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<p>The growing incorporation of artificial intelligence into economic frameworks has prompted investigations on the macroeconomic and policy determinants influencing AI investment, especially in the United States. Despite its increasing significance, there is a paucity of empirical study examining the collective impact of trade openness, renewable energy use, economic growth, globalisation, and energy policy uncertainty on AI investment. This study utilises sophisticated nonlinear methodologies Wavelet Quantile Regression (WQR) and Wavelet Quantile Correlation (WQC) to analyse distributional asymmetries and time-frequency dynamics from 2013Q1 to 2024Q4. The findings indicate that renewable energy consumption, economic growth, trade openness, and globalisation positively influence AI investment, but energy policy uncertainty has a nonlinear effect, with moderate uncertainty fostering innovation but high volatility hindering long-term investment. These results highlight the significance of stable energy policy, continuous economic growth, and improved global integration for promoting AI development. The study emphasizes the need for integrated policies that connect energy transition, macroeconomic stability, and digital innovation to maintain the United States’ technical supremacy.</p>

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Do energy policy uncertainty, trade openness, and renewable energy drive artificial intelligence investment? Evidence from the United States

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月26日

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  • Xin Jin,
  • Babatunde Sunday Eweade,
  • Dilber Uzun Ozsahin,
  • Berna Uzun

摘要

The growing incorporation of artificial intelligence into economic frameworks has prompted investigations on the macroeconomic and policy determinants influencing AI investment, especially in the United States. Despite its increasing significance, there is a paucity of empirical study examining the collective impact of trade openness, renewable energy use, economic growth, globalisation, and energy policy uncertainty on AI investment. This study utilises sophisticated nonlinear methodologies Wavelet Quantile Regression (WQR) and Wavelet Quantile Correlation (WQC) to analyse distributional asymmetries and time-frequency dynamics from 2013Q1 to 2024Q4. The findings indicate that renewable energy consumption, economic growth, trade openness, and globalisation positively influence AI investment, but energy policy uncertainty has a nonlinear effect, with moderate uncertainty fostering innovation but high volatility hindering long-term investment. These results highlight the significance of stable energy policy, continuous economic growth, and improved global integration for promoting AI development. The study emphasizes the need for integrated policies that connect energy transition, macroeconomic stability, and digital innovation to maintain the United States’ technical supremacy.