Modeling Climate Change Effects on Renewable and Non-Renewable Resources

Chapter

Abstract

This paper models climate change effects differentiating across primary commodities based on their exhaustibility factor. There is a direct pass-through to futures prices, but the impact differs across diverse commodity groups. This paper develops a theoretical model simulating dynamic consumption paths of renewable and non-renewable resources. Dynamic paths are calculated applying the Non-linear Model Predictive Control (NMPC) methodology. Current analysis draws a clear connection between intensifying impacts of climate change, commodity futures price volatility, rising urban-dependency pressures and the renewable and non-renewable resources production and consumption balance among advanced and emerging economies. Accumulated evidence suggests probable higher volatility in commodity prices in the near term, directly affecting small and large economies across all regions.

Keywords

Climate change Futures volatility Primary commodities Renewable and non-renewable resources Non-linear model predictive control (NMPC) Urban dependency 

References

  1. Arezki, R., Hadri, K., Loungani, P., & Rao, Y. (2013). Testing the Prebisch-Singer hypothesis since 1650: Evidence from panel techniques that allow for multiple breaks. IMF Working Paper No. 13/180.Google Scholar
  2. Baffes, J. (2007). Oil spills on other commodities. Policy Research Working Paper Series, 32(3), 126–134.Google Scholar
  3. Baffes, J., & Haniotis, T. (2010). Placing the 2006/08 commodity price boom into perspective. Policy Research Working Paper 5371.Google Scholar
  4. Bernard, L., & Semmler W. (Eds.). (2015). The Oxford handbook of the macroeconomics of global warming. New York, NY: Oxford University Press.Google Scholar
  5. Bernard, L., Greiner, A., & Semmler, W. (2012). Agricultural commodities and their financialization. AESTIMATIO The IEB International Journal of Finance, 5, 2–25.Google Scholar
  6. BP. (2015). 64th edition of the BP Statistical Review of World Energy – Data workbook. Available online: http://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html. (Accessed October 31, 2015)
  7. Canuto, O. (2014). Commodity Super Cycle to Stick Around a Bit Longer. Available online. http://cfi.co/africa/2014/08/world-bank-group-commodity-super-cycle-to-stick-around-a-bit-longer/. (Accessed October 31, 2015)
  8. Dobbs, R., Oppenheim, J., Thompson, F., Mareels, S., Nyquist, S., & Sanghvi, S. (2013). Resource revolution: Tracking global commodity markets. McKinsey Global Institute. Available online: http://www.mckinsey.com/insights/energy_resources_materials/resource_revolution_tracking_global_commodity_markets. (Accessed October 1, 2015)
  9. Enders, W., & Holt, M. (2013). The evolving relationships between agricultural and energy commodity prices: A shifting-mean vector autoregressive analysis. NBER 12810.Google Scholar
  10. Gevorkyan, A. V., & Kvangraven, I. H. (2016, forthcoming). Assessing recent determinants of borrowing costs in Sub-Saharan Africa. Review of Development Economics. doi:10.1111/rode.12195.
  11. Gevorkyan, A., & Gevorkyan, A. (2012). Derivatives, commodities, and social costs: Exploring correlation in economic uncertainty. Contemporary Studies in Economic and Financial Analysis, 94, 47–70.CrossRefGoogle Scholar
  12. Greiner, A., & Semmler, W. (2008). The global environment, natural resources, and economic growth. Oxford: University Press.CrossRefGoogle Scholar
  13. Grune, L., & Pannek, J. (2011). Nonlinear model predictive control. New York, NY: Springer.CrossRefGoogle Scholar
  14. Hamilton, J., & Wu, J. (2014). Effect of index-fund investing on commodity futures prices. NBER Working Paper doi:10.3386/w19892
  15. Harvey, M., & Pilgrim, S. (2011). The new competition for land: Food, energy, and climate change. Food Policy, 36(1), S40–S51.Google Scholar
  16. Havlík, P., et al. (2013). Crop productivity and the global livestock sector: Implications for land use change and greenhouse gas emissions. American Journal of Agricultural Economics, 95(2), 442–448.CrossRefGoogle Scholar
  17. Henderson, V. (2002). Urbanization in developing countries. The World Bank Research Observer, 17(1), 89–112.CrossRefGoogle Scholar
  18. Herrero, M., et al. (2010). Smart investments in sustainable food production: Revisiting mixed crop-livestock systems. Science, 327, 822–825.CrossRefGoogle Scholar
  19. International Monetary Fund. (2015). IMF Primary Commodity Prices. Available online: http://www.imf.org/external/np/res/commod/index.aspx. (Accessed October 25, 2015)Google Scholar
  20. Jones, C., & Sands, R. (2013). Impact of agricultural productivity gains on greenhouse gas emissions: A global analysis. American journal of agricultural economics, 95(5), 1309–1316.CrossRefGoogle Scholar
  21. Knittel, C., & Pindyck, R. (2013). The simple economics of commodity price speculation. NBER Working Paper doi:10.3386/w18951
  22. Manera, M., Nicolini, M., & Vignati, I. (2012). Returns in commodities futures markets and financial speculation: A multivariate GARCH approach. FEEM Working Paper No. 23.2012. Available at SSRN: http://ssrn.com/abstract=2041177Google Scholar
  23. NASA/GISS. (2015). Global Temperature. Available online: http://climate.nasa.gov/vital-signs/global-temperature/. (Accessed October 25, 2015)
  24. Quigley, J. M. (1998). Urban diversity and economic growth. Journal of Economic Perspectives, 12, 127–138.CrossRefGoogle Scholar
  25. Roache, K. (2010). What explains the rise in food price volatility? IMF Working Paper, WP/10/129Google Scholar
  26. Ruta, M., & Venables, A. (2012). International trade in natural resources: Practice and policy. World Trade Organization, Working Paper ERSD-2012-07.Google Scholar
  27. Schlenker, W., & Roberts, M. (2009). Nonlinear temperature effects indicate severe damages to U.S. crop yields under climate change. PNAS, 106(37), 15594–15598.CrossRefGoogle Scholar
  28. Tilman, D., Balzerb, C., Hillc, J., & Beforta, B. (2011). Global food demand and the sustainable intensification of agriculture. Proceedings of the National Academy of Sciences of the United States of America, 108(50), 20260–20264.Google Scholar
  29. United Nations. (2015). World urbanization prospects the 2014 revision. New York, NY: United Nations.Google Scholar
  30. World Bank. (2000). Dynamic cities as engines of economic growth, Entering the 21st Century: World Development Reporter: 125–138.Google Scholar
  31. World Bank Development Indicators. (2015). World Development Indicators – online database. Available online: http://data.worldbank.org/products/wdi. (Accessed October 1, 2015)

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.The Peter J. Tobin College of Business, St. John’s UniversityNew YorkUSA
  2. 2.New School for Social Research, The New SchoolNew YorkUSA

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