World Food System Disruptions in the Early 2000s: Causes, Impacts, and Cures

2015

World Economy

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In addition to multilateral trade agreements under the World Trade Organization (WTO), the world has seen a remarkable proliferation of regional trade agreements (RTAs) in the last two decades. This study investigates whether these multilateral and regional trade institutions increase food trade and bring the world into a freer flow of food. The gravity model of international trade is used for the empirical analysis. The model is developed in a large panel data setting and attempted to address some potential problems in the estimations including multilateral trade resistances, zero trade values and endogeneity. The results suggest that both the WTO and RTAs have delivered significant positive effects on trade among the participant countries, but not food. Only RTAs are found to have increased food trade among the participant countries. However, although on average the WTO is found to have negative implications on food trade, it facilitates the developing countries more than the developed countries.

Section: Discussionmentioning

confidence: 99%

Do Trade Agreements Increase Food Trade?

Mujahid

2015

World Economy

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“…14 Figure 6 further illustrates that about 850 million poor people might be affected by price changes of US cereals futures contracts (140 million with transmission rates of 30 percent or higher) which is in particular relevant for the debate on speculation and financialization (Tadesse et al, 2013;von Braun et al, 2013). Transmission elasticities from commodity prices and price indices for countries with at least 1 million people below the poverty line are listed in Table 4 in the Appendix.…”

Section: Figure 5 Number and Extent Of Poor People Potentially Affecmentioning

confidence: 99%

How Strong Do Global Commodity Prices Influence Domestic Food Prices in Developing Countries? A Global Price Transmission and Vulnerability Mapping Analysis

2014

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractThis paper analyzes the transmission from global commodity to domestic food prices for a large set of countries. First, a theoretical model is developed to explain price transmission for different trade regimes. Drawing from the competitive storage model under rational expectations, it is shown that domestic prices can respond instantaneously to global prices even if no trade takes place but future trade is expected. Using a global database on food prices, we construct national and international grain price indices. With an autoregressive distributed lag model, we empirically detect countries in which food prices are influenced by global commodity prices, including futures prices. Mapping transmission elasticities with the size of the population below the poverty line which spends typically a large share of its income on food, we are able to estimate the size of vulnerable population. Our empirical analysis reveals that 90 percent of the global poor (income below 1.25$/day) live in countries where domestic food prices respond to international prices -but the extent of transmission varies substantially. For 360 million poor people, international prices transmit to their country at rates of 30 percent or higher within three months.

“…The impact of excessive speculation on forecast performance, though positive, is very small and almost negligable. Thus, the benefits of speculation found in our analysis have to be weighted against possible costs due to increased volatility or extreme price spikes (see von Braun et al 2014 for an overview).…”

Section: Discussionmentioning

confidence: 99%

Back to the Futures: An Assessment of Commodity Market Efficiency and Forecast Error Drivers

Algieri

2014

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractThe role of futures markets in stabilizing spot prices has been extensively discussed. Nevertheless, the ability of these markets to achieve the stabilizing function significantly depends on whether they are 'efficient' in the sense that futures prices 'fully reflect' the available information. The purpose of this study is first to gauge the extent to which futures markets for a set of traded commodities can be considered efficient in predicting spot prices. We then go beyond traditional analyses of efficiency and assess the relative forecasting performance of futures markets; i.e., the difference between the realization and prediction of future spot prices, and what factors affect these forecast errors. The results of the analysis show that maize, soybeans, and wheat markets are not informationally efficient, so that investors can make outsize profits. We find that short-term speculation, measured by the scalping index, increases the noises in the information formation process, thus increasing forecast errors. Conversely, long-term speculation, proxied by the Working-T index and the speculative pressure index, reduces forecast errors although their quantitative effect is negligible. Other relevant factors that drive forecast errors up are a high level of realized price volatility, the lack of liquidity in the market, and a longer contract maturity horizon.