Grain price and volatility transmission from international to domestic markets in developing countries
Abstract
Understanding the sources of domestic food price volatility in developing countries and the extent to which this volatility is transmitted from international to domestic markets is critical to help design better global, regional, and domestic policies to cope with excessive food price volatility and to protect the most vulnerable groups. This paper examines price and volatility transmission from major grain commodities to 41 domestic food products across 27 countries in Africa, Latin America, and South Asia. We follow a multivariate generalized auto-regressive conditional heteroskedasticity approach to model the dynamics of monthly price volatility in international and domestic markets. The period of analysis is 2000 through 2013. In terms of price transmission in levels, we observe only lead-lag relationships from international to domestic markets in few cases. To calculate volatility spillovers, we simulate a shock equivalent to a 1 percent increase in the conditional volatility of prices in the international market and evaluate its effect on the conditional volatility of prices in the domestic market. The transmission of price volatility is statistically significant in just one-quarter of the maize markets tested, almost half of rice markets tested, and all wheat markets tested. Volatility transmission seems to be more common when trade (imports or exports) is large relative to domestic requirements.Non-PRIFPRI1; C Improving markets and trade; CRP2MTID; PIMCGIAR Research Program on Policies, Institutions, and Markets (PIM- Discussion paper
- Discussion paper
- prices; markets; models; commodities
- volatility transmission; price transmission; grain commodity prices; domestic markets; multivariate generalized autoregressive conditional heteroskedasticity (MGARCH)
- Q11 Agriculture: Aggregate Supply and Demand Analysis, Prices; C32 Multiple or Simultaneous Equation Models: Time-Series Models, Dynamic Quantile Regressions