CNBC Article Rating

To help pay for Trump tax cuts, new taxes on worker benefits become GOP target

  • Bias Rating

    -40% Somewhat Liberal

  • Reliability

    45% ReliableFair

  • Policy Leaning

    -50% Medium Liberal

  • Politician Portrayal

    16% Positive

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.

Sentiments

Overall Sentiment

35% Positive

  •   Liberal
SentenceSentimentBias
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Bias Meter

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Bias Meter

Contributing sentiments towards policy:

63% : Taxing employees for fringe benefits such as employer-provided transportation, free food and on-site gyms is up for discussion.
57% : Currently, employer-provided transportation benefits, like transit passes and parking, up to $315 per month, are excluded from taxable income.
52% : Taxing employees for these perks could save around $157 billion over 10 years, according to Republican estimates. To be sure, these proposals are still in the early stages and there's a lot of jockeying by lawmakers to accommodate Trump's $4 trillion extension of the 2017 tax cuts as well as make good on campaign promises for tax breaks on tips, overtime pay and Social Security benefits -- in all, the tax cut promises made on the campaign trail by Trump could take the total to near $10 trillion.
49% : Here's what workers might expect if these provisions are enacted: Employees would likely have to pay the tax If enacted, workers would likely have to pay income tax on the fair market value of the fringe benefits they are getting from their employer, said Jeff Martin, tax principal at Grant Thornton's Washington National Tax Office.
46% : Competition for talent will also factor in, said Norman Richter, adjunct lecturer at Babson College, who teaches classes on tax policy.

*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.

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