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Relationship Between Spatial Price Transmission And Geographical Distance In Brazil


  • Hernandez-Villafuerte, Karla Vanessa


The price transmission between markets is often interpreted as providing insights into the market’s infrastructure efficiency and transaction costs. Thus, finding a possible explanation for the degree of integration has become an issue of special interest. Recent researchers have pointed out the distance between markets as one of the possible factors. However, the distance is closely related with other elements, such as road quality and the proximity to an export point, which affect transport costs, opportunity costs and thus the integration. Therefore, what the most important factor is when determining the relationship among markets remains unclear. The cointegration framework, OLS and principal component regressions are applied in order to investigate the influence of geographical distance on the cointegration relationship between Brazil`s rice markets. In response to changes of the agricultural policies during the period of investigation, the presence of multiple structural breaks in the long run equation is allowed. The results point out a weak, negative and significant relation between distance and the elasticity of cointegration. Moreover, the region in which the market is located and a better access to export points are the main variables which defined the strength of the price transmission.

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  • Hernandez-Villafuerte, Karla Vanessa, 2011. "Relationship Between Spatial Price Transmission And Geographical Distance In Brazil," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114545, European Association of Agricultural Economists.
  • Handle: RePEc:ags:eaae11:114545
    DOI: 10.22004/ag.econ.114545

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    References listed on IDEAS

    1. Gregory, Allan W. & Hansen, Bruce E., 1996. "Residual-based tests for cointegration in models with regime shifts," Journal of Econometrics, Elsevier, vol. 70(1), pages 99-126, January.
    2. Kejriwal, Mohitosh & Perron, Pierre, 2010. "Testing for Multiple Structural Changes in Cointegrated Regression Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(4), pages 503-522.
    3. Thomas Gries & Wim Naudé & Marianne Matthee, 2009. "The Optimal Distance To Port For Exporting Firms," Journal of Regional Science, Wiley Blackwell, vol. 49(3), pages 513-528, August.
    4. Gloria González-Rivera & Steven M. Helfand, 2001. "The Extent, Pattern, and Degree of Market Integration: A Multivariate Approach for the Brazilian Rice Market," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 576-592.
    5. Javier Escobal & Arturo Vásquez, 2005. "Market integration for agricultural output markets in Peru: the role of public infrastructure," Urban/Regional 0507003, University Library of Munich, Germany.
    6. Sanogo, Issa, 2008. "SPATIAL integration of the rice market: emprirical evidence from mid-west and far-west Nepal and the Nepalese-Indian border," MPRA Paper 14488, University Library of Munich, Germany.
    7. Steven M. Helfand & Gervásio Castro de Rezende, 2015. "Brazilian Agriculture in the 1990s: Impact of the Policy Reforms," Discussion Papers 0098, Instituto de Pesquisa Econômica Aplicada - IPEA.
    8. King, Gary & Honaker, James & Joseph, Anne & Scheve, Kenneth, 2001. "Analyzing Incomplete Political Science Data: An Alternative Algorithm for Multiple Imputation," American Political Science Review, Cambridge University Press, vol. 95(1), pages 49-69, March.
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    Demand and Price Analysis;


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