Eatery, energy, environment and economic system, 1970-2017: Understanding volatility spillover patterns in a global sample

This paper explores the complex patterns of volatility transmissions among oil price, agricultural energy consumption, biofuel consumption, food production, greenhouse gas (GHG) emissions, and gross domestic product (GDP) per capita in a sample of 157 countries spanning the period 1970-2017. We employ a panel vector autoregressive model to construct time-varying volatility spillover indices. The main findings include the following: (i) On average, spillover effects account for about 20% of total volatility in the system in the sample period. (ii) Agricultural energy consumption is the dominant gross volatility emitter in this system, while GHG emissions are the dominant gross volatility receiver. (iii) Oil price fluctuation contributes approximately 43% to the total volatility in GDP per capita. We do not observe a strong link between agricultural emissions and GDP per capita in terms of volatility spillovers. Importantly, given the observed significant impact of oil price, energy consumption, and food production on changes in welfare, we conjecture that monitoring the interactions of these sectors is a policy priority.

Automated summary

Using a panel vector autoregressive model, this study explores the complex patterns of volatility transmissions among oil price, agricultural energy consumption, biofuel consumption, food production, greenhouse gas emissions, and GDP per capita in a sample of 157 countries. Agricultural energy consumption is found to be the dominant gross volatility emitter, while greenhouse gas emissions are the dominant gross volatility receiver. Monitoring the interactions among these sectors is crucial given their significant impact on welfare changes.