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Cross-Correlations in Meat Prices in Brazil: A Non-Linear Approach Using Different Time Scales

Author

Listed:
  • Derick Quintino

    (Department of Economics, Administration and Sociology, University of São Paulo, Piracicaba 13418-900, SP, Brazil)

  • José Telo da Gama

    (VALORIZA—Research Center for Endogenous Resource Valorization, 7300-555 Portalegre, Portugal
    Instituto Politécnico de Portalegre, 7300-110 Portalegre, Portugal)

  • Paulo Ferreira

    (VALORIZA—Research Center for Endogenous Resource Valorization, 7300-555 Portalegre, Portugal
    Instituto Politécnico de Portalegre, 7300-110 Portalegre, Portugal
    CEFAGE-UE, IIFA, Universidade de Évora, Largo dos Colegiais 2, 7004-516 Évora, Portugal)

Abstract

Brazil is one of the world’s largest producers and exporters of cattle, chicken and swine. Therefore, co-movements of Brazilian meat prices are important for both domestic and foreign stakeholders. We propose to analyse the cross-correlation between meat prices in Brazil, namely, cattle, swine and chicken, including also in the analysis information from some commodities, namely maize, soya beans, oil, and the Brazilian exchange rate. Our sample covers the recent period which coincided with extensive macroeconomic and institutional changes in Brazil, from 2011 to 2020, and is divided in two periods: (i) presidential pre-impeachment (P1), occurring in August 2016, and; (ii) post-impeachment (P2). Our results indicate that in P1, only the prices of swine and chicken showed a positive and strong correlation over time, and that cattle showed some positive correlation with chicken only in the short run. In P2, there was also a positive and consistent correlation between swine and chicken, and only a positive association with swine and cattle in the long run. For more spaced time scales (days), the changes in the degree of correlation were significant only in the long run for swine and cattle.

Suggested Citation

  • Derick Quintino & José Telo da Gama & Paulo Ferreira, 2021. "Cross-Correlations in Meat Prices in Brazil: A Non-Linear Approach Using Different Time Scales," Economies, MDPI, vol. 9(4), pages 1-12, September.
  • Handle: RePEc:gam:jecomi:v:9:y:2021:i:4:p:133-:d:640280
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    References listed on IDEAS

    as
    1. Zebende, G.F. & da Silva Filho, A.M., 2018. "Detrended Multiple Cross-Correlation Coefficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 91-97.
    2. David, S.A. & Inácio, C.M.C. & Quintino, D.D. & Machado, J.A.T., 2020. "Measuring the Brazilian ethanol and gasoline market efficiency using DFA-Hurst and fractal dimension," Energy Economics, Elsevier, vol. 85(C).
    3. da Silva, Marcus Fernandes & Leão Pereira, Éder Johnson de Area & da Silva Filho, Aloisio Machado & Nunes de Castro, Arleys Pereira & Miranda, José Garcia Vivas & Zebende, Gilney Figueira, 2015. "Quantifying cross-correlation between Ibovespa and Brazilian blue-chips: The DCCA approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 124-129.
    4. Oussama Tilfani & Paulo Ferreira & My Youssef El Boukfaoui, 2021. "Dynamic cross-correlation and dynamic contagion of stock markets: a sliding windows approach with the DCCA correlation coefficient," Empirical Economics, Springer, vol. 60(3), pages 1127-1156, March.
    5. Zebende, G.F., 2011. "DCCA cross-correlation coefficient: Quantifying level of cross-correlation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(4), pages 614-618.
    6. Derick David Quintino & Paulo Ferreira, 2021. "Diesel prices in Brazil: A dynamic fractional integration analysis," Economics and Business Letters, Oviedo University Press, vol. 10(2), pages 116-125.
    7. Zingbagba, Mark & Nunes, Rubens & Fadairo, Muriel, 2020. "The impact of diesel price on upstream and downstream food prices: Evidence from São Paulo," Energy Economics, Elsevier, vol. 85(C).
    8. Mourad Zmami & Ousama Ben-Salha, 2019. "Does Oil Price Drive World Food Prices? Evidence from Linear and Nonlinear ARDL Modeling," Economies, MDPI, vol. 7(1), pages 1-18, February.
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