Scenarios of Systemic Transitions in Energy and Economy

For the energy economics sector, earlier forecasting approaches (e.g., a Kaya identity or a double-logarithmic function) proved too simplistic. It is becoming necessary to systemically include the emergence of new discrete evolutionary changes. This paper provides a novel quantitative forecasting m...

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Main Author: Gilbert Ahamer
Format: Article
Language:English
Published: National Research University Higher School of Economics 2022-09-01
Series:Foresight and STI Governance
Subjects:
Online Access:https://foresight-journal.hse.ru/article/view/19163
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author Gilbert Ahamer
author_facet Gilbert Ahamer
author_sort Gilbert Ahamer
collection DOAJ
description For the energy economics sector, earlier forecasting approaches (e.g., a Kaya identity or a double-logarithmic function) proved too simplistic. It is becoming necessary to systemically include the emergence of new discrete evolutionary changes. This paper provides a novel quantitative forecasting method which relies on the Global Change Data Base (GCDB). It allows for the generation and testing of hypotheses on future scenarios for energy, economy, and land use on a global and country level. The GCDB method envisages systemic variables, especially quotients (such as energy intensity), shares (such as GDP shares, energy mix), and growth rates including their change rates. Thus, the non-linear features of evolutionary developments become quantitatively visible and can be corroborated by plots of large bundles of time-series data. For the energy industry, the forecasting of sectoral GDP, fuel shares, energy intensities, and their respective dynamic development can be undertaken using the GCDB method.
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spelling doaj-art-42d8a3d11efd475491f57d2b71aa47f32025-08-20T02:26:06ZengNational Research University Higher School of EconomicsForesight and STI Governance2500-25972022-09-0116310.17323/2500-2597.2022.3.17.34Scenarios of Systemic Transitions in Energy and EconomyGilbert Ahamer0Environment Agency Austria, Spittelauer Lände 5, 1090 Vienna, Austria; Institute for Economic History at the Graz University, Brandhofgasse 5, 8010 Graz, Austria For the energy economics sector, earlier forecasting approaches (e.g., a Kaya identity or a double-logarithmic function) proved too simplistic. It is becoming necessary to systemically include the emergence of new discrete evolutionary changes. This paper provides a novel quantitative forecasting method which relies on the Global Change Data Base (GCDB). It allows for the generation and testing of hypotheses on future scenarios for energy, economy, and land use on a global and country level. The GCDB method envisages systemic variables, especially quotients (such as energy intensity), shares (such as GDP shares, energy mix), and growth rates including their change rates. Thus, the non-linear features of evolutionary developments become quantitatively visible and can be corroborated by plots of large bundles of time-series data. For the energy industry, the forecasting of sectoral GDP, fuel shares, energy intensities, and their respective dynamic development can be undertaken using the GCDB method. https://foresight-journal.hse.ru/article/view/19163scenariosenergy foresightglobal modellingGlobal Change Data Basetrends extrapolationland use change
spellingShingle Gilbert Ahamer
Scenarios of Systemic Transitions in Energy and Economy
Foresight and STI Governance
scenarios
energy foresight
global modelling
Global Change Data Base
trends extrapolation
land use change
title Scenarios of Systemic Transitions in Energy and Economy
title_full Scenarios of Systemic Transitions in Energy and Economy
title_fullStr Scenarios of Systemic Transitions in Energy and Economy
title_full_unstemmed Scenarios of Systemic Transitions in Energy and Economy
title_short Scenarios of Systemic Transitions in Energy and Economy
title_sort scenarios of systemic transitions in energy and economy
topic scenarios
energy foresight
global modelling
Global Change Data Base
trends extrapolation
land use change
url https://foresight-journal.hse.ru/article/view/19163
work_keys_str_mv AT gilbertahamer scenariosofsystemictransitionsinenergyandeconomy