Commodity price developments and the minerals industry

Raputsoane, Leroi (2024): Commodity price developments and the minerals industry.

Abstract

This paper analyses the reaction of the minerals industry to Commodity price developments in South Africa. This is achieved by augmenting a Taylor rule type central bank monetary policy reaction function with a measure of commodity prices. The results provide evidence of a statistically significant effect of an increase in commodity prices on output of the mining industry, which peaks at 0.69 percentage points after 3 months, with statistically significant impact that lasts up to 5 months. This is consistent with the hypothesis that the prices of Commodities and economic growth co move in the short run, while the large and persistent movements in commodity prices exhibit no such changes in economic growth, particularly in most resource rich countries. The results have also shown that the effect of the increase in output of minerals industry on commodity prices is, however, statistically insignificant in all periods, which implies inadequate market share of the minerals industry in commodities markets. The results support the hypothesis of a transitory comovement of the prices of commodities and output of the minerals industry, hence policy makers and mining authorities should continue to monitor developments in commodity prices to support overall economic activity as well as the minerals industry.

• Item Type: MPRA Paper
• Language: English
• Keywords: commodity prices, Minerals industry, Economic cycles
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C11 - Bayesian Analysis: General; E - Macroeconomics and Monetary Economics > E5 - Monetary Policy, Central Banking, and the Supply of Money and Credit > E52 - Monetary Policy; L - Industrial Organization > L7 - Industry Studies: Primary Products and Construction > L71 - Mining, Extraction, and Refining: Hydrocarbon Fuels; L - Industrial Organization > L7 - Industry Studies: Primary Products and Construction > L72 - Mining, Extraction, and Refining: Other Nonrenewable Resources

References

Auty, R. M. (2002). Sustaining Development in Mineral Economies: The Resource Curse Thesis. Routledge, Oxfordshire.

Auty, R. M. (2005). Resource Abundance and Economic Development. Oxford University Press, Oxford.

Baxter, M. and King, R. G. (1999). Measuring Business Cycles: Approximate Band Pass Filters for Economic Time Series. Review of Economics and Statistics, 81(4):575–593.

Blanchard, O. J. and Gali, J. (2007). The Macroeconomic Effects of Oil Shocks: Why are the 2000s So Different from the 1970s? Working Paper Series, 13368. National Bureau of Economic Research (NBER).

Blanchard, O. J., Hall, R. E., and Hubbard, R. G. (1986). Market Structure and Macroeconomic Fluctuations. Brookings Papers on Economic Activity, 1986(2):285–338.

Blanchard, O. J. and Quah, D. (1988). The Dynamic Effects of Aggregate Demand and Supply Disturbances. Working Papers Series, 2737. National Bureau of Economic Research (NBER).

Burns, A. F. and Mitchell, W. C. (1946). Measuring Business Cycles. National Bureau of Economic Research (NBER), Cambridge, Massachusetts.

Canova, F. (2011). Methods for Applied Macroeconomic Research. Princeton University Press, Princeton, New Jersey.

Christiano, L. J. and Fitzgerald, T. J. (2003). The Band Pass Filter. International Economic Review, 44(2):435–465.

Del Negro, M. and Schorfheide, F. (2011). Bayesian Macroeconometrics. Handbook of Bayesian Econometrics, 1(7):293–387.

Diebold, F. X. and Rudebusch, G. D. (1970). Measuring Business Cycles: A Modern Perspective. Review of Economics and Statistics, 78(1):67–F77.

European Central Bank (ECB) (2012). Stock Prices and Economic Growth. Monthly Bulletin, October. European Central Bank (ECB).

Evans, C. and Kuttner, K. N. (1998). Can VARs Describe Monetary Policy? Working Paper Series, 9812. Federal Reserve Bank of Chicago.

Frankel, J. A. (2008). An Explanation for Soaring Commodity Prices. VoxEU Columns, 25 March. Centre for Economic Policy Research (CEPR).

Frankel, J. A. (2010). The Natural Resource Curse: A Survey. Working Paper Series, 15836. National Bureau of Economic Research (NBER).

Frankel, J. A. (2012). The Natural Resource Curse: A Survey of Diagnoses and Some Prescriptions. Working Paper Series, RWP12-014. Harvard University Research.

Friedman, M., Schwartz, A. J., et al. (1963). Money and Business Cycles. Bobbs-Merrill Company, Indianapolis, Indiana.

Gali, J. (1992). How Well Does the IS-LM Model Fit Post War US Data? The Quarterly Journal of Economics, 107(2):709–738.

Giannone, D., Banbura, M., and Reichlin, L. (2010). Large Bayesian Vector Autoregressions. Journal of Applied Econometrics, 25(1):71–92.

Giannone, D., Lenza, M., and Primiceri, G. E. (2015). Prior Selection for Vector Autoregressions. Review of Economics and Statistics, 97(2):436–451.

Gordon, R. J. (2007). The American Business Cycle: Continuity and Change, volume 25. University of Chicago Press, Chicago.

Hamilton, J. D. (1994). Time Series Analysis, volume 2. Princeton university press, Princeton, New Jersey.

Hodrick, R. and Prescott, E. C. (1997). Postwar U.S. Business Cycles: An Empirical Investigation. Journal of Money, Credit and Banking, 29(1):1–16.

Hyndman, R. and Athanasopoulos, G. (2018). Forecasting: Principles and Practice. OTexts, Melbourne, 2nd Edition.

Jacks, D. S. (2013). From Boom to Bust: A Typology of Real Commodity Prices in the Long Run. Working Paper Series, 18874. National Bureau of Economic Research (NBER).

Kadiyala, K. R. and Karlsson, S. (1997). Numerical Methods for Estimation and Inference in Bayesian VAR models. Journal of Applied Econometrics, 12(2):99–132.

Kaminsky, G. L., Reinhart, C. M., and Vegh, C. A. (2004). When It Rains, It Pours: Procyclical Capital Flows and Macroeconomic Policies. Macroeconomics Annual, 19:11–53. National Bureau of Economic Research (NBER).

Koop, G. and Korobilis, D. (2010). Bayesian Multivariate Time Series Methods for Empirical Macroeconomics. Foundations and Trends in Econometrics, 3(4):267–358.

Koop, G. M. (2013). Forecasting With Medium and Large Bayesian VARs. Journal of Applied Econometrics, 28(2):177–203.

Kydland, F. E. and Prescott, E. C. (1990). Business Cycles: Real Facts and a Monetary Myth. Quarterly Review, 4:3–18. Federal Reserve Bank of Minneapolis.

Labys, W. C., Achouch, A., and Terraza, M. (1999). Metal Prices and the Business Cycle. Resources Policy, 25(4):229–238.

Labys, W. C. and Maizels, A. (1993). Commodity Price Fluctuations and Macroeconomic Adjustments in the Developed Economies. Journal of Policy Modeling, 15(3):335–352.

Litterman, R. (1984). Forecasting and Policy Analysis with Bayesian Vector Autoregression Models. Quarterly Review, Fall. Federal Reserve Bank of Minneapolis.

Litterman, R. B. (1979). Techniques of Forecasting Using Vector Autoregressions. Working Paper Series, 115. Federal Reserve Bank of Minneapolis.

Litterman, R. B. (1980). Bayesian Procedure for Forecasting with Vector Autoregressions. Working Paper Series, 274. Federal Reserve Bank of Minneapolis.

L¨utkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer Books, New York. Mise, E., Kimand, T., and Newbold, P. (2005). On Suboptimality of the Hodrick Prescott Filter at Time Series Endpoints. Journal of Macroeconomics, 27(1):53–67.

Morgan Stanley Capital International (MSCI). (2014). Cyclical and Defensive Sectors. Indexes Methodology, June. Morgan Stanley Capital International (MSCI).

O’Hara, K. (2015). Bayesian Macroeconometrics in R. New York University Press, New York, 0.5.0 edition.

Quah, D. (1988). Sources of Business Cycle Fluctuations: Comments. Macroeconomics Annual, 3:151–155. National Bureau of Economic Research (NBER).

Ravn, M. O. and Uhlig, H. (2002). On Adjusting the Hodrick-Prescott Filter for the Frequency of Observations. Review of Economics and Statistics, 84(2):371–376.

Romer, C. D. (1986). Is the Stabilization of the Postwar Economy a Figment of the Data? The American Economic Review, 76(3):314–334.

Romer, C. D. (1993). Business Cycles. In Henderson, D. R., editor, The Fortune: Encyclopedia of Economics, volume 330.03 F745f. Warner Books.

Rudebusch, G. D. (1998). Do Measures of Monetary Policy in a VAR Make Sense? International Economic Review, 39(4):907–931.

Schwarz, G. (1978). Estimating the Dimension of a Model. Annals of Statistics, 6:461–464.

Shapiro, M. D. (1987). Are Cyclical Fluctuations in Productivity Due More to Supply Shocks or Demand Shocks? Working Paper Series, 2589. National Bureau of Economic Research (NBER).

Shapiro, M. D. and Watson, M. W. (1988). Sources of Business Cycle Fluctuations. Macroeconomics Annual, 3:111–156. National Bureau of Economic Research (NBER).

Sims, C. A. (1980). Macroeconomics and Reality. Journal of Economic Perspectives, 48(1):1–48.

Sims, C. A. (1989). A nine Variable Probabilistic Macroeconomic Forecasting Model. Discussion Paper, 14. Federal Reserve Bank of Minneapolis.

Sims, C. A. and Uhlig, H. (1991). Understanding Unit Rooters: A Helicopter Tour. Econometrica, 59(6):1591–1599.

Spatafora, N. and Tytell, I. (2009). Commodity Terms of Trade: The History of Booms and Busts. Working Paper Series, 09/205. International Monetary Fund (IMF).

Stock, J. H. and Watson, M. W. (1999). Business Cycle Fluctuations in US Macroeconomic Time Series. Handbook of Macroeconomics, 1(Part A):3–64.

Stock, J. H. and Watson, M. W. (2001). Vector Autoregressions. Journal of Economic Perspectives, 15(4):101–115.

Stuermer, M. (2018). 150 Years of Boom and Bust: What Drives Mineral Commodity Prices? Macroeconomic Dynamics, 22(3):702–717.

Taylor, J. B. (1993). Discretion Versus Policy Rules in Practice. Carnegie-Rochester Conference Series on Public Policy, 39:195–214.

Van Wijnbergen, S. (1984). The ’Dutch Disease’: A Disease After All? The Economic Journal, 94(373):41–55.