Tesla's China Exports in Crosshairs of EU Anti-Subsidy Probe
- Bias Rating
-36% Somewhat Liberal
- Reliability
40% ReliableFair
- Policy Leaning
-36% Somewhat Liberal
- Politician Portrayal
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The A.I. bias rating includes policy and politician portrayal leanings based on the author’s tone found in the article using machine learning. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral.
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Contributing sentiments towards policy:
58% : After having collected initial evidence that formed the basis for launching the investigation, the EU is now looking to consult with relevant authorities -- including in China -- and companies to determine the extent to which subsidies may be undercutting EU producers, if at all.56% : These and other forms of support that China provides domestic manufacturers, including credits from state-owned banks, capital provisions from state investment funds, and provisions of land and electricity, are now coming under EU scrutiny.
55% : Tax breaks, cheap loans and other forms of assistance helped turn China into Tesla's most important market outside the US.
54% : Some European companies, such as BMW AG and Renault SA, that operate joint ventures with Chinese manufacturers will also be included in the probe along with all carmakers that produce in China and export to the EU, the people said.
53% : In recent probes of other sectors such as e-bikes and fiber-optic cables, the EU discovered subsidy margins ranging from 4% to 17%, people familiar with the findings said.
50% : The EU adopted standards earlier this year requiring manufacturers to slash 55% of CO2 emissions from new passenger cars by 2030, and to zero out emissions five years later.
43% : Both sides have ample reason to proceed carefully: While the EU risks exposing its manufacturers to potential retaliation, the bloc is the most attractive export destination for Chinese companies rife with excess production capacity.
*Our bias meter rating uses data science including sentiment analysis, machine learning and our proprietary algorithm for determining biases in news articles. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral. The rating is an independent analysis and is not affiliated nor sponsored by the news source or any other organization.