The Economic Impact of Social Security
If Social Security payments were reduced by only five percent, the nation’s economic output would decrease by $63 billion, 419,000 jobs would be lost and tax revenues would decrease by $7.8 billion.
Those figures reflect Social Security payments made in 2009 and come from a study we conducted to measure the role this program plays in the U.S. economy. The study was done at the Southern Rural Development Center at Mississippi State University. (To download data, maps and the technical report supporting this article, go here.)
Social Security is a massive program. A little over 51 million people received some kind of Social Security payment in 2009 — a disability benefit, a survivor benefit or a retirement check. This amounted to 16.7 percent of the total U.S. population. Even slight changes in this program can have tremendous effects in the nation.
Social Security plays a much larger role in rural America. In rural counties, 23.6 percent of the population receives a monthly Social Security check. In counties with small cities (under 50,000 population), 21.2 percent of the population in 2009 received Social Security benefits
Payments in 2009 were $675 billion — or 5.5 percent of total personal income in the U.S. Social Security payments in rural counties constituted 9.3% of total personal income in 2009.
In counties with small cities, the program accounted for 8.2 percent of total personal income. (Total personal income includes, wages, salaries, employer-provided health insurance, dividends, interest, Social Security benefits and other types of income.)
There are two things about this program we’d like to emphasize. First, the role Social Security plays in the local economy varies across the country — and its local impact is changing. Some states and counties are growing more dependent on Social Security while the proportion of Social Security payments is declining in other places.
Second, it is clear that Social Security supports a large proportion of the nation’s economic output and a great number of jobs.
To measure how dependent states and counties are on Social Security, we compiled an index. We included three factors: the percentage of total county population receiving Social Security; the percent of a county’s total personal income derived from Social Security; and the average per capita payment in a county (that is the total amount of Social Security received in a county divided by the total number of residents).
Using the Social Security dependency index, we compared states and counties in 2000 and 2009. Some states and counties grew more dependent on Social Security over this period. In other places, the impact of Social Security payments diminished during this time period. You can see these shifts in the map above.
The map above shows only rural (“noncore” according to federal terminology) and “micropolitan” counties (those with cities under 50,000 population). The white areas are urban counties.
Purple areas grew more dependent on Social Security Green counties became less dependent on Social Security from 2000 to 2009.
The ten counties nationally most dependent on Social Security payments are either rural or small city counties. Sumter County, Florida, a retirement county in the central part of the state, is the most dependent in the nation, followed by Alcona County, Michigan; Lewis County, Idaho; Roscommon County, Michigan; Hickory County, Missouri; Montmorency County, Michigan; Polk County, Texas; Iosco County, Michigan; Citrus County, Florida; and Sharp County, Arkansas.
We did the same dependency calculations with states. The results are seen in the map below. (Click on either map to see a larger version.) Dark blue states became more dependent on Social Security between 2000 and 2009 while light blue states became less dependent. White states remained the same. Southern Rural Development Center
The numbers on each state show their relative rank. West Virginia is the most dependent on Social Security, so it is marked with a “1.” Alaska is the least dependent.
Economic Impact of Social Security
We used the economic modeling system known as IMPLAN to measure the economic impact of Social Security at the national level and in Sumter County, the Florida county that was the most dependent on Social Security in 2009.
We found that for every dollar of Social Security payment, an additional 80 cents of economic output was created. At the national level, Social Security’s $675 billion in payments in 2009 supported a total output in the nation of $1.2 trillion.
These payments supported approximately 8.4 million jobs (full and part-time). And this activity generated $157.2 billion in tax revenues — $71.9 billion in state and local taxes and $85.2 billion in federal taxes.
The Social Security multiplier in Sumter County, Florida, was 1.5 — for every dollar of Social Security payments, an additional 50 cents was generated.
In Sumter, Social Security payments of $622 million generated an an additional $316 million in economic output, 3,077 jobs and $41.1 million in state, local and federal taxes.
Now, what if Social Security payments were cut?
Our analysis finds that a 5 percent cut would reduce the nation's output by $63 billion. It would cut employment by 419,000 and would reduce tax revenues by $7.8 billion. A 15 percent cut would reduce national output by $190 billion and cut employment by 1.2 million jobs.
We realize this study is exploratory. We don’t know from this study why states are increasing or decreasing in their dependency on Social Security. It is interesting that states and counties that ranked high in the dependency index were not necessarily those that had populations that are becoming proportionally older.
This is a beginning. And it shows that Social Security has an enormous impact on local economies.
Roberto Gallardo is an assistant extension professor and economic development specialist at the Southern Rural Development Center at Mississippi State University. Al Myles is a professor of economics and interim associate director of the Southern Rural Development Center. This study was supported by a grant from the National Academy of Social Insurance.