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121 Seiten, Note: Excellent
TABLE OF CONTENTS
LIST OF TABLES
LIST OF ACRONYMS
CHAPTER ONE INTRODUCTION
1.2. Problem Statement
1.2.1. Research Questions
1.3.1. General Objective
1.3.2. Specific objectives
1.4. Significance of the Study
1.5. Scope of the Study
1.6. Description of the Study Area
1.7. Limitation of the Study
CHAPTER TWO LITRATURE REVIEW
2.2. Theoretical Literature Review
2.2.1 Understanding the concept and definition of poverty
2.2.2. Economic theories of poverty
2.2.3. Measuring Poverty
184.108.40.206. Concepts of measuring poverty
220.127.116.11. Indicators and measurements of welfare
18.104.22.168. Poverty Line
22.214.171.124. Equivalence and Economies of Scale
2.3. Empirical Literature Review
CHAPTER THREE RESEARCH METHODS
3.2. Research Type and Approach
3.3. Sample Design
3.3.1. Sampling Techniques
3.4. Data Sources and Methods of Collection
3.5. Measurements of poverty
3.5.1. Setting Poverty Line
3.5.2. Developing Poverty Profiles
3.5.3. Poverty Indices and Decompositions
3.6. Econometric Model Specification
3.6.1. Determinants of Rural Household Poverty
3.7. Description of Variables
3.7.1. Dependant variables
3.7.2. Independent Variables
3.8. Data Analysis and Interpretation
CHAPTER FOUR RESULTS AND DISCUSSIONS
4.2. Descriptive Analysis on Socio-Demographic Characteristics of the Study
4.3. Economic characteristics of sample households
4.4. Access to Resources and Different services
4.5. Household Consumption Expenditure Analysis
4.6.2. Indices based poverty profile of the study area
4.6.3. Poverty decomposition across sample Kebeles
4.6.4. Poverty decomposition across socioeconomic characteristics
4.7. Econometric Results Analysis
4.7.1. Determinants of household consumption expenditure
4.7.2. Determining factors of poverty status
4.7.3. Determinants of poverty depth and severity
4.8. Participatory Poverty Analysis
4.8.1. Perception and definition of poverty
4.8.2. Wellbeing ranking
4.8.3. Participatory analysis on determinants of poverty
CHAPTER FIVE CONCLUSIONS AND RECOMMENDATIONS
As a beginning and an end, I need to thank Lord Jesus Christ and his Mother, St. Merry for helping me to finish my work and reach here. Next to that, I need to express my gratitude and appreciation to Yom Institute of Economic Development (YIED) for its initiative to start this collaborative masters program that opened an opportunity for many students like me.
Onwards, my deepest gratitude goes to Dr. Abrham Seyoum, my senior advisor, for his unlimited support, constructive comments, and assistance in each parts of my thesis work. Successful accomplishment of this research would have been very difficult without his support starting from proposal design to the final write up. I need also forward my heartfelt thanks to Mr. Addisu Mekönnen, my coadvisor for his restless and unreserved support not only providing comments and suggestions on my thesis but also coordinating the whole program by representing Debre Markos University.
It is time to give thanks to Dr. Zerayhu Sime, who thought me more than five courses, for his inspiration, encouragement, restless effort to qualify us and his brotherhood advice. I also appreciate the strength and devotion of all instructors form YIED who thought us by traveling more than 300 Km from Addis Ababa to Debre Markos every week.
Thanks to my father Yigzaw Tilahun and my mother Mosit Amsalu, you are my heroes. I have no words to say about your wish and enthusiasm to teach your children. A gain, I need to forward my heartfelt thanks to my wife Menbere Zurbachew for her unlimited support and encouragement throughout my life.
I am very much indebted to convey my gratitude to Facilitator for Change (FC) management team particularly Mr. Gelaye Hailu, director of the organization, who understand my interest and allowed me to extend my education further. Furthermore, I need to extend my deepest gratitude to all Facilitator for Change, Debre Markos area project staffs for their understanding and valuable support during data entry. The last but not the least, I would like to express my thanks and appreciation to all of my colleagues and friends.
Table 4.1 Distribution of sample household across Kebeles
Table 4.2 Mean age of the house hold heads and the family
Table 4.3 Average household size and dependency ratio
Table 4.4 Adult equivalent family size of sample households
Table 4.5 Education status of household heads
Table 4.6 Land holding per adult equivalence
Table 4.7 Households’ access to credit service
Table 4.8 Daily food and nonfood consumption expenditure per adult equivalent
Table 4.9 Food share from total consumption expenditure per adult equivalent per day
Table 4.10 Poverty profile of households
Table 4.11 Poverty indices across sample kebeles
Table 4.12 Poverty decomposition by major agroecological zones
Table 4.13 Poverty decomposition across socioeconomic variables
Table 4.14 Determinants of consumption expenditure per adult equivalent of households (OLS regression model)
Table 4.15 Determinants of poverty status of households (Logit regression model)
Table 4.16 Determining factors of poverty depth (Tobit regression model)
Table 4.17 Determining factors of poverty severity (Tobit regression model)
Table 4.18 Composition of PPA participants by sample kebele
Table 4.19 Developed subjective criteria to measure wellbeing status of households
Table 4.20 Wellbeing rank of PPA participant households
Table 4.21 Participatory scoring matrix on determinants of poverty
Appendix 1: Food poverty line derivation at current market price
Appendix 2: Energy content per 100 gm of edible portion of food items
Appendix 3: Calorie Based Nutrition Adult Equivalence Scales
Appendix 4: TLU conversion factor for different animals
Appendix 5: Determinants of consumption expenditure per adult equivalent (OLS regression model)
Appendix 6: Determinants of poverty status of households (Logit regression model)
Appendix 7: Determining factors of poverty depth (Tobit regression model)
Appendix 8: Determining factors of poverty severity (Tobit regression model)
Appendix 9: Household Survey Questionnaire
Appendix 10: Guide to conduct Participatory Poverty Assessment
Abbildung in dieser eseprobe nicht enthalten
In developing countries like Ethiopia, our dayto-day formal and informal discourses are rarely out of poverty issues that can be linked directly or indirectly. Despite the determined effort of government and development agencies to reduce poverty and ensure sustainable development, poverty remains an everlasting challenge of the world. This study aims to examine rural household poverty and its determining factors using alternative poverty measurement approaches, in case of Gozamin Woreda, East Gojjam Zone of Amhara Region. It used both objective and subjective based poverty analysis approaches, where the survey based analysis and PPA of the study depend on randomly selected 242 and 42 sample households respectively. Using cost of basic needs approach (CBN), the poverty line of the study area is estimated as 19.16 Birr per day per adult equivalent. The study engaged Foster, Greer and Thorbecke (FGT) group of poverty measures to assess the incidence, depth and intensity of poverty and decompositions were made across sample Kebeles and socioeconomic variables. OLS, logit and censored (Tobit) regression models were also applied to identify determining factors of household consumption expenditure, poverty incidence, depth and severity. Accordingly, 35.12 % of the population lives under poverty and it is closely estimated as 33.33% using PPA. Poverty becomes sever challenge in Dega agroecological areas of the Woreda, where 57.37% of the population lives under poverty. Family size and agroecological location (from Kolla to Dega) have significant negative effect on consumption expenditure, but positively affect poverty incidence, gap and severity. Access to credit service, cooperative services, health extension services and offfarm activities have significant positive effect on consumption expenditure; while negatively affect the incidence, depth and severity of poverty. PPA findings revealed that, perception of the community towards poverty is beyond the conventional, income/consumption based definition. Therefore, development policies and poverty reduction strategies should respond to rapid rural population growth. Moreover, Dega agroecological areas need particular attention all the way through poverty reduction efforts.
Key words: Rural household, Poverty, Foster Greer and Thorbecke (FGT), Cost of Basic Needs (CBN), Participatory poverty Assessment (PPA)
There is a commonly used public proverb that says “there are so many words which are getting old without being internalized properly”. The basic idea is to emphasize the presence of too many issues which are frequently raised and discussed by development agents, political leaders and ordinary peoples without having indepth understanding and know how. Poverty is among those issues raised and discussed in each and every corner of the development agenda, while it needs critical understanding to contextualize and internalize beyond the mere word. Especially, in developing countries like Ethiopia, our dayto-day formal and informal discussions are rarely out of poverty related issues where it could be linked directly or indirectly. On the other hand, understanding of a certain issue or problem is considered as having half of its means to come up with the final solution. Likewise, understanding the concept, situations and nature of poverty in a certain community or area could be taken as a vital step before proceeding to undertake subsequent actions and measures to reduce its rate and severity.
Although poverty is a widely used meaningful concept in all countries of the world, there isn’t universally agreed upon definition which can serve for all disciplines. “It often seems that if you put five academics (or policy makers) in a room you would get at least six different definitions of poverty” (Gordon, 2006). This implies that, it is common to find controversies and opinion differences among literatures on the conceptual definitions of poverty.
The United Nations (UN) defined absolute poverty as “a condition characterized by severe deprivation of basic human needs, including food, safe drinking water, sanitation facilities, health, shelter, education and information. It is dependent not only income but also on access to services” (UN, 1995).
The Programme of Action of the World Summit for Social Development (United Nations, 2006, resolution 1, annex II) characterized poverty as follows: Poverty has various manifestations, including lack of income and productive resources sufficient to ensure sustainable livelihoods; hunger and malnutrition; ill health; limited or lack of access to education and other basic services; increased morbidity and mortality from illness; homelessness and inadequate housing; unsafe environments; and social discrimination and exclusion.
The World Bank’s definition of poverty indicates that poverty is “...a pronounced deprivation of wellbeing related to lack of material income or consumption, low levels of education and health, vulnerability and exposure to risks and voiceless and powerlessness (World Bank 2001a, as quoted by Pradham& et al., 2002).
In terms of money metric measurement, households with daily consumption of less than World Bank’s famous poverty line, $1.25 per person per day are considered to be living in extreme poverty. A dollara day poverty line was revised by the World Bank to $1.25 per person per day in 2008 using the international price of the year 2005 and the head count poverty rate is used as measurement to show the proportion of the overall population living below $1.25 per person per day.
Based on the World Bank policy research report (2015), substantial progress had made to reduce global poverty in the past few decades where the number of people living in extreme poverty reduced by half to around 1 billion (14.5 percent of the world’s population and 17 percent of the developing world’s population) between the years 1990 and 2011. From the above figure, Sub-Saharan Africa countries account the largest proportion, 415.4 million people (46.8 percent of the Region’s population) followed by South Asia with 399 million people, 24.5 percent of the population(World Bank, 2015). Ethiopia is among Sub-Saharan Africa countries and a home of 90.07 million people, the second populous country in Africa with 80.6 percent rural population. Based on Central Statistics Agency, (2015), 29.6 percent of the country’s population lives below poverty line and this figure goes up to 30.4 percent in rural areas. The country is among the poorest nation in the world; where a multidimensional character of poverty is reflected in many aspects, such as destitution of assets, vulnerability and human development. The poor in Ethiopia are entangled in a web of interrelationships between the various determinants of poverty. Basic deficiencies in the resource base of the productive forces have become critical drawbacks in alleviating the poverty situation. Lack of equity in the access to productive resources and basic services and their consequential benefits as well as lack of access to opportunities to develop skills and human capabilities have impeded the socioeconomic development of the poor. In addition, absences of the means by which the poor can address their problems and enhance their active participation in decisionmaking have hindered their attempts to move out of the state of deprivation.
Several institutions and scholars are highly involved in research and poverty assessment programs to have an updated understanding of its dimensions, root causes, dynamics, measurements, trends and current situations of poverty both at global, national and specific to regional level. Depending on the findings of assessments and research studies, global development institutions, states, Non-Government development organizations devise and set various policies and strategies to eradicate absolute poverty through promoting sustainable development. Understanding multidimensional characteristics, measurements and determinants of poverty are some basic foundation to have the precise policies and strategies to eradicate and /or reduce poverty within a certain country. With the same analogy, scientific researches and investigations on poverty either at national or specific level deemed to have multiple importance to enrich the ongoing development process with creditable recommendations based on scientific findings for further development of the nation.
Despite remarkable progress achieved to reduce absolute poverty, it remains a widespread challenge in many parts of the world, especially in Sub-Saharan Africa including our mother land, Ethiopia. Ethiopian poverty assessment report conducted by World Bank, (2014) revealed that the country has shown outstanding performance to reduce absolute poverty rate from 56% in 2000 to 31% in 2011 based on the international poverty line measurement, $1.25 PPP a day. However, about 14 % of nonpoor households in Ethiopia today consume only just enough to live above the poverty line which makes them easily vulnerable to fall into poverty. Besides, World Bank Group, (2015) revealed that more than 60% of Ethiopia’s populations are categorized under moderate poor and receive $1.25 to $ 4 dollar per a day. This shows that the progress to escape out the population from poverty can be easily reversed back unless the country’s development policies and strategies are designed based on scientific studies and research findings to address multidimensions of poverty.
On the other hand, poverty has a different scenario in rural and urban population of the country. It appears to persist in large sections of the rural society with gradual improvement of the living conditions of the rural poor. Referring back studies to link with the current situation, Ethiopian Ministry of Finance and Economic Development (MoFED) assessment of Household Income and Consumption Expenditure (HICE) for the year 1999/2000 and Welfare Monitoring Survey results concluded that the incidence of poverty is higher in rural than in urban areas with a poverty head count ratio of 45.4% and 36.9%, respectively (MoFED, 2002).The persistence of poverty variation among rural and urban areas continued, albeit the overall poverty rate has shown a declining rate. Ethiopia Central Statistics Agency official website indicates that the current poverty rate of the country is 26.9%, while in rural areas the figure goes up to 30.4% (FDRE, CSA, 2015). Moreover, about 80% Ethiopian population resides in rural areas and depends on traditional agriculture systems where the sector accounts 47.7% of the total GDP and 85 % of the labor force of the country (World fact sheet, 2014). No doubt on the need to provide a great deal of concern for the rural communities to improve the living condition of the society so as the country can register tremendous progress towards reducing the current state poverty in more acceptable way. In view of that, contextually sound development policies, programs and projects to reduce poverty and promote sustainable development are expected to be designed based on research studies and findings.
On the contrary, there are many studies and assessments conducted on poverty, but only a few are concerned about rural poverty which is highly important for countries with high rural population like Ethiopia. Most studies have utilized a single poverty assessment mainly focused to measure monetary indicator of welfare. For instance, Dercon & et al, (2012) in their study of “Growth and chronic poverty: Evidence from rural communities of Ethiopia” utilized only objective based poverty measurement based on consumption. Bogale and et al. (2005) in their study “Determinants of Poverty in rural Ethiopia” utilized consumption based poverty measurement which entirely focused on objective based poverty assessment.
Bradshaw (2001) in his poverty measurement analysis argued that it is important not to rely on a single measure of poverty but attempt to triangulate a variety of measures. In the end policy makers will have to decide which the most appropriate measure as target for policy is. With his poverty research working paper on using subjective data in measuring poverty Ravillon (2012) explained the three most importance of utilizing subjective data in poverty measurement. The first is as a means of testing objective poverty lines. The second is to calibrate a composite welfare index using the subjective welfare regression coefficients as the weights and the third is to derive a poverty line in the income space, defined as the income level at which some critical level of subjective welfare is reached in expectation.
Thus, the peculiar and distinguishing feature of this study is that it utilized different poverty measurements which has gone through both objective method and subjective method of poverty analysis. Among the vast literature and studies about poverty, it is not easy to find a study that engaged subjective poverty measurement or utilize more than one measurement to triangulate the findings of objective based assessment. In case of our country and in particular to the study area, there are limited studies which are conducted to assess poverty based on multidimensional measurement tools. Accordingly, this research was conducted to contribute to the assessment effort of poverty determinants using multidimensional poverty measurement approach to triangulate the findings from the conventional methods.
The inner most inquiries of the study circulated over the poverty status and its determinants across various characteristics of each rural household. Formally, the basic questions of the research can be articulated as follows: what are the determinants of poverty in rural households? How is the poverty status of rural households in the specified research area? Does the poverty status of the households vary across quantitative and qualitative measurement of poverty? These are the three major questions that are addressed by the findings and analysis of the study.
The general objective of the research is to examine rural household poverty and its determining factors using alternative poverty measurement approaches in the case of GozaminWoreda, East Gojjam Zone of Amhara Regional State.
The research has three specific objectives which can contribute to the general objective.
- To assess the poverty status in rural areas of the specific study area;
- To analyze, compare and contrast poverty status of rural households using various poverty measurement tools;
- To investigate the determinants of rural household poverty in Gozamin Woreda
It is believed that scientific research studies and investigations on poverty are highly important since most developing countries, development organizations and donor agencies are striving to eradicate the current challenge: absolute poverty and deprivation of human kind. Meanwhile, no policies and strategies are ever designed without the support of research findings to set goals and prospective actions.
Based on the above premises, this study can have multiple significances for Government policy makers, development organizations and implementing agencies to design contextually, precise policies and take informed decision through the way to reduce poverty across the nation. Besides, the study has its role in the entire poverty related research and literature world through providing some insight about poverty determinants and measurements in a geographically specified area.
It also serves as a reference document for the local government of the district to realize where they are and where to reach regarding to poverty reduction programs. Hence, the study can contribute its part for neverending effort of poverty reduction and development actions.
The last but not the least, the study can open a door or could be utilized as an initial base to conduct further research studies in various areas of the country as well as other developing countries.
In terms of geographical coverage, the study was conducted in one Woreda administration with four representative kebeles and limited sample households. It mainly focused on economic aspects, while poverty has multidimensional features. It provides clear insight about determinant characteristics which had a significant relationship with poverty status; however, it has limited analysis of root causes why each characteristic of the household seemed like that.
The study was conducted in Gozamin Woreda. It is among 20 Woredas (districts) of East Gojjam Zone in Amhara Region and located at 300 Km to the West of Addis Ababa, capital of Ethiopia. The administrative unit of the district is situated in Deber Markos, capital of East Gojjam Zone and Kebeles are found in all round directions of the town. According to the local elder’s saying, the name Gozamin was derived from the local Amharic dialect “Guzam” which refers wealthy and strong farmer, who work hard and has enough resources. The Woreda has 25 rural and 5 semiurban kebeles with a total of 151,442 (50.3% female) population (CSA, Population projection, 2015). 97% of the population lives in rural area which is even larger than the country’s urban rural ratio.
Gozamin is bordered with Baso-Liben Woreda to the South East, with Abay River to the South, which separates the district from the Oromia Region, with Debre Elias Woreda to the West, with Machakel Woreda to the North West, with Sinan Woreda to the North, and with Aneded to the East. Overall area coverage of the district is 121,781 hectares with different topographical structures; 42% plain area, 9% rugged terrain, 32%mountainous and 12% gorge. The agroclimatic condition of the Woreda is categorized as 1% very cold (Wurch), 9% cold (Dega), 74% mild (Woyna-Dega) and 16% is hot (Kolla). The highest altitude in the district as well as in East Gojjam Zone is Mount Choqie (also known as Mount Birhan); with an elevation of 4,154 meters above sea level and the lowest point is 800 meters located in a Blue Nile river gorge.In line with the presence of high altitude difference, average annual rainfall of the Woreda is 1,448 mm per annum (Gozamin Woreda FEDO, 2014).
Crop production shows variation across different rural Kebeles of the Woreda. Basically, production and productivity of the land in highland areas of the district are marginal and most of the communities are food insecure, while the lowland areas have relatively better production and productivity potentials. The vegetation cover is very low and land degradation and gully formation are a serious threat to the survival of the resident community, especially in highland parts of the Woreda.
Crop and animal production are the two major farming practices that the lives of most resident farmers relay on. Wheat, Teff, Bean, Maize and Barley are major field crops produced in the Woreda, while different fruits and vegetables are cultivated to supplement the household’s food need and generate additional income. Like other rural parts of the country, most community members are illiterate, have low level of awareness on development programs and limited skills to diversify their income sources.
Even though there aren’t clear and concrete evidences that can show the poverty rate of the Woreda, it is estimated to be high, especially in the highland part of the district where agricultural production and productivity is marginal. A baseline survey conducted by Facilitator for Change, (2013) to assess food security status of households indicates that 51% (n=192) of households often worried about shortages of food to secure the required amount for a year. In most cases, food shortage starts on June month and continues up to September and extends up to November with a declining rate. Household’s food insecurity status could be an initial insight for further study on persistence of poverty.
Though every type of survey has its own weakness, crosssectional (one at a time) survey method has limited capacity to show the poverty status of the household than longitudinal data which can show relatively better performance due to frequent observations over a period of time; however, such type of data is rarely available. On the other hand, the study mainly depends on household consumption to measure poverty status, while the consumption doesn’t include public goods like: road and public schools due to the sophisticated estimation for consumption of such goods. Besides, consumption expenditure is highly affected by shocks which could lead wrong estimation.
Poverty line of the area was estimated using cost of basic needs (CBN) approach and food bundles are drawn from the food consumption list of the lower reference group due to lack of reliable data source to take representative food basket usually consumed by poor peoples of the study area.
As a mitigation strategy for limitations from crosssectional data, sample households were selected randomly through providing equal chance of being selected from each representative kebeles. Although public goods consumption was not included, household consumption from other sources was carefully investigated to minimize the limitation. The research questioner was designed in a systematic way to countercheck the response of the respondents and enumerators were fully oriented on how to conduct the interview.
Various schools of thoughts reflected a wide range of views on poverty from multiple social science perspectives, including Economics, Sociology, Psychology, Anthropology and Political science theories. For the consumption of this research, only economic theories and empirical studies of poverty are subjected to review in order to link with the basic theme of the study. Accordingly, theoretical and empirical review, basic concepts and frameworks of household welfare and poverty measurements are major discussion points addressed by this chapter.
The father of modern economics, Adam Smith has defined poverty as “the inability to purchase necessities required by nature or custom” (Smith, 1977 as quoted by Davis, 2014). The definition of Adam Smith implicitly provides the same weight for social and psychological characteristic of poverty (custom) as that of the material, purely economic condition (nature) (Davis, 2014). Smith’s Theory of moral sentiment argues that poverty is a cause of shame, social exclusion and psychic unrest, rather than an economic condition (Gilbert, 1997). Director (2006) in their review of the economics of poverty explained Smith’s observation on economic inequality as part of all societies from the hunting to the herding stage with exceptional case of commercial societies who would not find poverty problematic since he felt that wage earners would not experience actual misery.
The evidence suggests that poverty is a multidimensional social phenomenon where its definitions and causes vary by gender, age, culture, and other social and economic contexts.
“Don’t ask me what poverty is because you have met it outside my house. Look at the house and count the number of holes. Look at my utensils and the clothes that I am wearing. Look at everything and write what you see. What you see is poverty” A poor man, Kenya 1997. This definition entails that it is vital to explore the definitions of poverty provided by poor people’s themselves to understand what poverty mean beyond sticking on what is stated by various scholars about poverty.
The resource document from World Bank summarized the definition of poverty given by the poor into five main findings through inductive approach. First, poverty is a complex multidimensional phenomenon due to interlinked nature of many determinant factors. Second, poverty is regularly defined as the lack of what is necessary for material wellbeing especially food, but also housing, land, and other assets. Poverty is the lack of multiple resources leading to physical deprivation. Third, poor people’s definitions reveal important psychological aspects of poverty. Poor people are highly aware of their lack of voice, power, and independence, which subject them to exploitation. Their poverty also leaves them vulnerable to rudeness, humiliation, and inhumane treatment by both private and public agents of the state from whom they seek help. Fourth, the absence of basic infrastructure particularly roads, transport, water, and health facilities emerged as critical. While literacy is viewed as important, schooling receives mixed reviews, occasionally highly valued but often notably irrelevant in the lives of poor people. Finally, poor people focus on assets rather than income and link their lack of physical, human, social, and environmental assets to their vulnerability and exposure to risk.
Contemporary theories and institutions defined poverty in a broad sense that poor individuals cannot be studied in isolation from their socioeconomic environment. Among contemporary institutions, World Bank provides a more detailed definition of poverty adaptable to different country conditions, whereby poverty is defined as “pronounced deprivation in wellbeing, comprising many dimensions. It includes low incomes and the inability to acquire the basic goods and services necessary for survival with dignity. Poverty also encompasses low levels of health and education, poor access to clean water and sanitation, inadequate physical security, lack of (political) voice, and insufficient capacity and opportunity to better one’s life" (World Bank, 2004 as quoted by Davis, E. P., 2014). On the other hand, Todaro & Smith (2012) defined absolute poverty as the situation of being unable or only barely able to meet subsistence essentials of food, clothing, shelter, and basic health care.
In narrow sense, poverty for an individual or household is defined as the state of having an income or consumption level below a certain standard, usually known as the poverty line (Ravallion, 1992; Lipton and Ravallion, 1995).
Based on the World Bank report, poverty could be classified under three major categories; extreme (absolute) poverty, moderate poverty and relative poverty. Absolute poverty refers that households are not able to meet their basic needs for survival, they are chronically hungry, unable to access health care, lack the amenities of safe drinking water and sanitation. Cannot afford education for some or all children, and lacks rudimentary sheltera roof to keep the rain out of the hut, a chimney to remove the smoke from the cook stove and basic articles of clothing, such as shoes. This type of poverty is only found in developing countries. Moderate poverty is the second type of poverty which refers to conditions of life in which basic needs are met but just barely. The third one is relative poverty which addresses households below a given proportion of average national income. Relative poverty in high income countries refers to lack of access to cultural goods, entertainment, recreation and quality health care, education and other perquisites for upward social mobility (Sachs & Jeffery , 2015)
Different economic schools of thoughts have different views on poverty since the development of classical theory in 18th and 19th century; however, all thoughts were developed based on the idea, assumption and limitation of the preceding one. Classical economic theory which includes the prominent work of Adam Smith and David Ricardo emphasized individuals’ responsibility for poverty as a foundation for laissezfaire policies, while neoclassical theory is more diverse and provides an explanation for poverty, mainly market failure beyond individual control (Davis, 2014).
E Philip Davis and Miguel Sanchez-Martinez in their review of economic theories of poverty stated “Broadly speaking, classical theory typically assumes that the outcomes of the exchanges taking place in the marketplace are efficient, and hence wages faithfully reflect individual productivity. Accordingly, poverty is mainly seen as a consequence of poor individual choices (e.g. the poor lack “selfcontrol”) that affect productivity negatively, although it is also acknowledged that pure differences in underlying genetic abilities are also potential causes of poverty” (Davis,2014) . Classical school of thought perceives welfare programs as a potential cause for or reinforcement of poverty through welfare dependence. Beyond a minimum level to prevent destitution, state intervention is generally viewed adversely as a source of economic inefficiency; by generating incentives that are misaligned between poor individuals and society as a whole. The government is, at most, justified to intervene whenever poor people need supportive activities or threats to correct for perverse economic incentives. A large majority of the policy prescriptions under this view focus on efforts to raise the productivity of deprived individuals in order for them to join the labor force.
Taking the classical traditions as a base, neoclassical theory focuses on the role of the uneven initial endowments of talents, skills and capital, which determine productivity of an individual in generating poverty, within a marketbased competitive economic system. Market failures such as externalities, moral hazard and adverse selection, as well as incomplete information are also viewed as aggravators of poverty (Davis, 2007).
Keynesian or Liberal theory adhere that underdevelopment with its multiple facets causes poverty beyond market distortion. Keynesians suggests that growth can promote economic development and thus eradicate poverty; hence this theory further justifies the role of government intervention at the macroeconomic level through fiscal and monetary policy, mainly to tackle involuntary unemployment.
Marxian or Radical theory suggested that the cause of poverty is capitalism and related social and political factors based on class division. This school of thought advocates that “the market is inherently dysfunctional” (Blank, 2010). According to this school of thought, poverty in capitalist economy can only be alleviated through undertaking strict market regulation like minimum wage since it is believed that capitalist societies keep the cost of labor abnormally lower than its value added through the threat of unemployment (the “reserve army of unemployed”). Marx argued that an inherent dysfunction of the labor market is due to the presence of unemployed workers, which is ultimately caused by the need of capitalists to have surplus labor through artificially lowering wages. Among the central elements of Marxist theory is that the primary aim of the state regulation should be to enhance the working conditions of laborers and promote higher wages among them (Blank, 2010).
A wider range of authors in the political economy field suggest that structural factors, including stratified labor markets as well as prejudice and corruption are major causes of poverty. In the above cases, the policy implication is that antidiscrimination laws and labor market reforms are essential to overcome structural barriers that impede employment and cause poverty (Davis, 2014).
Proceeding to others’ view on economic theories of poverty, Blank has developed six major theoretical approaches that describe the principal causes of poverty which can be discussed under three major economic thoughts (Blank, 2003, in Director (2006). Blank started her perspective with economic underdevelopment and the absence of effective functioning markets as the basic cause of poverty, where she suggested that poverty can be alleviated through the expansion of markets to the poor regions. Lack of human capital development is raised as the second perspectives where individuals are not ready or unable to take part the work force. The third perspective is that the market is inherently dysfunctional which creates poverty. Her fourth perspective identifies the social and political forces that can happen outside the market, which includes, political partiality and racism that contribute to poverty. The fifth perspective focused on the attribution of poverty on individual behavioral characteristics and choices, including marriage, family size, alcohol and substance abuse. The basic principle of this perspective is that the problem of poverty is within the control of the poor themselves, keeping in mind their values about work and education. The six and final perspectives proposes that efforts to alleviate poverty can cause poverty which is referred as welfare dependency or poverty trap.
Blank summarized the six perspectives of poverty using three major schools of thoughts. The first two perspectives (economic underdevelopment and lack of human capital) are common approaches in liberal economics thoughts whose primary figure John Maynard Keynes promoted the belief that the market can promote economic development (Jensen, 1998). Liberal economic tough promoters, especially, Marshall and Keynes believe that poverty is caused by economic underdevelopment and lack of human capital (Director, 2006). The second two perspectives (market dysfunction and social and political factors outside the market) are basic ideas of Marxian theories (Capitalism causes poverty) or political economy theories (social and economic forces cause poverty). The last two perspectives (individual behaviors cause poverty and welfare dependency causes poverty) reflect the traditional views of classical economics. The classical economists feel that government intervention to alleviate poverty only rewards the bad behavior of the poor and should be discontinued, while neoliberal economists focus on social and political forces.
In different outlooks, some literatures provide poverty analysis using three major schools of thoughts; Welfarist school, the Basic Need School, and the Capability schools (Asselin & Dauphin, 2001). A person is judged to be poor whenever he or she is lacking, in the shortage of some particular things compared to the reasonable minimum level. Although, the three approaches vary in many ways, the major difference lay on their perspectives for lacking or missing part of the poor people.
Welfarist approach considers economic wellbeing sometimes referred as economic welfare as the lacking part to define poverty. In line with the framework of welfarist schools, Lipton & Ravallion (1993) explained that “Poverty can be said to exist in a given society when one or more persons do not attain a level of economic wellbeing deemed to constitute a reasonable minimum by the standards of that society.”
The lacking part for basic need approach is basic goods and services specifically identified and deemed to meet the basic needs of all human beings. Though there are different views to determine the basic needs across various disciplines, a person who lacks this basic goods and services is considered to be below poverty.
For capability approach, the missing part is not utility or fulfillment of basic needs rather human abilities or capabilities. The capability school considers as poor a person that doesn’t have the possibility to achieve a certain subset of functioning. The functioning varies from such elementary physical ones as being wellnourished, being adequately clothed and sheltered to more complex social environments such as taking part in the life of the community, being able to appear in public without shame and so on (Asselin & Dauphin, 2001).
Measuring the status of poverty at various levels could be a basic step to design, development policies and poverty reduction strategies, to track progressive changes, to make comparisons among different geographical settings, regions and countries.
A handbook produced on poverty and inequality discussed four major importance measuring poverty. It helps to keep poor people on the agenda, identify poor people to design appropriate interventions, monitor and evaluate projects and policy interventions geared to poor people and evaluate the effectiveness of institutions whose goal is to help poor people (Haughton & Khandker, 2009). Despite its importance, the challenging issue is how to measure poverty which can tell us the rate and severity of poverty in a specific area.
Foster, Lokshin & Sajaia (2013) argued that poverty measurement should pass the following three vital steps. The first step is choosing the space in which poverty will be assessed. The common traditional spaces include income, consumption, or other welfare indicators measured in monetary units. The second step is identification of the poor using the selected poverty line which indicates the minimum acceptable level of income or consumption. The third step is aggregating the data into an overall poverty measure. The head count ratio is the most common aggregation method, while following the work of AmartyaSen other aggregation techniques are becoming popular to evaluate the depth and severity of poverty.
Indicating Ravallion (1998) as back reference, the handbook on poverty and inequality by Haughton & Khandker (2009) also discussed the steps to measure poverty as defining an indicator of welfare, establishing a minimum acceptable standard for defined indicator to separate the poor from nonpoor, and thirdly, generating a summary statistic to aggregate the information from the distribution of this welfare indicator with respect to the poverty line.
Despite there are different approaches to measure welfare, it is possible to discuss using two broad and distinct approaches, which are: ‘wlfarist’ and ‘nonwelfarist’ approachs. The major distinguishing feature of the two approaches relay on the importance that attached to the individual’s own judgment in relation to his or her wellbeing (Ravallion, 1992). The welfarist approach emphasizes that, value attached to commodities by the consumer himself and the subsequent preference of ordering is sufficient in order to assess a person’s wellbeing. While, the nonwelfarist approach attempts to assess the wellbeing of an individual based on certain basic achievements such as being adequately nourished, clothed and sheltered and this approach gives smaller attention for information on utilities.
Regarding to standards of living measurement, the welfarist approach typically emphasizes aggregate expenditure on all goods and services that has to be consumed including consumption from own production, and it valued at appropriate prices; whereas, the nonwelfarist approach focused on the specific commodity forms of deprivation, such as inadequate food consumption (Ravallion,1992).
The most important question in poverty measurement is the choice of welfare indicator which enables to clearly specify the wellbeing of individuals. Income and/or consumption expenditure are the most common widely used monetary indicators of welfare. Consumption expenditure and income can be acceptable as a measure of welfare, since both measure the capacity to obtain goods and services. In several cases, the measures would produce similar results. However, in some cases consumption and income measure fails to take into account some important aspects of welfare. Such as consumption of commodities supplied by, or subsidized by the public sector including schools, health services, and roads and also several dimensions of the quality of life, such that, consumption of leisure and the ability to lead a long and healthy ( Engvall, 2006 ).
Consumption expenditure as a proxy indicator of welfare is widely used in many poverty analysis literatures. Haughton & Khandker (2009) argued that in societies with large agriculture or selfemployed populations, income is seriously understated due to various reasons. People may forget received income from different sources especially when they are asked in a single interview; they may be reluctant to disclose the full extent of their income due to fear of tax; they may not need to report income earned illegally and some parts of income are difficult to calculate.
Coudouel, Hentschel & Wodon (2002) explained that consumption expenditure is a better indicator of welfare than income, especially in the case of poor and agrarian economies income for rural household fluctuates during the year based on the harvesting cycle which implies the difficulty for households in correctly recalling their income. Additional difficulty in estimating income consists in excluding the inputs purchased for agricultural production from the farmer’s revenue. Large share of income remain will not be monetized if the household consume their own their own production or exchange it for other goods.
Consumption is more closely related to a person’s wellbeing and may better reflect a household’s actual standard of living to meet basic needs. Consumption expenditure can reflect not only goods and services that a household can command based on its current income but also whether that household can access credit markets or household savings at times when current income is low or even negative, may be in case of seasonal variation, harvest failure or any circumstances that cause income to fluctuate widely (Coudouel & et al, 2002).
Ravallion (1992) argued that consumption contains smaller measurement error as compared to income and there is a belief that households are more willing to reveal their consumption behavior than their income.
Ravallion (2010) has defined poverty line as the money an individual needs to achieve the minimum level of “welfare” to not be considered as “poor.” In other words, poverty line may be explained as the minimum expenditure required by an individual to satisfy his or her basic food and nonfood needs (Haughton & Khandker, 2009).Most economists utilize a utility function defined on own consumption to address the question behind what concept of welfare should support the poverty line (Ravallion, 2010).
However, the central question in poverty analysis is how to set the poverty line in order to categorize households in two categories either poor or nonpoor. There are a number of approaches to set poverty line under two broad categories the objective or nutrition based and subjective approaches. Cost of Basic Needs (CBN) and Food Energy Intake (FEI) are among nutrition based types of poverty line setting, while Minimum Income Question (MIQ) and Economic Ladder question (ELQ) are among subjective poverty line setting methods (Ravallion, 2012).
The concept of equivalence and economies of scale is an integral part of poverty measurement and analysis where households of different size and composition have different needs, which are not easy to reflect in poverty measures. In poverty measurement, it is vital to think and consider adjustment of basic needs for different age groups and gender which refers equivalence scales and adjustment for household size which indicates economies of scale (Coudouel & et al , 2002).
It rare to find a poverty analysis literature at an individual level since conducting poverty analysis based on individual unit has various difficulties including survey costs. Tolerating the costs, any one may undertake detail survey at individual level through identifying all members of the household, but it is difficult to distribute a particular flow of earnings to one particular member in a household especially in agrarian rural societies where their income has irregular pattern. Besides, if the researcher utilize consumption based survey, it is not easy to find out who consumes which component of common food items of the study area. Even though individual unit is an ultimate concern for poverty analysis, information on consumption and income usually collected at household level.
On the other hand, households differ in size and composition where a simple comparison of aggregate household consumption may lead to wrong conclusion about the wellbeing of individual members in a given household. Flater (2006) argued that, the simpler comparison of aggregate household income or consumption is quite misleading about the true wellbeing of individual members of a given household.
Recognizing challenge due to difference in household size, most researchers use a straight forward method of dividing the total household expenditure by the number of individuals in the household which provides per capita consumption expenditure of the household as welfare measure of each household member (Haughton, & Khandker, 2009). Extending their analysis, Haughton & Khandker mentioned two major limitations of per capita consumption as welfare measure for individual member of the household. The first issue is the presence of difference in needs among household members, where different individuals have different needs. A young child typically needs less food than an adult, and a manual laborer requires more food that an office worker. The second issue is concerned on economies of scale in consumption of certain goods. For instance, it costs less to house a couple than to house two individuals separately.
Welfare measures using consumption per capita simply gives equal weight for all household members where both children and adult members treated equally. The most widely suggested solution for the above challenge is using equivalent scales which provide different weight for different members of the family. Despite there are different ways of formulating adult equivalence, consumption expenditure per adult equivalence is computed by dividing household consumption expenditure by the number of ‘adult equivalents’ in the household instead for the total household members.
The calculation of equivalence scale is still debatable where various literatures and institution apply different weights for individual household members to generate adult equivalents which enable to compare poverty households. Of different methods of generating adult equivalence scale, Haughton & Khandker (2009) discussed the following two major widely used adult equivalent calculation techniques.
The first scale is OECD scale. Regardless of its controversies, the Organization for Economic Cooperation and Development (OECD) scale is a popular method of calculating adult equivalent scale. It can be written as:
Where, AE refers to “Adult Equivalent.” A one adult household would have an adult equivalent of 1, and a two and three adult household would have AE of 1.7 and 2.4 respectively. Thus, 0.7 reflects economies of scale; the smaller the parameter, the more important economies of scale are considered to be.
The second scale is mostly used to analyze the result of the Living Standard Measurement Survey (LSMS). Its formula can be written as:
Where, measures the cost of a child relative to an adult, and ≤ 1 is a parameter that captures the effect of economies of scale. For instance, a family with two adults and two children and if = = 1, AE = 4 which indicates our welfare measure is equal to per capita expenditure. But, if = 0.7 & = 0.8, then AE = 2.67 which shows that the measure of expenditure per adult equivalent will be considerably larger.
In most household surveys, per capita consumption decreases with household size, which is probably more appropriate to interpret this as evidence that there are economies of scale to the expenditure member (Haughton & Khandker, 2009).
Coudouel & et al (2002) in their poverty measurement and analysis book clearly discussed that the implicit assumption when calculating per capita income or consumption of a household is that there is no economies of scale in expenditure exist. In this assumption, a twoperson household with a consumption of 200 would be equally well off as a oneperson household with a consumption of 100. However, larger households generally believed to have an advantage over smaller households because they can benefit from sharing commodities (such as stoves, furniture, housing, and infrastructure) or from purchasing produce in bulk, which might be cheaper. Though there is no single agreedon method to estimate economies of scale in consumption, the relationship between household size and the risk of being poor will be affected if economies of scale exist in consumption.
Economies of scale exist in consumption, such as housing; lighting and heating are some examples of household expense rather than individual’s. For such items, a number of people living together can do so more cheaply, in per capita terms as compared to those who live separately. Lanjouw and Ravallion (1995) argue that even in food consumption there can be important economies of scale. Therefore, adjustment for both equivalence and economies of scale are needed.
In spite of the fact that poverty is a hot spot socioeconomic agenda in every direction of the world, anyone can find substantial empirical literature studies, journal articles and dissertations produced by different scholars, universities and other development organizations. Focusing on the research topic and intended objectives, various studies from developing countries, including cases from Ethiopia are purposely selected and reviewed thoroughly to provide an empirical base for the study.
Bogale and et al. (2005) carried out a study entitled as “Determinants of Poverty in rural Ethiopia” in three purposely selected administrative districts of Ethiopia (Alemaya, Hitosa and Merhabete ) using a oneyear (1999/2000 cropping season ) with three round household survey of 149 randomly selected sample households. They found that poverty rate of sample was 38% and 43% using per capita household calorie consumption, 2,300 kcal (Dercon and Krishmann, 1998) and per capita household expenditure (average price of food bundles to attain 2,300 kcal respectively. Their study reveal that overall poverty depth in the study areas was 0.0466, which indicates that a resource which accounts 4.66% of the poverty line for each individual and distributed to the poor as per their need in order to come up each individual up to poverty line can lead to say at least poverty could be eliminated theoretically (Bogale and et al, 2005). The study realized that, if the bottom 30% of the poorest households are correctly addressed, the severity of poverty will be declined by 78.65%, while the severity of poverty will decrease only by 1% if the top 30% of the poor are to benefit from poverty reduction programs. This indicates that, poverty has become sever for the poorest of the poor, which has a remarkable importance during target selection for development programs intended to reduce poverty.
By using a binary logit regression model, landholding per adult equivalent and ownership of oxen are significant variables to determine the probability of a household to be poor. Household size and composition have shown the desired sign; however, their effect is not statistically significant where this weak relationship can express that child, even at a lower age engaged in labor work which able to contribute to the production capacity of the households. Education level of the household head was found to be statistically significant variable to determine poverty status of the households. It reflects the prominent role of human capital in determining poverty (Bogale and et al, 2005).
In contrast to the above study “Growth and chronic poverty: Evidence from rural communities of Ethiopia” using longitudinal household survey data collected by the Ethiopian Rural Household Survey (ERHS) with the years (1994 -2009) from fifteen selected villages, the number of children in a family is found to be statistically significant variable to determine poverty status in Ethiopia. Having children has a strong effect to increase the likelihood of being found in chronic poverty during this period, with children under five and especially, girls adding the most. The study has also crossed checked the effect of children using consumption per adult and the result on poverty status shows the same result as the above. It also indicates that with the principle of ceteris paribus, additional child appears to increase the probability of being found chronic poor by 12% (Dercon & et al, 2011).
Bogale and et al. (2005) in their study to assess determents of poverty in rural Ethiopia revealed that maleheaded households have high probability of being poor considering per capita food energy consumption, while femaleheaded households have the same scenario if household consumption expenditure measurement is considered. This indicates that, though maleheaded households have better capacity to comply with the minimum consumption expenditure required, they failed to realize it in terms of actual food consumption. However, femaleheaded households allocate their available resources in such a way as to obtain more calories per capita than their counterpart. In contrast, Alemayhu & et al (2005) in their study of determinants of poverty in Kenya found that femaleheaded households are more likely to be poor than households of which the head is a men.
Tsehay and Bauer (2012) examine the dynamics and determinants of rural household poverty and vulnerability in the Northern highlands of Ethiopia using Ethiopian household survey data 1994-2010 in the two peasant associations; Shumsheha and Yetmen. They found that in the panel period, Shumsheha has shown a consistent decline in poverty incidence until 2004 however, it increased dramatically in 2010. On the other hand, the trend for Yetmen has been fluctuating throughout the panel. It means that poverty indices significantly varies over time and across the districts that it shows different causes may account for the household either being poor or not. Landholding, access to credit and agricultural extension services has welfare gains, but the household with large family size had lower consumption expenditure.
Hagos and Holden (2003) studied in the analysis of poverty determinants in the rural households of Tigray 1997-2000, and they found that around 61 and 66 percent of the population in the region during 1997 and 2000 lived below the poverty line of meeting basic consumption requirements respectively. Consequently, they were revealed that, human capital resources like household’s educated heads and the heads with any kind of acquired skills and physical asset endowments such as farm size, livestock holding including oxen were found to have significant welfare enhancing effects.
A study on poverty and its determinants among smallholder farmers in the eastern Hararghe highlands of Ethiopia by Bogale and Korf (2009), revealed that household composition in terms of (size per adult equivalent & dependency ration), access to irrigation and offfarm income significantly improves the household consumption expenditure and strongly correlated with lower probability of being poor. In the same area, Bogale and Genene (2012) applied the similar methodology in poverty analysis and they found that around 38% of the sample households live in absolute poverty. Multivariate regression revealed that family size, educational level of any household member, size of own land, age of household head, livestock holding, amount of credit received, frequency of extension visit were the major significant variables that affect the household consumption expenditure, hence welfare.
Fredu (2008) examined the importance of demographic characteristics, education, households asset holding, community characteristics, offfarm income and access to public service in the poverty analysis under the works of poverty, asset accumulation, household livelihood and interaction with local institutions in northern Ethiopia using the three round panel data over the period 2004 – 2006. Accordingly, his finding showed that over the period 2004-2006, the incidence, depth of poverty and severity of poverty persistently declined. Using Hausman-Taylor model the study reveal that, age of household head, family size and access to market had an adverse effect on the household consumption expenditure per adult. While, physical asset holding such as oxen, current value asset holding and land size had a significant positive welfare gains. In addition, access to inputs such as fertilizers and seeds, access to irrigation had a positive and significant welfare improvement effect.
In analysis of determinants of poverty in the rural Ethiopia using 1999/2000 rural household income and expenditure survey data, Demeke & et al. (2003) found that demographic characteristics such as family size at different age categories, livestock ownership, land holdings and education significantly associated with household consumption expenditure. All the above determinant variables except household size affect household welfare positively and also male headed households have greater consumption per capita than their counterparts.
A binomial and polychotomous logit model household level analysis conducted to identify determinants of poverty in Kenya using about ten thousand households from1994 Welfare Monitoring Survey (Government of Kenya 1998, 2000) revealed that poverty is concentrated in rural areas in general, and in the agricultural sector in particular. Being employed in the agricultural sector, accounts for a good part of the probability of being poor. The size of land holding is not a determinant of poverty status may suggest the importance in poverty reduction not only of improving the quality of land, but also of providing complementary inputs that may enhance productivity (Alemayhu & et al, 2005).
The study on determinants of rural household poverty severity in Nigeria using data from randomly sampled 233 rural farmers in Benue State revealed that coefficients of dependency ratio and household size had a significant and positive relationship with poverty severity. However, access to credit, access to agricultural extension service, and household with market access, farm size and membership in cooperatives or other farmers’ associations had a significant and negative relationship with poverty severity. This indicates that the poverty intensity strongly associated with household characteristics, asset holding, access to different public services and infrastructural facilities (Asogwa & et al, 2009).
The study by Runsinarith (2011) examines the determinants of rural poverty in Cambodia using households surveyed in 2001, 2004 and 2008 and applying fixed effect estimation panel regression analysis. The study revealed that dependency ratio, large family size and shock had negative and statistically significant effect on household consumption expenditure. On the other hand, livestock, irrigated land and access to micro finance service were exerting positive and significant effects on per capita consumption expenses.
Participatory Poverty Assessment (PPA) was conducted in Niger using participatory assessment tools which involved 3,950 respondents where 1,181 people participated in individual interview and 1,787 people were take part focus group discussions. The findings of the study revealed that 59% of respondents perceived living conditions as a sort of sieve that has allowed poverty to seep in. The community considered poverty by associating with quality of life and as a process of ongoing deterioration in living conditions. The study indicated that the community understand that poverty begins with penury, then turns into an inability to act, and finally leads to dependency and destitution. In other words, the population does not view poverty as a static condition, but instead as a process. It is first an economic phenomenon that then takes on a social dimension, and in the end becomes a reality with psychological repercussions.
Besides, PPA in Niger explained that, rapid population growth without sufficient economic growth, recurrent drought, deterioration of productive potentials, inadequate investment, physical remoteness, household characteristics (widowhood, divorce, lack of job opportunities, old age, outmigration) as well as certain beliefs and sociocultural attitudes are among major determinants of poverty in the society.
This chapter entirely concerned with the methods, approaches and models of the study to provide clear insight about status and determinants of poverty using sample households. Sampling design and methods, data sources and methods of data collection, econometric models, and data analysis techniques and interpretation systems are among thoroughly discussed issues of the chapter.
Depending on major research inquiries; the study mainly followed both a descriptive and econometric type of research where poverty status of rural households and major determinant characteristics of poverty are investigated using a crosssectional household survey. Beyond describing what has been happening, the study engaged alternative econometric regression approaches to observe the determination level of each variable keeping other variables constant as an assumption. The study also provided detail description analysis on poverty status of rural households and the relationship of key characteristics which significantly determine poverty. Comparative analyses are also provided on poverty status of the households using various poverty measurement tools.
Kothari (2004) explained that research approaches are broadly classified under two categories: quantitative and qualitative. The former involves the generation of data in quantitative form which can be subjected to rigorous quantitative analysis, while the latter is concerned with subjective assessment of attitudes, opinions and behavior where results either in nonquantitative form or in the form which are not subjected to rigorous quantitative analysis. The inferential research approach is among the subcategories of quantitative approach and its main purpose is to form a database from which to infer characteristics or relationships of population.
Accordingly, the study utilized both quantitative and qualitative approaches. In its quantitative approach in general and inferential approach in particular, the study has involved sample households thorough out the assessment of poverty status and its determinants where findings are inferred to the entire population. Besides, qualitative approach is introduced to triangulate and complement the findings of quantitative analysis.
A sample is a segment of the population selected to represent the population as a whole. Ideally, the sample should be representative and allow the researcher to make accurate estimates of the characteristic and behavior of the larger population.
Based on the data of Gozamin Woreda Agriculture Office, the Woreda has a total population of 151,442 (50.3% female), of which 97% lives in rural areas. Out of the total 30 Kebeles of the Woreda, five are considered as semiurban (outgrowing urban); while, this study was subjected to the remaining 25 rural Kebeles since its major focus was assessing the status and determinants of rural household poverty. The total number of households in 25 rural Kebeles of the Woreda is 22, 752, of which 2,047 (8.99%) are female headed households (Gozamin Woreda Agriculture Development office, 2015). From selected total sample households, 14.46% are female headed households and the figure is above the Woreda level female headed composition (8.99%).
Household Survey Sampling: The study utilized a mix of stratified, proportionate and systematic random sampling techniques where it was passed through two major steps. Depending on the three major agroecological zones of the Woreda, Kebeles were categorized under Dega (cold) , Woyena-Dega (mild) and Kolla (hot) agroecological zones. It is also common to observe the production potential of the study area, Gozamin Woreda, in two major categories; the less productive highland and the productive low land area. As initial step, 25 rural Kebeles of the woreda were stratified under the three major agroecological zones and four rural Kebeles (one fromDega; two from Woyenadega and one from Kolla) agroecological areas were selected randomly.
Secondly, households of the selected kebeles were stratified based on the sex of the household head (male headed and female headed) which intended to get appropriate representation of female headed households. Accordingly, proportionate number households were selected through systematic sampling method from each Kebele. Throughout the study, households are major units of analysis where samples were selected based on systematic random sampling from the strata list of respective households.
Regarding to the sample size determination, the researcher has taken into account both availability of limited resources and number of explanatory variables used in the econometric regression model. Accordingly, the study utilized a sample determination formula which is adapted by (Yamane, 1967:886).
It is a simple formula represented as follows:
Abbildung in dieser eseprobe nicht enthalten
Where[Abbildung in dieser eseprobe nicht enthalten], Represents the sample size,
Denotes the total population of the study and
Represents the level of precision
It is common to use 95% confidence interval (precision level of 0.05) to determine sample size; however, this study has taken 93% confidence interval (0.07 precision level) considering the cost and availability of time without compromising the probability of generating reasonable sample which can represent the entire population of the study The total number of households in four randomly selected Kebeles is 3,674 (WOA, 2015).
Accordingly, using the above formula a total of 193 households were needed to conduct the study. By, allocating 10% contingency of the calculated sample size (193*10% = 19), the total sample size of the study was taken as the sum of calculated sample size plus 10% contingency (193+19= 212). However, by extending outmost efforts and using existing opportunities at grass root level, the sample size of the study was increased to 242 households and selected by using proportionate and systematic sampling method from sample frame of respective sample rural Kebeles.
Participatory Poverty Assessment Sampling: Considering major agroecological zones of the study area, two among four sample kebeles of survey based assessment were selected to conduct participatory poverty assessment. Namely, Girraram and Denba Kebeles were purposely selected kebeles from Kolla and Dega agroecological zones respectively. A total of 42 participants (52.38% male headed, 26.19% male headed, 9.52% elders and 11.91% youths) were randomly selected to undertake participatory poverty measurement using multiple participatory assessment tools. Representativeness of PPA participants was maintained through randomly selecting participants from different community categories where male and female headed households, elders and youths were included. In order to reduce information biases and help study to address more households for over all poverty assessment, PPA participants were selected from sample frame of households who were not selected for survey based assessment.
In order to address the stated objectives, the study mainly utilized primary data collected using household survey questionnaire, focus group discussion and other participatory poverty assessment techniques. Primary data of household’s demographic composition, consumption expenditure (food and nonfood expenditure), land holding, access to resources and services, farm implements and household durable assets were collected using semistructured questionnaire. The survey was conducted through interview where 20 (3 female) enumerators who have educational qualification of grade 10 complete and above were selected, oriented and deployed to administer the survey. The survey questioner filled by each enumerator was checked by the researcher and assigned supervisors where in completed questionnaires were returned back to enumerators to refill the missing part or wrongly interviewed sessions. The quality of the survey data was maintained through assigning many data collectors and supervisors which enabled them to take enough time for a single interview; through providing detail orientation and conducting close followup.
On the other hand, Participatory Poverty Assessment (PPA) tools including focus group discussion, wellbeing ranking and participatory scoring matrix were utilized to generate qualitative information to assess the perception and subjective judgment of the community on the status and determinants of poverty as per the contexts of their locality. The researcher has developed guide notes, checklist, matrix formats and openended questions in order to facilitate PPA effectively. The researcher facilitated each session of PPA, while detail discussion points were jotted by assigned note takers. As it was mentioned earlier, the main purpose of conducting such qualitative data collection tools was to triangulate and complement the findings of quantitative analysis through addressing the subjective evaluation and perception of the community towards existing poverty.
Measuring poverty using subjective data is less common in most empirical studies, while it has great contribution for poverty measurement through recognizing the understanding of the specific society on what minimum level of income or adequate consumption is enough to meet basic needs. Ravillon (2012) argued that subjective welfare measurement through participatory data collection tools have a great deal of importance in order to triangulate the objective based poverty measurement results.
On the other hand, the study utilized secondary data from various Government institutions including Ministry of Finance and Economic Development (MoFED), Woreda Office of Finance and Economic Development (WOFED), Woreda Office Agriculture (WOA), the Central Statistics Agency (CSA) and other reliable institutions. Moreover, findings of previous empirical studies and journals were used to triangulate and make comparative analysis among theoretical and empirical bases and findings of the study.
 Federal Democratic Republic of Ethiopia Central Statistics Agency (FDRE, CSA) population projection for the year 2015
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