Energy Economics Letters

Asymmetric responses of industrial output to oil price volatility: A GARCH approach in East Asia-Pacific developing countries

2025-07-27T05:20:59-05:00

Crude oil represents a vital energy source essential for sustaining economic manufacturing activity and growth. Energy reliability is an absolute requirement for economic growth and development to occur. Widespread transmission across the economy becomes more complicated and nonlinear because of both business cycle patterns and policy changes. This study examines the asymmetric responses of industrial output to oil price volatility in East Asia-Pacific developing countries. The research utilizes monthly data from January 1997 to December 2024 on Brent oil prices and industrial production in these countries. It employs DCC and CDCC-GARCH models for symmetric analysis, while advanced asymmetric GARCH models (GJR-GARCH, FIEGARCH, HYGARCH) are used to detect asymmetric relationships. The results reveal significant differences in the effects of positive versus negative oil price shocks on industrial output growth. Symmetric GARCH models show weak correlations between oil price volatility and output, whereas asymmetric GARCH models uncover significant nonlinear and asymmetric relationships. The findings indicate that industrial output in East Asia-Pacific developing economies responds more strongly to oil price increases than decreases. The study concludes that the relationship between oil price volatility and industrial output growth is asymmetric, characterized by persistent and clustered volatility patterns. Furthermore, asymmetric GARCH models significantly outperform their symmetric counterparts in capturing these dynamics.

Energy consumption in Nigeria and socio-economic implications: Evidence from household data

2025-09-15T21:22:25-05:00

The purpose of this study is to examine energy consumption, its socioeconomic determinants, and implications with evidence from household data. The multinomial logistic regression model was used for analysis using data from the General Household Survey 2024 for Nigeria. The findings of this study reveal that per capita expenditure and education are major determinants of kerosene use. While sector shows a significant determinant of coal use for cooking. The determinants of household energy for lighting indicate that regular blackouts and electricity expenditure are major determinants of battery use, and sector influences the use of candles. It is suggested that rural sector electrification should be enhanced and that efforts should be geared towards subsidizing environmentally friendly energy sources for people who do not have the means and currently depend on firewood for survival.

The cautious march of central banks toward climate policy measures

2025-10-08T00:40:29-05:00

This study examines central banks' cautious yet evolving approach toward integrating climate-related policy measures within their mandates. An extensive literature search finds that unconventional monetary and collateral-based policies have the possibility of violating the market neutrality rules and may face political resistance. Regarding carbon tax, central banks can play a supportive rather than a pivotal role, and stress-testing, which can be an effective tool to disclose climate risk, is still nascent. Furthermore, a binomial logistic regression model has been employed using three key indicators: green bond issuance, carbon intensity of GDP, and the green macroprudential index, along with GDP and climate vulnerability as control variables across 55 countries. Results show that although central banks are the dominant climate risk regulators in most countries studied, their involvement does not significantly predict superior green financial outcomes. Notably, a negative association is observed between regulatory stringency and central bank enforcement, suggesting that non-central bank institutions may administer mature green regulations. The jackknife method indicates that central banks can be an efficient facilitator of green bond issuance when the data of the United States, the key opponent of green central banking, is excluded from the model. The study recommends a clearly defined mandate for central banks and advocates for coordinated monetary-fiscal strategies to ensure effective and balanced climate action.

Asymmetric impacts of energy, finance, and urbanization on CO₂ emissions: Evidence from Algeria and Egypt

2025-10-10T02:16:25-05:00

This study examines the dynamic relationship between carbon dioxide (CO₂) emissions and key determinants, including economic growth, renewable and non-renewable energy consumption, financial development, institutional quality, and urbanization, in Algeria and Egypt over 2000–2024. The purpose is to provide new insights into how these factors shape environmental sustainability in two North African economies. To achieve this, the analysis employs both Autoregressive Distributed Lag (ARDL) and Non-linear ARDL (NARDL) approaches, capturing short- and long-run effects and potential asymmetries in response to positive and negative shocks. The findings confirm the Environmental Kuznets Curve (EKC) hypothesis, indicating that economic growth initially increases emissions but eventually reduces them beyond a certain threshold. Moreover, significant asymmetric effects are observed, particularly regarding energy shocks and urbanization changes, highlighting the importance of directionality in influencing CO₂ emissions. These results provide practical implications for policymakers, emphasizing the need to promote renewable energy adoption, strengthen institutional frameworks, and manage urban expansion sustainably to achieve long-term environmental improvements. By integrating a comprehensive set of determinants and applying both symmetric and asymmetric econometric frameworks, this study offers a novel perspective on environmental dynamics in Algeria and Egypt.

Measuring and analysing multidimensional energy poverty with unequal weights: A logistic PCA and AI approach

2025-11-07T23:56:11-06:00

This study develops a robust methodological framework for measuring and analyzing multidimensional energy poverty using unit-level household survey data. The approach integrates logistic principal component analysis (Logistic PCA) to construct a composite index that assigns unequal weights to diverse energy deprivation indicators, thereby capturing the heterogeneity and complexity of energy poverty more accurately than equal-weight methods. The index is further disaggregated into moderate and severe categories, enabling a nuanced assessment of deprivation intensity. To complement the measurement stage, artificial intelligence techniques specifically multilayer perceptron (MLP) and artificial neural networks (ANN) are employed to model the socio-demographic and economic determinants of energy poverty. This dual-stage design allows for both explanatory and predictive insights: the statistical modeling validates the significance of key predictors such as household wealth, family size, and access to basic amenities, while the AI models enhance predictive accuracy for identifying high-risk households and regions. By combining unequal-weight composite measurement with AI-driven predictive modeling, the framework offers a scalable and transferable tool for researchers and policymakers. It facilitates targeted, data-driven interventions aimed at reducing energy poverty and promoting equitable energy access. The methodological innovations presented here are adaptable to diverse contexts, making them valuable for comparative studies and policy applications beyond the specific dataset used.

Energy transition and economic transformation in an emerging market: The case of Saudi Arabia's vision 2030

2025-11-07T23:59:55-06:00

This paper addresses the challenge facing resource-rich nations in the global energy transition by examining Saudi Arabia’s economic transformation under Vision 2030. To identify an optimal pathway, this study quantitatively assesses the macroeconomic trade-offs of different policy speeds, addressing a critical literature gap concerning the unquantified dynamic shocks of sequencing reforms. A dynamic stochastic general equilibrium (DSGE) model tailored to the Saudi economy is employed, featuring sectoral disaggregation and dynamic adjustment costs to capture realistic transition frictions. Using this framework, four distinct scenarios Reference, Accelerated Transition, Delayed Transition, and Hydrogen Leader are simulated through 2050 to analyze the economy-wide effects of different policy choices. The simulations reveal severe risks from improper timing; an accelerated transition triggers a sharp rise in unemployment to 12.3%, while delaying reform leads to a long-term fiscal crisis. The central finding is that a strategic focus on becoming a global hydrogen leader offers the most balanced and resilient pathway, yielding solid GDP growth (3.4%), manageable unemployment (9.2%), and long-term fiscal sustainability. The paper identifies this hydrogen-focused industrial strategy as a viable mechanism for a resource-rich nation to convert its geological inheritance into a sustainable economic future, circumventing the resource curse. It provides critical, data-driven insights for policymakers, demonstrating that the optimal strategy involves transforming not abandoning energy leadership through carefully sequenced reforms, pre-emptive labor market policies, and strategic fiscal investment.