The impact of commodity price shocks among regional economies of a developing country

Volatile commodity prices have become commonplace in the world economy. Although is widely accepted that commodity‐rich countries are affected by this phenomenon, information about how commodity price shocks impacts their regional economies is scarce. This work analyses how shocks in copper prices impact the economies of the major copper‐producing regions in a developing country, such as Chile. To achieve this goal, a two‐step method is implemented. First, we estimate long‐term copper prices using the Wets and Rios approach (2015) and these estimates are then contrasted with those forecast by the Chilean public advisory committee. Second, a general equilibrium model is implemented to simulate the effects of both expansive and restrictive copper price cycles within major producing regions in Chile. Our results show that the proposed approach yields more homogeneous price projections than those made by the Chilean Government, which, in turn, are very close to variations in response to negative shocks. The price simulations confirm that price cycles affect the savings of government and business, which directly dampens regional production, mainly via investment, capital mobilisation and diversification of production. Because of this, fiscal revenues generated by copper sales act as a trade cycle term multiplier in regional economies. Overall, within copper‐producing regions, we suggest implementing long‐term policies to improve profit distribution efficiency.     

Measuring producer welfare under output price uncertainty and risk non-neutrality

Procedures to measure the producer welfare effects of changes in an output price distribution under uncertainty are reviewed. Theory and numerical integration methods are combined to show how for any form of Marshallian risk-responsive supply, compensating variation of a change in higher moments of an output price distribution can be derived numerically. The numerical procedure enables measurement of producer welfare effects in the many circumstances in which risk and uncertainty are important elements. The practical ease and potential usefulness of the procedure is illustrated by measuring the producer welfare effects of USA rice policy.     

Measuring price discovery between nearby and deferred contracts in storable and nonstorable commodity futures markets

Using price discovery measures, including Putniņš’ (2013) information leadership share and intraday data, we quantify the proportional contribution of nearby and deferred contracts in price discovery in the corn and live cattle futures markets. On average, nearby contracts reflect information more quickly than deferred contracts in the corn market, but have a relatively less dominant role in the live cattle market. In both markets, the nearby contract loses dominance when its relative volume share dips below 50%, which typically occurs when the nearby is close to maturity. Regression results indicate that the share of price discovery is mainly related to trading volume and time to expiration in both markets. In the corn market, price discovery share between nearby and deferred contracts is also related to inverse carrying charges, crop year differences, USDA announcements, market crashes, and commodity index position rolls. Differences between corn and live cattle markets are consistent with differences in the contracts’ liquidity and commodity storability.     

Predictive performance of the World Bank's commodity price projections

The World Bank's commodity price projections are widely used for various planning purposes. Two aspects of the Bank's projections of relative prices are studied in this paper. The first is whether the forecasts make efficient use of the information available at the time the forecast is made. The second is whether the forecasts predict future prices with greater accuracy than alternative forecasting methods. These matters are studied by comparing the World Bank's past price projections with the actual prices that were subsequently observed. The results show that, overall, the World Bank forecasts do not pass either test. First, the World Bank forecasts are informationally inefficient. Prediction error (projection minus actual price) tends to be positively correlated with the projections themselves. Although the direction of future price movements tends to be correctly predicted, the magnitude of these movements tends to be overpredicted. Second, the World Bank forecasts do not perform well even compared with the simplest of alternative forecasting methods - the prediction of no change.     

Modeling regime‐dependent agricultural commodity price volatilities

In stark contrast to financial markets, relatively little attention has been given to modeling agricultural commodity price volatility. In recent years, numerous methodologies with various strengths have been proposed for modeling price volatility in financial markets. We propose using a mixture of normals with unique GARCH processes in each component for modeling agricultural commodity prices. While a normal mixture model is quite flexible and allows for time varying skewness and kurtosis, its biggest strength is that each component can be viewed as a different market regime and thus estimated parameters are more readily interpreted. We apply the proposed model to ten different agricultural commodity weekly cash prices. Both in‐sample fit and out‐of‐sample forecasting tests confirm that the two‐state NM‐GARCH approach performs better than the traditional normal GARCH model. A significant and state‐dependent inverse leverage effect is detected only for pork in the regime where the price is expected to drop, indicating the volatility in this regime tends to increase more following a realized price rise than a realized price drop.     

Extent and possible causes of intrayear agricultural commodity price volatility

Wheat, corn, rice, soybeans, and cotton experienced higher volatility in the second half of the 2000s. For the sample at hand, the unit root tests only validate a new period of high volatility for wheat and cotton. If in the next couple of years however, corn, rice and soybeans maintain their higher volatility, a new period of high volatility may also be validated statistically. Regarding the factors driving the intrayear volatility GMM estimates show that “commodity market fundamentals” i.e., the stock‐to‐use ratio and to a lesser extent the degree of internationalization, are the most systematically statistically significant coefficients among commodities. Over time, consecutive low stock‐to‐use ratios and a thin international market provoke typically high volatility. Speculative activity and liquidity in the agricultural derivative market have a stabilizing effect on the spot price, if any. Finally, “common macro” factors significantly impact volatility, especially the volatility of petrol and of exchange rates; their dispersion importance over the sample is quite sizeable. However, it is difficult to establish a link between, on the one hand, loose monetary policy, business cycle and inflation, and, on the other hand, commodity price volatility, as the sign of the estimated coefficient changes depending on the commodity and the estimated elasticities are quite low.     

Use of composite forest commodity price indices for cointegration analysis

Time series data on forest product prices used in research is frequently the product of temporal, spatial as well as product aggregation. This paper analyzes the implications of the use of composite commodity price indices in cointegration analysis and tests the validity of the assumptions underlying it. It tests for the presence of a common stochastic trend in disaggregated softwood lumber product price series in multiple US markets, a validity condition supported by the Generalized Composite Commodity Theorem (Lewbel, 1996. Aggregation without separability: a generalized composite commodity theorem. The American Economic Review 86(3), 524–543.). The presence of a common stochastic trend in softwood lumber product price series tested is consistently rejected by Johansen's (1988. Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control 12(2–3), 231–254.) multivariate cointegration analysis. Together with rejection of non-stationarity property for a significantly large number of price series tested, the results highlight the significance of the assumptions underlying the use of composite forest commodity price indices for cointegration analysis.     

The use of organized commodity markets to manage food import price instability and risk

The article explores the possibility of insuring the price risks of wheat and maize imports of low‐income food‐deficit countries (LIFDCs). Optimal strategies for an importing agent, who hedges with futures and options are derived, based on the objective of minimizing the unpredictability of import bills. Ex post simulations for a set of LIFDCs are run on wheat and maize imports hedged with futures and options in the Chicago Board of Trade, to explore the extent to which hedging reduces the unpredictability in import bills. Simulations encompass both periods of normal price behavior, as well as the period of global upheaval that occurred in 2007 and 2008. Results show that hedging with futures alone affords agents considerable opportunities for reducing import cost unpredictability, and the same holds with options, albeit, to a lesser extent. However, during the recent price spike of 2007–2008, hedging with options would have increased the unpredictability of some countries’ maize import bills, due to the combination of erratic import patterns and pronounced market uncertainty.     

Macroeconomic impacts of export commodity price subsidy in Papua New Guinea

A macroeconometric simulation study is undertaken to evaluate the impacts of a price subsidy for tree crops in Papua New Guinea (PNG). The price subsidy had favourable impacts on tree crop export income, aggregate demand, private consumption, and investment and employment. It increased imports, the budget deficit, and the demand for money and adversely affected the fiscal balance, inflation and interest rates, the BOP position and macroeconomic stability. The price subsidy contributed favourably to internal balance but adversely affected external balance. It worked against many of the policy objectives and made macroeconomic management difficult. With the introduction of the price subsidy, the government violated the commitments made under the Uruguay Round Agreement on Agriculture and PNG's Structural Adjustment Program.     

A simple model of endogenous agricultural commodity price fluctuations with storage

A debate has been raging for centuries regarding the effects of interannual storage on commodity prices. Most analysts consider storage to function as a price stabilizer, while others place it at the core of an explanation of intriguing features of commodity price series, such as skewed distributions. Most studies have been developed in the context of the theory of competitive storage where random shocks affect supply or demand. Recently, the endogenous chaotic behavior of markets has become another possible hypothesis regarding the origin of commodity price fluctuations. We develop a nonlinear cobweb model with intra‐ and interannual storage, risk averse agents, and adaptive expectations. Like the theory of competitive storage, this nonlinear cobweb model with storage can reproduce some of the stylized facts of agricultural commodity prices (autocorrelation of first rank, low kurtosis, and skewness). In addition, the effects of storage on price variation are mixed. In the presence of interannual storage, chaotic price series show less variation compared to a situation without interannual storage but we find that storage contributes to the endogenous volatility of prices by making chaotic dynamics more likely.     

Measuring farm productivity under production uncertainty

This research introduces a novel empirical application to the assessment of farm productivity growth. While the existing research on productivity change has primarily focussed on ex post output observations, it has been shown that ignoring production uncertainty can lead to unreliable results. Using a state-contingent framework to represent the stochastic production environment, we extend the recent line of research that merged the state-contingent approach and efficiency measurement to productivity change using the Malmquist and Luenberger productivity indices. Using a balanced panel of 117 arable crop farms surveyed in 2011 and 2015, we show through the study results that productivity decreased, with technological regress being the major source of productivity change. Differences in productivity change between nonstochastic and stochastic modelling show the relevance to consider the state-contingent framework when assessing farms' productivity.     

Nontraded food commodity spatial price transmission: evidence from the Niger millet market

Using an Augmented Factor Vector Autoregressive (FAVAR) Model, this study analyzes spatial millet prices transmission in Niger. Our results did not find condition for millet markets integration existence. However, the Granger causality tests and impulse response functions from the estimated short‐term dynamic as FAVAR model revealed the existence of leading markets whose millet prices affect a maximum number of other regional millet prices, while some regions seem to be isolated from trade or information flows. Furthermore, the significance of a shock depends also on the characteristics of the region where it originates in terms of millet demand or supply, indicating that the region to target and where the price shock originated matter for the policies’ success.     

Food commodity price changes and consumer welfare in Bangladesh: Valuable lessons for today

The recent rise in global food prices threatens many countries worldwide, especially the vulnerable populations. Viable coping strategies can only be designed based on the important policy lessons learned from the experiences of these countries in confronting the similar shocks of 2007–2011. However, the disproportionate effects of these events and the impacts of policy responses remain largely unexplored. We examine the impact of a food price surge and the effectiveness of various mitigating policies in Bangladesh, one of the most populous, densely populated countries in the world that is plagued by poverty. Specifically, we combine individual-level expenditure survey data with recent advances in consumer theory to examine the welfare consequences across income groups and geographic areas of the country over 2000–2016. Our empirical findings lend support to the hypothesis that the brunt of the price surge was borne by relatively less affluent and rural households, and government poverty alleviation programmes were largely ineffective.     

How much of commodity price behavior can a rational expectations storage model explain?

A rational expectations competitive storage model was applied to the U.S. corn market, to assess the aptness of this framework in explaining monthly price behavior in an actual commodity market. Relative to previous models, extensive realism was added to the model, in terms of how production activities and storage costs are specified. By modeling convenience yield, “backwardation” in prices between crop years did not depend on the unrealistic assumption of zero ending stocks. Our model generated cash prices that were distributed with positive skewness and kurtosis, and mean and variance that increased over the storage season, comparable to the persistence and the occasional spikes observed in commodity prices. Futures prices were generated as conditional expectations of cash prices at contract maturity, and the variances of futures prices exhibited realistic time–to‐maturity and seasonal patterns. Model realizations of cash and futures prices over many “years” were used to demonstrate the wide variety of price behaviors that could be observed in an efficient market with a similar market structure, implying that economic and policy implications drawn from short, historical samples of prices could be misleading.     

Management flexibility,price uncertainty and the adoption of carbon forestry

A price on carbon has the potential to drive significant land use change through reforestation. Understanding the likely locations and extent of these changes is therefore a key focus for researchers and policy makers. Models of reforestation based on net present values (NPV) typically compare the economic returns of carbon forestry to alternative land uses. However, these models often neglect the impact of uncertainty. Two sources of uncertainty highly relevant to carbon forestry are the opportunity cost of the land on which the trees are established (i.e. future returns from alternative land uses) and carbon prices. In addition to foregoing the current land use, a landowner making a permanent land use change such as carbon forestry is also giving up the opportunity to change management in the future, for example by changing crop mix in response to commodity price changes. We develop a Monte Carlo model to demonstrate the value of management flexibility, based on a case study property in Australia. While in the absence of management flexibility carbon forestry is more profitable than the current land use, under uncertain future commodity prices it is less attractive to a landowner. We go on to show that, even if the returns from carbon exceed those from more flexible agricultural land use, uncertainty over future carbon prices is likely to delay the adoption of carbon forestry. Overall the models presented in this paper demonstrate that the adoption of carbon forestry is likely to be substantially lower, and slower, than models based on static values would suggest.     

The impact of water price uncertainty on the adoption of precision irrigation systems

We examine whether a firm is more or less likely to adopt precision technology when input prices are stochastic. The results are important to determining whether programs and contracts that reduce input price uncertainty may deter the adoption of conservation practices. An economic model of the technology adoption decision shows that the net effect of input price risk is ambiguous and depends on several factors including the shutdown effect, the mean price effect, the precision expansion effect, and the risk aversion effect. An empirical implementation of the model relies on data on water price and irrigation technology adoption observed in a California irrigation district over the period 1999–2002. The results show that a stable input price increases the adoption of precision technology, but the impact depends on crop choice and land quality characteristics.