One of the main political issues of 2009 was the health system reform plan that Congress is still working on. Due to the vociferous debate over the plan, US citizens have probably become much more informed about the amount of debt the US government carries. Much of that debt is held by countries like China and that fact has also captured the attention of the public.
But, there is another type of debt that is not talked about as often. I refer to what is called unfunded liabilities. In essence, the US government has made promises to pay money today and in the future to its citizens. We are talking about Social Security and Medicare.
The government raises funds for these expenses 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 the projected expenses. The numbers are actually quite staggering. Social Security’s unfunded liability is projected to be $17.5 trillion.
In reality, the unfunded liability of Medicare is projected to be much larger. Medicare actually has Parts A, B, and D, Part A funds hospital care. Part B funds doctor 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 amount of the unfunded liability is just over $100 trillion, or about $33,000 for every man, woman, and child in the country. And since the Federal Reserve estimates the private net worth of all Americans combined to be just over $50 trillion dollars, you can see the problem.
The reason many are concerned is that the only two ways to rectify the situation are to dramatically increase taxes or cut promised benefits. Since most analysts feel that it is too politically difficult to cut promised benefits, most foresee significant tax increases in the future. There are some analysts who are much more optimistic about the problem, arguing that there are so many assumptions built into these analyzes that they could be significantly inaccurate.
