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Monetary policy shocks and real commodity prices

  • Christopher Phillip Reicher EMAIL logo and Johannes Friederich Utlaut
Published/Copyright: October 12, 2013
The B.E. Journal of Macroeconomics
From the journal The B.E. Journal of Macroeconomics Volume 13 Issue 1

Abstract

In this paper we document the effects of monetary policy shocks on real commodity prices. Based on a VAR estimated using long-run restrictions, an expansionary monetary policy shock causes real commodity prices and output both to rise sharply for a short period of time. We find that a simple dynamic equilibrium model of commodity supply and demand can give a realistic response of real commodity prices to monetary policy shocks, for a wide range of parameter values. Furthermore, we find that based on historical simulations, shocks to monetary policy played an important role in commodity price fluctuations during the Great Recession, but they have contributed negligibly to commodity price movements overall since 1970. Even though monetary policy shocks have a robust and large marginal effect on real commodity prices, most monetary policy shocks are small, and most fluctuations in real commodity prices are correspondingly small.

Keywords: commodity prices; long-run restrictions; monetary policy; overshooting; JEL Codes: E31; E52; E65; Q00
Corresponding author: Christopher Phillip Reicher, Kiel Institute for the World Economy, Hindenburgufer 66, 24105 Kiel, Germany, Tel.: +49 (0)431 8814 300, e-mail:
  1. 1

    Kilian (2009), for instance, presents convincing evidence that movements in commodity demand due to movements in real global economic activity are an important driver of oil prices. Hamilton (2009a) discusses the role of global oil demand in the context of the 2007–2008 runup in oil prices. Barsky and Kilian (2002) blame an unanchoring of monetary policy for much of the commodity price volatility of the 1970s, and Barsky and Kilian (2004) further discuss the idea that oil prices are endogenous.

  2. 2

    Lastrapes (2006) looks at the dispersion of individual commodity prices over time in response to inflation. Lastrapes and Selgin (1995) do not look at commodity prices, but they use long-run restrictions to investigate the liquidity effect.

  3. 3

    Results from these tests are available from the authors upon request, as are the impulse response charts for alternate specifications.

  4. 4

    The assumption of competitive, flexibly-priced markets in the supply of commodities may apply better to some markets (e.g., some portions of world agricultural markets) than to others (e.g., oil before the 1970s or in the presence of OPEC). Despite a certain degree of unrealism, we follow the macroeconomic literature in making this assumption in order to concentrate on the basic macroeconomic issues surrounding an inelastic supply of commodities.

We would like to thank seminar and workshop participants at the Kiel Institute and especially Harmen Lehment for their helpful comments. We also thank Jim Hamilton, Henning Weber, Arpad Abraham, and two anonymous referees for their helpful feedback. All remaining errors are ours.

Appendix A: The data on long-term forward inflation expectations

This appendix discusses our long-term forward inflation expectations series, which we construct from a combination of data on inflation forecasts and interest rates. We construct a consistent series of 1-to-10 year forward inflation forecasts derived from a composite of median forecast surveys, for the CPI following 1983 and for the old fixed-weight GDP deflator (which mimics the CPI in the long run) before that. After 1990, the longer-term forecasts come directly from the Survey of Professional Forecasters, and all shorter-term forecasts come from that survey. From the end of 1979 to 1990, the longer-term forecasts come from a composite of the Blue Chip Survey and the Livingston Survey provided by the Philadelphia Fed. Before 1979 and during missing quarters, we interpolate by projecting CPI inflation using the forward interest rate. The regression coefficient equals 0.662, which yields about the same cointegrating relationship as that which Crowder and Hoffman (1996) find between interest rates and CPI inflation. We interpolate inflation expectations using that rate and coefficient, correcting linearly for errors in closure. The spreadsheets provided by the Philadelphia Fed give the details of the data underlying the different surveys. In general our measure tracks that of Clark and Nakata (2008) extremely well, though we think that more historical scholarship is needed if we wish to firm up our estimates of trend inflation beyond the early 1970s.

The top panel of Figure 1 shows the behavior of the composite measure of expected forward inflation throughout the sample along with two other alternative measures, all at annual rates. The measures of trend inflation coincide with the idea that the 1970s were a period of high trend inflation, while the 1990s and 2000s were periods of low and stable trend inflation. Monetary policy has also deviated less from its trend in the short run, except for the notable large deflationary episode which occurred during the Great Recession. Figure 1 also shows the 10–20 year forward treasury rate, calculated using constant maturity data from the FRED database. For the period when no data exist for 20-year treasuries, we linearly project quarterly changes in the 20-year rate using changes in the 10-year and 30-year rates and then correct linearly for the error of closure. Other interpolation methods give almost the exact same results. The composite forward rate broadly tracks changes in inflation expectations but shows more short-run volatility, particularly during the early to mid 1980s. There are also important medium-frequency movements in real interest rates (particularly during the mid 1980s) which show up in the forward interest rate series but do not show up as strongly in the forward inflation rate series. This is why we choose our composite inflation indicator as our measure of trend inflation; there do appear to be factors which affect long-term interest rates in the medium run apart from trend inflation.

Because of these concerns about using interest rates to project inflation expectations back through the 1970s, we also create a regression-based expected inflation indicator broadly similar to that developed by Kozicki and Tinsley (2006), also shown in Figure 1. The Livingston Survey goes back before 1979 but it lacks explicit information on long-term inflation forecasts. Kozicki and Tinsley estimate a state-space model in order to extract trend and temporary components to inflation forecasts. We do something simpler which delivers a very similar result to theirs. We take the Livingston Survey median forecasts for the CPI and regress our post-1980 forward inflation indicator on forecasted 2-year-ahead inflation (based on the 2 year forecast and the 1 year forecast) and on 14-month inflation (based on the 12-month forecast and base-period levels which are reported with a lag of 2 months). Our measure of longer-term expected inflation seems to track their measure relatively well.

Appendix B: Solving the model

B.1. Steady state

Solving for the steady state of the model involves solving the following system of equations:

or in closed form,

and

Real interest rates are stationary and unrelated to inflation, so their long-run values pin down β. Long-run steady states are well behaved as a function of inflation so long as inflation is within the admissible range, so simple numerical search algorithms work well at solving this system.

B.2 The linearized model

The linearized model is fairly straightforward, with one complication that we have to look at two sectors at once. The New Keynesian aggregate supply equation no longer has a closed form, which makes things somewhat more complicated as well. Lower case letters denote linearized objects. Prices here are in real terms, using economywide output as the numeraire. We use the code provided by Sims (2002) to solve for the nonexplosive equilibrium of the system, which is locally determinate in the economy which we study.

The asset pricing equation becomes:

The economywide production function and sectoral demand equations become:

and

The sticky price-setting equation, as a reminder, is given by

and it can be written as

where

and

Around a no-inflation, no-growth steady state, the three equations reduce into the familiar New Keynesian aggregate supply relationship. In the presence of trend inflation, the ability to neatly reduce the size of the model vanishes, so we must carry around the two auxiliary variables LHS and RHS. The linearization is given by:

and

The index of sticky prices becomes:

Sticky-price goods productivity is given by:

Flexible-goods pricing implies that:

and flexible-good production is given by:

Household labor supply is given by:

and market clearing in labor yields the expression:

The linearized monetary policy rule becomes:

The three driving processes zt, and xt are held constant at zero.

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Published Online: 2013-10-12
Published in Print: 2013-01-01

©2013 by Walter de Gruyter Berlin Boston

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https://doi.org/10.1515/bejm-2012-0083
Keywords for this article
commodity prices; long-run restrictions; monetary policy; overshooting; JEL Codes: E31; E52; E65; Q00

Articles in the same Issue

  1. Masthead
  2. Masthead
  3. Advances
  4. How have global shocks impacted the real effective exchange rates of individual euro area countries since the euro’s creation?
  5. Employment by age, education, and economic growth: effects of fiscal policy composition in general equilibrium
  6. Overeducation and skill-biased technical change
  7. Strategic wage bargaining, labor market volatility, and persistence
  8. Households’ uncertainty about Medicare policy
  9. Contributions
  10. Deconstructing shocks and persistence in OECD real exchange rates1)
  11. A contribution to the empirics of welfare growth
  12. Development accounting with wedges: the experience of six European countries
  13. Implementation cycles, growth and the labor market
  14. International technology adoption, R&D, and productivity growth
  15. Bequest taxes, donations, and house prices
  16. Business cycle accounting of the BRIC economies
  17. Privately optimal severance pay
  18. Small business loan guarantees as insurance against aggregate risks
  19. Output growth and unexpected government expenditures
  20. International business cycles and remittance flows
  21. Effects of productivity shocks on hours worked: UK evidence
  22. A prior predictive analysis of the effects of Loss Aversion/Narrow Framing in a macroeconomic model for asset pricing
  23. Exchange rate pass-through and fiscal multipliers
  24. Credit demand, credit supply, and economic activity
  25. Distortions, structural transformation and the Europe-US income gap
  26. Monetary policy shocks and real commodity prices
  27. Topics
  28. News-driven international business cycles
  29. Business cycle dynamics across the US states
  30. Required reserves as a credit policy tool
  31. The macroeconomic effects of the 35-h workweek regulation in France
  32. Productivity and resource misallocation in Latin America1)
  33. Information and communication technologies over the business cycle
  34. In search of lost time: the neoclassical synthesis
  35. Divorce laws and divorce rate in the US
  36. Is the “Great Recession” really so different from the past?
  37. Monetary business cycle accounting for Sweden
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