Becker, Torbjorn, Olivier Jeanne, Paolo Mauro, and Romain Rancière, 2007, “Country Insurance: The Role of Domestic Policies,” Occasional Paper No. 254, IMF.
Bems, Rudolfs, and Irineu de Carvalho Filho, 2009, “Current Account and Precautionary Savings for Exporters of Exhaustible Resources,” IMF Working Paper 09/33.
Caballero, Ricardo J., and Stavros Panageas, 2008, “Hedging Sudden Stops and Precautionary Contractions,” Journal of Development Economics, Vol. 85, pp. 28-57.
Campbell, Patrick, Bjorn-Erik Orskaug, and Richard Williams, 2006, “The Forward Market for Oil,” Bank of England Quarterly Bulletin, pp. 66-74.
Carroll, Christopher D., 2006, “The Method of Endogenous Gridpoints for Solving Dynamic Stochastic Optmization Problems,” Economic Letters, pp. 312-320.
Cashin, Paul, Hong Liang, and C. John McDermott, 2000, “How Persistent Are Shocks to World Commodity Prices?,” IMF Staff Papers, Vol. 47, No. 2, pp. 177 - 217.
Durdu, Ceyhun Bora, Enrique G. Mendoza, and Marco E. Terrones, 2009, “Precautionary Demand for Foreign Assets in Sudden Stop Economies: an Assessment of the New Merchantilism,” Journal of Development Economics, Vol. 89, pp. 194 - 209.
Ghosh, Atish R., and Jonathan D. Ostry, 1997, “Macroeconomic Uncertainty, Precautionary Saving and the Current Account,” Journal of Monetary Economics, Vol. 40, No. 1, pp. 121-139.
Grossman, Herschel, and John Van Huyck, 1988, “Sovereign Debt as a Contingent Claim: Excusable Default, Repudiation, and Reputation,” American Economic Review, Vol. 78, No. 5, pp. 1088-97.
Pagano, Patrizio, and Massimiliano Pisani, 2009, “Risk-Adjusted Forecasts of Oil Prices,” European Central Bank Working Paper No.999.
Pallage, Stephane, and Michel A. Robe, 2003, “On the Welfare Cost of Business Cycles in Developing Countries,” International Economic Review, Vol. 44, No. 2, pp. 677-98.
Powell, Andrew, 1989, “The Management of Risk in Developing Country Finance,” Oxford Review of Economic Policy, Vol. 5, No. 4, pp. 69-87.
Appendix I. Commodity Price Data
Appendix II. Model with heding
Appendix III. Notes on numerical solution
Appendix IV. Maximum Likelihood Estimation
We would like to thank seminar participants at a NBER workshop, the Bank of Canada and the International Monetary Fund for useful comments. The views expressed in the paper are those of the authors and do not necessarily represent those of the Inter-American Development Bank or the International Monetary Fund.
Commodity export data are from UN COMTRADE retrieved though World Integrated Trade Solution (WITS). We use the IMF Commodity Unit product aggregates based on the SITC3 classification. GDP data are from the World Bank World Development Indicators database. We consider countries with at least 3 data points over 2002-2007.
Standard deviations are computed with data from the countries listed in Table 1, starting from the first year at which X/Y > 5 percent. The table reports the standard deviations of the log of commodity export and non-commodity income detrended with a time trend. The standard deviations by commodities are obtained as the simple average of country volatilities.
The risk premium is computed as the average ex-post forecast error over the sample period.
Lower risk premia are generally found using a longer time sample (Pagano and Pisani (2009)). Over the last five years oil prices have been mostly rising and therefore part of the gap between spot and futures prices can be due to a peso effect. Note that the limited availability of long-term contracts does not preclude long-term hedging, which can be partially achieved by rolling forward short-maturity contracts.
Similar sizes of open interest position in futures relative to world production are also reported in the World Economic Outlook (2007, April) for natural gas, copper, corn, and soybeans.
We underestimate the extent of hedging by leaving aside over-the-counter transactions (Campbell, Orskaug and Williams (2006)). However, open interest positions overestimate hedging by including contracts underwritten by speculators without a direct exposure to oil prices. The U.S. Commodity Futures Trading Commission reports that around 30 percent of the open interest positions on the NYMEX are held by speculators, and this share is likely to be higher on the ICE market which is subject to less stringent regulation.
We do not use an AR1 in levels to rule out negative prices. We also prefer to avoid working with an AR1 in logs, which complicates the computation of conditional expectations and the pricing of futures contracts.
We allow for default in section V.B in order to assess its potential as an alternative insurance mechanism.
This condition is sufficient if ρ < 1. A stronger restriction is required if ρ = 1.
Formally the target is defined as the level of bt at which Etbt+1 = bt. For a formal proof of the existence of this target see Carroll (2008).
The difference between futures and forward contracts is that the former are traded in an organized market. The structure of the market does not matter for our results so that we will refer to the hedging instruments indifferently as futures or forward contracts.
With positive finite risk premiums, we must solve for the share of production that the country wants to sell forward at each available maturity, thus enlarging the choice set. The state space would become much larger due to the need of keeping track of the share of production in each future year that has already been sold forward.
Consider for example the case in which the country wants to secure at time t the price at t + 2 of q commodity units. If two-year futures are available, the country could lock export revenues of q(p + ρ2(pt − p)). The same result can be obtained by using one-year futures. By selling one year forward qρ/R and q units at time t and t + 1 respectively, the country would secure revenues of (qρ/R)(p + ρ(pt − p) − pt+1)R + q(p + ρ(pt+1 − p)) at time t + 2, equal to q(p + p2(pt–p)).
The country’s borrowing capacity is determined by the minimum level of export income because of the assumptions that only export income is pledgeable and that debt is default-free.
We could also obtain an unconditional measure of the welfare gain by taking the average of αf over a large number of realizations of the states.
Pallage and Robe (2003) have found business cycle fluctuations to be more costly in developing countries than in advanced ones because their economies are more volatile.
The consumption functions are solved in the (wt, pt) state space. Figure 4 shows the consumption function assuming that the commodity price is equal to its average, p.
Indeed, our model can be interpreted as one with overlapping generations and perfectly altruistic (but impatient) parents. It is perfectly equivalent to assume that individuals are infinitely-lived or that they care about their offsprings as much as about themselves.
The option price ξθ(pt) is computed numerically using Monte Carlo simulations.
The options become equivalent to futures as the strike price goes to infinity.
The country could insure itself perfectly by issuing liabilities that are contingent on the commodity price. There is a line of literature on sovereign debt that views default as a way of approximating the optimal state contingency (see, e.g., Grossman and Van Huyck (1988).
These results, however, clearly depend on the parameters of the model and in particular on the impatience factor. With a lower discount factor or growth rate, the country’s desire to borrow against future income decreases and the relative importance of reducing the volatility of income increases. Therefore, a higher ζ with more frequent default becomes more appealing.