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Raising SALT Cap to $20,000 Would Mostly Benefit High-Income Households

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  • Raising SALT cap to $20,000 would increase federal debt by $225 billion from 2025-2034
  • Nearly all the benefit would go to households making about $200,000 or more
  • The change would cut household taxes overall by an average of about $100
  • Almost none of the benefit would go to middle- or low-income households
360 summary
  • The SALT deduction cap was originally implemented as a political maneuver by former President Trump, primarily targeting high-tax blue states like New York and California.
  • Supporters of the cap argue that it helps increase federal revenue and only targets higher-income taxpayers, while critics say it's unfair since it's more harmful in states with higher costs of living and taxes.
  • Removing the cap or increasing it would significantly benefit residents of states like New York and California, enabling them to deduct a larger portion of the taxes they pay throughout the year.
NewsweekNewsweek
  • Households making $200,000 or less would see no change in their after-tax incomes if Congress increases the cap to $20,000.
  • Those making between about $430,000 and $1 million (the highest-income 95-99 percent of households) would get a tax cut averaging nearly $1,400, or about 0.3 percent of their after-tax income.
  • The average tax cut for married couples would be about $270. But middle-income couples would get a tax cut averaging about $10. Those in the 95th-99th percentile would get an average tax cut of about $1,500.
ForbesForbes
ExploreThe above information is compiled by Newsweek、Forbes and does not represent any position of Arbor. It does not constitute any investment advice made by Arbor. Before making any investment decisions, investors should consider the risk factors related to the investment products based on their own circumstances and seek advice from professional investment advisors if necessary. We strive to ensure but cannot guarantee the truthfulness, accuracy, and originality of the above content, and we make no promises or guarantees in this regard. As machine learning has a probabilistic nature, it may lead to incorrect reflection of facts in certain situations. You should appropriately evaluate the accuracy of any information summary based on your usage, including through manual evaluation of the information summary. We are not responsible for any losses or liabilities incurred by you due to your use, viewing, and access of the platform or failure to do so.
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