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Digital Infrastructure Construction and Energy Efficiency: A Quasi-Natural Experiment with Double Machine Learning

Jie Huang et al.

Emerging Markets Finance and Trade2026https://doi.org/10.1080/1540496x.2026.2617478article
AJG 2ABDC B
Weight
0.41

Abstract

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2 citations

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https://doi.org/https://doi.org/10.1080/1540496x.2026.2617478

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@article{jie2026,
  title        = {{Digital Infrastructure Construction and Energy Efficiency: A Quasi-Natural Experiment with Double Machine Learning}},
  author       = {Jie Huang et al.},
  journal      = {Emerging Markets Finance and Trade},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1080/1540496x.2026.2617478},
}

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Digital Infrastructure Construction and Energy Efficiency: A Quasi-Natural Experiment with Double Machine Learning

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Evidence weight

0.41

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.25 × 0.4 = 0.10
M · momentum0.55 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.