Brazil nuts a non-timber potential: Uncertainties and investments
DOI:
https://doi.org/10.33448/rsd-v10i15.21868Keywords:
Investment; Attractiveness; Non-timber forest product; Volatility; Price.Abstract
The Brazil nut is one of the main non-timber forest products in Brazil, but its price fluctuations generate uncertainties and risks for both extractivists and investors. Econometric models or other simpler methods can estimate price changes and indicate the investment attractiveness of the Brazil nut. The objective of the present study was to analyze the risk-return relationship and the export price for both volatility of the Brazil nut over a 15 years period. The historical series of Brazil nut export prices, shelled and unshelled nuts, was evaluated from 2002 to 2016. The geometric growth rate and the variation coefficient indicate the return and risk respectively, associated with its price series. The price volatility of shelled and unshelled Brazil nuts was estimated with the standard deviation of the price series and with generalized models of ARCH (GARCH, EGARCH and TARCH). The shelled or unshelled Brazil nut coefficient increased over 15 years, with a low risk-return ratio. The shelled Brazil nut volatility was lower in the 2002 to 2006, 2007 to 2011 and 2012 to 2016 periods than for the unshelled nut when estimated by the standard deviation method than for the unshelled nut. The shelled Brazil nut price was higher from 2002 to 2016, with low volatility and persistent shocks. The estimate of the shelled and unshelled Brazil nut price volatility was better with the TARCH and the EGARCH models, respectively.
References
Ahenkan, A., & Boon, E. (2010). Commercialization of non-timber forest products in ghana: processing, packaging and marketing. J. Food, Agric. Environ. 8, 962-969.
Andersen, T. G., Bollerslev, T., Diebold, F. X., & Ebens, H. (2001). The distribution of realized stock return volatility. J. Financ. Econ. 61, 43–76.
Andersson, M., & Gong, P. (2010). Risk preferences, risk perceptions and timber harvest decisions — An empirical study of nonindustrial private forest owners in northern Sweden. Forest Policy Econ. 12, 330–339.
Andreou, E., & Ghysels, E. (2002). Detecting multiple breaks in financial market volatility dynamics. J. Appl. Econ. 17, 579–600.
Angelo, H., Almeida, A. N., Calderon, R. A.,Pompermayer, R. S., & Souza, Á. N. (2013). Determinantes do preço da castanha-do-brasil (Bertholletia excelsa) no mercado interno brasileiro. Sci. For. 41, 195–203.
Assies, W. (1996). Amazon nuts, forests and sustainability in Bolivia and Brazil. Semin. Proc. ‘NFTP Res. Tropenbos Program. Results Perspect. 26, 95–106.
Baquião, A.C., Zorzete, P., Reis, T.A., Assunção, E., Vergueiro, S., & Correa, B. (2012). Mycoflora and mycotoxins in field samples of Brazil nuts. Food Control. 28, 224–229.
Barak, S., Arjmand, A., & Ortobelli, S. (2017). Fusion of multiple diverse predictors in stock market. Inform. Fusion. 36, 90–102.
Baroi, G. N., Gavala, H. N., Westermann, P., & Skiadas, I. V. (2017). Fermentative production of butyric acid from wheat straw: Economic evaluation. Ind. Crops Prod. 104, 68–80.
Bayma, M. M. A., Malavazi, F. W., Sá, C. P., Fonseca, F. L., Andrade, E. P., & Wadt, L. H. O. (2014). Aspectos da cadeia produtiva da castanha-do-brasil no estado do acre, brasil. Bol. Mus. Para. Emílio Goeldi. Cienc. Nat. 9, 417–426.
BCB - Banco Central do Brasil. (2017). Cotação. http://www4.bcb.gov.br/pec/taxas/port/ ptaxnpesq.asp?id=txcotacao
Belcher, B., & Schreckenberg, K. (2007). Commercialisation of Non-timber Forest Products: A reality check. Dev. Policy Rev. 25, 355–377.
Bhar, R., & Nikolova, B. Return, volatility spillovers and dynamic correlation in the BRIC equity markets: An analysis using a bivariate EGARCH framework. (2009). Global Financ. J. 19, 203–218.
Bojnec, Š., & Fertő, I. (2012). Complementarities of trade advantage and trade competitiveness measures. Appl. Econ. 44, 4, 399-408.
Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. J. Econ. 31, 307–327.
Brasil. Ministério do Meio Ambiente. (2017). Castanha-do-Brasil: boas práticas para o extrativismo sustentável orgânico / Ministério do Meio Ambiente. Secretaria de Extrativismo e Desenvolvimento Rural Sustentável. Departamento de Extrativismo. – Brasília, DF: MMA, p.1-55.
Brokamp, G., Valderrama, N., Mittelbach, M., Barfod, A. S., & Weigend, M. (2011). Trade in palm products in north-western south america. Bot. Rev. 77, 571–606.
Buckley, P. J., Pass, C. L., & Prescott, K. (1988). Measures of international competitiveness: A critical survey. J. Mark. Manag. 4, 175–200.
Chen, C. W. S., & Yu, T. H. K.(2005). Long-term dependence with asymmetric conditional heteroscedasticity in stock returns. Phys. A Stat. Mech. Appl. 2005, 353, 413–424.
Chkili, W., Hammoudeh, S., & Nguyen, D. K. (2014). Volatility forecasting and risk management for commodity markets in the presence of asymmetry and long memory. Energy Econ. 41, 1–18.
Christie, A. (1982). The stochastic behavior of common stock variances value, leverage and interest rate effects. J. Financ. Econ. 10, 407–432.
Collinson, C., Burnett, D., & Agreda, V. (2000). Economic viability of Brazil nut trading in Peru. Natural Resources Institute, University of Greenwich, Report 2520, Chatham Maritime, pp. 1–64.
Coslovsky, S. V. (2014). Economic development without pre-requisites: How bolivian producers met strict food safety standards and dominated the global brazil-nut market. World Dev. 54, 32–45.
Costa, J. R., Castro, A. B. C., Wandelli, E. V., Coral, S. C. T., & Souza, S. A. G. (2009). Aspectos silviculturais da castanha-do-brasil (Bertholletia excelsa) em sistemas agroflorestais na amazônia central. Acta Amazon. 39, 843–850.
Ding, Z., & Granger, C. W. J. (1996). Modeling volatility persistence of speculative returns: A new approach. J. Econ. 73, 185–215.
Duchelle, A. E., Cronkleton, P., Kainer, K. A., Guanacoma, G.; & Gezan, S. (2011). Resource theft in tropical forest communities: Implications for nontimber management, livelihoods, and conservation. Ecol. Soc. 16, 4.
Dwyer, L., Forsyth, P., & Rao, P. (2000). The price competitiveness of travel and tourism: a comparison of 19 destinations. Tour. Manag.21, 9–22.
Elyasiani, E., & Mansur, I. (2017). Hedge fund return, volatility asymmetry, and systemic effects: A higher-moment factor-EGARCH model. J. Financ. Stabil. 28, 49–65.
Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of united kingdom inflation. Econometrica. 50, 987.
Enríquez, G. (2010). Amazônia – Rede de inovação de dermocosméticos sub-rede de dermocosméticos na Amazônia a partir do uso sustentável de sua biodiversidade com enfoques para as cadeias produtivas da castanha-do-pará e dos óleos de andiroba e copaíba. Parcerias Estratégicas. 14, 51–118.
Food and Agriculture Organization (FAO). (2017). Available at: http://www.fao.org/home/en/
Geltner, D. M., & Van De Minne, A.(2017). Do different price points exhibit different investment risk and return in commercial real estate?. The J. Portif. Manag. 43, 105-109.
Goeschl, T., & Igliori, D. C. (2006). Property rights for biodiversity conservation and development: extractive reserves in the Brazilian amazon. Dev. Change. 37, 427–451.
Goyal, A., & Arora, S. (2012). The Indian exchange rate and Central Bank action: An EGARCH analysis. J. Asian Econ. 23, 60–72.
Hansen, P. R., & Lunde, A. (2009). A forecast comparison of volatility models: does anything beat a GARCH(1,1)?. J. Appl. Econom. 20, 873–889.
Hayes, A. F., & Cai, L. (2007). Using heteroskedasticity-consistent standard error estimators in OLS regression: An introduction and software implementation. Behav. Res. Methods. 39, 709–722.
Helbingen, A. J. B. (2001). Balance is beautiful: assessing sustainable development in the rain forests of the bolivian amazonia. PROMAB scientific series 4: Utrecht, Netherlands. pp. 255.
Homma, O. A. K., Carvalho, R. de A., Ferreira, C. A. P., & Júnior, J. de D. B. N. A destruição dos recusros naturais: o caso da castanha-do-pará no sudeste paraense. In: Proceedings of the Anais do Encontro da Sociedade Brasileira de Economia Ecológica; 2001; p. 1–25.
Ingram, V., Ndoye, O., Iponga, D. M., Tieguhong, J. C., & Nasi, R. (2012). The Non-timber forest products: contribution to national economy and strategies for sustainable management. In: de Wasseige, C., de Marcken, P., Bayol, N., Hiol, F.H., Mayaux, P., Desclée, B., Nasi, R., Billand, A., Defourny, P., Eba’a, R. (Eds.). Forests of the Congo Basin. State of the Forest. Office des publications de l'Union Européenne, Luxembourg, p. 276.
,İnkaya, A., & Yolcu Okur, Y. (2014). Analysis of volatility feedback and leverage effects on the ISE30 index using high frequency data. J. Comput. Appl. Math. 259, 377–384.
Instituto Brasileiro de Geografia e Estatística (IBGE). (2017). Quantidade produzida e valor da produção na extração vegetal, por tipo de produto extrativo Available at: https://sidra.ibge. gov.br/tabela/289 (
INPE - Instituto Nacional de Pesquisas Espaciais. (2016). PRODES estima 7.989 km2 de desmatamento por corte raso na Amazônia em 2016. http://www.inpe.br/ noticias/noticia. php?Cod_ Noticia=4344
Jubert, R. W., Monte, P. A., Paixão, M. C. S., Lima, W. H. (2008). Um estudo do padrão de volatilidade dos principais índices financeiros do Bovespa : uma aplicação de modelos Arch. Rev. Contabil. Gestão e Gov. 11, 221–239.
Kainer, K. A., Wadt, L. H. O., & Staudhammer, C. L. (2007). Explaining variation in Brazil nut fruit production. Forest Ecol. Manag. 250, 244–255.
Kalliola, R., & Flores, P. (2011). Brazil nut harvesting in peruvian amazonia from the perspective of ecosystem services. Fennia. 189,1-13.
Koutmos, G., & Booth, G. G. (1995). Asymmetric volatility transmission in international stock markets. J. Int. Money Financ. 14, 747–762.
Lamoureux, C. G., & Lastrapes, W. D. (1990). Persistence in variance, structural change, and the GARCH model. J. Bus. Econ. Stat. 8, 225.
Langley, S. V., Giugale, M., Meyers, W. H., & Hallahan, C. (2000). International financial volatility and agriculturalcCommodity trade: A primer. Am. J. Agric. Econ. 82, 695–700.
Lantz, V. Measuring scale, technology and price effects on value-added production across Canadian forest industry sectors. Forest Policy Econ. 2005, 7, 333–344.
Lee, C. F., Chen, G., & Rui, O. M. (2001). Stock returns and volatility on china’s stock markets. J. Financ. Res.24, 523–543.
Li, W. K. & Lam, K. (1995). Modelling asymmetry in stock returns by a threshold autoregressive conditional heteroscedastic model. Statistician. 44, 333.
MAPA, 1976. Portaria No 846 sobre padronização, classificação e comercialização interna da Castanha do Brasil. Diário Oficial No 846, Brasília-DF, 8-11-1976.
Marius, M. A. (2012). Contribution to multivariate volatility modeling with high frequency data. Doctoral Thesis, Departament Economia, Ciències Socials i Mètodes Universitat Ramon Llull, 2012.
Matei, M. (2009). Assessing volatility forecasting models: Why GARCH models take the lead. Rom. J. Econ. Forecast. 12, 42–65.
McAleer, M., & Hafner, C. (2002). A one line derivation of EGARCH. Econometrics 2014, 2, 92–97
McKenzie, M. The economics of exchange rate volatility asymmetry. Int. J. Financ. Econ. 7, 247–260.
MDIC consultas. (2016) http://comexstat.mdic.gov.br/pt/home/.
Monteiro, L. de M., Nogueira, R. M., & Pires, E. M. (2016). A valid method for determining the water content of the Brazil nut (Bertholletia excelsa). Biosci. J. 952–959.
Montgomery, D. C., Peck, E. A., & Vining, G. G. (2012). Introduction to Linear Regression Analysis.; John Wiley & Sons, Org.; John Wiley & Sons. 821.
Morettin, P. A., &Toloi, C. M. C. (2006). Análise de séries temporais, 2nd ed; Edgard Blücher: São Paulo,Brasil. pp. 538.
Mugido, W., & Shackleton, C. M. (2018). Price determination of non-timber forest products in different areas of south africa. Ecol. Econ. 146, 597–606.
Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: a new approach. Econometrica. 59, 347-370.
Nelson, V., Galvez, M., & Blowfield, M. (2000). Social impact of ethical and conventional Brazil nut trading on forest-dependent people in Peru. Natural Resources Institute, University of Greenwich, Chatham Maritime. Pp. 46.
Noce, R., Silva, M. L. da, Mendes, L. M., Souza, A. L. de, Rezende, J. L. P. de; Carvalho, R. M. M. A., Canto, J. L. do, & Oliveira, J. M. de. (2010). Relationship risk-return of native species sawn wood in the state of Pará, Brazil 2003-2007. Cerne. 16, 199–207.
Oliveira Neto, S. N., Lana, V. M., & Costa, C. B. V. M. (2012). Sistemas agroflorestais para adequação ambiental de propriedades rurais. Inf. Agropecuário. 33, 70–78.
Otuki, T. F., Weydmann, C. L., & Seabra, F. ()2009. Febre aftosa e volatilidade dos preços do produtor de carne suína. Rev. Econ. e Agron. 7, 235–258.
Pacheco, A., & Scussel, V. (2009). Aflatoxins evaluation on in-shell and shelled dry brazil nuts for export analysed by lc-ms/ms - 2006 and 2007 harvests. World Mycotoxin J. 2, 295–304.
Pacheco, A. M., & Martins, M. (2013). Brazil nut sorting for aflatoxin prevention: a comparison between automatic and manual shelling methods. Food Sci. Technol. 33, 369–375.
Peter Ferderer, J. (1996). Oil price volatility and the macroeconomy. J. Macroecon. 18, 1–26.
Purcell, W. D., & Koontz, S. R. (1999). Agricultural futures and options: Principles and strategies, 2nd ed; Prentice Hall, Upper Saddle River: New Jersey, United States. pp.645.
Rabadán, A., González-Moreno, Á., Sáez-Martínez, F. J. (2019). Improving firms’ performance and sustainability: The case of eco-innovation in the agri-food Industry. Sustainability. 11, 5590.
Reis, T. A., Baquião, A. C., Atayde, D. D., Grabarz, F., & Corrêa, B. (2014). Characterization of Aspergillus section Flavi isolated from organic brazil nuts using a polyphasic approach. Food Microbiol. 42, 34–39.
Riguero, A., Fernández, S., & Sáez-Martinez, F. J. (2018). Inbound open innovative strategies and eco-innovation in the Spanish food and beverage industry. Sustain. Prod. Consum. 15, 49–64.
Ros-Tonen, M. A. F., Van Andel, T.,Morsello, C., Otsuki, K., Rosendo, S., & Scholz, I. (2008). Forest-related partnerships in Brazilian Amazonia: There is more to sustainable forest management than reduced impact logging. Forest Ecol. Manag. 256, 1482–1497.
Sabiruzzaman, M., Huq, M. M., Beg, R. A., & Anwar, S. (2010). Modeling and forecasting trading volume index: GARCH versus TGARCH approach. The Quart. Rev. Econ. Financ. 50, 141–145.
Santos, S. J. P. (2003). Um estudo de eficiência de mercado usando séries temporais com diferenciação fracionária: o caso de commodities agrícolas. Doctoral Thesis, Departamento de Economia- Universidade Federal de Pernambuco, Recife. pp. 103.
Sardeshpande, M., & Shackleton, C. (2019). Wild edible fruits: a systematic review of an under-researched multifunctional NTFP (Non-Timber Forest Product). Forests. 10, 1-467.
Sathre, R., & Gustavsson, L. (2009). Process-based analysis of added value in forest product industries. Forest Policy Econ. 11, 65–75.
Schirigatti, E. L., Aguiar, G. P., Silva, J. C. G. L., Frega, J. R., Almeida, A. N., & Hoeflich, V. A. (2016). Market behavior for in shell brazil nuts produced in Brazil from 2000 to 2010. Floresta e Ambiente. 23, 369–377.
Scoles, R., & Gribel, R. (2011). Population structure of brazil nut (Bertholletia excelsa, Lecythidaceae) stands in two areas with different occupation histories in the brazilian amazon. Hum. Ecol.39, 455–464.
Scussel, V. M., Giordano, B. N., Simao, V., Manfio, D., Galvao, S., & Rodrigues, M. N. F. (2011). Effect of oxygen-reducing atmospheres on the safety of packaged shelled Brazil nuts during storage. Int. J. Anal. Chem. 2011, 1–9.
Seekell, D. A., Carpenter, S. R., & Pace, M. L. (2011). Conditional heteroscedasticity as a leading indicator of ecological regime shifts. Am. Nat. 178, 442–451.
Shanley, P., Silva, M. S., Melo, T., Carmenta, R., & Nasi, R. (2012). From conflict of use to multiple use: forest management innovations by small holders in amazonian logging frontiers. Forest Ecol. Manag. 268, 70–80.
Siggel, E. (2006). International competitiveness and comparative advantage: A survey and a proposal for measurement. J. Ind. Compet. Trade. 6, 137–159.
Silva, A. A., Santos, M. K. V., Gama, J. R. V., Noce, R., & Leão, S. (2013). Potencial do extrativismo da castanha-do-Pará na geração de renda em comunidades da mesorregião baixo Amazonas, Pará. Floresta e Ambiente. 20, 500–509.
Silva, C. A. G. (2009). Modelagem de estimação da volatilidade do retorno das ações brasileiras:os casos da Petrobras e Vale. Cad. do ime - Série Estatis. 26, 1-15.
Silva, C. A. G., & Ferreira, L. D. R. (2015). Long-memory presense in the volatility of fat ox daily prices in brazil of fat ox daily prices in Brazil. Int. J. Res. Soc. Sci. 4, 48–55.
Silvertown, J. Sustainability in a nutshell. Trends Ecol. Evol. 2004, 19, 276–278.
Soares, N. S., & Silva, M. L. (2010). Competitividade brasileira no comércio internacional de produtos extrativos vegetais. Rev. Econ. Nordeste. 44, 879–893.
Soriano, M., Mohren, F., Ascarrunz, N., Dressler, W., & Peña-Claros, M. (2017). Socio-ecological costs of amazon nut and timber production at community household forests in the bolivian amazon. PloS One. 12, 1-25.
Stoian, D.(2005). Making the best of two worlds: rural and peri-urban livelihood options sustained by nontimber forest products from the bolivian amazon. World Dev. 33, 1473–1490
Stoian, D. (2000). Shifts in forest product extraction: the post-rubber era in the bolivian amazon. Int. Tree Crop. J. 10, 277–297.
Stoian, D., & Henkemans, A. B. (2000). Between extractivism and peasant agriculture: differentiation o rural settlements in the bolivian amazon. Int. Tree Crop. J. 10, 299–319.
Toledo, R. A., Gomes, C. S., & Palmieri, R. (2016). Panorama nacional da cadeia de valor da castanha-do-Brazil; Instituto de Manejo e Certificação Florestal e Agrícola (IMAFLORA): São Paulo. pp. 60.
Tonini, H., & Pedrozo, C. A. (2014). Variações anuais na produção de frutos e sementes de de castanheira - do - brasil (Bertholletia excelsa Bonpl., Lecythidaceae) em florestas nativas de roraima. Rev. Arv. 38, 133–144.
Tule, M. K., Ndako, U. B., & Onipede, S. F. (2017). Oil price shocks and volatility spillovers in the Nigerian sovereign bond market. Rev. Financ. Econ. 35, 57–65.
Turtiainen, M., & Nuutinen, T. (2012). Evaluation of information on wild berry and mushroom markets in european countries. Small-Scale For. 2012, 11, 131–145.
Wadt, L. H. O., Kainer, K. A., Staudhammer, C. L., & Serrano, R. O. P. (2008). Sustainable forest use in Brazilian extractive reserves: Natural regeneration of Brazil nut in exploited populations. Biol. Conserv. 141, 332–346.
Wu, G. (2001). The determinants of asymmetric volatility. Rev. Financ. Stud. 14, 837–859.
Yang, H., & Wu, X. (2011). Semiparametric EGARCH model with the case study of China stock market. Econ. Model. 28, 761–766.
Yang, J. (2009). Brazil nuts and associated health benefits: a review. Lwt - Food Sci. Technol. 42, 1573–1580.
Yaya, O. S., Akinlana, D. M., & Shittu, O. I. (2017). Modelling Nigerian Banks ’ share prices using smooth transition GARCH models. CBN J. Appl. Stat. 7, 137–158.
Zaffaroni, P. (2009). Whittle estimation of EGARCH and other exponential volatility models. J. Econometrics. 151, 190–200.
Zakoian, J. M. (1994). Threshold heteroskedastic models. J. Econ. Dyn. Control. 18, 931–955.
Zuidema, P. A. (2003). Demography and management of the brazil nut tree (Bertholletia excelsa). PROMAB Scientific series 6: Utrecht,Netherlands. pp.1-113.
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