One of the most important political issues in 2009 was the plan for health care reform, which is still working with Congress. Due to the loud debate about the plan, American citizens have probably become much more knowledgeable about the amount of debt owed by the US government. A large part of that debt is held by countries like China and even this fact has caught the attention of the public.
But there is another type of debt that is not often talked about. I am referring to what is called unfunded debt. Essentially, the US government has promised to pay money today and in the future to its citizens. We’re talking about Social Security and Medicare.
The government collects funds for these expenditures from various taxes and then uses the money to finance the program. These programs are considered as unfunded liabilities as the revenue from taxes will not be able to finance the estimated expenditure in the future. The numbers are actually quite astonishing. The Social Security’s unfunded debt is estimated at $ 17.5 trillion.
Medicare’s unfunded debt is actually expected to be much higher. Medicare actually has parts A, B and D, part A finances hospital care. Part B finances doctor visits and Part D finances prescription drugs. Part A unfunded liabilities are estimated at $ 36 trillion, Part B at $ 37 trillion and Part D at $ 15 trillion.
The total amount of unfunded liability amounts to just over 100 trillion dollars, or about 33,000 dollars for every man, woman and child in the country. And since the private net worth of all Americans together is estimated at just over $ 50 trillion by the Federal Reserve, you can see the problem.
The reason why many are worried is that the only two ways to rectify the situation is to either raise taxes significantly or cut back on the promised benefits. As most analysts believe that it is politically very difficult to cut promised benefits, most anticipate significant tax increases in the future. There are some analysts who are much more convinced of the problem and claim that there are so many assumptions built into these analyzes that they can be significantly wrong.