Keys to Inclusion of Small-Scale Producers in Dynamic Markets

Methods for Assessing Determinants, Costs, and Benefits of Small Farmer Inclusion in Restructured Agrifood Chains

Resource Paper for Component 1

Thomas ReardonDepartment of Agricultural Economics, Michigan State University

Jikun HuangCentre for Chinese Agricultural Policy, Chinese Academy of Sciences

Version 6, October 2005

Note that the authors are the Coordinators of Component 1 of the Regoverning Markets Program. An earlier version this Resource Paper was presented at the Regoverning Markets Methodology and Planning Workshop, 27-30 August 2005, Amsterdam

Table of contents

1. Introduction......................................................................................................................12. The Questions Addressed by and the Modular Structure of the Field Research of Component 1........................................................................................................................33. The Operational Approach of Component 1......................................................................5

3.1. Methodological workshop...........................................................................................53.2. Empirical research – Country Studies.........................................................................6Action Plan Component 1..................................................................................................73.3. Capacity building of national researchers...................................................................93.4. Inter-country and inter-regional comparison and global synthesis.............................93.5. Dissemination of findings and connections to policy................................................10

4. Specific Methods for the Modules...................................................................................104.1. Module 1: The National (Meso) Study of Industry or Market Level Restructuring......10

4.1.1. General Structure and Themes of the National-Meso Module.............................104.1.2. Dairy processing restructuring illustration..........................................................134.1.3. Operational Issues for the national-meso Study.................................................16

4.2. Module 2: Local-Meso Module, using Participatory Rural Appraisal...........................174.2.1. Objectives...........................................................................................................174.2.2. Methods..............................................................................................................18

4.3. Module 3: Micro Level Decision Making -- Participation in Restructured Market Channels and/or in Traditional Channels, and Attendant Behaviors.................................19

4.3.1. The basic conceptual framework........................................................................204.3.2. Operationalisation of the conceptual framework with illustrative questionnaires..................................................................................................................................... 244.3.3. Sampling and Operational issues........................................................................24

5. Final Report Table of Contents.......................................................................................25

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Methods for Assessing Determinants, Costs, and Benefits of Small Farmer Inclusion in Restructured Agrifood Chains

1. Introduction

The central issues of the research program discussed in this document are: (1) the rapid change taking place in the structure and governance of local, national, and regional agrifood markets, driven by the transformation of the “food industry” in developing countries. The “food industry” comprises three elements: (1) retailing (which includes both retail for purchase to consume at home, and retail to consume on the premises, the latter being the food service or restaurant sector); (2) food processing; (3) and wholesaling;1 (2) the implications for small/medium producers and rural labourers of the restructuring of the food industry; (3) the implications for policies and programs.

The food industry changes include consolidation, institutional, organizational and technological transformation, and multinationalisation. These changes are occurring very quickly in developing regions: it can take developing regions as little as ten years to reach the levels of food industry restructuring that took five or more decades in Europe or North America. The restructuring is driven by a mix of socioeconomic factors on the demand side (increases in consumer incomes and urbanization) and various factors on the supply side (huge flows of foreign direct investment, facilitated by FDI liberalization, from OECD country food industry firms into developing regions, and competitive investments by domestic food industry firms; and changes in procurement systems of food industry firms, helping them to penetrate food markets).

The program emphasizes the study of the restructuring of all the segments of the food industry, thus capturing the complexity of agrifood market change. The restructuring of the individual food industry segments (retail, processing, wholesale) is occurring in simultaneous and interdependent ways, albeit at different rates and in different ways across countries and products. That is, the food industry segments are often evolving in “symbiotic” ways (Reardon and Timmer, 2005). One example is that of the dairy processing segment; in South America it is consolidating and multinationalising, and changing the organizational and institutional measures it takes to coordinate its supply chains in order to maximize quality and minimize cost. In some countries, such as Chile, this is the principal change agent in the dairy market, causing restructuring of the dairy products wholesale sector, as well as facilitating the increase of the share of dairy in the restructuring retail sector, led by supermarkets and hypermarkets. In other larger markets, such as Argentina and Brazil, retail and processing and wholesale restructure simultaneously, with the restructuring of each segment facilitating the restructuring in other segments. Another example is that of the fruits and vegetables market. In China, one is observing the rapid development of the wholesale segment, leading change in the food industry, reminiscent of similar developments in South America in the 1970s/1980s. In Central America, the retail and wholesale sectors are co-evolving and restructuring rapidly (Berdegue et al. 2005, Wang et al., 2005, Farina et al. 2005, Reardon and Timmer, 2005).

1 Note that the word “industry” does not imply the adjective “industrial” or the process “industrialization”; “industry” implies neither a scale (small or large), nor a technical level (such as modern or traditional), nor a level of formality (such as informal versus informal). “Industry” merely implies a set of segments producing like services or products. “Industry” focuses attention the actors, and “market” on the demand and supply forces and transactions among actors. In the agrifood economics literature, the terms are often used interchangeably and loosely, referring to the agrifood industry or the agrifood market. The food industry is the set of actors or segments “downstream” in the food chain, with the farmer and the farm inputs segment upstream from them.

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The above changes bring rapid change in the organizational, institutional, and technological practices all the way “upstream” in the agrifood systems. These practices are driven by the “higher bar” placed by restructured food industry firms – demanding stiffer requirements for product and transaction attributes/standards. Those in turn require investments and changes in practices by producers, rural brokers, and input suppliers. Small-scale agriculture, which supports the livelihoods of the majority of rural poor, is poorly prepared for these food industry changes. The latter bring opportunities for farmers and labourers - but also can cut domestic producers out of traditional markets, and impose high barriers to entry into promising new markets.

There is an urgent need to fill the gap in knowledge regarding the implications and opportunities for small-scale producers and small and medium enterprises of the above food industry restructuring, and how to help these actors to avail themselves of the opportunities and face the challenges of restructuring markets. It is crucial to understand what are the best practices for connecting small-scale producers with dynamic markets, and bring these findings into the wider policy arena.

To respond to this need, the Regoverning Markets program is starting an intensive two-year program of collaborative research and policy support is planned, built around a global consortium of Southern and Northern institutions. The focus of the research program is on the restructuring of dynamic national and regional food industries, and the effects that this market restructuring is having on small-scale farmers and implications for local rural economies including local labourers. The program emphasizes analysis of all three segments of the food industry in each case (retail, processing, and wholesaling), as they are intimately connected, in particular in the cases of fresh produce and processed dairy products that are the foci of the country studies. The identified challenges facing primary producers and their economic organizations in negotiating market access conditioned by liberalization and modernization. These include technological, organizational and financial demands placed on small-scale farmers.

The work has two overarching objectives: (1) to inform, with facts and recommendations for practical action, public sector policy and private sector strategies; (2) to build local capacity to continue to inform the policy debate and process.

The research program spans three regions, Asia, Latin America, and Africa. A crucial element of this undertaking is to emphasize cross-country comparisons within regions, and across regions, reflecting varying degrees of food industry restructuring and the different policy environments. The program will support learning platforms and activities at international, regional and national levels. These will aim to share lessons learnt and contribute to policy dialogue and policy influence.

The research program of Component 1 comprises inter-linked, modular studies at the national-meso level (study of food industry change through key informant interviews structured with a commodity value chain analysis), local-meso level (study of product and factor market change and institutional, social, and organizational context at the community level, through Participatory Rural Appraisal to sharpen the policy advice and enhance participation of policy stakeholders), and at the micro level (study of farm level practices and responses, through farm-level surveys and analysis).

The present document focuses on the research questions, field research program design, and field research methodology, specifically for Component 1 of the Regoverning Markets Program. The latter comprises three components, and Components 2 and 3 are treated in other documents as well as the document on the overall program. The present document is written by the coordinators of the Component 1 with the objective of informing the

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consortium members, and a wider audience, of the methods for addressing the research questions of Component 1.

The rest of the document is laid out as follows. Section 2 discusses the research questions and concomitant general structure (into modules) of the field study of Component 1. Section 3 discusses the operational steps of the field research to prepare for, undertake, and report on to policymakers, civil society, private sector, and donors the research results. Section 4 enters into detail on each of the modules of Component 1. Section 5 outlines the required final reports of the studies. An Annex under separate cover presents examples (from Central America, Mexico, and China) of questionnaires for farm survey module of the study.

2. The Questions Addressed by and the Modular Structure of the Field Research of Component 1

This section sets out the questions and “maps” them to field study “modules.”

There are three interlinked “modules” cast at different levels, as noted in section 1: (1) the national-meso level, (2) the local-meso level, and (3) the micro level.

There are four sets of questions addressed by Component 1, derived from the general questions of the Regoverning Markets Project.

(1) What is the nature of the restructuring (consolidation, multinationalisation, changes in organization, institutions, and technology) of the food industry hence the agrifood system downstream from the farmer, for the product(s) in question? What are the implied changes (relative to traditional markets) in incentives and requirements facing the farmer in restructured markets, derived chiefly from the product and transaction attributes/standards (such as quality, safety, volume, consistency over time of delivery, and packaging)?

This question set is asked at “national-meso” and “local-meso” levels. For example, the national-meso study in India would examine the restructuring of the dairy industry paying particular attention to the national patterns in processing, wholesale, and retail change. The national-meso study results serve as context for and inform the content of the local-meso level study. The latter focuses, in the study zone(s), on how the first-stage processing and local wholesale segments are restructured, and the social, institutional, and organizational context, including power relationships within the chain and government intervention.

The patterns and determinants of the restructuring of the downstream segments of an agrifood chain are usually analyzed, in the social sciences, in terms of the business strategy, the industrial organization, and the social-economic interactions among groups in the segments of the chain, from the perspectives of supply chain analysis and business strategy (Cook and Chaddad, 2001), commodity value chain analysis (Kaplinsky and Morris 2001), and socio-cultural analysis of social interactions and power relationships (Epstein accessed 2005, Chambers 1994, IDRC accessed 2005).

(2) What are the market channel choices and multi-market strategies of farmers (comparing restructured markets and traditional markets)? How do they undertake those strategies, collectively or individually? What are the determinants of those choices?

This question set is asked at the “micro level” and the “local-meso” levels. For example, the local-meso level study in India would examine, in the study zone(s), the procurement system choices of local dairy processors and those choices and the structure of local dairy farmer cooperatives, within the context of the more broadly restructuring dairy sector. The local-

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meso study results serve as context for and inform the content of the micro-level study. The latter focuses, in the study zone(s), on how dairy farmers choose between restructured dairy and traditional dairy market channels, how they interact with those channels and why (individually or collectively), and what characterizes (in terms of physical, financial, human, and social capital) the producers that take one path or another.

Farmer marketing behaviour is usually analyzed in social sciences by analysis of the set of incentives facing farmers, and the capacity of the farmers to respond. Quantitative questions about choices of farmers and their characteristics are important, as are qualitative questions about attitudes toward the marketing channels. There is a long tradition for example in applied agricultural economics to use a rich, diverse set of incentive and capacity variables, both quantitative and qualitative, in the set of potential determinants; these variables are both quantitative variables such as prices, risk reflected in price variability, costs of inputs needed to undertake the behaviour, and levels of asset holdings needed to undertake the behaviour (such as predetermined holdings of greenhouses and irrigation assets that are needed for quality consistency and year-round delivery of fruit, or proximity to roads) – as well as many qualitative variables that proxy cultural values (such as ethnicity) and policy and regulatory variables that condition sets of incentives and capacity (see Feder, Just, and Zilberman, 1985).

Collective behaviour, such as producer organization response to local market alternatives, is usually analyzed in social sciences by analysis of the “map” of organizations in an area, and how they interface with the different market channels (for example, are they used to collect and market product, monitor and enforce quality, and assist member producers?). An example from Chile is Berdegué (2001).

(3) What are the technological2, managerial, and organizational practices/behaviour related to (either previous to, simultaneous with, or ensuant to) the market channel choices of the farmers? What are the determinants of their behaviour? What are the net effects of the combination of their market channel choices and the attendant costs of these practices, in terms of net incomes and entry requirements of the restructured versus traditional market channels for the product(s) in question?

This question set is again asked at the “micro level” and the “local-meso” levels. This set of questions is just the farm and organization level behavioural questions counterpart of the market channel choice analysis. For example, in the India dairy case, the local-meso study would examine, in the study zone(s), the technological and market requirement reasons for the choice of sourcing patterns among farmers. The local-meso study results serve as context for and inform the content of the micro-level study. The latter focuses, in the study zone(s), on how dairy farmers choose farm-level and post-harvest level technologies, managerial approaches, and organizational approaches in order to meet market requirements. From that can be inferred costs and benefits for farmers (and combined with question 4, for labourers) of the different market channels.

Farmer technology, organization, and managerial behaviour is usually analyzed in social sciences in analyses analogous to the adoption analysis discussed above for market channel 2 A technology is a combination of factors to produce a given unit of product x. Hence, 2 units of labor, 2 units of capital, and 1 unit of land is a different “technology” from 3 units of labor, 1 unit of capital, and 1 unit of land. Technologies are characterized by their “factor bias”, hence the second one is more labor intensive (less capital intensive) than the former. The term “technology-embodying capital” is used in the technology literature to mean a physical capital asset that is the “anchor” to a particular technology, like an irrigation-based technology where the adoption of the latter is proxied by adoption of or investment in irrigation capital. By capital we mean physical capital unless specified otherwise; in most empirical work, capital is disaggregated into its components, such as tractors, irrigation equipment, etc. Note that “financial capital” is not included in a production function, rather it is only in an input demand function.

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choices, with quantitative and qualitative variables explaining the choices. Central American examples can be found in Balsevich et al. (2005) and Hernandez et al. (2004).

Similarly analogous (to that used in question set 2) analysis of collective behaviour is relevant here for the producer organization and processors choices.

(4) What are the interactions between the market and production practice behaviour of producers and local food industry segments on the one hand, and labour, land, other inputs, and financial services markets, on the other?

The above behaviours of food industry firms and farmers, locally, in response to the restructuring food industry occurring locally and nationally, has impacts on factor markets – for labour, land, other inputs such as equipment and seeds, and financial services. It is not feasible, given budget constraints, for extensive additional survey work on factor markets to be undertaken in this program. Rather, the meso level effects on factor markets, and thus on groups such as labourers, can be extrapolated, or “aggregated up” from the micro level information, and from the Participatory Rural Appraisal information for the food industry firms in the study zone, hence from the answers to questions 1-3, as well as additional pointed questions in the local-meso study.

For example, in the India dairy case, this question set implies understanding, inter alia, the labour intensity (per unit of output) of the different technologies linked to restructured versus traditional market channels, and thus to infer the effects of restructuring on the rural labour force.

3. The Operational Approach of Component 1

Component 1 addresses the research questions presented above via field surveys to collect primary data and qualitative observations from local villages, farmers, wholesalers, processors, retailers, and other key informants. This section provides reviews the four main activities that combined represent the planning, execution, and dissemination of findings from this field work.

3.1. Methodological workshop

The International Methodology Development workshop held in August 2005 (at which a draft of this document was presented) included a discussion of Component 1 objectives, steps, and methods. To elaborate the methods, we took as a point of departure the method (see Reardon et al. 2004) designed during Phase 1 of the Regoverning Markets program, that had been piloted in Central America but drawing on several additional points and on recent experience in China and Mexico.

The main differences between the methods document draft and the present final version were based on comments at the workshop: (1) add a local-meso module to complement the national-meso and micro modules; (2) make more explicit the importance of effects of restructuring on rural labourers; (3) emphasize the importance of all three segments of food industry (retail, processing, and wholesale), making clear that the study is not focusing only on retail restructuring; (4) emphasize that the studies are using both quantitative and qualitative variables; (5) emphasize that the studies are examining producers both as individuals and as collectives where relevant; (6) strengthening the cross-country and cross-regional comparison aspect; (7) make sure that macroeconomic variables such as the overall policy and business environment figure in the national-meso module. All these have been incorporated in the present document.

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At the workshop, the countries and cases were selected and are noted below.

3.2. Empirical research – Country Studies The research questions will be addressed through a well-coordinated set of eight country studies. The locations of the studies were decided in the methodology development workshop. The locations reflect variation over two dimensions:

The first is variation over (country) stages of food industry restructuring, reflected in the variation over degree of concentration in the segments of the food industry and thus levels of modernization of agri-food markets. That concentration is proxied by the share of modern retail (supermarkets and hypermarkets and convenience stores) in urban food retail and the share of large-scale processors and food manufacturers in the processed foods sector.

The second is variation over (country) farm sector structure. That structure is reflected in a number of variables, but a useful one here is skewedness of farm size distribution. It is, however, a complex task to class countries by this criterion for our purposes. For example, in countries as diverse as China, India, Poland, Mexico, Kenya, or Zambia, the dairy sector is made up mainly of many tiny farms. But the dairy processing sector is much more concentrated in Mexico and China than in India, Zambia or Kenya. Moreover, while the grains and livestock farming sector have very large farms in a number of Latin American countries, the typical vegetable farm for the domestic market in Mexico, Guatemala, China, or Indonesia – is very small, with of course variation around the mean in all of those countries. Thus, if one is studying effects of retail concentration on vegetable farming, most of Latin America, China and Indonesia do not differ much in terms of farm structure.3 If one is studying the livestock farm sector for those same places the farm structure is vastly more concentrated in Latin America than in the Asian countries. An important point here is whether there is a segment of medium to large producers on which supermarkets can rely (at least up to certain supply limits) and easily establish direct relations. That is the case in which one most naturally finds exclusion of small farmers as supermarkets have “options.” Where “all” farmers are small, exclusion can still occur, but this time not according to land category but by non-land assets category. While land distribution is easier to know a priori in making case study choices, knowing non-land asset distributions is much harder, basically not feasible without a survey.

It is ideal to maximize the variation of these two variables over case study countries, while limiting the variation in product and food industry segment. That is to have a mix of food industry segments’ restructuring and product types, such as a mix of produce and dairy processing studies over the countries. That was in fact decided in the workshop. This provides inter-segment and inter-product variation. In the case of dairy, there is interplay of processing, retail, and wholesale restructuring, and in the case of produce, between the retail and wholesale restructuring.

The eight countries and corresponding products chosen for case studies include4:

Country India ZambiaOrMozam.

China IndonesiaOr Philippine

SouthAfrica

Mexico Turkey Poland

3 This is illustrated in Central American case studies (see Balsevich et al., 2004, Hernandez et al. 2004, and Flores (2004). These show that while most of the tomato and lettuce farmers selling to supermarkets are “small” in terms of land size (and at most small-medium), they tend to be substantially more “capitalized” than the average small farm, and thus be in the upper tier of small farmers in terms of assets (productive, human, organizational). 4 A final decision will be made in November 2005 between Mozambique and Zambia, and between Indonesia and the Philippines.

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sStage of Food Industry Restructuring

Initial Initial Interm. Interm. Interm. Advan. Advan. Advan.

Products Dairy FFV FFV FFV FFV FFV FFV Dairy

The studies will be conducted according to a common or unified methodology laid out in this document. It will include the following main activities, focused in each country on the segments of the transforming food industry, on the key products noted, and on several key zones of production of the primary products.

Action Plan Component 1

October 31, 2005 Component 1 leaders provide final revised version of the component background paper and draft questionnaire format for module 3

November 30, 2005

Proposals from identified and candidate country teams are received by Component 1 leaders, the regional coordinators, and Regoverning Markets Director

December 15 2005

Final selection of teams

January-June 2006 First two modules (national-meso and local-meso) are implemented. Policy ‘champions’ selected and policy process launched.

May 30-31, 2006 Workshop in India (tbc) for C1 teams with regional coordinators and C1 coordinators to discuss specific plan for module 3 (micro)

July 31, 2006 Deadline for the draft reports of the modules 1 and 2 of the case studies, elaborated by the country team and approved by the regional coordinator

August 2006 Country level policy stakeholder workshops to review and comment draft reports

July-August 2006 Review of the draft reports of modules 1 and 2 by the component coordinators. Elaboration of the final reports by the country teams. Draft synthesis of the emerging issues by the component leaders.

August 2006 Visits by C1 coordinators to selected country study sites for design of module 3

September 2006 Mid-term workshop

October 2006 Finalize module 3 plan and select farmer sampleNovember 2006 – February 2007

Module 3 survey

March 2007 Data entry and cleaningApril-May 2007 Module 3 data analysis; planned (tbc) meeting in Beijing of the teams to

undertake a portion of analysis together and receive technical support and undertake collegial exchange and comparison in a group

May-June 2007 Module 3 report writingJune 30, 2007 Module 3 report submittedJuly 2007 C1 coordinators review Module 3 reports, provide commentsAugust 15, 2007 Deadline for country case studies of module 3 to be finalized, submittedAugust 15-September 15, 2007

C1 coordinators write draft synthesis of country case studies for C1

End September 2007

Synthesis global workshop

October 2007 Country-level synthesis workshops to get insights from policy 7

stakeholdersNovember 2007 Revisions and finalization of country studies and global synthesis papersDecember 2007 Final synthesis paper and methodological guide by the component

leaders

Each study will be carried out by a national research team, with support and oversight provided by the regional coordinator. The Component 1 leaders (Reardon and Huang) and other members of the working group will provide professional advisory support as necessary. The teams contracted with conducting each study will be identified by the Regoverning Markets consortium, not necessarily be from among its members. The key criterion used in this selection will be a track record of relevant research and methodological knowledge.

The two Component 1 leaders will (a) play a major role in guiding and backstopping all the projects under their component; (b) play a major role in writing and/or outlining and reviewing the final Component synthesis documents, and, (c) organize and edit the final publications of their component.

The regional coordinators will play a major role, in conjunction with the Component 1 coordinators and others in the consortium, in suggesting potential country team leaders. The regional coordinators will support those potential project leaders in preparing proposals. The country proposals will then be vetted by the Component coordinators, with input from the regional coordinators and others in the consortium. The regional coordinators (with the exception of East Africa, in which there are no case studies in this component), like the Component coordinators, will be limited to a maximum of one project each in terms of direct participation, but will lend support to all the projects in their regions.

It is important that each selected national research team has a proven capacity and track record in several domains in senior parts of the team: (1) food industry/agribusiness economics, especially important for module 1 of Component 1; (2) agricultural economics/economics expertise in particular in farm/farm household economics; (3) a track record of farm household surveys and rapid reconnaissance industry studies; (4) knowledge of the qualitative/PRA techniques; (5) a national and international publication record from the above work; (6) policy and stakeholder contacts.

In all cases, the teams will have to submit a proposal that will be peer-reviewed for quality assurance purposes by the coordinators and advisors of Component 1, with the support of external anonymous reviewers.

3.3. Capacity building of national researchers

For each country study, the project plans to support the participation of 1-2 Ph.D. students or postdoctoral fellows from the country in which the study is conducted.

3.4. Inter-country and inter-regional comparison and global synthesis

The rationale behind a global program is to be able to address questions of relevance to countries and regions throughout the world, and to see if there are regional and global patterns in the answers. If so, then the basis will have been laid for the concept of anticipatory strategic policy advice. Moreover, the selection of countries at different points in food industry restructuring allows “seeing around the corner” and anticipation of policy issues that will arise as the restructuring continues.

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The results of the eight national studies will be synthesized, taking into consideration the contributions from other research programs and organizations not affiliated with the Regoverning Markets consortium.

Two synthesis papers will be written: The titles here are indicative and inelegant because we want to show the content of the papers explicitly.

1. Patterns in and Determinants and Effects (on farm technologies and incomes and local labour and land markets) of farmers’ marketing strategies in developing countries (based on farm household survey), based on micro analysis concerning farmer (individual and collective) choice of market channels and accompanying changes in practices (technologies, institutions, organizations) in the face of restructuring food industries, hence summarizing the farm-survey and local-meso survey evidence on these themes and their implications for policy and for civil society and private sector strategies.

2. Patterns in, and Determinants of Evolution of agri-food marketing chains (or restructuring) in the developing countries, based on the meso analysis of food industry restructuring and commodity value chain change, summarizing the national-meso and local-meso evidence on these themes, and their implications for policy and for civil society and private sector strategies.

The coordinators of Component 1 will write these synthesis papers, in collaboration with representatives of the research teams (who in turn draw from policy learning workshops at two points in the field studies) that were involved in the eight studies of Component 1, will be intimately and actively involved in the preparation of these synthesis papers.

3.5. Dissemination of findings and connections to policy

The drafts of the two synthesis papers, and the reports from the eight country studies, will be presented and discussed together with emerging findings and lessons learnt from components 2 and 3 in a two-day International Workshop of leading researchers and private and public opinion and policy makers (about 50 participants selected for their outstanding regional and/or global leadership in the issues covered by the program).

Under Component 1, a small fund will be retained to support with small grants the participation of the researchers and the component leaders in regional or international multi-stakeholder meetings that have a high potential of making an impact on private or public policy or opinion. Participation in purely or largely academic meetings will not be supported.

There will be a simultaneous interaction between the projects in Component 1 and the policy learning platforms developed or supported under Component 3--Learning Processes and Policy Dialogue.

Finally, the program will undertake to publish a Special Issue of a leading international policy-oriented journal, in order to influence the global information base on which the policy and development strategy debates draw. This Special Issue will include the best four articles from the empirical research projects and the synthesis papers.

4. Specific Methods for the Modules

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This section is organized in the order of implementation of the modules, from national-meso to local-meso to micro.

4.1. Module 1: The National (Meso) Study of Industry or Market Level Restructuring

In this section we discuss the meso component. We first lay out a simple structure for the module, illustrated with actual study questions. The specific questions will vary in obvious ways according to the product and restructuring segments studied, so we just use an illustration – the dairy industry – that covers several restructuring segments. No questionnaire is needed, as this component is based on semi-structured interviews with a simple list of questions to guide the researchers. It is suggested that the post-doctoral fellows or senior researchers do these interviews themselves rather than delegate to junior staff, due to the delicate nature of contacts with companies.

4.1.1. General Structure and Themes of the National-Meso Module

The module undertakes a description and analysis of the evolution of restructured food industry segments at a national level over a period of 10-15 years. The themes, focused on the specific product(s) where possible, include:

(a) per segment (of the food industry), the key patterns in the dynamics of market restructuring (e.g., consolidation, trans-nationalization, emerging and disappearing market agents); and per segment, the determinants of the restructuring (e.g., key macro policy changes, foreign direct investment (FDI), trade liberalization, changes in consumer behaviour and purchasing power);

This activity is based on secondary data, literature review and a large number of interviews with key informants in the private sector, in governmental and non-governmental organizations, in universities and research centres, and producer and SME associations. One by-product of this activity is the selection of the specific products within the general category of product already selected (for example, which fruits and vegetables under the general rubric of FFV) which are broadly illustrative of the key market restructuring trends for the general product category chosen, on which to focus the following activities. This activity allows us to refine the initial research hypotheses for each of the four research question sets.

(b) per segment, analysis of the trends in the evolution of procurement systems, and when applicable, the relations between them. Procurement systems are analyzed as value chains for the purpose of this activity. This activity includes in-depth interviews with a large number of participants in the market chain, from top managers of major retail and processing firms and wholesale companies and field brokers. For purposes of comparison, a similar analysis is conducted of the traditional markets and procurement systems for the same product or set of products. The largely qualitative data derived from this activity is critical to answering the research questions and, in particular, to aid in the interpretation, and the formulation of questions in the other two modules. (Note that during this analysis, examples of innovation and potential good practice may be identified which could be explored within the framework within the activities of Component 2.)

The restructuring of an agrifood chain, such as dairy, can be thought of as a set of changes (that might be simultaneous or cascading/recursive in practice, or they might be independent, depending on the product and country), from (1) the restructuring of the retail segment, to (2) the restructuring of the processing segment, to (3) the restructuring of the

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wholesale segment; (4) to changes in behaviour at the farmer level. The general conceptual framework that can be applied to each of the first three segments is presented below. We draw on Reardon et al. (2005) which happens to focus on the retail transformation case, but the heuristic conceptual framework showing patterns, determinants, and effects, is broadly applicable to all three segments of food industry and their restructuring.

A first illustration here is the restructuring of dairy product channel involves: the restructuring of retailing (with the rise of supermarkets and other modern retail)

and the sourcing practices of modern retailers; the restructuring of the dairy processing segment (with the rise of large-scale dairy

processors); the restructuring of the wholesale sector for dairy products, with the rise of

specialized/dedicated wholesalers to source from medium and small processors while the large processors interface directly with the supermarket chains. An example of this three way restructuring is found in Dries and Reardon (2005) for the Russian dairy industry, or for the simultaneous (and symbiotic) restructuring of the first two segments, see Farina et al. (2005) for the cases of Argentina and Brazil. A vary similar triple restructuring can be found in the beef industry; see the example from Nicaragua and Costa Rica in Balsevich et al. (2004).

A second illustration is the restructuring is in the fresh fruit and vegetable (FFV) industry/market. There are two variants on this, early and latter stages:

This restructuring can be mainly in the wholesale market, as in the early stages of overall market transformation when retail (say of vegetables) is dominated by the traditional retail sector, but the wholesale market is restructuring. The latter can include the rise of wholesale markets as large centralized structures (a shift from fragmented “truck markets”), as one found in Brazil in the 1960s/1970s and in China in the late 1980s and 1990s. That transformation of wholesale markets also usually carries with it a differentiation of types and levels of wholesalers (large wholesalers, networks of small brokers), a shift from the earlier fragmented system of local small brokers converging on truck markets (Reardon and Timmer, 2005).

Alternatively, this restructuring can be in both the retail and the wholesale market. This tends to be in the later stages of overall market transformation when supermarkets begin to have substantial penetration of the FFV retail sector, such as Brazil in the 2000s. Supermarkets begin to shift away from the complex wholesaler/broker structure and large traditional wholesale markets set up in the 1960s-1980s. They begin implementing the procurement system change noted below, including increased reliance on direct procurement from farmers or more commonly, reliance on specialized/dedicated wholesalers who retain a foothold in wholesale markets but begin to backward integrate into packing plants and de facto contractual relationships with farmers (see Mainville 2004 for Brazil, and Reardon et al. 2005 for the emerging case in several FFV items in Mexico).

For simplicity we use an example to illustrate the module conceptually, with two parts (as discussed at the start of this subsection): (1) the restructuring of the food industry segments in the chain; (2) transformation of the procurement systems of each segment which then condition the relations of a given segment with its supplier upstream. We present the conceptual framework while illustrating it with the example of the restructuring dairy products chain in India, to be consistent with the illustrations above5. 5 Reardon et al. 2005 lay out the conceptual framework for retail and wholesale segments restructuring, and use fresh fruits and vegetables chain as the illustration, and add evidence from recent work including work part of the Regoverning Markets project phase 1 (in collaboration with other projects) in Central America as well as Kenya and

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In general any case under study is a mapping of a value chain or product agrifood system, all of which take this general form:6

Production input suppliers farmers first-stage processors/packers wholesalers/distributors/transporters second-stage processors/packagers retailer consumer

Recall that we define the channel by the product and the restructuring food industry segment leading the channel, or co-leading it, so that we can say “the large-processor dairy product channel” as the case (which is not under-emphasizing that there is concomitant restructuring in the retail and wholesale sectors that are studied as part of the module).

To illustrate the operationalisation (“implementation”) of the general conceptual framework for a specific case, we in fact choose that channel, and show a combination of retail and processing and wholesale segments restructuring. Think of the conceptual framework as decomposed into modules corresponding to the restructuring segments of the dairy system, and for simplicity, think of them as a set of changes that depending on the context can be cascading, simultaneous, or to some degree, independent.

The module can be broken up into a cascading set of submodules for the set of restructuring segments, including processing, retailing, and wholesale. As an illustration, we show one of these sub-modules here, the one focusing on the processing segment. The other sub-modules would be analogous, but with wholesale and retail segments as the foci. Examples of this kind of research on dairy segments restructuring can be found in Dries and Reardon (2005) for the case of Russia, and the issues in Farina et al. (2005) and Dirven (2001) for Brazil and Argentina, and Chile cases, and Dries and Swinnen (2004) for Poland, respectively. The specific issues will of course differ by country, but with some broad similarities.

4.1.2. Dairy processing restructuring illustration.

In this subsection we present an illustration for a dairy processing study.

Patterns in demand (downstream). Here one compares large- or medium-scale modern processors of dairy products with traditional small-scale processors.

(1) What is the demand (by retailers, comparing supermarkets and traditional retailers) for large-scale dairy processor services (proxied by observed purchases or sales) relative to traditional processors? What do the “data” say about the (theoretically relevant) determinants?

(a) relative time/transport cost and transaction risk of sourcing from large-scale modern processors versus traditional small scale processors?

(b) relative price of large-scale processors’ dairy products versus traditional processors – controlling for type and quality

(c) product diversity and quality/safety attributes (large-scale modern versus traditional)

Brazil evidence.6 Of course, for a given product and a given channel, some of these segments might be missing or others added; for example, producing a common tomato for a traditional local market might involve just the tomato grower and an informal trader that acts as both wholesaler (collecting from the farmer) and retailer (selling to the villager).

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(d) per capita income levels (such as in different consumer strata) and growth (hence derived demand via supermarkets for quality milk products)

(2) What is the supply of large-scale dairy processor services in the country? In terms of quantity, product diversity, quality and safety attributes, and so on? What do the “data” say concerning these (theoretically relevant) determinants?

(a) FDI in processing

(b) Procurement system modernization, reflected in observable investments in physical, organizational, and institutional capital and practices: Centralization of procurement of milk from farmers? Centralization of distribution centres to deliver dairy products to retailers? Implicit contracts via preferred supplier systems with dairy farmers? Private standards for milk quality? For milk safety?

Again, it is necessary to understand the dairy processors’ objective function in adopting (or not) changes in the procurement system of milk from the farmers – and NOTE – to determine whether and to what extent these objectives are derived from the requirements of the retailer, or from company global policy, or from legal regulations, or some other motive, to:

(1) minimize milk cost (2) minimize transaction costs (3) maximize milk quality (which can also reduce processing costs)(4) maximize product diversity to seek or counter spatial monopolistic competition

The choice vector of the procurement offices of the processing firms. These choices are:

continue to buy from the traditional wholesale markets the milk needed, hence spot market;

buy direct from farmers; buy from specialized/dedicated wholesaler who (mainly) buys direct from a preferred

supplier list of farmers (imposing the standards of the chain, and using implicit contract/preferred supplier system.

How can the observed choices be explained? Again, that is revealed in qualitative interviews with the procurement offices of the processors (and comparison through interviews with traditional processors). What do the “data” say concerning the importance and nature of the following:

(1) the capacity of the traditional wholesale market to meet procurement officer objectives;

(2) alternatively, the expected and observed capacity (and cost) and willingness of local farmers to supply the processor directly

(3) alternatively, the ease (cost) of sourcing the milk that meet the above attributes internationally (such as in the Russian case from fresh milk shipment over borders or powdered milk imported);

(4) the cost (for example the interest rate) of the investment needed to meet the objectives; to that can be added the costs imposed by certifications and regulations;

(5) the capacity (such as financial and management capacity) of the processor to undertake investments to meet the objectives;

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(6) the price vector of the competitors, hence cost competition among processors and with traditional processors, per retail – hence consumer - segment;

(7) quality and product differentiation of the products sold by competing processors, combined with retail (hence consumer) effective demand for those attributes;

(8) threshold firm size to justify investments in procurement system change;

(9) the “importance” of restructured retailers’ demand in the processors’ competitive positioning

How the meso restructuring “translates” to changes in conditions facing farmers. This set of questions is asked in a general, national way in this module, and then in a local, contextualized way in the module 2, the local-meso module.

In general, a restructured market channel represents, relative to a traditional market channel, different (usually more demanding) product attributes7 and transaction attributes8 required of farmers, processors, and wholesalers. The differentiation of those attributes is determined by the difference in the procurement system of the restructured dairy industry segment(s) and the marketing strategy of the latter toward their client (such as product differentiation).

The differential demand (between restructured and traditional channels) of product and transaction attributes potentially translates into different requirements of technological (pre and post harvest), managerial, organizational and financial capital on the part of farmers. Those requirements imply differential costs to enter and stay in restructured versus traditional channels.

To the extent that the benefits (in terms of higher price and/ or lower risk) of entering the restructured channel on average outweigh the additional costs, the restructured channels are good opportunities for the average farmer. Note that the costs should be estimated as “net costs” in that some potential costs are footed by the food industry firm for the farmer (in the form of technical assistance, implicitly subsidized credit or transport, and other benefits sometimes provided by the food industry firm to the farmers to resolve idiosyncratic factor market failures or make supplying them more attractive, winning them away from traditional channels and locking them into new technologies that imply asset specificity to the channel. Those benefits are sometimes offset by fines or other punishment for contract infringement.

7 Product attributes are specified by product grades and standards. A standard is a variable, such as the set of quality and safety attributes specified. A grade is a level for a given standard; hence there could be a standard for residual of pesticide x on a piece of fruit, and a grade for that variable is the maximum amount of that residual allowed. Product attributes include quality (e.g., color and size), safety (e.g. bacterial, hormone, or pesticide residues), and characteristics of production processes (such as “bird friendly”). Product standards specifying those attributes can be “outcome” or “process” standards. Outcome standards specify attributes of the product at a particular point in the chain, say reception by the retailer; for example, an apple received by the retailer must be x size, y color, and have w and z levels of bacterial and chemical residues on it. By contrast, process standards specify particular technologies to be used pre- and post-harvest. 8 Transaction attributes are a vector of characteristics of the transaction between the seller and buyer. Controlling for the product attributes, the transaction attributes include volume at a point and over time, timing, presence of a contract that organizes the transaction, and so on. Note that the term “contract” is quite general, using Hueth et al. (1999) definition, where two parties agree to specifications for the product and the transaction, and there is – some- penalty for withdrawing from the transaction (from intangibles like loss of reputation to tangibles like fines). The contract can be written or verbal, formal or informal. Hence, a contract can be as “informal” as inclusion, with a verbal accord, or a farmer in a preferred suppliers list, or as formal as a written legally enforceable contract

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That the average farmer may face a net benefit does not mean, however, that all farmers can net-benefit. There may be farmers that are “investment poor” with respect to the market channel (Reardon 2000), lacking the specific assets needed, such as a skill set, or irrigation, or an effective organization to bulk product to the required volume. Knowing the required asset set for a particular channel can help policymakers estimate “investment poverty maps” with respect to the restructured markets and identify vulnerable groups as the restructured market channels become dominant.

The identification of who can and do participate, and what concomitant behaviours they undertake, is the subject of micro analysis to which we turn next.

Policies and programs, associations, and other context. These questions will obviously be highly specific to each country, product, and chain. This part of the module involves understanding the ways that programs and policies and other organizational, cultural, and institutional factors have moulded the way that the chain has restructured. In turn, this information is crucial to form “qualitative shifter variables” in the micro part of the study.

4.1.3. Operational Issues for the national-meso Study

We proceed to issues of sampling and operationalisation.

It is important to note that depending on the geographical boundaries of the segments, and parts thereof, of the agrifood chain being studied, portions of this module can be addressed in the local-meso module, and vice versa. For example, in Mexico we found in the guava sector that the wholesale sector had its main interface with the retail sector in Mexico City, but a subset of the wholesalers, and a host of local brokers, also operated directly and had part of their headquarters in Michoacan, the main guava production zone. Hence we undertook the equivalents of the national-meso module in Mexico City, and the local-meso focus groups with wholesalers and brokers – inter alia – in the production zone of Michoacan where we undertook also the micro survey.

With the above qualification about which interviews and actors are “mapped” to which module, we note here that interviews are to be conducted with relevant representatives from each significant agent in each market channel and each product, including:

(a) Organized and un-organized farmers(b) Leaders of farmers’ organizations (coordinating where possible with Component 2)(c) Wholesalers (both dedicated and non)(d) Processors (e) Alternative clients for farmers in relevant local, regional or national markets

(including informal traders or middlemen)(f) Procurement officers and other staff in the relevant restructured food industry

segments (supermarkets, modern food service, large scale processors, and/or wholesalers) who deal directly, on a day to day basis, with agents upstream from them (the other food industry segments upstream from them, the farmers and farmers) and downstream (the other food industry segments downstream from them)

(g) Private suppliers of support services to producers, traders or processors (technical assistance, credit, third-party certification, brokerage, market and price information...)

(h) Relevant governmental organizations and community leaders

For effective and convincing analysis and results, the comparison and triangulation of data from diverse actors is essential.

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Each study will follow an iterative process moving from one end of the chain (the food industry segments) to the other (i.e. the farmers) to clearly identify key information, triangulate data across actors and answer questions that arise during the fieldwork.

(a) The starting point will be semi-structured interviews with the relevant food industry segment to identify key issues related to chain governance (both legislative and judicial/executive) including specific contractual arrangements with the farmers and SFO and executive functions performed by the later, production and post-harvest technology requirements and income implications.

(b) The second step of the case study will focus on wholesalers – both dedicated and non – as well as middlemen that work with the farmers and SFO by revisiting their governance functions in the chain. Greater emphasis will be placed on support services provided to the farmers and SFO directly by the wholesalers or through third parties.

(c) Finally, semi-structured interviews will be organized with farmers and SFO members either individually or in a focus group and SFO leaders. In these sessions, key wholesalers, middlemen, private service providers, government agencies and community leaders will be identified.

(d) Based on information from supermarkets, food service, and/or processors and/or wholesalers and the SFO, semi-structured interviews with private service providers and relevant government agencies will proceed to identify support strategies that do or do not facilitate on-going farmer and SFO participation in the supermarket channel.

(e) Finally, previously identified community leaders will be interviewed to assess the larger economic and social impact of participation in the restructured markets.

4.2. Module 2: Local-Meso Module, using Participatory Rural Appraisal

A second “meso” level analysis is needed, this time at the local level, in the area where the farm survey is conducted. This analysis is used to extend to a specific zone the meso study conducted at a national level, thus understanding the interface between the downstream segments of the chain, such as retailers and second-stage processors in large urban areas that are analyzed in the national-meso module, and the upstream segments of the chain in the farming areas. This “in-between” domain is that of the local institutions, organizations, and society that govern the way the broader market forces translate into specific opportunities and incentives, as well as challenges, for local producers. That “in-between” domain comprises also the first-stage processors, local wholesalers and brokers, local producer organizations zones, and local retailing options facing the producers. The knowledge generated by this module completes the value chain analysis (complementing the information of the national-meso module) and serves to sharpen and mould the micro level questions for the farmer survey.

4.2.1. Objectives

The local-meso module has three objectives:

(1) Systematic use of semi-structured focus groups (using a PRA, or Participatory Rural Appraisal method) in the local area (of the producer-level study zone) to understand the local manifestation of the segments of the food industry under study, including where relevant retail, processing, and wholesale/brokering segments, and supplier segments of the chain, in particular the collective organizations and associations

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involved in the market. The research questions are similar to those posed at the national level for the same chain, with respect to the patterns and determinants of restructuring and the organizational, institutional, and technological implications for producers.

(2) Systematic use of PRA techniques to understand the policy, politico-social, business environment, and institutional and organizational context determining power relations in the agrifood chain(s) under study in that zone.

(3) Use of PRA techniques to have policy dialog with key stakeholders relevant to the product and agrifood chain in question in the zone(s) in order to have the maximum relevance of the study and appropriateness of design, and the maximum useful policy impact and relevance for the stakeholders (see Adamo, 2003, and Lindquist, 2004).

4.2.2. Methods

The method to be used is a “Participatory Rural Appraisal” (PRA). Background on this method can be had in Epstein (accessed 2005), Chambers (1994), and World Bank (accessed 2005). We draw on these, in particular the World Bank resource, here.

“PRA is a label given to a family of participatory approaches and methods that emphasize local knowledge and enable local people to make their own appraisals, analyses, and plans. PRA uses group animation and exercises to facilitate information sharing, analysis, and action among stakeholders. The purpose of PRA is to enable development practitioners, government officials, and local people to work together to plan context-appropriate programs, in this case first of research, with the goal of planning follow up actions in the sector.”

“PRA evolved from rapid rural appraisal (RRA) - a set of informal techniques used by development practitioners in rural areas to collect and analyze data. RRA developed in the 1970s and 1980s in response to the perceived problems of outsiders missing or mis-communicating with local people in the context of development work. In PRA, data collection and analysis are undertaken by local people, with outsiders facilitating rather than controlling. PRA is an approach for shared learning between local people and outsiders.”World Bank (2005) lays out the key tenets of PRA:

“Participation. Local people's input into PRA activities is essential to its value as a research and planning method and as a means for diffusing the participatory approach to development.

Teamwork. To the extent that the validity of PRA data relies on informal interaction and brainstorming among those involved, it is best done by a team that includes local people with perspective and knowledge of the area's conditions, traditions, and social structure and either nationals or expatriates with a complementary mix of disciplinary backgrounds and experience. A well balanced team will represent the diversity of socioeconomic, cultural, gender, and generational perspectives.

Flexibility. PRA does not provide blueprints for its practitioners. The combination of techniques that is appropriate in a particular development context will be determined by such variables as the size and skill mix of the PRA team, the time and resources available, and the topic and location of the work.

Optimal ignorance. To be efficient in terms of both time and money, PRA work intends to gather just enough information to make the necessary recommendations and decisions.

Triangulation. PRA works with qualitative data. To ensure that information is valid and reliable, PRA teams follow the rule of thumb that at least three sources must be consulted or techniques must be used to investigate the same topics.”

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“PRA is an exercise in communication and transfer of knowledge. A series of open meetings (an initial open meeting, final meeting, and follow-up meeting) generally frame the sequence of PRA activities. Other tools common in PRA are:

Semi-structured interviewing Focus group discussions Preference ranking Mapping and modeling Seasonal and historical diagramming.”

The World Bank (2005) recommends the following organization of the PRA. “A typical PRA activity involves a team of people working for two to three weeks on workshop discussions, analyses, and fieldwork. Several organizational aspects should be considered:

Logistical arrangements should consider nearby accommodations, arrangements for lunch for fieldwork days, sufficient vehicles, portable computers, funds to purchase refreshments for community meetings during the PRA, and supplies such as flip chart paper and markers.

Training of team members may be required, particularly if the PRA has the second objective of training in addition to data collection.

PRA results are influenced by the length of time allowed to conduct the exercise, scheduling and assignment of report writing, and critical analysis of all data, conclusions, and recommendations.

A PRA covering relatively few topics in a small area (perhaps two to four communities) should take between ten days and four weeks, but a PRA with a wider scope over a larger area can take several months. Allow five days for an introductory workshop if training is involved.

Reports are best written immediately after the fieldwork period, based on notes from PRA team members. A preliminary report should be available within a week or so of the fieldwork, and the final report should be made available to all participants and the local institutions that were involved.”

4.3. Module 3: Micro Level Decision Making -- Participation in Restructured Market Channels and/or in Traditional Channels, and Attendant Behaviors

The two meso level modules lead to an understanding of the market signals and requirements emanating from the downstream segments of the food industry. These signals and requirements are, in particular, prices, and product and transaction attributes or standards that farmers must meet to access particular market channels.

To understand in turn how those signals and requirements affect farmers’ behaviour and welfare, a “micro” level analysis, specifically at the level of farmers, is required. The analysis is based on a survey of farmers and their farm level and organisational behavior. That analysis aims at:

(a) understanding the patterns and determinants of producers’ strategies and responses to restructured markets,

(b) comparing those with their strategies toward alternative, traditional markets;(c) understanding the net effects, in costs and benefits, of participation in different

market channels, restructured and traditional.

4.3.1. The basic conceptual framework

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Let us for convenience in this methodology discussion abstract for the moment from with which product, country, and food industry segment(s) that are restructuring.

The choice set of the farmer in this simple conceptual framework is of two choices: (1) choose the “restructured market channel” versus the “traditional channel;” (2) choose the “new technology” versus the “traditional technology.” He we use a simple model, from the economics literature (Sadoulet and de Janvry 1995) of the farmers’ choices of these behaviours. The functions are as follows:

Output supply = f(output prices, input prices, risk, vector of quasi-fixed capital, shifters)

Input demand = f(output prices, input prices, risk, vector of quasi-fixed capital, shifters)

Now, it is easy for us to rewrite this standard economics conceptual framework to have each function a binary choice fit to our double choice scenario above:

Output supply to restructured markets (versus traditional markets) = f(output prices (in the two channels), input prices, risk, vector of quasi-fixed capital (of the farmer and his/her area or organization), shifters)

Input demand for inputs among farmers selling to the restructured market versus the traditional market = f(output prices, input prices, vector of quasi-fixed capital of the farmer and his area and his organization, and shifters, conditioned on choice of marketing channel)

Note that we show the market choice to be binary, but we can easily specify it as shares over the market channels (and thus the portfolio of market strategies of farmers), which then would be the composition of output supply from the farmer to a set of market channels.

Note that as an adoption (of market channel or technology or both) conceptual framework it is customary to introduce a vector of variables for “risk and uncertainty” into each of the equations.

The above conceptual framework is a simplified form of the entire micro analysis of Component 1. In the rest of this section we “unpack” it conceptually, and then below we show how to get the information for this conceptual framework from a survey. In the “unpacking” we will, however, continue to avoid distinctions between types of restructured markets (thus complicating the discussion with the various food industry segments or products). We will reserve the complication for the discussion of categories of technologies.

Note that the costs and benefits of choosing the restructure market channel (versus the traditional) are calculated based on the observed behaviour, including net sales and costs of the choices of the market channel and the technology used.

What is the farmer choosing when he/she chooses the restructured market channel? The “channels” in the “channel choice” analysis are actually vectors or sets or packages of transaction attributes that include payment terms, transaction terms such as implicit contract terms and conditions (such as monitoring, standards specified, etc.), and risk and periodicity. That is, implicit in choosing one or the other channel is that he/she may get paid more or less, paid differently (sooner or later), and be implicitly required to undertake a certain technology after entering the channel, or be doing a certain technology before entering the channel (think of this capitalized-technology for example as “irrigation”).

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On the one hand, we can use observed differential conditions and terms of various channels to define the channel choice set; that becomes more necessary when one wants to model more than two channels or when one needs to “map” in various observed channels into the binary categories of restructured versus traditional. For example, in Nicaragua we faced the issue of whether to lump the leading and second tier chain into one channel (“supermarkets”) or maintain them as separate choice channels. Or one can do the opposite, use the differences in conditions and terms of observed channels to make the choice set richer and enter into the nuances of a mixed, diversified market portfolio strategy.

On the other hand, one can use knowledge of terms and requirements to hypothesize signs on the coefficients of the various determinants. For example, if one knows that entering the restructured market channel requires agronomic skill to meet the requirements, all else equal, one expects agricultural education or experience in the crop to affect channel adoption.

What is the farmer choosing when he/she chooses the new versus the traditional technology? Let’s use an example to illustrate. A common requirement of a dairy processor is to receive milk all year from a farmer. Assuming seasonality of rainfall, and assuming the farmer cannot practice transhumance, and assuming away for the moment fodder markets, the farmer needs irrigation of his/her fodder crops to feed his/her cows all year to produce milk all year. Now, there is a set of inputs needed to produce milk all year (perhaps inoculations, milking equipment, etc., plus irrigation to produce fodder to produce milk), but all else equal, economists would say that irrigation in this case is “technology-embodying capital” and that investment in or adoption of that capital, is a proxy for adoption of that technology. The “new technology” can then be a vector of such capital along with variable inputs needed for certain product attribute outcomes. For example, in guava production in Mexico, there is a set of chemical inputs needed to produce guavas of premium quality or better, which is the minimum amount bought by the supermarket or restaurant sectors.

The set of product and transaction attributes required by the restructured channel, discovered in undertaking the meso studies, in principal imply the set of required new technologies; for example, if the fruit must be spotless, and abstracting from organic practices to achieve that, the implied specific set of new technologies is a set of chemicals that kills the pests that damage the fruit surface. Now, one can do a statistical study from the survey data and find out if those choosing the restructured channel then also choose the specific set of new technologies. If they do not choose the latter, then one can ask whether those specific new technologies were actually needed to meet the requirements, or those that chose the restructured market channel actually did not meet the latter’s requirements but still sold to them so that one infers that the buyers in that channel relaxed its standards to get adequate supply, or some other reason. Alternatively, if one knows from the meso study that actors in the downstream segments of the restructured channel monitor well the meeting of its standards, but one is not sure what the new technology is implied by that channel’s requirements, then one can observe the technologies used by the farmers and infer what technologies are needed to meet the requirements of that channel.

How do the choices of market channel(s) and technology together imply net income outcomes? The net income impacts are derived from the choices of channel and technology of the farmer. The market channel choice gives an output price vector, the technology choice gives the weights for the input costs vector, and given the output levels to different market channels, the net income of the producer is thus calculated.

What are the potential links between choice of market channel and technology? Theoretically, a farmer can:

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(1) Choose the marketing channel “first”, then given the predetermined channel cum requirements (volume and consistency requirements, quality standards etc.), choose technology (adjusting the technology used to the requirements of the channel); note that a variant on this is the choice of a crop which “embodies” a market channel choice; for example, if a farmer moves from semi-subsistence maize production for the local market, to the production of guava for the urban wholesale market, that brings with it a set of production requirements needed for guava itself (irrigation for example) as well as a set of pre and post harvest technology requirements to produce for the variety of market channels for guava (different degrees of application of chemicals, water control, packaging, and so on; see Berdegue et al. 2005).

(2) Choose the technology “first” (based on a large variety of possible determinants), and then choose the marketing channel that fits what he/she can do (volume, quality, etc.) based on the predetermined technology.

(3) A string of (1) and (2); for example, say one has a set of farmers in the traditional spot market and producing without irrigation. Then the government starts an irrigation program. The farmers now with irrigation choose a market channel that requires year-round supply (say the supermarket channel), and with the profits from that channel, upgrade from canal to drip irrigation for better water control, and from there enter an even more demanding market channel, say the export channel. This is actually a sequence we have observed in the field. Another sequence starts with a market shock: say a dairy processor comes to a farmer cooperative and says “we would like milk from you, are willing to pay more than the traditional market, but require the milk be cooled and delivered to us.” The cooperative might then change its technology (investing in cooling equipment and trucks) to enter that new market channel. That could start a cascade of new technology upgrading, new market channels, and so on.

(4) Choose his/her technology and marketing channel(s) simultaneously.

The first three sequences are called “recursive”. There is a simple and a complex way to conceptual framework them.

(1) The simple way is to make sure that the survey instrument captures the sequence over time of the key variables and then includes those in the equations so that the effect of lagged variables can be tested for.

(2) The complex but most interesting way is to conceptual framework the process as a Markovian chain. That is a dynamic sequence of household choices. An example is where a household chooses for example a market channel, then based on that (and the incentives and capacities that implies), chooses a technology for that market. Based on the first two steps and the earnings those together imply, the farmer might simultaneously further upgrade and choose a new market channel. And so on. This sequence could be initiated by a restructured food industry segment offering a contract to the farmer, for instance.

The above are essentially econometrics variants of implementation form and estimation methods of the basic conceptual framework. The main requirements for the various approaches will vary in terms of making sure there are observations for different periods. For example, productive capital assets observed/recalled before and after market channel choice. This can be handled in the questionnaire structure.

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In practical study form, how can the determinants of the choice of the market channel conceptualized? While the categories of variables are the vector of incentives and capacity variables noted above, and therefore “science,” one needs both science and art in fleshing out the operational, implementation variables in each category of the function for the choice of market channel. Let us think of each of these variables as a vector, and unpack each vector.

Several preliminary “tricks of the trade” should be noted:

(1) Each variable can be measured at different levels. For example, for transportation capital, one can measure this at the farm level (does the farmer have a truck? How far is the farmer’s farm from the paved road?) as well as the village or district level (what is the road density in the district?). Thus, a set of household-level and village-level specific variables are “mapped into” the theoretical variable categories.

(2) It is common that in practice one does not have a direct observation on a variable, so one has to find an observable “proxy” for that variable. For example, one might want to have a measure of market risk, such as the variation in the price of the product in that channel over the past five years. But that might not be feasible to discover. In that case, it might be necessary to proxy it with other measures of variation that are observable (for instance, rainfall variation in that district).

(3) Sometimes a proxy variable becomes problematic because it proxies too many things at once. For example, one might use a dummy variable for district to reflect infrastructure access, but the districts might also vary for other reasons such as risk differences

(4) Sometimes the variable is proxied by a the existence of a policy or regulation or program known to have some effect measured by a variable, but one does not have a direct observation on the variable, only on the program. An example is a subsidy.

The output and input price vectors are self-explanatory.

Risk can be directly measured (such as inter-year price variation in the area) and also proxied by the existence of insurance schemes, contracts, and government programs.

The capital vector is the most complex and site-specific. It comprises a number of “household and village and area characteristics” such as holdings of productive capital, organizational capital (membership), social capital, and infrastructure access.

The “shifters” (including instrumental variables for identification of conceptual framework) are the last element of the equations, and include government programs and other exogenous influences on the choice process.

This section will be added to in the final form of this document, with more specifics.

4.3.2. Operationalisation of the conceptual framework with illustrative questionnaires

A survey questionnaire must be designed, field-tested and revised repeatedly, until it complies with the following conditions:

(a) It must allow us to answer each and every research question. It must be explicit which sections and questions of the survey form will be used to obtain results to answer which research question(s). Each question in the survey form must be justified in terms of actually contributing to one or more research questions.

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(b) A farmer must be able to understand and answer all the questions. The questions must be unambiguous and clear from the point of view of the respondent, without the need for any further action by the enumerator aside from reading the questions as they are written in the questionnaire.

(c) A farmer should be able to answer the complete questionnaire within 60-90 minutes.

The questionnaire covers land use, assets, production inputs and prices, output and marketing behaviour and terms, and organization, technical assistance and credit. An example of a questionnaire now being applied in the field is available from the authors. In the final form of this document, a fully annotated version will be appended to deal with details that arise in the survey.

4.3.3. Sampling and Operational issues

It is crucial to emphasize random sampling to the extent possible, while combining sufficient variation over participants and non-participants in the restructured channels. In practice, this is one of the biggest challenges of the study, in order to obtain census or other kinds of lists from which to draw. Moreover, it is uncommon for farmers to sell directly to restructured food industry segments, such as directly to supermarkets, so it will be necessary to sample in such a way that one gets information on both the farmers, and the diversity of wholesale segments linked to various processing, food service, or retail segments. That implies a close relationship between the meso module and the choice of variables and structure of the micro survey instrument. That is reflected in the guava producer questionnaire attached.

Purposeful sampling can be undertaken, combining reasoned choice of specific areas, then random sampling within them. This is discussed in Pitt and Khandker (1998) wherein they undertook: (1) random selection of villages from a universe (thus a probabilistic choice of the villages with the desired characteristics, in their case, program participation); (2) non-random, choice-based sampling (using the choice variable from the behavioral equation as the selection criterion for households in the villages that participate in the program and a counter-sample for comparison in those villages and in the non-participating villages); (3) use of the WESML (weighted exogenous sampling maximum likelihood) estimator to deal with the non-randomness of the second stage (household) selection (increasing efficiency), combined with LIML and Fixed Effects (for village effects) conceptualizing.

5. Final Report Table of Contents

The final report of the case study will have the form of a Journal-type article, ready for publication. The article will be written in the main language of the country in which the case study is conducted, and, once reviewed, approved and edited, will be translated into English. The maximum length of the article will be of 20,000 words, including the full content, from the title to the list of references. If necessary, more than one such article can be prepared and submitted per case study, in order to cover all the important aspects of the case study; in this case, each article must be self-standing, in the sense that the reader must be able to understand it without necessarily having to read the full set of articles.

The table of comments will be thus:

1. Executive summary – A comprehensive executive summary is essential. It must give clear and sufficient information about the background of the case study, the methods used, results and conclusions and recommendations.

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2. Background – This section will provide descriptive information about the case study, its contexts, and its relevance for the country and/or region as well as for the Regoverning Markets Program.

3. Literature review – This section will review the relevant literature concerning the case study and the issues involved in the case study. It will highlight the knowledge gaps which the case study addresses, and why these are important from the perspectives of policy (public and private) and of policy research.

4. Methods – This section will present in detail the methods used to conduct the case study, both for data collection and analysis. The choice of methods will be justified. If standard, well established methods are used, this section can be shortened by providing references to the appropriate literature were the methods are described in greater detail.

5. Results – This section will present the major findings of the case study, for each of the case study questions, with the exception of lessons learned, which are covered in another section of the article. The implications of the results will be drawn out. It is essential that the overall objectives and research questions of the Regoverning Markets Program be used as key reference points for this analysis, as the case study is expected to contribute to meeting precisely those objectives and answering those questions.

6. Conclusions and recommendations – This section will highlight the critical factors that have enabled or hindered the success of the participation of the smallholder producers in restructured markets, as well as the lessons learned.

7. References – a complete list of references cited in the text will be provided.

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References

Adamo, A. 2003. Influencing Public Policy through IDRC-Supported Research: Synthesis of Document Reviews, Final Report, Prepared for the Evaluation Unit, IDRC, January.

Berdegué, J.A., A. Martinez, T. Reardon, and F. Balsevich. 2005. “Guava Growers, Wholesalers, and Supermarkets in Mexico,” Working Paper, Rimisp/MSU.

Chambers, R. (1994) 'Participatory Rural Appraisal (PRA): analysis of experience.' World Development, Vol.22. No.9: 1253-1268.

Epstein, S.T. accessed 2005. “The relationship between rapid rural appraisal (RRA) and development market research (DMR),”

Feder, G., R.E. Just, and D. Zilberman. 1985."Adoption of Agricultural Innovations in Developing Countries: A Survey," Economic Development and Cultural Change, 32 (2) (January): 255-298. 

Hueth, B.M., E. Ligon, S. Wolf, and S. Wu. 1999. “Incentive Instruments in Agricultural Contracts: Input Control, Monitoring, Quality Measurement, and Price Risk,” Review ofAgricultural Economics, Vol. 21, No. 2: 374-389.

IDRC. Accessed 2005. “Information Resources on Participatory Research and Development,” accessed October, http://www.idrc.ca/en/ev-85105-201-1-DO_TOPIC.html

Kaplinsky, R. and M. Morris. 2001. A Handbook for Value Chain Research, November: report to IDRC.

Lindquist, E. 2003. “IDRC Projects and Policy Influence: Some Perspectives to Consider,” powerpoint at IDRC Workshop “Cases, Concepts, Connections,” Ottawa, March 24-25.

Pitt, M.M. and S.R. Khandker. 1998. “The Impact of Group-Based Credit Programs on Poor Households in Bangladesh: Does the Gender of Participants Matter?” The Journal of Political Economy, 106(5), October: 958-996.

Reardon, T., J.A. Berdegué, M. Lundy, P. Schütz, F. Balsevich, R. Hernández, E. Pérez, P. Jano, and H. Wang. 2004. Supermarkets and Rural Livelihoods: A Research Method, Report for the Regoverning Markets Project, the RAISE-SPS Project, the PFID Project, and the Central American Beef Project, funded by DFID, USAID, and Common Fund for Commodities. September.

Reardon, T. and P. Glewwe. 2000. “Agriculture” and “Module for Chapter 19" in M. Grosh and P. Glewwe (eds.) Designing Household Survey Questionnaires for Developing Countries: Lessons from Fifteen Years of the Living Standards Measurement Study, Washington: The World Bank, 139-182 and 407-453.

Rozelle, S., J. Huang, X. Dong, H. Wang, and T. Reardon. 2005. “Marketing Channels with Chinese Characteristics: Petty Traders, Supermarket Giants and Poor Horticulture Producers in China,” Presentation at Pre-conference workshop on “Supply Chains and Farmers”, EAAE Meeting Copenhagen, 23 August.

Sadoulet, E. and A. de Janvry. 1995. Quantitative Development Policy Analysis. Baltimore, MD: The Johns Hopkins University Press.

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World Bank. Accessed 2005. “Methods and Tools,” in The World Bank Participation Sourcebook, accessed October

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ANNEX 1 – FORMAT TO SUBMIT PROPOSALS OF CASE STUDIES

A. THE CASE STUDY (maximum 4 pages)

Describe the specific implementation you intend for the three modules of C1, in terms of specific product(s), geographic areas, specific issues or themes (policy, organization, institutional, technological) you will address per module (under the general rubrics noted in those), and the composition of the team you will uses to undertake those modules.

B. THE STUDY TEAM AND ITS CAPACITIES

a. A statement of capacity to do the work (a list of all the team with CVs, addresses and emails, academic records and experience on rural and food industry surveys and case studies).

b. A statement that the team’s level of motivation for and commitment to the work, and why (eg fits into ongoing research and interests, part of building a long term research program, capacity building etc.)

d. Any 'matching' resources than can be brought to the work, including in-kind participation of staff and students

e. Evidence of connection to policy making in the country/region

ANNEX II CRITERIA FOR EVALUATION OF THE PROPOSALS

A. Eligibility criteria (classification in Yes/No):1. Does the proposal fall within the themes, objectives and field of interest of the C1

Component of the Regoverning Markets Program?2. Do we have sufficient information to evaluate the proposal, that is, has the format in

Annex 1 been completed?

B. Merit criteria (classification in Excellent/Good/Average/Insufficient):1. Quality of the research team. A main criterion for selection is the research team’s

familiarity and track record (experience with similar work, publications) with the thematic field and analytical and field techniques (for all three modules of C1) of Regoverning Markets C1.

2. Links to the public sector, private sector and civil society. The main thrust of the Regoverning Markets program is to influence policy change. Hence we encourage case study proposals where there is proven interest and involvement by stakeholders from the public sector, private sector or civil society.

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