Commercialization and welfare outcomes of smallholder farmers. In a case of Guraghe Zone

Contents

Acknowledgement

Acronym and Abbreviation

List of Figures

List of Tables

ABSTRACT

CHAPTER ONE
1. INTRODUCTION
1.1. Background of the Study
1.2. Statement of the problem
1.3. Research Question
1.4. Objectives of the study
1.4.1. General Objective
1.4.2. Specific Objective
1.5. Significance of the study
1.6. Scope and Delimitation of the study
1.7. Organization of the Paper

CHAPTER TWO
2. LITERATURE REVIEW
2.1. Theoretical Review
2.2. Empirical Literature Review
2.3. Conceptual Framework

CHAPTER THREE
3. RESEARCH METHODOLOGY
3.1. Description of the Research Area
3.2. Research Design
3.3. Data Sources and Collection Methods
3.3.1. Sampling T echnique
3.3.2. Sample Size
3.4. The Model
3.4.1. Theoretical Framework
3.4.2. Methods of Data Analysis
3.4.2.1. Model Specification for Commercialization of Smallholder
3.4.2.2. Model Specification for Smallholder Welfare
3.5. Discerption of the Variables
3.5.1. Dependent Variable
3.5.2. Explanatory Variables
3.6. Diagnostic test

CHAPTER FOUR
4. RESULTS AND DISCUSSION
4.1. Descriptive Results
4.1.1. Socio-economic and Demographic characteristics of households
4.2. Probit Estimation Result for Commercialization
4.3. OLS estimation result for welfare outcome
4.4. Welfare of households with level of Commercialization
4.5. Diagnostic Tests
4.5.1. Diagnostic test for Probit regression
4.5.2. Diagnostic test for OLS model

CHAPTER FIVE
5. SUMMARY, CONCLUSIONS AND RECOMMENDATIONS
5.1. Summary of findings
5.2. Conclusions
5.3. Recommendation

References

Appendix
1. Questionary
2. Econometric test results

Acronym and Abbreviation

Abbildung in dieser Leseprobe nicht enthalten

List of Figures

Figl. Ethiopians Market Characteristics

Fig 2 Conceptual Framework

Fig 3 Guraghe Zone Administrative Map

Fig 4 Irrigation Users

Fig 5 Usage of Fertilizer

Fig 6 Nature of the Land

Fig 7 Cereal crops produced in Guraghe zone

List of Tables

Table 3.1 Sample Size Determination

Table 3.2 Explanatory Variable and Expectations

Table 4.1: Descriptive Statistics of Categorical Variables

Table 4.2: Summarization of Continues Variables

Table:4.3 The Probit Model Result

Table 4.4 Multiple Regression Estimates and The Effects of Explanatory Variables

Table 4.5: Welfare of Households with level of Commercialization

ABSTRACT

The current Ethiopian economy is based on agriculture and the transition from subsistence to commercial agriculture is important. This study, focused on identifying the determinants of commercialization and evaluating the welfare outcomes of smallholders at different level of commercialization in SNNP, Guraghe Zone. Descriptive and econometric methods were employed to analyze the data collected from a sample of 188 households using structured household questionnaires. The design of data was both qualitative and quantitative multistage sampling methods were used. The findings from the descriptive shows 79% of the households participate in output market and 21% is not. From the (CCI) result commercialization of households is leveled into low, medium and high on the average consumption of food, non-food and durable goods. A probit regression model was applied to analyze the determinants of the commercialization. The findings from the probit regression model the explanatory variables: sex of households, education, extension package, access to credit, transport access, fertilizer, family size and distance from home to market are important and statistically significant impact on commercialization of householders. From the variables only distance is the negative impact but rest of them have a positive impact. In the second dependent variable (welfare outcome) the OLS model were employed. The result shows, the explanatory variables human capital, Commercialization of smallholder farmers, Family size, Total income, and food security were a significant. Finally, the findings indicate that the farmers can be highly integrated with the market, then gate better skill on price of product and appropriate information to produce market- based products and farmers with high level of commercialization makes better- welfare outcomes.

Key words: - Smallholder, Commercialization, Welfare outcome, Market participation, Subsistence farming, Probit model, OLS estimation, Guraghe Zone

CHAPTER ONE

1. INTRODUCTION

1.1. Background of the Study

Commercialization of smallholder agriculture is part of agricultural transformation in which a given farm household shifts its production from a highly subsistence-oriented production towards more commercialized and advanced production system that is based on comparative advantage among smallholder farmers. targeting market for its input demand and output supply (Jaleta et al., 2009).

In the long run, subsistence production may not be feasible to achieve sustainable household food security and welfare. It is considered as an indispensable pathway towards economic growth and development for most low-income countries relying on the agricultural sector. Commercial agricultural production is likely to result in welfare gains through the realization of comparative advantages, economies of scale and fluctuation of economies. Commercialization enhances the links between the input and output sides of agricultural markets (Braun et al., 1994).

Smallholder farmers always can earn more profit, increases their family income and promotes standard of living. So, commercialization of agriculture is not only just making a shift from subsistence to market oriented, but also making better welfare outcomes for smallholder farmers in the form of increasing consumption of basic needs and sufficient food, and durable goods, education, healthcare and non-food consumption for the smallholder farmers. When the degree of commercialization is low, the low output would be marketed and vice versa. Urban centers are deemed to be a primary driver of commercialization as they are a source of huge demand for many agricultural products (Gebreselassie et al., 2007).

Sub-Saharan Africa countries face critical challenges in a socio-economic affair. Most of Africans live on less than US$1 *per day. The highest percent of the continent’s poor work¹ in agriculture. Clearly, Africa’s agriculture has underperformed and under “business as- usual” projections for agriculture, Africa will increasingly depend on food imports to meet its basic consumption (Rosegrant et al., 2005).

It underpins the livelihoods of over two-thirds of Africa’s poor and assumes even greater importance in the continent’s poorest countries, such as Burundi, Ethiopia and Malawi. also, Africa’s agricultural performance has ranked the worst in the world according to most conventional measures. Given low levels of land and labor productivity, technology, input and infrastructure. African farmers produce output per capita valued at low level. Many countries and international development agencies give due concern to intensification and commercialization of smallholder agriculture as a means of achieving poverty reduction (Leavy et al., 2007).

In Ethiopia, there were many attempts to integrate the farmers into the market, in 1950s the emphasis had been on improving productivity and reducing economic dependence on agriculture whereas in the 1960s, it shifted to agro-industrial economy (AIE) and increment of foreign earnings (Sharp et al., 2007).

In the 1970’s the focus shifted to smallholder potential after inefficiencies were observed in mechanized farms. In the 1980’sthe country adopted the socialist agricultural development strategy. Since the current government (FDRE) in the 1990s, strong focus has been given to smallholder’s economy by improving the farming system. Supporting agricultural intensification to fulfill sustainable development goal of no poverty and zero hunger should a prime policy goals for developing countries (MoFEC, 2000).

In Ethiopia, by far the largest proportion of the crops produced utilizes livestock inputs in terms of purchase power. In rural Ethiopia, lack of plough oxen has direct impact on the size of land to be put under cultivation and is considered as a very strong indicator of welfare² among rural households. In areas where mixed farming (crops and livestock production), are jointly undertaken, farmers use livestock for coping with adverse situations during crises of crop failure by selling animal products. With regard to direct food supply and/or cash income generation, livestock will play an increasingly important role (Atsbaha, et al., 2008).

The commercialization of Agricultural crops grown by small-scale and resource-poor farmers has the potentially increase the household food security, reduce rural poverty, and contribute a significant effect on agricultural and the whole economic growth. The encouragement of the improved agricultural inputs, farming techniques, diversification out of low-yielding subsistence crops and specialization in more tradable crops makes small holders to commercialize (Geta et al., 2016). This study as well as motivated to direct contact farmers with buyers and aimed to participate farmers in products price decision making.

In this study, the focus has been due on identifying socio-economic factors determining market participation and welfare outcomes of smallholder farmers. Such kind of study is very necessary and requires a thorough understanding because the society in the Guraghe zone has a good knowledge about market participation but agricultural product commercialization is very limited. Most importantly, the farmers don’t produce surplus and didn’t supply to the market principally.

In the recent time (after 2000 E.C) in Ethiopia each kebeles have built agricultural training centers (FTC) and gives the service of agricultural, market and health related information. This makes the farmers to learn more, increase the ability to production; yet still less is known about the effect, therefore, this study should incorporate recent development on smallholder farmers education, agriculture and market.

1.2. Statement of the problem

The Agricultural Development Led Industrialization (ADLI) Strategy is among the pillars of SDPRP³. In order to accelerate and expand industrial development and increase overall economic growth, it is essential to develop the agricultural sector which is crucial to ensure the provision of inputs for industries as well as to fulfill food requirements. Furthermore, the sector is the subdivision of the economy where the major human power required for development is engaged (MoFEC, 2006).

In the Ethiopian context commercialization of smallholder farming for their economy is not yet high enough to enable farmers’ economic benefit from increases income and the farmers are not yet out of the subsistence-oriented agriculture (Mahelet, 2007); In addition to that market imperfections and high transaction costs have hindered smallholder farmers from exploiting the welfare outcomes of commercialization. This is not possible to integrate with the market and use the benefits of commercialization unless remove hurdles and make better environment.

AdemSmith (1776) was sure that specialization and division of labor complemented by commercialization improve the welfare of every one. This formally modeled in the neoclassical model of the farm as can be seen in any agricultural economics text books like Elise (1993), Colman and Young (1989), Sadhu and Singh (2002). Those neoclassical models of the farm which are simple extension of micro economic models of the neo classical school in to farming formally, under very restrictive assumptions, show that specialization and commercialization is beneficial to everyone.

Agriculture and its commercialization play a dominant role in supporting rural livelihoods and economic growth over most of Africa countries continue to depend on this sector for their economic progress as well as livelihood development of their nations, the relevance of commercializing and integrating smallholder to market remains a priority. As the largest segment of the population makes their livelihoods directly from the sector, the sector’s development through innovation, technology, and market orientation would present sustainable poverty reduction and achievement of the sustainable development Goals (Abera,2009).

Bekele et al (2013) in his study education of the household head was the positive relationship and significant impact on the sales value of horticultural crops and the literate household earn about 1,625 Ethiopian Birr more as compared to illiterate household head on average, from sales of horticultural crops.

Why producing for market is not as simple as looking at market prices of crops and deciding what to produce. Under such reality, commercialization promoted without farmer’s consent is highly probable to have negative effect on farmers’ welfare. Evidence by many studies show that even when farmers are given access to rewarding cash crop, using institution of contract farming to solve many market failures, they always produce stable crops side by side with cash crops. The survey of commercialization pattern from around the world. (Miyata et al., 2009).

Most of the previous studies are based on only one agricultural crop, but in this study tries to include more than one agricultural crop that are current market based and most of the literature on commercialization missed explanatory variable distance and on welfare didn’t include the explanatory variables human capital and physical capital. Not only that there was weakness on theoretical approach, for instance the studies⁴ are not clearly show the theories in their studies. In this study, the researcher tried to fill the gap by including missed variables and clearly showing the theoretical approach.⁵ The theories have three common objectives: that are expansion of farm output, income and advancing structural transformation raising the welfare of the farm population and fostering changes in rural attitudes and behavior that would have beneficial effects on the process of rural development and modernization.

1.3. Research Question

- What are the determinants that affect Commercialization of smallholder farmers’ in a case of Guraghe Zone?
- How does commercialization affect the welfare outcome of smallholder farmers?
- How does household participate in the input and output market?

1.4. Objectives of the study

1.4.1. General Objective

The main objective of this study is to identify factors that determine commercialization and welfare outcomes of smallholder farmer’s in the case of Guraghe Zone.

1.4.2. Specific Objective

- To identify the determinants of market participation (commercialization) of smallholder farmers in Guraghe Zone
- To examine the effect of (commercialization) on welfare outcomes of smallholder farmers in the study area.
- To assess the level of household participation in output markets.

This study can be a valuable input in substantiating these efforts with empirical evidence from Guraghe Zone. The study would contribute to agricultural sector and nongovernmental (NGOs) sectors in Guraghe Zone like productive Safety Net Program and World Vision institute of Ethiopia. Study would be used as reference on the area of limited knowledge and literature whose study is related to commercialization or welfare of small household farmer’s. Therefore, it would be an input for policymakers, academicians and researchers; in the direction of agriculture commercialization, improvement of welfare, reducing poverty and increase the economic situation of smallholder farmers in study area.

1.6. Scope and Delimitation of the study

This study used to identify demographic, socioeconomic and institutional factors determining the decision of smallholder’s participation in/out put markets and analyzing the welfare outcomes of smallholders at different levels of commercialization. The crosssectional study was employed from the sample three woredas in the study area. The smallholder farmer’s economic situation and identifying the demographic, socioeconomic, institutional and environmental factors determining the price of agricultural products in the output marketing the context of Guraghe Zone.

1.7. Organization of the Paper

This study organized into five chapters. Following the introductory chapter, the second chapter presents a review of literatures. The third chapter deals about study area, methodology and data used followed by Chapter four, results and discussion. Finally, chapter five presents the summary, conclusions and recommendation of the study.

CHAPTER TWO

2. LITERATURE REVIEW

2.1. Theoretical Review

Commercialization as a concept is multi-dimensional and no one definition has been able to capture all its facets. The definitions differ in focus and breadth, which has also influenced its measurement. It is more than whether or not a cash crop is present in a production system (Braun et al., 1994). Sometimes a proportion of the so-called traditional food crops are sold while on the other hand, some proportions of the so-called traditional cash crops are retained for home consumption. Similarly, agricultural commercialization is more than marketing agricultural outputs because commercialization can also occur on the input side with use of purchased inputs in agricultural production (von Braun et al., 1994).

Agriculture has been playing significant role in the development of nations for countries. The World Development Report 2008 states that agriculture can “produce faster growth, reduce poverty, improve sustainable environmental and living stander” of small holder farmer’s economy (World Bank, 2007). In fact, the report stipulates three ways through which agriculture contributes to development: as an economic activity, livelihood and environmental services (World Bank, 2007). Most of sub-Saharan African countries are living under poverty line. To alleviate poverty, they have different strategies on agricultural technology and to full fill sustainable development goal on no hunger and zero poverty.

De Janvry et al., (1991) argue that substantial benefits would be gained if missing markets could be re-opened for trade by decreasing the costs of transaction. The reducing the obstacles for private households to participate especially in food market are reduced trade restrictions and better roads is well pronounced.

Agricultural commercialization is different from agricultural marketing. Agricultural commercialization is achieved when household product choice and input use decisions are made based on the principles of profit maximization (Pingali, 1995). Agricultural commercialization has comparative compensations over subsistence production which can generate income for the smallholder farmers. The shift of subsistence economy towards market (commercializing) can significantly increase the income and welfare of smallholder farmer’s economy as well as contribute to economic growth and poverty alleviation (Zhou et al., 2013).

In order to get their necessity (to purchase of essential consumption goods, services and non-farm inputs), smallholders participate in the output market. They make a rational choice that can maximize their utility (Gebreselassie & Ludi,2008).

Commercialization of smallholder agricultural producers through increased participation in output markets has been promoted as one of the best strategies to address low agricultural productivity that has led to high levels of poverty and food insecurity among rural farming households in developing countries (Jaleta et al., 2009). When smallholders commercialize, developing countries with large population shares in the agricultural sector can generate more income, thus economic growth. Increased income in the agricultural sector raises demand for manufactured goods and services in the other sectors of the economy, thus stimulating further growth.

Commercial transformation of smallholder agriculture entails production decisions based on market signals and significant participation in input and output markets. Hence, analysis of the commercial transformation requires analysis of market orientation and market participation. Policy, institutional and technological strategies to enhance commercial transformation based on the analysis of market participation alone may not be adequate if the determinants of market orientation and market participation are not the same (Gebremedin et al., 2010).

Ethiopia has adopted commercialization of smallholder agriculture as a plan for its economic transformation. The agricultural services of extension, credit and input supply are expanding significantly to support commercial transformation, although the dominant player in these services still remains to be the public sector. A recent study by (Gebremedhin et al. 2009) shows that the expansion of the agricultural services has significant impact on the intensity of input use, agricultural productivity and market participation of Ethiopian smallholders.

The higher the level of production the higher would be the probability of farmers engaging in commercially-oriented agriculture. However, a simple correlation analysis suggests that the more a farmer sold, the lower the proportion of output marketed (r=0.12 or r2=0.1). In other words, as the volume of marketed output increases the volume of output consumed on the farm also increases, but by a higher proportion. This finding, from cross-sectional analysis of households in a given period, is paralleled by observations from the qualitative fieldwork about the pattern of change over time (Kay sharp et al., 2008).

Building a market for All (“to connect all buyers and sellers in an efficient, reliable, and transparent market by harnessing innovation and technology, and based on continuous learning, fairness, and commitment to excellence”).

Figl. Ethiopians Market Characteristics.

removed for copyright reasons

Source: Adopted from Ethiopian Commodity Exchange (2012).

As farmers gain access to better market information, they see the price differences between different grades of traded commodities. This information encourages them to know what their goods are worth and to bring better-quality of goods to market. As access to information has become more balanced, marketing costs due to inefficient and lengthy marketing chains have shrunk, and local, national, and even global prices have started to converge. Because they are negotiating better prices and they can plan to invest in more inputs and improved farming practices. (Eleni-GabreMadhin, 2012).

Ethiopia is the another most populous country in Africa next to Nigeria. Before decades the country followed socialist economy. Ethiopia grew at a rate between 8% and 11% per annum - one of the fastest growing states among the 188 IMF member countries. This growth was determined by government investment in infrastructure, as well as sustained progress in the agricultural sectors. More than 70% of the population is still employed in the agricultural sector, but services have surpassed agriculture as the major source of GDP. The country has the lowest level of income-inequality in Africa and as well as in the world, with a Gini coefficient comparable to that of the Scandinavian countries.

Yet despite progress in the direction of removing extreme poverty, Ethiopia remains one of the poorest countries in the world, due both to rapid population growth and a low starting base. Variations in rainfall connected with world-wide weather patterns resulted in the worst drought in 30 years in 2015-16, creating food insecurity for millions of Ethiopians. The state is heavily involved in the economy. Continuing infrastructure projects include power production and distribution, roads, rails, airports and industrial parks. Main sectors are state-owned, including telecommunications, banking and insurance, and power distribution. (CIA World Fact book, 2008 and other Sources).

Smallholder farmers in Ethiopia account for most of the Ethiopian population and the food grain production (Betre, 2006). Smallholder family farms cultivate approximate to 95% of the total cropped land and produce more than 90% of the total agricultural output in Ethiopia. It is in response to these facts that the Ethiopian government has prioritized commercialization of farms in general and smallholder agriculture in particular. In its second Poverty Reduction Strategy Plan, PASDEP, set for the time span 2005/06 to 2009/10, the government of Ethiopia.

Many remain convinced that fast growth in agriculture plays a crucial role in the efforts of African countries to achieve the MDGs. In fact, the Millennium Development Goals Hunger Task Force concluded in 2005 that “the world could meet the MDG of halving hunger by 2015”, and that “development of agriculture is critical to that goal” (World Bank, 2007). The current issue is (2030 SDGs) Agenda for Sustainable Development, including the 17 Sustainable Development Goals (SDGs), are new global objectives that succeeded the Millennium Development Goals on January 1, 2016. The SDGs will shape national development plans over the next 15 years. From ending poverty and hunger to responding to climate change and sustaining our natural resources, food and agriculture lies at the heart of the 2030 Agenda.

The measurement of welfare outcomes is discussed as livelihood assets, health and education. Sustainable rural livelihood as a base and with certain modifications comprised of the livelihood assets such as human capital, social capital, physical capital, financial capital and food security.

Human capital: - the ability of human being to good competency. Measured by education, health and employment generation. In our case human capital is measured by un expenditure of education and environmental protection.

Physical capital: - this would be measured by considering the accumulation of physical assets like house, household articles and entertainment materials farm equipment and the social capital: - measurement is based on the proportion of money generation from UA for expenditure and accumulation of the financial in terms of saving.

Food security: - measured by availability of food grains, vegetables, milk and also proportion of expenditure on food. In this issue agricultural activities considered as high, medium and low for the livelihood assets of farmers. Similarly; for those variables like proportion of income, proportion expenditure on cost of education and cost of food financing. These phenomena depend on how much the HH wants to consume and the drudgery of labour. Up to a certain minimum the consumption level of the HHs can said to be determined exogenously reflecting the nutrient requirement for self-sustenance. In which case the drudgery of labour would have to be met, there being no option. It would be up to nature whether this necessary amount of labour supply is burdensome or not.

The transition process from subsistence to market-oriented production under track one can be divided into two stages. In stage one the HH has a significant amount of marketable surplus and income can be viewed as a proxy for consumption with a somewhat convenient assumption that at this phase of commercialization farmers do not save in cash. Food security program is designed to address the problems of shortfalls in food production, vulnerability to falls in consumption, incomes and consequent hunger that the country has faced repeatedly, through adaptation of development alternatives to bring about lasting solution. The effort to reduce vulnerability is central to the five years plan strategy (MoFEC, 2006).

Commercialization did increase farm and total income. However, its effect on household static welfare and livestock wealth is questionable. It is highly probable it did improve families’ access to better housing and generated a huger rural saving in form of cash. Diversion of income to none basic goods does not seem to be serious problem. However, it may have negative effect on gender empowerment of rural women (Gebru Menasbo et al.,2014).

According to (Govereh et al., 1999) “commercialization can be measured along a continuum from zero (total subsistence-oriented production) to unity (100% production is sold).” (Strasberg et al., 1999) suggested a measurement index called household Crop Commercialization Index (CCI) which is computed as the ratio of gross value of all crop sales over gross value of all crop production multiplied by hundred. The advantage of using this approach is that it “avoids the use of crude distinctions as commercialized and non- commercialized farms” (Govereh et al., 1999).

However, this index has not its limitations. For instance, consider the case when a farmer growing one quintal of teff sells that all and another farmer producing ten quintals of teff sells only two quintals. The CCI would tell us that the first farmer is fully commercialized (100%) while the second is semi-commercialized (20%). This interpretation does not make sense in such circumstances. Even though this limitation of using CCI is worth noting, there is still some room to use it in practice especially in the context of developing countries where it is less likely to get smallholders selling all of their output and very large farms selling none of their output (Govereh et al., 1999).

As can be understood from the preceding discussion, the degree of participation in the output market is the conventional way to measure commercialization. However, (Von Braun et al., 1994) provide other dimensions to the measurement of commercialization. Commercialization is calculated as percentage of the total produce sold from a household or as a percentage of cash crops as compared to all crops cultivated by a household. Von Braun et al (1994), have specified the forms of commercialization and integration into the cash economy from at least three different angles and measured the extent of their prevalence at the household level with the following ratios.

Commercialization of agriculture (output side) = Value of agricultural sales in markets divided by Agricultural production value. Commercialization of agriculture (input side) = Value of inputs acquired from market divided by Agricultural production value; Commercialization of rural economy = Value of goods and services acquired through. market transactions divided by Total income. Degree of integration into the cash economy = Value of goods and services acquired by cash transactions divided Total income; Household Commercialization Index (HCI) = (gross value of all crop sales / gross value of all crop production) *100

2.2. Empirical Literature Review

Empirical evidence indicates that commercialization of smallholder farms has the potential to enhance incomes and welfare outcomes and take smallholder farmers out of poverty if constraining factors such as lack of capital, basic skills (farming and commercialization), high transaction costs, lack of infrastructure, lack of information and lack of education could be eliminated (Lerman, 2004). So far, the literature on commercialization of smallholders makes little study on the impact of market participation on smallholder’s economy. Therefore, such like studies attempt to fill the gap by conducting an empirical research on identifying, analyzing and understanding the impact of smallholders’ commercialization on welfare situation and those elements that are responsible for variation in smallholder commercialization and welfare that is needed to guide policy decisions, device appropriate interventions and integrated efforts to combat smallholder’s commercialization.

Samuel and Kay (2008) the likelihood of market participation is high among smallholders specializing in teff (the major cash crop produced in the study areas). On average, market participant farmers allocated three quarters of their cultivated land to teff, whereas nonparticipants allocated only one third of theirs. Non-participant households also cultivated only a small proportion of their land: 62% of them rented out a significant part (about 85%, on average) of their 1.1 hectare.

Goitom Abera (2009) the study used the probit regression analysis revealed that the level of production; improved seeds, irrigation and total landholding size are the most important factors affecting the capacity of a smallholder to participate in output markets. Moreover, the findings from OLS estimation showed that the level of food and cash crop production, gender, technology use (irrigation and improved seeds), use of fertilizer and the number of oxen possessed per household are important factors determining the level of commercialization of smallholder farms. The one-way ANOVA investigation indicated that farm households with high degree of commercialization leads households a better welfare outcome.

Gebremedhin and Jaleta (2010) commercialization enhance the links between the input and output sides of agricultural markets. Commercialization entails market orientation (agricultural production decision destined for market based on market signals) and market participation (offered for sale and use of purchased inputs). Literate households are expected to have better skills, and better access to information and ability to process information, and thus may be positively associated with market orientation and market participation. Household size increases domestic consumption requirements and renders households more risk averse.

The work by (Chanyalew et al., 2011) in Kombolcha district of East Hararghe in Ethiopia used a survey of 133 randomly selected potato growers from a purposively selected peasant association. Using an OLS method for the analysis of quantitative data, they found out that farm size allocated to potato, access to irrigation and access to market information were found to be significant in affecting extent of market participation (commercialization).

Wondmagegn (2013) in the few decades in the world has brought an excess demand for different types of agricultural products. As a result, policy makers and international institutions have been advocating several policy instruments aimed to boost agricultural production and food security. In most cases, however, the potential role of smallholder commercialization has not been given due attention despite its importance. In the assesses the potential role of commercialization for smallholder agricultural productivity and food security in Ethiopian farm households. The Cobb- Douglas production function theory was employed and the stochastic frontier analysis is used. From the result imply that output can be increased up to 59.8% by improving input mixes used in the production process and the remain value are educational level and asses to relevant information.

Ele et al (2014) conducted an assessment of the extent of commercialization of smallholder households in cross river state of Nigeria. The study was conducted to examine the variation in the level of commercialization among households’ in three agricultural zones. The study used a survey of 120 HH with the application of household commercialization index (HCI). Their findings revealed that the degree of commercialization in the study area was moderately high (about 60.40%). On average, households sold about 56.10%, 66.60% and 58.50% of their total production (in grain equivalent terms) for the Southern, Central and Northern zones respectively. The tobit regression analysis showed that total quantity of food crops produced, farming experience, access to agricultural extension service, size of land used for cultivation, membership in cooperatives and household family size were important factors determining the level of commercialization of smallholder farms.

The cross-sectional study obtained data from a sample of 160 smallholder horticultural farmers selected randomly from four peasant associations in the district. A double hurdle model was applied to analyze the determinants of the commercialization and level of commercialization. For the first argument Probit Regression Model revealed that, independent variables a significant role in smallholder commercialization. In the second hurdle, the result of Truncated Regression Model exposed that, household education, household size, access to irrigation; cultivated land, livestock, and distance to the nearest market were the factors that determine the level of smallholder’s commercialization. the double hurdle model result showed that farm size and distance to the nearest market were cross-cutting determinants of smallholder horticultural crops commercialization (Aman Tufa et al.; 2014).

Taddese Mezgebo (2014) Commercialization of chat increase income of farmers/ leading to increased cash saving but did not generate or improvement on welfare. This is clear indication of the fact that increase in income is not transmitted in to more consumption of basic and none basic items within family. The sample 200 households are selected through systematic random sampling method. Cobb Douglas production function with fixed effect model is used. The OLS for continuous, Logit for binary, negative binominal with mean dispersion for count and OLS when SSM is replaced by simple treatment model with linear probability specification and incidence of commercialization is modelled by multivariate and bivariate Probit models.

Kumilachew Alamerie Melesse (2016). Consultation the challenge of improving rural incomes in Ethiopia will require some form of transformation of the subsistence, low-input and low-productivity farming systems to agricultural commercialization. In Kombolcha Woreda, the extent to which farmers have commercialized potato production was not known. This study was then undertaken to analyse the extent to which potato was oriented towards the market (denoted by commercialization index). A multi-stage sampling technique was used to select 130 sample households from six sample kebeles. In the study, both primary and secondary data sources were used. Results showed that potato production was lucrative and semi-commercialized i.e. about 59.50% of the potato produce were sold. The two limit-Tobit regression model was employed results indicated that non/off farm income, access to information, access to improved seed and access to irrigation affect proportion of the value of potato sold positively and significantly while number of plots affects it negatively.

Getachew Eshetu, (2018) Commercialization of smallholder agriculture increase income of rural households. Selling of the crop, especially staple food crop is the most common way of earning cash income in Ethiopia. Among the staple crops, teff has become the essential source of in the country. The study used a multi-stage sampling technique. Both qualitative and quantitative data obtained from primary and secondary sources. The random sample selected from primary data was 155 and secondary data were collected from Jamma office of agriculture. The average level of teff commercialization ratio sold to produced was 37%. Double hurdle result of probit model showed that sex of the household head, literacy status, land allocated to teff, application of chemical fertilizer, row sowing and improved teff seed significantly affected market participation while the truncation regression model result showed that family size, literacy status, frequency of extension contact, land size, application of fertilizer and use of improved teff affected level of farmers market participation in teff output.

From the above literature reviews, it is evident that several studies have been done on commercialization and welfare out comes of smallholder farmers. The sustainable development goal of poverty reduction is the main issue. Methodologically, current empirical studies on market participation typically adopt probit regression, two-limit tobit regression, Double Hurdle, Truncation regression model and OLS Models, have been widely used. The review also showed that the fundamental theory of market participation is derived from the modernization and (Cobb & Douglas) rational producers are to maximize profit/by minimizing cost. All the empirical results show agricultural commercialization have a positive relation with developing countries economy. The problem that still remains solution in additional to results of those researches have informed national polices, agricultural strategies and new technologies that make contribution in changing farmers commercialization and welfare out comes.

2.3. Conceptual Framework

Fig 2 Conceptual Framework

Abbildung in dieser Leseprobe nicht enthalten

Source: Adopted from Gutu T. Boka 2016

CHAPTER THREE

3. RESEARCH METHODOLOGY

3.1. Description of the Research Area

Gurage Zone is located in the central and southeastern mountainous area of Ethiopia in SNNPR and the Zone capital (Wolkite) is located 158 km South West of Addis Ababa and 432 km north from the regional capital city (Hawassa). Gurage zone is one of the 15 zones in SNNPR and it consists of 13 woredas and 2 city administration. The zone is bordered on the southeast by Hadiya zone and Yeme special woreda, on the west, north and east by Oromia region, and on the southeast by Silte zone.

Topographically the zone lies within an elevation ranging from 1000 to 3600 meters above sea level. It has a land size of about 5932 square kilometers. The zone has three agroecological zones dega (35%), wenadega (62%) and kolla (3%). The annual average temperature of the zone ranges from 13 to 30°C and the mean annual rainfall ranges from 600-1600 mm. Considering the land utilization, 52% of the total area is a cultivated land, 13 .4% is a grazing land, 9.9% is a natural and manmade forest land, 7.3% unproductive land and the remaining 17.6% is covered by others.

The Zone is one of the most densely populated zones in the region and the total population of the zone in 2017/2018 was estimated about 1,773,894 (Gurage zone Finance and Economy office, 2017/2018). In the zone there are 13 woredas and in those woreda there are about 35 urban and semi urban areas and the rest are rural areas. From those about 75,005 households live in those kebeles (Gurage zone rural development office, 2016).

Fig 3 Guraghe Zone Administrative map

removed for copyright reasons

Source! Gurage Zone finance and economy office.

3.2. Research Design

The study is based on cross-sectional research design. Accordingly, the study was used both quantitative and qualitative research strategies. The quantitative method was used to analyze data that were collected from structured household surveys. The qualitative research also used to analyze the data that was collected by unstructured interviews with key informants! agricultural and rural experts from Guraghe zone finance and economy department.

The developed questionnaires were tested for consistency, clarity and duplication/ homoscedastic. Appropriate training, including field practice, were necessarily developed the enumerators’ skill, regarding the objectives of the study and the content of the questionnaire, on approach the respondents and conducting the interview. The design appropriately shows the determines welfare outcomes and commercialization of smallholder farmers in Guraghe Zone, the OLS and probit was designed.

3.3. Data Sources and Collection Methods

Both primary and secondary data were used. Multi-stage random sampling method was employed and the structured household survey questionnaire were used to collect primary data on the identification of the demographic, socioeconomic, institutional and environmental factors that determining market participation (non-participation) and welfare outcomes on smallholder farmer’s economic situation at differing levels of commercialization in the case of Guraghe Zone. Smallholder’s farmers are randomly selected from a representative random sample of household heads. In addition, unstructured interviews were conducted from the key informants at sub-district levels. Furthermore, secondary sources such as documents, journal articles and related materials were used to back up the findings from primary sources.

3.3.1. Sampling Technique

Multi-stage random sampling methods were used to obtain the necessary information from formal informants. The first stage of the section of selection is the study area (Guraghe zone); as a result, the smallholder farmer’s necessarily needs to commercialize their agricultural output to output market. In the second stage, 3 woreda are randomly selected from the total of 13 woreda’s and two towns administrative in the zone. Third stage from each selected woreda’s 2 kebeles and totally 6 kebele’s were selected by simple random sampling. The woredas and kebeles in Guraghe zone are homogenous in all attitudinal, economical, agro ecological, institutional, demographic and socioeconomic factors. The households would be drawn from the selected kebeles using random sampling techniques to avoid sample selection bias.

3.3.2. Sample Size

The following formulas by (Kothari, 2004) would be used to determine sample size:

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Where: n= the desired Sample Size

Z = standard normal deviation (1.96 as per table of area under normal curve for the given confidence level of 95%), e = margin of error for this study 7% was taken (0.07), the general accepted margin of error for representative sample is 10% or less.

N= total household number of smallholder farmer in study areas of Gurage zone (75,005), which was taken from Gurage zone rural development office. p = sample proportion, success for each household to be included in the sample proportion (p= 0.5) and q = 1- p q= 0.5, failure for each household to be including in the sample.

Table 3.1 Sample Size Determination

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Source: Own survey 2018

3.4. The Model

3.4.1. Theoretical Framework

Unimodal and bimodal rural development approaches are defined in terms of the path selected for development of agriculture. Agriculture is the primary and core sector predominantly determining the economic and social development of the rural sector (rural development) in many developing countries today. The central axes of the debate by the two approaches are the argument for the necessity of the development of large-scale units of farm production (bimodal or capitalist approach to agricultural development) and the argument for agricultural transformation on the basis of small-scale peasant farms (unimodal or neo-populist approach).

Unimodal approach is based on conceptual perspective of specific peasant economy. It argues that small producers who are not separated from their means of production and. who survives in the sense of household producers retain a degree of control over land and family labor in spite of secular differentiation that may take place in the economy due to commoditization and commercialization. The strategy aims at the progressive modernization of the entire agriculture sector (e.g. Japan and Taiwan). The approach's major strategy is maximum mobilization of labor and land resources of the developing countries, cognizant of the fact that agriculture is subject to demand constraints in relation to non-agricultural sectors and the resulting purchasing power. It is however the nature of technical innovations and their diffusion among farmers that is decisive in minimizing the cost of the sector-wide expansion of farm output and in determining the pattern of development.

Bimodal approach is a crash modernization strategy that concentrates resources in highly commercialized sub-sector, with the resulting development pattern based on a dualistic size structure of farm units (e.g. Mexico, Colombia). The approach is based on differentiation theoretical perspective which asserts that commoditization and commercialization process inevitably generate differentiation in agrarian societies whereby rural producers are set apart into distinct classes (agricultural capitalist, small farmer, land less agricultural employee) and producing a dual size structure of farm units (Harriss, 1982).

These two agricultural development paths are different in their contribution to achieve the three major objectives of an agricultural development strategy. The objectives are: expansion of farm output, income and advancing structural transformation (raising the welfare of the farm population and fostering changes in rural attitudes and behavior that would have beneficial effects on the process of rural development and modernization. The embraced path of agricultural commercialization needs to facilitate the fulfillment of the objectives and policies and components of the agricultural strategy chosen. Any agricultural strategy would comprise, programs of institution-building related to such activities as agricultural research, rural education and farmer training, programs of investment in infrastructure, including irrigation and rural roads, improving product market and the distribution of inputs, policies related to prices and land tenure.

The aggregate of all firms in a given market is termed the industry. The production theory and the consumer theory in the agricultural sectors of developing and developed countries, there are farms, producing cash crops for the domestic or foreign market. In the developing countries there may also be a number of subsistence farms in which all production is consumed and none passes through the market. However, pure subsistence farming is rare (Wharton,1970) and it is more common that farms produce some amount of marketable surplus. Indeed, the main drawback of the theory when applied to the developing countries is not its focus on commercial aspects of production but rather on the distinction between firms and consumers. Many farms are both production and consuming units (in the sense that a proportion of their output is consumed on the farm).

According Modernization theory, the world is dichotomized into modern and traditional. The rural economy in developing countries is traditional dominated by traditional farming/subsistence-oriented agriculture, handicrafts and poor markets. According to modernization perspective, the traditional economy and agriculture need to be transformed into modem large-scale market-oriented agriculture employing modern technology transferred from developed countries.

The descriptive statistics method analysis the socio-economic and demographic issues of households. Identifying the necessary variable that affect market participation and to evaluate how commercialization, affect the household welfare, the study tries to estimate the econometric functional relationship. From literature review, it is clear that there exists for determinants of commercialization and relationship between commercialization and household welfare.

3.4.2. Methods of Data Analysis

Descriptive and econometric method was used to analyze the primary data, after that the enumerator collects from smallholder household heads using structured questionnaire. Descriptive Statistics are used to describe the basic features of the gathered data. Descriptive methods such as measure of averages, percentages, using graphically displays and tabular description which summarize the data. The method is used the statistical tools and economic theories in combination to estimate the economic variables and to forecast the intended variables.

The assumptions of OLS such as Multicollinearity/ Correlation, Heteroskedasticity and normality tests were conducted for the variables used in the study to check adequacy of the model. The Statistical test mainly used to analyze the impact of commercialization on welfare outcomes of smallholder farmer’s economy. The probit regression was employed to analyses what are the determinants that affect small household market participation or not and Multivariate linear regression analysis was used to examine the welfare effect of commercialization. STATA and SPSS software packages were used.

3.4.2.1. Model Specification for Commercialization of Smallholder

The logit and probit models are the most frequently used models when the dependent variable is dichotomous (Gujarati, 2004; Verbeek, 2004; Green, 2003; Woodridge, 2002). The probit and logit models are quite similar, so they usually generated predicted probabilities that are almost identical. Econometric models such as the Logit model which is corresponding to a logistic distribution function and probit model that corresponds to normal distribution are commonly used for qualitative responses like “yes” or “no” a qualitative binary variable.

Logit and probit model can be used interchangeably and the two models give nearly similar results. The study applies probit regression model to identify the determinant variables and their marginal effect on households’ participation for the two sets of market participant and not. This is because we assume household participation decision in those activities may not be independent. Babatunde and Matin (2010) modeled similar problem in Nigeria that decides cultivated farm size contributes positively to total income, and especially to farm income. For this study two dependent variables are used. In the first stage, a probit is estimated on the decision to work market with data from both participants and nonparticipants. In the second stage estimation of OLS model for how commercialization on smallholder welfare would be used data from the commercialized households only while including inverse mills ratio to account selection bias is then undertaken. Therefore, the determinant of welfare from commercialization is estimated using multiple linear regression (OLS).

The study was used the probit regression model to identify the factors that determine the commercialization of smallholders. The fact that the dependent variable is a dichotomous one justifies the use of probit model. Accordingly, the dependent variable assumes only two values: 1 if the household participates in output market and 0 otherwise.

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Where Yi is a vector of binary variables, such that Yi = 1 if the ith 'respondent partspante in output market and 0 other wise, xi is a vector of explanatory

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Consequently, if N observations are available, then the likelihood function is

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The logit or probit model arises when Pi is specified to be given by the logistic or normal cumulative distribution function evaluated at Xi'ß. Let F (Xi'ß) denote cumulative distribution functions.

3.4.2.2. Model Specification for Smallholder Welfare

The second dependent variable of the study is welfare of smallholders. In order to fulfill objectives of this study the following functional form would be used. The OLS estimator is constant when the Gauss-Markov assumptions (sometimes called OLS assumptions or assumptions of the CLRM) are met. The OLS estimator requires that in explanatory variables when there is no perfect multicollinearity. Furthermore, OLS is optimum in the class of linear unbiased estimators when the errors are homoscedastic and serially uncorrelated. Under these conditions, the method of OLS provides minimum-variance and mean-unbiased estimation when the errors have finite variances. Under the additional statement that the errors be normally distributed.

Abbildung in dieser Leseprobe nicht enthalten

'Where Yt is welfare of smallholder farmer

Xlhuman capitals X 2participationinmarket X3 physical capitals XAirrigation The econometric model for the functional form stated in equation (3)

Xi represents the the independent variables thataffectthe welfare of smallholders ßO and ßl — k are estimable parameters U is the error term

3.5. Discerption of the Variables

3.5.1. Dependent Variable

The dependent variable for the econometric model of this study is the market participation, the variable is binary, the study was used the probit regression model to identify the factors that determine the commercialization of small holder farmers. In this situation the dependent variable is a binary one justifies the use of probit model. The dependent variable assumes the two values: 1 if the household participates and 0 otherwise and the second dependent variable is welfare of smallholder farmers. The variable is assumed to be continuous and it expressed by annual consumption of households.

3.5.2. Explanatory Variables

The main explanatory variables of this study are: age of the small hold farmers, sex of respondent, land size, education, family size, asses to Credit, characteristics of farm product, asset endowment, distance from main market, Transport Access, non-farm and farm income house hold income and rainfall, physical assets, food security, extension service, fertilizer usage, oxen, livestock, nature of land holding and consumption.

Age (hh_age): This variable can be measured in years in which the younger the age the - higher may be his/her productivity/ knowledge, and the higher the age the lower his/her productivity may be this lead young age highly participate in output market than older age. But in other case may the higher age are highly producing and participate in the output market. Sex (sex1): the variable is categorical variable; there are controversial statistics among many commodity extent specialists that uphold that male headed smallholder farmers are highly participate in output market than female headed. However, others expect that female headed households are highly knowledgeable in input purchasing market. Hence this variable was expected to have a positive relationship with market participation.

Education (Educ): is a continues variable that schooling smallholders. Education is the major factor to transform from subsistence economy of smallholder farmers to commercial. If the farmers increase their educational level, then increase their skills to use input and to organize the seasons. Many farmers in rural areas do not have the most up-to-date information on how to get food efficiently and economically. Improving their knowledge of new techniques and technologies; to increase local food availability, to increase farmer income, to increase sustainability of agricultural practices and in addition to providing them with any physical resources necessary for implementation, can dramatically increase the farmers’ level of productivity (Rosegrant & Cline, 2003). There for education expected to have a positive relationship with commercialization of smallholder farmer’s economy. Other scholars like Gebremedhin, B., M. Jaleta and D. Hoekstra, (2009) discuss the increase education by one more level; crop input market increase by 0.5385 units.

Land size (tlands): is a continuous variable that is measured by tsimad⁶ / hector; there is large amount of land the farmers expected to have highly participate in output market; so, this variable has positive relationship with dependent variable. Rainfall (rfl) is a categorical variable that the distribution is adequate /not adequate rainfall access in farm season. It has appositive/negative relationship with dependent variable.

Access to credit (as_crd): is the financial sector that it is near to the farmers home is used to improve their commercialization. But farmers credit for out of agricultural production purpose maybe it has own negative conscience. The variable categories as asses to use and does not use the sector. The variable also has a positive/ negative relationship with response variable.

Crop Production (crp1): is a type of a variable that farmers grow the agricultural product in the given year. The variable has a positive relationship with dependent variables. Irrigation (irrig): has categorical variable which is categorizes in to irrigation users and not users, positive relationship with dependent variable.

Non-farm participation: Income from livestock (lstk), income from non-farm (nf_inc), income from off-farm; these variables have a negative relationship between dependent variables and all other variables also have their own influence on commercialization of small holder farmer’s economy. Commercialization of agriculture is not an end for farmers, but an intermediate outcome on the way to welfare goals. The consumptions of smallholder farmers; continues variable and it is proxy of welfare, extension service, nature of soil, public good and service have also positive relationship with dependent variable and income from non-farm participation, income from off-farm have a negative relationship.

Table 3.2 Explanatory Variable and Expectations

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Source: Adopted from (Samuel and Key 2008)

3.6. Diagnostic test

Multicollinearity problem arises when at least one of the independent variables is a linear combination of the others. To solve this problem, check the variance inflation factor (VIF) technique was employed for identifying whether the problems of multicollinearity among explanatory variables exist or not (Gujarati, 2006). If VIF value is greater than 10, it is used as a signal for strong multicollinearity among the explanatory variables.

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Where, Ri2 is the square of multiple correlation coefficients that results when one explanatory variable (Xi) is regressed against all other explanatory variables.

Heteroscedastic is the test for disturbance term normally distributed or not. Robust the result is the solution. The other tests Hosmer-Lemeshow test for good ness of fit binary dependent variable using p-v >0.05 the model is good fit. And normality test checked by using Shapiro swilk test (W >0.05) the sample is normally distributed.

CHAPTER FOUR

4. RESULTS AND DISCUSSION

4.1. Descriptive Results

4.1.1. Socio-economic and Demographic characteristics of households

The section emphasizes that socio-economic and demographic structure of the respondents. In this study 196 questioners were distributed, from those 188 householders were responded and 8 householders are not responded. So, this section clearly discusses that all 188 respondents; minimum, average and maximum values.

Table 4.1: Descriptive Statistics of Categorical Variables.

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Source: STATA version 13 using Own survey 2018

The summary of above table 4.1 shows that the Guraghe Zone householders socioeconomic and demographic features. Gender is essential variable and then the number of males to female ratio is relatively the male headed households (56.38%) higher than female headed households (43.62%). The marital status of household’s heads in the Zone are married (81.38%) and then the rest of (18.82%) is covered by single and divorced with the percentage of 12.23 and 6.38 respectively.

The farmers land nature in studies area steeply sloping (1.6%), plain (57.98%) and mixed sloping (40.43%). Most of the study areas get sufficient amount of rain; that means (80.85%) and the rest (19.15%) didn’t get sufficient amount. From the total sample of the study, large number of households (64.89%) are a member and the rest (35.11%) are not a member of extension package, i.e. approximately 2/3 of the farmers are covered and servant. almost all the farmers are crop producers (99.47%) and their economy is based on agricultural crop production.

In this study area there is no vast irrigation technology as a result (63.30%) of the respondents are not irrigation users but only (36.70%) are irrigators. This small number of irrigation users are more profitable and highly commercialized because they can grow three or more times in a year. Due to this reason most of the farmers grow their agricultural product in rain season.

Fig 4 Irrigation Users

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Source: STATA version 13 using Own survey 2018

As the response of the respondents in the study area almost all of the farmers use fertilizer (90.43%) and only (9.57%) of the respondents were using composite, muck and excrement other than fertilizer. From the responses of fertilizer users have two outlooks, using fertilizer adequately gives better results, but using less/ extra amount would lose/ damages the production. The response of muck or composite users are not familiarized the fertilizer for their land.

Fig 5 Usage of Fertilizer

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Source: STATA version 13 using Own survey 2018

Micro finance and other money borrower’s institution are very essential factors for smallholder farmers. From the respondents (58%) have an opportunity to have credit from micro finance and (42%) of the household doesn’t credit and those who didn’t have transport access is (29.26%) but most part of the area (70.74%) have transport access.

The rural farmers almost all (97.87%) of them have a physical capital like own house and a lest percent (2.13%) doesn’t have, i.e. they live their relative/ rent house. Their food status of the households almost half of them (51%) are food secure and the rest (49%) of the households are food in secure. The commercialization features of most of them are a market participant (79.26%) of the others (20.74%) are not participant.

Table 4.2: Summarization of Continues Variables.

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Source: STATA version 13 using Own survey 2018

The above table 4.2 discuss that, the household headed average age is 49.377 from the youngest age of 25 (the productive) and the oldest age 81 years old. The average household size is 6 from minimum of household size 3 and maximum household size 10 then the average household size shows that most of them have more than five.

From the real-world realities Land is one of the most important inputs for large scale and small-scale farmers. Land ownership, size and quality are important factors determining the agricultural production and market participation of households. In this study included households have more or less the size of own land. Their average land holding size is 2.71. This from the largest land holding size 6 and smaller size holder 1 hectare. The table result shows largest numbers of farmers hold less than or equal to 3 hectares.

The average of schooling of the farmer’s educational level is grade 7. This result shows that most of the farmers learn primary school. The average number of un oxen is 2; this shows that most of the farmers plough their cultivated land by their own oxen. But fewer numbers of the farmers can plough through rents oxen/tractor. The average distance 4.263 km far from home to the main market. This shows there is some availability of the market, but still need near and available place of farmers in their locality/ kebele.

In the study area most of the farmer’s income source are farming activity. on average, households yearly earn farm income is 51158.51 Birr. The lower farmers earn farm income 9,000 Birr and the potential farmer earns 160,000 Birr. In another direction the household’s deployment on non-farm farm activities. So that the households earn the average non-farm income 22537.07 birr in the year. The households earn income from non-farm activity lower- and upper-income boundary is 2,300 and 60,000 Birr respectively.

The summary table 4.2 shows that the monthly average expenditure of human capital (Health and Employment generation) of the households is 150.69 birr. So that average expenditure of human capital shows there is a large gap between the lower household and upper one. The average food and non-food expenditure of households is 2968.968 birr. In this study the household’s minimum monthly consumption is 1,600 birr and maximum consumption of the households is 6930 Birr. The farmers average yearly total income is 73917 from the low-income generation level of farmers birr 33300 and high-income level of farmers birr 186750.

Land holding size is one of the major determinants for agricultural harvest and commercialization. One way ANOVA test revealed that there is a statistically significant difference among the land holding size in terms of the mean level of total crop production value (Prob >F= 0.0000), total crop sold (Prob >F= 0.0000) and degree of commercialization, DoC, (Prob >F= 0.0011). land holding size is a sufficient condition and necessary input for transforming agriculture from subsistence to commercial. But not only the size of the land quality, soil type, and the nature of land holding are un important factors.

Fig 6 Nature of the Land

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Source: Own survey 2018

The nature of land, fertility and soil type are very important for commercialization as well as household welfare. From the randomly selected woredas of Guraghe Zone most of the households cultivated land is (58%) plain and (40.4%) mixed sloping. But very small number of households (1.6%) cultivate steeply sloping.

Fig 7 Cereal Crops produced in Guraghe Zone.

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Source: STATA version 13 using Own survey 2018

In the Guraghe zone teff, maize, barley, wheat, peppercorn and sorghum are widely producing. The Fig 7 shows that the largest percent of the cereal are covered by maize and teff and in the second stage wheat and peppercorn are cultivated for consumption as well as for market.

4.2. Probit Estimation Result for Commercialization

Maximum likelihood estimates of the probit model and the Marginal effects of the variables

Table:4.3 The Probit Model Result

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Source: STATA version 13 using Own survey 2018

Where ***, ** and * significance level at 1%, 5% and 10% Wald chi2(11) = 49.04

From the above table 4.3, eleven total explanatory variables are included in the model, eight of them are significant impact on dependent variables. The determinants of small household’s commercialization affect either positively or negatively were; the distance from home to main market is negatively affect smallholder farmers commercialization and the other variables has a positive impact.

The table 4.3: result shows the marginal effect of the probit regression model the probability that the smallholder farmers participate input output markets. The LR chi square which measures the overall significance of the model, i.e., with the null hypothesis that all coefficients are zero is rejected this showing that at least one of the coefficients is different from zero. From econometric variables likelihood of market participation of a small householder farm given the statistically significant variables. Therefore, those eight statistically significant explanatory variables are: - sex of households, education, extension package, access to credit, transport access, fertilizer, family size and distance from home to market.

The sex of household head is important and statistically significant variable (at 1%). The households are male headed they are highly participating input output market than female headed. This leads householder’s commercialization to upward and positive direction. Male headed households have 0.00068 higher probability of market participation as compared to Female headed households. This may happen most of the time females have many tasks in their home and society specially in developing countries.

The smallholder farmer’s level of schooling increases the productivity and participation in output market of farmers are increase. The increment of education improves every aspect of socio economic and political cultures. The educational level of farmers is statistically significant (at 5%) level of significance, then it increases commercialization to upward and the farmers economic situation changes from subsistence living standard to commercialized. The marginal effect result indicates the householder’s One more level of education increases the probability of market participation of households increases by 5.71e-06, on average. The farmers education increases then it improves the skill of farming, gathering better market information, improves better connection with merchants to assess market-based crops and agricultural professionals to produce by plan for the market as well as for the home consumption. This study is in lined with Bekele et al., (2013). In his study education of the household head was the positive and significant impact on the sales value of horticultural crops and the literate household earn about 1,625 Ethiopian birr more as compared to illiterate household head on average, from sales of horticultural crops. So, the same justification in our study the more educated farmers have the ability to improve their marketing performance and farm plan.

The farmers member of extension package increases by one unit the members extension package has 0.007 higher probability to market participation in output market than those who does not a member of the extension package. The member can support the farmers by many ways like giving agricultural training, improved seeds, fertilizer and giving priority of better market information for the members.

Household Size or all the family members those who are found in productive ages should help their family in farming season by supporting labour and skill without price or at lower prices as compared to market value. The marginal effect of household size is positive and significant at 10% significance level. Then the household size increases by one person then the smallholder market participation increases 2.41e-06 on average. In other word, the family size increases /higher the number of people in the household, then the great possibility to participate in the output market than a smaller number of family size. This study is in line with Jaleta et al., (2009) who argued that large household size leads to market participation. Moreover, household labor can work at a lower cost and reduced transaction cost.

Financial sectors have a very crucial on farmers participation on input output market of their products to the market. Access to credit in the above table result shows it have a positive effect on small householder farmers commercialization at 1% significance level. It positively helps in solving farmers cash problems. Then they want cash money in the time of farming season to purchase agricultural inputs such as fertilizer, improved seed, lobour force, crop protection chemicals. The marginal effects result show that the probability of access to credit increase by one more unit, then the of small householder commercialization increases by 0.00133 unit on average than those who does not access to credit. Previous finding Tadele Mamo et al., (2016). In line with this study. Similarly, in this previous finding farmers was borrowed for agricultural input purchasing rather than other extravagance.

The fact that the distance from home to market is high the small household farmers have a serious challenge in participating in output market. Either the challenges are financial, customer holding, information gap or extra use of human power than those who are near to the main market. Distance in (km) has negative relationship with farmer’s market participation and significant (at 5%) significance level. The larger distance from the farmers home to market; may small household farmers lose reliable information, use extra labour force, extra time and increases transaction cost. The distance from home to market increase by one unit, then the farmers market participation decreases by -3.16e-06 unit. So, the nearest market shorter distance improves such kind of extravagance or short distance increases this much time of farmers agricultural commercialization than those who are large distant. The nearest market itself motivates the farmers to produce market-based crops and participate highly in output market based on market information. This result is in line with the findings of Bekele et al., (2013).

The usage of fertilizer is a positive and significant impact on smallholder farmers output market at 5% level of significance. The fertilizer usage of the farmers increases by one unit, then the small householder market participation increases by 0.0037544 unit on average than those who didn’t use fertilizer. Fertilizers gives the nitrogen and potassium for the soil this adds the fertility of the soil. The soil fertility increases then leads to increase the productivity of agricultural crops. Finally, this make to increase farmers economy from subsistence to commercial. But extra usage of fertilizer especially on fertile soil may damage agricultural products.

A transport access is very important variable for every human being in any socio-economic aspects. There is a transport access from home to main market the famers can purchase and sales their output in the market without any challenge. Transport access have a positive relation and a significant impact (at 5%) level of significance. The high transport access leads the farmers market participation highly and change farmers economic situation from subsistence to commercialization than no transport aces. Transport access is very important variable for farmers market participation. The marginal effect of the transport access increases by one unit in each villages of small householders, the farmers output market participation increases by 0.0874 than those have less access or the farmers not have a transport access. There is high access of transport the small householders take their product easily to the market and sells in a few times; this make farmers economy leads from subsistence to commercialization.

The explanatory variables age, total income (farm and non-farm income) and land holding size have not significant impact on commercialization small householders in the study area. The age of household on average is 49, which implies more market participants are higher age householders but the contribution of productive age group is less in this study area. The land holding size is not yet sufficient for agricultural production but also proper management and soil fertility necessary and may be an access for other income rather than farm and non-farm income.

The Pseudo R2 results 88% show that variation in the dependent variable, which implies that percentage of the variation to small householders’ commercialization is explained by the variables included in the model. The 99.9% of dependent variable predicted by independent variables, then the model is good for prediction. The model overall significance and fitness can be checked with the chi2 test; thus, Prob > chi2 = 0.0000 indicates that the explanatory variables predict the dependent variable. (See appendix 2.2)

4.3. OLS estimation result for welfare outcome

This econometric result is analyzed by multivariate linear regression mode. A total of 11 independent variables were considered in the econometric model. From those variables almost half of them were a significantly influence on the intensity of welfare of smallholder farm households. These variables were human capital at 1%, Commercialization of smallholder farmers at 5%, Family size at 1%, Total income at 1% and food security at 1% were a significant and the remaining variables were found to have no significant effect on the welfare outcomes of smallholder farmer.

Table 4.4 Multiple Regression Estimates and Effects of Explanatory Variables

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Source: STATA version 13 using Own survey 2018

Where ***, ** and * the level of significance at 1%, 5% and 10%

The above table 4.7 the explanatory variables predict the dependent variable. From the 11 total explanatory variables almost half of them are significant impact on dependent variables. Human capital is positive and statistically significant at 1% level of significance impact on small householders’ welfare. possible that increase in human capital leads to higher in in health and environmental protection, which would give higher potential to produce goods and services for consumption as well as for market.

According to the above table, Commercialization of small householder farmers are a positive and statistically significant at 5% level of significance. When the commercialization increases by one unit the welfare out comes of farmers increases by 198 unit. But the previous finding of Gutu T. Boka (2016) disagree with this result, Commercialization is not contributing to the poverty reduction strategy in the areas. This is because the strength of the link between commercialization and poverty level is very weak. Hence, slow involvement should be made in enabling business-oriented farming as a way out of the poverty reduction.

Total income of the farmers is highly significant and positive impact on farmers welfare. The income from farm and non-farm is very important variable for welfare. The farmer total income increases by one unit /one Ethiopian birr the welfare of small householder increases by 0.0164. The increment of total income increases the expenditure on consumption of food, non-food, education and livelihood of households. So, such increment positively leads the welfare of households.

Food security is an important variable and positively significate at 1% significance level. The availability of food from produced area (high production place to high demanded area meet the farmers consumption) and quality of food or nutrient increase in one unit the small householder welfare increases by 214.6 unit. This study in lined by (Jaleta M, et al 2009).

Family size is positive and highly significant variable on the small householder welfare. The family size of the households increases leads to increase total income of the family and cooperation on welfare goal. The increment of family size by one person the farmers welfare increases by 95 unit. The finding of this study is not integrated as Ele et al., (2013) that the finding shows increase in family size leads dependence ration and leads more consumption. So, it affects the small householder welfare negatively.

The explanatory variables physical capital, irrigation, extension package, total land and nature of land on welfare of smallholder. The soil fertility is an important for production, but in our study area 58% of the land is plain on average. The physical capital and the usage of extension package is higher but their support on agricultural production are less. The users of irrigation are only 37% it is not sufficient and the users also didn’t use as much as possible.

From the results R-squared 84.5% show that variation in the dependent variable, which implies that percentage of the variation to small householders’ welfare is explained by the variables included in the model. The model overall significance and fitness can be checked with the F value; accordingly, Prob > F = 0.0000 indicates that the explanatory variables predict the dependent variable. (see appendix 2.6)

4.4. Welfare of households with level of Commercialization

The objective of commercialization after all, is to bring the needed rural transformation for the improvement of the welfare of society and enable them to sustain progress out of the current multifaceted poverty. This means that commercialization of agriculture is not an end by itself for farmers, but it is rather an intermediate outcome on the way to welfare goals. Hence, by so many authors and organization such as von Braun (2008), Samuel and Sharp (2007) noted that the ultimate objective of commercialization of agriculture is the attainment of better welfare outcomes for the smallholder farmer, the World Bank (2007) asserts three components of welfare that can be achieved through commercialization. These aspects of welfare are poverty, inequality and vulnerability. It is from this view points that this study was determined to examine as to whether households or individuals have enough resources or abilities to meet their needs through commercialization of their farming. Welfare represented in terms of consumption of basic food (grains), non-food, durable goods, education and healthcare are included in this study.

Table 4.5: Welfare of Households with Level of Commercialization.

Abbildung in dieser Leseprobe nicht enthalten

Source: Own survey 2018

Where ***, ** and * significance level at 1%, 5% and 10%

The table 4.4 result emphasize that the one the households have better commercialization makes the welfare of small householders better. The monthly consumption of food, nonfood and durable goods of the high commercialized households have better welfare than low /medium commercialized. The one-way ANOVA test results confirms that the variation in consumption of basic food, non-food consumables and durable goods among small household’s farm at different levels of commercialization is statistically significant at 1%, 5%, and 10% level of significance respectively (see Appendix 2.1).

4.5. Diagnostic Tests

4.5.1. Diagnostic test for Probit regression

The most common issues when working with cross-sectional data are multicollinearity and heteroscedasticity. Multicollinearity is where two or more independent variables are correlated with each other. The existence of multicollinearity might cause the estimated regression coefficients have the wrong sign. As to Gujarati, (2004) multicollinearity is a serious problem if the VIF of the variables is higher than 10. But as we can see there is no a variable with VIF exceeding 10. Therefore, we find nothing that multicollinearity is a serious problem in the model and the mean values of VIF for explanatory variables were 1.79. (See appendix 2.2.3)

Heteroscedasticity is where the variance of the error term is not constant. Heteroscedasticity is a situation where the disturbance terms, do not have constant variance. Since the presence of heteroscedasticity would result in inconsistent estimators, the model was then estimated with STATA version 13 software and used robust standard error to eliminate heteroscedasticity problem.

Probit model for commercialization, goodness-of-fit test. The Hosmer-Lemeshow test is a statistical test for goodness of fit for Probit regression model. It is used frequently in risk prediction models. The test assesses whether or not the observed event rates match expected in the model. This statistical test is widely used in the probit/logit model statistical/econometric model that, in its basic form of the binary dependent variable. This goodness-of-fit test compares the observed proportions to the test proportions to see if the differences are statistically significant or not. The p-value is less than the significance level (0.05) then the model is not a good fit. Then we conclude that the market participation effect is not significant, and then the econometric model is wellfit. (See the test result in appendix 2.2.3)

4.5.2. Diagnostic test for OLS model

The test result shows in the explanatory variables on welfare of smallholders there is no multicollinearity problem as an individual and overall mean because all value of VIF is less 10, (See appendix 2.3.1). In the cross-sectional data by default there was the heteroskedasticity problem, so to remove this problem either robust or transform is the solution. The robust was engaged for this study.

The normality test tells us random sample came from a normal distribution, the test gives us a W value; small indicate the sample is not normally distributed and large value / Prob 0.63520 > alpha 0.05 indicate that the data is normally distributed. (see appendix 2.3.1)

CHAPTER FIVE

5. SUMMARY, CONCLUSIONS AND RECOMMENDATIONS.

5.1. Summary of findings

Commercialization is an indispensable pathway towards economic growth and development for most low-income countries relying on the agricultural sector. Smallholder farmers always can earn more profit, increases their family income and promotes standard of living. So, commercialization of agriculture is not only just making a shift from subsistence oriented to market oriented, but also making better welfare outcomes for smallholder farmers in the form of increasing consumption of basic needs. The sufficient amount food, durable goods, education, healthcare and non-food consumption for the smallholder farmers. The degree of commercialization is low, then the low output would be marketed and vice versa.

The agricultural led industrialization strategy for development and the dominance of smallholder agriculture in Ethiopia, it becomes imperative that smallholder farmers be transformed from the subsistence-based production to market oriented production system. But the level of agricultural commercialization is not as much as possible.

The socio-economic and demographic factors of the small household farmers are analyzed in the descriptive result of categorical and continues independent variables of the study.

This study analyzes determinants of commercialization and welfare outcomes of small householder farmers. The focuses of study were on Guraghe zone farmers in the situation of in put out put market participation in 2018 own survey. The quantitative and qualitative research design and simple random sampling technique was employed. The study used the probit regression model for the determinants of commercialization and multiple regression for the effect of commercialization on welfare of small householder farmers. The heteroskedastic, goodness of fit test, normality, multicollinearity and correlation tests were also employed to test the statistical reliability of regression results.

The findings of commercialization indicate that majority of the households in the study area are mixed crop producers and most of the households purposely produce food-based crops for own consumption. This indicates that the majority of the households are subsistence-oriented. From the total respondents, the majority (79%) of them participated in the output market while the rest (21%) did not.

The study variables have either positive or negative impacts on small household farmers. From the variables only the explanatory variable distance from home to the market is statistically negative effect on the small householder commercialization. The findings from the probit regression analysis exposed what factors determine the attitude of smallholder commercialization. The survey result shows that eight explanatory variables were found statistically significant effect on their commercialization; namely, sex of household level (in value terms) at 1%, educational level at 1%, extension package at 1%, use of fertilizer at 5%, asses to credit at 1%, transport assesses at 5%, distance from home to market at 5% and household size at 10%.

The second dependent variable of the study is welfare outcome of the farmers. In this dependent variable Multiple regression model and 11 explanatory variables have employed. From those variables 5 of them have statistically significant impact on welfare. Finally, the OLS model that examines the effect of commercialization on welfare outcomes of smallholders. The dependent variable was measured by the annual consumption of households and the explanatory variables that have statistically significant were human capital at 1%, commercialization at 5%, food security at 1%, total income at 1% and household size at 1%.

Finally, the degree of smallholder’s commercialization leveled by market participation grouped into three categories such as low, medium and higher based on the result of consumption commercialization index (CCI).

5.2. Conclusions

The survey result from the total respondents in the study area, the majority (79%) of householders are participated in the output market while the rest (21%) did not participate.

The findings from the probit regression analysis exposed what factors determine the attitude of smallholder commercialization. Statistically significant variables regressed in probit model, namely; sex of household, educational, extension package, use of fertilizer, asses to credit, transport assesses, distance and household size. From the next dependent variable, human capital, commercialization, food security, total income and household size have a significant impact on smallholder’s welfare outcome.

From the findings of probit model, Male headed households have 0.00068 higher probability of market participation as compared to Female headed households. This may happen most of the time females have many tasks in their home and society specially in developing countries.

The smallholder farmer’s level of schooling increases the productivity and participation in the output market of farmers are increasing. The increment of education improves every aspect of socioeconomic, political and cultural outlook of farmers. The marginal effect result indicates the farmers one more level of education increases the probability of market participation of households increases by 5.71e-06, on average. So, this improves the skill of farmers on farming market-based crops and information.

The farmers member of extension package increases then improve the farmers market participation; through giving agricultural training, agricultural inputs and market information for the members. As the result 65% of farmers are covered but less functional. The usage of fertilizer gives the nitrogen and potassium for the soil this adds the fertility and increase productivity of agricultural crops, but extra usage especially on fertile soil may damage agricultural products. The financial sectors have a significant role on farmers participation and it helps in solving farmers cash problems in the time of production season to purchase agricultural inputs. On the other hands, improving this infrastructure for small householders could promote the level of commercialization.

A transport access is very important variable for every human being in any socioeconomic aspects. Transport access has a positive relation with commercialization of farmers and highly support to change the farmers’ economic situation. From the explanatory variables only the distance from home to the market is statistically negative effect on the small householder commercialization. The distance from home to market is high the smallholder farmers have a serious challenge in participating in output market. This is because the market was far from farmers home, then the householders traveled to get market beneficiaries, access, information, different services and does not easily take their agricultural input from the market and goes their product to the market. So, this makes commercialization of smallholder affects negatively and increased transaction cost.

Human capital is positive impact on small householders’ welfare. possible that increase in human capital leads to higher in in health and environmental protection, which would give higher potential to produce goods and services for consumption as well as for market. Whereas, the Impact of commercialization on welfare has positive effect of small householder farmers.

Family size, Total income and food security have positive impact on small householder welfare. Despite the fact increase family size and most of family members engaged by through their skills and potentials participate on family income generating activities. The family members participate on IGA then after increase total income of the households. The increments of family total income lead to increase purchase power of food (quality /nutrient food) and other inputs of the family. In other word the family enhance food security and cooperate on welfare goal of smallholder’s farmers.

Use of irrigation technology is necessarily solve farmers food insufficiency, but in this study area there is no vast irrigation technology as a result only (37%) of the respondents are irrigation users. As compared to its advantage, the amount is very small. Finally, the level commercialization increases, then improves welfare outcomes of smallholders in other word this change support to shift farmers from subsistence economy to more commercialized.

5.3. Recommendation

- The intensity to increase the householder’s commercialization, the government should encourage the farmers that they grow market-based crops.
- The female’s participation in output market is very less in study area, but the involvement of female headed householders is necessary for economy of the country. So, the household head as well as the concerned body should improve such kind of problem through sharing or minimizing tasks from their home and work place, giving an awareness on importance of female’s participation for the society, the giving beneficiary information about market and involving females in agricultural related training.
- The smallholder farmer’s level of schooling increases then the productivity and commercialization of farmers increase. So, the governmental and NGOs considering those advantage, should build the educational and agricultural centers for farmers.
- The extension package has the significant role in improve the farmers market participation; so, the government should check the package level of functionality and the distribution of fertilizer is adequate or not. The government should build governmental financial sectors in appropriate place of farmers and supports the private financial sectors to supply cash for smallholders.
- The government should build road infrastructure, ensure accessibility of transportation and establish market nearly from community to supply their production (output and input) for/from market, minimize extra use of energy and transaction cost.
- The government should increase the budget on health and educational expenditure to empowered small householder farmer on human capital.
- The government should develop the small householders’ skills of farming activities, improve production and commercialization the output through provide training and experience sharing within farmers. The small householders should encourage their family members to participate on income generating activities and government should hold the budget to increase the irrigation technology.
- Finally, this study suggests further research to delve more on the topic by including additional variables and new dimensions on small household commercialization and welfare outcomes. Furthermore, one can conduct research on the topic to identify possible determinants in small household farmers commercialization and how commercialization affects welfare outcomes by using cross sectional data and other econometric theories/analytical foundations to solve this statement in well manner.

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Appendix

1. Questionary

Determinants of Commercialization and Welfare outcomes of Smallholder Farmers Dear Sir/Madam

My name is . I am an enumerator for a research thesis conducted by

Tarku Tagesse an MSc student at Wolkite University. His research title is “Determinants of Commercialization and Welfare Outcomes of Smallholder Farmers in SNNP: A Case of Gurage Zone”. This questioner is designed for the purpose of collecting data from rural households to examines their participation in the market and welfare outcome of their participation. This questioner is purely an academic and any information you provide use will be used confidentially. So, feel free and respond to the question to be asked below. I would like to thank you in advance for your time and willingness to participate in this survey.

Thank you for your cooperation!!!!!

W oreda

Kebele

1.1. Basic Demographic characteristics of Respondents

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1.2. Farm Characteristics

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1.3. Farm input technology and financial service.

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1.4. Asset Endowment

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1.5. Market and Transport related issues.

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1.6. Income and Welfare related issues

a. Social capital Related issues.

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b. physical capital

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c. Human capital and related issues

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d. Food Security

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e. Income and Expenditure of household.

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2. Econometric test results

2.1. One- way ANOVA

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2.2. Probit Estimation for commercialization

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2.2.1. After robust action was taken

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2.2.2. Marginal effect

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2.2.3. Diagnostic test probit regression model Multicollinearity test

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Hosmer-Lemeshow goodness of fit for commercialization

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Correlation of independent variable

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2.3. OLS Estimation result for Welfare outcome

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2.3.1. Diagnostic test for OLS

Multicollinearity test

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Normality test

swilk resid

Shapiro-Wilk W test for normal data

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[...]

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¹ Exchange rate 1USD = 28 Ethiopian birr at the time of study (2018/19)

² Welfare in this sense, the rural households have plough oxen and enough land that improves the farmers consumption style and living standard.

³ Sustainable Development Poverty Reduction Program

⁴ See [Adem Bekele et al., 2013, Goitom Abera, 2009, Samuel and Kay, 2008]

⁵ So, this study is based on Unimodal, Bimodal and modernization theories. Unimodal strategy aims at the progressive modernization of the entire agriculture sector (e.g. Japan and Taiwan). The approach's major strategy is the maximum mobilization of labor and land resources of the developing countries and bimodal the approach is based on different theoretical perspective which asserts that commoditization and commercialization (e.g. Mexico, Colombia). modernization theory, modernization perspective and the need to be transformed traditional agriculture economy into modem large-scale market-oriented agriculture

⁶ Four tsimad is equivalent to one hectare