Can Computer Technology, Semiconductors, and Artificial Intelligence Shape a Sustainable Future? Evidence From Leading Semiconductor‐Producing Countries

Sustainable Development, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 24, 2025

ABSTRACT Technological innovation is redefining environmental quality by promoting green and efficient technologies. Keeping in view, this study brings a novel sophisticated idea to address these challenges sustainable development integrating key innovative determinants, including computer technology, semiconductors, artificial intelligence with development. Our employs panel Autoregressive Distributed Lag‐Pooled Mean Group (ARDL‐PMG), Lag‐Mean (ARDL‐MG), Lag‐Dynamic Fixed Effects (ARDL‐DFE), Lag‐Error Correction Model (ARDL‐ECM) techniques from 2000 2020 analyze relationship among the top 12 semiconductor‐producing countries. The results indicate that intelligence, usage of semiconductor technology positively correlate tech‐leading states. Apart this, findings reveal presence geopolitical risk decreases progression index. Besides, provides important suggestions concerned states for designing effective policies.

Language: Английский

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Comprehensive analysis of factors influencing EU-countries household energy consumption (2000–2022): Trends and vulnerability to COVID-19 and the Russia-Ukraine war

Energy Strategy Reviews, Journal Year: 2025, Volume and Issue: 59, P. 101728 - 101728

Published: April 29, 2025

Language: Английский

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Exploring Multifractal Asymmetric Detrended Cross-Correlation Behavior in Semiconductor Stocks

Fractal and Fractional, Journal Year: 2025, Volume and Issue: 9(5), P. 292 - 292

Published: May 1, 2025

This study investigates the multifractal behavior of four leading semiconductor stocks—Intel (INTC), Advanced Micro Devices (AMD), Nvidia (NVDA), and Broadcom (AVGO)—in relation to key financial assets, including Dow Jones Industrial Average (DJI), Euro–U.S. Dollar exchange rate (EUR), gold (XAU), crude oil (WTI), Bitcoin (BTC), using Multifractal Asymmetric Detrended Cross-Correlation Analysis (MF-ADCCA). The analysis is based on daily price return time series from January 2015 2025. Results reveal consistent evidence multifractality across all asset pairs, with generalized Hurst exponent exhibiting significant variability, indicative complex nonlinear stock dynamics. Among stocks, NVDA AVGO exhibit highest levels cross-correlation, particularly DJI, WTI, BTC, while AMD consistently shows lowest, suggesting comparatively more stable behavior. Notably, cross-correlation exponents BTC are highest, reaching approximately 0.54 for AMD. Conversely, pairs EUR display long-term negative correlations, around 0.46 stocks. spectrum highlights that broader pronounced characteristics, largely driven by higher fluctuation intensities. reveals stocks paired DJI show greater persistence during market downturns, whereas those XAU demonstrate stronger upward trends. sources surrogate confirms influence fat-tailed distributions temporal linear correlations in most exception which less Overall, findings underscore utility asymmetric capturing intricate dynamics approach provides valuable insights investors portfolio managers accounting multifaceted asset-dependent nature under varying conditions.

Language: Английский

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The dynamics of energy generation, consumption, and pricing on industrial growth in the SSA region; exploring the moderating effect of financial development and technological advancement

Technology in Society, Journal Year: 2024, Volume and Issue: 81, P. 102796 - 102796

Published: Dec. 13, 2024

Language: Английский

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