growth and poverty

reduction in the small and rural farm sector. However, to benefit from this on a larger scale would require broader infrastructure development as well as targeted institutional and policy support so as to minimize disparities and marginalization of small holder farmers.

2.2 Production risk reduction strategies adopted by small scale horticultural farmers

Farmers constantly cope with and manage different types of agricultural risks. Risk inherently involves adverse outcomes, including lower yields and incomes and can also involve catastrophic events, such as financial bankruptcy, food insecurity and human health problems, although higher expected returns are typically one of the positive rewards for taking risk. Farmers therefore cope simultaneously with and manage multiple risks that can have compounding effects (Wauters et al., 2014). The compounding effects may affect decisions and outcomes at scales well beyond the farmer. One initial cause of the 2007/08 world food price crisis was production risk related to severe droughts but the impacts of the ensuing price spikes were exacerbated by some governments imposing export restrictions. During this crisis farmers faced production risk (drought), market risk (price spikes), and institutional risk (unexpected changes in government policy) all within a short period. Thus, risk outcomes can have cascading effects where one type contributes to another type occurring for example, excessive rainfall during harvest is an event that can engender another set of risks such as financial risks associated with being unable to repay loans (Pelka, 2015).

Given that multiple types of agricultural risks are likely to occur simultaneously, several policy-driven initiatives have begun to address these risks more holistically. These initiatives examine risk management issues and strategies that concentrate on multiple sources of risk. They include the Platform on Agricultural Risk Management, the World Bank’s Forum for Agricultural Risk Management in Development (FARM-D), and programs in the Center for Resilience. Funders of agricultural research are also beginning to support more projects that focus on the multiple risks that farmers encounter. Examples include the SURE-Farm project and the INFORM index for risk management (Meuwissen et al., 2019) In addition, both academics and policy researchers are taking a more earnest focus on risk, such as the PIIRS Global Systemic Risk research community and the recent efforts by the OECD’s risk management and resilience topic group. This new focus and reorganization of human and financial resources, often in the context of the resilience of farms and the agricultural sector to adverse events, suggests that a growing appreciation exists that multiple types of risk are important.

Farmers have always faced multiple risks; for example, in premodern Iceland major concerns for farmers included weather variability and personal illness, Campbell et al. (2016) argue that the growing number of studies that focus almost exclusively on the link between weather variability and crop yields provide only marginal increases in knowledge and by only studying one risk we only gain an inadequate picture of all the types of risk farmers encounter. The implication of this argument is that analyses of multiple concurrent sources of risks are likely to generate more useful insights. The IPCC (2019) reinforces this view by discussing how diverse types of risks co-occur or reinforce each other and how such co-occurrence can limit the effectiveness of adaptation planning for climate change. The IPCC indicates a possible remedy may be policymaking that considers multiple risks. Other researchers have also argued that the risks associated with climate change, economic volatility, globalization, and political instability have become more pronounced and severe (Hansen et al., 2019), Whether farmers’ exposure to risks, in general, has increased over time remains an open question as the quantitative evidence seems mixed and context specific, especially for weather and commodity prices (Wildemeersch et al., 2015), However, unanticipated events with considerable impacts on farmers continue to occur (Just, 2001) which suggests that the nature of risk has changed over time. The challenges to the agricultural sector from a growing world population, from changing diets with higher demand for animal-source foods, and from climate change, make managing multiple risks more important than ever.

The types of risks relevant to them on their farms. Ideally, new initiatives that seek to promote and support holistic risk management should be underpinned by evidence on how farmers cope with multiple risks. However, the evidence from our study indicates that the existing literature may not adequately provide such support. Our study describes and synthesizes the trajectory and status of the peer-reviewed literature on the types of agricultural risks that researchers have examined.

CHAPTER THREE: METHODOLOGY

3.0 Introduction

This chapter provides justifications of the methodology that will be used for the study. The research design and analytical path of any research project should have a specific methodological direction based on its research objectives and framework. Provided is therefore a scientific process that will be followed to qualify the generalization of findings on the analysis on the vulnerability of small holder urban horticultural farmers to agricultural risks in Mbale city. They include the research design, study population area, sample size, sampling techniques and procedure, data collection methods, data collection instruments, validity and reliability, data quality control, data analysis, data measurements, ethical considerations and limitations of the study.

3.1 Research Design

According to Fisher (2007), a research design is defined as a detailed outline of how an investigation takes place. The study will adopt a descriptive survey design which will provide descriptions of the variables to answer the research questions. This study will use two approaches; the qualitative and quantitative research design. Kothari (2004) notes that quantitative design is based on measurement of quantity hence this will be used in calculating simple percentages and the number of respondents. Bryman et al., (2003) reiterates that quantitative design also allows comparisons between respondents, giving the right perspective on the variables under study. The choice of this technique is also guided by the fact that the study aims at generating findings, which would facilitate a general understanding and interpretation of the problem. The quantitative data will be triangulated with Focus Group Discussions and Key Informant Interviews to provide explanatory information to the statistical data.

3.2 Study population and Area

Mbale city is located in the Eastern Uganda. It is the main municipal, administrative and commercial center of Mbale district and the surrounding sub-region (Bugisu). It is made up of 3 divisions, 12 wards and 83 cells some of which include: Namatala, Malukhu, South central, North central, Moni, Boma, Namakwekwe, Nkoma, Busamaga, Nabiyonga, Wanale and others. It covers about 2,467km², anticipated to have a population of about 96,189 people as of 2014 census.Mbale city has a total of 500 small holder farmers in the horticulture agriculture business.

3.3 Sampling techniques

This study will employ both probability and non-probability sampling techniques. Probability sampling techniques will include simple and stratified random sampling which will be used to Select small holder farmers in Mbale city. This will ensure that there is representativeness. Besides, it will provide an equal chance to all of being selected. Non-probability sampling techniques will include purposive; namely key informants to ensure people with particular information about the subject under study are selected. Snow ball sampling will be used to reach respondents through referrals and enable the researcher interview respondents who can provide data on the topic under study.

3.4 Determination of the sample size

The study will employ both Random and Purposive sampling procedures; secondary and primary data will be collected. The secondary data will be gathered from published literature while primary data will be collected from surveys or field observations, mapping, Interviews (Household and Key informant interviews), the researcher will use a sample of 217 respondents to be representative of the population and this will be determined by using the Krejcie and Morgan (1970) Table of Determining Sample Size. The sample size will be 217 out 500 members of Small holder farmers In Mbale. Sekaran (2003) contends that a sample size item larger than 30 and less than 500 is appropriate for most studies.

3.5.0 Data sources and collection instrument

Majorly, two types of data sources – primary and secondary will be used for this study

3.5.1 Data sources, Collection Procedure and Instruments

Two types of data namely primary and secondary data will be used to collect data using different methods. Primary data will be collected using questionnaires and direct interviews. The study will adopt a mixture of qualitative and quantitative methods to obtain data on the topic under study. Qualitative data will be collected using Focus Group Discussions (FDGs) and Key Informant Interviews (KIIs). FDG guides and KII guides will be used to collect data on feelings, beliefs and attitudes regarding the subject under study. Quantitative methods will be used to generate quantifiable data, using a questionnaire, which will be the main instrument used because of its convenience and efficiency in data collection. The different tools and data sources will be used to make triangulation feasible (Amin 2005). The primary data will be collected using questionnaires administered to individual women, FDGs and Key Informant Interviews.

3.5.2 Secondary data sources

Secondary sources of data that will be reviewed include scholarly books, magazines, dissertations journals and articles. This source is useful in collecting data from already written literature for example e-books, journals, published articles and periodicals as part of literature review. Documentary resources will be classified in order to facilitate the data collection and textual analysis (Mubazi, 2008).

3.6 Data Collection Methods and Instruments

The study will adopt a mixture of qualitative and quantitative methods. Qualitative data will be collected using interview guides for FDGs and KIIs. The use of interview guides to enable data collection on feelings, beliefs and attitudes regarding the subject under study. While quantitative data will be collected using a questionnaire.

3.7.1 Questionnaire

Ahuja (2009) defines a questionnaire as a structured set of questions that are given to people in order to collect facts or opinions about something. The researcher will use closed-ended questions because they are easy and quick to answer, and they are helpful in improving consistence of the responses.

3.7.2 Interviews

According to Ahuja (2009), an interview is a two-person conversation initiated by the interviewer for the specific purpose of obtaining research-related information. It focuses on the content specified by the research objectives, description and explanation. An interview guide, which is referred to as a set of questions for which answers, will be used by a researcher to interview respondents. The use of this tool gives the researcher control over the line of questioning hence time saving. Interviews will be conducted in a quiet place without noise. The purpose of the interview explained, including reassuring respondents of confidentiality of the information provided. The format of the interview will be informal conversation where questions are asked, and answers recorded by the interviewer.

3.8 Data collection procedure

The researcher will obtain a recommendation and an introductory letter from Makerere University, after which she will seek permission from the different respondents in Mbale city

3.9 Data Quality Control of the Instrument

3.9.1 Reliability of the questionnaire

According Bruton (2000), reliability is established by testing the instruments for the reliability of values (Cronbatch, 1946) and analysis for Alpha values for each variable under study. Sekaran (2001), notes that Alpha values for each variable under study should not be less than 0.6 for the statements in the instruments to be deemed reliable. To ensure that all variables are subjected to this test, the researcher will use the internal consistency method that provides a unique estimate of reliability for the given test administrations. The most popular internal consistency reliability estimate has been given by Cronbach’s Alpha.

3.9.2 Validity of the questionnaire

After developing the questionnaire, the researcher will contact the supervisor and three other experts to ensure that the tools to collect the required data is valid. Hence, the researcher will ensure validity of the instruments by using expert judgment method suggested by Gay (1996). Thereafter, research instruments will be refined based on expert advice. The following formula will be used to test the validity index. CVI= No. of items regarded relevant by judges over Total No. of items judged.

3.10 Data Collection Procedures

The questionnaire will be structured and pre-tested by the researcher in industrial division-Mbale since it also has an urban setting with similar study characteristics. This will be done after approval by the supervisor. A letter of introduction by the institute will enable the researcher to carry out research.

3.11 Data Processing and Analysis

This section covers methods of data processing and analysis.

3.11.1 Data Processing

In order to ascertain the accuracy, consistency, uniformity, proper arrangement and completion of the data, the researcher will use the computer for data entry, editing and data coding. The computer will be used because it increases the speed of computation and data processing and handles huge volumes of data, which is not possible manually. It facilitates copying, editing, saving and retrieving the data easier and validation, checking and correction of data.

3.11.2 Data Analysis

Descriptive statistical analysis -Excel and SPSS tools, will be used in data analysis ,ARC GIS tools like Data Management tools, Spatial Analyst Tools, multi- level logistic regression for prediction of variables, and using CorelDraw software to illustrate connectivity and inter relations among different stake holders and variables.

3.12 Ethical consideration

Ethical considerations will be taken care of by, first seeking authorization from the Makerere University administration and other relevant authorities. Questionnaires will be structured in such a way that there is no mention of the interviewee’s name which ensures strict confidentiality in data.

Further, responses will be optional and respondents will not be given any inducements to participate in the study. Ethical considerations will be taken care of by the researcher by briefing the respondents on the purpose of the research, their relevance in the research process, and expectations from them as explained by Lloyd Bevan (2009).

Informed consent will be ascertained from informants/respondents. They will be promised confidentiality about the information they provide. The researcher will explain to the respondents the purpose of the study as purely academic and that the information obtained will be treated with utmost confidentiality. If anybody other than the University authority is to have access the information, the researcher would first seek the consent of the respondents.

3.11 Limitations of the Study

The study may have the following limitations:

The respondents may fear to answer questionnaire thinking that they might be spying on them.
The COVID-19 pandemic is a huge challenge, since most of the residents fear to associate with strangers because of the disease.