Abstract
This paper quantifies the rising global dynamic, interconnected relationship between energy and water commodities. Over the last decade, increased international concern has emerged about the water-energy nexus. However, recent research still lacks a quantified understanding of the role of water within a financial-economic view of the nexus. The complexity of commodity markets contributes to this lack of understanding. These markets consist of a wide variety of participants having different objectives, resulting in non-stationary time series. Wavelets are mathematical functions that detect common time-localized oscillations in non-stationary time series. The novelty of our analysis lies in applying wavelet techniques to better quantify the financial implications and understand opportunities of the dynamic relationship that exists in the water-energy nexus. Using daily water and energy commodity ETF price data from 2007 to 2017 we deconstruct each of the time series into different horizon components and evaluate their respective wavelet transforms. Comparing the wavelet squared coherence (WSC) and the windowed scalogram difference (WSD) allows us to specify nexus similarities and differences. We further analyze the wavelet local multiple correlations (WLMC) by including S&P500 ETF price data to conditionally eliminate market effects. Previous studies heavily focused on the qualitative relationships between water and energy. Whereas the analysis in this paper, to the best of our knowledge, is the first to confirm the time-varying relationship in a quantitative manner. The most significant financial-economic result from our analysis is that water prices, at certain time horizons, lead energy prices during specific localized economic events.
Highlights
In trying to understand the extremely volatile price dynamics after the 2008 financial crisis, economic researchers introduced the concept of commodity financialization (Cheng and Xiong, 2013), giving rise to energy finance becoming a standalone stream of research
Vacha and Barunik (2012) pointed out that energy commodities affect a wide range of markets and that it is fundamentally important to Wavelet-Based Applications: The Water-Energy Nexus study the statistical properties and interconnections of these markets
The addition of SPY is to explore the dynamic interaction of XLE and CGW or the water-energy nexus with respect to the S&P500 Index
Summary
In trying to understand the extremely volatile price dynamics after the 2008 financial crisis, economic researchers introduced the concept of commodity financialization (Cheng and Xiong, 2013), giving rise to energy finance becoming a standalone stream of research. Zhang (2018) further clarified the concept of energy finance by discussing the fields interdisciplinary nature and emphasizing the need for analyzing linkages between energy commodity markets and other markets to better understand price dynamics. Vacha and Barunik (2012) pointed out that energy commodities affect a wide range of markets and that it is fundamentally important to Wavelet-Based Applications: The Water-Energy Nexus study the statistical properties and interconnections of these markets. Publications ranging from policy implications to the econometric quantification are supporting the increased need for evaluating the water-energy nexus. Studies that impact policy include the integrated risk analysis of the water-energy nexus with reasonable policy recommendations by Cai et al (2019), evaluations of water-related impacts due to energy-related decisions by Wang et al (2019), and a detailed review of existing methods and tools to analyze the water-energy nexus by Dai et al (2018). Ozturk (2017) goes even further by evaluating the dynamic relationship between food-water-energy and agricultural sustainability in sub-Saharan countries, as well as in earlier work examining countries that make up BRICS (Ozturk, 2015)
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