Dynamic connectedness and volatility spillover in the Brazilian agricultural market after the Covid-19 pandemic

Authors

DOI:

https://doi.org/10.1590/1980-53575446dclg

Keywords:

Commodities market, Dynamic Connectedness, Volatility Spillover, Covid-19 pandemic, Brazil

Abstract

Agricultural commodities price volatilities experienced an increase in the period of 2006 2008 and since then, the shocks from the global crises have been affecting these markets, as the Covid-19 pandemic period. Many studies have evaluated volatility spillovers around agricultural markets by focusing on crises cycles. However, few of these studies focus on emerging markets. This study examines the impacts of the Covid 19 pandemic on Brazilian agricultural price volatility. This study also considers the USD/BRL exchange rate and crude oil prices. We examine the volatility spillover effects and dynamic connectedness among the markets. A TVP-VAR model was applied, considering the specifications proposed by Antonakakis et al. (2020). The results indicate an increase in volatility connectedness after the Covid-19 outbreak, where volatility transmission affected all markets domestically. These effects were still significant after the Russia Ukraine conflict and dissipated from mid-2022 onwards. Overall, the exchange rate and soybean were the largest net transmitters during the pre- and post-Covid-19 pandemic, and corn was a net receiver. Crude oil had a significant transmission effect after a short period after the Covid-19 outbreak and the Russia-Ukraine war. Additionally, wheat was a significant volatility receiver after the Russia-Ukraine conflict and rice was a net transmitter during the Covid-19 pandemic. These findings corroborate that the crises cycles also affect Brazil but highlight that in the context of an emerging market, the exchange rate is more important in explaining agricultural price dynamics than crude oil.

Downloads

Download data is not yet available.

References

Acemoglu D., Johnson S., Robinson J. A. and Thaicharoen Y. 2003. “Institutional causes, macroeconomic symptoms: volatility, crises and growth”. Journal of Monetary Economics 50 (1): 49-123. https://doi.org/10.1016/S0304-3932(02)00208-8.

Antonakakis, N., Chatziantoniou, I. and Gabauer, D. 2020. “Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions”. Journal of Risk and Financial Management 13 (4): 84. https://doi.org/10.3390/jrfm13040084.

Babar, M., Ahmad, H. and Yousaf, I. 2023. “Returns and volatility spillover between agricultural commodities and emerging stock markets: new evidence from COVID-19 and Russian-Ukrainian war”. International Journal of Emerging Markets, In Press, Accepted Manuscript. https://doi.org/10.1108/IJOEM-02-2022-0226.

Balcilar, M., Gabauer, D. and Umar, Z. 2021. “Crude Oil futures contracts and commodity markets: New evidence from a TVP-VAR extended joint connectedness approach”. Resources Policy 73: 102219. https://doi.org/10.1016/j.resourpol.2021.102219.

Beckman, J. and Countryman, A. 2021. “The importance of agriculture in the economy: impacts from Covid-19”. American Journal of Agricultural Economics 103 (5): 1595-1611. https://doi.org/10.1111/ajae.12212.

Borgdards, O., Czudaj, R. L. and Van Hoang, T. H. 2021. “Price overreactions in the commodity futures market: An intraday analysis of the Covid-19 pandemic impact”. Resources Policy 71: 101966. https://doi.org/10.1016/j.resourpol.2020.101966.

Cabrera, B. L. and Schulz, F. 2016. “Volatility linkages between energy and agricultural commodity prices”. Energy Economics 54: 190-203. https://doi.org/10.1016/j.eneco.2015.11.018.

Capitani, D. H. D. and Gaio, L. E. 2023. “Volatility Transmissionin Agricultural Markets: Evidence from the Russia-Ukraine Conflict”. International Journal of Food and Agricultural Economics 11 (2): 65-82.

CEPEA – Center for Advanced Studies on Applied Economics. 2023. “Spot prices indicators”. Piracicaba: ESALQ/USP. Accessed August 20, 2022, http://www.cepea.org.br.

CONAB – National Supply Company. “Monitor of the Brazilian harvest”. Brasilia. Accessed May 27, 2024, http://www.conab.gov.br/info-agro/safras.

De Vijlder, W. 2020. “The COVID-19 Pandemic: Economic Consequences Pervasive Uncertainty, Delayed Recovery”. Paris, France: BNP Paribas, Economic Research Department.

Diebold, F. X. and Yilmaz, K. 2012. “Better to give than to receive: predictive directional measurement of volatility spillovers”. International Journal of Forecasting 28 (1): 57-66. https://doi.org/10.1016/j.ijforecast.2011.02.006.

Dmytrów, K., Landmesser, J. and Bieszk-Stolorz, B. 2021. “The Connections between COVID-19 and the Energy Commodities Prices: Evidence through the Dynamic Time Warping Method”. Energies, 14 (13): 4024. https://doi.org/10.3390/en14134024.

Elleby, C., Domínguez, I. P. and Adenauer, M. 2020. “Impacts of the COVID‑19 Pandemic on the Global Agricultural Markets”. Environmental and Resource Economics 76: 1067–1079. https://doi.org/10.1007/s10640-020-00473-6.

Fang, Y., and Shao, Z. 2022. “The Russia-Ukraine conflict and volatility risk of commodity markets”. Finance Research Letters 50: 103264. https://doi.org/10.1016/j.frl.2022.103264.

FAO. 2022. “Impact of the Ukraine-Russia conflict on global food security and related matters under the mandate of the Food and Agriculture Organization of the United Nations (FAO)”. Rome: CL169/3. Accessed August 06, 2022, https://www.fao.org/3/ni734en/ni734en.pdf.

Farid, S., Naeem, M. A., Paltrinieri, A. and Nepal, R. 2022. “Impact of COVID-19 on the quantile connectedness between energy, metals and agriculture commodities”. Energy Economics 109: 105962. https://doi.org/10.1016/j.eneco.2022.105962.

Frenk, D., and Tuberville, W. 2011. “Commodity Index Traders and the Boom/Bust Cycle in Commodities Prices”, Washington, DC: Better Markets (Oct., 2011). https://doi.org/10.2139/ssrn.1945570.

Gaio. L. E. and Capitani, D. H. D. 2023. “Multifractal cross-correlation analysis between crude oil and agricultural futures markets: evidence from Russia Ukraine conflict”. Journal of Agribusiness in Developing and Emerging Economies, In Press, Accepted Manuscript. https://doi.org/10.1108/JADEE-11 2022-0252.

Huchet-Bourdon, M. 2011. “Agricultural Commodity Price Volatility: An Overview”. OECD Food, Agriculture and Fisheries Papers No. 52, Paris: OECD Publishing. http://dx.doi.org/10.1787/5kg0t00nrthc-en.

Hung, N. T. 2021. “Oil prices and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak”. Resources Policy 73: 102236. https://doi.org/10.1016/j.resourpol.2021.102236.

IBGE. Brazilian Statistics Institute. 2022. “Consumer Price Index”. Accessed August 27, 2022. http://www.ibge.gov.br.

Irwin, S. H. and Good, D. L. 2009. “Market instability in a new era of corn, soybean and wheat prices”. Choices 24 (1): 6–11.

Jeong, S. and Gopinath, M. 2022. “International market information and agricultural price dynamics”. Journal of Agribusiness in Developing and Emerging Economies 14 (2): 376-392. https://doi.org/10.1108/JADEE-06-2022-0126.

Just, M. and Echaust, K. 2022. “Dynamic spillover transmission in agricultural commodity markets: What has changed after the COVID-19 threat?”. Economics Letters 217: 110671. https://doi.org/10.1016/j.econlet.2022.110671.

Kamdem, J. S., Essomba, R. B. and Berinyuy, J. N. 2020. “Deep learning models for forecasting and analyzing the implications of COVID-19 spread on some commodities markets volatilities”. Chaos, Solitons and Fractals, 140: 110215. https://doi.org/10.1016/j.chaos.2020.110215.

Koop, G. and Korobilis, D. 2014. “A new index of financial conditions”. European Economic Review 71, no. 1 (October): 101–116. https://doi.org/10.1016/j.euroecorev.2014.07.002.

Kristoufek, L., Janda, K. and Zilberman, D. 2014. “Price transmission between biofuels, fuels, and food commodities”. Biofuels, Bioproducts & Biorefining 8: 362-373. https://doi.org/10.1002/bbb.1464.

Kumar, A., Mishra, A. K., Saroj, S. and Rashid, S. 2022. “Government transfers, COVID-19 shock, and food insecurity: Evidence from rural households in India”. Agribusiness 38: 636-659. https://doi.org/10.1002/agr.21746.

Lahiani, A., Nguyen, D. K. and Vo, T. 2013. “Understanding Return and Volatility”. The Journal of Applied Business Research 29 (6): 1781-1790. https://doi.org/10.19030/jabr.v29i6.8214.

Mishra, A. K., Arunachalam, V., Olson, D. and Patnaik, D. 2023. “Dynamic connectedness in commodity futures markets during Covid-19 in India: New evidence from a TVP-VAR extended joint connectedness approach”. Resources Policy 82 (1): 103490. https://doi.org/10.1016/j.resourpol.2023.103490.

Palazzi, R. B., Assaf, A. and Klotze, M. C. 2024. “Dynamic connectedness between energy markets and the Brazilian cash market: An empirical analysis pre- and post-COVID-19”. Journal of Futures Markets 44: 27-56. https://doi.org/10.1002/fut.22463.

Quintino, D., Ogino, C., Haq, I. U., Ferreira, P. and Oliveira, M. 2023. “An Analysis of Dynamic Correlations among Oil, Natural Gas and Ethanol Markets: New Evidence from the Pre- and Post-COVID-19 Crisis”. Energies 16 (5): 2349. https://doi.org/10.3390/en1605234.

Rajput, H., Changotra, R., Gautam, S., Gollakota, A. R. K. and Arora, A. S. 2021. “A shock like no other: coronavirus rattles commodity markets”. Environment, Development and Sustainability 23: 6564-6574. https://doi.org/10.1007/s10668-020-00934-4.

Saghaian, S., Nemati, M., Walters, C. and Chen, B. 2018. “Asymmetric Price Volatility Transmission between U.S. Biofuel, Corn, and Oil Markets”. Journal of Agricultural and Resource Economics 43 (1): 46-60. http://www.jstor.org/stable/44840974.

Serra, T. 2011. “Volatility spillover between food and energy market: a semiparametric approach”. Energy Economics 33 (6): 1155-1164. https://doi.org/10.1016/j.eneco.2011.04.003.

Serra, T. and Zilberman, D. 2013. “Biofuel-related price transmission literature: A review”. Energy Economics 37: 141-151. https://doi.org/10.1016/j.eneco.2013.02.014.

Shahrestani, P. and Rafei, M. 2020. “The impact of oil price shocks on Tehran Stock Exchange returns: Application of the Markov switching vector autoregressive models”. Resources Policy 65: 101579. https://doi.org/10.1016/j.resourpol.2020.101579.

Siami-Namini, S., Hudson, D., Trindade, A. D. and Lyford, C. 2019. “Commodity price volatility and U.S. monetary policy: Commodity price overshooting revisited”. Agribusiness 35: 200-218. https://doi.org/10.1002/agr.21564.

Thanh, P. T., Duy, D. T. and Duong P. B. 2021. “Disruptions to agricultural activities, income loss and food insecurity during the COVID-19 pandemic: evidence from farm households in a developing country”. Journal of Agribusiness in Developing and Emerging Economies 12 (3): 551-547. https://doi.org/10.1108/JADEE-09-2021-0243.

Trujillo-Barreras, A., Mallory, M. and Garcia, P. 2012. “Volatility Spillovers in U.S. Crude Oil, Ethanol, and Corn Futures Markets”. Journal of Agricultural and Resource Economics, 37 (2): 247-262. https://doi.org/10.22004/ag.econ.134275.

Tyner, W. E. 2010. “The integration of energy and agricultural markets”. Agricultural Economics 41: 193-201. https://doi.org/10.1111/j.1574-0862.2010.00500.x.

UNCTAD. 2022. “Impact of Covid-19 pandemic on trade and development: lessons learned”. Geneve. Accessed September 05, 2022, https://unctad.org/system/files/official-document/osg2022d1_en.pdf.

Vacha, L., Karrel, J., Kristoufek, L. and Zilberman, D. 2013. “Time-frequency dynamics of biofuel-fuel-food system”. Energy Economics 40: 233-241. https://doi.org/10.1016/j.eneco.2013.06.015.

Wang, J., Shao, W. and Kim, J. 2020. “Analysis of the impact of COVID-19 on the correlations between crude oil and agricultural futures”. Chaos, Solitons and Fractals 136: 109896. https://doi.org/10.1016/j.chaos.2020.10989.

Wang, Y., Bouri, E., Fareed, Z. and Dai, Y. 2022. “Geopolitical risk and the systemic risk in the commodity markets under the war in Ukraine”. Financial Research Letters 49: 103066. https://doi.org/10.1016/j.frl.2022.103066.

World Bank. 2020. “Commodity markets outlook”. Washington, DC: Special Focus (April). Accessed September 03, 2022, https://thedocs.worldbank.org/en/doc/c5de1ea3b3276cf54e7a1dff4e95362b-0350012021/original/CMO-April-2021.pdf.

Wright, B. D. 2011. “The economics of grain price volatility”. Applied Economic Perspectives and Policy 33 (1): 32–58. https://doi.org/10.1093/aepp/ppq033.

Yildrim, D. Ç., Erdogan, F. and Tari, E. N. 2022. “Time-varying volatility spillovers between real exchange rate and real commodity prices for emerging market economies”. Resources Policy 76: 102586. https://doi.org/10.1016/j.resourpol.2022.102586.

Zhang, Z., Lohr, L., Escalante, C. L. and Wetzstein, M. E. 2010. “Food versus fuel: What do prices tell us?”. Energy Policy 38 (1): 445–451. https://doi.org/10.1016/j.enpol.2009.09.034.

Zheng, T., Ye, S. and Hong, Y. 2023. Fast estimation of a large TVP-VAR model with score-driven volatilities. Journal of Economic Dynamics and Control 157: 104762. https://doi.org/10.1016/j.jedc.2023.104762.

Downloads

Published

03-12-2024

Issue

Section

Articles

How to Cite

Capitani, D. H. D., & Gaio, L. E. (2024). Dynamic connectedness and volatility spillover in the Brazilian agricultural market after the Covid-19 pandemic. Estudos Econômicos (São Paulo), 54(4), e53575446. https://doi.org/10.1590/1980-53575446dclg