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Price transmission in domestic agricultural markets: the case of retail and wholesale markets of maize in Rwanda

  • Ngango, Jules (Department of Agricultural Economics, Chungnam National University) ;
  • Hong, Seungjee (Department of Agricultural Economics, Chungnam National University)
  • Received : 2020.07.09
  • Accepted : 2020.07.28
  • Published : 2020.09.01

Abstract

One of the main challenges receiving much attention in the Rwandan agriculture and food industry in recent decades is the increases in maize prices. Indeed, a rise in maize prices causes higher living expenses for households because maize, which is a major staple food crop, constitutes a significant share of total food consumption among households in Rwanda. The aim of this study was to assess the extent of integration and how prices are transmitted between retail and wholesale markets of domestic maize in Rwanda. This study used monthly data of retail and wholesale prices of maize from January 1995 to December 2019. This empirical investigation was based on a linear cointegration approach and an asymmetric error correction model framework. Using the augmented dickey-fuller residual-based test and the Johansen Maximum Likelihood cointegration test, the results revealed that the retail and wholesale markets of maize are integrated. Hence, prices in these markets do not drift apart in the long run. The results of the Granger causality test revealed that there is a unidirectional causal relationship flowing from wholesale prices to retail prices, i.e., wholesale prices influence retail prices. Accordingly, the results from the asymmetric error correction model confirmed the presence of a positive asymmetric price transmission between wholesale and retail prices of maize in Rwanda. Thus, we suggest that policymakers take a critical look at the causes and factors that may influence asymmetry price transmission.

Keywords

References

  1. Abdulai A. 2007. Spatial and vertical price transmission in food staples market chains in eastern and southern Africa: What is the evidence spatial and vertical price transmission in food staples market chains in eastern and southern Africa: What is the evidence? Paper pr. In FAO Workshop on Staple Food Trade and Market Policy Options for Promoting Development in Eastern and Southern Africa. Accessed in https://www.researchgate.net/publication/239547250 on 25 June 2020.
  2. Acquah H, Micah J, Owusu R. 2012. Price transmission in domestic agricultural markets: Evidence from selected Cassava markets In Ghana. Journal of Sustainable Development in Africa 14:218-228.
  3. Alexander C. 2001. Market models: A guide to financial data analysis. John Wiley & Sons, Hoboken, NJ, USA.
  4. Azzam AM. 1999. Asymmetry and rigidity in farm-retail price transmission. American Journal of Agricultural Economics 81:525-533. https://doi.org/10.2307/1244012
  5. Balcombe K, Morrison J. 2002. Commodity price transmission: A critical review of techniques and an application to selected export commodities. A Study for the Food and Agricultural Organization (ESCR) of the United Nations, Rome, Italy.
  6. Barahona JF, Trejos B, Lee JW, Chulaphan W, Jatuporn C. 2014. Asymmetric price transmission in the livestock industry of Thailand. APCBEE Procedia 8:141-145. https://doi.org/10.1016/j.apcbee.2014.03.016
  7. Dickey DA, Fuller WA. 1979. Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association 74:427-431. https://doi.org/10.1080/01621459.1979.10482531
  8. Engle RF, Granger CWJ. 1987. Co-integration and error correction: representation, estimation, and testing. Econometrica 55:251-276. https://doi.org/10.2307/1913236
  9. FAOSTAT. 2019. Food and Agriculture Organization of the United Nations. Accessed in http://www.fao.org/faostat/en/#data/QC on 19 June 2020.
  10. Frederick B, Cho GD, Kim IS. 2018. Asymmetric price transmission in the domestic rice market in South Korea. Korean Journal of Agricultural Economics 59:205-223.
  11. Houck JP. 1977. An approach to specifying and estimating nonreversible functions. American Journal of Agricultural Economics 59:570-572. https://doi.org/10.2307/1239663
  12. Johansen S, Juselius K. 1990. Maximum likelihood estimation and inference on cointegration-with applications to the demand for money. Oxford Bulletin of Economics and Statistics 52:169-210. https://doi.org/10.1111/j.1468-0084.1990.mp52002003.x
  13. Morales LE. 2018. The effects of international price volatility on farmer prices and marketing margins in cattle markets. International Food and Agribusiness Management Review 21:335-350. https://doi.org/10.22434/IFAMR2017.0020
  14. Mulinga N. 2013. Economic analysis of factors affecting technical efficiency of smallholders maize production on Rwanda. Rwanda Journal 1:52-62.
  15. Musabanganji E, Karangwa A, Lebailly P. 2015. Price transmission mechanism analysis: An application to selected foodstuffs on the main markets of the Southern Rwanda. East African Journal of Science and Technology 5:179-200.
  16. Ngango J, Kim SG. 2019. Assessment of technical efficiency and its potential determinants among small-scale coffee farmers in Rwanda. Agriculture 9:1-12. https://doi.org/10.3390/agriculture9010001
  17. Nsabimana A, Habimana O. 2017. Asymmetric effects of rainfall on food crop prices: Evidence from Rwanda. Economics 8:137-149.