Do biofuel production and financial speculation in agricultural commodities influence African food prices? New evidence from a TVP-VAR extended joint connectedness approach

Guo, Jin; Tanaka, Tetsuji

doi:10.1016/j.eneco.2022.106422

Cited by 23 publications

(5 citation statements)

References 53 publications

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“…Furthermore, the food price index is an important standard economic indicator that gives an overview of the situation of food security in a nation using the rate of changes in food prices over time, which has been very useful in several high-impact studies on related topics [50]. Therefore, it will help us to evaluate or reveal the situation of food price stability in different clusters.…”

Section: Methodsmentioning

confidence: 99%

Trends and Characterization of Primary Energy Sources by Energy and Food Prices

et al. 2023

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This study introduces the most important energy trends and global food systems, as well as the relationship between the human development index (HDI) and energy supply and the relationship between energy prices and food prices. Based on seven important indicators as variables in 18 relevant countries worldwide, before and after the pandemic, with the help of cluster analysis and comparative analysis, five different primary energy clusters were created and analyzed. Our results prove the high volatility of the composition of these clusters within a short period. Another important finding is that renewable energy sources (RES) are probably not viable options for the largest (developed and developing) countries in the short term. The human development index and food production per capita are the lowest in the renewable energy cluster and the highest in countries dominated by nuclear energy and oil with typically the highest GDP, since they are able to finance the price hike in both food and energy markets. Generally, it can be stated that although there is a relationship between the measured indicators, it is not constant in all cases. Our results and methodology may be a good basis for further research to examine the relationship between the most important relevant indicators in different countries, as well as the effect of a global crisis on strengthening food and energy security.

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Section: Methodsmentioning

confidence: 99%

Trends and Characterization of Primary Energy Sources by Energy and Food Prices

et al. 2023

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“…To investigate the relationship among the examined indicators, a Vector Auto-Regression (VAR) model is employed, a commonly used method in the literature for similar data series (Guo and Tanaka 2022;Umar et al 2021;Abbas and Lan 2020). The VAR methodology allows for bidirectional influence among the variables in the model and incorporates the influence of lags on the current value (Hyndman and Athanasopoulos 2021).…”

Section: Vector Auto Regression Analysis-grange Causality Testmentioning

confidence: 99%

Resource Price Interconnections and the Impact of Geopolitical Shocks Using Granger Causality: A Case Study of Ukraine–Russia Unrest

Kostaridou,

Siatis,

Zafeiriou

2024

JRFM

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Political events significantly impact economic indices, including agricultural commodities. While Granger causality is a well-established method for analyzing interdependencies between time series data, its traditional application can be challenging to interpret across multiple periods. This research enhances the Granger causality method to quantify changes in the interlinkages among variables over time, offering a more intuitive framework for analyzing how political events affect economic indices. The proposed method involves conducting Granger causality tests across different periods, forming vectors from the results to capture transitions from Granger-causing to non-Granger-causing variables. These vector amplitudes provide quantitative measures of changes with explanatory power over time. The dataset includes eight variables over a decade, focusing on the following major geopolitical events: the Russian occupation of Crimea in 2014 and the invasion of Ukraine in 2022, with an intermediate “no-shocks” period as the reference. The results show significant changes in the interlinkages among the variables during crisis periods compared to stable periods. This enhanced method provides valuable insights, informing trading strategies and risk management during periods of geopolitical instability. This innovative approach offers a novel tool for market participants to better understand and respond to economic shocks caused by political events.

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“…Increased demand for bioenergy feedstocks, such as corn, soybeans, and sugarcane, can lead to higher prices and price volatility in agricultural markets, particularly in regions with significant biofuel production capacity. However, the extent of price effects depends on factors such as policy incentives, technological advancements, and market integration (Abreu et al, 2022;Calvin et al, 2021;Guo & Tanaka, 2022).  Changes in Land Use Decisions: The expansion of bioenergy production has significant implications for land use decisions, with potential trade-offs between bioenergy development and food security, environmental conservation, and rural livelihoods.…”

Section: Integration and Synthesis Of Reviewed Literaturementioning

confidence: 99%

Systematic review of the economic impacts of bioenergy on agricultural markets

Jephta Mensah Kwakye,

Darlington Eze Ekechukwu,

Olorunshogo Benjamin Ogundipe

2024

Int. j. adv. economics

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This systematic review examines the economic impacts of bioenergy on agricultural markets, synthesising findings from existing literature across various regions and climatic conditions. Analysing effects on crop prices, land use decisions, and economic sustainability, the review highlights key insights. It identifies common trends, patterns, and divergences. Bioenergy production interacts with agricultural markets through multiple channels, influenced by policy interventions, technological innovation, and market dynamics. Implications for policy, practice, and future research are discussed, emphasising the importance of considering economic factors in bioenergy development and agricultural policy-making. The findings underscore the need for integrated modeling approaches, data improvements, and cross-sectoral collaboration to inform evidence-based decision-making and promote sustainable bioenergy development. Keywords: Bioenergy, Agricultural Markets, Economic Impacts, Crop Prices, Land Use Decisions, Sustainability.

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Do biofuel production and financial speculation in agricultural commodities influence African food prices? New evidence from a TVP-VAR extended joint connectedness approach

Cited by 23 publications

References 53 publications

Trends and Characterization of Primary Energy Sources by Energy and Food Prices

Trends and Characterization of Primary Energy Sources by Energy and Food Prices

Resource Price Interconnections and the Impact of Geopolitical Shocks Using Granger Causality: A Case Study of Ukraine–Russia Unrest

Systematic review of the economic impacts of bioenergy on agricultural markets

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