Publication Date:
2024-03-28
Description:
Energy and its economic implications have been in the spotlight of policymakers, academics, traders, speculators and the industry for decades now. It has been an active research topic for more than 150 years. From the 19th century, the problem of creating, processing, storing and transporting energy was well defined. The issues of efficiently producing, pricing, distributing, and forecasting the demand, supply and prices of energy-related products and services are central to most modern economies irrespective of their level of development. These issues are apparent in times of relative tranquility in the respective markets but become central for all stakeholders in times of turbulence. This volume focuses on emerging methodologies of analysis, description, modelling, and forecasting in the topical area of Energy Economics. Includes emerging and innovative methodological approaches from the areas of machine learning, artificial intelligence, econometrics, and statistics aimed to model, describe or forecast the energy markets at all levels. Additionally, the volume also presents a bibliographical review, summarizes and compares results of different studies in the energy-sustainable economic growth and development nexus. The practical importance of the results to all energy market stakeholders in terms of regulating, pricing, and distributing energy is evident. Theoretical robustness, methodological innovation, and possible direct applicability of the conclusions were the basic requirements for research work to be included in this publication.
Keywords:
economic growth
;
innovation activity
;
globalization
;
international trade
;
uncertainty
;
spillovers
;
realized variance
;
crude oil
;
forecasting
;
bibliometric analysis
;
development economics
;
energy
;
renewable energy
;
energy-growth nexus
;
sustainable economy
;
new economics
;
critical review
;
natural gas
;
spot price
;
machine learning
;
energy commodities
;
financial crises
;
Brent
;
WTI
;
gasoline
;
clustering
;
t-SNE
;
COVID-19 pandemic
;
target model
;
Greek wholesale electricity market
;
day-ahead market
;
intraday market
;
balancing market
;
trading volumes
;
COVID-19
;
pandemic
;
energy market volatility
;
announcements
;
deaths
;
infections
;
load forecasting
;
load series
;
mode decomposition
;
extreme learning machine
;
kernel density estimation
;
geopolitical risk
;
renewable energy sources
;
energy production
;
ARDL
;
GDP
;
CO2 emissions
;
n/a
;
thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
;
thema EDItEUR::P Mathematics and Science::PH Physics
Language:
English
Format:
image/jpeg
