Commodity Price Volatility And The Sources Of Growth

This paper studies the impact of the level and volatility of the commodity terms of trade on economic growth, as well as on the three main growth channels: total factor productivity, physical capital accumulation, and human capital acquisition. We use the standard system GMM approach as well as a cross-sectionally augmented version of the pooled mean group (CPMG) methodology of Pesaran et al. (1999) for estimation. The latter takes account of cross-country heterogeneity and cross-sectional dependence, while the former controls for biases associated with simultaneity and unobserved country-specific effects. Using both annual data for 1970-2007 and five-year non-overlapping observations, we find that while commodity terms of trade growth enhances real output per capita, volatility exerts a negative impact on economic growth operating mainly through lower accumulation of physical capital. Our results indicate that the negative growth effects of commodity terms of trade volatility offset the positive impact of commodity booms; and export diversification of primary commodity abundant countries contribute to faster growth. Therefore, we argue that volatility, rather than abundance per se, drives the "resource curse" paradox.

Commodity prices have declined sharply over the past three years, and output growth has slowed considerably among countries that are net exporters of commodities. A critical question for policy makers in these economies is whether commodity windfalls influence potential output. Our analysis suggests that both actual and potential output move together with commodity terms of trade, but that actual output comoves twice as strongly as potential output. The weak commodity price outlook is estimated to subtract 1 to 21⁄4 percentage points from actual output growth annually on average during 2015-17. The forecast drag on potential output is about one-third of that for actual output.

"The conference was organized by the three editors of this book and took place on August 15-16, 2012 in Seattle."--Preface.

This paper studies the impact of the level and volatility of the commodity terms of trade on economic growth, as well as on the three main growth channels: total factor productivity, physical capital accumulation, and human capital acquisition. We use the standard system GMM approach as well as a cross-sectionally augmented version of the pooled mean group (CPMG) methodology of Pesaran et al. (1999) for estimation. The latter takes account of cross-country heterogeneity and cross-sectional dependence, while the former controls for biases associated with simultaneity and unobserved country-specific effects. Using both annual data for 1970-2007 and five-year non-overlapping observations, we find that while commodity terms of trade growth enhances real output per capita, volatility exerts a negative impact on economic growth operating mainly through lower accumulation of physical capital. Our results indicate that the negative growth effects of commodity terms of trade volatility offset the positive impact of commodity booms; and export diversification of primary commodity abundant countries contribute to faster growth. Therefore, we argue that volatility, rather than abundance per se, drives the "resource curse" paradox.

This paper studies the volatility of commodity prices on the basis of a large dataset of monthly prices observed in international trade data from the United States over the period 2002 to 2011. The conventional wisdom in academia and policy circles is that primary commodity prices are more volatile than those of manufactured products, even though most of the existing evidence does not actually attempt to measure the volatility of prices of individual goods or commodities. Rather the literature tends to focus on trends in the evolution and volatility of ratios of price indexes composed of multiple commodities and products. This approach can be misleading. Indeed, the evidence presented in this paper suggests that on average prices of individual primary commodities may be less volatile than those of individual manufactured goods.

This book provides fresh insights into concepts, methods and new research findings on the causes of excessive food price volatility. It also discusses the implications for food security and policy responses to mitigate excessive volatility. The approaches applied by the contributors range from on-the-ground surveys, to panel econometrics and innovative high-frequency time series analysis as well as computational economics methods. It offers policy analysts and decision-makers guidance on dealing with extreme volatility.

We develop an empirical model to predict banking crises in a sample of 60 low-income countries (LICs) over the 1981-2015 period. Given the recent emergence of financial sector stress associated with low commodity prices in several LICs, we assign price movements in primary commodities a key role in our model. Accounting for changes in commodity prices significantly increases the predictive power of the model. The commodity price effect is economically substantial and robust to the inclusion of a wide array of potential drivers of banking crises. We confirm that net capital inflows increase the likelihood of a crisis; however, in contrast to recent findings for advanced and emerging economies, credit growth and capital flow surges play no significant role in predicting banking crises in LICs.

There is a common perception that the prices of unrelated commodities move together. This paper re-examines this notion, using a measure of comovement of economic time series called concordance. Concordance measures the proportion of time that the prices of two commodities are concurrently in the same boom period or same slump period. Using data on the prices of several unrelated commodities, the paper finds no evidence of comovement in commodity prices. The results carry an important policy implication, as the study provides no support for earlier claims of irrational trading behavior by participants in world commodity markets.