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The aggregated leapfrogging estimate: a novel approach to defining energy leapfrogging
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The aggregated leapfrogging estimate: a novel approach to defining energy leapfrogging
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Journal Article
The aggregated leapfrogging estimate: a novel approach to defining energy leapfrogging
2023
Overview
Energy leapfrogging (i.e., skipping non-renewable grid infrastructures to micro-grid renewable sources) has been promoted by researchers and politicians as a solution in fighting against climate change and for access to electricity in less developed countries. Despite research on its potential, quantitative measurement of leapfrogging is still required to determine those nations who have utilized energy leapfrogging's promise. In this study, we present a quantitative analysis using World Bank Open Database data from 2000 to 2015, creating an aggregated leapfrogging estimate (ALE) through renewable energy consumption (i.e., percentage of total energy consumption) and access to electricity (i.e., percent of total population with access). We defined the ALE by subtracting (renewable consumption % in 2000 / access to electricity % in 2015) from (renewable consumption % in 2015 / access to electricity in 2000). We included only countries whose renewable energy consumption increased during the study interval. Low-income countries collectively leapfrogged more than other income groups. Somalia (48.11), Togo (3.05), Eswatini (2.76), and Timor-Leste (1.04) all had ALE values greater than 1 (range: 1.7 × 10 −5 –48.11). We then conducted a policy analysis of these countries, confirming that all four had implemented renewable energy policies to create access to electricity. Our ALE accurately determined countries with energy leapfrogging, uniquely incorporating access to electricity, consistent with the fundamental purpose of leapfrogging as a strategy to increase access. Future studies are needed to understand why low-income countries with low ALEs and access to electricity failed to leapfrog in the past. Future studies are also required to design prospective quantitative statistical models predicting the outcomes of leapfrogging strategies.
Publisher
EDP Sciences
