Does Trade Policy Impact Food And Agriculture Global Value .
Title:Does trade policy impact food and agriculture global value chain participation of Sub-SaharanAfrican countries?Authors details: Jean Balié, Food and Agriculture Organization of the United Nations (FAO) Jean.Balie@fao.org Davide Del Prete, Food and Agriculture Organization of the United Nations (FAO) and IMT Lucca, Italy,Davide.DelPrete@fao.org eUnitedNations(FAO)Emiliano.Magrini@fao.org Pierluigi Montalbano, Department of Economics and Social Sciences, Sapienza University of Rome, Italyand Department of Economics, University of Sussex (UK), pierluigi.montalbano@uniroma1.it Silvia Nenci, Department of Economics, Roma Tre University, Italy, silvia.nenci@uniroma3.itCorresponding Author: Pierluigi Montalbano, Department of Economics and Social Sciences, Sapienza University of Rome, P.leA.Moro,500185Rome(Italy)T( 39)0649910739-F( 39)0649690329pierluigi.montalbano@uniroma1.it, and Department of Economics, University of Sussex, JubileeBuilding, Falmer, Brighton, BN1 9SN. E-mail: p.montalbano@sussex.ac.ukAcknowledgements:The authors would like to thank all the participants in the ‘European Trade Study Group’ Conference (Helsinki,Sept. 2016); the ‘FAO Rural Transformation Conference’ (Rome, Sept. 2016); the ‘Third SITES/IDEAs AnnualConference’ (Florence, Sept. 2016); the ‘Italian Trade Study Group’ (Lucca, Oct. 2016); the ‘Workshop onUpgrading in Global Value Chains in Developing and Emerging Economies’ (Bonn, Nov. 2016) for usefulcomments. The usual disclaimers apply. This research was conducted in the context of Monitoring and AnalyzingFood and Agricultural Policies (MAFAP) Program implemented by the Food and Agricultural Organization (FAO)in collaboration with the Organization for Economic Co-operation and Development (OECD) and financiallysupported by the Bill and Melinda Gates Foundation, USAID, the Netherlands and Germany. www.fao.org/inaction/mafap.1
Does trade policy impact food and agriculture global value chainparticipation of Sub-Saharan African countries?August, 2017AbstractThe most recent literature on international trade highlights the key role of global value chains (GVCs) in structuraltransformation, development and growth. The common perception is that Sub-Saharan African (SSA), unlike most LatinAmerican and Asian countries, has not been able to successfully engage into global production networks. By applying thebilateral gross exports decomposition method developed by Wang et al. (2013) to panel data from EORA Input-Output Tables,we provide two main contributions to the literature: i) an extensive investigation of sectoral and bilateral SSA GVCparticipation in food and agriculture; ii) a sound empirical test to estimate the impact of bilateral trade protection on theirbackward and forward linkages. We show that: i) despite their low world trade shares, participation of SSA countries inagriculture and food GVCs is higher than that of many other regions in the world and is increasing over time ii) bilateralprotection significantly affects backward and forward GVCs participation; that is, import tariffs may have a depressing impacton the domestic value added content embodied in partner countries’ exports as well as provide rents to foreign suppliers ofinputs. These results call for a refinement of trade policy priorities in SSA.Keywords: global value chains, agro-food, trade policy, gravity model, Sub-Saharan Africa.JEL codes: F15, L23, O11, O55, Q17.1.IntroductionSince the last decade of the 20th century, the so-called agri-food global value chains (GVCs) keep growing as more productscross national borders and the international production networks become more organized under the lead of modern foodprocessors and retailers (Lee et al., 2010; De Backer and Miroudot, 2014).1 The common wisdom is that the emergence ofGVCs can represent a golden opportunity for supporting the on-going transformations of Sub-Saharan Africa, especially inagriculture and food markets, which could move from a subsistence oriented and farm-centered agri-food system to a morecommercialized, productive and off-farm centered activity (IMF, 2015; Greenville et al., 2016). 2 A growing number ofanalyses highlight that GVC participation may stimulate public and private investments in infrastructure that would otherwisenot be profitable, and spur local production in the agriculture sector through minimum scale achievements (IMF, 2015;Taglioni and Winkler, 2016). At the micro level, GVC participation is supposed to foster firms’ productivity in developingcontexts reinforcing the so-called “learning-by supplying” hypothesis emphasized by the theoretical literature (Montalbano1 The term GVC refers to the global networks of activities required to bring a product from its conception to end use and beyond (foradditional details see Humphrey and Memedovic, 2006; Gereffi and Fernandez-Stark, 2011).2Some scholars stress that the impact of globalization on the structural transformation of Africa is occurring mainly via foreign directinvestment (FDI) and – to a lesser extent – via international trade (Reardon and Timmer, 2007). According to this strand of the literature,in most developing countries, the liberalization of the FDI in the food industry during the 1990s allowed the diffusion of supermarkets, thetransition from local sourcing to global procurement networks, and the diffusion of public and private standards (Reardon et al., 2009).2
et al., 2016, 2017a). By generating higher and more stable incomes, higher GVC participation can also have importantspillovers on the food security of small-holder farmers since it is associated with increasing employment, better remuneratedjobs, use of resources, governance, and political stability (Minten et al., 2009; Bellemare, 2012; Cattaneo et al., 2013;Swinnen, 2014; Swinnen and Vandeplas, 2014; Bellemare et al., 2017; Montalbano et al., 2017b).Despite these potential benefits, the economic literature has not yet: i) quantitatively assessed the participation andintegration of SSA countries in the agriculture and food GVCs; ii) formulated any evidence-based policy recommendationson how to increase this participation. Assessing the level of SSA participation in agriculture and food supply chains impliesunpacking the different phases of the production process to identify the amount of each country’s contribution to trade flowsin terms of value-added (i.e, value that is added by countries/industries in producing goods and services).3 This exerciserequires the use of multi-region input-output tables (MRIO) to disaggregate the structure of the world economy betweencountries and sectors. Thanks to the release of the EORA database (Lenzen et al., 2012; 2013) such a comprehensive databasewith panel data on Sub-Saharan countries is now available for the first time. Concerning policymaking, the spectrum ofpolicies that can potentially influence GVC participation in agriculture and food is wide. It ranges from agricultural-specificinterventions aimed at increasing country’s competitiveness and specialization to more general supportive policies that cancreate the right market environment for boosting production, processing, wholesale, retail, and export activities. 4 However,the likely effects of trade policies have been theoretically and empirically analyzed only recently in light of the emergence ofGVCs (Antràs and Staiger, 2012; Blanchard and Matschke, 2015; Gawande et al., 2015; Caliendo et al., 2016).Our aim is to study whether bilateral import tariffs and shifts in trade regimes associated with regional trade agreements(RTAs) affect the agriculture and food GVCs and, specifically, the SSA countries’ backward participation (i.e., the use offoreign inputs for exports) and forward participation (i.e., the use of domestic intermediates in third country exports). Thechannels through which these policies are linked to the international fragmentation of production are not straightforward.They imply both a “magnification effect” (i.e., goods that cross national borders multiple times incur tariffs several times)and a “chain effect” (i.e., tariffs on imports may have a depressing impact on the domestic value added content embodied inpartner countries’ exports as well as provide rents to foreign suppliers of inputs). Also, free trade agreements or customsunions can affect GVC participation by including rules of origins and possible non-tariff issues such as general regulatorypolicies (Curran and Nadvi, 2015).The relevance of the link between trade policies and participation in GVCs in the agricultural and food sector isremarkable for several reasons. First of all, the SSA countries’ protection in these two sectors is the highest in the world witha high incidence of both tariff peak for some products and tariffs applied as specific duties, suggesting that there is a discretemargin for intervention (Bown and Crowley, 2016; Caliendo et al., 2016). Indeed, policy makers often pursue the stabilizationof their domestic markets and isolate consumers from negative global events mainly by means of trade barriers. A good3Using conventional gross trade statistics, the final producer appears to capture most of the value of goods, while the role of countriesproviding inputs upstream – such as SSA countries in the agricultural and food supply chains – could be largely underestimated (Koopmanet al., 2014).4Recent empirical literature investigates the determinants of developing countries' involvement in GVCs (Elms and Low, 2013; Kowalskiet al., 2015; Greenville et al., 2016; Taglioni and Winkler, 2016) and identifies a number of pre-conditions that need to be observed suchas adequate professional skills and human capacity, efficient ancillary services (e.g., electricity, telecommunication capabilities, etc.) andmore efficient physical infrastructure for transport and logistics (e.g., roads, railroads, airports, and ports).3
example is the recent 2007/08 food price crisis in which a number of SSA governments imposed export restrictions and variedimport duties in an attempt to insulate domestic consumers from rapidly rising international food prices (Anderson andMasters, 2009; Abbott and De Battisti, 2011; Anderson and Nelgen, 2012; Magrini et al., 2017). Second, understandingwhether and how trade policies incentivize or penalize SSA countries’ participation in GVCs would be extremely relevant ina region where agriculture still generates about 25% of GDP (50% if we look at the broader agribusiness sector) and involvesroughly 65% of the local population, mostly in family farming activities. Finally, the emerging interdependence betweensmallholders in exporting countries and processors and retailers in importing ones exacerbates the negative effects of theseprotectionist measures: even relatively low tariffs can have significant knock-on consequences for a chain by, for example,discouraging either foreign outsourcing (Yi, 2003) or the development of within-firm vertical production networks (Hansonet al., 2005). In this perspective, GVCs may provide new scope for deeper bilateral and multilateral trade agreements, wellbehind the standard terms-of trade motives (Olper, 2016).To the best of our knowledge, this paper is the first attempt to assess GVC participation in agriculture and food sectorsfor SSA and provide empirical evidence on the impact of trade policies on its forward and backward components by usingpanel data. By applying the bilateral gross exports decomposition method developed by Wang et al. (2013) to the EORA paneldata, we provide two main contributions to the literature: i) an extensive investigation of sectoral and bilateral SSA GVCparticipation in agriculture and food; ii) a set of sound empirical tests to estimate the impact of bilateral trade protection inthese sectors (net of multilateral integration) on the total, backward and forward participation of the SSA countries. Since theempirical literature on GVCs does not provide a “gold standard” to investigate the impact of bilateral protection, in this workwe rely on the well-established gravity model which is traditionally seen as the workhorse model for empirical issues ininternational trade (Baier et al, 2017). The solid theoretical foundations of the gravity framework (Anderson, 1979;Bergstrand, 1985; Deardorff, 1998; Eaton and Kortum, 2002) make it the best tool so far to quantify the effects of trade policyin a multi-country environment in a tractable framework. It also provides a convenient approach to address the endogeneityconcerns by controlling for characteristics of the source and destination countries in value chain trade (Kowalski et al., 2015).We acknowledge that the gravity equation is not expected to fit perfectly well with value added flows compared to grossexports because bilateral value added flows do not depend only on bilateral trade costs but also on costs with third countriesthrough which value added transits from source to destination (Johnson and Noguera, 2012; Baldwin and Taglioni, 2014).Since empirical complications arise in trying to capture these additional indirect effects of trade in value added flows (Johnsonand Noguera, 2012), in our empirical exercise we isolate the impact of bilateral protection on the dyadic relationship betweenreporter and partner countries, by filtering it out from the influences of third countries. We believe that our identificationstrategy is the best way to look at the issue by adopting a parsimonious empirical approach.Our findings are consistent with the most recent literature and suggest that Africa is more integrated into GVCs thanmany other developing regions (Foster-McGregor et al., 2015). It also highlights that global linkages have been increasingover time even if much of Africa’s participation in GVCs is essentially in upstream production activities, specializing inproviding primary inputs to firms in countries further down the value chain (Del Prete et al., 2017a). Furthermore, we showthat SSA trade in value added in agricultural and food products is primarily addressed to the European and emerging countriesrather than to regional partners. Finally, our gravity-like estimates reveal that bilateral trade policies are key determinants of4
both backward and forward GVC participation in agriculture and food for the SSA countries analyzed. In other words, thesetrade policies appear to have an important “chain effect” suggesting that a trade restriction imposed by one country actuallyimpacts other countries but also the country itself through value chain linkages. This has strong policy implications since itconfirms the theoretical argument that optimal tariff policy no longer primarily depends on the location of the importinggoods, but on the nationality of the value added content embodied in traded goods. In short, given the changes in the tradenetwork that have taken place over the last twenty years, a new "thinking value chain" in trade policy should also beimplemented (Hoekman, 2014).The remainder of the paper is organized as follows: Section 2 presents the methodology for decomposing trade in valueadded. Section 3 provides a comprehensive map of agro-food GVC participation in SSA and relative trade partners. Section4 describes the identification strategy. Section 5 presents the outcomes of the empirical analysis; Section 6 adds somerobustness checks; Section 7 concludes and suggests policy implications.2.Measuring GVC participation: the methodological approachDifferent stages of the same production process are now likely to be allocated to different countries while intermediate inputscross borders multiple times and are then counted each time by gross trade flows. Consequently, conventional trade statisticsbecome increasingly misleading as a measure of value produced by any particular country. The recent availability of newinput-output data combined with bilateral trade statistics allows us to allocate the value added embedded in trade flows to thecountries and sectors of origin and destination and decompose gross exports into various components (Koopman et al., 2014),namely: the domestic value added (DVA) (i.e., value added exported in final goods or in intermediates absorbed by directimporters); the foreign value added (FVA) (i.e., other countries domestic value added in intermediates used in exports); andthe “pure double counting” term (PDC), that arises when intermediate goods cross borders back and forth multiple times. 5 Inthis work, we calculate the various components of trade flows in value-added and provide measures of GVC participationusing the methodology developed by Wang et al. (2013) (hereafter WWZ). The authors generalize the gross exportsaccounting framework proposed by Koopman et al. (2014) from a country-level perspective to one that decomposes grosstrade flows at the sector, bilateral, or bilateral-sector level. The WWZ framework is particular informative because it not onlyallows us to extract value added exports from gross exports, but also to recover additional useful information on the structureof international production with a high level of disaggregation.A simple example concerning cocoa beans’ exports of Ivory Coast can help to clarify this decomposition. Let us assumethat the value of cocoa beans’ gross exports from Ivory Coast to France is USD 100. Let also assume that this gross exports’value is composed by USD 50, that is the value of the imported inputs from abroad (e.g. fertilizers, pesticides, insecticides,etc.) and USD 50 that is the value added by Ivorian famers growing cocoa beans. Let us now assume that USD 20 of the valueadded of cocoa beans exported from Ivory Coast to France is absorbed and consumed into the French domestic market,whereas USD 30 is used as intermediates into the French chocolate production exported abroad. Using the jargon of trade invalue-added, the value of the cocoa beans exported by Ivory Coast would embed USD 50 of domestic value added (DVA)5Someof the terms in the PDC bucket double count value added originated in the home country, while other terms in the double count valueadded originated in foreign countries (WWZ, 2013).5
and USD 50 of foreign value added (FVA). Also, the DVA of Ivorian exports should be further decomposed into USD 20 ofdirect domestic value added (DirDVA), that is the part of cocoa beans’ exports directly absorbed - as both final andintermediate goods - by the French market and USD 30 of indirect domestic value added (DVX), that is, the part of cocoabeans’ intermediates further re-exported by France to third countries as chocolate primary and confectionary products. Finally,the chocolate products (e.g., cocoa paste, butter etc.) eventually exported by Ivory Coast using the chocolate primary productsimported from France (e.g., cocoa powder) includes a PDC term due to the value of cocoa beans originally exported to France.In our empirical exercise, we calculate the WWZ components at their finest level which relies on the decomposition ofthe bilateral-sector trade flows. In the WWZ decomposition of bilateral-sector gross exports, the main components (i.e. DVA,FVA and PDC) are further disaggregated into sixteen value-added and double counting terms (see Figure 1A and Figure 2Ain the Appendix). For the purpose of our analysis, we exploit some of these sixteen terms to retrieve three key components ofvalue added exports:i)the direct domestic value added (DirDVA), that is, the domestic value added in intermediates and final goods exportsabsorbed and consumed by direct importers (calculated as the sum of the terms T1 and T2 of the WWZ decomposition, seeFigure 1A). In the example above, this represents the USD 20 of Ivorian cocoa beans directly absorbed by France. Since it isthe result of a single exchange of goods, in our empirical exercise we use it as a proxy for gross exports;ii) the indirect domestic value added (DVX), that is, the domestic value added in intermediate goods further re-exportedby the partner country (i.e., from T3 to T8 in Figure 1A). In the example above, the DVX for Ivory Coast is USD 30, whichis the DVA not absorbed by its partner country, i.e. France, but further re-exported to third countries. It measures the jointparticipation of the bilateral trade partners in a GVC since it contains the exporter’s value added of a specific sector that passesthrough the direct importer for a (or some) stage(s) of production before it reaches third countries (or eventually returnshome6). More specifically, it captures the contribution of the domestic sector to the exports of other countries and indicatesthe extent of involvement in GVC for relatively upstream industries. In our empirical analysis, we use this component as ameasure of forward GVC participation;iii) the foreign value added (FVA) used in the production of a country’s exports, which consists of the value addedcontained in intermediate inputs imported from abroad, exported in the form of final or intermediate goods (that sums theterms from T11 to T15 of the WWZ decomposition, see Figure 2A). In the example above, Ivorian FVA is USD 50 whichcorresponds to the value of imported inputs from abroad and used to produce and export cocoa beans. It captures the extentof involvement in GVC for relatively downstream industries. We use this component as a measure of backward GVCparticipation.To isolate the dyadic relationship of the bilateral-sector trade flow which involves only the country pairs, we identify twofurther sub-components:iv) from the DVX, we aggregate only the share of re-exported domestic valued added that ultimately returns homeexclusively via the partner country (DirRDV) (T6 and T8 in Figure 1A). Following the example above, the DirRDV from6TheDVX component includes also the returned value added (RDV), that is the portion of domestic value added that is initially exportedbut ultimately returned home by being embedded in the imports from other countries and consumed at home.6
Ivory Coast to France would be the share of Ivorian DVX contained in the French primary and confectionary chocolateproducts that are re-exported to Ivory Coast;v)from the FVA, we aggregate only the share of the foreign value added that comes from the direct importing country(MVA) (T11 and T12 in Figure 2A). For example, assuming that France is one of the foreign countries providing inputs tothe production of cocoa beans (e.g. fertilizers, pesticides, insecticides, etc.), the MVA of the Ivorian exports to France wouldbe the share of FVA from France embedded in the Ivorian exports of cocoa beans to France.Data used in this work come from the EORA Multi-Region Input Output (MRIO) database. This database brings togethera variety of primary data sources including national I-O tables and main aggregates data from national statistical offices andcombines these primary sources into a balanced global MRIO, using interpolation and estimation to provide a contiguous,continuous dataset for the period 1990-2013 (Lenzen et al., 2012; 2013).7 The EORA tables are particularly useful since theyprovide access to each country’s structure and function and also information on the interactions between trading partners.Hence, the world trading system can be viewed as a single entity with all trade flows reconciled in economic terms. EORAcontains data for 186 countries - of which 43 are in SSA - and 25 harmonized ISIC-type sectors.8 Specifically, we focus onthe agriculture (ISIC codes 1, 2) and food and beverages (ISIC codes 15, 16) sectors.3.Mapping agriculture and food GVC participation in SSAIn this section, we map agriculture and food GVC participation in SSA. To get a comprehensive picture of trade in valueadded for a single country across all partners in each sector we sum up the DVX, the FVA and the PDC components derivedin section 2 and provide an overall GVC participation index (Koopman et al., 2011; Rahman and Zhao, 2013; Cappariello andFelettigh, 2015; Borin and Mancini, 2015). The higher (or lower) the value of the GVC participation index, the larger (orsmaller) the participation of a country in global supply chains. The maximum value of GVC index is 1 in the extreme casewhere gross exports are only determined by the above components.Figure 1a shows the aggregate GVC participation index in 2013 (the last available year) across all sectors and by regions,distinguishing between the FVA, DVX and PDC components. As a preliminary remark, we can notice that the EU27 andASEAN countries are the most integrated. 9 Nevertheless, the SSA participation rate is surprisingly high (40%), matching thelevel found for China and India, in line with the previous literature applying different decomposition methods (see, amongothers, African Development Bank, 2015; Foster-McGregor et al., 2015; Kowalski et al., 2015). This means that almost half7The use of EORA database is the only option to look at the issue for a comprehensive set of countries in Sub-Saharan Africa. None of theother similar efforts such as the Asian IO tables (IDE‑Jetro), the GTAP project, the OECD-WTO TiVA initiative and the WIOD projecthas the same extension in terms of country coverage and the same level of detail for end-use categories in Sub-Saharan Africa.Notwithstanding the growing use of the EORA database to carry out GVC studies (see, among others Caliendo et al., 2015; and Del Preteet al., 2017b), we made additional sensitivity analysis by comparing EORA and WIOD for overlapping sectors and countries. Thishighlighted consistent trends and a slight upward bias from WIOD (both at the country level and at the world level) likely due to the factthat the latter includes an artificial ‘Rest of the World’ country whose I–O matrix has been derived through a proportionality assumptionbased on an ‘average’ world technology. As pointed by the UNCTAD (2013) this assumption could yield a downward bias in the computedworld FVA, as the world average I–O includes by definition large, relatively close, countries, while most excluded countries in the ‘Rest ofthe World’ aggregate tend to be small, relatively more open, economies.8 We exclude from our analysis the recently born South Sudan (2011) and Sudan, and Zimbabwe for data inconsistency.9 Note that the reported measures tend to be inflated by intermediate flows between countries of the same region. This inserts a bias in favorof the EU27 relative to other large single countries or smaller regional groups (e.g., NAFTA).7
of all trade activities in SSA are GVC-related. Then, looking at the different components of the GVC participation, Africa(especially North Africa, denoted NA) seems to be the best performer in providing value added to other countries in the world(DVX). About 25% of the domestic value added produced in SSA are inputs for other countries’ exports (over 35% in thecase of NA). As a comparison, these figures are in line with those of the Middle East region (25%) and higher than those ofthe EU27, China, and NAFTA that register rates of around 20% (see the DVX component in Figure 1a). Note, however, thatas opposed to other methods, the WWZ methodology allows us to properly isolate the pure double counted term (i.e., PDC inthe figure) which appears to be substantial (e.g., 12% for the EU; 4% for SSA). Figure 1b, on the other hand, shows theemergence of the international fragmentation of production over the last two decades. Although GVC participation isincreasing worldwide, China experienced the highest growth rate at 40% especially after WTO accession in 2001, whereasthe SSA growth rate between 1995 and 2013 is about 8%.Figure 1 GVC participation index by world areas (all sector)1a: Components (2013)Source: Authors’ elaboration on EORA data1b: TrendIn Figure 2 and Figure 3, we compute the sectoral contributions of agriculture and food to the measures of GVCparticipation described above.10 Figure 2 shows that the SSA agricultural sector is the most involved in GVC if compared toother regions of the world (Figure 2a) and its participation is increasing over time (Figure 2b). About 3% out of 40% of totalGVC participation is due to the agriculture sector, i.e. a contribution equal to 7% across all 25 EORA sectors. For instance,the same figure for the EU27 is only 2%. Furthermore, the sector presents a relatively high domestic value added componentsused by other countries’ exports (DVX) with respect to foreign value added components (FVA), confirming its upstreamposition along the chain where it acts as a supplier of intermediate inputs.10The sum across all the sectors therefore equals the value of total GVC participation reported in Figure 1.8
Figure 2 Agriculture GVC participation index by world areas2a: Components (2013)Source: Authors’ elaboration on EORA data2b: TrendFor the food sector (Figure 3), the EU27 and Latin American countries, on the other hand, present the highest participationrates (Figure 3a). Only 4% of the total GVC participation in SSA is due to food activities and its share does not change overtime (Figure 3b). Unlike the agricultural sector, its position lies closer to the final consumers (i.e, downstream position) asshown by the more balanced ratio between the DVX and FVA components.Figure 3 Food GVC participation index by world areas3a: Components (2013)Source: Authors’ elaboration on EORA data3b: TrendTo sum up, SSA takes part in GVCs by contributing mainly to the upstream phases, being confined to low value addedstages of production, but with important heterogeneity in value added trade between agriculture and food exports. Also, theseoverall figures hide a substantial degree of heterogeneity within the region. To shed more light on this, in Table 1A (AppendixA) we report the same GVC components for the 43 SSA countries present in our data, together with the sectoral contributionof Agriculture and Food in 2013. Some SSA countries, such as DR Congo, Ethiopia, Lesotho and Guinea, regi
1 Title: Does trade policy impact food and agriculture global value chain participation of Sub-Saharan African countries? Authors details: Jean Balié, Food and Agriculture Organization of the United Nations (FAO) Jean.Balie@fao.org Davide Del Prete, Food and Agriculture Organization of the United Nations (FAO) and IMT Lucca, Italy, Davide.DelPrete@fao.org
6.2.5 Impact of food aid on food availability 153 6.2.6 Impact of food aid on food accessibility 153 6.2.7 Impact of food aid on food utilisation 154 6.2.8 Impact of food aid on vulnerability 154 6.2.9 Impact of food aid on local markets in Ngabu 154 6.3 RECOMMENDATIONS 154
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