What is the total unfunded liability of the US government?
One of the most important political topics of 2009 was the health care reform plan that Congress is still working on. Because of the vociferous debate over the plan, US citizens have likely become much more aware of the amount of debt the US government owes. Much of this debt is held by countries such as China, and this fact has also attracted public attention.
But there’s another type of debt that isn’t talked about as often. I mean the so-called unfunded liabilities. Essentially, the US government has made promises to pay money today and in the future to its citizens. We’re talking about Social Security and Medicare.
The government raises funds for these costs from various taxes and then uses the money to fund the program. These programs are considered unfunded liabilities because, projected into the future, tax revenues will not be able to finance planned expenditures. The numbers are actually quite staggering. The unfunded liability for Social Security is projected to be $17.5 trillion.
Medicare’s unfunded liabilities are actually expected to be much higher. Medicare actually has parts A, B and D, part A funds hospital care. Part B funds medical visits and Part D funds prescription drugs. The unfunded liability of Part A is estimated at $36 trillion, Part B at $37 trillion, and Part D at $15 trillion.
The total unsecured liability is just over $100 trillion, or roughly $33,000 for every man, woman and child in the country. And since the private net worth of all Americans combined is estimated at just over $50 trillion dollars by the Federal Reserve, you can see the problem.
The reason many are concerned is that the only 2 ways to fix the situation are to either raise taxes significantly or cut the promised benefits. Because most analysts believe it is politically very difficult to reduce the promised benefits, most foresee significant tax increases in the future. There are some analysts who are much more optimistic about the issue, arguing that there are so many assumptions built into these analyzes that they can be vastly inaccurate.
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