The University of Dodoma University of Dodoma Institutional Repository http://repository.udom.ac.tz
Social Sciences Master Dissertations
2015 The Role of Input Vouchers in Improving Agricultural Productivity among the Smallholder Farmers in Geita District, Tanzania
Bukombe, Joseph
The University of Dodoma
Bukombe, J. (2015). The Role of Input Vouchers in Improving Agricultural Productivity among the Smallholder Farmers in Geita District, Tanzania (Masters dissertation). The University of Dodoma, Dodoma. http://hdl.handle.net/20.500.12661/1862 Downloaded from UDOM Institutional Repository at The University of Dodoma, an open access institutional repository. THE ROLE OF INPUT VOUCHERS IN IMPROVING
AGRICULTURAL PRODUCTIVITY AMONG SMALLHOLDER
FARMERS IN GEITA DISTRICT, TANZANIA
By
Joseph Bukombe
A Dissertation Submitted in Partial Fulfilment of the Requirements for the Degree of
Master of Arts in Development Studies of the University of Dodoma
The University of Dodoma
October, 2015 CERTIFICATION
The undersigned certifies that he has read and hereby recommends for acceptance by the University of Dodoma a dissertation entitled “The Role of Input Vouchers in
Improving Agricultural Productivity among the Smallholder Farmers in Geita
District, Tanzania,” in partial fulfillment of the requirements for the degree of
Master of Arts in Development Studies of the University of Dodoma.
……………………………………
Prof. Davis G. Mwamfupe
(Supervisor)
Date……………………………….
i DECLARATION
AND
COPRIGHT
I, Joseph Bukombe, do hereby declare that this is my own original work and has not been submitted and will not be submitted to any other University for a similar or any other Degree award.
…………………………………………….
No part of this dissertation may be reproduced, stored in any retrieval system, or transmitted in any form by any means, electronic, mechanical, photocopying, recording or otherwise without prior written permission of the author or the University of
Dodoma.
ii ACKNOWLEDGEMENT
First and foremost let me praise and honour the Almighty God for the opportunity and capacity given to me to realize my aspiration, your name shall be glorified.
I wish to express my sincere gratitude to my supervisor, Prof. Davis G. Mwamfupe for his encouragement and willingness to offer time for discussing and critiquing my work.
His contribution to the completion of this dissertation is priceless. Appreciation should also go to all academic staff members of the Department of Development Studies at the
University of Dodoma for their advice, counseling and encouragement during the entire period of the study.
My sincere appreciation and thanks also go to my brothers and sisters; Christopher,
Gregory, Herman, Raymond, Scholastica, Rosemary, Marietha and Magdalena for their moral and financial support in pursuing this degree of master, without their support I could not reached anywhere. I have always felt that you are behind my achievements and I will forever count on you, please keep the good spirit.
I extend my sincere thanks to Geita District Council for giving me permission to collect data, cooperation and support during data collection within the district.
My special gratitude is due to my lovely wife; Pausia Muhamila for taking care of the family and supporting me while I was away. Also, special thanks and appreciation are due to my beloved daughters; Salome and Cresencia for enduring my absence and being patient.
iii DEDICATION
This dissertation is dedicated to my beloved parents; my late father Mr. Sebastian
Kumalija Bukombe my mother Salome Suki Mashini who laid foundation of my education.
iv ABSTRACT
This work is about the Role of Input Vouchers in Improving Agricultural
Productivity among Smallholder farmers in Geita District, Tanzania. The study was carried out in four villages of Geita District, namely Nyakamwaga, Ntono,
Imalampaka and Buyagu. The study was associated with the use of improved inputs like inorganic fertilizer, seeds and pesticides in the study area with its adoption rate in improving agricultural productivity.
A sample size of 100 respondents was selected using random sampling and purposive sampling techniques. Primary data were collected using interviews, observation, survey and Focus Group Discussions. Descriptive statistics were applied in analyzing data, Statistical Package for Social Sciences (SPSS) version
16.0 and MS excel computer packages as tools for quantitative data were used to obtain frequencies and percentages which were presented in tables.
The findings from the study reveal that the productivity per acre in maize and rice increased, for instance there was great changes in maize productivity from
4bags/acre to 16bags – 28bags/acre. While in rice changes were from 13bags/acre to
35bags – 40bags/acre. Also, input vouchers enabled smallholder farmers to access improved agricultural inputs closer to the village or ward agro-dealers at subsidized prices. The study recommends that actors in agricultural sector should look for possibility of lowering farmers’ level of contribution to the voucher value to be less than 50% due to existence of poverty in most of smallholder farmers. Furthermore, smallholder farmers should be encouraged to form associations of crop producers for their agricultural produces.
v TABLE OF CONTENTS
CERTIFICATION ...... i DECLARATION AND COPRIGHT ...... ii ACKNOWLEDGEMENT ...... iii DEDICATION ...... iv ABSTRACT ...... v TABLE OF CONTENTS ...... vi LIST OF ABBREVIATIONS ...... x
CHAPTER ONE: BACKGROUND INFORMATION ...... 1 1.1 Introduction ...... 1 1.2 Background Information ...... 2 1.3 Statement of the Problem ...... 7 1.4 Objectives of the Study ...... 10 1.4.1 General Objective ...... 10 1.4.2 Specific Objectives ...... 10 1.4.3 Research Questions ...... 10 1.5 Significance of the Study ...... 11 1.6 Scope and Limitation of the Study ...... 11
CHAPTER TWO: LITERATURE REVIEW ...... 13 2.1 Introduction ...... 13 2.2 Definitions of Key Terms ...... 13 2.3 Theoretical Review ...... 14 2.3.1 The New Institutional Economics Theory ...... 14 2.3.2 Structural Constructivism Theory ...... 15 2.4 Empirical Review ...... 17 2.4.1 The Universal Subsidy Programmes in Sub-Saharan Africa ...... 17 2.4.2 The Market Smart Input Subsidy Programmes in Sub-Saharan Africa ...... 19 2.4.3 Case Studies of Market Smart Subsidies in Sub-Saharan Africa ...... 21 2.4.3.1 Market Smart Subsidies in Malawi ...... 21 2.4.3.2 Market Smart Subsidies in Zambia ...... 24 2.4.4 Improved Agricultural Technologies ...... 27 vi 2.4.5 An Overview of Input Farm Input Supply in Tanzania ...... 29 2.4.6 The National Agricultural Input Scheme (NAIVS) ...... 31 2.4.7 Significance of Input Vouchers ...... 33 2.4.8 Factors on Agricultural Productivity of Smallholder Farmers ...... 34 2.4.9 Agriculture Sector in Tanzania ...... 37 2.4.10 Maize and Rice Production and Productivity ...... 38 2.5 Research Gap ...... 39 2.6 Conceptual Framework ...... 40
CHAPTER THREE: RESEARCH METHODOLOGY ...... 42 3.1 Introduction ...... 42 3.2 Area of the Study ...... 42 3.2.1 Geographical Location ...... 42 3.2.2 Climate and Soils ...... 42 3.2.3 Economic Activities ...... 43 3.3 Justification of the Study Area ...... 43 3.4 Research Design ...... 44 3.5 Study Population ...... 45 3.6 Sampling Design ...... 45 3.6.1 Sampling Frame ...... 45 3.6.2 Sample Size ...... 46 3.7 Sampling Techniques ...... 47 3.8 Data Collection Design ...... 48 3.8.1 Primary Data ...... 48 3.8.2 Secondary Data ...... 48 3.8.3 Data Collection Methods ...... 49 3.8.3.1 Interviews ...... 49 3.8.3.2 Observation ...... 49 3.8.3.3 Survey ...... 50 3.8.3.4 Focus Group Discussions ...... 50 3.8.3.5 Documentary Review ...... 50 3.9 Analysis of Data ...... 51 3.10 Validity and Reliability ...... 51
vii 3.10.1 Validity ...... 52 3.10.2 Reliability ...... 52 3.11 Ethical Considerations ...... 53
CHAPTER FOUR: RESULTS AND DISCUSSION...... 54 4.1 Introduction ...... 54 4.2 The Distribution of Respondents by Villages ...... 54 4.3 Respondents’ Socio- Economic Profile ...... 54 4.3.1 Age Groups of Respondents ...... 55 4.3.2 Sex of Respondents ...... 56 4.3.3 Marital Status of Respondents ...... 56 4.3.4 Education Level of Respondents ...... 57 4.3.5 Main Occupation of the Respondents ...... 58 4.4 The Extent Usage of Input Vouchers among Smallholder Farmers in Geita District ...... 59 4.4.1 Awareness on Input Vouchers under NAIVS in Study Area ...... 59 4.4.2 The Agricultural Inputs Accessibility before Input Vouchers ...... 60 4.4.3 Input Price in Geita District 2009/2010 to 2011/2012 ...... 62 4.4.4 Preferable Time for Distribution of Input Vouchers to Smallholder Farmers . 64 4.4.5 Annual Income of the Respondents ...... 65 4.4.6 Sources of Funds for Purchasing Input Vouchers ...... 66 4.4.7 Distribution of Input Vouchers ...... 66 4.4.8 The Quality of Inputs ...... 67 4.5 The Effects of Input Vouchers on Farmer’s Efficiency in Production ...... 68 4.5.1 Size of land Owned by a Household ...... 68 4.5.2 Farmers’ Access to Land for Agricultural Production ...... 69 4.5.3 Units of Land used for Maize and Rice Production ...... 70 4.5.4 Usage of Improved Inputs per Acre ...... 71 4.5.5 Yield of Maize and Rice per Acre ...... 74 4.6 The Challenges for Effective Accessibility and Utilization of Input Vouchers in the Study Area ...... 75 4.6.1 Contact with Extension Officers ...... 76 4.6.2Access to Credit ...... 77
viii 4.6.3 Distribution of Improved Inputs on Time to Targeted Households ...... 78 4.6.4 Mismanagement of Vouchers ...... 79 4.6.4.1 Local Officers Colluding with VVC to Jeopardize the Vouchers ...... 79 4.6.4.2 Selling Vouchers to Agro-dealers or other Wealthy Farmers by Smallholder Farmers ...... 81 4.7 Other Challenges for Effective Accessibility and Utilization of Vouchers in the Study Area ...... 82 4.8 Smallholder Farmers’ Suggestions for the Input Vouchers to be Successful ..... 82
CHAPTER FIVE: SUMMARY, CONCLUSION AND RECOMMENDATIONS 84 5.1 Introduction ...... 84 5.2 Summary of the Findings ...... 84 5.3 Conclusion ...... 88 5.4 Recommendations ...... 90 5.5 Areas for Further Research ...... 92
REFERENCES ...... 93 APPENDICES ...... 103
ix LIST OF TABLES Table 3.1: Composition of the sample size ...... 47 Table 4.1: Village Names and Number of Respondents ...... 54 Table 4.2: Percentage Distribution of Respondents by Age ...... 55 Table 4.3: Percentage Distribution of Respondents by Sex ...... 56 Table 4.4: Percentage Distribution of Respondents by Marital Status ...... 57 Table 4.5: Percentage Distribution of Respondents by Education Level ...... 58 Table 4.6: Percentage Distribution of Respondents by Main Occupation of the Respondents ...... 59 Table 4.7: Sources of Information about Input Vouchers ...... 60 Table 4.8: Reasons for Low Usage of Improved Inputs in the Study Area before Input Vouchers ...... 61 Table 4.9: The Value of Subsidy Voucher and Top up Payment made by Smallholder Farmers in 2009/10 ...... 63 Table 4.10: The Value of Subsidy Voucher and Top up Payment made by Smallholder Farmers in 2011/2012 ...... 63 Table 4.11: Reasons for Distributing Input Vouchers in September ...... 64 Table 4.12: Annual Income of the Respondents ...... 65 Table 4.13: Sources of Funds for Purchasing Input Vouchers ...... 66 Table 4.14: Distribution of Input Vouchers ...... 67 Table 4.15: Smallholders’ Response about the Quality of Inputs ...... 68 Table 4.16: Size of land Owned by a Household ...... 69 Table 4.17: Farmers’ Access to Land and Mode of Land Acquisition ...... 70 Table 4.18: Units of Land used for Maize and Rice Production ...... 71 Table 4.19: Usage of Improved Inputs per Acre ...... 73 Table 4.20: Yield of Maize and Rice per Acre ...... 75 Table 4.21: Contact with Extension Officers ...... 76 Table 4.22: Factors for low or absence of accessing to credit from financial institutions ...... 77 Table 4.23 Reasons for Late Delivery of Vouchers to Smallholder Farmers ...... 79 Table 4.24: The Reasons for Local Authorities to Jeopardize the Vouchers ...... 80 Table 4.25: Reasons for Selling Vouchers or/and Inputs to Agro Dealers or Wealthy Farmers ...... 81
x Table 4.26: Other Challenges for Effective Accessibility and Utilization of Vouchers in the Study Area ...... 82 Table 4.27: Smallholder Farmers’ Suggestions for the Input Vouchers to be Successful ...... 83
xi LIST OF FIGURES
Figure 2.1: Conceptual Framework ...... 41
xii LIST OF ABBREVIATIONS
ACT Agricultural Council of Tanzania
AFDFM Africa Fertilizer Development Financing Mechanism
AGRA Alliance for Green Revolution in Africa
AISP Agricultural Input Subsidy Programme, Malawi
CAN Calcium Ammonium Nitrate
CIP Crop Intensification Programme, Rwanda
DADP District Agricultural Development Plan
DALDO District Agricultural and Livestock Development Officer
DAP Di-Ammonium Phosphate
FAC Future Agricultures Organization
FAO Food and Agriculture Organisation of the United Nations
FGD Focus Group Discussion
FMSP Federal Market Stabilization Programme, Nigeria
FSP Fertilizer Support Programme, Zambia
GDP Gross Domestic Product
IFA International Fertilizer Association
IFDC International Fertilizer Development Centre
IMF International Monetary Fund
MACO Ministry of Agriculture and Cooperatives, Zambia
MAFC Ministry of Agriculture, Food Security and Cooperatives in Tanzania
MRP Minjingu Rock Phosphate
MS Microsoft
NAAIP National Accelerated Input Programme, Kenya
NAIVS National Agricultural Input Voucher Scheme, Tanzania
xiii NEPAD New Partnership for Africa’s Development
NGOs Non-Governmental Organizations
NIE New Institutional Economics
NMB National Microfinance Bank
OECD Organization for Economic Cooperation and Development
OPVs Open Pollinated Varieties
REPOA Research on Poverty Alleviation
SACCOS Savings and Credit Cooperative Societies
SAPs Structural Adjustment Programs
SPSS Statistical Package for Social Sciences
SSA Sub Saharan Africa
TFC Tanzania Fertilizer Company
TIP Targeted Input Programme, Malawi
URT United Republic of Tanzania
VVC Village Voucher Committee
WAEO Ward Agricultural Extension Officer
WARC Ward Agricultural Resource Centre
ZFSP Zambia Fertilizer Support Program
xiv CHAPTER ONE
BACKGROUND INFORMATION
1.1 Introduction
Smallholder farming is the dominant agricultural activity in most developing countries, particularly in the least developing countries. Globally, there are about
500 million smallholder farmers. Together these smallholder farmers support 2 billion people, account for 97 per cent of agricultural holdings, and produce food for a substantial proportion of the world’s population (Landesa, 2014). Most of these people operate outside the formal business economy, farming to meet their own needs for food staples and selling small surpluses for extra cash. Half of the world’s undernourished people and the majority of people living in absolute poverty. In much of Africa and South Asia, small farms still account for the largest share of agricultural output (Nally, 2013).
Smallholder farmers in developing countries are facing a number of problems including inability to access and use inputs such as improved seeds, fertilizers and pesticides, inadequate investment in irrigation which makes farmers very vulnerable to droughts. This problem is exacerbated by the fact that the frequency of droughts has increased significantly because of climate change in the recent past and the absence of crop insurance. Other problems are poor infrastructure, especially roads, high postharvest crop losses caused by poor storage structures and inadequate access to pesticides, inadequate market access for both crops and livestock products, problems in accessing credit for Agricultural production and marketing and inadequate investment in processing for both crop and livestock products (Philip,
2011).
1 Besides, the decline of soil fertility due to erosion, land degradation and population growth had lowered agricultural productivity among smallholder farmers in most developing countries, including Tanzania. Regarding the efforts that have been done by the agricultural stakeholders in ensuring amendment of soil fertility, such as encouraging the use of inorganic fertilizer by the smallholder farmers through universal subsidies and market smart subsidies, where vouchers are used, the rate of adoption is still low because of high fertilizer prices. Therefore, this study examines the role of input vouchers in improving agricultural productivity among smallholder farmers by looking the importance of vouchers in delivering improved inputs and factors that affect vouchers.
1.2 Background Information
Failures in agricultural input markets are common in developing countries and are a major constraint to productivity growth. Smallholder farmers in developing countries like Sub-Saharan African face particularly acute constraints, with poor output price incentives, high fertilizer and seeds prices, lack of liquidity/credit and lack of knowledge. In low input/low output agricultural systems, fertilizer and seed subsidies can play a role in raising fertilizer and improved seeds use and agricultural productivity. They can help demonstrate the benefits of fertilizers and improved seeds and/or kick-start market development by raising input demand at a large scale.
However, subsidies do not represent a suitable policy option on the long run, as they do not address the root causes of low fertilizer and improved seeds use on input or outputs markets and they involve unsustainable fiscal costs for the economy
(Druilhe and Hurle, 2012).
2 Universal price subsidies on fertilizers and improved seeds were common from the
1960s to the 1980s in Sub-Saharan Africa (SSA) and in Asia. In Asia, subsidies are considered to have played an important role in promoting increased use of fertilizer and improved seeds to have partly contributed to the significant increases in yields
(Morris et al., 2007), although their contribution to agricultural growth and poverty reduction after the initial phases is considered to have been very low (Fan et al.,
2007). In Africa, most of countries sold fertilizer and improved seeds at subsidized prices through a centrally controlled input importing and distribution system.
Variations on this system were used in SSA in Kenya, Malawi, United Republic of
Tanzania, Zambia, and Zimbabwe and in some West African countries (Burkina
Faso, Senegal, Mali, Nigeria and Ghana) up to the mid-1990s in some cases
(Crawford et al., 2006).
Experience with universal subsidies in Sub-Saharan Africa nations (SSA) was largely negative; it resulted in inefficiencies, such as adverse selection of programme beneficiaries (capture by influential/well-off farmers) and displacement of commercial sales, and had disproportionate fiscal costs against their benefits
(Morris et al., 2007).
The failure was accelerated by a shift of development paradigms towards Structural
Adjustment Policies (SAPs), which eventually led to the dismantling of fertilizer and seeds subsidies, the liberalization of most fertilizer and seeds markets and a switch of fertilizer policy towards supporting the development of private-sector-led markets
(Minot, 2009). However, even during that period voices claiming a role for limited subsidies remained (Reardon et al., 1996).
3 Many observers note that the removal of subsidies coincided with a reduction in food production and in fertilizer/seeds use (Banful, 2011). As Banful and Olayide
(2010) note for Nigeria, “the pattern of total fertilizer consumption has followed the ebb and flow of federal and state government subsidies”. The country abandoned universal subsidies as late as 1997 to resume with reformed subsidy programmes as early as 1999.
From the early 2000s onwards, the conjunction of agricultural production stagnation, rising food insecurity, low soil fertility and environmental degradation has sparked fresh interest, from policy makers and development partners alike, in promoting input subsidies as a tool for addressing food insecurity. African governments and development partners have embraced the increase of fertilizer and improved seeds use as an enabling technology to boost food production.
A milestone in the flow of fertilizer subsidies, the African Fertilizer Summit held in
2006 in Abuja stated in its final declaration (African Union, 2006) that African policy-makers should grant “targeted subsidies in favour of the fertilizer sector, by granting, with the support of Africa’s Development Partners, targeted subsidies in favour or the fertilizer sector” (page 3) Since then the African Union, through
NPCA, is monitoring the progress towards the goals set in the Abuja Declaration and is coordinating the establishment of an African Fertilizer Development
Financing Mechanism (AFFM).The Alliance for an African Green
Revolution(AGRA) also advocates for making available improved seeds and fertilizers that are subsidized by governments and delivered through the private sector to poor farmers. Last, the Millennium Villages programme also called for
4 governments to boost fertilizer use, with subsidies if necessary (Minot, 2009). The fertilizer industry seems to be more cautious, reducing the scope for fertilizer subsidies to certain cases; acknowledging that subsidies alone will not be effective without a broader enabling environment supportive of agricultural development; and highlighting the need for more fertilizer supporting policies such as reduced taxation, regulatory harmonization and better infrastructure (IFA, 2010). Last, but not least, fertilizer subsidies are being put forward for inclusion into the Food Aid
Convention as support to post-emergency recovery efforts to rehabilitate adversely affected agriculture sectors (Konandreas, 2010).
The Malawian government pioneered the return to fertilizer and improved seeds subsidies in 1998 when it started distributing free fertilizer and improved seeds after having discontinued similar programmes in the early 1990s. It was followed by
Nigeria (1999); Zambia (2000); the United Republic of Tanzania (2002), Kenya
(2006) and Ghana (2008). After the 2008 food and fertilizer prices crisis, subsidies have become all the more popular as governments have felt the urge to quickly improve domestic food production and have been able to use direct budget support from donors who were previously reluctant (Kelly et al., 2011). Importantly, they also remain an attractive policy option for national governments because they are visible.
The revival of fertilizer and improved seeds subsidies came along with innovations in design seeking to avoid the downsides of past programmes (high costs, poor targeting and displacement of the private sector). The new “smart” subsidies are directed at specific smallholder farmers; they also aim at supporting private-sector
5 distribution and market-friendly solutions, generally with an associated poverty reduction and welfare enhancement objective. They frequently use vouchers (or coupons) to entitle beneficiaries and deliver against those objectives (Baltzer and
Hansen, 2012).
The smart subsidies differ in names from one country to another, for example,
United Republic of Tanzania: NAIVS (National Agricultural Input Voucher
Scheme), Kenya: NAAIP (National Accelerated Agricultural Input Programme),
Malawi: Starter Pack 1998; TIP (Targeted Input Programme) 2003-04; AISP
(Agricultural Input Subsidy Programme) 2005-to date, Rwanda: CIP (Crop
Intensification Programme), Zambia: FSP (Fertilizer Support Programme) and
Nigeria: FMSP (Federal Market Stabilization Programme) (Druilhe and Hurle,
2012).
Tanzania depends mainly on agriculture for economic growth and had reintroduced agricultural inputs subsidies in 2003/2004 to support technology adoption by smallholder farmers in the country, but it was implemented in the 2007/2008, the programme is known as the National Agricultural Input Voucher Scheme (NAIVS).
The programme was necessitated by the fact that the utilization level of improved agricultural inputs was very low by regional and international standards. As a result the country experienced low and declining production and productivity. Maize productivity in the Big Four regions of the Southern Highlands namely Ruvuma,
Mbeya, Iringa and Rukwa began to decline because the soils required greater use of fertilizer (URT, 2012).
6 The NAIVS focuses on maize and rice, the main staple crops in Tanzania. The target areas are the high agro-ecological potential areas for these crops, but it has expanded to areas throughout the country that grow these crops. The NAIVS provides vouchers for a 50% subsidy on a package of fertilizers and improved seeds directly to farmers growing rice and maize in target areas. The eligibility criteria include all households in the selected regions cultivating less than 1 hectare of maize or rice, with the highest priority being given to female headed households and resource-poor farmers who have not used fertilizer in the past five years. Beneficiaries are eligible to receive the vouchers for a maximum of three years. The voucher distribution is to be complemented by a number of critical activities to ensure its success, including an awareness campaign, supporting the expansion of agro-dealers network, strengthening the national seed systems, and monitoring and evaluation. The implementation arrangements for the NAIVS include two key features: a participatory and transparent targeting mechanism using a farmer-elected Village
Voucher Committee (VVC), and strengthening and deepening the network of private sector agro-dealers to promote sustainable access to agro-inputs in rural areas (URT,
2014).
1.3 Statement of the Problem
There is a general agreement among academicians, researchers and policy makers concerning the role of farm input subsidy programs, particularly input vouchers in rising agricultural productivity. For instance, there is a broad agreement on the potential role of input vouchers in providing improved agricultural technologies such as fertilizer and hybrid seeds to the smallholders (Chibwana, et al., 2010). Farm input subsidy programs have led to the improvement of agriculture sector in many
7 countries in the world as highlighted by Kelly (2006), these are instruments for achieving a wide range of diverse goals such as soil fertility replenishment, soil conservation, food security, GDP growth and poverty alleviation.
The introduction of input vouchers under NAIVS in Tanzania 2007/2008 was because persistence of food crisis, hence the Government of Tanzania launched an input voucher pilot program in 56 districts to increase the production of two of its major staple crops: maize and rice and enhance its national food security. The program was geographically targeted to areas most suitable for maize and paddy rice production, while also taking into account the number of agricultural households who cultivated less than one hectare of maize or rice. As food prices remained high and unstable in the aftermath of the crisis, the program was expanded in 2009 to 65 districts to reach 2.5 million households in 2012 (World Bank, 2009). The target areas are concentrated in the Southern Highlands, the Northern Highlands, and the
Western Region and focused on agro-ecological zones suitable for the target crops.
The input package distributed consisted originally of three vouchers: 1) one for two bags of urea, 2) one for one bag of Di-ammonium Phosphates (DAP) or two bags of
Minjingu Rock Phosphate (MRP) with nitrogen supplement, and 3) one for 10 kilograms of hybrid or open-pollinated maize seeds or 16 kilograms of rice seeds, sufficient for half a hectare of maize or rice. Vouchers for each input had a face value equivalent to 50 percent of the market price of the respective input. The remaining 50 percent was to be paid by the farmers (Pan and Christiaensen, 2011).
8 Despite the efforts the Government is making, the distribution of input vouchers in targeted areas is still limited by a number of factors as reported by REPOA (2013) revealing that smallholders continued to purchase agricultural inputs such as fertilizers and improved seeds at higher prices posed by agro-dealers which make difficult the continuous uptake of vouchers by poor farmers and their lives, cheating by agro-dealers, farmers often sell signed vouchers back to the agro-dealers with cheap prices, where agro-dealers could receive redemption of full price as if they had sold inputs and the late delivery of vouchers. Also the implementation of targeting criteria for beneficiaries of vouchers and farmers’ knowledge about targeting criteria slightly differ among villages, which sometimes made targeting of vouchers to the people who were not intended by the programme. This brings a number of questions to be asked. What is not yet critically assessed on the input vouchers in rising agricultural productivity to smallholders? Is it the structure of
NAIVS and management that are unable to assist smallholders in making effective use of input vouchers? Alternatively, is the problem of misusing vouchers like sell signed vouchers back to the agro-dealers is because of ignorance or low level of education by smallholders that is leading to input vouchers not being able to play a significant role improving agriculture? On the other hand, is it the absence of viable policies and strategies that is leading the input vouchers not having a significant impact on improving agricultural productivity?
It is of critical importance to have a deeper understanding of the role of input vouchers in rising agricultural productivity in smallholder farmers, particularly how smallholders are using fertilizers and hybrid seeds as well as extension services. It is becoming of increasing importance in examining the role of input vouchers in the
9 development of agriculture. Therefore, this study is aiming at examining the role input vouchers in improving agricultural productivity among smallholder farmers in
Tanzania, a case of Geita district.
1.4 Objectives of the Study
1.4.1 General Objective
The overall objective of this study is to examine the role of input vouchers in improving agricultural productivity in smallholder farmers in Geita District,
Tanzania.
1.4.2 Specific Objectives
The specific objectives of this research are;
i. To examine the extent usage of input vouchers to smallholder farmers in the
study area.
ii. To investigate the effect of input vouchers on farmers’ efficiency in
production in smallholder farmers in Geita District.
iii. To identify the challenges for effective accessibility and utilization of input
vouchers in Geita District.
1.4.3 Research Questions
The following are research questions;
i. To what extend do input vouchers are used by the smallholder farmers in the
study area? ii. Do input vouchers increase the efficiency in production of smallholder
farmers in Geita District?
10 iii. What are the challenges for effective accessibility and utilization of input
vouchers in Geita District?
1.5 Significance of the Study
The findings from this study are expected to contribute to the knowledge on the role of national agricultural input voucher scheme with specific reference to the role of input vouchers in improving the agricultural production and productivity in smallholder farmers.
The results will be useful to policy makers and development practitioners as it provide useful information in formulating more effective policies, strategies and measures related to improved seeds and fertilizers for the smallholder farmers. In addition, the study provides a direction for future researchers since input voucher subsidies program is still new and much is not known yet especially in Tanzania, where many studies have been conducted to analyze factors responsible for low input use in agricultural production by small scale farmers in rural areas.
1.6 Scope and Limitation of the Study
The study was carried out in Geita District where it covered four villages namely;
Nyakamwaga, Ntono, Imalampaka and Buyagu. Moreover, the study concentrated on smallholder farmers who received improved inputs (fertilizer, seeds and pesticides) through vouchers to improve maize and rice productivity.
The limitations of the study were: some respondents were reluctant to openly respond to some of the questions because of fear that the information given out could be useful for security purposes, some respondents do not keep records and 11 due to memory lapse take time to recall some information, it was difficult in getting sampling frame and samples because some farmers demanded money before being interviewed, some respondents were using traditional measures such as plastic buckets instead of bags or kilogram which then caused to re-phrase some questions to get correct units conversion.
12 CHAPTERTWO
LITERATURE REVIEW
2.1 Introduction
This chapter explores literature on the themes which are related to this research topic. It consists of five sections; the first section gives definitions of key terms, section two highlights theoretical review, section three shows empirical review.
Section four discusses knowledge gap and section five shows conceptual framework. The aim of this chapter is to give an insight into what has already been done by others as well as to enable the researcher to show clearly knowledge which has been added by this study.
2.2 Definitions of Key Terms
The Input Vouchers refer to the delivery mechanisms which provide farmers with access to agricultural inputs and/or services. Beneficiaries are provided with a voucher that they can exchange for inputs at existing shops (i.e. retailers/suppliers)
(FAO, 2013).
Smallholder Farmers are defined as farmers who manage areas varying from less than one hectare to 10 hectares. Smallholder farmers are characterized by family- focused motives such as favouring the stability of the farm household system, using mainly family labour for production and using part of the produce for family consumption. Many of these householder farmers are extremely poor; living with their families below the poverty line and associated with employment in agriculture and using low technology (Kristen and Vanzyl, 1998).
13 Agricultural Productivity is defined as a ratio between the index of total agricultural output and the index of total inputs used in farm production. It is, therefore, a measure of the efficiency of farming with reference to inputs applied in crop production, other things being equal (Rehman, 2003).
2.3 Theoretical Review
There are various theories governing and explaining the demand and supply of input vouchers to smallholder famers. Some of these theories are related to this study, including the New Institutional Economic Theory and Structural Constructivism
Theory. The two theories complemented each other in the discussion of this study.
2.3.1 The New Institutional Economics Theory
This is a new direction of economics considers that the cost or risk of transacting determined by institutions and institutional arrangements is the key to economic performance. (Kherallah and Kirsten, 2001).It is therefore argued that the institutions of a country such as legal, political, and social systems determine its economic performance (Coase, 2000). Institutions are considered as the mechanisms used to structure human interactions in the face of uncertainty, and they are formed to reduce uncertainty and risk in human exchange (Dorward, 2001).Approaches using New Institutional Economics (NIE) explore institutional structures at different levels and examine efficiency and welfare with respect to these structures. The purpose of the NIE is both to explain the determinants of institutions and their evolution over time, and to evaluate their impact on economic performance, efficiency, and distribution (Nabli and Nugent, 1989).In fact, by influencing enforcement mechanisms, transaction costs and co-ordination possibilities, 14 institutions can have the effect of either facilitating or retarding economic growth.
The specific contribution of NIE arises from its recognition that economic actors face a particular problem as a result of imperfect information about the behavior of other actors in transactions and institutions play an important role in addressing these problems (with varying benefits for different actors in a transaction and for wider participants in an economy (North, 1994, 1995).
The theory is relevant to this study because it is the institutions and institutional arrangements that address the challenges of agricultural development in poor rural economies in Africa. Also, the theory gives important in the analysis of agricultural input service delivery in Tanzania, whereby the government uses its economy, policies and legal framework to subsidy agricultural inputs such as fertilizer and seeds to enable smallholder farmers acquire these inputs at a lower price to improve productivity (Malinza and Chingonikaya, 2013). Therefore, the theory is helpful in correcting imperfect information among the actors’ particularly small holder farmers, by avoiding huge transaction costs and risks in the implementation of the programme.
2.3.2 Structural Constructivism Theory
Structural constructivism as propounded by Rousseau (1762) and Durkheim (1893)
(cited in Malinza and Chingonikaya, 2013). Parsons (1951), Berger and Luckmann
(1967) assume that institutions not only constitute choice sets or external society but they also influence individuals with regards to their abilities, ideals and needs. They influence perceptions, values, preferences and capabilities and therefore choices that individuals can make. Berger and Luckmann pointed out three important phases in
15 the process of institutionalization. Externalization refers to a condition where subjectively constructed routines take form and are expressed. Objectivation refers to the situation where others observe the routines as existing facts. Internalization is a point where habits are reproduced. This process is often called socialization.
The theory is applicable for this study due to the fact that social structures are need in implementing voucher schemes, for instance, smallholder farmers are supposed to be involved in creation of such criteria and guidelines important to their well being.
Social constructivist for example Berger and Luckmann argued that creation of institutions responsible for creating social order must be done in conditions of social cohesion. Furthermore, Ostrom (2000) put it clearly that for a long time the development of institutions occurred under conditions of great social cohesion. This is vital because people would feel they are part of a social construct, therefore willing and able to safeguard its interests. Barlow et. al. (1992) argued that the creation of rules must occur in a situation where trust, reciprocity and obligation had to be important elements. These are important issues for the analysis of agricultural input service delivery in Tanzania.
The design of institutions under NAIVS provides a typical example of state dominated policy regimes towards agricultural development planning. The design denotes a heavily state-centered development strategy focusing on the provision of public goods and overconcentration of resources for central government ministries and a secondary role for farmers, markets and private actors (Cooksey, 2012). The
MAFC assumed a central position in the design and implementation of the programme. Principally, the whole set up of institutions was based in Dar es Salaam
16 with a view of rectifying behaviors and understanding of actors motivations in remote rural areas of Tanzania. This was a false start as key actors (farmers and other non state actors) where left out of the loop. The advantages of participatory approaches to development planning are so vast for one to question the significance of this attempt by the MAFC (Malinza and Chingonikaya, 2013).
2.4 Empirical Review
Different forms of agricultural input subsidies have been implemented in most developing countries particularly in Sub-Saharan Africa in ensuring agricultural productivity. Among different forms include universal price subsidies on fertilizer and seeds, from 1960s to the 1980s. However, universal price subsidies were eliminated under the pressure from the IMF and World Bank during implementing
Structural Adjustment Program (SAP). The decline in soil fertility in the mid of
1990s necessitated reintroduction of fertilizer and seeds in Sub-Saharan countries in form of market smart input subsidy programs.
2.4.1 The Universal Subsidy Programmes in Sub-Saharan Africa
Many Sub- Saharan African countries pursued large scale universal subsidy programmes from the 1960’s up through the 1980’s (Dorward, 2009). These programmes were characterized by a government-controlled input (and output) marketing system, in which farmers were supplied with agricultural inputs at controlled and subsidized prices, and often on heavily subsidized credit (Baltzer and
Hansen, 2012; Dorward, 2009). The experiences under these programmes were mixed and all farmers in a particular location were eligible to acquire inputs. The programmes succeeded in raising input use by farmers and increasing agricultural
17 productivity in many cases. However, they were extremely expensive, most subsidies tended to benefit relatively well-off and better connected farmers, and the advances in agricultural productivity were dependent on continued government support. Further, the fertilizer subsidy programmes were prone to inefficiencies arising from high administrative costs, government monopolies and political manipulation (Banful, 2010b). As the subsidy programmes were dismantled and input markets liberalized as a part of the structural adjustment process in the 1980’s and 1990’s, input use and agricultural productivity declined (Crawford et al, 2006).
Universal input subsidies were socially regressive because they created rents for better-off producers who would have used fertilizers anyway (Druilhe and Hurle,
2012). Universal input programmes created displacement which refers to the non- subsidized sales that were displaced as a result of the subsidy, and in worse case generated no increment in total fertilizer use (Morris et al. 2007; Chinsinga, 2004).
Other studies by World Bank (1994 and 2008) argued that central governments managed and distributed subsidies inputs which discouraged the emergence of a viable private sector for agricultural inputs distribution as it undermines the private sector’s incentives to invest to reduce prices.
Failure of universal programmes in most Sub-Saharan African countries resulted into substantial low use of farm inputs, (for example, fertilizer) and increased food shortage in most of rural poor households; low soil fertility and environmental degradation (Morris et al, 2007).
18 2.4.2 The Market Smart Input Subsidy Programmes in Sub-Saharan Africa
Market smart subsidy programmes are meant to address the shortcomings of the universal subsidies. To be smart (Minde et al, 2008; Tiba, 2009) explain that subsidy programmes should adhere to a number of design principles, which are:
Targeting specific farmers. Smart subsidies should be targeted specifically at
farmers, who do not already apply agricultural inputs, as well as the poorest and
most vulnerable households. This reduces the risks of displacing commercial
(non-subsidized) input sales and promotes pro poor growth.
Market-based solutions. Smart subsidy programmes should utilize and support
the further development of existing private input supply networks, rather than
supplant them with state controlled distribution systems. This enhances the
efficiency of input delivery as well as increases the likelihood that the
programme has a sustained impact after its termination.
Exit strategy. Smart subsidy programmes should devise credible exit strategies
to put a time limit on the support. This is primarily to reduce the risks that the
programme becomes controlled by political interests (Dorward, 2009) and to
facilitate long term sustainability. If stakeholders expect the support to continue
indefinitely they are less likely to prepare for self sustained use of inputs on
market terms. Also, a firm exit strategy helps control the costs of the
programme.
Baltzer and Hansen (2012) agree with Dorward (2009) in their study on smart input subsidy, that if subsidies are well targeted, the greater demand for inputs is likely to encourage potential entrepreneurs to establish new businesses, which promotes the development of a competitive input market. Baltzer and Hansen (2012) add that the
19 more efficient is the targeting and input delivery system, the more effective and credible the exit strategy will be. However, Pan and Christiaensen (2011) precaution that, smart subsidies may fail to work if the subsidized inputs primarily displace commercial input sales, private dealers may be hurt by the unfair state-supported competition and may choose to exit the market, thereby reducing competition.
Market-smart input subsidies often use vouchers; vouchers entitle farmers to buy modern inputs (usually fertilizer and improved seeds) from participating input retailers at a subsidized price (Pan and Christiaensen, 2011). Distribution of the vouchers to the beneficiary farming households is delegated to different levels of government, whereby geographic targeting the selection of districts and villages within districts based on their agro-ecological potential is often combined with community based targeting the selection of beneficiaries within the village by the community (Coady, Grosh, Hoddinott, 2004).
Decentralized targeting is frequently applied in anti-poverty interventions and safety net programs (Grosh, 2008). Teslius and Ouerghi (2008) explain that decentralized seeks to exploit the privileged knowledge local governments and communities have about the conditions of the beneficiaries to reduce the administrative cost of targeting. A similar view is held by Alderman and Faguet (2004) assumes that local leadership is more likely to act in the interest of the beneficiaries than central governments, as local leaders are likely to be held more accountable by their local constituencies, who have difficulties monitoring a distant central government.
Alderman and Faguet (2004) conclude that market-smart works well under the supervision of the local authorities; they have cited examples in Albania and
20 Bolivia, where decentralization of agricultural programs improved the livelihood of the poor farmers.
2.4.3 Case Studies of Market Smart Subsidies in Sub-Saharan Africa
This subsection reviews the performance, success and limitations of the market smart subsidies in Sub-Saharan Africa, a case of Malawi and Zambia.
2.4.3.1 Market Smart Subsidies in Malawi
In Malawi 88% of the population lives in rural areas and slightly more than half of these are poor. The rural households are almost exclusively maize producers, but only 10% of them are net sellers, whereas around 60% of smallholders are net buyers of maize. This dependency on market purchases of maize leaves poor households vulnerable to the high and volatile maize prices usually observed in
Malawi (Baltzer and Hansen, 2012). Chinsinga (2011) argues that the political motives for supporting improvements in agricultural productivity are largely driven by a desire to increase smallholder self-sufficiency in maize production and reduce their exposure to maize market risks.
The Malawian government implemented the Agricultural Input Support Programme
(AISP) in the 2005/6 season, as a smart subsidy programme. The overall objective of this programme is to increase resource poor smallholder farmers’ access to improved agricultural inputs in order to achieve food self-sufficiency and to increase resource poor smallholder farmers’ income through increased food and cash crop production (Dorward et al, 2010).
21 The AISP is based on a voucher system. Selected recipient households receive two coupons, each of which can be redeemed for a bag of maize or tobacco fertilizer or a bag of maize seed (hybrid or Open Pollinated Variety (OPV).Maize fertilizer consists of a 50kg bag of urea, tobacco fertilizer covers a 50 kg bag of Compound D or Calcium Ammonium Nitrate (CAN), and maize seeds come in 2kg bags of hybrid seeds or 3-4kg bags of OPV seeds (Baltzer and Hansen, 2012).
The AISP appears to have had a substantial effect on maize output. The study done by Chibwana et al. (2010) reports that official estimates suggest that national maize harvests increased by around 1 million tonnes in 2005/6 rising to more than 2 million tonnes in the 2008/9 season (around 54% and 114%) compared to the 2002/3 and 2003/4 seasons. Dorward et al. (2010) whose study on evaluation of maize yields, says that average maize responses to fertilizer, put the increase in maize output at around 400,000 tonnes in 2005/6 to 1,000,000 tonnes in 2008/9
(corresponding to an increase of 23% and 54%) compared to pre-AISP harvests.
Ricker-Gilbert and Jayne (2011) estimated the dynamic effects of the AISP and found that a fertilizer subsidy significantly increases maize production within the same year, and there are some indications of positive effects on maize production in subsequent seasons but these are surrounded by greater uncertainty. On the other hand, they find little evidence of a long-term effect on household assets or general wellbeing.
An impact assessment based on household surveys by Chibwana et al (2010) suggests that the programme increased maize yields of recipient farmers by 447 kg/ha (around 42%), of which just over half (249 kg/ha) can be attributed to
22 fertilizers and the rest to improved seed. Chibwana et al(2010) also reports that the
AISP caused some change in cropping patterns, as farmers’ reallocated land from alternative food crops such as cassava or sweet potato towards maize. To the extent that fertilized maize is more productive, this shift represents a further expansion in food production. Minde et al. (2008) and Chinsinga (2011) revealed that AISP made
Malawi to the maize exporter in southern Africa region, for example, in 2007 the government contracted with the government of Zimbabwe to export 400,000 tonnes of maize to Zimbabwe. The government managed to export only around 283,000 tonnes before suspending the contract due to rapidly increasing domestic prices.
Dorward et al. (2010) add that in 2009/10 the government added130,000 tonnes of maize to the strategic grain reserve and private traders accumulated a further
100,000 tonnes.
Baltzer and Hansen (2012) found that AISP managed to reduce rural poverty, where rural real wages increased continuously over the AISP lifetime even for poor non- beneficiaries. As maize production by AISP beneficiaries’ increases, the households’ dependence on off-farm work is reduced and more jobs are available for non-beneficiaries and land-less poor.
The findings of Chibwana et al. (2010), Dorward et al.(2010) and Chinsinga (2011) conclude that the Malawi AISP has a substantial positive effect on the use of agricultural inputs, agricultural productivity and food production due to affordability of smallholder farmers to purchase inputs at low prices.
23 However, the AISP faced a number of problems during the implementation (Morris et al., 2007) including uncertainty such as weather, leading to weathering of crops, complains from the smallholder farmers that OPVs maize seeds do not generate higher yields than hybrid maize seeds, though OPVs are more suitable for smallholders, as they are more resistant to pests and diseases, more drought resistant and more familiar to farmers. Chinsinga (2011) supports (Morris et al., 2007) by clarifying that harvested OPV maize may be retained as seeds for the next season, unlike hybrid seeds, which must be bought from the market each season. Thus, adopting subsidized hybrid seeds may generate a dependency on the multinational producers, which may prove devastating for smallholders once subsidies are phased out.
The efficiency of the programme is also affected by the timing of deliveries and the extent of fraud and corruption by programme stakeholders (Kachule and Chilogo,
2007). In Malawi, agricultural inputs should be available to farmers by end of
November to ensure their effective use. Baltzer and Hansen (2012) argue the timing of input deliveries has improved over the lifetime of the programme, only 30% of all sales had arrived by end November in 2008/9 season, most of the rest was delivered during the following month.
2.4.3.2 Market Smart Subsidies in Zambia
The Fertilizer Support Programme (ZFSP) in Zambia follows earlier attempts at stimulating the adoption of agricultural inputs, mainly fertilizers and hybrid seeds, in the production of maize. Earlier programmes focused less on direct subsidies and more on controlling input prices and making sure that inputs were available to
24 smallholders through state-managed production and distribution. Indirect and unintentional subsidization was provided in the form of state-provided credit, of which only 5%-10% was recovered (World Bank, 2010).
In 2001 the government estimated that only 30% of smallholders had access to improved seeds and just 20% had access to fertilizers. Small-scale farmers had too few financial resources to generate sufficient demand to support a competitive private input supply sector. In this context, the ZFSP was launched at the start of the
2002/3 agricultural season. It sought to break from earlier programmes by subsidizing inputs directly rather than providing credit and by focusing on the development of a competitive private input supply sector rather than relying on state-managed distribution (Kalinda and Simfukwe, 2007).
The ZFSP is designed to reach around 125,000 farming households, although in
2006/7 and 2008/9the government budgeted for some 200,000 households. The programme targeted farmer cooperatives, specifically approved by the government,
Farmer cooperatives, specifically approved by the government, play a central role in identifying beneficiaries and collecting the farmers’ payments, which are deposited before the inputs are handed out. According to the targeting criteria, recipient households should be an active small-scale farmer, have the capacity to cultivate between one and five hectares of land, be able to cover 40% of commercial input prices and should have no prior history as a defaulter in earlier government subsidized credit programmes (Minot, 2009). Baltzer and Hansen (2012) add that farmers need to be a member of the cooperative to benefit from the ZFSP. Each beneficiary household is entitled to pick up a package of agricultural inputs,
25 consisting of sufficient amounts of fertilizers and hybrid seeds to cultivate one hectare of land using the dosage recommended by the government.5 Compared to the value of the vouchers distributed by AISP in Malawi, the ZFSP packages are considerably larger, by a factor of around 8-10.Selected farmers received one package consists of four 50kg bags of compound D basal fertilizer, four 50kg bags of urea top dressing, as well as one 20kg bag of hybrid(Minde et al 2008).
The programme has brought some changes in maize production, Kachule and
Chilongo (2007) reported that participants achieved an average yield of around 2 tonnes per hectare, World Bank (2010) estimates that total production in Zambia increased by 146,000 tonnes of maize 2007/8, corresponding to 89% growth in output as a result of the ZFSP. This increase covers output due to higher yields
(estimated as 82,000 tonnes or 50% yield increase) as well as expansion in the area cultivated by maize (around 64,000 tonnes).
The ZFSP in Zambia is plagued by many challenges which hinder its efficiency in delivering inputs to the targeted small scale farmers. The study conducted by Minde et al.(2010) pointed out that the programme is theoretically targeted at smallholders in the 1-5 ha category, but in practice this criteria is not enforced and one sees that among the 1-20 ha landowners, farmers with the greatest landholdings receive disproportionately more inputs from the subsidy. The World Bank (2010) found it is difficult for smallholder farmers in Zambia rural areas to adopt input utilization due to lack of access to inputs in remote areas and, where they are available, high prices partly due to imperfect competition. NEPAD (2011) highlights that unlike most other recent targeted schemes; the scheme does not use vouchers. Inputs are to be
26 accessed directly through approved farmer cooperatives or other registered farmer groups who procure the fertilizer at the local decentralized state offices. Programme costs have grown considerably since the FSP was launched and risk displacing other development priorities. Between 2000 and 2008, input subsidies accounted for roughly 38% of MACO’s total budget. The 2007/08 ZFSP cost 23% more than expected (World Bank, 2010). Minde et al (2010) concludes that the geographic allocation of FSP inputs has been determined without consideration for the level of private-sector development in different parts of Zambia. The risk of displacement of the nascent private sector could be reduced by including geographic criteria relating to the presence of private suppliers in the targeting of the ZFSP programme.
2.4.4 Improved Agricultural Technologies
Crop production in Tanzania and many SSA countries is faced with low use of fertilizer and consequently low crop productivity. Several factors have been pointed out as cause of low fertilizer use in SSA and Tanzania in particular. One of the factors is the high uncertainty of water availability due to temporal rainfall variability, especially in rain fed agriculture (Pan and Christiaensen, 2011). Water uncertainty inhibits poor farmers to invest in the soil, and especially in fertilizer, a bad rainy season will lead to crop loss and thus of the money invested. This is a risk that poor farming households cannot simply afford to take. Another factor that is associated with the low use of fertilizer is the crop yield response. Kelly (2006) has pointed out that the crop yield response to fertilizer use in Africa has been much lower than in Asia, and that for many farmers fertilizer use may even be uneconomic, especially those whose farms have poor soils.
27 In Tanzania there is still low level of technologies practiced or adopted in agriculture in terms of inputs; agricultural implements or machinery and irrigation facilities to enable both the expansion and intensification of agricultural production
(Hepelwa, et al., 2013). The use of fertilizer in the country is far below other countries in Africa with similar conditions. It is estimated that only 12% of farmers use mineral fertilizers (AFAP, 2012). Currently Tanzania uses 9kg of nutrients/ha while Malawi uses 27kg of nutrients/ha, South Africa uses 53kg of nutrients/ha. The average usage per hectare in other regions is 41kg of nutrients in Latin America ha,
Asia is 85kg of nutrients/ha and Europe is 225 kg of nutrients/ha (FAO, 2008; URT,
2010).The low use of fertilizer in Africa can be explained by demand side as well as supply-side factors. Demand for fertilizer is often weak in Africa because incentives to use fertilizer are undermined by the low level and high variability of crop yields on the one hand and the high level of fertilizer prices relative to crop prices on the other.
Currently, Tanzania is putting significant effort to stimulate private sector to participate in agricultural input market through various food security programs which can promote access to farm inputs and use of farm inputs to enhance food productivity among poor farmers in rural areas, (MAFC, 2009).Among others, input voucher program is an approach adopted by the government to strengthen the agro- dealer’s network by improving their businesses and technical skills through provision of training, link them with input supply wholesalers, and enable access to credit and provision of improved customer services to smallholder farmers. This initiative has positioned agro-dealers at the centre that connects input wholesalers and smallholder farmers in the rural areas (Minot, 2009).The adoption of agro-
28 dealers model is based on findings from several researches that signal the problem of low agricultural productivity due to low farm input use by smallholder farmers who lack access to modern inputs in rural areas (Chianu et al., 2008). Therefore, building agro-dealers network via input voucher programs is taken as a cornerstone which can increase accessibility to agricultural inputs by poor farmers in the rural areas (Minot, 2009).
2.4.5 An Overview of Input Farm Input Supply in Tanzania
The history of farm input subsidies in Tanzania can be traced back to 1967 when the
Tanzanian Villagization programs were adopted to aggregate rural living units to facilitate the provision of rural population services as schools, health centers, piped water, electricity and access to roads (Coulson, 1982). Importation and distribution of agricultural inputs were state-controlled with highly subsidized input prices. The
World Bank (2007), Minde et al. (2008) and Tiba (2010), Tanzania supported the use of fertilize through universal subsidy. Under this policy the import, procurement, pricing and distribution of fertilizer were legally monopolized by public sector,
Tanzania Fertilizer Company (TFC) was the sole monopoly in importation, procurement, supply and pricing of fertilizer in all regions.TFC was 100% owned by government and fertilizer was subsidized up to 80% via donor’s funds (World Bank,
1994). There was no private company involved in input distribution market because there was no policy to promote commercial private input supply market.
The economic crisis of the mid-1980s led to the commencement of an economic reform program in 1986, involving liberalization of agricultural markets and foreign exchange, removal of domestic price controls, and reform of state monopolies. The
29 World Bank and International Monetary Fund (IMF) stopped to support subsidy programs because; subsidies weaken private sector and results into missing markets of farm input, subsides are expensive and increases government budget, subsides distorts farmers incentive and benefit rich farmers instead of poor farmers (World
Bank, 2008; Minot and Benson, 2009; Tiba, 2010; Chinsinga, 2011).
Agricultural market liberalization started with the food crop markets, and then cash crops market in early 1990s. Input subsidies were phased out between 1991 and
1994. Fertilizer subsidies decreased from 80 percent in 1990, to 55 percent in 1992, and to no more that 20 percent by mid-1992 (Putterman, 1995).
Ten years later, the government instituted a transport subsidy for fertilizer to encourage broader use of this input. The program aimed at encouraging access and use of farm inputs by poor farmers to enhance food productivity. The program targeted a few selected food crops such as maize and paddy, and a few cash crops such as tea, coffee and cashew nuts without government involvement in importation, pricing, procurement and distribution of inputs due to privatization policy (MAFC,
2009). However, debates about the cost effectiveness, targeting and distribution of benefits derived from this subsidy led to a redesign of the program around 2007. The transport subsidy was phased out, and replaced with a voucher based subsidy – the
NAIVS - aiming to lift the buying power of targeted groups of smallholders with the greatest potential to expand maize and rice production. In 2007/08, the voucher based subsidy was piloted in two districts, and then expanded to encompass 53 districts distributed across 11 high potential Regions in 2008/09 (URT, 2014). Under
NAIVS the importation, procurement, pricing and distribution of agricultural inputs
30 were now controlled and managed by private sector in Tanzania (URT, 2014 and
Kelly et al, 2003).
2.4.6 The National Agricultural Input Scheme (NAIVS)
The accessibility and utilization of agricultural inputs particularly fertilizer and improved seeds are still very low in a country. To address this issue, the
Government has initiated a piloting a smart subsidy programme in 2007/08. This has grown into the National Agricultural Input Voucher Scheme (NAIVS), with increasing pilots in 2008 and the development of a very large programme with
World Bank (Chirwa and Dorward, 2013). Minot (2009) argues that the programme intends to facilitate fertilizers use in high- potential areas, to offset rising international fertilizers costs, to reduce food prices by stimulating production, to stimulate expansion and increased capacity in the private input supply system. He continues explaining that the main features of the programme includes the use of vouchers for food crop inputs (fertilizers and maize and rice seeds) and distribution to targeted beneficiaries with complementary support to help them improve the efficiency of input use and to expand input suppliers’ financial and skills capacity.
Prior to the original implementation of the program, it was estimated that 2.5 million households were eligible, but the government distributed vouchers to only 1.5 million households in 2000/10 and 2 million households in 2010/11. Thus, each year there have been fewer vouchers distributed than the number of eligible farmers
(URT, 2014). Awareness has been vital to the success of many agricultural input initiatives (Malhotra, 2013). It is the first, most crucial step in creating an effective demand for agricultural inputs and in speeding up input adoption. Bardhan and
31 Mookherjee (2000) support the idea of Malhotra that the level of awareness has also been identified as a factor that can advance the likelihood of elite capture of vouchers. The key findings suggest a need to focus on specific criteria and objective awareness of the programme.
NAIVS campaigns sought to facilitate small-scale farmers’ awareness of the scheme. Out of the total households surveyed, 93% were aware of a programme that provides farmers with vouchers to buy fertilizer and seeds However, almost half of the respondents were not aware of the programme’s eligibility criteria, suggesting the absence of informed participation, which is crucial to the programme’s overall objective. The awareness level about specific eligibility criteria was particularly high in Ruvuma and Rukwa, whereas the awareness levels in Morogoro, Arusha, and Iringa were relatively low (Malhotra, 2013).Even with input market access, the fact remains that seed and chemical fertilizer remain expensive commodities at the farmgate. Many farmers face difficulty finding the capital to make this investment during the start of the growing season. Besides input market access and inputs cost, awareness is also a significant factor that influences the input use. (URT, 2014) about 20 percent of respondents noted that lack of awareness about the use and benefits of improved inputs prevented them from applying improved seeds or chemical fertilizer. For chemical fertilizer specifically, 16 percent of respondents believed their land was fertile and therefore did not require the application of any chemical fertilizer, which may also be an issue of lack of information and knowledge.
32 Farmers commonly complain about the late delivery of vouchers, as well as the late delivery of inputs once the vouchers were in hand. However, the period of delay varied considerably depending on the district and local practice. For example, in
2010/11, the subsidy vouchers were printed late, arrived in early December, but then in the port of Dar es Salaam until mid-January because of a tax dispute. Many farmers only received their vouchers in late January and early February – long after the planting season. The Ministry of Agriculture tried to offset this delay by printing certificates of input access for farmers and agro-dealers to sign prior to receiving the vouchers. These were accepted by many farmers and agro-dealers, but not all (URT,
2013).
2.4.7 Significance of Input Vouchers
If designed correctly, vouchers can promote free market competition among sellers, providing them an incentive to improve their services. Vouchers also allow for greater economic diversity by offering small farmers opportunities to purchase inputs which were previously unaffordable. Thus, vouchers would also help to shift small farmers’ mindset to focusing attention on how to get as much value as possible from their vouchers. In other words, small farmers will start to demand that sellers be efficient. For example, in Malawi smallholder farmers are demanding high quality inputs delivered in a timely fashion (Kachule and Chilongo, 2007).
Mangisoni et al. (2007) noted that vouchers reduce transaction costs and beneficiaries are given a choice in the type and quantity available of any input. At the same time vouchers allow participation of the private sector and have potential for market development at local level.
33 Input vouchers are believed to be important instruments that can be used to build the capacity of agro-dealers on provision of affordable services to poor farmers in rural areas through assisting agro-dealers to acquire training in business skills, record keeping, sales and marketing, stock management, managing business working capital, input market search, customer service and knowledge on the proper use of modern technology (AGRA 2007; Chianu et al. 2008; Chinsinga 2011). Also, input voucher schemes connect agro-dealers with formal financial institutions and farm input wholesalers for credit purposes to increase their working capital base.
Normally trained agro-dealers receives a certificate which allows them to participate in selling agricultural input under input voucher program after signing a contract with the government to recover some of the costs involved in the transaction
(MAFC, 2009). Certified agro-dealers are linked to major agricultural input supply firm by credit guarantees to be supplied with inputs on credit bases and pay after 30 to 60 days. Therefore certified agro-dealers have a guaranteed input demand and profit margin for supplying farm inputs in rural areas which reduces risks and uncertainties in their business and increases business working capital (Tiba, 2010).
2.4.8 Factors on Agricultural Productivity of Smallholder Farmers
Factors that influence productivity of a particular smallholder farmer may depend on the quantity and quality of physical inputs used including land, labour and capital; farm and farmer characteristics, macroeconomic factors and legislative framework such as government policies and strategies and agro climatic conditions (Wiebe et al., 2001; Rehman, 2003; Dorward and Chirwa, 2011). Capital inputs among others include seed, fertilizer, and farm equipment. Farm and farmer characteristics on the other hand include factors such as size and topography of area cultivated, location of
34 the farm with respect to input and output markets, age, gender, education level, household size, access to extension services, and access credit. Agro-climatic conditions mainly imply soil conditions and weather factors including rainfall, temperature and humidity (Michele, 2001).
Adesina and Forson (1995), who studied farmers' adoption of new agricultural technology in Burkina Faso and Guinea, report that both young and old sorghum smallholder farmers in Burkina Faso adopt new technology to improve agricultural productivity. Young smallholder farmers adopt the technology because they have long term plans and are willing to take risks. On the other hand, old smallholder farmers adopt it because they have accumulated capital or have greater access to credit, due to their age. However, the effect of farming experience (measured by the age of the household head) is not always positively associated with farmers’ adoption behaviors. For example, Zavale et al. (2005) report that older smallholder farmers in Mozambique are less likely to adopt improved maize variety than younger smallholder farmers.
Feder et al. (1985) provide empirical evidence on the importance of human capital for example, farmer’s education in improving agricultural productivity. They argue that education enhances the ability of small scale farmers to acquire, synthesize, and quickly respond to disequilibria, thereby increasing their likelihood of adoption of new agricultural technologies. Adegbola and Gardebroek (2007), educated smallholder farmers are able to better process information, allocate inputs more efficiently, and more accurately assess the profitability of new technology, compared to smallholder farmers with no education.
35 Some new agricultural technologies, including improved varieties, are more labor intensive, compared to traditional varieties. Thus, labor shortage may prevent farmers from adopting new agricultural technology. A household with a large number of family members who are available to work on the farm are more likely to adopt new technologies than household with a small number of family members
(Feder et al, 1985).
Macroeconomic factors for example having access to extension services, credit, roads, price information from markets, irrigation and being a member of an agricultural association have been widely used to assess smallholder farmers’ productivity. Pattanayak et al. (2003) argue that access to extension services provided by the government, NGOs, and other stakeholders play a very important role in the adoption of new agricultural technologies thereby improving agricultural productivity. Farmers who are exposed to information about new technologies by extension agents through training, group discussion, plots demonstration, and other form of information delivery tend to adopt new technologies.
Capital constraints and limited access to credits hinder the adoption of agricultural technologies. These factors especially apply to new inputs or technologies that require a high initial capital investment and high operational costs (Feder et al.
1985). However, a few empirical studies report that some new technologies that do not require a high initial capital investment for example, improved varieties also have low adoption rates because smallholder farmers do not have sufficient capital and access to credits.
36 2.4.9 Agriculture Sector in Tanzania
In Tanzania, agricultural sector is one of the key sectors to the national economy.
Over 80% of the population lives in rural areas and their livelihoods depend on agriculture. The sector accounts for 26.4% of the GDP, 30% of export earnings and
65% of raw material for domestic industries (World Bank, 2010). Agriculture sector employs about74 percent of the labour force (Malhotra, 2013). However, the sector experience low growth. Given the importance of the sector as a source income, employment and food security, this low growth has translated into little progress on poverty reduction. The proportion of people living below the basic needs poverty line remains high at more than 33% in 2007.
Most recent agricultural census approximates 12.6 million hectares of land to be the land under agricultural activities in the country which includes both temporary and permanent crops as well as livestock keeping. Smallholder farmers occupy 91% of the total area under agriculture. The remaining 9% of the land is held by large scale farmers who own a total of 1.1 million hectares. The average food crop productivity in Tanzania stood at about 1.7 tons/ha far below the potential productivity of about
3.5 to 4 ton/ha .High dependence on rainfall is the main characteristics of the agricultural practices by the small holder farmers in the country. In addition, the crop cultivation is characterized by low mechanization where majority farmers are using poor farm inputs such as hand hoe and traditional seeds. The soils have been degraded with significant loss of nutrients and thus contributing to low productivity problem (Hepelwa, et al., 2013).
37 2.4.10 Maize and Rice Production and Productivity
In Tanzania maize is considered the most important food crop in Tanzania covering
40 percent of total land area planted to crops and 67 percent of the area planted to cereal grains in 2011/12. Approximately 60 percent of all smallholder farm households grow this crop (Agriculture Sample Census 2008-09). Maize is sown in all Regions of the country, with the largest share of crop area found in Iringa,
Shinyanga, Morogoro, Mbeya, and Kigoma. The southern highlands (Iringa, Mbeya and Ruvuma) tend to produce surplus maize compared to consumption levels, while there tend to be deficits in the northern highlands, Dar es Salaam, and central regions (URT, 2014).
Rice is the third most important cereal grain after maize and sorghum, offering an important source of food, employment, and income for many farming households.
According to the 2008-09 Sample census of Agriculture 20 percent of all agricultural households grow rice. In 2011/12, paddy accounted for eight percent of food crop area and 13 percent of the area planted to cereals in the country. Over 60 percent of the country’s rice production is concentrated in the regions of Mbeya,
Morogoro, Shinyanga, Mwanza, Tabora, and Arusha (URT, 2014).
Production of maize and paddy has been increasing over time largely as a product of expanding crop area. This can be linked, particularly in the case of maize, with rising farm populations. In the case of paddy, production decisions are more closely linked with the market (ACT, 2012; URT, 2014).
38 Both staple cereal grains have displayed almost no growth in productivity. This coincides with the limited rates of adoption of improved seed and chemical fertilizer. Almost all of the paddy production in the country is on irrigated or lowland fields, though most are small-scale informal irrigation schemes dependent on rudimentary water management systems during the rainy season. The country has expanded its formal irrigation systems to encompass almost 50% of the paddy area in recent years, and this is where the NAIVS targeted its support. Average yields on formal irrigation schemes are estimated to be two or three times higher than on informal schemes. In 2009/10 production of paddy was 1.6 million metric tons in the project regions with productivity at 2.4 metric tons per ha. In terms of quantity produced maize has been far better compared to paddy, while in terms of productivity paddy performs slightly better in comparison to maize. This trend in production and particularly productivity of maize and paddy can be explained by the fact that over time paddy becomes a more attractive crop to farmers due to its higher prices in the market compared to maize (ACT, 2012 URT, 2014).
2.5 Research Gap
Since independence Tanzanian government has been providing input subsidies to farmers without significant improvement in agricultural productivity. However, the level of fertilizer use in the country (8 Kg /ha) is one of the lowest in the world; compared to sub-Saharan Africa (13 kg/ha), and developing countries (94kg/ha)
(Minot and Benson, 2009).The NAIVS established in 2008 is also facing serious implementation and management challenges. Institutions and institutional arrangements are critical components in addressing challenges facing agricultural input service delivery and agricultural improvement in general (IFPRI, 2010). The effectiveness of public investment in agricultural input service delivery is reduced
39 by problems of bad governance, including top-down approach in supplying inputs because of lack of social construct among the actors.
Due to this situation, smallholder farmers do not significantly benefiting since input vouchers are being distributed to them during emergent time and are controlled by wealthier people, the information on the role of these vouchers to improve agricultural productivity is not well known to smallholder farmers. Therefore, this study aims to fill this gap by showing how input vouchers can improve agricultural productivity among smallholder farmers in Tanzania.
2.6 Conceptual Framework
Factors that influence the smallholder farmers to use input vouchers as to improve agricultural productivity can be grouped as Government that provides legislative framework, macroeconomic factors, improved agricultural technologies and farmer’s characteristics (Feder, et al., 1985; Dorward and Chirwa, 2011).
The institutions and institutional arrangements are independent variables.
Macroeconomic factors are intermediate variables while improved agricultural technologies, farmer’s characteristics and agricultural productivity in smallholder farmers are dependant variables.
The government is responsible for the growth of macroeconomic factors; supporting accessibility and utilization of improve technologies if the legislative framework is made to function well. Macroeconomics is significantly important to the entire production and distribution of improved agricultural technologies to the smallholders. However, the demand and supply of these technologies can be/is
40 affected by the farmer’s factors. If farmer’s characteristics are clearly stated, productivity in smallholder farmers can be improved leading to higher yield, labour productivity and gross profit. The relationship is illustrated diagrammatically in
Figure 1.1
Independent variable Intermediate variable Dependent variable
Institutions and Macroeconomic factors Farmer’s Institutional characteristics arrangements -Infrastructures (roads, i irrigation schemes, agro- -Age. -Polices and strategies. industries, E-vouchers). -Education level. -Regulations. -Input/output prices. -Family size. -Structure and -Research on agriculture. management guiding the -Income. institutions. -Creation of awareness. -Income/wealth. -Extension services. -Improved health.
-Access to credit.
Agricultural Agricultural Productivity in Smallholders Technologies
-High yield. -Fertilizer.
-Labour productivity. -Seeds.
-Gross profit. -Pesticides. -Traction.
Figure 2.1: Conceptual Framework
Source: Researcher’s illustration based on theories.
41 CHAPTERTHREE
RESEARCH METHODOLOGY
3.1 Introduction
The research methodology explains the area of the study, justification of the study area, research design, study population, sampling design, sampling techniques, data collection design, analysis of data, validity and reliability and ethical consideration
It presents the how and why aspects of the research.
3.2 Area of the Study
3.2.1 Geographical Location
The study was conducted in Geita District, in Geita Region. Geita District is one of the five districts in Geita Region. It is bordered by Sengerema District in the East,
Chato District in the West, Bukombe and Mbogwe Districts in the South,
Nyang’hwale District in South East and Ukerewe District in the North.
The district is located in North-West Tanzania lies between latitudes 2°8’ and 3°28’ south of the Equator and longitude 31°15´ to 32° 48’ East of Greenwich. The
District is 1,100 to 1,300 meters above sea level.
3.2.2 Climate and Soils
The district has moderate temperatures of between 22° C to 30º C with average rainfall of 900mm – 1200 mm per annum. Rainfall is fairly evenly distributed with short rains from September to December followed by a dry spell from January –
February before long and heavy rains set in between March till end of May. From
42 the first of June to September the district is subjected to dry season. During hot and rainy season the humidity ranges between 35% and 60% respectively (URT, 2013).
Geita district is characterized by undulating land spotted with hills and mountains.
The land is characterized by black cotton soil, loam, sand, sandy loam and clay loam soil which are suitable for growing varieties of crops including maize, paddy, cotton, cassava, pineapple, bananas, sweet potatoes, yams beans, groundnuts, millet, wheat, passion fruits, millet, sisal, sunflower, coffee, tobacco, pyrethrum, sorghum, mangoes, among others (URT, 2013)
3.2.3 Economic Activities
The main economic activity of the district is agriculture and it is carried out around the district. Agriculture employs 80% of the district population and dominated by small scale farmers. Major crops grown in Geita district are maize, paddy, cotton, cassava, pineapple, sweet potatoes and beans. Also, the district has a significant number of livestock mostly owned by individual families. Geita district has 792km2 of forest which enables the residents engage in timber production and beekeeping.
Mining activities are carried out by large scale and small scale. Other economic activities done in the district are fishing activities on the shores of Lake Victoria and tourist activities take place at Rubondo Island National Park, found South West of
Lake Victoria (URT, 2013).
3.3 Justification of the Study Area
The district was selected for the study because of the following considerations; majority of the people in the district are smallholder farmers living in rural areas and depending on agriculture for food and income generation, the district was among
43 those districts implemented the National Agricultural Inputs Voucher Scheme
(NAIVS) and the district is famous in cultivation of maize and paddy, the two crops targeted in the programme. Also, Geita district is supporting irrigation farming for maize and paddy at Nzera/Nyamboge irrigation scheme.
3.4 Research Design
Research design is the conceptual structure within which research is conducted; it constitutes the blueprint for the collection, measurement and analysis of data
(Mbogo et al., 2012). Burns and Grove (2005) state that is a designed study that help researchers to plan and implement the study in a way that will help them obtain the intended results, thus increasing the chances of obtaining information that could be associated with the real situation. Polit and Beck (2004) define the research design as the researcher’s overall plan for obtaining answers to the research questions guiding the study.
In conducting this research cross-sectional design was used because data were collected on more than one case and at a single point in time. Data were collected from different groups of respondents who are involving in the sector of agriculture in Geita District. The respondents were smallholder farmers, District Agricultural and Livestock Development Officers (DALDO), District Marketing Officers,
Extension officers, Ward and Village leaders, Village Voucher Committee (VVC),
Agro-dealers and the National Microfinance Bank Officers.
The researcher was interested in variation of the collected data, which enabled him to establish more than one case in the study. The data were collected by research
44 methods called interview, focus group discussion (FGD), observation, and survey.
Also a research tool which is questionnaire was employed.
3.5 Study Population
A population is the group of individuals, persons, objects and items from which samples are taken for measurement (Lapin, 1987). For the accomplishment of this study four villages of Kamena and Nyakamwaga wards, where input vouchers were distributed. These villages are Nyakamwaga, Ntono, Imalampaka and Buyagu. All smallholder farmers in these villages who received inputs under vouchers, District
Agricultural and Livestock Development Officers, District Marketing Officers,
Extension officers, Ward and Village leaders, Village Voucher Committee (VVC),
Agro-dealers and the National Microfinance Bank Officers constituted the study population and totaled 100.
3.6 Sampling Design
Sampling design refers to the technique or the procedure the researcher would adopt in selecting items for the sample (Kothari, 2012). Sample design may as well lay down the number of items to be included in the sample, for example, the size of the sample. Sample design was determined before data collection. In this study the sampling design consists of sampling frame and sample size.
3.6.1 Sampling Frame
A sampling frame is a complete list of all the cases in the population from which the sample is drawn (Magigi, 2015). In this study the sampling frame included smallholder farmers, District Agricultural and Livestock Development Officers,
45 District Marketing Officers, Extension officers, Ward and Village leaders, Village
Voucher Committee (VVC), Agro-dealers and The National Microfinance Bank
Officers.
3.6.2 Sample Size
A sample is a part of the target or (accessible) population that has been procedurally selected to present it (Oso and Onem, 2008). It is a representative subject of all items falling into a defined category (population) (Browers, 1991). The choice of a sample size is governed by the level of certainty that characteristics of the data collected will represent the characteristics of the total population, the accuracy required for any estimation from the sample, and the type of analysis that are going to be taken (Saunder et al.,2003). The sample size for this study is estimated basing on equation (1) suggested by Yamane (1967). n = N ...... (1)
1+N (e) 2
Where n=Sample size
N=Population size e=Precision level
According to the 2012 Population and Housing Census, the population of Geita
District is 807,619 people. Using the formula N=807,619 and Precision (e) = 10%, where precision desired (5-10%).
Therefore, the estimated sample size will be n = .The sample size was
100 respondents.
46 The sample size comprised of smallholder farmers, District Agricultural and
Livestock Development Officials (DALDO), District Marketing Officials, Extension officials, Ward and Village leaders, Village Voucher Committee (VVC), Agro- dealers and The National Microfinance Bank Officials. Table 3.1 shows composition of the sample size.
Table 3.1: Composition of the sample size
Category of respondents Number of Percentage (%) respondents Smallholder farmers 80 80 District Agricultural and Livestock Development Officers (DALDO) 2 2.0 District Marketing Officers 2 2.0 Ward Extension Officers 2 2.0 Ward and Village leaders 3 3.0 Village Voucher Committee (VVC) 6 6.0 Agro-dealers 3 3.0 The National Microfinance Bank 2 2.0 officers Total 100 100.0
Source: Researcher’s sample design, 2015
3.7 Sampling Techniques
Sampling techniques are defined as procedures used to select the sample. They describe the ways in which sample units of study were selected from a population
(McNabb, 2006). Both probability and non probability sampling techniques were employed. In probability sampling, random sampling technique was used in selecting smallholder farmers who received input vouchers from selected villages. 47 Random sampling technique was used because all respondents (smallholder farmers) had enough information about the role of input vouchers in improving agricultural productivity and most of them answered questions clearly. Non probability sampling was applied to select village or/and ward leaders, agro-dealers, DALDO and NMB officers. Also, it was used in selecting wards and villages benefited from input vouchers.
3.8 Data Collection Design
Data collection is the process of gathering and measuring information on variables of interest, in an established systematic fashion that enables one to answer stated research questions, test hypotheses, and evaluate outcomes (Dodge, 2003). For this study both primary and secondary data were collected. In order to address the objectives of the study, both qualitative and quantitative data were collected.
3.8.1 Primary Data
Primary data are the data observed or collected directly from first-hand experience(Dodge, 2003).In this study primary data collected included socio- economic characteristics of respondents, production practices and attitude towards input vouchers in improving agricultural productivity among smallholder farmers.
3.8.2 Secondary Data
Secondary data are the data that were collected by someone else or for a purpose other than the current one (Dodge, 2003). The study collected data from different sources such as books, journals, internet and research publications from library.
48 3.8.3Data Collection Methods
Data collection methods which were employed are interviews, observation, survey, focus group discussion and documentary review. The researcher employed interview because it is flexible to enable to change the question(s) depending on the situation, also observation was applied in order to avoid biases and prejudice by respondents and to overcome language barriers. Survey method enabled the researcher to gather data from a large number of samples within the located time. Also, the focus group discussion enabled the researcher to obtain information based on beliefs, ideas or opinions of the community concerning input vouchers from the key informants.
3.8.3.1 Interviews
Face to face interview by the use of both structured and semi-structured interview methods were applied to collect data. The structured interview mainly involved open ended questions to grasp demographic information from the 12 key informants, through free and open discussion. Semi-structured interview was conducted to collect information from DALDO, District Marketing Officers and NMB officers,
Ward Extension Officers and smallholder farmers. The interviewees were guided by the already prepared interview guides.
3.8.3.2 Observation
The observation method was also used in data collection. The researcher used a non- participatory observation to obtain information on input vouchers in the study area.
Information like units of land, quality of inputs and yields were observed by the researcher’ naked years. The researcher visited the Nzera/Nyamboge Irrigation
49 Scheme to observe practical methods used in paddy production among the smallholder farmers.
3.8.3.3 Survey
Survey method consisted of questionnaire with a series of questions about the study.
Most of questions were open ended in order to give respondents wide range their own views and obtaining detailed information from them regarding the role of input vouchers in improving agricultural productivity in smallholder farmers. The method was employed because it assured the researcher to collect data within a short time thereby covering a large area.
3.8.3.4 Focus Group Discussions
Focus Group Discussions were carried out by groups of eight respondents who shared similar characteristics which are relevant to the study. It produces a lot of information quickly and is good for identifying and exploring beliefs, ideas or opinions in a community (Kombo and Tromp, 2006). This method was applied to justify the already collected data because in a group, respondents are more willing to provide sensitive information which may sometimes not provided during individual interview. One focus group discussion was conducted in Nyakamwaga, Ntono,
Imalampaka and Buyagu villages consisting of four smallholder farmers, two agro- dealers, one Ward Agricultural Extension Officer and one Village Executive Officer.
3.8.3.5 Documentary Review
Documentary review involved both published and unpublished materials/documents such as books, articles, reports and journals as well as searching from the internet.
50 Information like geographical location, climate, economic activities were gathered through documentary review. The information from these sources provided important information on the background of input vouchers and the role being played to improve agricultural productivity in smallholder farmer.
3.9 Analysis of Data
Data analysis is the process of evaluating data using analytical and logical reasoning to examine each component of the data provided (Makul and Deepa, 2013). For this study the collected data were edited, coded, entered and summarized before quantitative analysis using Statistical Package for Social Science (SPSS) version
16.0 and MS excel computer software.
Descriptive statistics were used whereby cross tabulation and ranking were employed to identify the role of input vouchers in improving agricultural productivity and socio-economic characteristics of smallholder farmers for each village and to establish relationships for categorical data sets. The study results are presented by tables using frequencies and percentages.
3.10 Validity and Reliability
Reliability and validity are key indicators of the quality of the research; they are common used in quantitative and qualitative research (Magigi, 2015). The researcher can ensure validity by using multiple sources of data, for example; interview, observation, survey, focus group discussion and documentary review. The collected data should be reliable, whereby a researcher should find the right
51 respondents to provide data for the study, and thus before data collection process the pilot study is to be conducted, to know if sources of information are right.
3.10.1 Validity
Validity refers to the degree to which the instrument measures what it is supported to measure (Magigi, 2015). The researcher focused on content validity, which is the degree to which the items in an instrument adequately represent the universe of content. The researcher gave the questionnaire to twenty smallholder farmers at
Ntono village to review/verify and validate the questions. This group of smallholder farmers did not participate in the main study. The reviewers supported that the components of the questionnaire accurately reflected the phenomenon being studied and that the questions were appropriate to the role of input vouchers in improving agricultural productivity among smallholder farmers in Geita District.
3.10.2 Reliability
The instruments were pre-tested with a sample of twenty smallholder farmers before actual data collection. This was carried out to obtain information in order to improve the questionnaire. The respondents in a pilot study had similar characteristics to the study and it was done under similar settings. Conducting a pilot study assisted the researcher to identify problems with the questionnaire and indicate the time needed to complete the questionnaire, which was important in obtaining consent to participate (Burns and Grove, 2005).
52 3.11 Ethical Considerations
Ethics refers to as code of behavior that is considered correct (Pera and Tonder,
2005 cited in Philemon, 2007). Ethical considerations in conduct were of the research were followed to prevent ethical problems. To ensure ethical conduct of the study, permission to conduct this study was obtained from the Geita District
Executive Director and respondents. Informed consent was obtained from each respondent. To ensure confidentiality, neither the name of respondents nor that of institutions involved was requested on the questionnaires. No physical or psychological risks were involved as the study was non experimental. The list of respondents’ name for sampling purposes was kept safe to ensure confidentiality.
53 CHAPTER FOUR
RESULTS AND DISCUSSION
4.1 Introduction
This chapter describes the results of the study and some observations made during the study. The results and discussion of the findings are presented in line with the specific objectives and research questions.
4.2 The Distribution of Respondents by Villages
The distribution of respondents by villages is presented in Table 4.1 where it shows that 20 (25%) farmers were coming from Nyakamwaga village, 20 (25%) from
Ntono village, 20 (25%) from Imalampaka village, and 20 (25%) from Buyagu village.
Table 4.1: Village Names and Number of Respondents
Village name Number Percentage (%) Nyakamwaga 20 25.0 Ntono 20 25.0 Imalampaka 20 25.0 Buyagu 20 25.0 Total 80 100.0 Source: Field data, 2015
4.3 Respondents’ Socio- Economic Profile
The utilization of input vouchers by smallholder farmers in the study was determined by social and economic variables such as demographic characteristics
(age, sex, marital status and level of education). Economic variables included main economic activity, annual income, extension services, access to credit, distance and transport infrastructures, access to input and output market. These are variables used 54 to examine the role of input vouchers in improving agricultural productivity in smallholder farmers in Geita District.
4.3.1 Age Groups of Respondents
Age is one of the factors that can affect the probability of a farmer being successful in farming. It is contended (Dlova et al., 2004) that, older farmers are less capable of carrying out physical activities while younger ones are capable. The younger farmers are more ready to adopt agricultural modern technology. Thus younger people may be more adaptive and more willing than older people to try new methods, age is expected to be an influencing factor. Table 4.2 shows that 42.5% of the respondents are those falling between 31-40 age category, followed by age category of 41-50 which accumulated 27.5% while respondents with the age of 50 plus consisted of 16.2% of total respondents. The last age category is between 21-
30, which accounted for 13.8%.These findings imply that majority of the people
(42.5%) are in the active age group and hence are likely to be engaged in economic activities and more capable to adopt modern agricultural technology, for example, utilization of inputs via vouchers.
Table 4.2: Percentage Distribution of Respondents by Age
Age category of respondents Frequency Percentage (%) 21-30 11 13.8 31-40 34 42.5 41-50 22 27.5 50+ 13 16.2 Total 80 100.0
Source: Field data, 2015
55 4.3.2 Sex of Respondents
The survey sample was more dominated by males (70.0%) than females (30.0%) heads of households (Table 4.3). This is usual since the domination of male-headed households is common among African societies, most of which are patrilineal, for example in the study area, the family arrangement in Sukuma and Sumbwa ethnic group is dominated by males as the key leaders of the family. In addition, although the questionnaire was directly administered to either male or female heads of households, it happened often that whenever both spouses were present, the wife beckoned to the husband to answer the questions. The findings comply with that of
Stephens (1992) who argued that though most technologies are considered gender neutral, they are often gender biased during their introduction and use by societies.
Table 4.3: Percentage Distribution of Respondents by Sex
Sex category of respondents Frequency Percentage (%) Male 56 70 Female 24 30 Total 80 100.0 Source: Field data, 2015
4.3.3 Marital Status of Respondents
Most of the respondents in the study area are married (87.5%) as indicated in Table
4.4, while 7.5% are divorced. Besides, 3.8% of the respondents are widowed, and
1.2% is single. These results reflect the NAIVS implementation plan, through which priority was given to female headed household. The study found that the respondents who are divorced and widowed are females, they were considered as beneficiaries of input vouchers.
56 Table 4.4: Percentage Distribution of Respondents by Marital Status
Marital status of respondents Frequency Percentage (%) Married 70 87.5 Divorced 6 7.5 Widowed 3 3.8 Single 1 1.2 Total 80 100.0
Source: Field data, 2015
4.3.4 Education Level of Respondents
Education is valued as means of liberation from ignorance. It is the only principal mechanism for developing human skills and knowledge (URT, 2002). Respondents were grouped into three categories with respect to education background. The categories were no formal education, primary education and secondary education.
Findings revealed that the majority of respondents (83.8%) attained primary education and few (15.0%) have attained secondary education (Table 4.5). It is therefore evident that most of the smallholder farmers in the study are had basic education and they know how to read and write. This result of having a big number of people who attended the primary school is expected in Tanzania because basic education is regarded basic right of every Tanzanian, it is compulsory for every child. Such considerable high rate of literacy is an important input which may enable people to be aware, understand and adopt new skills more easily. Educated people are expected to perform certain jobs and functions with higher efficiency and are more likely to adopt new technologies in a shorter period of time than uneducated ones. This is mainly because more educated people can gather, process and interpret all available information from different diverse investment areas and make decisions more early. 57 Lack of formal education might hinder prosperity of micro enterprises hence lower the income generation. Makauki (1999) found also that knowing how to read and write was sufficient in adoption of technology whose dissemination demanded simple leaflets, pamphlets, posters, newspapers or other simple written materials.
According to the results of this study a large number of the respondents had attained primary education level than other levels. This means that there were relatively very few respondents who had attained secondary education in the selected sample. This situation may be due to geographical nature of the study area which is almost rural area. In normal expectation, most of high education graduates are rarely found in rural areas. The same situation was reported in a study conducted in Dodoma Region
(Mohani, 1991).
Table 4.5: Percentage Distribution of Respondents by Education Level
Education level Frequency Percentage (%) No formal education 1 1.2 Primary education 67 83.8 Secondary education 12 15.0 Total 80 100.0
Source: Field data, 2015
4.3.5 Main Occupation of the Respondents
Findings in Table 4.6 show respondents’ occupations whereby 58.8% were practicing farming only as their only main economic activity, followed by 23.8% respondents who were involved in both farming activities and livestock keeping,
12.5% of respondents were small a business persons respectively apart from farming and livestock keeping. Those engaged in livestock keeping and mining activities
58 were 2.5% each. These results indicate that 58.8% respondents in the study area had no other means of sustaining their livelihoods apart from farming. These findings comply with that of Mashindano et al. (2011) which states that approximately 74%
Tanzanian population draws their income and therefore their livelihood from farming activities.
Table 4.6: Percentage Distribution of Respondents by Main Occupation of the Respondents Main Occupation of the Respondents Frequency Percentage (%) Farming only 47 58.8 Livestock keeping only 2 2.5 Farming and livestock keeping 19 23.8 Mining activity 2 2.5 Small Business 10 12.5 Total 80 100.0
Source: Field data, 2015
4.4 The Extent Usage of Input Vouchers among Smallholder Farmers in Geita
District
This sub section presents data on one of specific objectives of the study which aimed at examining the extent usage of input vouchers to smallholder farmers in the study area.
4.4.1 Awareness on Input Vouchers under NAIVS in Study Area
The input vouchers were introduced in Geita District since 2009/2010 cropping season to enable smallholder farmers to access inorganic fertilizer, improved seeds for maize and cotton as well as pesticides. The input vouchers were distributed to
59 the smallholder farmers under the National Agricultural Input Voucher Scheme
(NAIVS). The study found that 100% of the interviewed respondents were made aware about input vouchers. The sources of information about input vouchers are as shown in Table 4.7. The survey findings in Table 4.7 indicate that respondents’ sources of information about input vouchers was through village meetings (45.0%), government extension officials (26.2%), agro-dealers (23.8%), mass media (2.5%) and from friends/neighbors (2.5%). According to the National Guidelines on the implementation of agricultural voucher system, the eligible farmers have been required a full understanding of their entitlement, rights and obligation.
Beneficiaries should be doing farming from beneficiary villages, able to top up the difference between input market value and voucher value and finally approved by village general meeting (URT, 2014).
Table 4.7: Sources of Information about Input Vouchers
Sources of Information Frequency Percentage (%) Village meetings 36 45.0 Extension officials 21 26.2 Agro-dealers 19 23.8 Mass media 2 2.5 Friends/neighbors 2 2.5 Total 80 100.0
Source: Field data, 2015
4.4.2 The Agricultural Inputs Accessibility before Input Vouchers
Smallholder farmers in Tanzania do not use farm inputs as a result the productivity is very, because they cannot afford to purchase farm inputs at the given high prices
(Minot and Benson 2009). Findings in Table 4.8 revealed that 60% of the 60 respondents have not been using improved inputs before input vouchers because of lack of knowledge on the use of improved inputs. In addition, 27.5% of respondents reported that improved inputs were not easily available; therefore during that time they used their local varieties and relied on natural soil fertility. Also it was found that 5% and 3.8% of the respondents in the study area had not used improved inputs before input vouchers because of high cost of inputs and lack of capital respectively.
These findings are matching with the baseline report which indicated that farmers used little fertilizer or improved seeds because these inputs were hard to obtain. The marketing and supply chain infrastructure for agricultural inputs remains weak and inefficient and discourages many farmers from investing in inputs to increase crop production (URT, 2009).
Table 4.8: Reasons for Low Usage of Improved Inputs in the Study Area before Input Vouchers Reasons for not utilize improved inputs Frequency Percentage (%) Lack of knowledge on the use of improved 48 60.0 inputs The improved inputs were not easily 22 27.5 available High cost of improved inputs 4 5.0 Lack of capital 3 3.8 Belief on natural soil fertility 2 2.5 Depending on local seeds and manure 1 1.2 Total 80 100.0
Source: Field data, 2015
61 4.4.3 Input Price in Geita District 2009/2010 to 2011/2012
Selected smallholder farmers in the district were provided with vouchers covering half of the cost of inputs sufficient for one acre of maize or rice that they redeemed with local agro- dealers. The results from FGD showed that the vouchers enabled smallholder farmers to acquire 50% subsidy either one 50kg bag of DAP or two
50kg bags of the Minjingu Rock Phosphate (MRP) for a basal dressing (planting fertilizer), one 50kg bag of urea for top-dressing (boosting fertilizer), and 10 kg of improved maize seed (open pollinated variety or hybrid). Farmers took the vouchers to local agro- dealers to obtain the inputs. Table 4.9 and 4.10 indicate the value of subsidy voucher and top up payment made by smallholder farmers in the study area between 2009/2010 and 2011/2012.
The top up prices for OPVs maize seeds and hybrid maize seeds in planting season of 2009/2010 were higher than subsidy of 50%. The smallholder farmers contributed
60.0% and 55.6%, while in 2011/2012 the top up price of hybrid maize seeds decreased to 50%, but OPVs maize seed continued to be 60%.
62 Table 4.9: The Value of Subsidy Voucher and Top up Payment made by Smallholder Farmers in 2009/10 Type of input Subsidy Farmer’s Market price % a farmer (Tshs) top up (Tshs) top up (Tshs) DAP (50kg) 50,000 20,000 70,000 28.8 MRP (100kg) 60,000 40,000 100,000 40.0 Urea (50kg) 40,000 30,000 70,000 42.9 Hybrid maize seeds (10kg) 20,000 25,000 45,000 55.6 OPVs maize seeds (10kg) 10,000 15,000 25,000 60.0 Paddy seeds (15kg) 10,000 10,000 20,000 50.0
Source: Field data, 2015
Table 4.10: The Value of Subsidy Voucher and Top up Payment made by Smallholder Farmers in 2011/2012 Type of input Subsidy Farmer’s top Market price % a farmer (Tshs) up(Tshs) (Tshs) top up DAP (50kg) 40,000 30,000 70,000 42.9 MRP (100kg) 60,000 40,000 100,000 40.0 Urea (50kg) 40,000 20,000 60,000 33.0 Hybrid maize 20,000 20,000 40,000 50.0 seeds (10kg) OPVs maize 10,000 15,000 25,000 60.0 seeds (10kg) Paddy seeds 10,000 10,000 20,000 50.0 (15kg)
Source: Field data, 2015
63 4.4.4 Preferable Time for Distribution of Input Vouchers to Smallholder
Farmers
The utilization of improved inputs via input vouchers in the study area is affected by time factor. The study found that the preferable time for distributing inputs in the study area is September. This is due to the fact that 71.2% of the smallholder farmers reported that the vouchers be distributed in September before the beginning of rain season (Table 4.11). Smallholder farmers said that if they received inputs in
September, it is possible to match with rain season which often starts in October.
Respondents reported that, they would prefer to have the vouchers immediately after the June – July harvest, when most smallholder farmers have cash and find it easier to make the 50 percent co-payment for the input vouchers.
Table 4.11: Reasons for Distributing Input Vouchers in September
Reasons for Villages Total distributing Nyakamwaga Ntono Imalampaka Buyagu inputs on September Before the 11 16 18 12 57 beginning of rain 13.8% 20.0% 22.5% 15.0% 71.2% season Time for land 6 4 1 5 16 preparation 7.5% 5.0% 1.2% 6.3% 20.0% Farmers have 3 0 1 3 7 cash 3.8% 0.0% 1.2% 3.8% 8.8%
Source: Field data, 2015
64 4.4.5 Annual Income of the Respondents
Information about household income in the study was very important as it could reveal if the smallholders can afford and access inputs under voucher scheme.
During the study the respondents were asked to mention their income per year. The results in Table 4.12 indicate that more than half (81.2%) of household respondents earn above 250,000/=per year. About 10.0% of respondents interviewed pointed out that their income per year was ranging between 20,000/= - 240,000/=, followed by a group of smallholder farmers (3.8%) whose annual income is between 150,000/= -
190,000/=, other smallholder farmers (1.2%) earn between100,000/= - 140,000/= and 50,000/= - 90,000/= while only few (2.5%) are those who earn below 50,000/= per year. Results of different empirical studies show the effect of annual income on households’ decision in using and adopt improved agricultural technologies. For example, Kidane (2001), Dejene at al., (2001) and Getahun (2004) reported positive influence of households’ farm income on adoption of improved agricultural inputs.
Table 4.12: Annual Income of the Respondents
Income earned annually Frequency Percentage (%) Below 50,000/= 2 2.5 50,000/= - 90,000/= 1 1.2 100,000/= - 140,000/= 1 1.2 150,000/= - 190,000/= 3 3.8 200,000/= - 240,000/= 8 10.0 Above 250,000/= 65 81.2 Total 80 100.0
Source: Field data, 2015
65 4.4.6 Sources of Funds for Purchasing Input Vouchers
The smallholder farmers who received input vouchers were asked to indicate the sources of funds for top up. The study found that 83.8% of respondents said that the main source of fund was from selling agricultural products harvested in the previous season, while 10.0% said that was from taking money from local lenders. Others covered the remaining costs through selling livestocks (3.8%) and providing labour in others’ farms (2.5%). These results in Table 4.13imply that all respondents in the study area were capable to access fund from various sources which influenced them to make a 50% subsidy top up for agricultural inputs under vouchers.
Table 4.13: Sources of Funds for Purchasing Input Vouchers
Respondents’ Villages Total sources of fund Nyakamwaga Ntono Imalampaka Buyagu Selling agricultural 17 16 17 17 67 products 21.2% 20.0% 21.2% 21.2% 83.8% Taking money from 1 3 2 2 8 local money lenders 1.2% 3.8% 2.5% 2.5% 10.0% Selling livestocks 1 0 1 1 3 1.2% 0% 1.2% 1.2% 3.8% Providing labour in 1 1 0 0 2 others’ farms 1.2% 1.2% 0% 0% 2.5% Source: Field data, 2015
4.4.7 Distribution of Input Vouchers
The researcher wanted to know how many times a householder received input voucher for agricultural usage in farms. The results from field survey show that
77.5% of smallholder farmers received input vouchers three times, while 13.8% 66 received input vouchers two times and 8.8% received input vouchers only one time
(Table 4.14).
Furthermore, during the interview with the village executive officers, extension officers and the District Agricultural and Livestock Development Officers
(DALDO) it was noted that smallholder farmers who received input vouchers three times were those managed to contribute the top up price for three years, but smallholders received input vouchers one or two times were those who either failed to contribute, and excluded from the program or were those added when the program had already started.
Table 4.14: Distribution of Input Vouchers
Duration for Villages Total receiving Nyakamwaga Ntono Imalampaka Buyagu inputs Once 0 3 1 3 7 0.0% 3.8% 1.2% 3.8% 8.8% Twice 0 4 5 2 11 0.0% 5.0% 6.2% 2.5% 13.8% Thrice 20 13 14 15 62 25.0% 16.2% 17.5% 18.8% 77.5% Source: Field data, 2014
4.4.8 The Quality of Inputs
The quality of inputs is very important in agricultural productivity of the smallholder farmers. Farmers’ responses about the quality of inputs are as shown in Table
4.15.Among the respondents, 68.2% reported that the quality of inputs received 67 through input vouchers was good although 13.0% said that MRP not good because its impact appeared in the next cropping season. These findings are in line with URT
(2012) who found that MRP and urea fertilizers had poor quality during the year
2011/12. During the interview, smallholders reported that the identified the qualities of inputs after applying to the field and realized high yield.
Table 4.15: Smallholders’ Response about the Quality of Inputs
Smallholder Villages Total assessment Nyakamwaga Ntono Imalampaka Buyagu Good 14 4 12 17 47 20.3% 5.8% 17.4% 24.6% 68.2% Very good 3 7 2 1 13 4.3% 10.2% 2.9% 1.4% 18.8% MRP impact 2 6 0 1 9 appeared in the 2.9% 8.7% 0.0% 1.4% 13.0% next cropping season Source: Field data, 2015
4.5 The Effects of Input Vouchers on Farmer’s Efficiency in Production
This part presents the effects of input vouchers on farmer’s efficiency in production, since input vouchers aimed at improving agricultural productivity of the smallholder farmers in Geita District.
4.5.1 Size of land Owned by a Household
Size of land owned and used by household is one of the factors which determine agricultural productivity of smallholder farmer. The smallholder farmers were asked 68 to indicate the size of land they owned. Table 4.16shows that majority (55.9%) of smallholder farmers owned land ranging between 1 and 3 acres. Another (30.5%) of respondents owned land ranging between 4 and 5 acres and only 13.6% owned six and above.
Table 4.16: Size of land Owned by a Household
Size of land (acres) Frequency Percentage (%) 1 – 3 33 55.9 4 – 5 18 30.5 6> 8 13.6 Total 59 100.0 Source: Field data, 2015
4.5.2 Farmers’ Access to Land for Agricultural Production
Results in Table4.17 show that all (100%) smallholder farmers in the study area had access to land. Also, (72.0%) of smallholder farmers purchased the land, (21.0%) inherited the land and (6%) rented the land for agricultural production. These findings show that most of the smallholder farmers (66%) in the study area purchased land.
69 Table 4.17: Farmers’ Access to Land and Mode of Land Acquisition
Farmers’ access to land Frequency Percentage (%) Yes 100 100.0 No 0 0.0 Mode of land acquisition Purchased 46 72.0 Inherited 13 21.0 Rented 4 7.0 Source: Field data, 2015
4.5.3 Units of Land used for Maize and Rice Production
Agricultural productivity is measured by determining the units of land used in production of agricultural output. During the field survey smallholder farmers who received input via vouchers were requested to indicate the units of land they used to cultivate maize and rice. The results are as shown in Table 4.18, where 63.0% of respondents were engaged in maize production and cultivated between 1 and 2 acres, 30.4% of respondents produced maize in units of land between 3 and 4 acres.
Less than half (6.6%) of smallholder farmers cultivated more than 5 acres.
On the other hand (47.1%) of small scale rice producers cultivated between 1 and 2 acres, 32.4% used 3 to 4 acres for growing rice and 20.5% of respondents cultivated more than 5 acres. According to focus group discussants, it was discovered that agricultural productivity was increased among the smallholder farmers because more units of land which were not cultivated before, were put in agricultural production. Utilization of inorganic fertilizer, improved seeds and pesticides stimulated agricultural production in the study area especially in the second and third year of the voucher system. 70 Table 4.18: Units of Land used for Maize and Rice Production
Units of Frequency Percentage Units of land Frequency Percentage land used (%) used for rice (%) for maize production production (acres) (acres) 1 – 2 29 63.0 1 – 2 16 47.1 3 – 4 14 30.4 3 – 4 11 32.4 >5 3 6.6 >5 7 20.5 Total 46 100.0 Total 34 100.0 Source: Field data, 2015
4.5.4 Usage of Improved Inputs per Acre
The productivity among the smallholder farmers was improved due to high efficiency in usage of fertilizer, improved seeds and pesticides than before vouchers.
Table 4.19 indicates that most of smallholder farmers (60.0%) in the study area applied 50kg or 100kg of fertilizer per acre for planting and boosting. Also, they used either 10kg of hybrid maize seeds or OPVs maize seeds per acre, the small scale rice producers planted 15kg of paddy seeds per acre. The findings show that majority of respondent applied pesticides to protect their plants against fungi and pests.
These results are in line with URT (2014) each targeted farmer was expected to apply 10 kg of either an improved open pollinated maize variety (OPVs), or a maize hybrid, suitable for planting approximately one acre of land. District extension officers decided in advance whether a village would receive the voucher for the open pollinated variety (OPVs) or the hybrid seed. The remaining 20 percent of
71 vouchers offered 15 kg of paddy seed – suitable for approximately one acre of irrigated rice.
One acre required 50kg bag of DAP of planting fertilizer or two 50 kg bags of
Minjingu Rock Phosphate (MRP). Smallholder farmers received 50 kg of boosting fertilizer which was almost universally designated as urea, sufficient for one acre (URT,
2014).
72 Table 4.19: Usage of Improved Inputs per Acre
Types of improved Villages Total inputs Nyakamwag Ntono Imalampaka Buyagu a Fertilizer, seeds and pesticides 5 14 16 13 48 DAP(50kg),MRP(1 00kg),Urea(50kg 6.2% 17.5% 20.0% 16.3% 60% hybrid maize seeds(10kg) or OPVs maize seeds (10kg), paddy seeds(15kg) and pesticides Fertilizer and seeds only 9 5 4 1 19 DAP(50kg),MRP(1 11.2 6.2 5.0% 1.2% 23.8 00kg),Urea(50kg)h ybrid maize seeds(10kg) or OPVs(10kg) and paddy seeds(15kg). Seeds and pesticides only 1 0 0 0 1 Hybrid maize seeds 1.2% 0.0% 0.0% 0.0% 1.2% (10kg) or OPVs(10kg), paddy seeds (15kg) and pesticide. Seeds only Hybrid maize 1 0 0 4 5 seeds(10kg) or 1.2% 0.0% 0.0% 5.0% 6.2% OPVs V(10kg) and paddy seeds(15kg) Fertilizer only 4 1 0 2 7 DAP (50kg), MRP 5.0% 1.2% 0.0% 2.5% 8.7% (100kg) and Urea(50kg) Total 20 20 20 20 80 25.0% 25.0% 25.0% 25.0% 100%
Source: Field data, 2015
73 4.5.5 Yield of Maize and Rice per Acre
Yield, which is commonly expressed in tones per acre (t/ha) is the measure of agricultural productivity and is defined as amount of agricultural output per unit of land used in production.
The researcher requested the respondents to indicate quantity of maize and rice they harvested per acre. The survey findings in Table 4.20 show that 40.4% of small scale maize producers in study area produced 1500kg to 1700kg of maize per acre after application of improved inputs. More than half (28.6%) of respondents harvested 1200kg to1400kg of maize per acre, while 14.3% produced 900kg to1100kg of maize per acre, 9.3% and 7.2% harvested 1800kg to 2000kg and
2100kg to 2300kg of maize per acre during input vouchers.
On the other hand 70.0% of small scale rice producers produced 4000kg to 4300kg of rice per acre, while 16.2% got between 3600kg and 3900kg per acre. Other 6.6% harvested between 2800kg and 3100kg per acre, while 3.2% produced either 3200kg to 3500kg or 2400kg to 2700kg per acre respectively.
During the FGD with the key informants and the extension officers reported that yield of maize and rice per acre increased more than before the input vouchers. They pointed out those smallholder farmers who applied inputs under voucher system had increased production of maize from 4bags/acre to 16bags – 28bags/acre. Similarly there was great increase in rice production from 13bags/acre to 35bags –
40bags/acre. Smallholder farmers in study area use bags as their units of
74 measurements. The illustrations from extension officers said that one bag contains of either 120kilogramme of maize or rice.
These results concur with the study of Mguruse (2007) and Mng’olage (2008) who found that there has been a significant increase in maize and rice yield since the inception of the subsidy programme in Tanzania. In Malawi, there has been a progressive increase in yield from less than 1.0MT/ha to 2.04MT/ha (Luhanga and
Sungani, 2007).
Table 4.20: Yield of Maize and Rice per Acre
Maize yield Frequency Percentage Rice yield Frequency Percentage (kg) (%) (kg) (%) 900 – 1100 6 14.3 2400- 2700 1 3.2 1200 - 1400 12 28.6 2800- 3100 2 6.6 1500 - 1700 17 40.4 3200- 3500 1 3.2 1800 - 2000 4 9.3 3600- 3900 5 16.2 2100 - 2300 3 7.2 4000- 4300 22 70.8 Total 42 100.0 Total 31 100.0 Source: Field data, 2015
4.6 The Challenges for Effective Accessibility and Utilization of Input Vouchers
in the Study Area
Although input vouchers improved agricultural productivity among the smallholder farmers who received them, there were many challenges which hindered effective accessibility and utilization in the study area.
75 4.6.1Contact with Extension Officers
During oral interviews the key informants pointed out that effective utilization of inputs is affected by shortage of extension services due to shortage of extension officers. Smallholder farmers in the study area lack contact with extension officers, it was found that every ward had only one extension officer who is responsible to provide extension services to more than five villages with more than 300 smallholder farmers.
In additional during household’s survey, respondents mentioned absence of village extension officers in every village, causing low adoption agricultural innovations such as use of improved seeds, spacing, harvesting methods, and storage techniques.
Table 4.21 shows 83.8% of respondents reported that the number of extension officers in the study area not enough to provide extension services, while 16.2% satisfied with a number of extension officers found in the study area, because they are nearly with these officers.
Table 4.21: Contact with Extension Officers
Contact with Villages Total extension officers Nyakamwaga Ntono Imalampaka Buyagu Yes 11 1 1 0 13 13.8% 1.2% 1.2% 0.0% 16.2% No 9 19 19 20 67 13.8% 23.8% 23.8% 25.0% 83.8% Total 20 20 20 20 80 25.0% 25.0% 25.0% 25.0% 100.0% Source: Field data, 2015
76 4.6.2 Access to Credit
Smallholder farmers in the study depend much on savings from their low incomes, which limits opportunities for utilization of improved inputs. Most of smallholder farmers acquired incomes to make contribution on input vouchers from agricultural activities, such as selling agricultural products, selling of livestocks and providing labour in others’ farms. Others obtained income to purchase inputs from the local money lenders found in the study area. However, those lend money from the local money lenders claimed high interest rates.
Table 4.22 indicates factors for low or absence of accessing to credit from financial institutions as mentioned by most of respondents in study area, where 61.3% reported lack of knowledge on financial institutions as a major hampering factor for smallholders to secure fund from formal financial institutions like commercial banks, community banks and Savings and Credit Cooperative Societies (SACCOS), while smallholder farmers (22.6%) fear to process loan because of weather uncertainity that leading to crop failure. Other limitations are lack of collateral requirements (8.6%), most of financial institutions are located in large urban centres
(6.5%) and high interest rate (1.1%).
77 Table 4.22: Factors for Low or absence of accessing to Credit from Financial Institutions
Factors Frequency Percentage (%) Lack of knowledge on financial institutions 57 61.3 Weather uncertainity leading to crop failure 21 22.6 Lack of collateral requirements 8 8.6 Most of financial institutions are located in large 6 6.5 urban centres High interest rate 1 1.1 Total 93 100.0% Source: Field data, 2015
4.6.3 Distribution of Improved Inputs on Time to Targeted Households
Timely delivery of inputs was mentioned as a challenge in effective utilization of improved inputs across surveyed villages. Sometimes smallholder farmers got input one month after the start of the season, especially during the 2009/2010 cropping season, where vouchers were delivered in November. Again, distribution of fertilizer was done during a period where majority of the smallholder farmers do not have money. Inputs were distributed during a time where villages were in financial hardships.
Results from the interviews and FGD with District Agricultural and Livestock
Development Officers (DALDO), District Market Officer, NMB officer and Ward
Agricultural Extension Officers (WAEO) point out the reasons for late delivery of vouchers to be late printing of vouchers due to government budgetary arrangement which was done in June and July, and therefore the government released funds by
78 September for preparing vouchers (56%), MAFC did not prepare vouchers for the future use (44%) in Table 4.23.
Table 4.23 Reasons for Late Delivery of Vouchers to Smallholder Farmers
Reasons for late delivery of vouchers Frequency Percentage (%) Late government budgetary 44 56 arrangement MAFC did not prepare vouchers for 36 44 future use Total 80 100.0 Source: Field data, 2015
4.6.4 Mismanagement of Vouchers
Input vouchers aim to target the poor resource farmers, findings in the study area reveal that benefit wealthy farmers and powerful local authorizes.
4.6.4.1 Local Officers Colluding with VVC to Jeopardize the Vouchers
The results from field survey indicate that majority of respondents pointed out the interference of local officer in the distribution of vouchers. The village leaders and
VVC selected some farmers, who were not qualified to be input voucher beneficiaries due to wealth they had and were capable to purchase improved inputs by using their own income. Also, they included farmers from neighbouring villages contrary to the NAIVS guidelines which required a beneficiary to be a full-time farmer residing in a particular village and willing to cultivate not more than 1.0 acre of land for maize and/or rice. Similarly, the local leaders and VVC members could have more than five vouchers in one household instead of three authorized vouchers. 79 The key informants reported that mismanagement of vouchers caused some smallholder farmers to fail to access and utilize improved inputs during the three years life of the voucher system, as they were not selected to be input voucher beneficiaries. However, respondents clarified the reasons for local authorities to jeopardize the vouchers as shown in Table 4.24, where 46.7% of respondents reported that local leaders violated NAIVS guidelines in order to accumulate personal wealth. Local officers received corruption from smallholders so that to select them, 40.3% of respondents said that local leaders used vouchers to gain political popularity so that to win political opportunities in future. Again, local leaders excluded their political opponents in voucher distribution as a punishment.
Other (13.0%) mentioned that jeopardize of vouchers among the VVC members was due to lack of allowances for their government responsibilities.
Table 4.24: The Reasons for Local Authorities to Jeopardize the Vouchers
Reasons Frequency Percentage (%) To accumulate person wealth 36 46.7 Local leaders wanted to gain political 31 40.3 popularity VVC members lacked allowances for their 10 13.0 government responsibility Total 77 100.0 Source: Field data, 2015
80 4.6.4.2 Selling Vouchers to Agro-dealers or other Wealthy Farmers by
Smallholder Farmers
The findings revealed that some of the smallholder farmers in the study area, who received vouchers, sold them back to the agro-dealers at cheap prices, where agro- dealers could receive redemption of full price as if they had sold inputs. Likewise, smallholder farmers sold inputs received via vouchers to other wealthy farmers with cheap prices. The results in Table 4.25 show that 81.0% of respondents reported existence of poverty among the smallholder farmers as a main reason for selling vouchers or and inputs back to agro-dealers or wealthy farmers, while 16.5% said it was due to the influence from wealthy farmers. In addition few respondents (2.5%) explained lack of awareness on the importance of using inputs in agricultural production as the reason behind.
Table 4.25: Reasons for Selling Vouchers or/and Inputs to Agro Dealers or Wealthy Farmers Reasons Frequency Percentage (%) Existence of poverty among the smallholder 65 81.0 farmers. The influence from wealthy farmers. 13 16.5 Lack of awareness on the importance of using 2 2.5 inputs in agricultural production Total 80 100.0 Source: Field data, 2015
81 4.7 Other Challenges for Effective Accessibility and Utilization of Vouchers in
the Study Area
The interviewed smallholder farmers reported other challenges for effective accessibility and utilization vouchers in the study area are as indicated in Table 4.26 where61.2% of respondents reported shortage of plant chemicals for protecting plants against insects and fungi, the quantity distributed was not enough. Some smallholder farmers (22.5%) in the study area shared the cost for the input package and shared the inputs, this caused them to utilize below recommended rates, thereby do not attain technical efficiency in production. Other 16.2% pointed out that crop failure due to shortage of rainfall limit utilization of inputs in the study area.
Table 4.26: Other Challenges for Effective Accessibility and Utilization of Vouchers in the Study Area Problems Frequency Percentage (%) Plant chemical were not enough to sustain farms 49 61.2 Some smallholder farmers shared the cost for the input package 18 22.5 Crop failures due to shortage of rainfall 13 16.2 Total 80 100.0 Source: Field data, 2015
4.8 Smallholder Farmers’ Suggestions for the Input Vouchers to be Successful
Based on the challenges encountered during project implementation, smallholder farmers in the study area said that for the input vouchers to be successful in the next phases the following suggestions should be considered as shown in Table 4.27.
82 Table 4.27: Smallholder Farmers’ Suggestions for the Input Vouchers to be Successful Smallholder farmers’ suggestions Frequency Percentages (%) Timely delivery of vouchers 34 42.5 Lower the farmer’s level of contribution 21 26.3 Targeting criteria should be categorized such that smallholder farmers who are not able to 12 15.0 contribute the top up are provided with free voucher that covers the whole cost of inputs Close supervision during voucher distribution 5 6.3 Smallholder farmers to repay top up value after 4 5.0 harvest Regular contacts with extension officers 2 2.5 Availability of financial credit 1 1.2 Regular rehabilitation of rural roads 1 1.2 Total 80 100.0 Source: Field data, 2015
83 CHAPTER FIVE
SUMMARY, CONCLUSION AND RECOMMENDATIONS
5.1 Introduction
This study was carried out with the general objective of examining the role of input vouchers in improving agricultural productivity in smallholder farmers in Geita
District. It consists of specific objectives that aimed to; examine the extent usage of input vouchers to smallholder farmers in the study area, to investigate the effect of input vouchers on farmers’ efficiency in production in smallholder farmers in Geita
District and to identify the challenges for effective accessibility and utilization of input vouchers in Geita District. Also, this chapter summarizes findings, provides conclusion, recommendations and suggests areas for further research.
5.2 Summary of the Findings
The summary of the findings are based on the research objectives, where research objective one sought to examine the extent usage of input vouchers to smallholder farmers in the study area. It is evidenced from the discussion that 100% of the interviewed respondents were made aware about input vouchers through village meetings (45.0%), government extension officials (26.2%), agro-dealers (23.8%), mass media (2.5%) and from friends/neighbors (2.5%) as shown in Table 4.7. The findings of this study are consistent with a number of scholars including; Kelly et al.
(2003) and Malhotra (2013) who all demonstrated that awareness is the first, most crucial step in creating an effective demand for agricultural inputs and in speeding up input adoption.
84 The results revealed that 60% of the respondents in the study area have not been using improved inputs before input vouchers because of lack of knowledge on the use of improved inputs. In addition 27.5% of respondents reported that improved inputs were not easily available; consequently throughout the time they used their local varieties and relied on natural fertility. Moreover, it was found that 5% and
3.8% of respondents in the study area had not used improved inputs before input vouchers because of high costs and lack of capital respectively as indicated in Table
4.8.The researcher noted that the studies by Minot and Benson (2009), URT, (2009),
Druilhe and Hurle (2011) were all correlative studies and they had similar conclusions and so was this study.
Smallholder farmers in the study area applied either one 50kgs bag of DAP or two
50kg bags of MRP for planting fertilizers, one 50kg bag of urea for boosting fertilizer and 10kg of improved maize seeds (open pollinated variety or hybrid) for one acre. The Top up price for OPVs maize and hybrid maize seeds in planting season of 2009/2010 were higher than the subsidy price of 50% and hence, smallholder farmers contributed more than 50%. Nonetheless, in 2011/ 2012 the top up price of hybrid maize seeds dropped off to 50%, while OPVs maize seeds continued to be 60%.Regardless high contribution, the small scale farmers in study area were able to top up since 65% of them earned more than 250,000/= per year.
The study found that 83.8% of respondents’ main source of fund was selling agricultural products harvested in the previous season, 10.0% acquired fund from local money lenders. Other covered the remaining costs through selling livestocks
(3.8%) and providing labour in others’ farms (2.5%).
85 The results from field survey showed that 77.5% of respondents received input vouchers for three years consecutively, these were those managed to contribute the top up price for three years, while 13.8% received vouchers two times and 8.8% received vouchers only one time since some of the respondents were either failed to contribute and for this reason were excluded from the program or were those added when the program had already started.
The research findings indicate that the introduction of input vouchers in the villages surveyed contributed to the usage of quality inputs (87.0%), these inputs are fertilizer, maize seeds such as hybrid and OPVs, paddy seeds and pesticides.
However, 13.0% of smallholder farmers reported dissatisfaction with MRP fertilizer since its impact appeared in the next cropping season.
The objective two was to investigate the effect of input vouchers on farmers’ efficiency in production in smallholder farmers in Geita District. The study discovered that the average maize yield of input voucher users after input vouchers is 1700kg/ha while before input vouchers it was only 480kg/ha. Productivity in paddy increased too, whereby the average paddy yield of input voucher users after is
4300kg/ha while before vouchers, it was 960kg/ha. The results are also in line with
URT (2014) argument that farmers receiving subsidized maize seeds, rice seeds and fertilizer increased their maize yields per acre, but at average of 433 kg of maize per acre and 263 kg of rice per acre.
The last objective identified the challenges for effective accessibility and utilization of input vouchers in Geita District. The data from survey revealed that input
86 vouchers improved agricultural productivity among the smallholder farmers, nevertheless the vouchers encountered numerous number of challenges which hindered effective accessibility and utilization, most of smallholder farmers (83.8%) in the study area lack contact with extension officers. Only few number of smallholder farmers (16.2%) in all surveyed area observed close contact with extension officers. The majority of smallholder farmers in Nyakamwaga village observed close contact with extension officers as indicated in Table 4.21.
Smallholder farmers in the study area lack accessibility to sources of credit, hence are unable to top up the subsidy price as well as to purchase improved inputs since most of them (61.3%) lack of knowledge on financial institutions, whilst smallholder farmers (22.6%) fear weather uncertainity that often leads to crop failure. Other restrictions are lack of collateral requirements (8.6%), nearly all of financial institutions are located in large urban centres (6.5%) and high interest rate
(1.1%).
Distribution of seeds and fertilizer on time to targeted households was too challenging. Timely delivery of inputs was a major setback across surveyed villages.
In many villages smallholder farmers got input one month after the start of the season, especially in 2009/2010 cropping season when vouchers were delivered in
November. However, late delivery was caused by late government budgetary arrangement (56.0%) and MAFC did not prepare vouchers for future use (44.0%).
Moreover, the results from field survey indicate that local officers colluded with
VVC to jeopardize the vouchers to accumulate person wealth (46.7%), local leaders
87 sought to gain political popularity (40.3%) and VVC lacked allowances for their government responsibility (13.0%).
It was further found that some of the smallholder farmers in the study area sold vouchers back to the agro-dealers at cheap prices, likewise smallholder farmers sold inputs received via vouchers to other wealthy farmers at low-priced because of existence of poverty among the smallholder farmers (81.0%), the influence from wealthy farmers (16.5%) and lack of awareness on the importance of using inputs in agricultural production (2.5%).
5.3 Conclusion
The findings in this study have shown that input vouchers are helpful to smallholder farmers in the study area, since most of them lack economic stability. Input vouchers enabled smallholder farmers to access improved agricultural inputs closer to the village or ward agro-dealers at subsidized prices as compared with the situation before input vouchers. The beneficiaries appreciated the benefits of using fertilizer, improved maize, paddy seeds and pesticides as well. On the other hand, input vouchers had raised awareness of using improved vouchers among the smallholder farmers; this means that some smallholder farmers are purchasing inputs even after graduating from the programme.
Input vouchers had contributed to the improvement in farmers’ efficiency in terms of increased land units for cultivation owing to the availability of improved inputs, the productivity of maize and rice per acre has risen, this concludes that input
88 vouchers in the study area have positive significance since to some extent smallholder farmers were involved in the programme.
The implementation of input vouchers was affected by the institutions and institutional arrangements which are policies and strategies, regulations and management. Institutional arrangements were not set in proper way; this created a loophole for the local authorities to jeopardize the vouchers for their own gains, delivering of inputs under vouchers to smallholder farmers in different villages were done without consideration of availability of extension officers, thus, smallholder farmers applied those improved inputs traditionally ending up with low or none productivity. Also, poor management of the government in arrangement of budget and ineffective of the MAFC in preparation and distribution of vouchers led to disadvantaged huge business since vouchers were late delivered to smallholder farmers, hence they have nothing do with these inputs under vouchers rather than using them to untargeted crops.
Furthermore, social cohesion in implementing input vouchers among the key actors lacked, as a result every group of actors worked independently. For example, farmers’ views such as preferable time for vouchers distribution was not considered by District Voucher Committee, Regional Voucher Committee and National
Voucher Steering Committee, the MAFC resulting into late delivery. Similarly, instant solutions on the complexity of MRP were not taken. The actors failed to collect and analyze production information of maize and rice as well as inputs utilization at the ward and village level. This was accelerated by the entire set up of
89 institutions based in Dar es Salaam with a vision of rectifying and understanding of actors motivations in rural areas of Tanzania.
5.4 Recommendations
In view of the findings in chapter four, the study recommends the following dealings to be taken into consideration for the input vouchers to have remarkable positive impact to the intended smallholder farmers. These include:
Farmers’ Recommendations
(i) The government should look for possibility of lowering farmers’ level of
contribution to the voucher value to be less than 50% because farmers are
resource poor by reviewing the subsidy exit strategies.
(ii) Programme awareness need to be raised to all smallholder farmers to enable
them understand their rights and disciplinary measures to undertake for
unfaithful leaders, this is due to presence of local leaders who jeopardize the
vouchers for their personal gains.
(iii) Training on the use of improved inputs should be strengthening to know type,
when and rate of application. The government should set enough budgets for
training farmers on the use of improved inputs through Farmer Field School in
every village by close supervision from the Agricultural Extension Officials.
Also the district through District Agricultural Development Plan (DADP)
should incorporate farmers’ training on improved technologies in the plan.
DADP will strength the farmer’ knowledge on quality seed production,
management and marketing systems.
90 Recommendations for the Central Government
(i) The government should deliver input vouchers to the district before the
beginning of rain season mainly in September to enable smallholder farmers to
make cultivation as early as possible. This can be achieved by re-scheduling
budgetary cycle from June to April so that the government can release funds
by July each year. By doing so the procurement processes could be shortened.
Also the government should find the possibility of printing vouchers for the
following year. Therefore, the adoption of this option will correct the problem
of late delivery of vouchers to the districts.
(ii) The government should monitor the supply chain of input vouchers from
MAFC to the beneficiaries in order to avoid corruption. This can be achieved
through controlling whole-sellers and local agro-dealers. The intervention will
lower top up costs and increase sustainable use of full inputs package.
Furthermore, Village Voucher Committee members should be given allowance
based on their responsibilities in order to avoid corruption. During the time of
voucher distribution they work normally twice per week.
(iii) Soil analysis should be conducted before the implementation of the project in
the next phase in order to determine the recommended type of fertilizers in
the study areas because farmers complained that the impact of MRP appeared
in the following cropping season.
(iv) The government should establish rural financial institutions to address
farmers’ credit needs on loan terms with low interest rate. These institutions
will catalyze credit delivery to smallholder farmers and thereby accelerating
agricultural growth.
(v) The government should make sure rural transportation and infrastructures are
improved to make them passable in all seasons in to make all smallholder
91 farmers accessible to improved inputs and output market and thereby
contributing to timely input delivery.
Recommendations for Local Government
(i) Smallholder farmers should be encouraged to form associations of crop
producers, which will help them to find market for their products at profitable
rate. Further, associations will allow them to access financial services from
financial institutions.
(ii) Local leaders should be trained on the criteria for voucher provision, as village
leaders do formulate their own regulations that makes some eligible headed
households to miss the voucher just because of political differences between
them and their community leaders.
5.5 Areas for Further Research
Basing on the research findings, the following areas are suggested for further research:
(i) Comparative study on the implication of input vouchers on agricultural
productivity based on voucher beneficiaries and non-beneficiaries as unit of
analysis should be done.
(ii) Assessment of the role of various institutions in agricultural input service
delivery.
(iii) Examination of the institutional framework for implementation of the input
voucher scheme.
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102 APPENDICES
Annex I: Questionnaire for Smallholder Farmers in the Study Area.
Village…………………………………………
Ward…………………………………………..
Division………………………………………..
Section A: Farmer’s Characteristics (Farmer’s Factors)
Please put a circle where necessary in the following questions below.
1. Sex of a respondent
1= Male
2=Female
2. Age of a respondent (years)…………………………………....
3. Highest level of education have you attained …………………
4. Marital status of a respondent
1= Single
2=Married
3= Divorced
4= Widowed
5= Separated
5. What is the total number of household members (active labor force)? ……………………
Section B: Socio-economic Factors
6. What is the main economic activity of the household? ......
103 7. What type of crop are you growing at your household?
S/No Food crops S/No Cash crops 1. 1. 2. 2. 3. 3. 4. 4. 5. 5. 6. 6. 7. 7.
8. What is the main reason that prompted you to engage in agricultural production?......
9. What are the sources of family income? …………………………………………………..
(Rank them in order)
10. What amount of money you earn annually from your income sources?
1= Below 50,000/=
2=50,000/=-90,000/=
3=100,000/=-140,000/=
4= 150,000/= -190,000/=
5=200,000/=-240,000/=
6=Above 250,000/=
Section C: The role input vouchers in agricultural productivity
11. To what extent do you know about input vouchers?……………………………………
12. Where have you got information on input vouchers……………………………………
13. When did you get information about input vouchers?
1=2007/2008
2=2008/2009
3=2009/2010
104 4=2010/2011
5=2011/2012
6=2012/2013
7=2013/2014
8=2014/2015
14. When did you start utilizing input vouchers to obtain improved inputs?
1= 2007/2008
2=2008/2009
3=2009/2010
4=2010/2011
5=2011/2012
6=2012/2013
7=2013/2014
8=2014/2015
15. How many times have you received input vouchers at you household for the 5 past years?......
16. Where do you purchase/obtain input vouchers?......
17. How far do you travel to purchase input vouchers?...... ………………………….
18. How does the distance affect you in using inputs vouchers?......
19. How many shops of inputs are located within 5 kilometres from your household? …………......
20. How many kilogrammes/tones or litres of improved inputs do you receive at your household per year through input vouchers?......
21 Explain if the units of inputs you receive are adequate for your production………………………......
22.What is the top up price of inputs per kilogramme/litre?(Tshs)......
105 (Explain if top up price is affordable to a smallholder)………………………………….
23. What are the decisions do you take when top up price is unaffordable?
24. What type of extension services do you get and who are extension service providers?
……………………………………………………………………………………………...
25. How often do you get extension services from government officials? ……………….
……………………………………………………………………………………………
26. What extension services related to input vouchers do you most get from extension official?......
27. What is the contribution of input vouchers on the improvement of agricultural productivity in your household?......
28. How many times have you ever used credit to support your agricultural productivity and from which source of credit?
29. How frequent are you using credit to improve agricultural productivity?
30. How much money do you borrow from credit providers?......
31. What type of inputs you often purchase?......
32. What is the source of your money to top up on input vouchers?......
33. What size of land do you often cultivate (acre)?......
35. What are your yields per acre since you applied inputs under vouchers?
(i) Maize……………………………………………………………………………….
(ii) Rice……………………………………………………………………………….
36. What problems you are encountered related to input credit?
……………………………………………………………………………………………
37. What are your suggestions for efficient input credit service in the future?
……………………………………………………………………………………………
106 38. How does the market affect your produce?
……………………………………………………………………………………………
39. What are the main constraints regarding to market access of you produce?
……………………………………………………………………………………………
40. How do you evaluate the frequency of participation of stakeholders in delivering knowledge/information on input vouchers? (Indicate using V).
Name of stakeholders Frequency S/No Frequently Sometimes Rarely 1. Village Voucher Committee 2. Ward Voucher Committee 3. Agricultural Extension Officials 4. NGOs 5. Officers at Nzera/Nyamboge irrigation scheme 6. Service cooperatives 7. Others specify
107 Annex II: Questionnaire to Agricultural Extension Officers and Institutional
Representatives
Please assist me with the following particulars:
District…………………………………………….
Department………………………………………..
Designation……………………………………….
1. Sex of a respondent
1=Male
2=Female
2. Who are beneficiaries of input vouchers in your area?
……………………………………………………………………………………………
3. What are types of input vouchers supplied to smallholder farmers in the district/area?
……………………………………………………………………………………………
4. How many smallholder farmers are found in your district? ………………………………
5. How many smallholder farmers are benefiting from input vouchers in the district? …………………………………………………………………………………………….
6. How many input vouchers are been distributed to smallholder farmers per year in the district (Please mention)…………….……………………………………………………..
Of which value (Tshs)……………………………………………………………………………………
7. How are main suppliers of agricultural inputs in the district?......
8. Please fill the table below by indicating the quantity of input does a farmer receive, amount of money paid by the government and the top up done by a smallholder farmer per year.
108 Type of input voucher Quantity Subsidy (Tshs) T Farmer’s top up (Kg)/Littre (Tshs) 1.Fertilizer Urea DAP MRP 2.Maize seeds Hybrid Open-Pollinated 3.Rice seeds 4.Pesticides
Note: - DAP=Diammonium Phospates, MRP=Minjingu Rock Phosphate
9. How many kilogrammes/tones or litres of inputs a smallholder applies for an acre of maize and rice with a regard to topology of soil?
……………………………………………………………………………………………
10. What type of knowledge the smallholder farmers have on usage of input vouchers? ……………………………………………………………………………………………
11. How many seminars or workshops do smallholders have received/receive per year on usage of input vouchers?
……………………………………………………………………………………………
12. What are factors affecting the smallholders in usage of input vouchers?......
13. How do input vouchers improve smallholder farmers’ efficiency in production?
………………………………………………………………………………………..
14. What quantity(s) of yield does an acre produce when a smallholder farmer applies improved inputs in this area? (Please mention in kilogrammes or Tones for different crops cultivated in the district using input vouchers.)
………….…………………………………………………………………………………
15. What agricultural advanced technologies the smallholders have adopted in farming after the introduction of input vouchers?
……………………………………………………………………………………………
109 16. What is the agricultural productivity since the introduction of input vouchers in the district?
……………………………………………………………………………………………
17. How does the market influence agricultural productivity in the district? (Explain) ……………………………………………………………………………………………
18. What types of service cooperatives are available in the district? …….……………………
19.What services do the smallholder farmers get from service cooperatives?...... ……………...
20. How many smallholders receive loans from your SACCOS/Bank to develop agriculture per year?……………..………………………………………………………….
21. Whatis the impact of input vouchers on the development of related agricultural infrastructures?......
22. What is the trend of agricultural production in maize and rice for last 3-5 years before the introduction of input vouchers?
S/No Type of crop Tones 2002 2003 2004 2005 2006 1. Maize 2. Rice 3. Other crops
23. What is the trend of production of maize and rice in a district for last 3-5 years after application of improved inputs through input vouchers?
S/No Type of crop Tones 2009 2010 2011 2012 2013 1. Maize 2. Rice 3. Other crops
24. Do input vouchers have influenced the adoption of other advanced agricultural technologies in smallholders in the district?
25. How do you evaluate your user satisfaction? (Put V mark in the most appropriate).
110 S/No Type of service delivered Level of user satisfaction Very Good Good Fair Bad 1. Input voucher supply 2. Credit provision 3. Knowledge transfer 4. Other specify
26. What are shortcomings encountered by the smallholder farmers in accessing and utilizinginput vouchers in the district? (Explain)
……………………………………………………………………………………………
Thank you for your time.
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