9/26/2013

The Chained CPI: Shackling America’s Economic Recovery


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The Impact of Using the Chained CPI for Social Security Cost-of-Living Adjustments on Benefits, Output and Employment by Congressional District

 

This study calculates the congressional district-level impact of a proposal put forward by the Obama administration to use the chained Consumer Price Index as the basis for annual Social Security cost-of-living adjustments (COLA), beginning in calendar year 2015. Since the chained consumer price index has consistently shown a lower rate of inflation than the consumer price index for wage and clerical workers (CPI-W), the COLA would be lower if it were based on the chained CPI.  The Congressional Budget Office (CBO) has calculated that this difference would average 0.25 percentage points annually.

This study uses the CBO projections for cuts to national spending to make projections to cuts for each congressional district, based on the Social Security Administration’s data on Social Security spending by congressional district. It also makes projections for the impact on the reduction in output in each district applying the range of multipliers used by CBO for transfer programs such as Social Security. It also projects an employment impact for each district based on the projected reduction in output.

The nationwide numbers from CBO shows that a shift to the chained CPI would lead to reduction in benefits of $1.6 billion in 2015, $14.5 billion in 2020 and $23.0 billion in 2023, the last year in the CBO budget 10-year budget horizon.

If the economy is still operating below its potential, this loss in purchasing power will lead to a reduction in output. Using the mid-point of 1.45 for CBO’s estimates of the multiplier for government transfers like Social Security, these cuts would imply a loss of output of $2.3 billion in 2015, $21.0 billion in 2020, and $31.4 billion in 2023. (The study also shows projections using the high and low end of CBO’s range of multiplier estimates. Since most beneficiaries are likely to spend most of their payments quickly, and much of their consumption goes to services like health care, the actual multiplier is likely to be above the mid-point.)

Using CBO’s projected GDP and employment levels for these years it is possible to calculate the job loss that would be implied by this loss of output.  In other words, the calculations assume that the reduction in employment in each district is proportionate to the decline in its economic activity, the job loss for each district shows loss in a high, middle, and low scenario corresponding to the three multiplier scenarios discussed above. Nationwide, the cuts in benefits would lead to a loss of 19,400 jobs in 2015, 143,400 jobs in 2020, and 204,100 jobs in 2023.

This study applies these calculations to each congressional district. Many districts with large populations of retirees would be especially hard-hit by these cuts.

For example, in Florida’s 16th congressional district, which includes Sarasota and other cities along the Gulf Coast, the benefit cuts would be $6.1 million in 2015, $53.3 million in 2020, and $87.7 million in 2023. This would imply a loss of output in the district of $8.9 million in 2015, $80.2 million in 2020, and $127.2 million in 2023. The implied job loss would be 70 in 2015, 550 in 2020, and 780 in 2023.

In Pennsylvania’s 12th congressional district, a largely rural area in the southwest corner of the states, the benefit cuts would be $5.0 million in 2015, $44.9 million in 2020, and $71.3 million in 2023. This would imply a loss of output in the district of $7.2 million in 2015, $65.2 million in 2020, and $103.3 million in 2023. The implied job loss would be 60 in 2015, 440 in 2020, and 630 in 2023.

The study includes comparable projections for benefits cuts, loss in output, and job loss of each of the country’s congressional districts.

CPI Report Methodology

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(A National Committee to Preserve Social Security and Medicare Foundation Report prepared in consultation with Dean Baker, Co-Director, Center for Economic and Policy Research)

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