
China's Auto Export Wave Echoes Japan's in the '70s
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Bias Score Analysis
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:
67% : Coal was very conveniently located in the heartlands of Western civilization: central Scotland, northern England, south Wales, Belgium, the Ruhr and Pennsylvania.53% : There is a good argument that the Industrial Revolution itself happened in such places precisely because coal was abundant and therefore cheap, while labor was by global standards rather expensive.
53% : In response to the Chinese auto-export wave, we can therefore expect the US once again to rely on tariffs and other nontariff barriers to limit the threat to its own manufacturers.
53% : But Asia remains hooked on coal, and it is far from clear how quickly many industrial processes -- such as making steel and concrete -- can swap metallurgical coal for hydrogen.
50% : Despite the Reagan administration's rhetorical commitment to free trade and market forces, it could not ignore the domestic political pressure for some kind of action.
48% : Hence French President Emmanuel Macron's announcement last month that France's €7,000 purchase subsidy will be limited to cars with a low-carbon footprint in production -- i.e., not ones made in China, which manufactures its EVs with power generated by burning coal.
46% : However, rather than go down the routes available under the General Agreement on Tariffs and Trade, the administration found it easier to let Congress threaten Japan with quotas or domestic-content rules.
43% : That may be happening in some parts of the world -- Texas, for example -- where wind and solar are clearly displacing coal.
*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.