Research Article
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THE CAUSALITY BETWEEN AGRICULTURAL RAW MATERIALS AND ECONOMIC POLICY UNCERTAINTY: EVIDENCE FROM THE TIME-VARYING GRANGER CAUSALITY

Year 2023, Volume: 19 Issue: 1, 1 - 13, 24.03.2023
https://doi.org/10.17130/ijmeb.1186996

Abstract

This paper aims to examine the time-varying dynamics of the causality interaction between agricultural raw materials commodity prices and the US economic policy uncertainty (EPU). To this end, we use monthly data for the period spanning from January 1992 to November 2021. We employ a time-varying Granger causality test to provide empirical evidence about the time-varying dynamics of the causality interaction and thereby revealing potential heterogeneities of these interactions during major historical events. The results show that causality running from EPU to agricultural raw materials, as well as causality running from agricultural raw materials to EPU, exhibits time-varying dynamics. More specifically, the findings reveal that causality generally tended to run from agricultural raw materials to EPU for most of the 2000-2014 period, but reversed with the US-China trade war and the Covid-19 pandemic period. This result highlights the importance of modeling the potential causality interactions in the economic uncertainty-commodity prices nexus within a dynamic framework and implies that these interactions cannot be considered independently of the prevailing economic, political and global conditions.

References

  • Ahmed, M. Y., & Sarkodie, S. A. (2021). COVID-19 pandemic and economic policy uncertainty regimes affect commodity market volatility. Resources Policy, 74 (April), 102303. https://doi.org/10.1016/j.resourpol.2021.102303
  • Antonakakis, N., Chatziantoniou, I., & Filis, G. (2014). Dynamic spillovers of oil price shocks and economic policy uncertainty. Energy Economics, 44, 433–447. https://doi.org/10.1016/j.eneco.2014.05.007
  • Apergis, N., Hayat, T., & Saeed, T. (2021). US partisan conflict uncertainty and oil prices. Energy Policy, 150 (January), 112118. https://doi.org/10.1016/j.enpol.2020.112118
  • Bakas, D., & Triantafyllou, A. (2018). The impact of uncertainty shocks on the volatility of commodity prices. Journal of International Money and Finance, 87, 96–111. https://doi.org/10.1016/j.jimonfin.2018.06.001
  • Bakas, D., & Triantafyllou, A. (2020). Commodity price volatility and the economic uncertainty of pandemics. Economics Letters, 193, 109283. https://doi.org/10.1016/j.econlet.2020.109283
  • Baker, S. R., & Bloom, N. (2013). Does uncertainty reduce growth? Using disasters as natural experiments. NBER Working Papers, 1–31. http://www.nber.org/papers/w19475
  • Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring economic policy uncertainty. Quarterly Journal of Economics, 131(4), 1593–1636. https://doi.org/10.1093/qje/qjw024
  • Baker, S.R., Bloom, N., Davis, S.J., Terry, S.J., (2020). Covid-induced Economic Uncertainty. (0898-2937).
  • Bannigidadmath, D., & Narayan, P. K. (2021). Commodity futures returns and policy uncertainty. International Review of Economics and Finance, 72 (December), 364–383. https://doi.org/10.1016/j.iref.2020.11.009
  • Barsky, R. B., & Kilian, L. (2004). Oil and the macroeconomy Since the 1970s. Journal of Economic Perspectives, 18(4), 115–134. https://doi.org/10.1257/0895330042632708
  • Bloom, N. (2009). The impact of uncertainty shocks. Econometrica, 77(3), 623–685. https://doi.org/10.3982/ECTA6248 Bloom, N. (2014). Fluctuations in uncertainty. https://doi.org/10.2139/ssrn.2423515
  • Bloom, N. (2016). Fluctuations in uncertainty. Voprosy Ekonomiki, 2016(4), 30–55. https://doi.org/10.32609/0042-8736-2016-4-30-55
  • Bouri, E., Cepni, O., Gabauer, D., & Gupta, R. (2021). Return connectedness across asset classes around the COVID-19 outbreak. International Review of Financial Analysis, 73(May 2020), 101646. https://doi.org/10.1016/j.irfa.2020.101646
  • Clemente, J., Montañés, A., & Reyes, M. (1998). Testing for a unit root in variables with a double change in the mean. Economics Letters, 59(2), 175–182. https://doi.org/10.1016/s0165-1765(98)00052-4
  • Garner, A. (2017). Commodity Prices: Policy Target or Information Variable?: Note Author ( s ): C . Alan Garner Source: Journal of Money, Credit and Banking, Vol. 21, No. 4 (Nov., 1989), pp. 508-514 Published by: Ohio State University Press Stable URL: http://. 21(4), 508–514.
  • Hailemariam, A., Smyth, R., & Zhang, X. (2019). Oil prices and economic policy uncertainty: Evidence from a nonparametric panel data model. Energy Economics, 83, 40–51. https://doi.org/10.1016/j.eneco.2019.06.010
  • Huang, J., Li, Y., Zhang, H., & Chen, J. (2021). The effects of uncertainty measures on commodity prices from a time-varying perspective. International Review of Economics and Finance, 71(February 2020), 100–114. https://doi.org/10.1016/j.iref.2020.09.001
  • IMF (2022). International Monetary Fund. IMF Primary Commodity Prices. https://www.imf.org/en/Research/commodity-prices
  • Joëts, M., Mignon, V., & Razafindrabe, T. (2017). Does the volatility of commodity prices reflect macroeconomic uncertainty? Energy Economics, 68, 313–326. https://doi.org/10.1016/j.eneco.2017.09.017
  • Just, M., & 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
  • Kaldor, N. (1987). The role of commodity prices in economic recovery. World Development, 15(5), 551–558. https://doi.org/10.1016/0305-750X(87)90002-7
  • Kang, W., & Ratti, R. A. (2013a). Structural oil price shocks and policy uncertainty. Economic Modelling, 35, 314–19. https://doi.org/10.1016/j.econmod.2013.07.025.
  • Kang, W., & Ratti, R. A. (2013b). Oil shocks, policy uncertainty and stock market return. Journal of International Financial Markets, Institutions and Money, 26(1), 305–18. https://doi.org/10.1016/j.intfin.2013.07.001.
  • Kilian, L., 2009. Not All Oil price shocks are alike: disentangling demand and supply shocks. American Economic Review, 99, 1053–1069. https://www.jstor.org/stable/25592494.
  • Leduc, S., & Liu, Z. (2020). The Uncertainty Channel of the Coronavirus. Federal Reserve Bank of San Francisco.
  • Newey, W.K., West, K.D., 1987. A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica. 55, 703–708. https://doi.org/10.3386/t0055.
  • Sharif, A., Aloui, C., & Yarovaya, L. (2020). COVID-19 pandemic, oil prices, stock market, geopolitical risk and policy uncertainty nexus in the US economy: Fresh evidence from the wavelet-based approach. International Review of Financial Analysis, 70(April), 101496. https://doi.org/10.1016/j.irfa.2020.101496
  • Shi, S., Hurn, S., & Phillips, P. C. B. (2020). Causal change detection in possibly integrated systems: Revisiting the money-income relationship. Journal of Financial Econometrics, 18(1), 158–180. https://doi.org/10.1093/JJFINEC/NBZ004
  • Shi, S., Phillips, P. C. B., & Hurn, S. (2018). Change detection and the causal impact of the yield curve. Journal of Time Series Analysis, 39(6), 966–987. https://doi.org/10.1111/jtsa.12427
  • Shi, X., & Shen, Y. (2021). Macroeconomic uncertainty and natural gas prices: Revisiting the Asian Premium. Energy Economics, 94, 105081. https://doi.org/10.1016/j.eneco.2020.105081
  • Stock, J. H., & Watson, M. W. (2012). Disentangling the channels of the 2007-09 recession. Brookings Papers on Economic Activity, 1, 81–135. https://doi.org/10.1353/eca.2012.0005
  • Sun, T. T., Su, C. W., Mirza, N., & Umar, M. (2021). How does trade policy uncertainty affect agriculture commodity prices?. Pacific Basin Finance Journal, 66(February), 101514. https://doi.org/10.1016/j.pacfin.2021.101514
  • Sun, X., Chen, X., Wang, J., & Li, J. (2020). Multi-scale interactions between economic policy uncertainty and oil prices in time-frequency domains. North American Journal of Economics and Finance, 51(September), 1–15. https://doi.org/10.1016/j.najef.2018.10.002.
  • Tunc, A., Kocoglu, M., & Aslan, A. (2022). Time-varying characteristics of the simultaneous interactions between economic uncertainty, international oil prices and GDP: A novel approach for Germany. Resources Policy, 77(April), 102658. https://doi.org/10.1016/j.resourpol.2022.102658
  • Udmale, P., Pal, I., Szabo, S., Pramanik, M., & Large, A. (2020). Global food security in the context of COVID-19: A scenario-based exploratory analysis. Progress in Disaster Science, 7, 100120. https://doi.org/10.1016/j.pdisas.2020.100120
  • USDA, (2021). Has global agricultural trade been resilient under coronavirus (COVID-19)? findings from an econometric assessment Shawn Arita , Jason Grant , Sharon Sydow , and Jayson Beckman OCE Working Paper Preliminary U . S . Department of Agriculture Office of th. 1–38.
  • Wang, Yudong, Zhang, B., Diao, X., & Wu, C. (2015). Commodity price changes and the predictability of economic policy uncertainty. Economics Letters, 127, 39–42. https://doi.org/10.1016/j.econlet.2014.12.030
  • World Bank (2018). Global economic prospects: Broad-based upturn, but for how long? https://openknowledge.worldbank.org/bitstream/handle/10986/28932/9781464811630.pdf?sequence=16&isAllowed=y
  • Yakubu, M., Sarkodie, S.A., 2021. How COVID-19 pandemic may hamper sustainable economic development. Journal of Public Affairs. Article PA2675 https://doi.org/10.1002/PA.2675
  • Yan, W., Cai, Y., Lin, F., & Ambaw, D. T. (2021). The ımpacts of trade restrictions on world agricultural price volatility during the COVID-19 pandemic. China and World Economy, 29(6), 139–158. https://doi.org/10.1111/cwe.12398
  • Yin, L., & Han, L. (2014). Macroeconomic uncertainty: Does it matter for commodity prices? Applied Economics Letters, 21(10), 711–716. https://doi.org/10.1080/13504851.2014.887181

TARIMSAL HAMMADDELER VE EKONOMİ POLİTİKASI BELİRSİZLİĞİ NEDENSELLİK İLİŞKİSİ: ZAMANLA DEĞİŞEN GRANGER NEDENSELLIK TESTİNDEN KANITLAR

Year 2023, Volume: 19 Issue: 1, 1 - 13, 24.03.2023
https://doi.org/10.17130/ijmeb.1186996

Abstract

Bu çalışma, tarımsal hammadde emtia fiyatları ile ABD ekonomik politikası belirsizliği (EPU) arasındaki nedensellik etkileşiminin zamanla değişen dinamiklerini incelemeyi amaçlamaktadır. Bu amaçla, Ocak 1992 - Kasım 2021 dönemini kapsayan aylık veriler kullanılmıştır. Nedensellik etkileşiminin zamanla değişen dinamikleri hakkında ampirik kanıtlar sağlamak ve böylece önemli tarihsel olaylar sırasında bu etkileşimlerin potansiyel heterojenliklerini ortaya çıkarmak için zamanla değişen bir Granger nedensellik testi kullanıyoruz. Sonuçlar, EPU'dan tarımsal hammaddelere uzanan nedenselliğin yanı sıra tarımsal hammaddelerden EPU'ya uzanan nedenselliğin de zamanla değişen dinamikler sergilediğini göstermektedir. Daha spesifik olarak, bulgular 2000-2014 döneminin büyük bir bölümünde nedenselliğin genellikle tarımsal hammaddelerden EPU'ya doğru gitme eğiliminde olduğunu, ancak bu durumun ABD-Çin ticaret savaşı ve Covid-19 pandemi dönemi ile tersine döndüğünü ortaya koymaktadır. Bu sonuç, ekonomik belirsizlik-emtia fiyatları ilişkisindeki potansiyel nedensellik etkileşimlerinin dinamik bir çerçeve içinde modellenmesinin önemini vurgulamakta ve bu etkileşimlerin hakim ekonomik, politik ve küresel koşullardan bağımsız olarak düşünülemeyeceğini ima etmektedir.

References

  • Ahmed, M. Y., & Sarkodie, S. A. (2021). COVID-19 pandemic and economic policy uncertainty regimes affect commodity market volatility. Resources Policy, 74 (April), 102303. https://doi.org/10.1016/j.resourpol.2021.102303
  • Antonakakis, N., Chatziantoniou, I., & Filis, G. (2014). Dynamic spillovers of oil price shocks and economic policy uncertainty. Energy Economics, 44, 433–447. https://doi.org/10.1016/j.eneco.2014.05.007
  • Apergis, N., Hayat, T., & Saeed, T. (2021). US partisan conflict uncertainty and oil prices. Energy Policy, 150 (January), 112118. https://doi.org/10.1016/j.enpol.2020.112118
  • Bakas, D., & Triantafyllou, A. (2018). The impact of uncertainty shocks on the volatility of commodity prices. Journal of International Money and Finance, 87, 96–111. https://doi.org/10.1016/j.jimonfin.2018.06.001
  • Bakas, D., & Triantafyllou, A. (2020). Commodity price volatility and the economic uncertainty of pandemics. Economics Letters, 193, 109283. https://doi.org/10.1016/j.econlet.2020.109283
  • Baker, S. R., & Bloom, N. (2013). Does uncertainty reduce growth? Using disasters as natural experiments. NBER Working Papers, 1–31. http://www.nber.org/papers/w19475
  • Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring economic policy uncertainty. Quarterly Journal of Economics, 131(4), 1593–1636. https://doi.org/10.1093/qje/qjw024
  • Baker, S.R., Bloom, N., Davis, S.J., Terry, S.J., (2020). Covid-induced Economic Uncertainty. (0898-2937).
  • Bannigidadmath, D., & Narayan, P. K. (2021). Commodity futures returns and policy uncertainty. International Review of Economics and Finance, 72 (December), 364–383. https://doi.org/10.1016/j.iref.2020.11.009
  • Barsky, R. B., & Kilian, L. (2004). Oil and the macroeconomy Since the 1970s. Journal of Economic Perspectives, 18(4), 115–134. https://doi.org/10.1257/0895330042632708
  • Bloom, N. (2009). The impact of uncertainty shocks. Econometrica, 77(3), 623–685. https://doi.org/10.3982/ECTA6248 Bloom, N. (2014). Fluctuations in uncertainty. https://doi.org/10.2139/ssrn.2423515
  • Bloom, N. (2016). Fluctuations in uncertainty. Voprosy Ekonomiki, 2016(4), 30–55. https://doi.org/10.32609/0042-8736-2016-4-30-55
  • Bouri, E., Cepni, O., Gabauer, D., & Gupta, R. (2021). Return connectedness across asset classes around the COVID-19 outbreak. International Review of Financial Analysis, 73(May 2020), 101646. https://doi.org/10.1016/j.irfa.2020.101646
  • Clemente, J., Montañés, A., & Reyes, M. (1998). Testing for a unit root in variables with a double change in the mean. Economics Letters, 59(2), 175–182. https://doi.org/10.1016/s0165-1765(98)00052-4
  • Garner, A. (2017). Commodity Prices: Policy Target or Information Variable?: Note Author ( s ): C . Alan Garner Source: Journal of Money, Credit and Banking, Vol. 21, No. 4 (Nov., 1989), pp. 508-514 Published by: Ohio State University Press Stable URL: http://. 21(4), 508–514.
  • Hailemariam, A., Smyth, R., & Zhang, X. (2019). Oil prices and economic policy uncertainty: Evidence from a nonparametric panel data model. Energy Economics, 83, 40–51. https://doi.org/10.1016/j.eneco.2019.06.010
  • Huang, J., Li, Y., Zhang, H., & Chen, J. (2021). The effects of uncertainty measures on commodity prices from a time-varying perspective. International Review of Economics and Finance, 71(February 2020), 100–114. https://doi.org/10.1016/j.iref.2020.09.001
  • IMF (2022). International Monetary Fund. IMF Primary Commodity Prices. https://www.imf.org/en/Research/commodity-prices
  • Joëts, M., Mignon, V., & Razafindrabe, T. (2017). Does the volatility of commodity prices reflect macroeconomic uncertainty? Energy Economics, 68, 313–326. https://doi.org/10.1016/j.eneco.2017.09.017
  • Just, M., & 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
  • Kaldor, N. (1987). The role of commodity prices in economic recovery. World Development, 15(5), 551–558. https://doi.org/10.1016/0305-750X(87)90002-7
  • Kang, W., & Ratti, R. A. (2013a). Structural oil price shocks and policy uncertainty. Economic Modelling, 35, 314–19. https://doi.org/10.1016/j.econmod.2013.07.025.
  • Kang, W., & Ratti, R. A. (2013b). Oil shocks, policy uncertainty and stock market return. Journal of International Financial Markets, Institutions and Money, 26(1), 305–18. https://doi.org/10.1016/j.intfin.2013.07.001.
  • Kilian, L., 2009. Not All Oil price shocks are alike: disentangling demand and supply shocks. American Economic Review, 99, 1053–1069. https://www.jstor.org/stable/25592494.
  • Leduc, S., & Liu, Z. (2020). The Uncertainty Channel of the Coronavirus. Federal Reserve Bank of San Francisco.
  • Newey, W.K., West, K.D., 1987. A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica. 55, 703–708. https://doi.org/10.3386/t0055.
  • Sharif, A., Aloui, C., & Yarovaya, L. (2020). COVID-19 pandemic, oil prices, stock market, geopolitical risk and policy uncertainty nexus in the US economy: Fresh evidence from the wavelet-based approach. International Review of Financial Analysis, 70(April), 101496. https://doi.org/10.1016/j.irfa.2020.101496
  • Shi, S., Hurn, S., & Phillips, P. C. B. (2020). Causal change detection in possibly integrated systems: Revisiting the money-income relationship. Journal of Financial Econometrics, 18(1), 158–180. https://doi.org/10.1093/JJFINEC/NBZ004
  • Shi, S., Phillips, P. C. B., & Hurn, S. (2018). Change detection and the causal impact of the yield curve. Journal of Time Series Analysis, 39(6), 966–987. https://doi.org/10.1111/jtsa.12427
  • Shi, X., & Shen, Y. (2021). Macroeconomic uncertainty and natural gas prices: Revisiting the Asian Premium. Energy Economics, 94, 105081. https://doi.org/10.1016/j.eneco.2020.105081
  • Stock, J. H., & Watson, M. W. (2012). Disentangling the channels of the 2007-09 recession. Brookings Papers on Economic Activity, 1, 81–135. https://doi.org/10.1353/eca.2012.0005
  • Sun, T. T., Su, C. W., Mirza, N., & Umar, M. (2021). How does trade policy uncertainty affect agriculture commodity prices?. Pacific Basin Finance Journal, 66(February), 101514. https://doi.org/10.1016/j.pacfin.2021.101514
  • Sun, X., Chen, X., Wang, J., & Li, J. (2020). Multi-scale interactions between economic policy uncertainty and oil prices in time-frequency domains. North American Journal of Economics and Finance, 51(September), 1–15. https://doi.org/10.1016/j.najef.2018.10.002.
  • Tunc, A., Kocoglu, M., & Aslan, A. (2022). Time-varying characteristics of the simultaneous interactions between economic uncertainty, international oil prices and GDP: A novel approach for Germany. Resources Policy, 77(April), 102658. https://doi.org/10.1016/j.resourpol.2022.102658
  • Udmale, P., Pal, I., Szabo, S., Pramanik, M., & Large, A. (2020). Global food security in the context of COVID-19: A scenario-based exploratory analysis. Progress in Disaster Science, 7, 100120. https://doi.org/10.1016/j.pdisas.2020.100120
  • USDA, (2021). Has global agricultural trade been resilient under coronavirus (COVID-19)? findings from an econometric assessment Shawn Arita , Jason Grant , Sharon Sydow , and Jayson Beckman OCE Working Paper Preliminary U . S . Department of Agriculture Office of th. 1–38.
  • Wang, Yudong, Zhang, B., Diao, X., & Wu, C. (2015). Commodity price changes and the predictability of economic policy uncertainty. Economics Letters, 127, 39–42. https://doi.org/10.1016/j.econlet.2014.12.030
  • World Bank (2018). Global economic prospects: Broad-based upturn, but for how long? https://openknowledge.worldbank.org/bitstream/handle/10986/28932/9781464811630.pdf?sequence=16&isAllowed=y
  • Yakubu, M., Sarkodie, S.A., 2021. How COVID-19 pandemic may hamper sustainable economic development. Journal of Public Affairs. Article PA2675 https://doi.org/10.1002/PA.2675
  • Yan, W., Cai, Y., Lin, F., & Ambaw, D. T. (2021). The ımpacts of trade restrictions on world agricultural price volatility during the COVID-19 pandemic. China and World Economy, 29(6), 139–158. https://doi.org/10.1111/cwe.12398
  • Yin, L., & Han, L. (2014). Macroeconomic uncertainty: Does it matter for commodity prices? Applied Economics Letters, 21(10), 711–716. https://doi.org/10.1080/13504851.2014.887181
There are 41 citations in total.

Details

Primary Language English
Subjects Economics
Journal Section Research Articles
Authors

Ahmet Tunç 0000-0002-0864-2695

Savaş Savaş 0000-0002-9036-198X

Doğan Barak 0000-0002-8812-7668

Publication Date March 24, 2023
Submission Date October 10, 2022
Acceptance Date January 10, 2023
Published in Issue Year 2023 Volume: 19 Issue: 1

Cite

APA Tunç, A., Savaş, S., & Barak, D. (2023). THE CAUSALITY BETWEEN AGRICULTURAL RAW MATERIALS AND ECONOMIC POLICY UNCERTAINTY: EVIDENCE FROM THE TIME-VARYING GRANGER CAUSALITY. Uluslararası Yönetim İktisat Ve İşletme Dergisi, 19(1), 1-13. https://doi.org/10.17130/ijmeb.1186996