Linking Smallholder Farmers to Markets

Linking Smallholder Farmers to Markets Impact of the Purchase for Progress Pilot Programme

Linking Smallholder Farmers to Markets Impact of the Purchase for Progress Pilot Programme

Edited by Wisdom Akpalu Innocent Matshe Lemma W Senbet

University of Nairobi Press

African Economic Research Consortium

First published 2017 by University of Nairobi Press (UONP) Jomo Kenyatta Memorial Library University of Nairobi P.O. Box 30197 – 00100 Nairobi E-mail: [email protected] Website://:uonpress.uonbi.ac.ke © The University of Nairobi Press, and African Economic Research Consortium, 2017

The moral rights of the authors have been asserted. The University of Nairobi Press supports and promotes the University of Nairobi’s objectives of discovery, dissemination and preservation of knowledge, and stimulation of intellectual and cultural life by publishing works of the highest quality in association with partners in different parts of the world. In doing so, it adheres to the University’s tradition of excellence, innovation and scholarship. All rights reserved. Except for the quotation of fully acknowledged short passages for the purposes of criticism, review, research or teaching, no part of this publication may be reproduced, stored in any retrieval system, or transmitted in any form or means without a prior written permission from the University of Nairobi Press. University of Nairobi Library CIP Data

HD 1476 .A3L56

Linking smallholder farmers to markets:impact of the purchase for progress pilot programme/ed. by W. Akpalu, I. Matshe, and L.W. Senbet. – Nairobi: University of Nairobi Press, 2017 186p 1. Farms, Small – Government policy – Africa 2. Farmers’ markets – Africa 3. Agriculture – Economic aspects – Africa i. Akpalu, Wisdom ii. Matshe, Innocent iii. Senbet, Lemma W. iv. Title

ISBN 10: 9966 792 67 8 ISBN 13: 978 9966 792 67 9

Contents List of Tables ............................................................................... viii List of Figures ................................................................................ ix Preface.......................................................................................... xi Contributors ................................................................................. xv About the Editor.......................................................................... xvi About the African Economic Research Consortium .....................xviii

1.

Effects of Large-scale Procurement on Smallholders: An Overview ....................................................................... 1 Wisdom Akpalu, Innocent Matshe, Lemma W Senbet ........................................... 1

Introduction ................................................................................... 1 Objectives of this Volume ............................................................... 6 Constraints Faced by Smallholder Farmers in Accessing Markets .... 7 Key Highlights of the Four Chapters .............................................. 10 Concluding Note........................................................................... 12 References ................................................................................... 14

2.

Return to Investment in Agricultural Cooperatives: Evidence from a Natural Experiment ........................ 15 Dambala Gelo, Edwin Muchapondwa and Abebe Shimeles ................................ 15

Abstract ....................................................................................... 15 Introduction ................................................................................. 17 Motivation and Research Questions ............................................. 22

LINKING SMALLHOLDER FARMERS TO MARKETS

Econometrics ............................................................................... 24 Data and Descriptive Statistics...................................................... 26 Results and Discussion ................................................................. 28 Conclusion ................................................................................... 35 References ................................................................................... 38

3.

Access to Markets, Food Security and Poverty in Ghana: Evidence from Smallholder Farmers ......................... 41 Jacob Novignon, Raymond Boadi Frempong and Clifford Afoakwah ................... 41

Abstract ....................................................................................... 41 Introduction ................................................................................. 43 Literature review.......................................................................... 44 Methodology ............................................................................... 49 Results and Discussion ................................................................. 54 Summary and Conclusions............................................................ 63 References ................................................................................... 65 Appendices .................................................................................. 68

4.

Linking smallholder farmers to markets: Evidence from WFP Purchase for Progress Programme in Tanzania ...................................................................... 73 Afaf Rahim and Precious Zikhali ........................................................................ 73

Abstract ....................................................................................... 73 Introduction ................................................................................. 75 Smallholder Farmers Market Participation and Collective Action .. 79 Farming in Tanzania and the WFP/P4P Market Intervention ......... 81 Methods ...................................................................................... 86

[ vi ]

Contents

Results and Discussion ................................................................. 95 Conclusion and Policy Implications ............................................. 102 References ................................................................................. 106

5.

Demand Driven Smallholder Market Participation through WFP Purchase for Progress Capacity Building: Evidence from Mali ...................................................117 Sènakpon Fidèle Dedehouanou....................................................................... 117

Abstract ..................................................................................... 117 Introduction ............................................................................... 119 Data Collection ........................................................................... 122 Descriptive Statistics of P4P Farmers in Mali............................... 124 Treatment and Outcome Variables ............................................. 134 Methodology for Analysing Impact of P4P Capacity Building....... 139 Results and Discussion ............................................................... 144 Conclusion ................................................................................. 157 References ................................................................................. 159 Annexes ..................................................................................... 161

Index ..................................................................................167

[ vii ]


List of Tables Table 2.1: Baseline comparison of P4P participants and non-participants (2009) ........................................................................................... 28 Table 2.2: DID estimates of P4P effects on selected intermediary outcomes ...................................................................................... 31 Table 2.3: DID estimates of average treatment of P4P on welfare .................. 33 Table 2.4: DID estimates quantile treatment effect of P4P intervention on welfare ..................................................................................... 35 Table 3.1: Samples for Matching .................................................................... 56 Table 3.2: Estimates for 2013 follow period, total sample .............................. 57 Table 3.3: Estimates for 2015 follow period, total sample .............................. 57 Table 3.4: Estimates for 2013 follow-up, Ashanti region ................................. 58 Table 3.5: Estimates for 2015 follow period, Ashanti region ........................... 59 Table 3.6: D.I.D Estimates of the Impact of P4P Participation on Household Domestic Expenditure .................................................. 62 Appendix 3.1: Summary statistics for multi-dimensional poverty indicators ...................................................................................... 68 Appendix 3.2: Description of survey ............................................................... 70 Appendix 3.3: Baseline comparison of the characteristics P4P participants and non-participants at baseline survey (2011) ........... 71 Table 4.1: Summary statistics....................................................................... 112 Table 4.2: Summary statistics by size of landholdings ................................... 114 Table 4.3: Determinants of market participation levels ................................ 115 Table 5.1: Constraints farmers faced in selling selected crops (baseline survey, 2009)............................................................................... 125 Table 5.2: Problems farmer organisations face selling staple food commodities on behalf of their members (baseline survey, 2009)........................................................................................... 128 Table 5.3: Access (use of) to agricultural support services by smallholder farmers ....................................................................................... 130 Table 5.4: Panel P4P participant household characteristics........................... 133

[ viii ]

Contents

Table 5.5: Distribution of panel P4P farmers by group of support services used (final survey, 2013) .............................................................. 135 Table 5.6: Average proportion of commodities sold by panel P4P farmers (final survey, 2013) .......................................................... 138 Table 5.7: Average treatment effects on the percentage of harvested commodities sold, 2013 ............................................................... 145 Table 5.8: Average treatment effects in different marketing channels, 2013 ............................................................................................ 149 Table 5.9: Multivalued treatment effects results........................................... 151 Table 5.10: Average treatment effects of cumulative use of agriculture support services ........................................................................... 154 Table 5.11: Average treatment effects of being a P4P farmer and using any capacity building intervention service, on farmers market participation ................................................................................ 156 Table A1: Providers of agricultural support services for P4P smallholder farmers (Final survey, 2013) ......................................................... 161 Table A2: Providers of agricultural support services for P4P farmer organisations ............................................................................... 162 Table A3: Covariates used in the econometrics analysis ................................ 164

List of Figures Figure 3.1: The impact of P4P on Household Food Consumption Score ........... 55 Figure 3.2: The impact of P4P on Household Non-agricultural Expenditure ................................................................................... 55 Figure 4.1: The conceptual framework for market participation ...................... 88 Figure 4.2: Maize total marketing cost (in Tanzanian shillings) by region and by P4P status ........................................................................... 97 Figure 4.3: Count of P4P beneficiaries by gender and by region ...................... 97 Figure 4.4: Land owned (in ha) by region and by P4P status ............................ 98 Figure 4.5: Quantity of maize sold by region and by P4P status ....................... 98 Figure 5.1: Post-harvest activities undertaken for selected crops by P4P and non-P4P farmers (baseline survey, 2009) ............................... 129 [ ix ]

Preface The mission of African Economic Research Consortium (AERC) is to strengthen local capacity for conducting independent, rigorous inquiry into the problems facing economies in sub-Saharan Africa, and to promote evidence-based policy making in the continent. In furtherance of this mission, AERC collaborates with a range of partners to carry out research that informs economic policy-making in Africa. In this particular work, AERC has collaborated with the World Food Programme of the United Nations to better understand the effects of purchasing staples from smallholder farmers. This effort falls into the category of special projects within AERC’s portfolio of programmes. It is a requirement that such projects are not only in line with the research and capacity building mandate of the network, but also serve to advance the interest of development partners that have a keen interest in sustained African development This volume is in line with AERC’s mandate of contributing towards providing research evidence for policy making. AERC publishes technical research papers in special volumes, such as this, with the intention of reaching out to a wide audience with interest in the region’s development. This audience includes African policy makers, African and Africanist researchers and the international development community. We are pleased that the World Food Programme has partnered with AERC in its efforts to realize its basic goals of (a) providing timely and quality policy relevant information to the African and global policy-making communities, (b) developing the capacity of African economists and other actors (researchers, policy makers, students, etc.) and (c) contributing to global knowledge. This special volume features four AERC research papers on the theme: Linking Smallholder Farmers to Markets: Impact of the Purchase for


Progress Pilot Programme. The research is based on the monitoring and evaluation data that was collected by country offices over the course of the P4P pilot programme that was implemented in 20 countries in Africa, Asia and Latin America. It would be useful to put this knowledge generation in the context of recent Africa’s growth trajectory. Africa is growing, but the growth has not been sufficiently inclusive. For some countries, there is a co-existence of high growth and rising inequality and/or poverty, posing serious challenges for policy makers. For growth in Africa, particularly sub-Saharan Africa, to be inclusive and sustainable, there is a need to develop and increase the involvement of smallholder farmers in the wider economy. Smallholder farming is the largest contributor to household food security and nutrition needs of this population. Thus, agriculture is central to improving food security and poverty reduction in Africa. However, these farmers face imperfect markets and high transaction costs that significantly reduce their incentives for market participation and these supply side constraints detract from their productivity. The theme of smallholder farmer development through local procurement or participation in markets is, therefore a timely and contemporary policy issue for Africa. Throughout the implementation of the P4P pilot programme, there was growing anecdotal evidence of the positive effect and importance of provision of assured markets to smallholder farmers and ancillary supply-side support. The papers in this volume take a more objective technical consideration of this impact to find ways in which positive effects could be harnessed for purposes of strengthening policy making and widening local procurement as a vehicle for smallholder market participation. Although the results are mixed, these papers show that there has been a general positive effect of participation in the market by smallholder farmers with complimentary support to the purchase of [ xii ]

Preface

staples by the supply-side partners of WFP, leading to lowered transactions costs and increased per capita household consumption. Moreover, the results indicate improvements in many welfare indicators and market participation, although the welfare gains are mostly experienced by wealthier households. The volume also highlights that there may be binding constraints to market participation, particularly for very small plot-holders, where addressing land size becomes more imperative than providing an assured market. Overall, this volume provides sound arguments that the P4P initiative has filled an important gap. It is, therefore, timely and should hopefully inspire policy debates on approaches to encourage market participation and hence development of smallholder farmers. AERC is grateful to all those who supported this project in one way or another, from inception to completion. The generous finding from United Nations World Food Programme’s (WFP) Purchase for Progress (P4P) pilot programme made it possible for the project to get underway and move smoothly to conclusion, this is greatly appreciated. AERC also appreciates the services of the volume coordinators Wassie Berhanu, Addis Ababa University, Ethiopia; Wisdom Akpalu, University of Ghana and Innocent Matshe, Director of Training, AERC, for reviewing the proposals and all of the draft papers for the volume. Also working with them at various times over the life of this project were Clare Mbizule, Imed Khanfir, Gianluca Guerrini and Paulo Dias. We also extend our appreciation to all the participants who attended the inception workshop. We acknowledge with thanks the Data support from Dennis Kinambuga and Emmanuel Adjei-Addo as well as Monitoring and Evaluation expertise from Yibeltal Fentie, WFP, P4P Ethiopia and John Sitor, WFP, P4P, Ghana. Special thanks are also due to AERC Staff members Dr. [ xiii ]


Charles Owino, Manager, Publications who was instrumental in tracking the various pieces together to produce the volume arising from the project and Dr. Mark Korir, Manager, Collaborative Master’s in Applied and Agricultural Economics (CMAAE) for keeping things on course. Finally, I would like to acknowledge with gratitude the involvement of the many researchers and policy makers who undertook the studies and practical shaping of the agenda. Their efforts contributed to both quality of the finished product on the one hand, and it’s utility to the policy community, on the other. Their work stands as a valuable reference to P4P across the continent. To all of you, and to the many others who were involved in this project in various way, AERC says thank you.

Lemma W. Senbet, Executive Director, African Economic Research Consortium (AERC)

[ xiv ]

Contributors Clifford Afoakwah, School of Commerce, University of South Australia, Adelaide, Australia. Sènakpon Fidèle Dedehouanou, Lecturer, Department of Economics, University of Abomey-Calavi, Benin Raymond Boadi Frempong, Bayreuth International Graduate School of African Studies. University of Bayreuth, Bayreuth, Germany. Dambala Gelo, Postdoctoral Fellow, School of Economics, Faculty of Commerce, University of Cape Town. South Africa Edwin Muchapondwa, Professor, School of Economics, Faculty of Commerce, University of Cape Town. South Africa Jacob Novignon, Professor, Department of Economics, Kwame Nkrumah University of Science and Technology, Ghana. Afaf Rahim, Researcher, Kiel Institute of World Economy Abebe Shimeles, Acting Director, Development Research Department (EDRE), African Development Bank (AfDB), Côte d’Ivoire, and Adjunct Associate Professor, School of Economics, University of Cape Town. South Africa Precious Zikhali, Poverty Economist, World Bank Pretoria office, South Africa.

About the Editors Dr. Wisdom Akpalu is a Research Fellow at the United Nations University World Institute for Development Economics Research (UNU-WIDER), performing research collaboration with the University of Ghana, Accra. He obtained his PhD degree in Economics from the Gothenburg University, Sweden. He has worked as Associate Professor of Economics at the State University of New York, Farmingdale, New York. His research interests are in Development economics, modelling microeconomic behavior, empirical econometric analysis, optimal extraction of natural resources, and economics of climate change. Dr. Innocent Matshe is the Director of Training Programmes, African Economic Research Consortium (AERC). Dr. Matshe joined AERC from the Human Sciences Research Council (HSRC) where he was a Senior Research Specialist. A former member of the AERC Collaborative Master’s Programme (CMAP) Academic Board, he is an economist with 17 years university teaching and research experience in Microeconomics, Agricultural and natural resources Economics, Development, Information, and Health Economics. Dr. Matshe is widely published in the areas of natural resources, health; markets, employment, household livelihoods and micro‐macro linkages.

About the Editors

Prof. Lemma W. Senbet is the Executive Director, AERC. As the William E. Mayer Chair, Professor of Finance and Director of the Centre for Financial Policy at the University of Maryland Robert H. Smith School of Business, USA, Prof. Senbet has been a major contributor to the transformation of the finance programmes at the University of Maryland and University of Wisconsin, Madison. Prof. Senbet is internationally recognized for his widely cited contributions to corporate and international finance. Prof. Senbet has done policy work and consulted for many institutions, such as the World Bank, the International Monetary Fund, the United Nations, African Development Bank, and several governmental and private agencies in Africa and beyond on issues relating to capital market development, financial sector reforms, banking regulation and financial crisis.

[ xvii ]

About the African Economic Research Consortium The African Economic Research Consortium (AERC) is a leader in policy-oriented economic research in the continent. The Consortium was established in 1988 as a public not-for-profit organization devoted to building capacity for economic policy research. This is carried out through two main programmes: research and training. In response to the special needs of the region, the AERC Research Programme uses a flexible approach to improve the skills of local researchers, allow for regional determination of research priorities, strengthen national institutions concerned with economic policy research, and facilitate closer ties between researchers and policy makers. The Training Programme augments the pool of economic researchers in sub-Saharan Africa by supporting collaborative graduate programmes in economics – at Master’s and PhD levels – as well as improving the capacities of departments of economics and agricultural and applied economics in public universities. AERC is supported by donor governments, private foundations and international organizations.

CHAPTER 1 Effects of Large-scale Procurement on Smallholders: An Overview Wisdom Akpalu, Innocent Matshe, Lemma W. Senbet

Introduction Currently, about 1.4 billion people, across the world, live in remote rural communities and are engaged in smallholder agriculture. This includes approximately three quarters of the world’s poorest people, whose food, income and overall livelihoods are closely tied to agriculture. These people also face imperfect markets and high transaction costs that significantly reduce their ability and incentive to participate in markets (Barrett et al., 2009). In fact, empirical research has identified poor market integration of smallholder farmers in Sub-Saharan Africa as a major impediment to higher productivity, greater specialization, and higher agricultural incomes (Lubungu et. al, 2013).


Increasing the incomes of smallholder farmers calls for transformation, out of the semi-subsistence, low-input, low-productivity farming systems that currently characterize much of rural Africa. To this end, boosting agricultural productivity and improving the market participation of small-scale farmers have been widely considered as among the most promising strategies for supporting poverty reduction, rural development, and agricultural transformation, particularly in those countries where agriculture is the dominant means of livelihood. With this in mind, the United Nations World Food Programme (WFP) piloted the Purchase for Progress (P4P) initiative with the aim of addressing some of these challenges. The P4P approach is based on three components: (1) providing consistent demand for quality food; (2) building the capacity of smallholders, typically through farmer collective action organizations; and (3) coordinating the support of supply chain services by key providers and development partners. This overview considers the effect of buying from smallholders thus encouraging the market participation of smallholder farmers in the context of P4P and synthesizes the key elements of four research papers seeking to establish the impact of the P4P initiative. The purchase of commodities in a country or region, in which it is to be distributed, commonly referred to as local and regional procurement (LRP), has been practiced for several decades now. At first, it was mainly to cover shortfalls or delays in international food aid, but over time, LRP has become a mainstream approach (Upton and Lentz, 2011). Market participation in food staples is particularly important, given that rural households staple foods account for a significantly larger share of household expenditures. Commercial prospects for these poor smallholders, however, remain at best, insignificant. This fact challenges the role of smallholder farmers as ‘important food producers and rural agents’ (Barret, 2009).

[2]

Effects of Large-scale Procurement on Smallholders

Recognising that promoting market participation by smallholder farmers is constrained by poor or lack of infrastructure, fragmented production units and the small-scale nature of farmers production, there has been a concerted effort by national governments and their development partners, at supporting the role of collective institutional arrangements, such as farmers’ organisations, Savings and Credit Organisations (SCOs) and co-operatives, as potential intervention points, to link farmers to agricultural markets. These arrangements reduce information asymmetries and costs of access by agricultural households to local markets as well as allowing members of these institutional arrangements to build market power and improve their participation in the markets. Quite notably, it is the concurrent heightened interests in global food security issues in the last 10-15 years, coupled with the recognition that food aid can contribute to development objectives, which led the United Nations’ World Food Programme (WFP) to develop the Purchase for Progress (P4P) pilot programme. The aim of the P4P was to provide a local guaranteed market for food staples, using local and regional purchases to help stimulate competition, linking farmer groups to markets, and supporting food marketing infrastructure in 20 countries in Africa, Asia and Central America. Rural smallholder farmers in developing countries are among the most vulnerable groups during crisis and emergencies, and hence they represent a large group of beneficiaries from food aid and development support. Therefore, providing them with a path out of dependence into sustainable livelihoods as they are being supported to deal with crises, can be achieved through non-disruptive development support, in this case, through the market. The idea of P4P was based on two important premises: one, that the United Nations World Food Programme (WFP) is the largest single buyer of food for distribution in emergencies and in development programmes, and two: that previous studies have found substantial cost and time savings for certain commodities and in certain [3]


areas when procurement is carried out locally compared to similar inkind food aid (Barret et al., 2010). Following the decision in 2008, by WFP’s Executive Board, to allow the organization to purchase food in local and regional markets while adhering to the programme’s strict quality standards, the P4P was initiated to strengthen and exploit linkages between WFP’s procurement practices and increasing access to markets for smallholder farmers. This encouraged smallholder farmers to develop their capacity and make the necessary adjustments to enable them (with the help of development partners) to meet the requisite WFP quality standards and participate in the market. The modality used by the P4P, was based on buying through collective institutional arrangements of smallholder farmers, instead of buying directly from individual smallholder farmers. In this case, the P4P purchased grains from farmer organizations (FOs) and Savings and Credit organizations (in countries like Tanzania, for example), from selected areas in the e different countries where marketable surpluses of grains were expected. The WFP pilot prioritized learning from this intervention, establishing not only the feasibility of buying from smallholder farmers from a logistic point of view, but also, the impact of such an intervention on the welfare of rural smallholder households and their farmer organizations. Through the P4P, WFP was keen to learn the efficacy of alternative ways of purchasing food and examining the impact of these purchases on market development, access to markets, and the welfare of smallholder/low income farmers. This knowledge should be of interest and relevance not only to WFP, but also to a variety of stakeholders, and particularly national governments and development partners. As part of monitoring and evaluation, the WFP country offices collected longitudinal data from participating smallholder members of farmer organizations as well as from similar smallholder farmers who were not [4]


members of the FOs selling to WFP. Given the nature of the intervention it was not possible to establish impact using experimental methods such as control trials. Therefore, the methods adopted by the monitoring and evaluation unit and its partners were quasi-experimental, with data gathered in intervals of two seasons over five years. This volume, thus, considers the impact of the Purchase for Progress pilot initiative from the perspective of WFP. The data used was extracted from the monitoring and evaluation of household surveys over the project period and differs, depending on the timing of the data collection process. The African Economic Research Consortium has been a technical partner in coordinating the P4P activities, particularly monitoring and evaluation, and knowledge generation associated with P4P. The 2015 AERC Senior Policy Seminar on smallholder agriculture, held in Maputo Mozambique, and conducted in partnership with WFP, was inspired by the lessons from the P4P. The follow-up AERC –WFP activities have now yielded this book volume. This volume and its overview bring together recent research on the impact of the P4P on the welfare of smallholder farmers in four countries: Ethiopia, Ghana, Mali and Tanzania and draws implications of the interventions, for development policies. Instead of considering the impacts in a broad sense, the studies narrow their attention to the challenges that smallholder farmers face in terms of their organizational capacity (in Mali), food security (in Ghana), market participation (in Tanzania) and consumption and transactions costs (in Ethiopia). In particular, the volume emphasizes, first, the potential benefits to smallholder farmers of market participation, the positive contributions of an assured market to alleviating some of the constraining factors that smallholder farmers face, and second, the impact of the intervention to the welfare of smallholder farmers. Particular attention is drawn to the

[5]


effectiveness of collective institutional arrangements and the need to strengthen and enhance capacities. The rest of the overview is structured as follows. Chapter 2 presents the objectives of the volume. In Chapter 3 we identify a range of constraints that smallholder farmers face in accessing markets and how the P4P programme contributed to addressing the constraints. The chapter also noted how the WFP is contributing towards linking smallholders to markets through P4P, as addressed in the four studies in this volume. Chapter 4 provides key highlights of the four papers in this volume and Chapter 5 is a conclusion and summary.

Objectives of this Volume As mentioned above, during the course of the implementation of the P4P pilot, the African Economic Research Consortium (AERC), was a technical partner to WFP and conducted a variety of activities including country-level data collection; cleaning, validation and analysis of data; and knowledge sharing which produced individual country impact assessment and other descriptive reports, based on qualitative data and observations. These were meant not only to provide information on the progress of the project and its effect but also, to disseminate these findings and guide programming. In line with the need to further understand the effect of the intervention by WFP, particularly on building the capacity of smallholder farmers’ organisations, household food security, market participation and its likely policy implications, this volume has three objectives. First, the volume explores the impact of the P4P project on smallholder farmers in four countries (Ghana, Ethiopia, Tanzania and Mali), as reflected by monitoring and evaluation data from specific areas of the countries where the P4P project was implemented. For all four countries, the papers explore specific aspects of the project and through technical [6]


analysis, move beyond simple descriptive observations on the impact of the project on smallholder productivity and welfare, to identify salient areas for policy interventions for the development of smallholder farmers and their organisations. Given that the farmer’s organisational structures, in the different countries are quite different, and that the specific impacts being explored are also different, these studies provide a unique (though not ultimately exhaustive) cross-section of the effects of the P4P. Second, this volume aims to draw attention to the possibilities or benefits of such local and regional procurement initiatives on the market participation of smallholder farmers. In particular, the studies highlight the impact on (a) collective institutional arrangements on market participation; (b) household welfare; (c) food security; and (d) transaction costs faced by smallholders. Third, the volume draws attention to the implications of the way forward for the programme.

Constraints Faced by Smallholder Farmers in Accessing Markets Smallholder farmers in the developing world continue to face a myriad of challenges, across all the production chains. In Africa, these constraints take various forms depending on the value chains in question. How to assuage their impact has preoccupied smallholder farmer development discourse for some time now. One of the strategies for dealing with some of these constraints and to drive resilient sustainable growth, embraced in the region involves harnessing the opportunities presented by the markets. Meaningful market engagement by smallholder farmers is fundamental to inclusive growth and development in Africa, given that the sector is the largest contributor to both employment and food, for the majority of African countries.

[7]


Farmers also face imperfect markets and high transaction costs that significantly reduce their ability and incentive to produce for the market. This curtails food security, greater specialisation and higher agricultural incomes. Increasing the incomes of smallholder farmers requires transformation out of the semi-subsistence, low-input, low-productivity farming systems that currently characterize much of rural Africa. To that end, improving market participation of small-scale farmers has widely been considered as among the most promising strategies for supporting poverty reduction, rural development, and agricultural transformation in such countries. However, the small size of production units, poor infrastructure, lack of capital, poor information networks, and wide geographic dispersion of smallholder farmers have led to high transactions costs, and access to and significant participation in markets has been relatively limited. Moreover, developing countries, especially in sub-Sahara Africa (SSA), generally have lower agricultural productivity compared to farmers in the developed and emerging world economies. For example, West Africa has the lowest average productivity at less than 20 percent of global average productivity. Furthermore, over the past four decades, the average productivity growth in SSA is about 2.4 percent compared to 4.0 percent for the rest of the developing world. The high and increasing yield gap can be attributed to resource constraints – e.g., water, nutrients and crop protection agents – and limited market access. It is not surprising that yield gaps have been found that strongly correlate with poverty gaps in SSA. Thus, easing the constraints, including the inadequate access to product markets, faced by smallholder farm households, could enhance agricultural productivity and address poverty concerns in developing countries. Moreover, it is well-established that imperfect competition

[8]


within markets and poor market integration stems from high transaction costs. To assist in addressing this and building on its experience with LRP, the World Food Programme’s P4P pilot programme aimed at providing a guaranteed market for food staples that meet pre-determined quality standards. The P4P procures produce from farmer organizations (FOs), which, in turn, aggregate the produce of their individual members. The specific countries involved were: Afghanistan in Asia; Burkina Faso, Democratic Republic of Congo, Ethiopia, Ghana, Kenya, Liberia, Malawi, Mali, Mozambique, Rwanda, Sierra Leone, South Sudan, Tanzania, Uganda and Zambia in Africa; and El Salvador, Guatemala, Honduras and Nicaragua in South America. In addition to providing demand-side interventions, WFP partnered with several organisations that provide the smallholder farmers with technical support, facilitate credit access, and provide storage facilities. WFP chose to experiment with buying directly from smallholder farmers in these countries so that the money would be injected into the economy, and directly to the smallholder farmers’ households. This would address issues of food security and low-production equilibrium associated with these areas. The project was also aimed at building the capacity of farmer organizations to enable them to participate in formal markets, and consequently, get better prices, and deliver better services to their members resulting in improved livelihoods. Rural markets, in most developing countries, are poorly organized and characterized by a litany of agents, inadequately coordinated collective action and poor infrastructure. Trading arrangements are mainly informal with inadequate market information access (Chiuri, 2013).In addition, although women are major players in these value chains, they are disadvantaged in many ways. Through the P4P, WFP was keen to learn about the effect of its demand for locally produced food staples, and to [9]


put into action its commitment to use its purchasing power to support agricultural and market development, and thereby stimulate increased productivity and market access for smallholder and low-income farmers.

Key Highlights of the Four Chapters The P4P project aimed at providing guaranteed markets for food staples that meet pre-determined quality standards. The P4P purchased produce from farmer organisations (FOs) that represent smallholder farmers, which in turn aggregated the food staples from individual farmers who are members of the FOs. The specific countries involved were: Afghanistan in Asia; Burkina Faso, Democratic Republic of Congo, Ethiopia, Ghana, Kenya, Liberia, Malawi, Mali, Mozambique, Rwanda, Sierra Leone, South Sudan, Tanzania, Uganda and Zambia in Africa; and El Salvador, Guatemala, Honduras and Nicaragua in South America. In addition to providing demand-side interventions, the WFP partnered with several organisations that provide smallholder farmers with technical support, facilitate their access to credit and provide storage facilities. This volume, however, is a collection of stand-alone papers that evaluate the impact of the project on selected welfare indicators, market participation, and transaction costs, in four of those countries, namely: Ethiopia, Ghana, Mali and Tanzania. Chapter 2 analyses the impact of the P4P intervention at FO level in Ethiopia, using a semi-parametric difference-in-difference (DID) model, to identify impacts. The aim of the chapter was to assess the impact of the P4P project on household consumption and transaction costs, which is a key determinant of market participation. The driving hypothesis is that investments in infrastructure, undertaken by the supply-side partners of WFP, has lowered transaction costs and increased per capita household consumption among the beneficiaries. The data, after controlling for differences in pre-treatment characteristics among the [ 10 ]


smallholder farmers who were selected to benefit from the project and those smallholder farmers not selected, and the attributes of the FOs, generally confirms this hypothesis. A disaggregated analysis indicates that only wealthier households experience the welfare gain. Furthermore, regarding farmer characteristics, households where both spouses participated in the programme benefited more, than those where only one spouse participated. However, male and female participants in the project benefitted similarly, suggesting the gender neutrality of the project, which is quite intriguing. In the Ghana case study in Chapter 3, in addition to the household consumption that was studied in Ethiopia, poverty and food security are considered additional welfare indicators. Thus, the authors investigate the impact of the project on these indicators and realise mixed results. While multi-dimensional poverty appeared to have declined mid-way through the project, this finding was not sustained. Surprisingly, the programme did not improve on any of the remaining indicators (consumption and food security). This calls into question the extent to which the findings from these case studies can be generalized, across the countries. Unlike the two preceding studies that look directly at welfare indicators, the study on Tanzania investigates the impact of the P4P initiative on market participation of smallholder famer beneficiaries with relatively small plots, compared to farmers with bigger plots. This study is motivated by the need to determine whether the land scarcity, confronting several smallholder farmers, is a barrier to market participation where market opportunities are provided. Contrary to expectations, the farmers who had smaller plots were less likely to participate in the markets, despite the P4P intervention. Thus, implementing demand side interventions among smallholder farmers, without the development and implementation of policies to ease land [ 11 ]


access constraints, may not yield the desired market participation outcomes. This implies that there may be a low threshold of land size that is suitable for market participation. The last chapter, on Mali, is devoted to: evaluating the impact of supply side interventions, e.g., agricultural support services such as postharvest, selling and productivity enhancement services, associated with the P4P initiative, on market participation. As was the case for Tanzania, this study compares the beneficiaries and non-beneficiaries of the capacity building activities among smallholder farmers who belong to the P4P initiative. The results indicate that the initiative significantly improved market participation, at the farm gate, among the farmers who benefitted from the capacity building activities.

Concluding Note The case studies presented in this volume, provide insights on the potential benefits associated with providing market access to smallholder farmers. Although the results are generally mixed, there are some improvements in many welfare indicators including market participation. Within the programme, demand- side interventions are combined with capacity building activities, enabling the volume to capture an interesting assessment of the respective effects. Since smallholder farmers face imperfect markets and high transaction costs, that in turn significantly reduce their incentives to participate in the markets, with supply side constraints that limit their productivity, the chapters have provided good grounds for concluding that the P4P initiative fills an important gap, or alternatively, that guaranteed markets for smallholder farmers can positively contribute to welfare gains and increased market engagement. It is, therefore, important to consider how to use the large purchasing power of national governments in order to drive smallholder farmer participation and improve welfare. [ 12 ]


It is also noted, from the Tanzania study, that there may be constraints to smallholder farmers’ participation in the market, stemming from suboptimal land sizes. The issue of land size thus needs to be addressed if we are to realize positive outcomes. Land policies, therefore, are among the key factors in unlocking value in this sector. This suggests that an initiative of this type can lift large populations out of deprivation and misery; given that positive impacts are noted for relatively larger sized farms, and that, a large number of farmers face land scarcity.

[ 13 ]


References Barret, C. B., et al., (2009). Market information and food insecurity response analysis. Food Security p151-168. Barrett, C. B. and D. Maxwell (2010). Food Aid After Fifty Years: Recasting its Role. London, Routledge. Chiuri W., (2013). Market access for agro-enterprise diversity in the Lake Kivu Pilot, Learning Site of the sub-Saharan Africa Challenge Programme. African Journal of Agricultural and Resource Economics, 8(2):120-134. Lubungu M., et al. (2013). Analysis of the soya bean value chain in Zambia’s Eastern Province. Working Paper 74 May 2013, Indaba Agricultural Policy Research Institute (IAPRI). Upton, J. and Lentz, E. C., (2011). “Expanding the Food Assistance Toolbox.” In C. B. Barrett, A. Binder, and J. Steets eds., Uniting on Food Assistance: The Case for Transatlantic Cooperation. Rutledge, London.

[ 14 ]

CHAPTER 2 Return to Investment in Agricultural Cooperatives: Evidence from a Natural Experiment Dambala Gelo, Edwin Muchapondwa and Abebe Shimeles

Abstract Agricultural commodity markets in the developing world often operate in a constrained environment of prohibitive transaction costs. Consequently, smallholder farmers are only partly integrated into these markets, a situation that has trapped them at a lower level of development equilibrium (poverty trap). Although cooperative institutional alternatives, such as farmers’ organizations (FOs), may be set up to reduce transaction costs and revitalize agricultural production and commercialization, these have been rarely successful in fully delivering on these promises. It is against this backdrop, that the World


Food Programme (WFP) recently implemented a five-year Purchase for Progress (P4P) pilot project in 20 countries, to increase smallholder farmers’ participation in commodity markets. The project involves, inter alia, investing in the physical and human capital (capacities) of FOs to aggregate commodities and add value. In this study we use survey data from Ethiopia in order to estimate the income and transaction cost effects of the P4P programme. We used a semi-parametric difference-indifference (DID) model to identify these effects. Our analysis indicates that the intervention has raised the per capita consumption and reduced the transaction cost of market participation among smallholders. Specifically, estimates of the treatment effect on per capita consumption from alternative specifications of our preferred model ranged between Ethiopian birr (ETB) 188.3 and ETB 248.6 (15.10 percent and 19.93 percent, respectively). Moreover, our analysis revealed heterogeneous treatment effects, pointing to potential elite capture within FOs. The policy implications of these analyses are discussed in this chapter.

[ 16 ]

Return to Investment in Agricultural Cooperatives

Introduction Agricultural commodity markets in the developing world often operate in a constrained environment of prohibitive transaction costs. These arise from the inadequate provision of public goods such as physical infrastructure (roads, electricity, and telecommunication networks) and institutional infrastructure (effective legal mechanisms to enforce contracts, standardization and certification services, and market information services) (Gabre-Madhin, 2001; Barrett, 2008; Francesconi and Heerink, 2010). Transaction costs related to searching, screening, and enforcement result in considerably limited smallholder participation in agricultural commodity markets (Tadesse and Shively, 2013). Transaction costs are also responsible for the poor integration of geographic markets, and imperfect competition within these markets (Gabre-Madhin, 2001; Barrett, 2008). These, in turn, constrain the participation of smallholder farmers in the market via price volatility, and higher mark-up by merchants with monopsony market power (De Janvry et al., 1991).Consequently, smallholder farmers, are bound to engage in subsistence or semi-subsistence agriculture and thus unable to benefit from market reforms. Barrett (2008) observes that subsistence production is often characterized by limited specialization and rudimentary technology, leading to low productivity and thus lower income. This situation has captured smallholder farmers, relegating them to the lower levels of equilibrium (poverty trap) across eastern and southern Africa. Public investment in physical and institutional infrastructure is expected to remedy the situation by reducing transaction costs and stimulating smallholder farmers to participate in the market, thereby raising net returns to agricultural production (Renkow et al., 2004; Barrett, 2008). [ 17 ]


One, such institutional alternative is to organize agricultural marketing cooperatives, known as farmers’ organizations (FOs).1 The FOs economize on transaction costs and develop countervailing power by vertically integrating their members into marketing chains, either upstream (through purchasing cooperatives) or downstream (through marketing cooperatives). 2 The FOs provides a special form of vertical integration which involves vertical and horizontal coordination. That is, agents coordinate horizontally (form a club) to accomplish vertical integration (Sexton, 1986). This suggests that cooperatives face governance costs and incentive structures, which differ from those of vertically integrated investor-owned firms. The FOs failed to fully deliver on their promises, however, despite the common expectation that they would revitalize agricultural production and commercialization (Bernard and Taffesse, 2012).3 The FOs face growing competition, and substantial investment and commitment are required to survive this competition. Many FOs, however, appear to be severely resource-constrained and there has been a decline in membership. Theoretical and empirical evidence from organizational economic literature confirms that the FOs often suffer from incentive problems. These include: the lack of clearly defined property rights 1

2

3

Recent years have witnessed a proliferating optimism among policy analysts and donors related to the ability of FOs to overcome smallholders’ marketing constraints (World Bank, 2003). Transaction costs for Ethiopian smallholder farmers relate mainly to information asymmetry of price and product quality. Compared to traders, smallholders have minimal information about central market prices for their products. They thus face either considerable costs in searching for better prices, or receive prices for their produce which are below market value (Tadesse and Shively, 2013). The FOs generate economies of scale and reduce these costs through raising selling prices by providing smallholder farmers with bargaining power. These serve to stimulate the gainful market participation of smallholder farmers. Policy analysts and donors have begun to promote FOs as natural avenues to stimulate agricultural commercialization. This is related to their role in reducing the transaction costs of accessing input and output markets. It is also based on FOs’ ability to increase the bargaining power of small farmers’ vis-à-vis large buyers or sellers.

[ 18 ]


assignments, management inefficiencies, and eroding incentives for members to invest in FOs resources (Cook, 1995; Cook and Iliopoulos, 2000).4 Normally, one would expect members of a cooperative to invest in their organization in order to earn residual income in the form of higher prices for their produce. If, however, an open membership policy is adopted and FO services are also freely accessible to non-members, free-riding on investing in FOs resources is the optimal strategy of each member, which traps FOs in an equilibrium of underinvestment. This problem is real among Ethiopian FOs because they follow an open membership policy, and provide services for non-members in their respective villages (Bernard and Taffesse, 2012).5 As a solution, donors (NGOs) or the Ethiopian government often finance the necessary investments to leverage FOs’ capacities.6 Recent interventions by the World Food Programme (WFP) through the Purchase for Progress (P4P) initiative is a case in point. Since 2009, the WFP has implemented a five-year Purchase for Progress (P4P) pilot 4

5

6

Major incentive problems of traditional cooperatives are: The free riding problem (gains from cooperative action can be accessed by individuals who do not fully invest in developing these gains), the horizon problem (residual claims that do not extend as far as the economic life of the underlying asset), the portfolio problem (the organization’s investment portfolio may not reflect the interests of any given member), the control problem (control of an FO’s management by the members), and influence costs (decisions affecting the wealth distribution among members) (Cook and Iliopoulos, 2000). Ethiopian FOs are engaged in a broad portfolio of service provision, including improved seed and fertilizer, credit, agricultural services, price information, consumption services, literacy training, HIV prevention services and public infrastructure for members and non-members (Bernard and Taffesse, 2012). While some of these activities complement the core commercialization activities of FOs others, such as consumption services and public goods provision, are unrelated to their primary purpose. External (donors’) commitment is unlikely to be sustainable. However, combining donor support with the establishment of well-defined property rights may make it possible for FOs to avoid serious resource constraints.

[ 19 ]


initiative in 20 countries, in an effort to bolster the capacity of FOs’ to connect smallholder farmers to formal agricultural commodity markets. The P4P intervention is two-pronged: First, it addresses the resource constraints of FOs by investing in their physical and human capital. For example, it provides FOs with skills development, including training in organization management, farming techniques, quality control, and postharvest handling. It also equips FOs with storage infrastructure.7 These interventions are expected to reduce FOs’ resource constraints and help aggregate commodities, add value (e.g., achieve the quality standards of the WFP and its partners, to fetch better prices), and help farmers identify and sustainably access markets (Krieger, 2014b; Erin and Upton, 2015). Second, at the upstream level (demand side), the P4P provides an additional source of demand, by purchasing food for aid locally from FOs.8 In Ethiopia, FOs are two-tiered. The first tier is a Cooperative Union (CU), which comprises its members, while Primary Cooperatives (PCs), is the second tier. The WFP uses CUs as entry points by targeting CUs for procurement and capacity building support. The CUs have the capacity to aggregate commodities which, along with the capacity stimulus provided at CU level, is expected to transmit improved capacity to smallholder farmer members of PCs (Krieger, 2014a). We evaluated the welfare and distributional impacts of this multi-faceted P4P intervention. Drawing on panel data analysis, we provide cogent causal evidence that smallholder farmer participation in the P4P 7

8

This is referred to as supply-side (downstream level) intervention and is expected to further reduce transaction costs for smallholder farmers who sell their produce through the FOs. The WFP purchase of local food for aid takes the form of direct contracts, forward delivery contracts, and “soft” competitive tenders, although this appears to vary across intervention countries (Erin and Upton, 2015).

[ 20 ]


programmes raises households’ per capita consumption.9 We also provide evidence of the heterogeneity of these effects across gender and income groups. To test for the distributional bias of the programme, we used the Ethiopian P4P dataset for the analysis. Our analysis confirms that the P4P raises per capita consumption by 15.10 to 19.93 percent. This supports the hypothesis that the return to the P4P intervention is positive. We also uncovered the revelation that the distribution is heterogeneous, but also appears to be biased toward FO management team members and non-poor smallholder farmers. Each P4P component, or a combination of the P4P components, appears to have significant implications for smallholder farmers’ welfare outcomes. Supply-side interventions obviously lift the FOs’ capacity to aggregate products through improved management efficiency. Moreover, establishing the storage infrastructure not only increases product aggregation, but also adds value through quality management and speculative storage.10 On the demand side, the P4P procurement bolsters market demand and raises commodity prices. Higher prices increase income directly, and also provide farmers with an incentive to invest in productivity-enhancing technologies and practices, which, in turn, yield additional income (quantity effect). Overall, the production of larger quantities and selling at higher prices will eventually increase household welfare.

9

10

These items include all food consumption; non-food consumption items were restricted to direct consumables (matches, soap, linen, and clothes), school and health expenditure, taxes, and extraordinary contributions. This refers to deferring current sales and instead keeping inventory until higher prices prevail. This is especially true if FOs considers market outlets other than P4P procurement and if intertemporal arbitrage trade exists because of supply fluctuations. In addition to training members in quality handling, P4P supplements warehouses with equipment to clean, dry, grade, weigh, and bag commodities to maintain quality (Lentz and Upton, 2015).

[ 21 ]


Although this hypothesis is intuitively straightforward, preliminary impact evaluation studies in three programme countries, Ethiopia, El Salvador, and Tanzania, indicate inconclusive evidence of the impact of P4P on household welfare. The Ethiopian study finds that programme households have realized a fall in income, compared to the incomes of non-participating households (Krieger, 2014b). However, the analysis uncovers an insignificant welfare effect of the P4P on programme households in El Salvador and Tanzania (Krieger, 2014a and Krieger, 2014c).

Motivation and Research Questions Our study was motivated by some major empirical gaps in the literature. First, although preliminary analysis by Krieger (2014b), Krieger (2014a) and Krieger (2014c) provide initial indications of programme impacts, there remain some key methodological questions. These studies employ a standard difference-in-differences (DID) estimator, which is based on a strong identification assumption of parallel trend. This assumption requires that, in the absence of the treatment, the outcome variable follow the same trend in both the treated and untreated groups. Unfortunately, this assumption may not hold if the pre-treatment characteristics that are correlated with the dynamics of the outcome variable are unbalanced, between the treated and control groups. This may happen, for example, if selection for treatment is influenced by individual-transitory shocks on past outcomes (Abadie, 2005). From our data, the P4P programme roll-out did not follow a random assignment mechanism at FO and smallholder farmer levels (Krieger, 2014b). Exposure of FOs and their members to the programme was rather driven by observed and unobserved heterogeneities. As some of these heterogeneities are time varying and drive the dynamics of outcome variables, and the implausibility of the parallel trend [ 22 ]


assumption, the evidence that emerged from preliminary P4P impact evaluation is likely to be biased. Second, besides the restrictions imposed by programme design and sampling, the preliminary analysis does not control for attributes of FOs that are likely to shape the P4P effects. In mapping out the causal mechanism of the P4P impacts, there is need to account for the institutional context of FO governance. Marketing cooperative organisations are often prone to incentive and governance problems. 11 First, cooperative governance structures are such that members, as formal owners of a cooperative, delegate control to management teams, and exercise ownership rights through voting and influencing activities (Cook, 1995). The divergence of interests of the members (principals) and the management teams (agents), in a cooperative organization, constitutes the agency problem in the governance of these organizations. Agency problems exist, to a certain degree, within any organization where there is separation of ownership and control. However, the absence of a market for exchanging equity shares, and the lack of equitybased management incentive mechanisms and formal boards of directors exacerbate this problem, in cooperatives (Cook, 1995). Specifically, the control rights of cooperative management teams provide the scope for patronage and rent seeking (elite capture) (Banerjee et al., 2001). In a developing country context, several mechanisms give rise to elite capture within cooperative organizations. These include using retained earnings and funds made available by donors, with cooperative organizations engaging in a broad range of investments, including capacity expansion 11

Additional incentive problems in traditional cooperatives are: the horizon problem (residual claims that do not extend as far as the economic life of the underlying asset), the portfolio problem (the organization’s investment portfolio may not reflect the interests of any given member), and influence costs (decisions affecting the wealth distribution among members) (Cook and Iliopoulos, 2000).

[ 23 ]


of the organization, training, and the provision of public goods. Using their information power on the quality and cost of these goods and services, the elite can capture rents by over-invoicing for goods and services purchased for the project, or by outright theft or fraud.12. It follows that elite capture undermines the success of cooperative organizations in the commercialization of products as it erodes members’ incentives and trust in investment of the organization’s resources. The empirical literature on marketing cooperatives, however, rarely confirms the existence and extent of these incentive problems.

Econometrics Our data presents two major econometric challenges. First, non-random assignment to the P4P means that there are differences in the distribution of pre-intervention observable and unobservable characteristics across treatment and control groups. The presence of such differences leads to biased estimates of the programme’s causal effects. More worrying, if FO and smallholder farmer characteristics are unbalanced across the programme and control groups, and differences are associated with the dynamics of the outcome variable, they affect the difference in the outcome’s time trends between the two groups. This leads to a violation of the parallel trend assumption, and results in biased impact evaluation estimates.

12

They may be guarded against censure for such malpractices through political connections, which serve as a source of favoritism. Caeyers and Dercon (2012) find that rural Ethiopian households that are vertically connected to those in power within the Kebele have a 12-percentage-point higher probability of obtaining food aid. Moreover, Bernard and Spielman (2009) find that poorer households in Ethiopia are less likely to participate in marketing FOs. The authors also uncover the fact that when poorer households do participate, they are often excluded from decisionmaking processes. This supports our findings that control and management rests with an elite group.

[ 24 ]


Second, the programme effect can be heterogeneous across individual characteristics or group characteristics. Thus, pre-treatment differences in observed characteristics can lead to non-parallel outcome dynamics (Abadie, 2005). In responding to these econometric challenges, we draw on a broader set of identification strategies within the difference-in-differences (DID) method in order to evaluate the welfare effect of the P4P intervention. As a baseline, we use standard two-period DID specification in Equation 1:

Yipt = a + gdt + lt + t (dt * t ) + m p + n ipt ........................................... (1) Where Yipt is per capita household consumption of smallholder i in FO p at time t and d t is a dummy for P4P programme participation by

smallholder farmers i in FO p and t is a time dummy for the postprogramme intervention period, m p is the FO’s fixed effect and n ipt is the random error. Our parameter of interest in (1) is t , which represents a difference-in-difference treatment effect estimate of the P4P programme. The identification of t relies on the untestable assumption of parallel trend, which implies that E n ipt dt * t = 0 . The lack of an

(

)

explicit test for this assumption, however, raises concerns about the acceptability of t as an exact programme effect. To overcome these challenges and thereby provide cogent causal evidence of the programme, we employed alternative identification strategies of DID that relax the parallel trend assumption. First, we follow a class of DID models that matches treatment and control groups by adjusting for pre-programme covariates (Abadie, 2005; Blundell et al., 2001; Heckman et al., 1997). Particularly, we apply a semiparametric estimator adopted by Abadie (2005). This estimator relaxes the parallel trend assumption of the conventional DID model, as it allows [ 25 ]


for the distribution of both observed and unobserved factors to differ between the treated and untreated (Abadie, 2005). It also allows for treatment effects to vary among individuals, a feature that helps us unpack the effect of the treatment by gender and FO size. We match treatment and control smallholder farmers on selected baseline covariates including, but not limited to: size of landholding, education, gender, access to alternative markets, FO’s initial capacity, and distance from FO to the WFP warehouse. Moreover, we extend Equation 1 to a quintile DID method to estimate the distribution of treatment effects, and provide a wider indication of the welfare effects of P4P interventions. The variation of treatment effect across the welfare distribution allows us to describe the pro-poor or antipoor bias of the P4P. These models allow us to ascertain whether the treatment effect variation arises from the presence of elite capture within the programme.

Data and Descriptive Statistics Our analysis uses the Ethiopian P4P Panel Survey data on P4P primary cooperatives (PCs) by member households and non-P4P PC member households. The Ethiopian WFP country office collected data drawn from selected sample P4P Cooperative Unions (CUs/FO), primary cooperatives (PCs) as well as smallholder farmers in 2009, 2011and 2013. The survey also collected data from a sample of non-P4P CUs, PCs and smallholders farmers.13 These surveys generated a panel dataset of data from randomly selected members of the surveyed PCs on initial and current capacities (managerial and marketing) of CUs and PCs, their respective size, marketing experience, location, services provided to

13

Note that we are using CUs and FOs interchangeably.

[ 26 ]


members, storage capacity, marketing activity, and credit utilization, among other things. At the household level, it generated data on household characteristics, including the age, gender and education level of the household head, production practices, marketing activity, credit utilization, and income from crops, livestock, and off-farm sources, and consumption. Our treatment variable is defined as smallholder farmers’ participation in 14 FOs/CUs participating in P4P. We use per capita household consumption expenditure as the outcome variable. In studies like ours, for several reasons, consumption is widely used instead of income (Skoufias and Katayama, 2010). First, consumption, rather than income, is commonly believed to provide better evidence of standard of living. Second, an income survey may not capture informal, in-kind, or seasonal income and, thus, may be more susceptible to under-reporting. Third, due to consumption smoothing, consumption expenditure exhibits fewer fluctuations than income, in the short run. Fourth, consumption expenditure provides information about the consumption bundle that fits within the household’s budget, although credit market access and household savings can affect household budgets. Our data analysis (Table 2.1) indicates that the household level baseline covariates are balanced, with the exception of household size. These include: gender, landholding, land allocation to maize production, transaction costs of maize marketing, and per capita consumption. The same evidence emerged at FO level for many of the capacity measures (access to long-term storage, access to tent storage). However, there is evidence of unbalanced distribution in terms of FO size, access to basic 14

Major intervention in the Ethiopian P4P case took the form of the WFP’s direct investment in increasing the storage capacity of CUs’, suggesting that increased access to storage can be interpreted as a major part of the P4P treatment.

[ 27 ]


storage (granaries), capacity for long-term storage across the treatment groups, which raise concerns about the selection bias discussed earlier. Table 2.1: Baseline comparison of P4P participants and non-participants (2009)

SE – in parentheses*** p4

Baseline % 9.21

Followup 1% 9.69

Followup 2% 3.91

0-1

79.34

74.71

76.33

2-3 >3

17.63 3.03

21.02 4.27

21.17 2.49

0

73.42

64.86

60.14

1-2 >2

23.82 2.76

30.21 4.93

33.10 6.76

0

94.34

92.61

89.50

1-2 >2

5.26 0.39

6.57 0.82

10.32 0.18

80.47

89.44

85.05

33.86

50.56

55.34

78.92

90.56

94.48

13.47

20.82

24.02

2.37

2.32

2.14

47.49

75.74

65.12

Durable goods Whether household has radio or not Whether household has TV or not Whether household has mobile phone or not Whether household has fridge or not Whether household has generator or not Whether household has backpack sprayers or not [ 69 ]


Whether household has tractors or not Whether household has car or not Whether household has stove or not Health Whether no household member fell sick during the farming season

Baseline %

Followup 1%

Followup 2%

1.71

4.18

1.78

19.53

36.57

40.04

3.83

8.35

9.96

93.95

94.75

85.77

Source: Authors’ own computation

Appendix 3.2: Description of survey Survey (Year)

Participants

Non-participants

Total

Baseline

369

391

760

Follow up 1 (2013)

299

309

608

Follow up 2 (2015)

272

290

562

[ 70 ]

Access to Markets, Food Security and Poverty in Ghana

Appendix 3.3: Baseline comparison of the characteristics P4P participants and non-participants at baseline survey (2011) Factor

Number of farmers in household Number of males in household Number of females in household Number of children Number of adults How many people are in your household? Wealth index based on PCA Total amount of land owned by HH Land area used for agriculture during the season Revenue from sale of livestock Total income from sale of crops Food consumption score Total household food expenditure in the last month Total household nonfood expenditure in the

Non P4P

P4P

pvalue

Mean

SD

Mean

SD

3.62

1.96

3.75

2.18

0.37

2.91

1.67

3.02

1.89

0.38

2.94

1.68

2.91

1.73

0.82

2.54

1.92

2.63

1.97

0.51

3.35

1.59

3.34

1.68

0.94

6.74

3.11

6.99

3.04

0.27

0.96

0.05

0.96

0.01

0.80

8.48

7.35

7.61

6.11

0.076

4.18

1.02

4.02

1.12

0.043

134.46

359.05

178.52

497.2

0.16

1501.6

1412.01

1653.4

1736.1

0.19

74.75

15.14

74.39

17.29

0.76 Z

113.81

108.43

107.32

74.49

0.34

776.66

823.32

773.15

827.9 9

0.95

[ 71 ]


Factor

Non P4P

P4P

pvalue

Mean

SD

Mean

SD

Freq.

%

Freq.

%

351

89.80

329

89.20

40

10.20

40

10.80

last month Sex of household head Male Female Urban/Rural Rural Urban Credit (Cash or goods) in the last 12 months No Yes Major material of the roof of the main house Thatch Iron sheets Tiles Major material of the floor of the main house Dirt/mud/sand Wood Concrete Asbestos Major material of the walls of the main house Concrete/fired brick Mud/mud brick Mud/wattle N

0.78

0.001 354

90.50

305

82.70

37

9.50

64

17.30 0.90

264

67.50

250

67.90

127

32.50

118

32.10 0.29

206

53.10

168

47.30

181

46.60

186

52.40

1

0.30

1

0.30 0.34

120

30.90

91

25.60

8

2.10

10

2.80

257

66.20

249

70.10

3

0.80

5

1.40 0.057

136

35.10

117

33.00

195

50.30

162

45.60

57

14.70

76

21.40

391

369

[ 72 ]

CHAPTER 4 Linking Smallholder Farmers to Markets: Evidence from WFP Purchase for Progress Programme in Tanzania Afaf Rahim and Precious Zikhali

Abstract This paper uses household survey data collected by the World Food Programme (WFP) in 2013, as part of its monitoring and evaluation system, to examine the differential impact of WFP Purchase for Progress (P4P) initiative on the participation of smallholder farmers in maize markets in Tanzania. The paper contributes to a broader understanding of the impact of collective institutional arrangements on market participation of smallholder farmers in sub-Saharan Africa. To capture the variations across smallholder farmers in terms of landholdings, we use a cut-off point of two hectares and split the smallholders’ group into two distinct subsamples: the first subsample consists of farm households that own more than two hectares of land, and the second is made up of


farm households owning two hectares, or less, of land. Three fractional logit models are estimated to identify determinants of market participation levels, proxied as the quantity of maize sold as a share of total maize marketable surplus. The first logit model uses the full sample, the second model uses the subsample of households owning more than two hectares of land, and the third model use the subsample of households owning two or less hectares of land. Results suggest that being a member of a P4P farmer organization is associated with enhanced maize market participation by households holding more than two hectares of land, while no statistically significant impact of WFP/P4P is found among the group of households that hold relatively less land. This result suggests that the WFP/P4P programme has differential impacts across farming groups having different land holdings. The result could suggest that the relatively land constrained households tend not to benefit from the increased market opportunities provided by the WFP/P4P programme. The result, therefore, underscores the importance of assets such as land in promoting commercialization among Tanzania smallholder farmers. This, together with the finding that marketing costs constrain market participation, points to the need for policy makers to provide systematic and sustained support for resource-constrained smallholder farmers in order for such households to participate in output markets. In addition, access to post-harvest handling services matters if smallholder farmers are to participate in the markets, and therefore initiatives to promote and enhance market participation of the smallholders should be incorporated into development policy and planning.

[ 74 ]

Linking Smallholder Farmers to Markets

Introduction Existing evidence suggests that the magnitude of domestic staple food markets is greater than that for exported high-value agricultural commodities in most sub-Saharan African countries (Hazell, 2005; Diao et al., 2007). This implies that domestic staple food markets have the potential to involve a much larger number of smallholder farmers than the other commodity markets. However, more than a third of rural subSaharan Africa is geographically and economically isolated from market towns and transport costs in these areas are notably higher than in other comparable areas of the world (Livingston et al., 2011). This is compounded by lack of supporting institutions or organisations that could improve the bargaining power of smallholder farmers and enable them to gain market power and interact on equal terms with other market intermediaries. Building up the marketing power of smallholders is particularly important when markets are spatially segmented and marketing costs are substantial and involve a significant fixed cost component leading, at times, to natural oligopsony or monopsony power (Barrett, 2008). The degree of smallholder farmers’ participation in the market is both a cause and consequence of development. Smallholder farmers face many constraints that impede them from exploiting the potential gains from market engagement and commercialization. Typically living in remotely connected areas, smallholder farmers face imperfect markets and high transaction costs that significantly reduce their incentives for market participation (Key et al., 2000; Barrett, 2008). Yet, evidence suggests that the commercialization of surplus output is closely linked to higher productivity, greater specialization and higher incomes (Timmer, 1997; Barrett, 2008). Increasing the incomes of smallholder farmers will require some form of transformation out of the semi-subsistence, lowinput, low-productivity farming systems that currently characterize much [ 75 ]


of rural Africa (Govereh et al., 1999). To that end, and for several decades, boosting agricultural productivity and improving market participation of small-scale farmers has been widely promoted as key strategies for poverty reduction, rural development, and agricultural transformation. Recently, collective action has been adopted as a potential substitute for state direct interventions in rural markets through, for example, marketing boards and public enterprises (Wiggins & Keats, 2013). Policy analysts advocate and support such innovative institutional arrangements arguing that, as the state disengages from the provision of inputs, extension services, credit, and price supports, private firms and producers’ association can play this role in a more efficient way, and ultimately improve smallholders’ access to services and markets (Wiggins & Keats, 2013). In principle, farmers’ organisations can achieve economies of scale and therefore allow smallholders farmers to economize on transaction costs. Farmers’ organisations reduce information asymmetries, and allow members to build up market power (Fischer & Qaim, 2012).18 It is against this background that many public institutions and international organisations are promoting farmer organisations, cooperatives and similar forms of collective action as mechanisms to overcome smallholder farmers’ production and marketing constraints (Bernard et al., 2008; Francesconi & Heerink, 2011). The central motivation of these interventions is to induce increased smallholders’ market participation, reduce the costs of households’ access to local markets, and increase market competition. One example of an institutional arrangement model orchestrated to link smallholders to markets is the World Food Programme’s (WFP) five–

18

In this paper, the terms Farmers’ Organisation and Farmers’ Group are used interchangeably.

[ 76 ]


year Purchase for Progress (P4P) initiative. Although principally a humanitarian organisation rather than a development one, the WFP realized the role that local and regional procurement of largely grains could play in stimulating market-oriented production or market participation for smallholder farmers. The WFP/P4P initiative aims to use local and regional purchases to help stimulate competition, link farmer groups to formal commodity markets and support food marketing infrastructure in 20 countries in Africa, Asia and Central America.19 The P4P procurement modality implies that WFP is committed to buying from selected farmers’ organisations (FOs). WFP’s procurement would then catalyze the activities of other partners working to strengthen FOs and improve farmers’ productivity and market participation. This paper uses data from the WFP/P4P 2013 household survey to examine the differential impact of the WFP/P4P programme on market participation of smallholder farmers in Tanzania. Market participation decisions, however, are contingent upon the ability and propensity to generate marketable surpluses. Improving smallholders' production capacity to achieve higher productivity and generate marketable surpluses will potentially improve market access opportunities. On the other hand, the availability of an assured buyer also provides smallholders with the opportunity to guarantee reliable and consistent market outlets for their crops. This is expected to provide farmers with an incentive to boost production and increase marketable surpluses and subsequently improve market participation. Focusing on maize, which is the main staple crop in Tanzania, and for the purpose of this paper, market participation is captured via a market participation index (MPI) – which is defined as the share of actual maize sales in total marketable 19

The 20 P4P pilot countries are: Afghanistan, Burkina Faso, Democratic Republic of Congo, El Salvador, Ethiopia, Ghana, Guatemala, Honduras, Kenya, Liberia, Malawi, Mali, Mozambique, Nicaragua, Rwanda, Sierra Leone, South Sudan, Tanzania, Uganda, and Zambia.

[ 77 ]


surplus. A fractional logit model proposed by Papke and Wooldridge (1996) is employed for the econometric analysis, to examine, conditional on the generation of marketable surplus, the impact that the WFP/P4P has on smallholders’ maize market participation. The fractional logit model is appropriate given that market participation levels are captured via a market participation index which is a bounded variable and defined as the quantity of maize sold as a proportion of total maize marketable surplus. To assess the differential effects of the WFP/P4P intervention on market participation across different landholding sizes, three fractional logit models are estimated: the first model using the full sample, the second model using a subsample of households that own more than two hectares of land (herein referred to as Group A), and the third model using a subsample of households owning two or less hectares of land (herein referred to as Group B). The result suggests that the relatively land constrained households tend not to benefit from the increased market opportunities provided by the WFP/P4P programme. This could be due to differences in initial conditions across these groups, which influence market participation levels. That is, large-scale farmers are likely to start off from an advantaged position in terms of leveraging on the opportunities that the programme presents. The result, therefore, underscores the importance of assets, such as land, in promoting commercialization among Tanzania smallholder farmers. It is, therefore, important for programmes such as the WFP/P4P to categorize and identify programme participants, based on the size of landholdings or other important assets, at the onset of the project design, in order to address differential needs and constraints. This, together with the findings that marketing costs constrain market participation, and that smallholder farmers must access post-harvest handling services, points to the need for policy makers to provide systematic and sustained support for resource constrained smallholder farmers, in order to encourage them to participate in output markets. This [ 78 ]


also suggests that access to services that reduce post-harvest losses such as training, storage facilities and warehouse receipt systems enhances smallholders’ market participation. The rest of this chapter is organised as follows. Section 2 discusses the theoretical and conceptual basis for the promotion of FOs and similar forms of collective action in smallholders' farming context. This is followed by an overview of smallholder farming in Tanzania and the WFP/P4P programme in Section 3. Section 4 describes the methodological approach and econometric model used in this chapter. A presentation and discussion of summary statistics and estimation results is done in Section 5. Section 6 is the conclusion of the chapter.

Smallholder Farmers Market Participation and Collective Action The population of sub-Saharan Africa remains disproportionately rural, with the overwhelming majority of residents growing staple food grains mostly in semi-subsistence rather than commercial settings. Empirical evidence suggests that a relatively small share of households sell food grains, and many of those who sell end up buying food grains at other times of the year to fill the consumption gap. Jayne et al. (2005) found that the top 2 percent of commercial farmers sold about 50 percent of observed marketed maize in Kenya, Mozambique, and Zambia. Ellis (2005) also reveals that farmers in semi-arid areas of Africa have very low proportions of their output marketed. While there is a general agreement that improving market access and commercialization of smallholder farmers will help induce greater investment, improve productivity, and income, there remain several challenges in achieving progress. This holds true for both agricultural input and output markets. Empirical evidence concerning smallholder staple food grains market participation has adopted different approaches to categorize these [ 79 ]


constraints. Barrett (2008) stresses the importance of distinguishing location level constraints that tend to influence participation at meso or community scale, from household level constraints, that influence participation across households, within a given location. Other scholars have differentiated between transactions costs, risks, and resources constraints (e.g., skills, land, and capital) which may all manifest themselves at a meso or household level (Poulton et al., 2004; Bijman et al., 2007). Nevertheless, many researchers agree that a key constraint to improving smallholder farmers’ market participation is the high transactions costs resulting from the prevailing weak institutional and physical infrastructure in the rural areas (Omamo, 1998; Key, et al., 2000; Barrett, 2008). Transaction cost economics (Williamson, 1985) provides the conceptual basis for explaining the role of smallholder FOs. Transaction costs are the observable and unobservable costs of market exchange. Key et al. (2000) distinguish between fixed and variable transaction costs. Fixed transaction costs include the costs of searching for a trading partner, negotiating a price and bargaining, and enforcing the market transaction. Variable transaction costs depend on the volumes traded and are related to the costs encountered in transporting the product to its destination. Smallholder farmers tend to experience higher transaction costs because they have higher unit costs of getting market information, implementing standards and certification, marketing as well as procuring inputs, obtaining credit and other financial services (Wiggins et al., 2010). Moreover, smallholder farmers are more vulnerable to opportunistic behavior and have weak market bargaining power. These problems are particularly severe in sub-Saharan Africa where institutions and physical infrastructure are often weak. FOs are a form of collective action, defined by Markelova et al. (2009) as

“voluntary action taken by a group of individuals, who invest time and [ 80 ]


money to pursue shared objectives”. They can be oriented toward improving production, marketing, or livelihoods in general, sometimes serving more than one purpose (Bernard et al., 2008). FOs and other forms of collective action are viable mechanisms to reduce transaction costs (Valentinov, 2007; Markelova et al., 2009). FOs can achieve scale economies and thus help farmers to reduce transaction costs and information asymmetries. Through FOs, farmers can build marketing and bargaining power and obtain favorable prices. In such situations, collective action is likely to improve market access for smallholders (Holloway et al., 2000; Rao & Qaim, 2011). There are, however, concerns regarding the sustainability of FOs, which are often conditioned on external support, for example by NGOs, government agencies, or private businesses. Moreover, the FOs induces transaction costs related to internal governance and incentive problems (Fischer & Qaim, 2012). Additionally, FOs have been successful for high-value crops, but there is little empirical evidence on their performance when it comes to food grains and other staples (Barrett, 2008).20 By focusing on marketing of maize, this study aims to contribute to filling this gap in existing literature.

Farming in Tanzania and the WFP/P4P Market Intervention Tanzania’s agriculture sector is dominated by small-scale subsistence farmers, who produce most of the country’s food and cash crops as well as livestock rearing. Maize is the most important cereal crop in Tanzania: it is produced by about 82 percent of all Tanzanian smallholder farmers (Petro, 2015) and consumed by 90 percent of the 20

One exception is Bernard et al. (2008), who find that smallholder farmers grain marketing cooperatives in Ethiopia, achieve higher prices.

[ 81 ]


population (National Bureau of Statistics (NBS), 2014). The crop occupies about 45 percent of the total arable land, and generates about 50 percent of rural cash income (USAID, 2010; FAO, 2012). However, maize productivity is low, with an average annual yield of 1.3 tons per hectare, far below the world average productivity of 4.3 tons per hectare (FAO, 2009; Urrasa, 2010). In addition, there are variations in productivity at the regional, district, and household levels that lead to localized surpluses and deficits. The poor infrastructure and inadequate market information in Tanzania has resulted in a low rate of commercialization, poor market integration, and hindered trading between surplus and deficit regions. The low rate of commercialization is a result of several constraining factors, including among others, remoteness, poor transport and communication infrastructure, low farm gate prices, insufficient market information, and limited access to finance. In Tanzania, poor transport, communication and market institution infrastructure impedes smallholder farmers from accessing markets as it results in high transaction costs as noted by Mbise et al. (2010) and Maziku et al. (2015). Both studies find that smallholder farmers in Tanzania sell mostly at the farm gate and have limited access to district and regional markets. In addition, organised farmer groups are poorly developed, and maize marketing takes place either at the household level or within the village market. Returns for the small producers are meager owing to high transaction costs and lack of bargaining power (Krieger, 2014). The foregoing discussion suggests that the formation of market linkages between organised smallholder farmer groups and other market chain actors lies at the heart of improving smallholder farmer returns. Building the capacity of FOs will, not only improve farmers’ bargaining power and help them to obtain higher prices for their produce, but it would also enable them to reach service providers who can supply them with the [ 82 ]


production, credit, and marketing services they require to improve their incomes. The importance of maize to the livelihoods of smallholder farmers in Tanzania implies that improving the production capacity of smallholder farmers to generate maize marketable surplus as well as their market participation is a potential pathway to improving smallholder farmers' livelihoods and reducing poverty. This study assesses the differential impact of WFP/P4P intervention on maize market participation of smallholder farmers. The WFP’s five-year Purchase for Progress (P4P) pilot initiative, strives, through local and regional procurement of grains, to link smallholder farmers to formal commodity markets. In Tanzania, the WFP/P4P programme covered 14 districts in ten regions, reaching nearly 19,000 smallholder farmers. WFP has supported 25 FOs and provided capacity development programmes to improve the ability of smallholder farmers to engage in collective marketing and reduce post-harvest losses. This included training and investments for rehabilitating storage facilities and to link them to warehouse receipt systems (WFP, 2013)21. As part of its monitoring and evaluation system, WFP collected longitudinal data for the treatment (members of a P4P FO) and control (members of a non-P4P FO) group at both the FO and individual household levels for 2009, 2011, and 2013, in Tanzania. The treatment group was made up of 321 households while the control group comprised 343 households. 22 The

21

22

WFP targeted Savings and Credit Cooperatives (SACCOs), which provide credit and savings accounts to, registered smallholders while simultaneously building the capacities of Agricultural Marketing Cooperatives (AMCOs). Data was also collected from farmers’ organisation, and in particular 50 Savings and Credit Cooperatives (SACCOs): 25 that participated in the P4P programme and 25 that did not participate. The information collected on Farmers' Organisations (SACCOs) include information on services that they offer to members including storage capacity, marketing activity, and credit utilization. Household surveys collected data and information on household characteristics as well as agricultural production patterns.

[ 83 ]


households were randomly selected. The surveys collected information on household characteristics as well as agricultural production patterns. At this stage it is important to discuss the term ‘smallholder farmer’, in the context of WFP programme and this study – particularly as there exists no precise or universally accepted definition for the term and the definition of smallholders varies across countries and agro-ecological zones (Narayanan & Gulati, 2002; Dixon et al., 2003). The notion smallholder of farmer is generally defined by common characteristics of the farmers in terms of assets holdings, level of technology used, exposure to risk, and market orientation (Chamberlin, 2008). The primary approach adopted in agricultural development programmes and literature is to define smallholder farmers in terms of average landholdings. The World Bank, for example, defines a smallholder as a farmer with less than two hectares of cropland and those that have a low asset base (World Bank, 2003). Similarly, the Food and Agriculture Organisation of the United Nations (FAO) adopted two-hectare threshold as a broad measure of smallholder (IFAD, 2013). In identifying smallholder farmers, the WFP (in most of the P4P pilot countries) has adopted the definition by the Bill and Melinda Gates Foundation of “smallholder is a farm household cultivating less than two hectares of land”. In the case of Tanzania, however, the farmers’ organisations’ (FOs) records did not contain data on the amount of land cultivated by farmers, and as such, all farmers registered in the P4P selected organisations, are in principle, eligible to participate in the project. The concept of a smallholder, under this circumstance becomes ambiguous, since there are disparities within registered members of the P4Psupported farmer organisation in terms of land asset holdings as well as

[ 84 ]


the amount of land cultivated during the programme period.23 Intuitively, the size of land owned is expected to have a positive effect on market participation level because smallholder farmers, who have large landholdings, can potentially cultivate more land and subsequently have higher market participation levels. For the purpose of this study, and in order to capture the variations across smallholder farmers in terms of landholdings, a cut-off point of two hectares is used to classify smallholder farmers into two distinct groups: Group A which is a subsample of households that own more than two hectares of land and Group B, a subsample of those owning two or less, hectares of land. In this regard, the term smallholder is relative and relates to the limited land resources of one group, relative to the other, within the sampling population. Assessing the impact of the P4P smallholder farmers’ development support in Tanzania will generate valuable insights, particularly as there is relatively limited evidence regarding smallholder farmer market participation in staple food grains in eastern and southern Africa (Barrett, 2008). There is also relatively little documented success of collective institutional arrangements, in particular farmer groups in linking smallholders to food grain markets.24 In contrast, there is evidence that farmer groups proved successful in generating better terms of trade for producer members in cash crops, more specifically, dairy and horticulture (Minot & Ngigi, 2004; Poulton et al., 2004; Nyoro & Ngugi, 2007).

23

24

This disparity is reflected in large standard deviation among the sampled population with regard to land owned and number of cattle owned by the household (see Table 1). One exception is Bernard et al. (2008), who find that smallholder grain marketing cooperatives in Ethiopia achieve higher prices, even though this has no significant effect on the overall level of commercialization.

[ 85 ]


Methods Conceptual framework The overall objective of the empirical analysis is to estimate the differential impact of the WFP/P4P market intervention on farmers' maize market participation. Market participation is, however, directly related to the generation of marketable surpluses, which in turn depends on productivity levels. Marketable surplus is a theoretical and ex-ante concept. It represents the surplus that the farmer has their disposal, once the main requirements of the farmer for family consumption, payment of wages (including payments in kind), feed, seed and wastage have been deducted from the total harvest of a given crop, in that particular year (Alagh, 2014). For the purpose of this chapter, we estimate marketable surplus by using the quantity retained for consumption rather than the objective consumption needs, which requires adding the quantity retained for consumption to the quantity purchased or obtained from other sources for consumption.25 Marketable surplus is therefore, calculated based on the following equation: Market surplus =Total maize harvest – quantity retained for consumption – quantity retained for seeds – quantity retained for feed – post harvest losses

Market participation is captured via an index, the market participation index (MPI), which is defined as the share of actual maize sales in total marketable surplus. In other words, it is a proportion that indicates what a household actually marketed to what it could potentially sell. That is, 25

For smallholder farmers, the quantity retained for consumption is often less than the quantity actually required for consumption. In some cases, smallholder farmers resort to distress selling in order to satisfy other household needs. In such cases, they need to buy back to fill the resulting consumption gap. Unfortunately, the dataset did not include information on maize purchase for consumption; therefore, this transaction is not included in the construction of marketable surplus.

[ 86 ]


MPI i =

ü = 0 nonseller Actual sale i .................................... (1) ý Marketable surplus i þ > 0 seller

Sales are based on the quantities of sales and not the monetary values. Estimating market participation in this way, considers that smallholder farmers are sometimes unable to sell their surplus because of market inaccessibility, poor quality, or because they are unable to meet the quantity and quality standard set by the WFP/P4P programme. This is important because a central element of the programme is to facilitate market access and build the capacity of smallholder farmers to reach out to quality-conscious buyers. Households with zero marketable surpluses, meaning that Equation 3 is not defined, are not included in the analysis. These are assumed to lack the potential to participate in the market. Several independent variables were selected in order to estimate the predicted values of the dependent variable (MPI). The choice of explanatory variables, used in the analysis, is largely based on Heltberg and Tarp (2002), Lapar et al. (2003) and Barret (2008), who extensively reviewed factors influencing farmers’ market participation. Figure 1 outlines the conceptual framework adopted in this chapter. It presents the key variables included in the analysis and indicates how they are interrelated. Both the decision to participate in maize market as well as the extent of participation (i.e., market participation level) are influenced by the WFP/P4P intervention, as well as several other factors operating at the household level, the farmers' organisations, and the overall institutional, climate and policy environment. It is important to understand that the present chapter is interested in analysing the market participation levels, which is a stage that precedes the decision to participate in maize markets.

[ 87 ]


Figure 4.1: The conceptual framework for market participation Market factors Price information, marketing costs, geographic location market Household characteristics Gender, age, education level, household size, land ownership, livestock ownership, other livelihood sources besides agriculture

Market participation decision

Market participation level

Institutional factors Membership in a WFP/P4P FO, access to post-harvest services, access to marketing services, access to transport, access to inputs

Choice of marketing outlets

Increased household income

Source: Authors’ own representation

Household characteristics Commercialization and market engagement of smallholder farmers, depends on two fundamental preconditions. First, that the markets exist to facilitate specialization and exchange, and second, that households have the capacity to engage with the markets (Barret, 2008). Therefore, linking smallholder farmers to the market can only be achieved if households have the means and incentives for such participation. Factors that include smallholder resource endowments, including land, livestock ownership and other assets holding, labor and human capital are household-specific and considered to be internal determinants of market participation. [ 88 ]


Formal education captures human capital and management skills; it is, therefore, expected to be positively correlated with market participation levels. Similarly, the age of the household head can be viewed as a proxy for experience in maize market participation, and is thus, expected to be positively correlated with market participation levels. The impact of household size in the context of the present analysis is ambiguous. This is because, although bigger household size could place pressure on the household to provide food for the household members, thus reducing the probability of having a surplus26, a bigger household size could mean increased labor for the production of more maize, thereby increasing the household’s marketable surplus and subsequently, the market participation levels. Empirical research has indicated that male-headed households tend to have better access to agricultural technologies, implying that they experience higher productivity and subsequently increased production levels (see, for example, Mathenge et al., 2010). Moreover, women are often excluded from provisions of agricultural services such as credit and agricultural extension services (Farinde & Taiwo, 2003). Based on this, the gender of the household head is expected to influence the level of market participation, with male-headed households expected to participate more in maize markets relative to those headed by females. Barret (2008), studying market participation in staple grains, found that the barriers to participation in markets by smallholder farmers were mainly: land, livestock, capital and improved technologies (like farm equipment) needed to generate a surplus that influences market participation. Pravakar et al. (2010) found that households with larger land holdings, per adult member, sold larger volumes of their produce as 26

Lapar et al. (2003) hypothesized that the propensity of smallholder farmers to participate in to the market declines with the household members.

[ 89 ]


compared to those with smaller landholdings. The size of land owned is, therefore, expected to have a positive effect on market participation. Pravakar, et al (2010) also found that households with larger livestock endowments produced and sold more crops, the reason given is that the households used manure from the livestock to enhance crop yields. However, Jaleta (2009) pointed out that ownership of livestock by a household negatively affected its participation in the crop market because it distracts the farmer from farming, into looking for an alternative source of income. Livestock ownership could, therefore, be viewed as either complementary to or competing with maize production and marketing. The effect of having alternative sources of livelihood is indeterminate: on one hand, households that have other sources of livelihood are expected to participate less in maize markets because for these households, agriculture competes with other forms of livelihood. On the other hand, depending on the productivity of these alternative sources of livelihood, households could buy maize productivity enhancing inputs (e.g., improved seed and fertilizer) that lead to increased surplus and therefore increase market participation levels.

Market factors Market factors included in this chapter, are the cost of marketing, access to price information, as well as a regional dummy to capture geographical variation in terms of market conditions. Market participation levels are expected to be negatively correlated with costs of marketing (Barrett, 2008; Sebatta et al., 2014). Enete and Igbokwe (2009) found that price had an important influence on the level of farmers’ market participation in cassava markets as supported by the economic theory that price induces increased supply. In a related study, Omiti et al. (2009) also asserted that better output price and market information were key incentives for increased market participation. In order to measure access to price information, we constructed a score [ 90 ]


variable of the number of sources that a household has for its price information.

Institutional factors Institutional factors play an important role in market participation. Membership in a WFP/P4P FO is expected to reduce transaction costs and is, therefore, expected to be positively correlated with participation levels. Phiri and Otieno (2008) suggest that in most southern African countries, agricultural produce is lost soon after production largely because of poor post-harvest handling and lack of access to formal markets. In sub-Saharan Africa, on-farm storage facilities are mostly either not available or poorly constructed, and as such, are inadequate protection against insects and pests, resulting in huge post-harvest loss. 27 Insufficient on-farm storage solutions lead farmers to sell, immediately after harvest, where they receive lower prices because the market is flooded with grain. For example, Stephens and Barrett (2006), studying smallholder farmers in western Kenya, find that of the nearly 30 percent sample of net maize sellers in the harvest period, 62 percent were net maize buyers a few months later. The WFP/P4P provided capacity development programmes to improve the ability of smallholder farmers’ to engage in collective marketing and reduce post-harvest losses. This included training and investment in rehabilitating storage facilities and linking the farmers to a warehouse receipt system. Access to post-harvest handling services and marketing assistance was expected to increase smallholder farmers’ market participation levels. Similarly, the availability of transport was expected to promote increased market participation because of reduced transaction costs. 27

World Bank et al. (2011) estimates that the overall post-harvest losses in eastern and southern Africa is at 13.5 percent of the total value of grain production.

[ 91 ]


Econometric model The chapter examines market participation on the basis of exogenous explanatory variables, using a dependent variable in the form of an index that represents the proportion of actual maize sales to total maize marketable surplus. The dependent variable is therefore “bounded” between zero and one. The relationship between market participation and exogenous explanatory variables is assumed to be linear and is tested using the following equation:

MPI i = ddi + b X i + e i ....................................................................... (2) where, MPI i is the market participation index of the ith household and is the outcome variable in this analysis; di is the key explanatory variable of interest. It is a binary variable that equals one if a household i participates in a WFP/P4P FO and zero if it participates in a non-P4P FO; X i represents a vector of exogenous factors affecting the level of market participation. The variables included in this vector are highlighted in Figure 1 and comprise household characteristics (gender, age and education level of head of household, size of landholdings, size of livestock holdings, whether a household has other livelihood sources besides agriculture), market factors (costs of marketing, sources of price information, and a dummy for geographical location), as well as institutional factors (access to post-harvest services, access to marketing services, access to transport, access to chemicals to treat maize during storage). The parameters to be estimated are d and b where b is a vector of parameters. The error term is e i . Using Ordinary Least Square (OLS) to estimate Equation 2 will give inconsistent estimates given that the dependent variable is bounded between zero and unity. To overcome this challenge, the estimation

[ 92 ]


strategy used in this paper is to use the seminal fractional logit model of Papke and Wooldridge (1996). The model is specified as:

E ( MPI i / d i , X i ) = G (d id + X i b ......................................................... (3) where, G (·) is a known non-linear function such that 0 < G ( did + X i b < 1 . Papke and Wooldridge (1996) proposed that the fractional logit model be estimated via a quasi-likelihood method which maximizes the Bernoulli log-likelihood function specified as:

MPI i InG ( did + X i b ) + (1 - MPI i ) In(1 - G ( did + X i b )) ...................... (4) where, the cumulative distribution function (CDF) of the logistic distribution is used to represent G (·) . The Bernoulli log-likelihood function is well defined for 0 < G ( did + X i b < 1 . This way, the bounded nature of MPIi is taken into account such that the predicted values of MPIi will be between zero and one. The method results in an efficient Quasi-Maximum Likelihood Estimator (QMLE). Papke and Wooldridge (1996) indicated that using QMLE gives consistent estimated parameters, regardless of the distribution of MPI i conditional on the explanatory variables used provided E ( MPI i / d i , X i ) = G (did , X i b ) (Gourieroux et al., 1984). In addition, the estimated parameters are efficient and robust to arbitrary heteroscedasticity and correlation between residuals. The fractional logit model adopted in this chapter is specified as in Equation 3, where G ( did + X i b ) = exp( did + X i b ) /[1 + exp( d id + X i b ] is the cumulative distribution function of the logistic distribution. The estimated parameters at the mean values of the explanatory variables are used to evaluate the marginal effects. No distribution is assumed; the

[ 93 ]


only requirement is that the conditional mean be correctly specified for consistent parameter estimates. 28 This approach is a one-step approach in which the decision to participate in the maize market and the level of participation are modeled in one step. The analysis is performed using the Stata command fraclogit. It is important to mention that the decision to join a particular (specifically P4P or non-P4P) FO and the decision to participate or not in the market are assumed to be exogenous in this particular setting. This assumption is informed by the following reasons: First, FOs existed before the WFP intervention and farmers’ decision to participate in a particular FO mostly likely preceded the P4P programme. In fact, the data indicates that close to 98.7 percent of FOs (including both the P4P and non-P4P ones) in the survey, by 2013, had been in existence for more than four years, supporting the argument that farmers’ decision to participate in a particular FO most likely preceded the P4P programme, which was introduced in 2009. Second, the selection of FOs for support by the WFP/P4P is not made at household level, rather, the WFP made the selection based on a set of criteria such as proximity to on-going WFP programmes, well-established and well-functioning farmer groups, and farmer groups that are already affiliated to a network, which may provide technical assistance (WFP, 2013). In this study, it is assumed that these criteria are not linked to farmer and household characteristics.

28

A key difference between the fractional logit model and the logit (or probit) regressions is that the fractional logit model estimates the conditional expected value of the response variable, while logit and probit models predict the probability of occurrence of a certain event, which could require arbitrary dichotomizations of the dependent variable (Gallani et al., 2015).

[ 94 ]


Results and Discussion Consistent with Figure 1, explanatory variables included in the analysis can be classified into three main groups: (i) household characteristics which include gender, age and education level of head of household, size of landholdings, size of livestock holdings, whether a household has other livelihood sources besides agricultures, (ii) market factors comprising costs of marketing, score on sources of price information, and a regional dummy is included to capture the geographical and economic variation across the study setting. This dummy is equal to one if the household is located in the central region of Tanzania, which is a marketing hub, and zero otherwise, and (iii) institutional factors which include access to post-harvest services, access to marketing services, an indicator variable of whether the household used services aimed at assisting with selling of produce, access to transport, access to chemicals to treat maize during storage. Table 4.1 reports summary statistics for the pooled sample, the P4P group, and the non-P4P group. The means for market participation of the two groups are not different (around 0.74 for the P4P group and 0.76 for the non-P4P group). In fact, an independent sample test failed to provide enough evidence to suggest that there are differences between the means of the two groups with regard to the market participation index. The independent mean comparison, however, provides evidence that the P4P group had a higher proportion of households with other sources of livelihood besides agriculture; a higher average score on sources of price information; incurs higher marketing costs, on average; a higher share of households that used post-harvest handling services and households that made use of marketing services.29 The average land owned by a 29

In addition, two sample tests of proportions reveals significant differences between the two group means for: (1) whether the household received post-harvest handling services, (2) whether the

[ 95 ]


household in the P4P group is 3.79ha, slightly higher than the 3.51ha average land owned. Table 4.2 reports the summary statistics by size of landholdings using a cut-off point of two hectares. Independent mean comparisons between these two groups suggest that households that own more than two hectares of land have a significantly higher average age of the head of households, bigger household size, higher number of livestock, and a higher score on sources of price information. In addition, they tend to have a higher proportion of households that own a car, ox-drawn cart or bicycle. Figure 4.2 indicates that the mean marketing cost is larger for the P4P group compared to the non-P4P group (8.26 and 3.44 Tanzanian shillings, respectively). Figure 4.3 indicates the total number of P4P beneficiaries by gender and by region, and suggests that female-headed households represent a small proportion of the total number of programme beneficiaries (only 11%). The figure also suggests that the smallest sample is drawn from the southern zone. 30 Figure 4.4 reveals that those in the central and southern regions have relatively higher average land holdings compared to those living in the northern or western regions. By the same token, Figure 4.5 reveals that farmers in the central and southern regions outperform the farmers in the other two regions, in terms of the quantity of maize sold.

30

household accessed services that help with selling of produce, and (3) whether the household has other source of livelihood besides agriculture. Regions included in the northern zone are Kilimanjaro, Manyara and Arusha; in the southern zone are Rukwa, Iringa and Ruvuma; in the central zone are Dodoma and Singida; and in the western zone are Kigoma and Kagera.

[ 96 ]


Figure 4.2: Maize total marketing cost (in Tanzanian shillings) by region and by P4P status

Figure 4.3: Count of P4P beneficiaries by gender and by region

[ 97 ]


Figure 4.4: Land owned (in ha) by region and by P4P status

Figure 4.5: Quantity of maize sold by region and by P4P status

[ 98 ]


To assess the market participation differential effects of the WFP/P4P programme intervention across smallholder farmers with different land size holdings, three fractional logit models are estimated: Model (1) was estimated using the full sample model (n= 675, excluding households with zero marketable surplus), Model (2) was estimated for Group A (households with more than two hectares of land subsample n= 440), and Model (3) for Group B (households with two or less hectares of land, n = 235). The set of exogenous variables described earlier were used in the estimations using the fraclogit Stata command. Model parameter estimates and marginal effects associated with the included explanatory variables are presented in Table 4.3. Both the coefficients and marginal effects are presented. Being a member of a WFP/P4P FO was found to be associated with enhanced market participation only for the Group A (households with more than two hectares of land), while no significant association was found in both the full sample model and the Group B models (Model 1 and Model 3). The result could suggest that the relatively land constrained households tend not to benefit from the increased market opportunities provided by the WFP/P4P programme. This could be attributed to differences in initial conditions across these groups, which most likely influence market participation levels. That is, larger farmers are likely to start off from an advantaged position in terms of leveraging on the opportunities that the programme presents. The result, therefore, underscores the importance of assets such as land in promoting commercialization among Tanzania smallholder farmers. It is, therefore, important for programmes such as the WFP/P4P to categorize and identify programme participants based on the size of landholdings or other important assets at the onset of the project design in order to address differential needs and constraints. The result could also suggest the presence of other factors not explicitly controlled for in the estimations, which systematically differ across smallholders holding [ 99 ]


different sizes of land, and which could be driving their differences in maize market participation. Identification of these factors would benefit future WFP/P4P programme design and subsequently improve its impact on market participation of smallholder farmers. The total number of cattle owned by the household influences the maize market participation of Group A. The relationship is revealed to be nonlinear and U-shaped. One possible explanation for this convex effect of cattle owned on market participation of this group is that there are thresholds within the distributions of cattle, which are acting like a poverty trap on the maize producers. This means that at the low levels of cattle ownership, there might be competition between cattle rearing and farming in the poor households who have limited capital and labor resources endowments, which tend to reduce maize production and consequently selling of maize. However, beyond a certain threshold of cattle ownership, the relationship becomes positive and complementary, for example, having a large herd of cattle may reduce the risk of food insecurity since food staples can be sold in order to buy food, and as such, farmers might retain less for consumption and sell more. Also, cattle rearing could help generate more income that can be used to cover maize production and marketing costs and/or enable farmers to have more efficient production and marketing with the help of an ox or a cow ploughs. Heltberg and Tarp (2002) report a similar finding in Mozambique and suggest that the probability of market participation increases with household expenditure, implying that the non-poor are more likely to participate in the market compared to the poor. By the same argument, and taking land endowment as a proxy for wealth, land endowment is expected to correlate positively with market participation. In addition, more land could, ceteris paribus, be expected to be associated with increased marketable surplus. However, our results for Model 1 (the pooled sample) reveal a negative correlation, implying [ 100 ]


that higher land endowment is associated with reduced maize market participation levels. This could be a reflection that not all the land owned is cultivated, and/or the land could be allocated to other crops besides maize. Marketing costs exhibit a non-linear U-shaped relationship with market participation of the households owning more than two hectares of land (Group A). As with the relationship with the number of cattle that a household owns, the U-shaped relationship between market participation and marketing costs posits that maize market participation among this group are highest when marketing costs are low, and fall in the middle marketing costs spectrum. As marketing cost levels rise, the market participation of this group also rises. Thus, marketing costs alone cannot explain farmers’ market participation levels. The finding that farmers, particularly those owning more than two hectares of land, who face higher marketing cost participate less in the maize markets is plausible and consistent with the literature that smallholder farmers are located in the more remote areas, making the transportation and marketing costs high and hindering the transition of smallholder farmers into commercialization of their activities Key et al. 2000; Barrett, 2008; Minot 2010; Livingston et al., 2011. Access to post-harvest handling services matter for smallholders farmers, indeed, having used post-harvest handling services in the previous year was found to be associated with increased smallholder farmers maize market participation levels, a result that drives the positive and statistically significant result in the pooled sample. This suggests that access to services that reduce post-harvest losses such as training, storage facilities and warehouse receipt systems enhances the participation of smallholder farmers in the markets. Access to postharvest handling services does not, however, have a statistically significant impact on the maize market participation of Group A. [ 101 ]


The use of chemicals during storage of maize has a negative and significant impact on market participation levels but only for the pooled sample, driven by the smallholders owning two or less hectares of land (Group B). A possible explanation for this is that treating maize helps farmers preserve the maize for longer, meaning that they are not forced to market the maize within the same season. This could be good in so far as it allows farmers to hold on to their maize produce until such a time when they can get better deals in the form of, for example, better prices. Households living in the central region, which comprises Dodoma and Singida administrative regions, are more likely to have higher market participation rates, as suggested by the results which reveal that the central region dummy is positive and significant at 1 percent level of significance, in all the three models. The positive effect of the central region dummy is expected given that Dodoma and Singida are marketing hubs and the transportation infrastructure in this zone is relatively well developed. The central zone has several intermediary markets connecting smallholders in Dodoma and Singida to terminal markets like Dar es Salaam (TLZ, 2015).

Conclusion and Policy Implications Sub-Saharan Africa remains disproportionately rural, with smallholder farmer agriculture being an important source of income, underpinning the livelihoods of the majority of the population. The overwhelming majority of residents grow staple food grains mostly in semi-subsistence, rather than, commercial setting. While there is general agreement that improving market access and commercialization of smallholder farmers will help induce greater investment, productivity, and income, there remain several challenges in progress towards improving access to both agricultural input and output markets, particularly by smallholder farmers. These challenges range from relatively high transport and transaction costs due to geographic and economic isolation from market [ 102 ]


towns; imperfect markets; and lack of supporting institutions or organisations that could improve the bargaining power of smallholder farmers; among others. This is of concern, given the existing evidence that highlights the benefits of the commercialization of surplus output in terms of higher productivity, greater specialization and higher incomes. In an effort to reap these benefits, improving market participation of smallholder farmers, remains a key strategy for supporting poverty reduction, rural development, and agricultural transformation in subSaharan Africa. To this end, there has been an increasing role of collective institutional arrangements such as farmers’ organizations, as a potential substitute for state direct interventions in rural markets. Such arrangements, it has been demonstrated, reduce information asymmetries and costs of households’ access to local markets as well as allow members to build up market power and improve their participation in the markets. It is against this background that the World Food Programme developed the Purchase for Progress (P4P) programme with the aim of using local and regional purchases to help stimulate competition, link farmer groups to markets, and support food marketing infrastructure in 20 countries in Africa, Asia and Central America. The P4P procurement modality implies that WFP is committed to buying from selected farmer organisations. This chapter uses household survey data, collected by WFP in 2013, as part of its monitoring and evaluation system, to examine the differential impact of WFP/P4P programme on the participation of smallholder farmers in maize markets in Tanzania. Small-scale subsistence farmers who produce most of the country’s food and cash crops as well as livestock rearing dominate Tanzanian agriculture. Maize is the most important cereal crop in Tanzania: it is produced by about 82 percent of all Tanzanian smallholder farmers and consumed by 90 percent of the population. The crop occupies about 45 percent of the total arable land, and generates about 50 percent of the rural cash income. The poor infrastructure and inadequate market information in Tanzania has [ 103 ]


resulted in a low rate of commercialization; poor market integration and hindered trading between surplus and deficit regions. This chapter contributes to a broader understanding of the impact of collective institutional arrangements on market participation of smallholder farmers in sub-Saharan Africa. A fractional logit model is employed for the econometric analysis given the fractional nature of the dependent variable, which is defined as the quantity of maize sold as a proportion of total maize marketable surplus. To allow for differences between smallholders in terms of landholdings, a cut-off point of two hectares is used to split the smallholders sample into two distinct subsamples: the subsample of farm households that own more than two hectares of land, and subsample of those owning two hectares of land or less. In order to assess the differential impact of the WFP/P4P intervention on market participation of smallholders with different land size holdings, three fractional logit models are estimated: the first using the full sample, the second using Group A made up of households owning more than two hectares of land, and the third using a subsample of household owning two or less hectares of land (Group B). Explanatory variables included in the analysis can be classified into four main groups: (a) household characteristics (age, gender, education and household size); (b) capital and wealth variables (land and cattle ownership, and whether a household has any other form of livelihood, in addition to agriculture); (c) marketing and transaction variables (score on sources of price information, cost of marketing, ownership of transportation means and an indicator of whether a household made use of services aimed at assisting with selling of their produce; (d) postharvest and storage variables (having made use of services related to post-harvest handling, and using chemicals to treat stored maize thereby protecting it from rats and termites). A regional dummy is included to capture the geographic and economic variation across the study setting. Being a member of a P4P farmer organisation was found to be associated with enhanced maize market participation only for the households that [ 104 ]


own more than two hectares of land, while no statistically significant impact of WFP/P4P is found for the group owing two or less hectares. This result suggests that the WFP/P4P programme has differential impacts on market participation, across farmers with different sizes of landholdings. The result could also suggest that the relatively land constrained households tend not to benefit from the increased market opportunities provided by the WFP/P4P programme. This could be attributed to differences in initial conditions across these groups, which most likely influences smallholder farmers market participation levels. That is, larger farmers are likely to start off from an advantaged position in terms of leveraging on the opportunities that the programme presents. The result, therefore, underscores the importance of assets such as land in promoting commercialization among Tanzania smallholder farmers. It is, therefore, important for programmes such as the WFP/P4P to categorize and identify programme participants based on the size of landholdings or other important assets at the onset of the project design in order to address differential needs and constraints. The result also highlights the need for systematic and sustained support for assetconstrained (land) smallholder farmers, for a relatively longer period, with the aim of getting them to participate in output markets. Furthermore, the results support the contention that the non-poor (proxied by levels of cattle holdings) are more likely to participate in the market, compared to the poor. This, together with the finding that marketing costs constrain market participation, points to the need for policy makers to pay attention to strategies and initiatives aimed at alleviating resource constraints, as a way of facilitating market participation of sub-Saharan farmers in general, and Tanzanian farmers, in particular. In addition, access to post-harvest handling services matter for market participation of smallholder farmers should therefore be incorporated into initiatives to promote market participation of smallholder farmers.

[ 105 ]


References Alagh, M. (2014). Assessment of marketed and marketable surplus of major food grains in Gujarat. Ahmedabad: Centre for Management in Agriculture, Indian Institute of Management. Barrett, C. B. (2008). Smallholder market participation: concepts and evidence from Eastern and Southern Africa. Food Policy, 33: 299317. Bernard, T., T.A. Seyoum and E. Gabre-Madhin. (2008). Impact of cooperatives on smallholders’ commercialization behavior: Evidence from Ethiopia. Agricultural Economics, 39(2): 147–61. Bijman, J.G.T. and G. Meijerink. (2007). Empowering smallholder Farmers in Markets: National and International Policy Initiatives. Wageningen: WUR. Chamberlin, J. (2008). It’s a small world after all: defining smallholder agriculture in Ghana. International Food Policy Research Institute. Development Strategy and Governance Division. Discussion Paper No. 00823. Diao, X., P. Dorosh and S. Rahman. (2007). Market Opportunities for African Agriculture: a general equilibrium examination of demandside constraints on agricultural growth in East and Southern Africa. Research Report 154.International Food Policy Research Institute, Washington, D.C. Dixon, J., K. Taniguchi and H. Wattenbach. (2003). Approaches to assessing the impact of globalization on African smallholders: household village economy modeling. Proceedings of a working session on globalization and the African smallholder study. Rome: FAO, AGS, ESA, and the World Bank. Ellis, F. (2005). Rural Livelihoods and Diversity in Developing Countries. Oxford, UK: Oxford University Press. Enete, A.A. and E.M. Igbokwe. (2009). Cassava market participation decision of producing households in Africa. Tropicultura, 27: 129-36. [ 106 ]


FAO. (2009). Crop prospect and food situation: global cereal supply and demand brief. Rome: FAO. FAO. (2012). Analysis of incentives and disincentives for maize in the United Republic of Tanzania. Technical Notes Series, MAFAP, FAO, Rome. Farinde, A.J and K.A. Taiwo. (2003). Moving women from subsistence to commercialization: issues and policy imperatives. Paper presented at the Workshop Organised by FAO/IITA on “The Gender impact of commercialization of smallholder agriculture”. Institute of International Tropical Agriculture, Ibadan, 14-16 May. Fischer, E. and M. Qaim. (2012). Linking smallholders to markets: determinants and impacts of farmer collective action in Kenya. World Development, 40(6): 1255-68. Francesconi, G.N. and N. Heerink. (2011). Ethiopian agricultural cooperatives in an era of global commodity exchange: does organisational form matter? Journal of African Economies, 20(1): 153–77. Gallani, K.S. and J. Wooldridge.(2015). Applications of fractional response model to the study of bounded dependent variables in accounting research. Working Paper No. 16-016.Harvard Business School. Gouriéroux, C., A. Monfort and A. Trognon. (1984). Pseudo maximum likelihood methods theory. Econometrica, 52: 681-700. Govereh, J., T.S. Jayne and J. Nyoro. (1999). Smallholder commercialization, interlinked markets and food crop productivity: cross-country evidence in Eastern and Southern Africa”. At http://www.aec.msu.edu/fs2/ag_transformation/ atw_govereh.PDF Hazell, P. (2005). “Is there a future for small farmers?” Agricultural Economics, 32(1): 93:101. Heltberg, R. and F. Tarp. (2002). Agricultural supply response and poverty in Mozambique. Food Policy, 27(2): 103-124.

[ 107 ]


Holloway, G., C. Nicholson, C. Delgado, S. Staal and S. Ehui. (2000). Agroindustrialization through institutional innovation – transaction costs, cooperatives and milk-market development in the East-African highlands. Agricultural Economics, 23(3): 279-88. IFAD. (2013). Smallholder, food security, and the environment. Rome: International Fund for Agricultural Development. Jaleta, M., B. Gebremedhin and D. Hoekstra. (2009). Smallholder commercialisation: processes, determinants and impact. ILRI Discussion Paper No. 18. International Livestock Research Institute, Nairobi. Jayne, T.S., D. Mather and E. Mghenyi. (2005). Smallholder farming in difficult circumstances: policy issues for Africa. MSU International Development Working Paper No. 86. Department of Agricultural Economics and the Department of Economics, Michigan State University, East Lansing, Michigan. Key, N., E. Sadoulet and A. De Janvry. (2000). Transaction costs and agricultural household supply response. American Journal of Agricultural Economics, 82: 1273-79. Krieger, D. (2014).The Impact of P4P on SACCOs and Smallholder Farmers in Tanzania. P4P Global Learning Series. World Food Programme, Rome. Lapar, M.L., G. Holloway and S. Ehui. 2003. Policy option promoting market participation among smallholder livestock producers: a case study from the Philippines. Food Policy, 28: 187-211. Livingston, G., S. Schonberger and S. Delaney. (2011). Sub-Saharan Africa: the state of smallholders in agriculture. IFAD Conference on New Directions for Smallholder Agriculture 24-25 January 2011, Rome, International Fund for Agricultural Development. (At http://www.ifad.org/events/agriculture/doc /papers/ livingston.pdf) Markelova, H., R. Meinzen-Dick, J. Hellin and S. Dohrn. (2009). Collective action for smallholder market access. Food Policy, 34(1): 1–7.

[ 108 ]


Mathenge, M., F. Place, J. Olwande, D. Mithoefer (2010). Participation in agricultural markets among the poor and marginalized: analysis of factors influencing participation and impacts on income and poverty in Kenya. Egerton University, Tegemeo Institute of Agricultural Policy and Development, Study Report. Maziku, P. J.P. Hella and J. Makindara. (2015). Contribution of non-tariff barriers on market transaction costs for maize production and trade in Tanzania. Journal of International Review of Research in Emerging Markets and the Global Economy (IRREM), 1(1): 193-207. Mbise, M., D.H. Ngongola, H. Chale, B. Maonga and F.T. M. Kilima. (2010). Transaction costs and food security: a case of maize in southern highlands of Tanzania. Paper presented at the Regional Universities Forum for Capacity Building in Agriculture, Second RUFORUM Biennial Meeting. Entebbe, Uganda 20– 24 September. Minot, N. and M. Ngigi. (2004). Are horticultural exports a replicable success story? Evidence from Kenya and Cote d’Ivoire .EPTD Discussion Paper No. 120. International Food Policy Research Institute, Washington, D.C. Minot, N. (2010). Staple food prices in Tanzania. Washington, D.C.: International Food Policy Research Institute. National Bureau of Statistics (NBS). (2014). Tanzania National Panel Survey Report (NPS) - Wave 3, 2012–2013. Dar es Salaam, Tanzania. Narayanan, S. and A. Gulati. (2002). Globalization and the smallholders: A review of issues, approaches and implications. MSSD Discussion Paper No. 50. IFRI Markets and Structural Studies Division, Washington, D.C. Nyoro, J.K. and I.K. Ngugi. (2007). A qualitative analysis of success and failure factors of agricultural cooperatives in central Kenya”. In C.B. Barrett, A.G. Mude and J.M. Omiti, eds., Decentralization and the Social Economics of Development: Lessons from Kenya. Nairobi: CAB International. [ 109 ]


Omamo, S.W. (1998). Farm-to-market transaction costs and specialization in small-scale agriculture: explorations with a non-separable household model. Journal of Development Studies, 35(2): 152–63. Omiti, J.M., D.J. Otieno, T.O. Nyanamba and E. McCullough. 2009. “Factors influencing the intensity of market participation by smallholder farmers: a case study of rural and peri-urban areas of Kenya. African Journal of Agricultural and Rural Economics, 3: 5782. Papke, L.E. and J.W. Wooldridge. (1996). Econometric methods for fractional response variables with an application to 401 (K) plan participation rates. Journal of Applied Econometrics, 11(6): 619-32. Petro, M. (2015). Market access for maize smallholder farmers in Tanzania. Proceedings of the second European academic research conference on Global Business, Economics, Finance and Banking (EAR15 Swiss Conference). Zurich, Switzerland. Phiri, N.A. and G. Otieno. (2008). Report on managing pests of stored maize in Kenya, Malawi and Tanzania. Nairobi. The MDG Centre, East and Southern Africa. Poulton, C., et al. (2004). Competition and coordination in liberalized African cotton market systems. World Development, 32(3):519-36. Pravakar, S., I.V. Castellanos and D.B. Rahut. (2010). Commercialization of Agriculture in the Himalayas. IDE Discussion Paper No. 265. Rao, E.J.O. and M. Qaim. (2011). Supermarkets, farm household income, and poverty: insights from Kenya. World Development, 39(5): 784– 96. Sebatta, C. (2014). Smallholder farmers decision and level of participation in the potato market in Uganda. Modern Economy, 5: 895-906. Stephens, E.C. and C.B. Barrett. (2006). Incomplete credit markets and commodity marketing behavior. Cornell University Working Paper. TLZ. (2015). Tanzania livelihood baseline profile zone: Signida-Dodoma bulrush millet, sorghum, sunflower and livestock livelihood zone. [ 110 ]


(Accessed at http://www.kilimo.go.tz/ publications/english percent20docs/fslbp/T55 percent20FINAL.pdf) Urrasa, H. (2010). Rural households’ livelihoods, crop production and wellbeing after a period of trade reforms: A case study of Rukwa region in Tanzania. PhD thesis, University of Life Science of Berigeum. USAID. (2010). Staple foods value chain analysis. Country Report Tanzania. USAID – COMPETE Program Document. Timmer, C.O. (1997). Farmers and markets: the political economy of new paradigms. American Journal of Agricultural Economics, 79: 621-27. Valentinov, V. (2007). Why are cooperatives important in agriculture? An organisational economics perspective. Journal of Institutional Economics, 3(1): 55–69. WFP. (2013). The story of P4P in Tanzania 2009-2013. Internal Report. World Food Programme, Rome. Wiggins, S., J. Kirsten and L. Liamb́ı . (2010). The future of small farms. World Development, 38(10): 1341–48. Wiggins, S. and S. Keats. (2013). Leaping and learning: linking smallholders to markets. Agriculture for Impact. Imperial College London. Williamson, O. E. (1985). The Economic Institutions of Capitalism: Firms, Markets, Relational Contracting. New York: The Free Press. World Bank. (2003). Reaching the rural poor: a renewed strategy for rural development. Washington, D.C.: The World Bank. World Bank, FAO, NRI. (2011). Missing food: the case of post-harvest grain losses in Sub-Saharan Africa. Economic Sector Work Report No. 60371-AFR. The World Bank, Washington, D.C.

[ 111 ]


Table 4.1: Summary statistics

Market Participation Index P4P status Gender of head: 1=female Education of head

Quantity of maize sold as a proportion of total maize marketable surplus =1 if household belongs to a P4P farmers' organisation, 0 if it belongs to a non-P4P FO =1 if household head is female =1 if head completed primary school

Pooled Mean Std. Dev.

P4P Group Mean Std. Dev.

Non-P4P Group Mean Std. Dev.

P-value

0.75

0.43

0.74

0.44

0.76

0.43

0.52

0.5

0.5

0.11

0.31

0.1

0.3

0.12

0.33

0.45

0.89

0.31

0.9

0.29

0.88

0.32

0.38

Age of head

Age of head in years

49.76

11.26

49.78

11.33

49.73

11.2

0.98

Household size

Household size Total land owned by the household, in ha No of cattle owned by household =1 if household owns either a car, ox-drawn cart or bicycle

5.59

2.09

5.71

2.01

5.46

2.16

0.11

3.65

4.7

3.79

5.04

3.51

7.71

0.41

3.75

9.36

3.25

7.8

4.28

10.72

0.13

0.79

0.41

0.79

0.41

0.78

0.42

0.59

0.733

0.44

0.78

0.42

0.69

0.46

0.01***

Total land owned Number of cattle Transport Other Livelihood(s)

=1 if household has other source of livelihood

[ 112 ]


Access to price information Marketing cost Post-harvest services Marketing services Treated maize with chemicals during storage Central region

Score for sources of price information, out of 12 sources Total cost incurred to sell maize in Tanzanian shillings =1 if household used postharvest services =1 if household used selling assistance in the last 12 months =1 if household applied chemical treatment to protect the stored harvest from insects and pests =1 if household is in the central zone

Pooled Mean Std. Dev.

P4P Group Mean Std. Dev.

Non-P4P Group Mean Std. Dev.

P-value

7.94

4.44

8.32

4.58

7.54

4.26

0.02**

5.9

19.19

8.26

22.29

3.45

14.97

0.001***

0.18

0.38

0.2

0.4

0.15

0.36

0.08*

0.09

0.2

0.14

0.35

0.04

0.2

0.00***

0.5

0.5

0.49

0.5

0.51

0.5

0.52

0.37

0.48

0.36

0.48

0.37

0.48

0.70

Note: ***, **, * significant at 1%, 5%, and 10% levels of significance, respectively.

[ 113 ]


Table 4.2: Summary statistics by size of landholdings

Market Participation Index P4P status Gender of head: 1=female Education of head Age of head Household size Total land owned Number of cattle Transport Other livelihood(s) Access to price information Marketing cost Post-harvest services Marketing services Treated maize with chemicals during storage Central region

Group A: more than 2ha landholdings Mean Std. Dev. 0.757 0.429 0.512 0.500 0.112 0.316 0.888 0.316 50.434 11.203 5.815 1.941 5.067 5.371 4.456 10.704 0.825 0.381 0.725 0.447 7.751 4.237 6.510 20.668 0.167 0.373 0.093 0.291

Group B: 2ha or less of landholdings Mean Std. Dev. 0.739 0.440 0.500 0.501 0.112 0.316 0.899 0.302 48.574 11.304 5.209 2.262 1.121 0.469 2.399 5.734 0.720 0.450 0.754 0.432 8.375 4.740 4.924 16.429 0.201 0.401 0.095 0.293

P-value

0.507 0.444

0.480 0.223

0.495 0.000***

0.501 0.497

Note: ***, **, * significant at 1%, 5%, and 10% levels of significance, respectively.

[ 114 ]

0.501 0.417

0.584 0.762 0.989 0.633 0.034** 0.000*** 0.000*** 0.004*** 0.001*** 0.398 0.067* 0.284 0.252 0.940


Table 4.3: Determinants of market participation levels Model (2): Group A: more than 2ha landholdings Marginal Std. Marginal Coefficient effects Error effects

Model (3): Group B: 2ha or less of landholdings Std. Marginal Coefficient Error effects

Model (1): Pooled sample Variable

Coefficient Std. Error

P4P status Gender of head: 1= female Education of head Age of head Household size Total land owned Number of cattle Number of cattle squared Transport Other livelihood(s) Access to price information Marketing cost Marketing cost squared

0.193

0.211

0.193

0.462*

0.275

0.462

-0.062

0.455

-0.061

-0.210

0.346

-0.210

-0.221

0.436

-0.221

0.232

0.776

0.232

-0.113 -0.007 0.082 -0.045* -0.054**

0.355 0.00972 0.0524 0.0232 0.0218

-0.113 -0.007 0.082 -0.045 -0.055

-0.274 -0.009 0.081 -0.041 -0.062**

0.450 0.012 0.070 0.026 0.026

-0.274 -0.009 0.081 -0.041 -0.062

-0.056 -0.004 0.128 0.689 -0.001

0.789 0.022 0.108 0.512 0.092

-0.056 -0.004 0.128 0.689 -0.001

0.002***

0.000290

0.002

0.002***

0.000

0.002

-0.001

0.002

-0.001

-0.101 -0.269

0.266 0.237

-0.101 -0.269

-0.310 -0.144

0.369 0.304

-0.310 -0.144

0.395 -0.609

0.513 0.525

0.395 -0.609

-0.001

0.0252

-0.001

0.034

0.035

0.034

-0.020

0.049

-0.020

-0.055***

0.0178

-0.055

-0.059*** 0.022

-0.059

-0.057

0.043

-0.057

0.000**

0.00020

0.000

0.001**

0.001

0.001

0.001

0.001

[ 115 ]

0.000


Model (2): Group A: more than 2ha landholdings Marginal Std. Marginal Coefficient effects Error effects

Model (3): Group B: 2ha or less of landholdings Std. Marginal Coefficient Error effects

Model (1): Pooled sample Variable Post-harvest services Marketing services Treated maize with chemicals during storage Central region Constant Observations

Coefficient Std. Error 0.596**

0.282

0.596

0.386

0.372

0.386

1.620***

0.591

1.620

-0.329

0.383

-0.329

-0.638

0.489

-0.638

-0.602

0.841

-0.602

-0.407*

0.209

-0.407

-0.340

0.274

-0.340

-0.222

0.443

-0.222

1.346*** 1.371* 675

0.240 0.801

1.346

1.324*** 1.376 440

0.294 1.026

1.324

1.816*** -0.199 235

0.608 1.939

1.816

Note: *** pchi2

0.34 0.84

8.40 0.74 0.69 2.99 1.00 0.61 -12.98 ** 14. Post-harvest services a Dummy variables indicating the previous use (in 2009 or in 2011) of the agricultural support services are included as control in the outcome equations. Note: "-" means we are not able to estimate the ATEs due to either lack of convergence or violation of the overlap assumption. The chi2 and the corresponding probabilities indicate the test of endogeneity (Ho: treatment and outcome unobservables are uncorrelated). Significance level are indicated with *** p