Coffee market price as a reflection of the brazilian harvest
DOI:
https://doi.org/10.33448/rsd-v13i8.46481Keywords:
Arabic; Coffea sp.; Conilon; Correlation; Pearson.Abstract
Brazilian agribusiness has great importance in the constitution of national gross domestic product, reaching values of more than 27% representativeness. Within the agricultural products we have coffee as one of the great crops in our country. As it is known its market value fluctuates, like all products, by the most diverse factors. This work aimed to evaluate the existence or not of a correlation in the market price of coffee with production factors in Brazil. Variation along the years of Brazilian total coffee production, total area in production and area of crop formation was explored via a Pearson’s correlation analysis with significance of 95%. Pearson's correlation analysis identified a negative correlation of -0.33 between the negotiation price of the coffee sack (60 kg) and the total production volume of the Brazilian crop. Considering that the market value of this product can be affected by numerous factors we conclude the significant existence of this correlation.
References
Abebe, T. H. (2020). Modeling time-varying coffee price volatility in Ethiopia. Journal of Applied Economics, 23(1), 497-518.
Agrianual: Brazilian anuary of agriculture (2022). 185-203. São Paulo, SP, Brazil.
Barros Jr, F., Ferreira, A. L., Marcondes, R. L., & Prioste, R. R. W. (2019). Coffee exports and industrialization in Brazil. Applied Economics Letters, 26(9), 712-716.
Bernardes, T., Moreira, M. A., Adami, M., Giarolla, A., & Rudorff, B. F. T. (2012). Monitoring the biennial bearing effect on coffee yield using MODIS remote sensing imagery. Remote Sensing. 4 (9), 2492-2509.
Center for Advanced Studies on Applied Economics - CEPEA (2022). PIB do Agronegócio. https://www.cepea.esalq.usp.br/upload/kceditor/files/Cepea_CNA_PIB_JAn_Dez_2021_Mar%C3%A7o2022.pdf. Acessed in 19 may 2022
Camargo, A. P., & Camargo, M. B. P. (2001) Definições e esquematização das fases fenológicas do cafeeiro arábica nas condições tropicais do Brasil. Bragantia, 60(1), 65-68.
Cannell, M. G. (1976) Crop physiological aspects of coffee bean yeld – a review Kenya Coffee, 41, 245-253.
Chen, S., Li, Q., Wang, Q., & Zhang, Y. Y. (2023). Multivariate models of commodity futures markets: a dynamic copula approach. Empirical Economics, 64(6), 3037-3057.
DaMatta, F. M., Ronchi, C. P., Maestri, M., & Barros, R. S. (2007). Ecophysiology of coffee growth and production. Brazilian journal of plant physiology, 19, 485-510.
Garson, G. D. (2009). Statnotes: Topics in multivariate analysis. North Carolina State University. https://faculty. chass. ncsu. edu/garson/PA765/statnote. htm (accessed Feb. 02, 2021).
Halim, M. P., Yudistira, N., & Dewi, C. (2022). Multicommodity Prices Prediction Using Multivariate Data-Driven Modeling: Indonesia Case. IEEE Transactions on Computational Social Systems.
Hernandez, M. A., Pandolph, R., Sänger, C., & Vos, R. (2020). Volatile coffee prices: Covid-19 and market fundamentals (Vol. 2). Intl Food Policy Res Inst.
Lanna, G.B.M.; Reis, R.P. (2012). Influência da mecanização da colheita na viabilidade econômico-financeira da cafeicultura no sul de Minas Gerais In Portuguese. Coffee Science. 7(2), 110-121.
Mankiw, N. G. (2009). Principles of Economics. (5a ed.), Harvard.
Matiello, J. B. (2005). Cultura de café no Brasil: novo manual de recomendações In Portuguese. MAPA/Procafé; Varginha: Fundação Procafé.
Moore, L. M. (1996). The basic practice of statistics. Freeman.
Silva, F. M. D., Salvador, N., & Pádua, T. D. S. (2002). Café: mecanização da colheita. In Portuguese. Brazilian Research Symposium of Coffee. Poços de Caldas, MG, Brazil.
Pereira, S. O., Bartholo, G. F., Baliza, D. P., Sogreira, F. M., & Guimarães, R. J. (2011). Productivity and coffee biannuality depending on the crop spacing. Pesqui. Agropecuária Bras, 46, 152-160.
Santinato, F. (2016). Inovações tecnológicas para cafeicultura de precisão In Portuguese. 119f. [PhD dissertation] – São Paulo State University, Jaboticabal, São Paulo, Brazil
Stanton, JM (2001). Galton, Pearson e as ervilhas: Uma breve história da regressão linear para instrutores de estatística. Journal of Statistics Education, 9 (3).
Valadares, S. V., Neves, J. C. L., Rosa, G. N. G. P., Martinez, H. E. P., Venegas, V. H. A., & Lima, P. C. D. (2013). Yield and production bienniality of dense coffee plantations under different levels of N and K. Pesquisa Agropecuária Brasileira, 48, 296-303.
Volsi, B., Telles, TS, Caldarelli, CE, & Camara, MRGD (2019). The dynamics of coffee production in Brazil. PloS one. 14 (7), e0219742.
Wang, H. Y., & Feng, Y. S. (2020). Multivariate correlation analysis of agricultural futures and spot markets based on multifractal statistical methods. Journal of Statistical Mechanics: Theory and Experiment, (7), 073403.
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