FACTORS AFFECTING SMALLHOLDER COFFEE PRODUCTION IN KARAGWE DISTRICT, TANZANIA

FACTORS AFFECTING SMALLHOLDER COFFEE PRODUCTION IN KARAGWE DISTRICT, TANZANIA

By

Rodrick Wilbroad Mugishagwe

A Dissertation Submitted in Partial/Fulfilment of the Requirements for the Degree of Masters of Science in Economics (Project Planning and Management) of Mzumbe University

2015

CERTIFICATION

We, the undersigned, certify that we have read and hereby recommend for acceptance by the Mzumbe University, A dissertation entitled Factors Affecting Smallholder Coffee Production in Karagwe District, Tanzania, in partial/fulfilment of the requirements for award of the degree of Master of Science in Economics (Project Planning and Management) of Mzumbe University.

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I, Rodrick Wilbroad Mugishagwe, declare that this dissertation is my own original work and that it has not been presented and will not be presented at any other University for a similar or any other degree award.

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This dissertation is a copyright material protected under the Berne Convention, the Copyright Act 1999 and other international and national enactment, on intellectual property. It may not be reproduced by any means in full or in part except for short extract in fair dealings, for research or private study, critical scholarly review or discourse with an acknowledgement, without written permission of Mzumbe University, on behalf of both the author.

ACKNOWLEDGEMENT

Since I enrolled in my graduate program at Mzumbe University, I have received tremendous assistance and encouragement from individuals and institutions. First and foremost I would like to thank the Almighty God for the blessing of the gift of life and that he endowed me during my studies. Secondly, I would like to express sincere thanks to my academic advisor, Dr. Silvanus Mbano, who have continuously encouraged and assisted by providing me invaluable comments and suggestions for my thesis and academic plan as well. I am deeply indebted to him for all endless support and kind hearted assistance during my study period.

I would like to express my endless gratitude to Mr. Evodius Kanyamyoga for his helpful comments and encouragement. He provided extremely gracious suggestions with productive discussion throughout the thesis research.

I gratefully acknowledge my father Mr. Wilbroad Mugishagwe for providing financial support for my graduate studies. He also provided his invaluable advice on my proposal, keeping track of research implementation conducted in Karagwe.

I would like to mention with remarkable appreciation to my friends Janifer, Grace, Catherine, Nasra, Godliver, Mzee Rutahwa.; my Uncles Evodius, Holmisdas, Respicius, Magnus, Alistakius and my Aunties Furaha and Beatrice for their moral and material support. Truly, their encouragement and invaluable assistance I received from them were also the key factor to accomplish this work thanks for their unfathomable generosity.

I also extend my special thanks to faculty members from Department of economics, Mzumbe University for their advice and encouragement during my graduate studies.

I am indebted to more people than I can name. Thank you all for being present in this unforgettable stage of my life.

DEDICATION

This Dissertation is dedicated with deepest love and affection to my beloved parents, Mr. and Mrs. Wilbroad Mugishagwe and my mother Methodia Kazimoto. They have been my source of inspiration and for sure, I owe them a lot in my life. To my young sisters, Irene and Lineth, and little brother Isaka. This dissertation is also dedicated to poor small scale farmers in Karagwe that live in pathetic condition and hoping that the recommendations offered in the study will provide an input toward improving their welfare.

ABBREVIATIONS AND ACRONYMS

ARTES - Africa Rainfall and Temperature Evaluation System
ERP - Economic Recovery Program
FAO - Food and Agriculture Organization
FTF - Fair Trade Foundation
GDP - Gross Domestic Product
ICO - The International Coffee Organization
KDC - Karagwe District Council
KDCU - Karagwe District Co-operative Union
Ksh - Kenyan shilling
LGA - Local Governmental Authorities
NBS - National Bereau of Statistics
SAP - Structural Adjustment Programme
SPSS - Statistical Package for Social Scientists
TaCRI - Tanzania Coffee Research Institute
TCB - Tanzania Coffee Board
Tshs - Tanzanian shilling
URT - United Republic of Tanzania
USD - United States Dollar
OECD - Organisation for Economic Co-operation and Development
MDGs – Millennium Development Goals
ASDS – Agricultural Sector Development Strategy
BACAS - Bureau for Agricultural Consultancy and Advisory Service

ABSTRACT

The study examined the factors affecting smallholder coffee production in Karagwe district. It provides both qualitative and quantitative information about the prevailing conditions affecting coffee production in the study area. Various aspects of the existing factors affecting coffee production (such as agricultural inputs price, climatic change, market policy reforms and price volatility) were examined to ascertain the linkage between those factors and coffee production. A cross sectional study design was used as it was a more intensive study that seeks to give a certain finding pertains to a larger population at a point in time. The survey covered a sample of 120 farmers aged 16+ drawn from 8 wards using simple random sampling procedure. The field results revealed that the factors affecting smallholder coffee farmers included; 89(74.2%) high prices of agricultural inputs, 100(83.3%) unpredictable climatic conditions, 59(49.2%) said price volatility has led to low individual incomes and 72(60%) have benefited from the market policy reform through increased price. Other constraints to small scale coffee production were 40(33.3%) inadequate extension services, 25(20.8%) inadequate financial services, 22(18.3%) pests and diseases respectively. The study therefore, recommended the government to: finance farmers and provide subsidies on agricultural inputs (fertilizers and seed varieties) to reduce cost of production, improve the techniques of farming and construct irrigation schemes to reduce the effect of climate change especially prolonged droughts so as to increase productivity.

TABLE OF CONTENTS

CERTIFICATION i
DECLARATION AND COPYRIGHT ii
ACKNOWLEDGEMENT iii
DEDICATION iv
ABBREVIATIONS AND ACRONYMS v
ABSTRACT vi
LIST OF TABLES x
LIST OF FIGURES xi

CHAPTER ONE 1
BACKGROUND INFORMATION 1
1.1 Introduction 1
1.2 Background 1
1.3 Problem Statement 7
1.4 Objectives of the Study 8
1.4.1 General Objective 8
1.4.2 Specific Objectives 8
1.5 Research Questions 8
1.5.1 Main Research Question 8
1.5.2 Specific Research Questions 8
1.6 Significance of the Study 9
1.7 Limitation of the Study 10
1.8 Organization of the Study/Dissertation 10

CHAPTER TWO 11
LITERATURE REVIEWS 11
2.1 Introduction 11
2.2 Theoretical Literature 11
2.2.1 Concept of Production 11
2.2.2 Concept of Smallholder Production 12
2.2.3 Factors Affecting Coffee Production 13
2.3 Empirical Literature 20
2.4 Research Gap 25
2.5 Conceptual Framework 26
2.5.1 Relationships between Variables 27

CHAPTER THREE 28
RESEARCH METHODOLOGY 28
3.1 Introduction 28
3.2 Research Design 28
3.3 Study Area 29
3.3.1 District Profile 29
3.4 Study Population 30
3.5 Sample and Sampling Techniques 31
3.5.1 Sample Size 31
3.5.2 Sampling Techniques 32
3.6 Data Collection Methods 32
3.7 Data Collection Instruments 33
3.7.1 Self-administered questionnaire 33
3.7.2 Personal Interviews 33
3.7.3 Observation 33
3.7.4 Documentary Sources 33
3.8 Data collection and Analysis 33
3.9 Data Reliability and Validity 34

CHAPTER FOUR 36
PRESENTATION, ANALYSIS AND DISCUSSION OF FINDINGS 36
4.1 Introduction 36
4.2 Analysis, Discussion and Interpretation 36
4.3 General Socio-Economic Characteristics of Coffee Farmers 36
4.3.1 Age groups of respondents 36
4.3.2 Gender of respondents 37
4.3.3 Education level of respondents 39
4.3.4 Main source of household income 40
4.3.5 Household Size 41
4.3.6 The Existing Conditions Attached to Land Access and Coffee Production 42
4.4 The Effects of Agricultural Inputs Prices on Coffee Production in the Area 44
4.4.1 The influence of inputs purchase on coffee production 44
4.4.2 Impact of Agricultural inputs prices on coffee production 45
4.5 The influence of climate change on coffee production in the district 46
4.6 The influence of Market policy reforms on coffee production in the area 49
4.7 The effects of Coffee Price Volatility on Coffee Production in the Area 50
4.8 Other factors affecting smallholder coffee production in Karagwe District 52
4.9 Coffee production function analysis 54

CHAPTER FIVE 56
SUMMARY, CONCLUSION, AND POLICY IMPLICATIONS 56
5.1 Introduction 56
5.2 Summary of the Study Findings 56
5.3 Conclusion 57
5.4 Policy Recommendations 58
5.5 Limitations of the Study 59
5.6 Areas for further research 59

REFERENCES 61

APPENDICES................................................................................................................70

LIST OF TABLES

Table 1.1: Coffee Production in Kagera region in Tons 6
Table 3.1: Distribution of respondents by ward 32
Table 4.1: Age groups of the respondent 37
Table 4.2: Education level of respondents 39
Table 4.3: Main sources of income 40
Table 4.4: Occupations of Respondents 40
Table 4.5: Land size owned by coffee farmers 42
Table 4.6: Inputs purchasing among the farmers 44
Table 4.7: Reasons for not purchasing inputs 45
Table 4.8: Farmers' perception on inputs prices 46
Table 4.9: The trends of climate change in the area 46
Table 4.10: Any increase in output 47
Table 4.11: Reasons for increased or decreased coffee output 48
Table 4.12: Marketing channels 49
Table 4.13: Awareness on market reforms 50
Table 4.14: Impact of price volatility on production 50
Table 4.15: Coffee prices offered per kilo 52
Table 4.16: Other factors affecting coffee production 53
Table 4.17: Estimate of the production function analysis 55

LIST OF FIGURES

Figure 1.1: Main Coffee Production Regions/Districts in Tanzania 3
Figure 2.1: Conceptual Framework 26
Figure 2.2: Relationships between Variables 27
Figure 3.1: Karagwe District Map 30
Figure 4.1: Gender of respondents 38
Figure 4.2: Household Size 41

CHAPTER ONE

BACKGROUND INFORMATION

1.1 Introduction

This study was set to investigate the factors affecting smallholder coffee production. In this chapter, the study introduced the main issues covered. It mainly focused on the background information; statement of the problem, research objectives and questions. The significance of the study and its contributions was be identified and discussed. Limitations and organisation of the study are also provided at the end of this chapter.

1.2 Background

The agriculture sector is a key to overall economic growth and development of Tanzania. In the national development agenda, agriculture is expected to lead the growth and structural transformation of the economy and maximize the benefits of accelerated growth. Significant improvements in the productivity of the agriculture sector are required to raise the average real incomes of the Tanzanians as a whole. The food and agriculture sector also has direct impact on the attainment of some of the Millennium Development Goals (MDGs) (United Republic of Tanzania [URT], 1997).
Agriculture continues to be the second largest sector of Tanzania’s economy after the service (47.4%), contributing about 27.6 percent of GDP compared to about 25 percent for the industry sector and it also contributes to 35 percent of the foreign exchange earnings and about 80 percent of employment (URT, 2012). This indicates that Tanzanian like most low-income countries has a high proportion of their population dependant on agriculture for their means of livelihood. Therefore the sector is critically important in determining economic development of the country. Although economic theory suggests that the relative importance of agriculture declines as economies grow, agriculture is usually critical for such structural transformation to occur. Historically the sector in Tanzania has been mainly dominated by smallholder farmers who grow different kinds of crops for both domestic consumption and for cash. Crops are commonly cultivated on relatively small pieces of land averagely ranging from 0.9 to 3 hectares (URT, 2011). Main food crops grown are maize, rice, sorghum, wheat, pulses, cassava, millet and sweet potatoes while the main cash crops grown include coffee, cashew nut and sisal (ibd, 2011).

Coffee is the largest agricultural export crop in Tanzania which significantly contributes approximately Tshs. 193 billion ($115 million) to export earning every year (Baffes, 2003). Tanzania’s production of coffee is currently about 48,000 tons, or about 0.8% of the world’s output of 7.02 million tons per year (International Coffee Organization [ICO][1], 2004). Types of coffee grown are Arabica and Robusta. Arabica coffee makes up to 70 percent the total coffee production in Tanzania and Robusta constitutes the remaining 30 percent. The main coffee producing areas include Northern and Southern regions for Arabica coffee, and the Western region for Robusta coffee (Appendix 1). In the Northern region coffee production areas are composed of Rombo, Moshi, Hai, Siha, Mwanga, and Same districts in Kilimanjaro Region, as well as Arumeru District of Arusha Region. Those in the Southern region are mainly comprised of Mbozi and Rungwe districts of Mbeya Region and Mbinga District of Ruvuma Region, whereas the Western region is composed of Bukoba, Karagwe, and Muleba districts of Kagera Region. Tanzanian Coffee Board (TCB) estimates that 275,000 hectares are under coffee cultivation, large private estates can yield up to 2.5t/ha with irrigation and fertilizers, while smallholders average 0.3t/ha (TCB, 2010).

In global trade for agricultural produce, coffee is one of the most valuable primary products. It is predominantly grown by 25 to 30 million smallholder producers in about 80 countries in the tropics (Aderolu et al., 2014). In 1998/99, World coffee production averaged 6.3 million tons. In Latin American coffee production increased by almost 22 percent between 1997/98 and 1998/99, attributable to a 52 percent expansion in Brazilian production, which more than offset reductions in other major regional coffee producers (Food and Agriculture Organization of the United Nations [FAO], 2000). Production declined in Guatemala and Mexico by 19 and 14 percent respectively, between 1997/98 and 1998/99. This was due to damages sustained from Hurricane Mitch. Colombian production was also down by 6 percent for 1998/99 due to excessive rains which adversely affected bloom-stage tree development, resulting in reduced cherry output (ibid, 2000).

Exports of coffee were 4.8 million tons in 1998, a 12 percent increase over 1997. Exports from Brazil almost doubled to 1.3 million tonnes during 1998, and accounted for 28 percent of world total exports (ibid, 2000). Guatemala and Mexico, other major Latin American exporters registered declines in coffee exports. Shipments from major African coffee exporting countries such as Ethiopia, Kenya and Uganda increased over the same period, while exports from important Asian exporters, Indonesia and Vietnam, declined. The major coffee producing countries in Africa are Cote d' lvoire, Cameroon, Ethiopia, Uganda, Kenya and Tanzania (FAO, 2000). Global production in the 2002/2003 season was 7.2 million tons while consumption has been relatively stable in the last couple of years at fewer than 6.6 million tons (ICO, 2004).
A substantial proportion of Tanzanian coffee is grown by a large number of smallholders. It is estimated that between 400,000 and 500,000 smallholders, with an average area of 0.5 to 3 hectares, are responsible for 90 percent (50,000 Tons) of coffee produced every year and the remaining 10 percent is grown on estates (TCB, 2010). During the 1972/73 crop season, just before massive nationalisation of coffee estates, smallholders and large estates contributed 76 percent and 24 percent of coffee output, respectively. By 2004/05, the smallholders produced 93 percent of the country’s coffee output, and this proportion has not changed significantly since then (Mmari, 2012). This predominance of smallholders in commercial coffee production has led to some limitations in technological improvement in processing and farming intensity, which is associated with limited capacity in financial capital, skills, and economies of scale (ibd, 2012)

As part of the process of SAP, the Tanzanian government undertook a series of major reforms. These reforms included the decontrol of marketing of non-traditional export crops in 1986, decontrol of marketing of food crops in 1989 and finally a decontrol of marketing of traditional export crops in 1993/94 marketing season (URT, 1997). One important objective of the reform program was to increase the profitability of cash crops by allowing participation of cooperatives and private traders in the marketing aspects of all agricultural crops in a competitive marketing environment that included competitive prices and free entry of marketing actors (producers, traders, processors and exporters) at all levels of the marketing channel among other things (ibd, 1997).

Initially, large public enterprises dominated most industries and had legal monopolies in the pricing, marketing, and processing of agricultural crops (World Bank, 1977). Producers of cash crops (mainly coffee, cashew nuts, sisal, tea, and tobacco) traditionally Tanzania's main source of export earnings had to sell their products to marketing parastatals (quasi-governmental organizations), which offered prices well below world prices. However the farmers were faced with procurement prices that declined steadily, in relation to both the consumer price index and world prices. Those declines resulted from the appreciating real exchange rate, the increasing inefficiency of the marketing boards, and the government's policy shift to favouring food crops over export crops. By the mid-1980s, it was generally recognized that Tanzania's overly restrictive external trade policies and the consequent reduction in its exports were seriously undermining its economic performance. To address these issues, the government's 1996 Economic Recovery Program (ERP) sought to reinvigorate the export sector by eliminating cost-price distortions and introducing import liberalization measures (URT, 1997). Whereas these policy measures were considered necessary to recover the macro-level Tanzanian economy, Tanzania’s coffee producers suffered from lower earnings, shortages of agricultural inputs, and greater cost sharing of educational and health expenses.

For the past 15 years or so, coffee production in Tanzania showed varying trends (Bureau for Agricultural Consultancy and Advisory Service [BACAS], 2005). Coffee production moderately declined from the early 1990s to 1998 after which it gradually increased until 2003. Area under coffee expanded significantly during the 1970s and 1980s when prices were more favourable but declined thereafter. From 1980 to 1998 coffee sales (equivalent to total output) declined from 61,514 tons to 47,050 tons. Output declined from a nine-season pre-1994-95 average of 50,918 tons of a five season post-1994/95 average of 45,065 tons, a 13 percent decline. TCB estimates the current area of production in the country to be 250,000 ha compared to the area suitable for coffee production, which is 650,000 ha (TCB, 2010). According to aggregate data, productivity of coffee in Tanzania relative to other sub-Saharan African (SSA) countries, measured as three-year average yields, declined from the early 1990s to 1994, remained relatively stable to 1998 and then increased in 2003 (BACAS, 2005). Tanzanian coffee yields relative to the rest of the world have gradually declined over the 1990s and early 2000s.

In Karagwe district, coffee is the main cash crop grown and it accounts for about 50 percent of the coffee produced in Kagera region (TCB, 2010). About 95 percent of the coffee produced is sold for export; the remainder is sold to the local market (KDC, 2014). The main coffee marketing organization is the Karagwe District Co-operative Union (KDCU), though there are other private coffee buyers. Annual production volumes vary widely between 3,000 and 9,000 tons of green coffee (Fair Trade Foundation [FTF], 2011). This cyclical trend is attributed to a combination of unpredictable rainfall patterns, availability of fertile soils and the level of resources invested by farmers in terms of time and agricultural inputs. Table 1.1 shows coffee production by district in Kagera region.

Table 1.1: Coffee Production in Kagera region in Tons
|District |2005/06 |2006/07 |2007/08 |2008/09 |2009/10 |2010/11 |
|Karagwe |3,817 |9,123 |8,794 |21,384 |8,711 |10,450 |
|Bukoba |1,926 |5,187 |3,000 |2,161 |1,345 |3,575 |
|Ngara |147 |215 |339 |1,270 |138 |413 |
|Total |9,919 |21,213 |15,992 |
|Kanoni |15 |15 |100 |
|Nyaishozi |15 |15 |100 |
|Kituntu |15 |15 |100 |
|Ihanda |15 |14 |93.3 |
|Kihanga |15 |15 |100 |
|Igurwa |20 |19 |95 |
|Chanika |15 |12 |80 |
|Bugene |15 |15 |100 |
|Total |125 |120 |96 |

Source: Field Data Survey, 2015

3.5.2 Sampling Techniques

According to Kothari (2004), sampling refers to the process of picking up few or small units out of whole population for study. Such unit is expected to be representative of the whole population. Noting that famers were homogeneous in nature, simple random technique was used to select them. This was so because the study intended to provide equal chances of being included in the sample to avoid bias. Therefore, a total of 120 coffee farmers were chosen randomly.

3.6 Data Collection Methods

This study used both primary data and secondary, with quantitative and qualitative nature. The objective nature of primary data, since they were not been interpreted by any researcher before, were given the first priority in this research, without ignoring the importance of secondary data in accomplishing the study. The novelty of information gathered from primary data gives the researcher confidence in covering the gap, using the most recent information.

3.7 Data Collection Instruments

3.7.1 Self-administered questionnaire

The self-administered questionnaire (with open and close ended questions) was used to gather information from farmers. English and Kiswahili languages were used depending on how comfortable the respondent was in using a given language.

3.7.2 Personal Interviews

The researcher used the interview to collect information, which was difficult to be collected by the questionnaire method. The researcher had to communicate with respondent through face to face interview and non-structured interview was used as it gives interviewer much greater freedom to ask and allow the respondent to express freely.

3.7.3 Observation

The researcher used participatory observation method to observe daily practices, aspects and activities carried out in coffee farms in Karagwe district. This allowed the researcher to obtain first hand information through experience or seeing what was taking place.

3.7.4 Documentary Sources

Documentary review involved reviewing of existing literatures that provided key concept to be used in any area of interest. The researcher had to review various material records documents, books, journals and websites; from Internet and from library. This method of data collection was considered suitable in situations where farmers may fail to respond to all imposed questions due to lack of correct memories and shortage of time.

3.8 Data collection and Analysis

The study relied on primary and secondary sources of data. The secondary data involved the review of existing literatures and similar studies from other scholars to have clear understanding of the subject. Personal interviews, questionnaires and observation enabled the researcher to collect the primary data.

Statistical Package for Social Science computer software (SPSS) was used for analyzing both qualitative and quantitative data. Descriptive statistics such as mean, percentages, standard deviation and coefficient of variation were used to summarize the results. In addition, multiple regression model was employed to determine the factors affecting coffee production in the study district. The proposed regression model for this study adopted from Maddala (2002), was as shown below:
Q =f (PI, PCc, MPR, CC) (3.1)

Where,

Q = total output of coffee in terms of quantity (in kilograms) produced,
PI = agricultural inputs price
PC = coffee price
MPR = market policy reforms
CC = climate change

While the econometric model is specified as follows;
LnQ = lnα + β1ln PI + β2ln PC + β3ln MPR + β4lnCC + (i (3.2)

Where,

α = Constant term/ intercept

β1 - Β4 = Coefficients associated to the specific variables

(i = The Stochastic Error term

3.9 Data Reliability and Validity

To make sure we get a range of valid qualitative and quantitative data, the questionnaire included many closed ended and objective questions, which was meant to solicit answers from respondents which can be assigned numerical values in figures, percentages or intervals. Otherwise, the data was not measuring objectively, what the study intended to measure.

Moreover, in attaining the reliability of this research results, the random sampling and objective questionnaires were used in collecting data. By so doing, data collected and analyzed were expected to give results, which meant the same to the majority of coffee farmers in Tanzania.

CHAPTER FOUR

PRESENTATION, ANALYSIS AND DISCUSSION OF FINDINGS

4.1 Introduction

This chapter attempts to analyze the primary data collected with methodologies already discussed in the previous chapter. The chapter is divided into three major sections of which the first one discusses the characteristics of the respondents and the second section discusses the specific objectives of the study.

4.2 Analysis, Discussion and Interpretation

The response rate for the survey was high. One hundred twenty (120) representing 96% of the questionnaires were returned and respondents in all wards were equally selected. The high response rate was due to the fact that most of the questions were simple and asked directly to the respondents to be answered and the research could wait until the process is completed.

4.3 General Socio-Economic Characteristics of Coffee Farmers

The general description about small scale farmers gives an overview of the people who took part in the study. In view of the researcher, these demographic and socio-economic characteristics of respondents have so much bearing on responses given by the respondents on the state of coffee production in the district. They have important value attributes to any society as they reflect their behaviour in decision making and the expected responses. The general characteristics of respondents examined in this study included age, gender, education level, main source of income and family size to mention but some.

4.3.1 Age groups of respondents

This study considered age as an important variable since it determined various inter households and intra households’ characteristics, which include ownership and control of important resources such as land and household assets. Among the 120 respondents interviewed, majority 56(46.7%) were aged above 45 years, while 37(30.8%) were aged between 36 - 45 and others 17(5.8%) were aged between 16 and 25 respectively. The findings imply that, most of the respondents interviewed were mature and responsible people as were found engaging in different socio-economic activities in the area. They were therefore in a position of giving not only the information needed, but also relevant one to meet the purpose of the study.

This was considered important because most of the demographic events that determine population dynamics such as birth, death, dependency ratio and mobility are highly associated with the age variable. Physical strength depends also on age. Therefore, land acquisition and additional income can be influenced by age of a person. This indicates that majority of respondents were in active age and they can influence land acquisition in the society and living in rural areas means they would require land.

Table 4.1: Age groups of the respondent
|Age groups |Frequency |Percent |
|Below 16 years |3 |2.5 |
|Between 16 and 25 years |7 |5.8 |
|Between 26 and 35 years |17 |14.2 |
|Between 36 and 45 years |37 |30.8 |
|Above 45 years |56 |46.7 |
|Total |120 |100.0 |

Source: Field Data Survey and SPSS Output File, 2015

4.3.2 Gender of respondents

Gender significantly influences activities, resources and opportunities of people that is, by the socio-economic and cultural dimension of being male or female (Fernando, 1998). Moreover, different types of activities and tasks are generally allocated to women and men within the family in terms of subsistence production and production for the market. Figure 4.1 provides a summary of male and female proportion of the 120 surveyed respondents in Karagwe district. Results show that majority of the respondents 73(60.8%) were male. This pattern was followed by 47(39.2%) who were female headed households. This was due to the fact that majority of the customers attended for interviews were mostly male. Based on the obtained findings, it was evident that more men were found mostly involved in coffee production in Karagwe district than women. The findings were consistent with the results revealed in a study by Cheryl (2001) who came up with similar observations with more men being involved in cash crop production than women in Ghana. The reasons for this trend were linked to the fact that in rural areas men are often viewed as being responsible for producing cash crops, while women are responsible for producing substance crops for home consumption. Because of their limited access to essential production resources, such as land, labour, and inputs, women’s role in crop agriculture is often restricted to producing subsistence food crops with low potential to generate income. Besides this, it is believed that female farmers are very good in vegetable production and also assist their male counterparts on their farms.

According to URT (1997), it was revealed that the proportion of women to men shows a departure from the usual Tanzania pattern. In rural areas where 82% of women live, the importance of women as producers of wealth is out of proportion to their number. Women as a group are more vulnerable to health risks because of gender inequalities in terms of social and economic domains.

Figure 4.1: Gender of respondents
[pic]

Source: Field Data Survey and SPSS Output File, 2015

4.3.3 Education level of respondents

Agriculture has undergone considerable technological progress following the innovation of high-yielding crop varieties and massive use of chemical fertilizers. In a rapidly changing technological environment, education becomes even more important because farmers’ ability to deal with disequlibria induced by technological change depends largely on education. This study equally assumed that education level plays a significant role in general-skill building up. For instance, literacy enables farmers to follow written instructions for applying chemicals, whereas numeracy may assist in calculating correct dosages in the practices of application. Results in Table 4.2 presents a summary of education level of respondents with respect to years spent in schools. The results showed that out of 120 respondents interviewed, majority had attained primary school level education 65(54.2%) while a few of them 35(29.2%) attained secondary school education. These results indicate that, majority of the respondents who were evolved in this study had lower levels of education. The findings are in line with a study by Croppenstedt et al. (1998), in fertilizer marketing survey by using data of USAID, which resulted that literate farmers are more likely to adopt use of fertilizer than those who are illiterate. Empowering rural coffee smallholder producers to access quality education will mean empowering them to equal opportunities to access and own resources and hence improved livelihoods. According to Mongi (2005) education has always been valued as means of liberation from ignorance and enables a person to perform non- traditional roles. In the study area, most of the people in villages take up farming activities after completing their primary education. As a consequence, a high proportional of respondents were involved in farming. This suggests therefore that, concerted efforts must be made for the attainment of the MDGs and general empowerment of community members if the prevailing situation is to be reversed.

Table 4.2: Education level of respondents
|Variables |Frequency |Percent |
|No school attended |15 |12.5 |
|Primary school education |65 |54.2 |
|Secondary school education |35 |29.2 |
|Technical/Vocational |5 |4.2 |
|Total |120 |100.0 |

Source: Field Data Survey and SPSS Output File, 2015

4.3.4 Main source of household income

Of the 120 of all respondents interviewed, 109 (90.8%) attained their income from farming. That being the case, the need to own land as one of the very important asset for rural population empowerment and ultimately poverty reduction becomes imperative. Indeed, if we need to seriously address issues of poverty and food security especially among rural households, we ought to combat the prevailing imbalance in terms of land ownership and other resources. With reference to the study findings, only 11 (9.2%) obtained their income from business activities.

Table 4.3: Main sources of income
|Variable |Frequency |Percent |
|Farming |109 |90.8 |
|Petty Business |11 |9.2 |
|Total |120 |100.0 |

Source: Field Data Survey and SPSS Output File, 2015

Furthermore, when the respondents were asked on their main occupations, majority 116 (96.7%) attained their livelihoods from farming. However, 6 (3.3%) were found engaging in petty business as their main sources of occupation. Moreover, respondents were asked to estimate their income attained per month. Most of them (94.2%) were below Tshs. 50,000. This results shows that, most of the families were subject to low income earnings which could not enable them to afford for example to pay fees for their children. A large proportion of household productive activities were therefore just sufficient to support subsistence requirements and that, opportunities for marketed surplus were few during the year. Meeting household's cash needs for expenses such as school fees, buying inputs and other family requirements was a constant challenge for most households.

Table 4.4: Occupations of Respondents
|Variable |Frequency |Percent |
|Farming |116 |96.7 |
|Petty Business |6 |3.3 |
|Total |120 |100.0 |

Source: Field Data Survey and SPSS Output File, 2015

4.3.5 Household Size

Household size is very important in determining the size of family labour force. Family labour constitutes the main source of labour and sometimes, the only source of labour employed by resource small-scale farmers (Adegeye and Dittoh, 1985). It comprises the labour of all males, females and children in the family or household because they partake in the cultivation of the household holdings. Labour availability is known to increase the size of land put under cultivation, as strength of the labour availability is positively correlated with land placed under cultivation. The figure 4.2 provides a summary of households’ size. Results indicate that out of 120 respondents interviewed, 70 (58%) of the respondents ranged between 2 to 5 members and 50(41.67%) ranged between 6-9 members. As shown in 4.2, results of this study indicated that, in most cases, households size were distributed between 2 - 5 people and between 6 - 9 people. On average therefore, the households size ranged to an average of 8 people. These results imply that, the average household sizes were relatively higher when compared to an average household size 4.9 of Tanzania mainland (National Bereau of Statistics [NBS], 2002). However, the recorded family sizes are comparable to other densely populated areas in the country, such as Lushoto and Iringa rural Districts (Ngailo et al., 2007).

Figure 4.2: Household Size
[pic]

Source: Field Data Survey, 2015

4.3.6 The Existing Conditions Attached to Land Access and Coffee Production

Land is the basis for every form of physical development and constitutes the primary medium for agricultural production (Lasun, 2006). Hence, it’s the farmers’ most important asset and plays essential role in increasing as well as sustaining the agricultural production.

A number of land tenure systems were found in the study area. The associated effect of land tenure system on income poverty to rural households varied significantly from one type of tenure system to another. Customary land tenure system was found to be the most dominant type of land holding particularly for natural pasture resource in the study area. It should be noted here however that, the existing land tenure systems were found not favourable on part of female. With respect to the findings in this study, out of 120 respondents 80 (66.7%) owned land between 0-3 acres. A few 26 (21.7%) owned between 4-6 acres. Therefore, majority of the respondents owned between 1- 6 acres. However, the land tenure systems were male dominated when it comes to the issue of access and ownership of resources like land.

Table 4.5: Land size owned by coffee farmers
|Variables |Frequency |Percent |
|0-3 hectares |80 |66.7 |
|4-6 hectares |26 |21.7 |
|7-9 hectares |5 |4.2 |
|Above 10 hectares |9 |7.5 |
|Total |120 |100.0 |

Source: Field Data Survey and SPSS Output File, 2015

The study revealed further that, there was a direct relationship between access, ownership and control of land on one hand and improved living conditions of the people in the study area. This implies that, strengthening people's access to land could significantly contribute to poverty reduction and food security. This was evidenced by 90% of the respondents were engaging in agriculture as the main source of their livelihoods.

Moreover, the question of land tenure system was revealed by other empirical studies as the main challenge. Some of these challenges were policy-related and institutional constraints. For example, FAO (2009) indicated that, hopes that policies would bring about positive and durable results remain unmet. The remaining main policy bottlenecks include those that pertain to land tenure and land distribution to different segments of the population, marketing of agricultural commodities and inputs, and price regulatory frameworks. In Ethiopia, for example, the inappropriate agricultural policies related to land distribution, collectivization and rigid price regulation have been identified as one of the constraints to investment in agriculture and hence a handicap to productivity.

In Kenya persistently large public borrowing and high lending rates have discouraged investment in agriculture. Even though Tanzania has instituted several agricultural reforms and strategies including the agricultural development framework in the early 1970s and Agricultural Sector Development Strategy (ASDS), most of the policies had no significant impact on the majority smallholder farmers especially women. In Uganda, despite the adoption of the Plan for Modernization of Agriculture in 2002 the smallholder farmers still receive a disproportionately small amount of developmental resources.

No doubt, some of the inability of government to implement these programs stems from weak administrative and technical capacity particularly in ministries of agriculture. Institutional support to agricultural development in the four countries studied has been inconsistent and largely inadequate. As elsewhere in Africa, institutions responsible for agricultural development need to be strengthened, with an emphasis on well-functioning markets and risk management (FAO, 2009).

As the experience of successful agricultural reformers shows, the importance of market oriented reforms for sustained productivity improvements in agriculture cannot be overstated. For example, the increase in rice output and productivity in Vietnam during 1981-1994 can be ascribed mainly to market reforms and in spite of modest growth of most inputs and with limited technological change. The key factor among the Vietnamese market reforms was an institutional change – reform of land property rights, which markedly improved the economic incentives of farmers to use the land efficiently (Che et al., 2006).

At the same time, the experience of Tanzania illustrates that market reforms are necessary but not sufficient for raising agricultural productivity. Even though the country undertook substantial market-oriented reforms during the 1990s, agricultural performance remained disappointing. The main bottlenecks to farmers’ more effective supply responses to improved incentives were structural – limited access to markets, credit and inadequate infrastructure (Danielson, 2002). Hence the combined experiences of Vietnam and Tanzania show the importance of reforming the institutional framework underpinning agriculture as well as the complementarities of reforms in the area of infrastructure, access to markets and to credit.

4.4 The Effects of Agricultural Inputs Prices on Coffee Production in the Area

4.4.1 The influence of inputs purchase on coffee production

With respect to one of specific objectives of this research that intended to identify whether the cost of agricultural inputs affect coffee production and in line with the research question asking whether agricultural inputs prices affect coffee production in the study district. The findings of the study indicated that out of 120 respondents, majority 116 (96.7%) were not purchasing inputs and only 4(3.3%) purchase inputs.

Table 4.6: Inputs purchasing among the farmers
|Do you purchase inputs |Frequency |Percent |
|Yes |4 |3.3 |
|No |116 |96.7 |
|Total |120 |100.0 |

Source: Field Data Survey and SPSS Output File, 2015

Among the reasons attributed to this situation was on the fact that were too expensive to afford. This was responded by a large group of respondents 80 (70.7%) of the 116 farmers who were interviewed. This was a clear indication that, most of coffee farmers were not likely to afford the costs by purchasing agricultural inputs. This calls for concerted efforts by the government to support smallholder farmers producing coffee. In totality, this might be attributed to the fact that lack of effective use of purchased inputs was part of the persistently low productivity.

Table 4.7: Reasons for not purchasing inputs
|Do you purchase inputs |Frequency |Percent |
|It is too costly |82 |70.7 |
|Not available |34 |29.3 |
|Total |116 |100.0 |

Source: Field Data Survey and SPSS Output File, 2015

4.4.2 Impact of Agricultural inputs prices on coffee production

Availability of good quality affordable inputs is clearly a major constraint for smallholder farmers, the study wanted to investigate the cost of inputs and their impact on smallholder coffee production. The results are shown in Table 4.8.

Observations on the distribution indicate that majority of the farmers constituting 89 (74.2%) of the 120 respondents agree that the prices of inputs are very high. Not only that but also a few farmers constituting 16 (13.3%) of the total farmers said the price is average while a small number of farmers 5 (4.2%) of respondents said the price is low and about 10 (8.3%) of the total sample could not acknowledge on the prices of inputs. In this regard therefore, majority of respondents were in opinion that the prices of inputs are very high. This could be the reason why most of the farmers in Karagwe District do not use inputs for coffee production.

The results are in line with other studies pertaining to factors affecting coffee production Karanja and Nyoro (2002) in the a study on Coffee Prices and Regulation and their Impact on Livelihoods of Rural Community in Kenya revealed that the escalation of coffee production costs due to major increases in the cost of purchased farm inputs as a major cause for the coffees decline in productivity. Not only that but also, a large variety of studies in different regions of Nigeria have identified the scarcity and high cost of inputs (labour, agrochemicals, and fertilizer) as major impediments to raising the productivity of smallholder farmers (Ojo 2005; and Adejoh 2009).

Table 4.8: Farmers' perception on inputs prices
|Variables |Frequency |Percent |
|High |89 |74.2 |
|Average |16 |13.3 |
|Low |5 |4.2 |
|I don't know |10 |8.3 |
|Total |120 |100.0 |

Source: Field Data Survey and SPSS Output File, 2015

4.5 The influence of climate change on coffee production in the district

With respect to this variable, climate change was acknowledged as one of the most important factors affecting coffee production in the area. 120 farmers responded to this question. Study findings indicated that majority of the respondents 100 (83.3%) agreed that climate was not predictable. In terms of production rate, majority of the respondents 75 (62.5%) was reported to have no significant increase. That means, production rates were stagnant in a sense that no increase was realized. The reason for this situation was attributed to the recurring drought. This in turn was affecting more crop production.

Table 4.9: The trends of climate change in the area
|Variables |Frequency |Percent |
|Good for farming |11 |9.2 |
|Too dry |7 |5.8 |
|Too wet |2 |1.7 |
|Unpredictable |100 |83.3 |
|Total |120 |100.0 |

Source: Field Data Survey and SPSS Output File, 2015

Literature indicate further that increases in global warming leading to changes in main climate variables; temperature, precipitation, sea level rise, atmospheric carbon dioxide content and incidence of extreme events have significant affect on agricultural production. The study findings indicates that agricultural production in Karagwe has experienced unpredictable weather changes more and more frequently this often causes severe supply problems. Based on that, the study wanted to determine if there has any increment in the amount of coffee produced as a results climate change.
The study revealed that, on average, the output bags ranged between 1- 3 bags only 73 (60.8%). In this regard, the respondents said that there has been no increase in the number of bags harvested as a result of climate change. A few 27 (22.5%) reported that there was an increase in the number of bags. Change in climatic condition contributed much on determining the level of harvest to farmers because agricultural supply was mostly based on rain and highly dependent on the weather. Therefore, for the farmers the annual weather differences is more important than eventual climate change. Drought was identified as the main cause for the decrease in coffee production.

Table 4.10: Any increase in output
|Increase in bags |Frequency |Percent |
|Yes |45 |37.5 |
|No |75 |62.5 |
|Total |120 |100.0 |

Source: Field Data Survey and SPSS Output File, 2015

When the respondents were asked to give their opinion/reasons as to why their crop produce were fluctuating in terms of output per unit area, the responses were associated to occurrences of droughts 81 (67.5%) and heavy rains 35 (29.2%). With respect to this aspect, these two aspects were identified as the most important factors that were affecting coffee production in the area. It was further noted that, it is important to note that current initiatives to reduce the extent of global warming are mostly aimed at limiting further warming, not to rapidly reverse it. Complexity and uncertainty make it hard to be precise but it is generally accepted that climate change will affect smallholder coffee producers. Rising temperatures are expected to render certain producing areas less suitable or even completely unsuitable for coffee growing, meaning production may have to shift and alternative crops will have to be identified. Incidences of pests and diseases will increase whereas coffee quality is likely to suffer, both factors that may limit the viability of current high quality producers. More coffee may need to be grown under irrigation, thereby increasing pressure on scarce water resources.

Table 4.11: Reasons for increased or decreased coffee output
|Variables |Frequency |Percent |
|Droughts |81 |67.5 |
|Heavy rains |35 |29.2 |
|Humidity |2 |1.7 |
|Temperature |2 |1.7 |
|Total |120 |100.0 |

Source: Field Data Survey and SPSS Output File, 2015

The findings are in line with other studies such as Bello et al. (2012) when investigating Climate Change Impacts on Agriculture and Food Security in Nigeria, it was observed that, within the period of 105 years, rainfall decreased by 81 mm with increasing temperature of 1.1℃. The unpredictability of rainfall and steadily increasing air temperature were observed from 1971-2005. Christina and Mahama (2012) observed changing rainfall patterns over the past 20-30 in the research villages in Ghana: an increase in heavy rainfall causing floods; a delay of the rainy season; and an increase of the occurrence of dry spells associated with higher temperatures. The majority of the household respondents in the research site mentioned that changing rainfall patterns have a negative effect on crop production and in turn worsen the economic situation of the household. Dry spells and heavy rainfall events during critical stages in the planting season can negatively affect crop production, leading to reduced yields or harvest losses, and ultimately resulting in food shortages. Craparo (2015) revealed that + 1.42 °C increase in temperatures has led to Arabica yield decrease of 195 kg/ha in Tanzania, with many farmers in Tanzania giving up on coffee completely.

The unpredictability of rainfall and steadily increasing air temperature is posing threats to agricultural production in Karagwe of the climate-dependent nature of agricultural systems and lack of coping capabilities. Climate change impact studies have shown that the productivity of agricultural activities is highly sensitive to climate change. The effect of changes in climate on agricultural activities both physical and economic has been shown to be significant for low input farming systems, such as subsistence farming in developing countries in Sub-Saharan Africa that are located in marginal areas and have the least capacity to adapt to changing climatic conditions (Rosenzweig and Parry, 1994; Reilly and Schimmelpfennig 1999; Kates 2000; and McGuigan et al., 2002).

4.6 The influence of Market policy reforms on coffee production in the area

Following structural adjustment reforms, Tanzania implemented substantial liberalization of export crop markets, dissolving marketing boards and allowing private agents to operate as traders and exporters. The transition from government controlled policies to liberalized markets has been in operation for most developing countries since 1980, but the impacts of these policies on agricultural productivity are not clearly understood. For that reason the study wanted to know what contribution does market policy reforms has to smallholder coffee production in Karagwe. Results are shown in Table 4.12.

Table 4.12: Impact of coffee market reforms

|Variable |Frequency |Percent |
|Incresed price |72 |60.0 |
|Market for the produce |22 |18.3 |
|Not benefited at all |26 |21.7 |
|Total |120 |100.0 |

Source: Field Data Survey and SPSS Output File, 2015

Out of the 120 respondents, it was observed that 72(60%) said to have benefited from the market policy reform through increased price, 26(21.7%) said that farmers have benefited through increased market for the coffee produced, while 22(18.3%) did not benefit from the market policy reforms at all. Therefore majority of the farmers that is 72(60%) have benefited from market reforms through increased price.

From the study findings, it was also revealed that farmers can now sell coffee through different market channels, majority 101(84.2%) sold their coffee to private traders depended on private traders. A few of them sold their output to co-operatives 19(15.8%). This implies that now farmers have a wide market for the output especially private traders and the can sell their output to those who offer highest prices, unlike how it before liberalisations where farmers could only sell to one price set by the co-operatives.

Table 4.13: Marketing channels
|Variables |Frequency |Percent |
|Co-operatives |19 |15.8 |
|Private traders |101 |84.2 |
|Total |120 |100.0 |

Source: Field Data Survey and SPSS Output File, 2015

The findings are consistent with the empirical literature which attests to the significant achievements of agricultural market reforms, which have included both the withdrawal of state agencies from pricing and marketing activities and the relaxation of regulatory restrictions on private trade. These achievements are, notably, increased entry by private traders into agricultural trade, reduced marketing margins, increased producer prices, and the improved transmission of price signals in the economy (Barrett, 1994; Jones, 1996; Beynon et al, 1992).

Furthermore, when the respondents were asked to give their opinion on the level of awareness on market reforms, observations on indicate that majority 98 (81.7%) were aware of the reforms.

Table 4.14: Awareness on market reforms
|Variable |Frequency |Percent |
|Yes |98 |81.7 |
|No |22 |18.3 |
|Total |120 |100.0 |

Source: Field Data Survey and SPSS Output File, 2015

4.7 The effects of Coffee Price Volatility on Coffee Production in the Area

With respect to this aspect, the study findings indicated that commodity prices were affecting farmers because of their impact on variables such as income. In this regard, commodity price volatility was considered as one among the sources of vulnerability. This was so as it was attributed to the decrease of commodity prices and the absence of a predictable trend increased the challenge of how to maximize gains in a volatile environment. The price of goods plays a crucial role in determining an efficient distribution of resources in a market system (Kwame, 2013). Price acts as a signal for shortages and surpluses which help farmers respond to changing market conditions, the study wanted to know impact of price volatility on smallholder coffee production. Results are shown in Table 4.14

Table 4.15: Impact of price volatility on production
|Impact |Frequency |Percent |
|Poor Farmers’ Livelihood |26 |21.7 |
|Demotivated to produce more |35 |29.2 |
|Low individual income |59 |49.2 |
|Total |120 |100.0 |

Source: Field Data Survey and SPSS Output File, 2015

The study findings revealed that the price of agricultural product has a strong impact on coffee production. Out 120 farmers who responded (Table 4.14) 59 (49.2%) said price volatility has led to low individual incomes. Low Per capital incomes of farmer leaves farmers in a situation that cannot afford to meet their basic needs which are: to purchase food, clothes and shelter also taking their children to school as well as acquiring better health services. It was also pointed out by 35 (29.2%) that price volatility has demotivated the farmers to increase output; The research observed that some of the farmers were discouraged to the extent that had cut down the coffee trees and planted other crops like bananas, maize and beans helped them to maintain their income and meet their basic needs. Furthermore, 26 (21.7%) commented that price has led to poor famer’s livelihood. It was observed that majority of the farmers live in poor houses, have no access to pure water, infrastructure and health services. The findings are in line with the study of Huka et al. (2014) on Price Fluctuation of Agricultural Products and its Impact on Small Scale Farmers Development in Kilimanjaro. Findings showed that price fluctuation of agricultural product is a challenge towards achievement of small scale famer’s development which results to loss of capital and farmers shifting to other production activities.

The study also investigated the price at which the farmers sold their output last season (2013/2014). Observations on the distribution indicated that majority of the farmers 96 (80.0%) were selling their coffee at price equals to Tshs. 1200 per kilogram. About 15 (12.5%) of the farmers were selling their coffee at Tshs. 1000 per kilogram, while 5 (4.2%) sold coffee at 800 per kilogram, and about 3 (2.5%) sold coffee at 1300 per kilogram. Very few ranging from 1 (0.8%) sold coffee at 900 per kilogram. Therefore, majority of respondents sold their coffee at Tshs. 1200 per kilogram as shown in the Table below.

Table 4.16: Coffee prices offered per kilogram
|Price (Tshs) |Frequency |Percent |
|800 |5 |4.2 |
|900 |1 |.8 |
|1000 |15 |12.5 |
|1200 |96 |80.0 |
|1300 |3 |2.5 |
|Total |120 |100.0 |

Source: Field Data Survey and SPSS Output File, 2015

4.8 Other factors affecting smallholder coffee production in Karagwe District

In this study, it was important to consider other factors which were affecting coffee production in the area. As shown in the table below, respondents were asked to rank the most serious factors affecting the trend of coffee production. Of 120 respondents interviewed, majority 40 (33.3%) acknowledged that there was inadequate extension services as a barrier to enhance increased production. Inadequate financial services were earmarked as the second factor 25 (20.8%) affecting coffee smallholder producers. The prevalence of pests and diseases was also ranked high 22 (18.3%). The distribution of agricultural inputs was not that much ranked as a serious problem 16 (13.3%). The results of the study suggest therefore that, constructive measures must be undertaken by the government to ensure that extension services are effectively provided to farmers.

Table 4.17: Other factors affecting coffee production
|Variable |Frequency |Percent |
|Pest and diseases |22 |18.3 |
|Inadequate extension services |40 |33.3 |
|Inadequate agricultural inputs |16 |13.3 |
|Inadequate financial service |25 |20.8 |
|Soil exhaustion |3 |2.5 |
|Limited land |3 |2.5 |
|Coffee export restriction |6 |5.0 |
|Poor transport network |5 |4.2 |
|Total |120 |100.0 |

Source: Field Data Survey and SPSS Output File, 2015

These findings are in line with those revealed by studies by Katenga et al. (2014) and Nederlof and Wennink, (2010) respectively. It was shown that Agricultural extension describes the services that provide rural people with the access to knowledge and information they need to increase productivity and sustainability of their production systems and improve their quality of life and livelihoods. Extension services contributed to strengthening the assets of the rural poor and hence adapting and sustaining their livelihoods in a changing context. This study observed that there was a problem of access to agricultural services by coffee farming households in the study area. This situation has resulted in fewer (20.7%) sampled households to access agricultural extension service in the past one year. The respondents attributed this problem to shortage of agricultural extension workers in the District in such a way that most of the wards have only one agricultural extension worker. Therefore bigger wards like Bureza which contains four villages face an up-hill task to provide services to its citizens as one extension worker has to lender services to about 1,590 households in the ward. This situation has caused most of households (79.3%) in the study village not to access extension services that could have boosted their coffee production levels. The findings concurs with the observation by other studies that found out that most farmers in Tanzania still lack access to extension services as the number of extension workers is inadequate in most districts. The number of agricultural households that received crop extension was 20% of total crop growing households in Kagera region.

4.9 Coffee production function analysis

From the regression results, agricultural inputs price, climate change, price volatility and market reforms were observed to affect coffee output significantly and hence these were perceived as the determinants of coffee production in the study area. Using OLS technique of the Multiple Regression Model, the coefficients of the variables was estimated. For the study to estimate with OLS, the Cobb-Douglas production function was transformed to satisfy the Classical Linear Regression Model (CLRM), so that to come up with the usual assumption of Best Linear Unbiased Estimator (BLUE) of α and β respectively. (Gujarati 2009) and implies a Cobb-Douglas production function with unit elasticity of substitution (Maddala, 2002).

The command of linear regression gave the estimation results as it can be seen in table 4.16. An estimation results are substituted/fitted in the proposed model as follows.

lnQ = 1.119 - 0.132ln(PI) - 0.156ln(CC) + 0.0005ln(PC) + 0.1727ln(MPR) + ui

Where

Q = total output of coffee in terms of quantity (in kilograms) produced,
PI = agricultural inputs price
PC = price volatility
MPR = market policy reforms
CC = climate change

From the fitted estimation model standard errors and t-tests are shown from the equation above. Also R2, adjusted R2 and probability of F are shown. From the results R2 = 0.6918, imply that 69.18% of the variation in coffee output is explained by the explanatory variables. Considering price volatility, the elasticity value indicates that if price volatility is increased by 1%, the yield of coffee would increase by 0.0005%. If market policy reforms increase by 1%, yield of coffee would increase by 0.1727412%.

From the results, climate change as a factor has a negative influence on output from coffee as reported the coefficient (-.1567903). Output from coffee production is negatively related to climate change as reported by the coefficient -0.1567903. This means that when the climate change increases by 1%, the output from coffee production decreases by 0.1567903% if all other factors remain constant. Similarly the coefficient of agricultural inputs price is negative that is (-0.132037). This means that when agricultural inputs price increases by 1%, the output from coffee production decreases by 0.132037% if all other factors remain constant. The study results showed further that variables such as price volatility and market policy reforms are positively related to coffee output while agricultural inputs price and climate change were inversely related.

Table 4.18: Estimate of the production function analysis
Source SS df MS Number of obs = 120
-------------------------------------------------- F(8, 111) = 8.98
Model 29.7459022 8 4.95765036 Prob > F = 0.0001
Residual 13.251015 111 .552125625 R-squared = 0.6918
-------------------------------------------------- Adj R-squared = 0.6148
Total 42.9969172 119 1.43323057 Root MSE = .74305
--------------------------------------------------------------------------------------------------------------------------------
Outbags Coef. Std. Err. T P>|t| [95% Conf. Interval] inputspx -.132037 .0798388 -1.65 0.101 -.2903425 .0262685
Clmchange -.1567903 .0790895 -1.98 0.050 -.3136101 .0000295
Pxvolat .000512 .0007203 0.71 0.479 -.0009163 .0019403
Mktreforms .1727412 .09062 1.91 0.059 -.0069416 .352424 _cons 1.119133 1.078511 1.04 0.302 -1.019355 3.25762

Source: Field Data Survey and SPSS Output File, 2015

CHAPTER FIVE

SUMMARY, CONCLUSION AND RECOMMENDATIONS

5.1 Introduction

This section of the study presents the summary of findings, conclusion and it then proceeds to offer recommendations based on the findings drawn from the study and also presents the main areas recommended for further research.

5.2 Summary of the Study Findings

This study was conducted to assess the factors affecting smallholder coffee production in Karagwe district. A cross sectional study design was and the sample size for this study involved 120 respondents consisting of farmers aged 16+. Statistical Package for Social Science computer software was used to simplify the analysis of data. Descriptive statistics such as mean, percentages, standard deviation and coefficient of variation were generated. Multiple regression model was used to determine the factors affecting coffee production. The study found that coffee growers in Karagwe district have household characteristics common to most rural household settings elsewhere in Tanzania. Specifically, the study had the following specific objectives:
To investigate and determine how coffee production in Karagwe district affected by agricultural inputs price. The finding revealed that 89(74.2%) of the respondents indicated that the prices of inputs (fertilizers and improved seed verities) are very high which affected their input use and production.

Another specific objective was to find out whether climatic change affects coffee production in Karagwe district. The findings revealed that 100(83.3%) claimed that climate was unpredictable which resulted into a decline in the number of bags harvested.

The researcher also intended to determine how coffee production in Karagwe district is affected market policy reforms. The finding revealed that 72(60%) of the farmers in the coffee sector have benefited from market reforms through increased price of the produce.

Moreover the researcher intended to investigate how coffee price volatility has affected coffee production in Karagwe district. Based on the results 59(49.2%) said price volatility has led to low individual incomes.

Despite the fact that the researcher was guided by the specific objective, keeping other factors constant there was a need to give respondents open question to mention any other factors that affect coffee production. Other constraints to small scale coffee production were 40(33.3%) inadequate extension services, 25(20.8%) inadequate financial services, 22(18.3%) pests and diseases respectively.

From the regression results, agricultural inputs price, climatic change, market policy reforms and price volatility were observed to affect coffee output and hence are the determinants of coffee production in the study area. The R2 value for the regression is 0.6918 and this means that 69.18% of the variations in coffee output are explained by the factor inputs. The values of the coefficients indicate the elasticity of the various inputs to the output.

5.3 Conclusion

Karagwe district is endowed with fertile land capable of bettering the standard of living of the local people if adequately put to use especially in agricultural processes. Coffee being a major cash crop that has good potentials of high yield in the district can be a source of employment to the people of the district who are predominantly farmers if much attention is given to it.

Based on the main findings of the study, the following conclusion can be drawn. It is concluded that although coffee production is considered as the largest agricultural export crop in Tanzania and is produced by a large number of smallholders, its production has continued to decline. With respect to findings of this study, this situation was partly attributed to by price volatility, unpredictable climatic conditions especially prolonged droughts, low use of agricultural inputs (such as fertilizers, improved seed varieties, pesticides) due to high prices pests and diseases, poor crop management practices as well as insufficient support such as extension services have been found to be one of the root causes of low productivity.

This implies that the government tended to control agricultural activities rather than creating an enabling environment for small scale farmers to grow. The results of the study were further evidenced by the fact that the production environment was found not friendly to small scale farmers. The observed challenges included high input costs, unpredictable climatic conditions and decline in the coffee price, inadequate extension services, inadequate financial services, pest and diseases, inadequate agricultural inputs, export restriction, poor transport network, Soil exhaustion and limited land are the remaining challenges to small scale farmers in Karagwe district and Tanzania at large.

5.4 Policy Recommendations

As a measure of improving and sustaining the industry and also providing a source of livelihood for the farmers recommendations have been suggested. It is expected that the recommendations will contribute to the government’s vision of increasing coffee output and productivity at household level. Based on the study findings, the following recommendations aimed at improving coffee production are made:

i. Improvement in input and equipment supply to farmers. Farmers need to be assisted in obtaining input and farm equipments. That will enable households to access such credit at a reasonable cost. This can be effected through provision of loans which will be paid back during selling of their produce. Also it is recommended that a farmer agricultural bank be established in order to solve the problem of credit for farmers and processors. This could be achieved through the government facilitating SACCOS related to agricultural activities to mobilize resources and form an agricultural bank.

ii. Since the land is fixed, the government should encourage the use of fertilizer by providing incentives for the setting up of cooperative shops in order to provide fertilizers to households at an affordable price.

iii. The threat to Tanzania’s coffee production should spur the country’s authorities to design climate-smart practices that might help cushion farmers from worsening losses.

iv. Reliable market of coffee. These include reliable and stable prices of coffee. According to farmers’ views the prices offered in the season 20013/2015 were unstable and inadequate when compared to the production cost. Increase of price will encourage farmers to invest more on their coffee fields and by doing so the production and quality of coffee will be improved.

v. Development/improvement of training and extension services. Farmers need to access training and extension services in order for them to correctly appraise their investments. Technical skills training such as agronomy, post- harvesting handling and processing is an important component in rationalizing production and marketing of the crop. Increase in yield per hectare can be achieved through improved growing techniques. Inadequate knowledge of organic techniques by farmers can be developed with further training and exposure. Therefore field officers and trainers should be motivated to work hard so that they can provide farmers with adequate and quality extension services.

vi. The government should strive to develop roads, water, energy, and communication infrastructure. This will increase smallholder’s economic opportunities by reducing transaction costs and allowing farmers to get access to marketing information for productivity and smallholder coffee profitability.

vii. The government should encourage private sector to invest in credit facilities like small–scale banks to offer credit to farmers at affordable rates. This should be through legislation to facilitate credit creation.

5.5 Limitations of the Study

The following were the hindrances during the research. Firstly, due to time and financial constraints, the study concentrated solely on 120 small scale farmers within Karagwe District. There are many thousands of small scale farmers in the district that could be included in the study.

Secondly, Local Government officials during the research time could not fulfill the appointment they gave me (the researcher) giving reasons that they were busy with the administrative work.

Third some respondent’s did not concentrate on the questionnaire; they would put a tick or a circle on the factor that would be answered otherwise according to my view (Researcher). For example one male farmer assigned a tick on female position before the researcher asked him to make correction.

5.6 Areas for further research

• The study was conducted in Karagwe District only. There is a need therefore to study other coffee producing regions in Tanzania.

• Further studies should be carried out using adequate models and panel data (if possible) to verify the magnitude and major sources of the differences in the effects of determinants of coffee productivity in the various coffee producing zones of the country with a view of designing policies based on each zone’s peculiarities.

• More research on constraints and challenges faced by women and youth in coffee production is needed.

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APPENDICES

Appendix I

Questionnaires

MZUMBE UNIVERSITY

FACULTY OF SOCIAL SCIENCES

Dear respondent,
My name is Rodrick W. Mugishagwe, a Master of Science in Economics (Project Planning and Management) student at Mzumbe University. I am conducting an academic research on factors affecting smallholder coffee production in Karagwe District.

Kindly I request that you respond to the questions below with as much transparency as possible. All information provided will be treated as STRICTLY CONFIDENTIAL and it is for academic purpose only.
For more information contact me through 0719442434 OR rodrickwilbroad@live.co.uk.
_______________________________________________________________________

A. HOUSEHOLD INFORMATION
(Please fill in spaces provided or circle the appropriate answer)
1. Age a) Below 16 years b) Between 16 and 25 years c) Between 26 and 35 years d) Between 36 and 45 years e) Above 45 years
2. Gender a) Male b) Female
3. What is your education level?

a) No school attended b) Primary school education c) Secondary School education d) Technical/Vocational e) College/University education f) Other (Specify)............................................................
4. What is your Occupation? a) Farming b) Petty business c) Other (Specify).....................................................
5. What your estimated monthly earnings in Tanzanian shillings a) Less than 50,000/= b) 50,000-100,000 c) 100,000-150,000/= d) 150,000-200,000 e) Above 200,000
6. What is your main source of income? a) Farming b) Petty business c) Other (Specify).....................................................
B. CROP PRODUCTION AND MARKETING
(Please fill in spaces provided or circle the appropriate answer)

7. What is the size of your hectare under coffee? ................................................................... a) 0-3 hectare b) 4-6 hectare c) 7-9 hectare d) 10 hectare an above
8. Types of coffee grown? a) Robusta coffee b) Arabica coffee c) All the above d) Other (Specify).....................................................
9a. Do you purchase inputs for cultivating/harvesting your cash crop? a) Yes b) No
9b. If YES, how much did they cost you?
|Item |Amount |Cost pay per unit wt/vol./time? |
|Pesticides | | |
|Fertiliser | | |
|Labour | | |
|Other (specify) | | |

10c. If NO, give reason a) It is costly b) Not available c) Others (specify)..............................
11. How do you rate the price of inputs for your produce? a) High b) Average c) Low d) I don’t know
12. What are the unique climate trends occurring in your area? a) Good for farming b) Too dry c) Too wet d) Unpredictable
13. Where do you source your water from? a) Nearby river/stream/lake b) Rainfall c) Household supply d) Others (specify).....................................................
14. What do you do if rains are insufficient for planting? a) Plant a different crop b) Plant anyway c) Do not plant if rainfall is not good
15. In the drought years, at which growth stage(s) was the crop most affected? a) In the nursery, b) Between 1 and 5 months after planting, c) 5 months after planting, d) After harvest or during storage
16. In the excess rainfall years, at which growth stage(s) was the crop most affected? a) In the nursery, b) Between 1 and 5 months after planting, c) 5 months after planting, d) After harvest or during storage
17a. Has there been any increment in the Number of bags harvested recently? a) Yes b) No
17b. If YES or NO, specify the reason for the increase or decrease a) Drought b) Heavy rains, c) Humidity d) Temperature e) Other (Specify)...................................................
18. How many bags did you harvest last season? a) Below 1 bag b) Between 1 and 3 bags c) Between 4 and 6 bags d) Between 7 and 9 bags e) 10 bags an above
19. Where did you sell your coffee last season? a) Co-operatives b) Private traders c) Friend d) Others (specify)..............................
20. How has price volatility affected you? a) Poor farmer’s livelihood b) Demotivated to produce more c) Low individual income
21. What prices did you receive for your produce last season? ............................................................................................
22. Have you heard of the coffee market liberalisation in the last two decades? a) Yes b) No
23. How have you benefitted from coffee market liberalisation? a) Increased price b) Market for the produce c) Not benefitted at all d) Others (specify)...................................................
24a. Has there been any increment in the number of bags harvested recently? c) Yes d) No
24b. If YES or NO, specify the reason for the increase or decrease a) Increased price b) market for the produce c) Others (specify).....................................................

C: CHALLENGES OF COFFEE FARMERS
(Please fill in spaces provided or circle or tick the appropriate answer)
25. What is the main challenge affecting coffee production in your area? a) Agricultural inputs price b) Climatic change. c) Market policy reforms d) Coffee price volatility e) None of the above
26. What other challenge(s) do you face when producing this crop? a) .................................................................................................................................. b) .................................................................................................................................. c) .................................................................................................................................. d) ..................................................................................................................................

THANK YOU FOR YOUR COOPERATION

Appendix II

Main Coffee Production Regions/Districts in Tanzania

[pic]
Source: Ministry of Agriculture and Cooperative, (2001)

Appendix III

Karagwe District Map

[pic]

Source: Karagwe District Council

-----------------------
[1] International Coffee Organization (ICO) is the main intergovernmental organization for coffee, bringing MNR_®¯±³´µÖ×ÙÚÛêó ; R ïßÏ¿¯¿Ï¿¢’‚rbU’E5E5rh¤vnhVì5?CJOJQJaJh¤vnh¡

»5?CJOJQJaJhfHŒ5?CJOJQJaJh¤vnh7l[pic]5?CJOJQJaJh¤vnhÐd5?CJOJQJaJh¤vnhJ}5?CJOJQJaJh¤vnh‹`Ç5?CJOJQJtogether exporting and importing Governments to tackle the challenges facing the world coffee sector through international cooperation. Its Member Governments represent 97% of world coffee production and over 80% of world consumption.

[2] The Tanzania Coffee Research Institute (TaCRI) is a stakeholder owned and managed Institute to support the rejuvenation of the coffee industry in Tanzania to sustainable prosperity.
[3] A country’s individual exports may account for a small fraction of global exports with exceptions such as Brazil in the coffee market and Cote d’Ivoire in the cocoa market. As a price taker, a country does not have a significant proportion of global export to create changes in the price of a commodity.
[4] The term ‘Dutch disease’ originates from the discovery of oil in the Netherlands during the 1960s which caused an exchange rate appreciation, resulting in a loss in competitiveness for non-oil exports on the global economy.
[5] Storable refers to slowly perishable goods where producers can store output from one season to sell in a later time period.
[6] Climate Change, Agricultural Adaptation and Fairtrade, NRI Working Paper, Natural Resources Institute, May 2010, www.nri.org.

[7] A Debe refers to a tin used to measure coffee cheery which is about 12-15kg.

----------------------- • Capital

• Family size

• Farm size

• Farming experience

• Labor

• Level of education

• Price of agricultural inputs • Climatic change • Market policy reforms • Price volatility

COFFEE OUTPUT/ PRODUCTION

f

=

Coffee production/ Output

Agricultural inputs prices

Climatic change

Market policy reforms

Price volatility