Can Global Economic Policy Uncertainty Drive the Interdependence of Agricultural Commodity Prices? Evidence from Partial Wavelet Coherence Analysis

Abstract

This paper employed wavelet coherence and partial wavelet coherence to investigate the time-frequency effect of global economic policy uncertainty on the comovement of five agricultural commodities such as maize, oat, rice, soybean, and wheat using monthly data from January 1997 to December 2019. In general, we observed heterogeneity in comovement structures of the agricultural commodities market at different time-frequency scales which are profound at high frequencies from the bivariate wavelet coherence. The partial wavelet coherence analysis shows that global economic policy uncertainty is a driver of agricultural commodity market connectedness. This implies that extreme changes in economic policy uncertainty have the tendency to influence commodity price comovement. This poses risk to the stability of the agricultural commodities market, which requires the policymaker’s intervention to protect against the spillover risk contagion effect in uncertain times.

Oil and gold return spillover and stock market elasticity during COVID-19 pandemic: A comparative study between the stock markets of oil-exporting countries and oil-importing countries in the Middle East

“…It provides effective periodic signal detection and separation by balancing over time and frequency localization. Furthermore, it allows a better trade-off between identifying cycles and peaks or discontinuities ( Frimpong et al, 2021 ). Wavelet coherence uses a filter window “mother wavelet” to explain the information during the time which can be, calculated using the following equation: where (α and β) are respectively the scaling and translation coefficient belonging to a real number, and is the length of the mother wavelet ranging from −1 to 1.…”

On the Macroeconomic Conditions of West African Economies to External Uncertainty Shocks

“…The study examines the time-frequency comovement among country-specific macroeconomic variables using the vector wavelet and the degree of integration between the macroeconomic variables while considering the adverse impact of GEPU via the wavelet multiple. The relevance of using these techniques relates to the fact that financial time series experience rapid oscillations, exhibit asymmetric relationships and depict heterogeneous relationships (see, Owusu Junior et al 2018;Frimpong et al 2021;Asafo-Adjei et al 2021a, 2022a. Hence, other static models such as ordinary least squares regression and structural VAR, GARCH models, among others, would not be enough to reveal such dynamics.…”

“…The degree of interdependence between the series is represented by the surface colour and the colour palette. The red (warm) colour signifies parts that have major interactions, while the blue (cold) colour shows a lower series of correlations (Owusu Junior et al 2018;Frimpong et al 2021;Asafo-Adjei et al 2021a). The results outside the cone of influence are not significant since they are beyond the 95% confidence level.…”

“…Figure 6 presents the time-varying connectedness among country-level macroeconomic indicators in the midst of external shocks (GEPU). The GEPU is inculcated into the TVP-VAR estimations because the former was found to have a long-term impact on the dynamics of convergence as found by the prior literature (Frimpong et al 2021;Asafo-Adjei et al 2021b;Amoako et al 2022;Boateng et al 2022;etc.). It can be seen from Figure 6 that the degree of connectedness was strong prior to 2000.…”

“…The GEPU index encompasses a wide range of concerns, such as regulatory conflicts, income inequality disputes and global pricing swings to name a few, which occur around the world. As a result of the GEPU index's establishment, various empirical studies have been conducted (Huynh 2020;Asafo-Adjei et al 2020, 2021aFrimpong et al 2021;etc.). It has a significant impact on the fluctuations of macroeconomic fluctuations around the globe (Asafo-Adjei et al 2020, 2021bBoateng et al 2022;Asafo-Adjei et al 2022b).…”