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Producer to retailer price transmission in cereal markets of Ethiopia

Abstract

This paper investigates price transmission between producer and retail prices of teff, wheat, and maize in Amhara and Oromia, the two major cereal markets in Ethiopia. Market and cereal specific asymmetric error correction models were estimated to analyze producer-retail price transmission using monthly data from 2001 to 2011. For seven out of eight crop-market combinations, with the exception of the Amhara wheat market, we found no evidence of asymmetric price transmission from producer to retail prices in the long run. Neither contemporaneous nor long-run price transmission asymmetry was found in either the Amhara or Oromia teff markets. This was also the case for the maize market except that there existed a short-run asymmetric price transmission that disappeared in the long run in Oromia. We therefore conclude that there is no strong empirical evidence to support the purported ‘market power’ or ‘inventory holding’ behaviour in the Ethiopian cereal markets to explain asymmetric vertical price transmission in the long run. The evidence of asymmetric price transmission for the Amhara wheat market, unlike the wheat market in Oromia, may indicate some differential in the quality of infrastructure and the length and complexity of wheat value chains between these two markets. Symmetric price adjustments in these cereal markets suggest that input price changes may have positive long run implications for food security and welfare of the poor in Ethiopia.

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Notes

  1. 1.

    For instance, export ban of basic-consumption cereals, introduction of a price cap for major food items, rationing wheat and flour at subsidized prices to poor households in major urban centres and direct government import by the Ethiopian Grain Trade Enterprise (EGTE) for open market sales. The effectiveness of such measures to stabilize the market is, however, outside the scope of this paper.

  2. 2.

    Yet, incomplete transmission of high farm gate prices to retail prices could, in the short-run, be beneficial for food security of urban consumers.

  3. 3.

    According to the CSA (2012) report, in the 2011/2012 harvest season (meher), maize was the largest cereal crop in the country in terms of production volume, followed by sorghum, teff, and then wheat.

  4. 4.

    Meyer and von Cramon-Taubadel (2004) and Vavra and Goodwin (2005) provide a comprehensive summary of the causes of vertical APT as mentioned in the previous studies.

  5. 5.

    Menu costs refer to all costs associated with making adjustments in retail prices, which include advertising and labelling, as well as potential loss in the firm’s reputation due to frequent price changes (Vavra and Goodwin 2005).

  6. 6.

    See Meyer and von Cramon-Taubadel (2004), Weldegebriel (2004) and Frey and Manera (2007) for a comprehensive review of previous studies dealing with potential causes of asymmetries and methodological issues in price transmission.

  7. 7.

    Maize and teff are the main cereal staple food crops in Ethiopia, while teff is the most valuable cereal crop. In this analysis, we considered only white teff and white wheat varieties.

  8. 8.

    1 USD = 18.16 Ethiopian Birr in July 2012 (www.nbe.gov.et).

  9. 9.

    The CPI obtained from the FAOSTAT database (www.faostat.fao.org).

  10. 10.

    In the model selection criterion to test for ADF, the lag lengths are selected from the model that gives the lowest Akaike Information Criterion (AIC). Enough lag lengths are included in the model until the serial correlations in the residuals are eliminated. The number of lagged difference term to be included can be determined based on a t-test, an F-test, or using model selection criteria such as the AIC, Schwarz − Bayesian Information Criterion (SIC) and Hannan − Quinn Information Criterion (HQ).

  11. 11.

    The assumption of the linear adjustment from producer to retail market level is motivated for the reason that these commodities do not undergo any sort of processing along the market chain.

  12. 12.

    We start from the general ADF model that contains both a constant and a trend. Since the unit root is not rejected based on the general test form, we proceeded the test without a time trend and a drift. The results showed that both the trend and the drift were statistically not significant based on the ADF τ-statistics at the 5% significance level. Therefore, the ADF test reported in Table 2 was performed without drift and time trend.

  13. 13.

    The Engle-Granger test statistic is computed without any drift or deterministic covariates, and the choice to include lagged difference in the ADF regression was determined using automatic lag selection based on Schwarz Criterion with a maximum lag of 12.

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Correspondence to Muhammed A. Usman.

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Usman, M.A., Haile, M.G. Producer to retailer price transmission in cereal markets of Ethiopia. Food Sec. 9, 815–829 (2017). https://doi.org/10.1007/s12571-017-0692-0

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Keywords

  • Asymmetry vertical price transmission
  • Error correction model
  • Cereals
  • Ethiopia

JEL classification

  • C32
  • D40
  • Q13