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Cartels and Rent Sharing at the Farmer–Trader Interface: Evidence from Ghana’s Tomato Sector

  • Guyslain K. Ngeleza EMAIL logo and Elizabeth J.Z. Robinson
Published/Copyright: May 22, 2013
Journal of Agricultural & Food Industrial Organization
From the journal Journal of Agricultural & Food Industrial Organization Volume 11 Issue 1

Abstract

Itinerant traders provide an important route for West Africa’s farmers’ to get their perishable produce rapidly to the distant urban markets. But these farmers often accuse the traders of offering “unfairly” low prices while preventing direct access to these markets. Using Ghana’s tomato sector as a case study, we provide the first detailed exploration of the interface between Ghana’s farmers and traders, combining a theoretical model with novel empirical data on daily sales prices and tomato quality. We find that although the prices traders pay farmers are lower than prices in the urban markets, taking into account transport costs, these prices are higher than farmers receive from the local rural market. Our article suggests that policymakers would do better to focus on opening up access to the urban markets rather than on strengthening farmers’ bargaining power with the traders, which restricts market volumes further and harms farmers unable to sell to traders.

Keywords: arbitrage; agriculture value chains; trader cartels; Ghana

Appendix

Table 6

Price equality test, December 2009 to April 2010.

Marketing routeTradersLocal market
Traders (“market queens”)
Local markets0.101***
(0.011)
[107]
Processors0.194***0.104***
(0.029)(0.042)
[12][8]

Source: Author calculations.

Notes: [***]. Standard errors in parentheses and number of observations in brackets.

The analysis of variance test is a general robustness test that allows us to investigate the three marketing routes simultaneously to see if there is any difference in the mean prices farmers receive from each, although it does not enable us to say which group is different or the magnitude of that difference. We conducted pairwise t-tests on alternative pairs of marketing routes: traders versus local markets; traders versus agroprocessors; and local markets versus agroprocessors. For these pairs, we compare prices only when we have a sale on the same day.

Table 7

Differences in fruit quality between tomatoes sold by farmers to traders and through other marketing routes.

No. of obs.Shelf life (days)Fruit weightFruit diameter (cm)pHTSS (% Brix)ColorscoreTTA
Local markets71−2.7243.1450.0150.008−0.472***−0.313−0.012***
(1.968)(2.671)(0.076)(0.051)(0.167)(0.299)(0.005)
Agroprocessors13−0.893−2.284−0.0660.0840.647***−0.2130.013*
(3.382)(3.701)(0.104)(0.092)(0.272)(0.567)(0.009)

Source: Author calculations.

Notes: [***], [*]. Standard errors in parentheses and number of observations in brackets.

Table 8

Ordinary least squares (OLS) regression results of price received by Upper East farmers.

IIIIIIIVVVI
Log (quantity)–0.025***–0.078***–0.078***–0.0541**–0.067***–0.071***
(0.006)(0.023)(0.022)(0.024)(0.026)(0.027)
Marketing route (trader)0.330***0.324***0.336***0.381***0.411***
(0.048)(0.048)(0.048)(0.055)(0.059)
Log (wealth)0.026***0.082***0.088***0.084***0.080***0.091***
(0.006)(0.021)(0.021)(0.0213)(0.021)(0.022)
Belong to association0.093***0.480***0.399**0.351**
(0.035)(0.155)(0.162)(0.167)
Log (quantity)*belong to association–0.072*–0.045–0.040
(0.028)(0.032)(0.034)
Log (trader)*belong to association–0.136*–0.089
(0.081)(0.086)
Log (quality)
Shelf life0.0120.0100.006–0.009
(0.034)(0.034)(0.034)(0.039)
Fruit weight–0.582***
(0.218)
Fruit diameter1.646***
(0.541)
PH–0.193
(0.325)
Color score0.087
(0.106)
TSS0.151***
(0.052)
TTA0.089
(0.071)
Sub-seasonal dummy0.076***0.283***0.278***0.271***0.266***0.258***
(0.009)(0.033)(0.034)(0.033)(0.034)(0.035)
Bongo–0.013–0.346***–0.386***–0.391***–0.355***–0.424***
(0.021)(0.087)(0.088)(0.087)(0.090)(0.091)
Kassena Nankana East–0.084***–0.371***–0.369***–0.384***–0.396***–0.516***
(0.019)(0.072)(0.074)(0.074)(0.074)(0.083)
Kassena Nankana West–0.029–0.306***–0.287***–0.314***–0.312***–0.349***
(0.020)(0.075)(0.076)(0.076)(0.076)(0.081)
Talensi-Nabdam–0.022–0.350***–0.359***–0.382***–0.354***–0.362***
(0.022)(0.087)(0.086)(0.086)(0.088)(0.090)
CONS0.234***–1.533***–1.643***–1.722***–1.635***–1.519***
(0.033)(0.120)(0.159)(0.161)(0.169)(0.614)
Number of observation524524524524524500
R2-adjusted0.230.320.320.330.330.37
Wald χ223.84***31.14***25.88***24.38***22.66***16.95***

Source: Authors estimation.

Notes: [***], [**][*].

Figure 5 Price received by farmer member of an association and farmer non-member of an association.Source: Constructed by the authors from the 2009–10 dry-season irrigated tomato data.
Figure 5

Price received by farmer member of an association and farmer non-member of an association.

Source: Constructed by the authors from the 2009–10 dry-season irrigated tomato data.

Figure 5 shows a sub-sample of the sales that occurred throughout the season where we are able to match same-day sales by farmers belonging to a famer association or not. We find that prices received by farmers belonging to an association are higher. These results are confirmed by a t-test of the difference of means where farmers belonging to an association receive 0.037 GHc per kilo more than farmers who do not.

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  1. 1

    Limited processing is a typical characteristic of many agricultural markets in developing countries (see Sexton 1990).

  2. 2
  3. 3

    When data were collected, one Ghanaian cedi (GHS) was equivalent to US$0.71.

  4. 4

    Table 6 in the Appendix presents results of a simple OLS of our model specifications. While in terms of significance the OLS results are similar to the results in the instrumental variable regressions, they are smaller in magnitude.

  5. 5

    See Fafchamps, M. and R. V. Hill. 2005 for similar methodology.

  6. 6
Published Online: 2013-05-22

©2013 by Walter de Gruyter Berlin / Boston

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  1. Masthead
  2. Masthead
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  5. Cartels and Rent Sharing at the Farmer–Trader Interface: Evidence from Ghana’s Tomato Sector
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https://doi.org/10.1515/jafio-2012-0011
Keywords for this article
arbitrage; agriculture value chains; trader cartels; Ghana

Articles in the same Issue

  1. Masthead
  2. Masthead
  4. Identification of Market Power in the Hungarian Dairy Industry: A Plant-Level Analysis
  5. Cartels and Rent Sharing at the Farmer–Trader Interface: Evidence from Ghana’s Tomato Sector
  6. Research Article
  7. Understanding Challenges to Food Security in Dry Arab Micro-States: Evidence from Qatari Micro-Data
  8. Planning Marketing Channels: Case of the Olive Oil Agribusiness in Portugal
  9. (A)symmetry, (Non)linearity and Hysteresis of Pricing-To-Market: Evidence from German Sugar Confectionery Exports
  10. Oligopolistic Market Structure in the Japanese Pistachio Import Market
  11. Quality Differentiation with Flavors: Demand Estimation of Unobserved Attributes
  12. A Mechanism Design of Dispute Resolution Systems in a Regional-Free Trade Agreement
  13. Conflict over Cooperation: Why So Much Disagreement over the Proposed Dairy Market Stabilization Program?
  14. U.S. Brewing Industry Profitability: A Simultaneous Determination of Structure, Conduct, and Performance
  15. The Cooperative Yardstick Revisited: Panel Evidence from the European Dairy Sectors
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