Food Policy 49 (2014) 1–12

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Food Policy

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Formal institutions and social capital in value chains: The caseof the Ethiopian Commodity Exchange

http://dx.doi.org/10.1016/j.foodpol.2014.05.0150306-9192/� 2014 Elsevier Ltd. All rights reserved.

⇑ Corresponding author. Tel.: +31 317 485286; fax: +31 317 484037.E-mail address: Erwin.bulte@wur.nl (E. Bulte).

Gerdien Meijerink a, Erwin Bulte b,⇑, Dawit Alemu c

a LEI Wageningen UR, The Hague, The Netherlandsb Development Economics Group, Wageningen University, Box 8130, 6700 EW Wageningen, The Netherlandsc Ethiopian Institute of Agricultural Research (EIAR), Addis Ababa, Ethiopia

a r t i c l e i n f o

Article history:Received 7 February 2013Received in revised form 12 May 2014Accepted 31 May 2014

Keywords:Market integrationTrustInformal exchange

a b s t r a c t

We explore whether the creation of the Ethiopian Commodity Exchange (ECX) and its formal monitoringand enforcement institutions has affected social capital and trust in the Ethiopian segment of the sesamevalue chain. Consistent with a simple theoretical marketing model, our panel data suggest this is indeedthe case. Trade in sesame is increasingly governed by formal rather than informal institutions, and inresponse traders have broadened their trading network, rely more frequently on traders with whom theydo not have social relations, and have reduced the provision of credit that cements personalized relation-ships. They also have lower levels of trust in the intentions and capabilities of their trading partners, andattach less weight to trust.

� 2014 Elsevier Ltd. All rights reserved.

Introduction

The quality of institutions, broadly defined, is widely regardedas a key determinant of economic performance. There is littleconsensus about which specific dimensions of the institutionalframework matter most for development, and even less aboutthe mechanisms driving institutional change over time (but seeKingston and Caballero, 2009). The institutional framework isbroad, encompassing formal and informal institutions. The distinc-tion between formal and informal institutions is akin to thedistinction between the formal and informal economy (e.g., Hart,1973), which ultimately revolves around whether or not economicactivities are beyond the purview of the state (see Habib-Mintz,2009 for a discussion of the evolution of thinking about informal-ity). In the words of Roberts (1994, p. 8); ‘‘all markets are regulated. . . the issue is the balance between formal regulation based, ulti-mately, on the state, and informal regulation based on personalrelations such as those of kinship, friendship or co-ethnicity.’’ For-mal institutions are centrally designed and enforced, and informalones are subject to self-governance by economic agents (Dixit,2004; Williamson, 2009). Thus defined, formal and informal insti-tutions co-exist in all economies. It is increasingly recognized thatthe nature of the interaction between formal and informal institu-tions matters for economic outcomes (e.g. Boettke et al., 2008;

Williamson, 2009). Formal and informal institutions may providesubstitute mechanisms to govern (economic) transactions. If so,an exogenous expansion of the realm of formal institutions mayhave implications for informal arrangements, and the type ofgame-theoretic equilibria that can be sustained. Caselli (1997)and Dixit (2004) have demonstrated this may have unforeseenwelfare consequences.

Commodity exchanges are one particular ‘type’ of formal insti-tution that has gained prominence in African policy circles. WhileAfrican agricultural markets are increasingly liberalized, translat-ing into greater private investments and increased levels of regio-nal trade and market integration (Mason et al., 2011; Smale et al.,2011), price volatility of food staples remains high and traditionalforms of exchange still involve relatively high transaction costs(Sitko and Jayne, 2012). Such marketing challenges may be tackledvia commodity exchanges––platforms that bring together buyersand suppliers. According to Gabre-Madhin and Goggin (2005),commodity exchanges stimulate market transparency and pricediscovery, and attenuate collusion, (speculative) bubbles and pricevolatility. They may also lower transaction costs by increasing therange of trading partners, by providing monitoring and enforce-ment of standards and contracts, and by tackling conflicts via arbi-tration services (Sitko and Jayne, 2012). In light of these expectedbenefits, it is no surprise that donors and national governmentsare promoting and facilitating the emergence of commodityexchanges across the African continent (albeit with mixedresults—see Sitko and Jayne, 2012).

2 G. Meijerink et al. / Food Policy 49 (2014) 1–12

In this paper we examine the effects of the emergence of a com-modity exchange on informal marketing institutions.1 Specifically,we explore how the Ethiopian Commodity Exchange (ECX) affectedthe structure of the sesame supply chain within Ethiopia, and probethe consequences for transaction patterns and trust within thischain. Broadly speaking, we analyze how the emergence of a formaltrading structure affects various measures of structural and cognitivesocial capital within the sesame trade sector (key components ofinformal institutions governing the domestic trade in sesame). Toguide the analysis, we present a theoretical model proposed byAhlerup et al. (2009), which arrives at the testable hypothesis thatsocial capital and formal institutions are substitutes to guide eco-nomic behavior. Earlier studies of social capital in Africa confirmthe important economic role of social capital in early stages of devel-opment, supporting the view that social capital matters most whenformal institutions are weak (e.g., Narayan and Pritchett, 1999;Bigsten et al., 2000; Fafchamps and Minten, 2002). In our empiricalanalysis we ask whether the expansion of a formal institution—creation of the ECX—has substituted for informal institutions.

The paper is organized as follows. In ‘Sesame and the EthiopianCommodity Exchange (ECX)’ we provide background informationabout the ECX, and explain its workings. In ‘A Theoretical Model’we sketch a simple model highlighting the effect of formal oninformal marketing institutions, and derive several testablehypotheses. Most importantly, since formal and informal institu-tions provide substitute mechanisms to govern the flow of sesamefrom producer to exporter, the model predicts that the ECX willsubstitute for social capital in the trading sector. In ‘Data andMethodology’ we introduce our data and discuss our methodology.We use a simple identification strategy, based on a comparison ofpre- and post-ECX characteristics combined with differences inexposure to the ECX for different types of traders. Results are pro-vided in ‘Results’, supporting the view that the creation the ECXand its monitoring and enforcement apparatus has reduced therole of social capital in the sesame value chain—consistent withthe idea of formal institutions substituting informal ones. ‘Discus-sion and Conclusions’ concludes.

Sesame and the Ethiopian Commodity Exchange (ECX)

Sesame trade and the ECX

Sesame is the second-largest export crop in Ethiopia, aftercoffee, and accounts for over 90% of the value of oil seeds exports.Sesame exports from Ethiopia constitute around a fifth of worldsesame exports. In 2010, Ethiopia was the second-largest sesameexporter in the world, after India (FAOSTAT, 2012). Sesame isgrown mainly for export markets and little value is added in Ethi-opia (Wijnands et al., 2009). It is mainly grown by small-scalefarmers in four regions in Ethiopia (Tigray, Amhara, Oromia andBeneshangul Gumuz). In the past decade, the area under produc-tion has grown 8-fold to 316 thousand ha, or 2% of Ethiopia’s arableland (FAOSTAT, 2012).

The ECX was established in 2007 by the Ethiopian government,and started operations in 2008. The aim is to channel all exports ofmajor cash crops via the ECX, so that transaction costs decline,market transparency increases, and better price informationbecomes available for producers and traders. It was expected thatthe ECX would benefit small traders: ‘. . . the ECX [brokerage ser-vices] could particularly benefit many kinds of traders – thosewho lack social capital, those who suffer from liquidity constraints

1 Informal institutions may, of course, also have an effect on formal institutions;informal institutions may affect the way the formal rules linked to the EthiopianCommodity Exchange are applied. However, this is not the focus of this paper.

while their working capital is tied up in unsold stocks, those whocannot afford to pay for storage facilities under their exclusivelycontrol, those who are based in drought-prone areas and thosewho conduct long-distance purchases and rely upon non-asphaltroads’ (Quattri et al., 2012, p. 21). An additional benefit for the gov-ernment, albeit less clearly advertised, is that centralized tradingenhances the scope for efficient taxation.

The ECX opened up for sesame trade in 2009, and became themandatory channel for sesame exports in late 2010 (The Councilof Ministers Regulation No. 178/2010). The ECX specifies seven dif-ferent contracts for sesame, basing grading on foreign matter(max% by weight) and contrasting color (max% by weight). Not sur-prisingly, in light of the compulsory status, volumes of sesame andother crops traded via the ECX have grown rapidly. In its fourthyear of operation (2011/12), the total traded volume reached601.000 tonnes, consisting of coffee (39%), sesame (50%), and peabeans (11%) (ECX, 2012; Rashid and Negassa, 2011). Trading maizevia the ECX is not mandatory, and cereal traders prefer to rely oninformal markets––volumes of maize traded on the ECX havedecreased to almost zero.

The ECX is basically an open-outcry trading floor, resembling astandard spot market exchange. Traders who sell are known as‘suppliers’, retailers or ‘acrabis.’ They are mainly rural traderswho buy commodities from farmers. In addition, producers’organisations and large individual farmers sell on the ECX. Buyerson the ECX are usually exporters or processing companies. To beeligible to trade on the ECX, one has to become a member. Somemembers trade on their own account (‘trading members’) and oth-ers perform a brokerage role and trade for others (‘intermediarymembers’). Membership may be ‘full’ or ‘limited,’ with limitedmembership restricting trade in certain commodities on eitherthe buying or selling side. By the end of 2012, the ECX had 245 fullmembers and 283 limited members. Memberships are auctioned,and the price of membership increased from 50,000 birr (5100US$; 1US$ = 9.8 birr) in 2008 to 1.35 million birr (80.000 US$; 1US$ = 17 birr) in 2011 (ECX, 2012).

In addition to functioning as a trading floor, the ECX providesseveral services. It disseminates prices to 250 Rural Electronic PriceTickers at public market spaces, via radio and mobile phones. Inaddition, the ECX classifies, grades and stores commodities in 55warehouses, providing warehouse receipts in return. It maintainsan automated central depository of exchange warehouses receipts(see below), and has become a system for clearing and settling alltrades. The ECX also supports a system for market surveillance, riskmanagement and dispute resolution (through arbitration).

Sesame markets before and after the ECX

Before the ECX was created, farmers would typically sell to(visiting) traders. These traders ‘bulked’ sesame into larger quanti-ties for selling at larger regional wholesale markets, in AddisAbaba, or directly to exporters. Large farmers could also sell tocooperatives or exporters. In 2010, after the government of Ethio-pia decreed that ‘any person involved in sesame transactions shalleffect sesame transaction only at primary transaction centres(PTCs) and the Ethiopian Commodity Exchange’ (Government ofEthiopia, 2010), buying or selling sesame directly from farmersbecame illegal. Farmers must now sell at a PTC and traders mustbuy at a PTC. A PTC is a fenced location with certified scales, a mar-ket information board, and local inspectors certifying goods tradedat the PTC.

Traders buying from PTCs (acrabis) must obtain a Woreda ordistrict-specific certificate of competence, and demonstrate thatthey own a warehouse within the Woreda, as well as a weighingscale and a certain level of capital. When purchasing sesame froma PTC, the trader receives a certificate that allows him to sell and

G. Meijerink et al. / Food Policy 49 (2014) 1–12 3

deliver the sesame to an ECX warehouse. Officially, cooperativesare required to follow the same procedure. Currently it is notknown to what extent PTC regulation is enforced, or whether sometraders still bulk sesame by buying from small farmers and sellingthis at a PTC ‘in name of a farmer.’ Our 2012 survey suggests thatsome traders still buy directly from farmers.

The warehouse receipt system

In 2012, the ECX was linked to 55 warehouses for coffee, sesameand pea beans. Warehouses are based in 17 regional locations thatare main production areas. For sesame there are seven deliverylocations: Humera, Metema, Gonder, Assossa, Bure, Nekemte andAddis Ababa (ECX website October 2012). After classifying andgrading, traders can deposit their commodities in these ware-houses in return for a warehouse receipt. In the early days of theECX, these receipts were used as a delivery instrument. In March2011, the Warehouse Receipt Financing scheme was launched,allowing farmers, producers, and traders to access bank loans bypledging their warehouse receipts issued against commoditiesdeposited in warehouses. The ECX uses electronic WarehouseReceipts (e-WRs) issued by the ECX Central Depository, facilitatingboth the transfer of title on the ECX and pledging the commodity ascollateral for loans. Although the ECX reported in 2011 that farm-ers use the WRS, only a few large sesame traders use this system(Coulter, 2012; ECX, 2011). Especially small farmers still face sev-eral hurdles, including the lack of involvement of local banks (IFCand ECX, 2012).

Warehouse receipting is limited by the short expiry dates one-WRs, which is two months from issue for sesame. This expirydate enables loans for up to 50 days, discouraging stockpilingand speculation. The reason for the short expiry date is limitedstorage space at the warehouses, and the on-going need for exportrevenues by the Government. Sesame exporters also believe that aquick turn-over is advantageous because demand is high in thewinter months, when production takes place (Coulter, 2012). In2012, ECX warehouses still faced several capacity problems. Lim-ited storage weighting capacity caused long delays with longqueues of trucks waiting in front of warehouses. Because the ses-ame season is short (November–January), the strain on the deliveryinfrastructure for sesame is particularly large.

In the ECX contracts for sesame, quality is measured by foreignmatter (impurities) color contrast. In pre-ECX days, prices weremainly based on quantity and farmers and traders blended differ-ent seed types. This decreased the overall quality and value of theseeds. The ECX was supposed to improve sesame quality by grad-ing at warehouses, but various observers have noted that theactual quality of sesame may bear little resemblance to gradesaccorded by the ECX (Coulter, 2012; van den Broek, 2012). Thereare rumours that traders can bribe grading officials to upgradetheir produce, so that low grade sesame is delivered to traderswho paid for a higher grade.

Typology of traders

The very short supply season (November to January) invites theinvolvement of various agents in sesame marketing. Broadlyspeaking, two categories of sesame traders exist in Ethiopia: (i)those who buy and sell on their own account (wholesalers, assem-blers, suppliers, exporters) and (ii) those who perform an interme-diary function, and are contracted by the first category of traders(selling or buying agents and brokers). Buying and selling agentsdiffer from brokers because their remuneration depends on pricemargins; they may run a price risk. With the establishment ofthe ECX, brokers were obliged to be officially registered with theECX, which greatly reduced their numbers.

For this study, we interviewed buying and selling traders andhave not included intermediaries. More specifically, in whatfollows we distinguish between exporters and other traders(wholesalers, assemblers, suppliers). The reason for this distinctionis that exporters trade fully within the ECX system––buying ses-ame deposited at an ECX warehouse and selling to foreign import-ers (see Fig. 1, which also illustrates the sesame trade before theintroduction of the ECX). In contrast, other traders have one footin the ECX system and the other one in the traditional system. Thatis; they trade with ECX warehouses, but may also buy from othertraders (and sometimes farmers) or sell to other traders. Suchtransactions are arguably still governed by informal institutions,hence we speculate ‘other traders’ are less affected by the formalinstitutions of the ECX than exporters. We return to this issue in‘Data and Methodology’.

A theoretical model

In this section, we sketch a simple model that shows the inter-action between social capital (and trust) and formal institutions inthe process of value generation within the (sesame) value chain.This model is based on Ahlerup et al. (2009), but rather than ana-lyzing how an exogenous change in the level of social capitalaffects economic performance (and specifically how this impactis mediated by the quality of formal institutions—as in Ahlerupet al., 2009), we seek to examine the impact of a shock in termsof the quality of formal institutions—such as the sudden provisionof arbitrage, monitoring and enforcement services via the ECX. Weuse the term shock in this case because the ECX became mandatoryovernight in September 2010, when the Ethiopian Governmentmandated that all sesame destined for export be traded acrossthe exchange floor.

We closely follow the model of Ahlerup et al. (2009), using thesame sequential, principal agent supply game with a representa-tive supplier (S) and demander (D), and an outside agency thatmay be accessed for arbitrage services (A). The model is simplein that we ignore outside options beyond the trade opportunityanalyzed in the game, and reputation effects or other dynamiceffects do not play a role. The stages of the game are depicted inFig. 2.

(1) In the demand stage, the demander decides whether or notto purchase a certain quantity, valued at k, of the commodity(sesame) that is traded. If the demander chooses not topurchase the sesame the game ends, and payoffs for bothparties equal zero: uD = uS = 0. In case the demander decidesto purchase the sesame valued at k, the game enters thedelivery stage.

(2) In the delivery stage, the supplier decides whether to offerthe specified quantity and quality of sesame, or to renegeand offer an inferior package. In the former case, payoffsare defined as follows: uD = pD + sD and uS = pS + sS. In theseexpressions, pi denotes the standard gains from trade foragent i and si denotes a non-monetary social benefit associ-ated with being an honest trader (where i = S, D). This is asocial reward, or moral satisfaction stemming from general-ized trust and trustworthiness, and is associated with thelevel of social capital (see below). We may think of si notas an innate characteristic of traders, but as a payoff that isspecific to pairs of traders, conditional on prior experiences(i.e. as a function of past ‘investments’). That is, within around of the game, si may be treated as a parameter, butacross rounds these social rewards may change, becomingmore or less important (something we do not model explic-itly here, but discuss below). Obviously, si, pi > 0. The socially

Fig. 1. Stylised representation of the before after establishment of the Ethiopian Commodity Exchange (ECX).

Fig. 2. The extensive form of the principal agent supply game.

4 G. Meijerink et al. / Food Policy 49 (2014) 1–12

optimal outcome of honest trade does not eventuate, how-ever, when the supplier reneges. In that case the game entersthe arbitrage stage.

(3) In the arbitrage stage, the demander decides whether to takethe supplier to an arbitrage agency to enforce the initialcontract, or not. If the demander accepts the inferior packagewithout accessing arbitrage, the payoffs are defined asfollows: uD = � k + sD and uS = pD + pS. In words, if thedemander accepts the package he foregoes the full value ofthe sesame. Hence, without loss, we assume here the valueof the inferior package that was offered equals zero; the

analysis is easily augmented to capture the case where thevalue of the inferior package equals ak, so that the loss forthe demander is only (1 � a)k. The demander retains thesocial reward from being an honest trader. The supplier inthis case captures the full benefit from the trade, but ofcourse does not enjoy the non-monetary social reward(sS = 0). In contrast, when the demander decides to seekarbitrage, the game enters the ruling stage.

(4) In the ruling stage, the arbitrage agency rules in favor of thedemander, or not. The exogenous probability of enforcingthe contract, or a measure of the quality of formal

2 The model presented here explains how social capital and formal institutions aresubstitutes in promoting honest trade. This is an artefact of the way the model hasbeen developed—more complex specifications of the model can be envisaged,including ones where formal enforcement and social capital may be complements.For example, one may develop a model where socially-based exchanges serve as thebasis for formally-based exchanges, or where the quality of formal enforcementdepends on its mapping on existing informal institutions (as in Williamson, 2009). Inthe latter case, formal enforcement b enters as a function b(s), with b(s)>0.

G. Meijerink et al. / Food Policy 49 (2014) 1–12 5

institutions in what follows, is given by b. In case the agencysupports the demander, and enforces the initial contract, thepayoffs are defined as uD = pD + sD and uS = pS � d. In words,the demander is fully compensated, and in addition enjoysthe social reward. The supplier enjoys the regular benefitfrom trade, but has to pay a fine d, which is the cost ofrunning the arbitrage case. With probability (1 � b) the arbi-trage agency does not rule in favor of the demander, inwhich case the demander pays the fee so that payoffs aredefined as: uD = �k � d + sS and uS = pD + pS.

With these payoffs, the optimal strategies for the agents arereadily derived. The sub-game perfect Nash equilibrium of thegame, and associated best response strategies, are described asfollows.

� In the demand stage, the demander should demand if any of thefollowing three conditions is satisfied: (1) L = sD + b(pD + -k + d) � k � d P 0, (2) sD � k P 0, or (3) producer will be honest.If none of these conditions is satisfied, the demander should notpurchase any sesame. Note that high levels of social capital,represented by large realizations of sD, are conducive to trade.The same is true for the quality of formal institutions, b, orthe probability that deviations from honest behavior will bepunished by the arbitrage agency down the line – sD and b aresubstitute mechanisms to increase the probability of engagingin trade.� In the delivery stage, the producer should be honest if F = sS + -

b(pD + d) � pD P 0. Otherwise he should renege and offer theinferior package. Social capital, here entering via the term sS,again is conducive to honest trade, and so is the formal institu-tions parameter b. Social capital and formal institutions are sub-stitute mechanisms to discipline potentially cheating suppliers.� In the arbitrage stage, the demander should not seek arbitrage

services if both sD � k P 0 and b(pD + k + d) � d 6 0. Else heshould seek arbitrage.

We can use this model to probe the consequences of an exoge-nous shock in the quality of institutions (b), such as due to the newarbitrage and enforcement services made available by the ECX.Examining the optimal responses in the demand and deliverystage, it is obvious that raising b increases the probability of honesttrading behavior: @L/@b > 0 and @F/ob > 0. The probability thatimproving enforcement arbitrage ‘tilts’ the balance such that theequilibrium outcome of the game switches from no trade (orreneging) to honest trade is decreasing in the level of social capital.By design, formal institutions and social capital provide substitutemechanisms to foster honest behavior. For sufficiently large valuesof social capital, relative to monetary payoff parameters k, d andpD, improving the quality of formal institutions does not matter(i.e. both L > 0 and F > 0, even for really low values of b).

If formal institutions are poor or absent (i.e., b � 0), trade willnot occur unless social capital levels are sufficiently high. In theformal institutional vacuum of the pre-ECX era, trade beyond the‘flea-market’ or cash-and-carry types of exchange could only occurin the presence of trustworthiness and social rewards (si). Main-taining trust and trustworthiness requires investment in socialrelations, as was documented for the case of Ethiopian sesametrading by Cecchi and Bulte (2013). It also poses natural limits onthe expansion of trade levels and trade will only occur within asmall circle of trustworthiness (see Tabellini 2008 for a formaltreatment of ‘distance’ as a factor explaining trustworthy behav-ior). However, the availability of formal arbitrage conditions(b > 0) alters the rules of the game, enabling the transition frompersonalized to anonymous exchange within a broad set of (poten-tial) ‘strangers.’

This has two types of implications for the role of social capital ingoverning exchange, and on the equilibrium level of social capitalin the value chain. First, formal institutions enable transactingbetween traders that heretofore would never engage in trade(because of low levels of trust and associated social rewards), sonew trading pairs with low levels of si enter the market. Second,and somewhat beyond the simple model sketched above, theavailability of formal enforcement reduces the importance of socialcapital, potentially rendering on-going investments in social capi-tal redundant. If so, social capital erodes or si falls, even amongpre-existing trading pairs. A new equilibrium emerges character-ized by more trading pairs but, on average, lower levels of socialcapital between interacting parties. Formal institutions will gradu-ally substitute for informal ones.2

In what follows, we try to test this hypothesis using variousproxies of social capital among sesame traders in Ethiopia,collected before and after the introduction of the ECX.

Data and methodology

Data

We collected data during interviews with sesame traders in2010 and 2012—just before and after the introduction of the ECX.There are inherent (practical) difficulties in interviewing tradersin developing countries (e.g., Barrett, 1988, and Scott, 1995).Traders are often mobile, and may be reluctant to disclose informa-tion about their turnover and profits. Moreover, a complete list oftraders (the sampling frame) usually is not available—and it wasnot available for the population of Ethiopian sesame traders. Hencewe could not select a random subsample of traders for the inter-views. Instead, we visited 41 markets in 5 sesame producingregions (Gonder, Humera, Metema, Nekemt and Addis Ababa),and tried to interview all traders present. To avoid selection bias(e.g. certain traders are only present at certain times of the day)we tried to visit most markets at different times of the day (morn-ing, afternoon and evening). Overall, 70% of the traders partici-pated in the survey. An overview, broken down by type, of theparticipating traders is provided in the top panel of Table 1. Wealso report information on the subsample of traders for whichwe have been able to collect data during both rounds of interview-ing (the ‘‘panel subsample’’).

Total participation in the first (second) survey amounted to 194(196) traders, and the panel subsample amounts to 105 traders.We believe this constitutes a representative sample of traders inEthiopia’s sesame markets. While the total number of sesame trad-ers is unknown (there is no trading license specifically for sesame),we know there are around 80 sesame exporters in Ethiopia. No lessthan 45 of them are contained in our sample. Moreover, the sum ofEthiopian sesame production for 2010 and 2012 was about450,000 tons. Aggregating across individuals and survey years,the traders in our sample traded almost 300,000 tons. This amountalmost certainly includes some double-counting (as the samequantity of sesame may be sold more than once along the valuechain), so we cannot conclude that our sample covers 70% of totalproduction. But these statistics do suggest that we cover a sizable

Table 1Characteristics of traders in the 2010 and 2012 surveys and in panel data (frequency, means and standard deviation or proportion of population; s.d. in brackets).

All traders Traders in panel

2010 2012 (2010 and 2012)

Type of trader n % n % n %

Exporter 75 38.7 45 23.0 30 28.6Wholesaler 71 36.6 80 40.8 51 48.6Supplier 14 7.2 7 3.6 6 5.7Assembler 18 9.3 52 26.5 14 13.3Other type of trader 16 8.2 13 6.6 4 3.8

Demographic variables 2010 2012 2010 2012

Age of traders (in years) 40.63 (8.81) 39.07 (7.75) 39.73 (8.46) 40.11 (8.46)Female traders (proportion) 0.088 0.038 0.052 0.038Education (proportion)– Illiterate 0.31 0.12 0.20 0.20– Primary/secondary school 0.37 0.41 0.35 0.35– Third grade 0.33 0.47 0.45 0.45Age of firm 10.37 (8.60) 7.476 (4.91) 7.64 (4.77) 9.34 (6.54)

Sesame trade-related variables

Quantity purchased 1808.74 (3070.58) 2474.16 (14837.13) 1889.84 (3912.55) 3213.29 (19463.97)Purchase price 1541.81 (277.24) 1700.93 (196.98) 1568.31 (334.96) 1692.69 (229.30)Quantity sold 1652.78 (1760.22) 1381.62 (2232.39) 1511.32 (1839.51) 1552.86 (2376.83)Selling price 1614.12 (304.77) 1896.61 (273.68) 1587.84 (302.59) 1885.60 (295.47)

2010 survey: N = 194; 2012 survey: N = 196; panel data: N = 105.

6 G. Meijerink et al. / Food Policy 49 (2014) 1–12

share of total sesame production (even if the size of the tradersample is small – also see Loveridge, 1995).

In terms of demographics, the population of traders has notchanged much (Table 1). A small share of the traders in our sampleis female (around 4%), and this percentage has decreased some-what. Traders in the 2012 survey are on average two years youngerthan those in the 2010 survey (39 and 41 years, respectively, p-value = 0.008). There are fewer illiterate traders and more traderswith a third grade education (after secondary school). The averagetime the trader has been in business (age of firm) is around 3 yearsshorter than in 2010. These shifts seem to indicate that the ECX hasmade the sesame business more demanding, leading to a small exitof illiterate, female and older traders. We have also included somevariables about involvement in the sesame trade, which show thattraders tend to purchase more in 2012 than in 2010. The amountsold is similar or even a little less, indicating that traders had notsold everything at the time of the second interview. Prices werehigher, but this largely captures inflation.

As is evident from Table 1, the composition of the trader popu-lation has changed considerably. For example, in 2012, there werefewer exporters and more assemblers, reflecting (financial)requirements implied by ECX membership and a trend towardslarger volumes. Most of the interviewed traders say they use theECX through members, especially the wholesalers and assemblers.Hence, they do not sell directly on the ECX, but sell to other traderswho are full or limited members. While most exporters have full orlimited ECX membership, the picture for suppliers is mixed.

Methodology

Defining social capitalWe are interested in exploring whether the creation of the ECX

has affected the role of social capital in the sesame value chain.Social capital is a multi-faceted concept, and we measure it by sev-eral indicators or proxies. For example, following Fafchamps andMinten (2002) we seek to capture measures of the size andstrength of a trader’s network. First, following Fafchampsand Minten (2002), we consider the number of trading contacts

and regular customers. If formal regulation reduces the risk of mal-feasance, replacing trust and personal connections, then we wouldexpect the number of trading contacts to expand as traders cannow engage with a broader set of partners. Second, we askedwhether and how much trade credit traders provide to their cli-ents. Providing trade credit to other traders requires social capital,and can be used to create personalized relationships (Fisman andRaturi, 2004; Giannetti et al., 2011; Hermes et al., 2012). If lesscredit is extended in the sesame value chain, this might indicatean erosion of social capital. Third, we measure the use of interme-diaries such as selling and buying agents. Such intermediaries cansubstitute for social capital (Gabre-Madhin, 2001; Quattri et al.,2012), so an increase in the use of intermediaries may signal areduction in social capital. In addition, we look at the ‘nature’ ofthe social relationship of traders with intermediaries. Fourth andfinally, we measured trust perceptions of traders. Specifically, wemeasured their assessment of the trustworthiness of their partners(i.e. goodwill trust) and their appraisal of the ability of theirpartners (Das and Teng, 2004; Williamson, 1993).

Causal effects and attributionOur main objective is to explore how the ECX has affected the

role of social capital in the sesame value chain. Identification ofsuch effects is complicated by the fact that the ECX affects all trad-ing parties in Ethiopia – all sesame exports are traded via the ECX,and the impact of the ECX (for example via the dissemination ofprice information) affects all trading parties to some extent. Inother words: a proper control group does not exist for the ECXtreatment, and a simple difference-in-difference approach to gaug-ing the impact of the ECX is not feasible.

We therefore have to resort to an identification strategy that isdecidedly second-best. We first compare ‘before’ and ‘after’ socialcapital measures for various subsamples of traders, and attributedifferences over time to the creation of the ECX. This is clearly astrong assumption as other factors may have intervened—affectingsocial capital levels. We therefore emphasize that the empiricalresults should be interpreted with care.

G. Meijerink et al. / Food Policy 49 (2014) 1–12 7

To attenuate concerns about attribution we argue the following.First, the time lag between the two survey rounds was relativelyshort (2 years), so the scope for other factors to intervene was lim-ited. Second, we focus the presentation on panel data, whichimplies we automatically control for time-invariant factors. Third,we seek to exploit variation in the degree to which traders areactually governed by the ECX. As mentioned, while all transactionsof exporters are governed by the ECX monitoring and enforcementsystem, the other traders in the system (assemblers, wholesalers,suppliers) have one foot in the realm of the ECX and the other inthe domain of informal institutions and social capital—conductingtrades beyond the scope of the ECX enforcement and arbitrage ser-vices. By assessing differences in the evolution of social capital forthe two types of traders, we are hopefully able to learn somethingabout the causal effect of the ECX on social capital. Since all othermacro factors (e.g., changes in policies, prices) are the same for thetwo types of traders, any differences in the evolution of social cap-ital cannot be attributed to these. Instead, we argue, it is morelikely they can be attributed to the ECX. Specifically, the theoreticalmodel predicts that formal institutions substitute for informalones, so we expect that changes in our measures of social capitalshould be larger for ‘‘exposed’’ exporters than for ‘‘semi-exposed’’other traders.

Fourth, as a robustness test we estimate a simple regressionmodel. We estimate the following model for the panel sub-sample:

sit ¼ aþ b1T it þ b2Eit þ b3EitT it þX

ciXit þ eit ð1Þ

where s represents a measure of social capital for individual i = 1,. . ., 105 at time t (2010 or 2012), T is a treatment dummy (or adummy for the 2012 observations), E is an exporter dummy, andX is a vector of trader controls (summarized in Table 1). As usual,e is an iid error term. We also estimate models with trader fixedeffects, replacing a in (1) with ai.

The hypothesis that formal institutions substitute for social cap-ital for suppliers, wholesalers and assemblers is consistent with theresult that b1 < 0 for some variables (e.g., probability of extendingcredit or advance payments, number of regular suppliers). Forother variables, such as the number of trading contacts or the shareof goods purchased via a buying agent, the substitution hypothesisis consistent with a positive coefficient. Moreover, in light of thefact that exporters are more exposed to the ECX and are therefore(even) more likely to be characterized by a fall in social capital, wealso hypothesize that b3 < 0 for some variables, and b3 > for others.

Results

We now discuss how the formal institutions created by the ECXhave impacted various dimensions of social capital for the 105

Table 2Trading contacts and the ECX (panel data only, N = 105).

All traders

Indicator 2010 2012

Number of trading contactsNumber of trading contacts in main purchase market 5.37 5.77Number of trading contacts in main sales market 3.84 3.14

Number of regular suppliersNumber of regular suppliers 13.66 8.85Proportion of purchases with regular suppliers 49.90 29.59Number of regular suppliers you meet socially 5.60 2.34Number of regular suppliers who are close relatives 1.30 0.53Number of suppliers who sell exclusively to you 5.18 2.02

* Indicates significance at 10%.** At 5%.

*** At 1%.

traders for whom we have collected pre-ECX (2010) and post-ECX (2012) data. We have also compared the 2010 and 2012cross-section data (using all respondents, not just the panel sub-sample), to compare the characteristics of the sampled populationsof traders over time. This nearly doubled the sample (improvingthe power), but of course makes attribution even more difficultas we cannot control for time-invariant characteristics. Qualita-tively, the results for the cross-section comparison tend to supportthe panel results, but identification based on distinguishingbetween exporters and ‘other traders’ is less successful (whichmay not be surprising given the changes in the composition ofthe trader population following the introduction of the ECX). Toeconomize on space the cross-section are not reported here, butdetails available in an on-line appendix.

Trading contacts and the ECX

We speculate that the presence of formal enforcement and arbi-trage institutions enables traders to engage in trade with a largernumber of parties, no longer confining them to interact with aninner circle of trusted partners. In Table 2 we summarize paneldata on the number of trading contacts, distinguishing betweenthe full panel subsample and the two sub-types of traders. Whileat the aggregate level there is no evidence to suggest that the num-ber of trading contacts has significantly changed after the ECX, wenote that the number of contacts in the purchase market hasincreased for the subsample of exporters. This is consistent withthe expectation that exporters can more easily broaden their setof trading partners.

Consistent with our expectations, the same is not true for ‘othertraders’ operating outside the governance system supported by theECX. Indeed, the reverse seems true. While the number of contactson the purchase side has stayed the same, the number of tradingpartners on the sales side has decreased—arguably reflecting over-all consolidation in higher segments of the sesame value chain(due to increased fixed costs of trading via the ECX). In contrast,the mean number of trading contacts for exporters in sales marketsincreased from 4.5 to 6.1, but this increase is not significant. Inwhat follows, we will focus on social capital among Ethiopian trad-ers, and not on governance between exporters and importers(details about how the ECX affected governance on the sales sideare available on request).

We have also asked about the identity of trading contacts, andparticularly whether the ECX affected the propensity to limit tradeto ‘regular customers and suppliers.’ Table 2 shows that regularsuppliers have become less important after the ECX. Aggregatingacross all traders, our data are consistent with the hypothesis thatin the ECX era, the number of regular traders and the proportion of

Exporters Other traders

p 2010 2012 p 2010 2012 p

3.14 5.16 * 6.35 6.124.5 6.1 3.7 2.02 **

10.43 1.46 ** 14.92 11.61*** 68.80 25.00 *** 43.74 31.32 *

* 1.36 0.14 * 6.87 3.160.00 0.04 1.65 0.72

*** 3.73 0.36 *** 5.52 2.64

8 G. Meijerink et al. / Food Policy 49 (2014) 1–12

sesame purchased from regular traders have gone down. Ourrespondents also trade less with friends (traders they meetsocially) or close relatives—trading partners characterized byrelatively low informal monitoring and enforcement costs(Gabre-Madhin, 2001). The same patterns emerge in the data whenwe consider customers (sales side of the market). These data sug-gest it has become less important for traders to have a network ofregular customers and suppliers, as the ECX has taken over the roleof the trading network, and that traders are investing less in main-taining social capital (by meeting socially with regulars). Whendistinguishing between exporters and other traders, it is evidentthat these results are especially driven by developments amongthe subsample of exporters. Other traders still predominantly tradewith the same regular partners as before, and continue to spendtime with these partners outside business hours as well.

Credit and the ECX

The extension of credit is an important part of social capital andpersonalized exchange in trading networks. We have two proxiesfor credit: the share of purchases associated with the extensionof credit (via advanced or delayed payments), and a measure ofthe stated willingness of traders to extend credit to each other.Table 3 indicates that the share of commodities purchased oncredit has decreased, and that ‘payment on delivery’ has becomethe dominant mode of purchasing (now covering some 72% of alltrades). If we break this result down by distinguishing betweenexporters and other traders, a mixed picture emerges. Comparingbaseline (2010) data, it is evident that exporters have always reliedmore on ‘payment upon delivery’ and less on the extension ofcredit to their partners than the category of ‘other traders.’ Never-theless, suppliers’ credit became even less important after imple-mentation of the ECX (to a paltry 0.17% of all purchases), whilesuppliers’ credit became significantly more important for othertraders (from nearly 16% to 24% of all purchases). However, we alsodocument that advance payments to traders became less impor-tant for ‘other traders.’ We believe this reflects the establishmentof primary trading centres (PTCs), so that securing supply via bro-kers and small-scale traders has become less important. Thedecline in advance payments to farmers simply reflects that buyingdirectly from farmers is now officially banned.

Table 3 also provides information on the willingness of suppli-ers and customers to provide credit, and the willingness of the tra-der to provide credit. Consistent with the results above, andconsidering the full panel, we find that this willingness hasdecreased. Across the board, this seems true for both exporters

Table 3Credit and the ECX (panel data only, N = 105).

All traders

2010 2012 p

Payment mode (as a share of total purchases)Suppliers credit 12.08 17.25Advance payment to traders 7.18 3.03 **

Advance payment to farmers 16.94 5.59 ***

Payment upon delivery 58.87 71.63 **

Credit received or advance given in sesame tradeDo suppliers let you buy on credit?a 2.13 1.42 ***

Do you let customers buy on credit?a 1.17 1.30 ***

Do you buy with advance to farmers?b 2.38 1.40 ***

Do you buy with advance to traders? 1.84 1.35 ***

a 1 = None; 2 = some; 3 = all. Values are average scores.b 1 = Never; 2 = sometimes; 3 = often; 4 = always. Values are average scores.* Indicates significance at 10%.

** At 5%.*** At 1%.

and other traders, but ‘other traders’ are more willing to extendcredit customers in 2012. Overall, the overall patterns in the dataare consistent with the hypothesis that formal institutions substi-tute for informal ones, and curtail the extension of credit in infor-mal trading networks. But we acknowledge that attributing thesechanges to the ECX is not straightforward as there is some evidenceof a broad trend of reduced credit extension affecting both export-ers and other traders.

Use of intermediaries

If social capital becomes less important, traders can more easilywork through intermediaries. Hence, we expect that the number ofbuying agents and brokers used by the trader should increase, andthat the interaction between traders and intermediaries becomesincreasingly ‘professional’ – i.e., less closely governed by socialinteractions. The reduced importance of ‘regular trading partners’was already established in Table 2. The results in Table 4 providefurther support for this hypothesis. We observe that exportershave significantly increased the number of intermediaries viawhom they trade, and that they seem somewhat less likely to meetsuch buying agents socially (even if the latter effect is not signifi-cant at the 10% level). Similar patterns in the data do not existfor ‘other traders.’

The share of goods purchased through an intermediary (buyingagent) has increased. Distinguishing between exporters and othertraders, we observe that this result is driven by both categoriesof traders, but also note that the exporters’ share of goods pur-chased through a buying agent has especially increased (from 5%to nearly 70%, compared to an increase from 15% to only 26% for‘other traders’).

Trust and disputes: goodwill trust and trust in ability

If formal institutions substitute for informal ones, we wouldexpect that transactions are increasingly governed by rules ratherthan shared norms and trust. If so, we also expect an deteriorationin (average) trust levels in the sesame value chain—not necessarilybecause traders suddenly distrust their existing trade partners, butbecause they have expanded the set of partners with whom theyinteract and trade. We distinguish between two types of trust:goodwill trust, or trust in the intentions of others, and trust inthe ability of partners to produce or deliver as promised. Table 5summarizes traders’ perceptions.

Across the board, we indeed find that goodwill trust and trust inability have decreased over time. Traders increasingly believe their

Exporters Other traders

2010 2012 p 2010 2012 p

2.43 0.17 * 15.93 24.18 *

1.90 8.00 9.29 1.01 ***

2.47 1.67 22.73 7.18 ***

83.8 83.5 48.89 66.82 ***

2.31 1.00 *** 2.07 1.59 ***

1.10 1.10 1.20 1.44 ***

2.43 1.07 *** 2.36 1.53 ***

1.90 1.10 *** 1.81 1.44 ***

Table 4Number of intermediaries used in total purchases and relationships with those intermediaries (panel data only, N = 105).

All traders Exporters Other traders

2010 2012 p 2010 2012 p 2010 2012 p

Number of buying agents 0.58 0.93 ** 0.4 0.88 ** 0.65 0.95Number of buying agents you meet socially 0.29 0.46 0.25 0.12 0.31 0.51Number of buying agents that are close relatives 0.17 0.2 0.25 0.08 0.13 0.25Share of goods purchased via buying agent 12.08 34.42 *** 5.17 69.17 *** 15.32 25.6 **

** Indicates significance at 5%.*** At 1%.

Table 5Average scores for trust perceptions of sesame traders (panel data only, N = 105).

All traders Exporters Other traders

2010 2012 p 2010 2012 p 2010 2012 p

Goodwill trustAverage trust in suppliers 3.15 3.14 3.94 2.46

*** 2.81 3.44 ***

Knows price well but not sharing info 3.33 3.13 3.96 2.57*** 2.79 3.16

Know quality of produce but does not share info 3.25 2.69*** 3.96 2.57

*** 2.87 2.75

Knows quantity well but does not share info 3.28 2.84** 3.89 2.71

*** 2.98 2.89

Able to pay but cheats 3.47 3.57 4.20 2.39*** 3.08 4.10 ***

Colludes with other buyers/sellers suppliers 3.05 3.91 *** 3.67 2.61** 2.80 4.49 ***

Trust in abilityAverage trust in ability of suppliers 3.34 3.06

* 3.96 2.66*** 3.09 3.23

Does not know price well 3.16 2.98 3.96 2.96*** 3.00 3.21

Does not know quality of produce 3.39 2.84*** 3.96 2.57

*** 2.87 2.75

Does not know quantity 3.56 2.62*** 4.00 2.39

*** 3.39 2.71***

Cannot pay you because short of cash 2.82 3.36 2.92 2.25 2.79 3.86 ***

GeneralImportance of trust 4.04 3.71

** 4.45 4.10* 3.88 3.56

*

How much do you trust traders in general 3.87 3.6* 4.28 3.83

** 3.71 3.51

How much do you trust buyer of last transaction 3.93 3.54*** 4.46 3.76

*** 3.73 3.45*

Number transaction you undertake before trust 3.85 3.43 3.81 3.10 3.86 3.52Number of years it takes to trust trade partners 2.81 1.45

*** 2.40 0.95*** 2.96 1.58

***

1 = Very low trust; 2 = low trust; 3 = neutral; 4 = high trust;5 = very high trust. Values reflect averages for traders of these scores.Underlined figures denote a significant decrease, bold figures denote a significant increase.

* Indicates significance at 10%.** At 5%.

*** At 1%.

G. Meijerink et al. / Food Policy 49 (2014) 1–12 9

partners may try to benefit from asymmetric information, and thattheir partners are unable to properly assess the quantity andquality of sesame they promise to deliver. This is due to the factthat quantity and quality is now assessed at the warehouses bywarehouse managers, and corresponds with findings by Coulter(2012). One positive point is that traders see less collusion amongthe sellers from whom they purchase sesame—trust levels in thisarea have increased. One possible reason is that social capitalmay facilitate collusion (Adler, 2000; Fafchamps and Minten,2002) so that a reduction in social capital may lead to lower levelsof collusion.

Consistent with expectations, there are striking differencesbetween exporters and ‘other traders’ in their trust perceptions.While exporters’ perceptions of goodwill trust and trust in abilityhave significantly deteriorated across all dimensions, the same isnot true for ‘other traders.’ Indeed, in contrast, average goodwilltrust among these traders has increased, as has trust for specificdimensions (less cheating, less collusion). Trust in ability amongother traders has not been affected robustly in either direction.

Turning to more general statements at the bottom of Table 5, itis interesting to note that traders argue that trust between tradershas become less important, but is still highly valued. Traders also

state it takes fewer years to trust other traders. This may bothreflect ECX’s increasing transparency and decreasing contractdefault.

We have also looked at trade disputes in the sesame valuechain. Specifically, Table 6 summarizes the share of traders withtrade disputes over various issues, and documents how often suchdisputes occur (as a share of all disputes). This table substantiatesanecdotal evidence about quality problems reported by Coulter(2012) and van den Broek (2012), and corroborates the results oflow trust in quality hinted at in Table 5.

As expected, the ECX resulted in a reduction in disputes overrenegotiation with suppliers (as when prices change quickly).The warehouse system also attenuated problems associated withstolen property. However, disputes over measuring units persist,and around a third of all traders reports this, although the actualnumber of disputes is low.

Breaking down the results between exporters and other traders,we again detect significant differences. Overall, exporters are morelikely to report an increase in disputes, and indicate an increase inthe share of disputes with suppliers due to bad quality, measuringunits, or the place of delivery. However, they also reported adecreases in the shares of disputes due to disagreement over

Table 6Reported disputes by sesame traders (panel data only, N = 105).

All traders Exporters Other traders

Indicators 2010 2012 p 2010 2012 p 2010 2012 p

Dispute with suppliers due to bad quality purchase 0.28 0.50 *** 0.10 0.48 *** 0.47 0.66 **

% Of all disputes with suppliers due to bad quality purchase 15.08 18.39 2.67 19.64 ** 16.14 18.02

Dispute with suppliers due to disagreement over measuring unit 0.22 0.22 0.07 0.28 ** 0.31 0.30% Of all disputes with suppliers due to disagreement over measurement 9.40 8.17 5.00 3.00

** 9.78 10.05

Dispute with suppliers due to attempt to renegotiate 0.40 0.19*** 0.76 0.10

*** 0.87 0.37***

% Of all disputes with suppliers due to attempt to renegotiate 11.24 15.67 13.09 2.67*** 10.57 17.11 **

Dispute with suppliers due to stolen property 0.06 0.03 0.03 0.00 0.11 0.06% Of all disputes with suppliers due to stolen property 3.11 4.00 0.17 0.00 2.88 4.00

Dispute with suppliers due to place of delivery 0.25 0.13*** 0.17 0.21 0.39 0.12

***

% Of all disputes with suppliers due to place of delivery 2.14 3.19 0.57 7.61 ** 2.77 1.36

Disputes variables measure the proportion of traders indicating they have had a dispute.% of all disputes. . . reflects how important the particular dispute was compared to alldisputes a trader may have had (in%).Underlined figures denote a significant decrease, bold figures denote a significant increase.

** Indicates significance at 5%.*** At 1%.

Table 7Robustness analysis: Regression results.

OLS Fixed effects model

Parsimonious Elaborate Parsimonious Elaborate

Number of trading contacts in main sales marketYear (ECX dummy) �0.47 (0.31) �0.30 (0.31) �0.9 (0.61) �0.61 (0.75)Exporter dummy �3462.0** (1173) �2693.0** (1165) �8.14 (6.06) 0.76 (5.97)Interaction term (year * exporter) 1.72** (0.58) 1.34** (0.58) 3.4*** (1.16) 2.81* (1.41)

Number of trading contacts in main purchase marketYear (ECX dummy) 0.30 (0.54) �0.02 (0.64) 0.7 (1.07) �0.81 (1.30)Exporter dummy �2261.0 (2057) �3138.0 (2406) �11.42 (10.63) �5.74 (10.37)Interaction term (year * exporter) 1.12 (1.02) 1.56 (1.20) 2.35 (2.03) 2.63* (2.45)

Proportion of purchases with regular suppliersYear (ECX dummy) �6.36* (3.45) �9.77** (3.86) �17.52*** (7.05) �23.86** (9.40)Exporter dummy 31687.3** (13838) 58090*** (15840)Interaction term (year * exporter) �15.75** (6.88) �28.89*** (7.88) �39.98** (15.09) �38.38* (20.80)

Do suppliers let you buy on credit?Year (ECX dummy) �0.24*** (0.05) �0.25*** (0.05) �0.49*** (0.1) �0.53*** (0.12)Exporter dummy 836.40*** (173.9) 843.20*** (192.9) 0.98 (0.99) 1.24 (0.96)Interaction term (year * exporter) �0.42*** (0.09) �0.42*** (0.10) �0.86*** (0.19) �0.716*** (0.23)

Do you let customers buy on credit?Year (ECX dummy) 0.12*** (0.04) 0.11*** (0.04) 0.23*** (0.07) 0.208** (0.09)Exporter dummy 233.50* (135.4) 344.1** (156.7) �0.02 (0.67) 0.231 (0.71)Interaction term (year * exporter) �0.12* (0.07) �0.17** (0.08) �0.25* (0.13) �0.309* (0.17)

Do you buy with advance to farmersYear (ECX dummy) �0.42*** (0.10) �0.44*** (0.06) �0.84*** (0.11) �0.89*** (0.14)Exporter dummy 535.62** (217) 526.8** (240.1) �1.66 (1.07) �0.84 (1.13)Interaction term (year * exporter) –0.27** (0.l0) –0.26** (0.12) –0.53** (0.21) �0.35 (0.27)

Do you buy with advance to traders?Year (ECX dummy) �0.19*** (0.04) �0.17*** (0.05) �0.37*** (0.07) �0.30*** (0.09)Exporter dummy 421.97** (170.4) 546.3*** (193.1) 0.15 (0.71) 0.78 (0.73)Interaction term (year * exporter) �0.21** (0.08) �0.27*** (0.l0) �0.46*** (0.14) �0.42** (0.17)

Share of goods purchased via buying agentYear (ECX dummy) 5.82** (2.34) 3.99 (2.85) 11.14** (4.97) 4.84 (6.86)Exporter dummy �53220*** (9160) �54500*** (1050) 61.18 (48.32) 34.81 (54.0)Interaction term (year * exporter) 26.47*** (4.56) 27.11*** (5.49) 50.37*** (10.01) 39.78*** (13.43)

Standard errors reported in parentheses.Full regression output is provided in on-line Appendix Tables A6–A9.

* Indicates significance at 10%.** At 5%.

*** At 1%.

10 G. Meijerink et al. / Food Policy 49 (2014) 1–12

measurement or attempts to renegotiate. The overall conclusion isthat the ECX has succeeded in bringing down the incidence of dis-putes in some areas, but has increased them in other areas. Giventhe fact that not all of the components of the ECX are functioningas expected (such as the quality control at warehouses), this is tobe expected.

Robustness analysis

As a robustness analysis we used a regression analysis toexplain variation in our main dependent variables (equation 1).To economize on space we only report coefficients and standarderrors associated with the ECX dummy, the exporter dummy, and

G. Meijerink et al. / Food Policy 49 (2014) 1–12 11

the interaction term (additional details are available in the onlineappendix). Additional controls were included in the estimations.In one model we only include demographic characteristics (age,education, sex, years in business), obviously exogenous to the cre-ation of the ECX. In another model we include both demographic aswell as potentially endogenous variables (amounts purchased andsold, prices paid and received). In light of the potential endogeneityof these variables we emphasize these latter regression resultsshould be interpreted with care. We ran the regression model forall indicators shown in the previous tables and find that, overall,the regression results support the patterns discussed above; socialcapital became less important after the introduction of the ECX, inparticular for exporters.

Table 7 contains the results for a large and representative sampleof social capital indicators. Columns (1) and (2) present OLS resultsand columns (3) and (4) contain the regression output for modelswith trader fixed effects. The coefficient associated with the ECXdummy picks up any effect of the ECX on social capital for othertraders. Depending on the nature of the proxy, as mentioned above,the substitution hypothesis is consistent with a negative (e.g., creditprovision) or positive coefficient (e.g., number of trading contacts).Similarly, for the ECX to have a more profound effect on exportersthan on other traders, the coefficient of the interaction term shouldbe negative for some proxies and positive for others.

The regression results tend to match our earlier findings, asreported in Tables 2–6. For example, consider the results in the col-umn of the parsimonious OLS regression model. While the numberof trading contacts in the main sales market has remained more orless the same for all traders (b1 = 0), it has increased for exportersafter the introduction of the ECX (b3 > 0). Results for the number oftrading contacts in the purchase market are not significant. Theproportion purchased with regular suppliers decreased for all trad-ers, but especially for exporters (b1 < 0, b3 < 0). The same is truewith respect to the provision of credit: all traders, especiallyexporters, are less likely to obtain credit (b1 < 0, b3 < 0). Also, incontrast to other traders, exporters are less likely to extend creditafter the introduction of the ECX (b1 > 0, b3 < 0). We also obtain sig-nificant results for the proxy measuring the extension of advancepayments to farmers, and find that advance payments to othertraders have fallen for all traders, b1 < 0, and especially for export-ers, b3 < 0. Finally, and also consistent with our earlier results, trad-ers are more likely to use a buying agent (b1 > 0), and again we finda differential response from exporters (b3 > 0).

The regression results for the elaborate model are even stron-ger, and now we also obtain significant year and interaction effectsfor the variable measuring advance payments to farmers (b1 < 0,b3 < 0). The fixed effects results in columns (3) and (4) are alsoroughly similar. Even if the exporter dummy no longer enters sig-nificantly in these models, the year variable and year-exporterinteraction term tend to enter significantly and are of the ‘‘right’’sign.

Discussion and conclusions

A small literature considers the multi-faceted relation betweenintegration in formal markets and trust. It is clear that trust fosterstrade. For trade to extend beyond what Fafchamps (2004) hascalled a ‘flea market’ exchange, where sales are made on a cash-and-carry basis, moral obligations of fairness and reciprocityshould extend to strangers, not just to kith and kin. Generalizedmorality and trust enables expansion of markets (e.g., Tu andBulte, 2010). But, in turn, trade may also affect trust. For example,Henrich et al. (2010) argue that integration into markets (or thetransition from personalized to anonymous exchange) is associ-ated with higher levels of generalized trust. They propose that

‘market norms may have evolved as part of an overall process ofsocietal evolution to sustain mutually beneficial exchanges in con-texts where established social relations (for example, kin, reciproc-ity, status) were insufficient’ (p. 1480). Hence, market integration‘involved the selective spread of those norms and institutions thatbest facilitated successful exchange. . .’ (p. 1484). If markets fostertrust, and trust fosters market integration, then markets and trustare complements in development, enabling virtuous cycles ofdevelopment.

However, market integration and trust may not necessarilyevolve hand-in-hand. For example, Kumar and Matsusaka (2009)emphasize the difference between ‘village social capital’ and ‘mar-ket social capital.’ Village social capital typifies rural economies inpoor countries, capturing kinship ties, patron-client relations, andrepeated personalised exchange governed by trust and reciprocity.In contrast, market social capital involves access to and knowledgeabout third-party punishment, including courts, auditors, creditratings, and so on – or the type of formal institutions associatedwith the ECX and analyzed in the current paper. To fully benefitfrom specialisation and trade, Kumar and Matsusaka argue, com-munities should adjust the composition of their social capitalstocks––divesting in village capital and investing in market capital.If so, market integration and trust are substitutes, rather than com-plements, in development. Tentative evidence provided by Sizibaand Bulte (2012) supports this perspective.

Are formal and informal institutions complements or substi-tutes? To a large extent the answer to this question depends onthe perspective chosen. For example, market integration may fos-ter generalized trust (enabling exchange with anonymous others)while simultaneously eroding (average) trust in trading partners(personalized trust).

In this paper we further probe the relation between formal andinformal institutions as mechanisms to govern trade. Focusing onthe sesame value chain, we document evidence suggesting thatthe Ethiopian Commodity Exchange (ECX) has substituted informalgovernance mechanisms—traders have expanded the set of partieswith whom they trade, are less likely to extend credit to their part-ners, and are less likely to invest in ‘social relations’ with theirtrading partners. Moreover, traders express that trust has becomeless important following the creation of the ECX, and state thatthey trust their trading partners less than before. These patternsin the data are more pronounced for exporters than for ‘other trad-ers,’ consistent with the hypothesis that the substitution effects areespecially pronounced for exporters who fully operate within therealm of the ECX (in contrast to ‘other traders’ who operate withinand beyond the realm of the ECX).

We realize that methodological issues remain. The time lagbetween the creation of the ECX and our ex-post measurementsis very short, and attribution is far from perfect because a propercontrol group does not exist––no traders in the sesame value chainare unaffected by the ECX. Hence our empirical results should beinterpreted with care, and we argue in favor of future scrutinyand replication in different contexts. Nevertheless, we believeour results to be relevant. Commodity exchanges are increasinglyregarded as a powerful tool to promote agricultural developmentin developing countries, yet the impact of these institutions ontraders is unclear. Indeed, we believe this is the first attempt todocument the impact of commodity exchanges on social capitalof traders—a crucially important yet chronically under-researchedset of actors in the broader development debate.

Our tentative results may have significant implications for pol-icy makers. The erosion of social capital could, in theory, attenuateor reverse the potential welfare gains associated with expansion offormal institutions (such as commodity exchanges). For example,Dixit (2004) compares the outcomes of relational and formal con-tracting, and demonstrates that opportunities created by formal

12 G. Meijerink et al. / Food Policy 49 (2014) 1–12

contracting may undermine the scope for relational contracting.Formal contracting may make first-best outcomes unattainable,so that overall efficiency deteriorates as formal institutionsdevelop. The mechanism explaining this counter-intuitive resultis as follows: the harsher is the punishment facing deviators, thebetter the informal (repetitive) equilibrium that can be sustained.If formal contracting provides a fall-back option for deviating trad-ers, then deviating will occur more often unless the scope for suchbehavior is reduced by altering the terms of the informal contract.In other words, when the incentive contract is binding and theinformal contract yields a second best outcome, then a partialimprovement in formal institutions worsens the outcome of theinformal contract. However, even in the absence of such counter-intuitive outcomes, it is important for policy makers to realize thatformal institutions have an effect on informal institutions, and thatthe expansion of formal contracts, by new regulations or policies,may invite the erosion of norms and informal rules in the sameor adjacent domains of human interaction.

Appendix A. Supplementary material

Supplementary data associated with this article can be found, inthe online version, at http://dx.doi.org/10.1016/j.foodpol.2014.05.015.

References

Adler, P.S., 2000. Social Capital: The Good, The Bad and The Ugly. In: Lesser, E.L.(Ed.), Knowledge Social Capital: Foundations Applications. Butterworth-Heinemann.

Ahlerup, P., Olsson, O., Yanagizawa, D., 2009. Social Capital vs Institutions in theGrowth Process. Eur. J. Polit. Econ. 25 (1), 1–14.

Barrett, H.R., 1988. The marketing of foodstuffs in the Gambia, 1400–1980: ageographical analysis. Avebury, Aldershot.

Bigsten, A., Collier, P., Dercon, S., Fafchamps, M., Gauthier, B., Gunning, J.W., Oduro,A., Oostendorp, R., Patillo, C., Soderbom, M., Teal, F., Zeufack, A., 2000. Contractflexibility dispute resolution in African manufacturing. J. Develop. Stud. 36, 1–37.

Boettke, P., Coyne, C., Leeson, P., 2008. Institutional stickiness the new developmenteconomics. Am. J. Econ. Soc. 67 (2), 331–358.

Caselli, F., 1997. Rural markets and credit markets. J. Dev. Econ. 54, 235–260.Cecchi, F., Bulte, E., 2013. Does market experience promote rational choice?

Experimental evidence from rural Ethiopia. Econ. Develop. Cult. Change 61 (2),407–429.

Coulter, J., 2012. Review of WRS in Eastern Southern Africa – Ethiopia (UnpublishedPaper).

Das, T.K., Teng, B.-S., 2004. The risk-based view of trust: a conceptual framework. J.Business Psychol. 19 (1), 85–116.

Dixit, A., 2004. Lawlessness and Economics. Princeton University Press, Princeton.ECX, 2011. Farmers become beneficiary of ECX warehouse receipt scheme.

Gebeyachin 1 (4).ECX, 2012. ECX Announces Solid End-of-Year Performance Results (No. June 28,

2012). Addis Abeba: Ethiopia Commodity Exchange.Fafchamps, M., 2004. Market Institutions in Sub-Saharan Africa: Theory and

Evidence. MIT Press Books, Cambridge, Massachusetts.Fafchamps, M., Minten, B., 2002. Returns to social network capital among traders.

Oxford Econ. Pap. 54, 173–206.FAOSTAT, 2012. FAO Statistical Database: Trade. Rome: Food and Agriculture

Organisation: <http://faostat.fao.org/> (accessed February 4th, 2012).

Fisman, R., Raturi, M., 2004. Does competition encourage credit provision? evidencefrom african trade and credit relationships. Rev. Econ. Stat. 86 (1), 345–352.

Gabre-Madhin, E., 2001. Market Institutions, Transaction Costs, Social Capital in theEthiopian Grain Market. IFPRI, Washington DC.

Gabre-Madhin, E., Goggin, I., 2005. Does Ethiopia Need a Commodity Exchange? AnIntegrated Approach to Market Development (Working Paper No. 4). EDRI-ESSPPolicy Working Papers (p. 26). IFPRI, Washington DC.

Giannetti, M., Burkart, M., Ellingsen, T., 2011. What you sell is what you lend?Explaining trade credit contracts. Rev. Financ. Stud. 24 (4), 1261–1298.

Government of Ethiopia, 2010. Regulation No. 178/2010 Sesame White Pea BeansTransaction Council of Ministers Regulation (No. 178/2010). Council ofMinisters, government of Ethiopia.

Habib-Mintz, N., 2009. To what extent can the informal economy conceptadequately explain the dynamism of the non-formal sector in developingcountries? J. Int. Busin. Econ. 10 (1), 1–19.

Hart, K., 1973. Informal income opportunities and urban employment in Ghana. J. fModern Afr. Stud. 11 (1), 61–89.

Henrich, J., Ensminger, J., McElreath, R., Barr, A., Barrett, C., Bolyanatz, A., Cardenas,J., Gurven, M., Gwako, E., Henrich, N., Lesorogol, C., Marlowe, F., Tracer, D., Ziker,J., 2010. Markets, religion, community size, and the evolution of fairness andpunishment. Science 327, 1480–1484.

Hermes, N., Kihanga, E., Lensink, R., Lutz, C., 2012. The impact of trade credit oncustomer switching behaviour: evidence from the Tanzanian rice market. J.Develop. Stud. 48 (3), 363–376.

IFC and ECX, 2012. Session summaries. Presented at the Warehouse ReceiptSystems for Inclusive Agriculture Finance, June 4–5 2012, Addis Ababa.

Kingston, C., Caballero, G., 2009. Comparing theories of institutional change. J. Inst.Econ. 5 (2), 151–180.

Kumar, K.B., Matsusaka, J.G., 2009. From families to formal contracts: an approachto development. J. Dev. Econ. 90, 106–119.

Loveridge, S., 1995. A multi-product sub-setor study in Rwanda. In: Prices, Products,and People: Analyzing Agricultural Markets in Developing Countries (pp. 99–114). Lynne Rienner Publishers, Boulder, Colorado.

Mason, N., Jayne, T., Chapoto, A., Donovan, C., 2011. Putting the 2007/2008 globalfood crisis in longer-term perspective: trends in staple food affordability inurban Zambia Kenya. Food Policy 36, 350–367.

Narayan, D., Pritchett, L., 1999. Cents and sociability: household income and socialcapital in rural Tanzania. Econ. Dev. Cult. Change 47, 871–897.

Tu, Q., Bulte, E.H., 2010. Trust, market participation and economic outcomes:evidence from Rural China. World Dev. 38, 1179–1190.

Quattri, M., Ozanne, A., Beyene, S.T., 2012. The Development of AgriculturalMarkets: New Evidence from Ethiopia (No. 36). ESSP II Working Paper, IFPRI,Washington DC.

Rashid, S., Negassa, A., 2011. Policies Performance of Ethiopian Cereal Markets (No.21), IFPRI, Washington DC.

Roberts, B., 1994. Informal economy and family strategies. Int. J. Urban Reg. Res. 18(1), 6–23.

Scott, G.J., 1995. Prices, Products, and People: Analyzing Agricultural Markets inDeveloping Countries. Lynne Rienner Publishers, Boulder, Colorado.

Sitko, N., Jayne, T.S., 2012. Why are African commodity exchanges languishing: acase study of the Zambian agricultural commodity exchange. Food Policy 37 (3),275–282.

Siziba, S., Bulte, E.H., 2012. Does market participation promote generalized trust?Experimental evidence from Southern Africa. Econ. Lett. 117, 156–160.

Smale, M., Byerlee, D., Jayne, T., 2011. Maize Revolutions in Sub-Saharan Africa.Policy Research Working Paper # 5659, World Bank, Washington DC.

Tabellini, G., 2008. The scope of cooperation: values and incentives. Quart. J. Econ.123, 905–950.

Van den Broek, J., 2012. Overview ECX in Ethiopia. Presented at the Food Securityvideo conference organised by EKN Kigali 18 October 2012.

Wijnands, J., Biersteker, J., Van Loo, E.N., 2009. Oilseeds Business Opportunities inEthiopia 2009 (p. 62). Public Private Partnership on Oilseeds, The Hague, TheNetherlands.

Williamson, O.E., 1993. Calculativeness, trust, economic organization. J. Law Econ.36, 453–486.

Williamson, C., 2009. Informal institutions rule: institutional arrangementseconomic performance. Public Choice 139, 371–389.